Regulation of microRNAs by stress and gonadal hormones in male and female mouse hippocampus
by
Carolyn Elaine Creighton
A Thesis presented to The University of Guelph
In partial fulfillment of the requirements for the degree of Doctor of Philosophy in Biomedical Sciences and Neuroscience
Guelph, Ontario, Canada
© Carolyn Elaine Creighton, January, 2017
ABSTRACT
REGULATION OF MICRORNAS BY STRESS AND GONADAL HORMONES IN MALE AND FEMALE MOUSE HIPPOCAMPUS
Carolyn Elaine Creighton Advisor: University of Guelph, 2017 Neil J. MacLusky
Hormonal changes have profound effects on the structure and function of the central nervous system. One region that is especially affected by hormonal changes is the hippocampus, a brain region known for its roles in learning and memory. Within the hippocampus, different hormones –gonadal and stress –interact in a sex-dependent fashion to control hippocampal structure and function. While research has explored the role of different receptors and cell signaling pathways in this interaction, the underlying mechanisms are incompletely understood. This thesis begins to explore the possible role of microRNAs (miRNAs) as mediators of gonadal/stress hormone interactions. In non-neural tissues, miRNAs are regulated by hormones and in turn control hormone signaling. In neural tissues, miRNAs are known to regulate important structural processes such as dendritic arborisation. Since these structural changes are also regulated by hormones, miRNAs could be important regulators of the hormone- mediated gene expression that underlie these processes.
The first objective of this thesis was to examine the effects of 17β-estradiol on hippocampal miRNA expression in the female mice using small RNA sequencing. Mice were given a single injection of 17β-estradiol, and the rapid effects on miRNA expression examined. Interestingly, this study revealed that even the mild stress
ii associated with handling and injection altered miRNA expression, which could interfere with the effects of estradiol. The initial study was then expanded into the second objective to specifically determine the effect of the stress of handling on miRNA expression, and to examine if changes in expression were similar between males and females. The final objective looked at the direct, rapid effects of modulators of the stress-response system on miRNA expression using an in vitro model system.
Specifically the effects of corticotropin-releasing hormone (CRH) and dexamethasone on miR-34c-5p expression in SH-SY5Y neuroblastoma cells were assessed. Together the results presented in this thesis suggest that gonadal and stress hormones may both affect the expression of a subset of miRNAs in the hippocampus.
iii ACKNOWLEDGEMENTS
I would like to thank my friends and family. Thank you to my husband, Connor, who has been with my throughout my time in graduate school. You have kept me sane and always believed that I could do it all, even when I lost faith in myself. Thank you to my parents, Janis and David, who provided love and support along the way. I would also like to thank the friends I have made along the way –Anja, Carmon, Jacky, Kayla, and Sarah –for being people I could bounce ideas off of and share this graduate school experience with.
I would like to thank my advisory committee, Dr. Neil MacLusky, Dr. Bettina Kalisch, Dr. Jonathan LaMarre and Dr. Elena Choleris, for their support, advice and encouragement throughout. Neil, thank you for the opportunity to work in your lab. Through this experience I have learned so much about myself that would not have been possible otherwise. Bettina, thank you for first inspiring my interest in research during my undergraduate research project. Your kindness and support have been greatly appreciated, and you have always been someone I could talk to when needed. Jon and Elena, your advice and expertise helped this project to take shape.
Thank you to past and present members of the MacLusky group that have helped and supported me along the way, especially to Ari Mendell. I would also like to thank members of the Kalisch, Choleris and LaMarre labs. Special thanks to Cameron Wasson and Colin Howes for teaching me the ovariectomy and castration surgeries, Dr. Leanne Stalker and Allison Tscherner for their help with qPCR, and Dr. Graham Gilchrist for his advice with bioinformatics analysis.
I would like to thank Dr. Monica Antenos and Dr. Laura Favetta for all their help with technical issues that came up along the way.
Finally, I would like to thank the other graduate students, staff and faculty of the department who have help me along the way.
iv DECLARATION OF WORK PERFORMED
I declare that with the exception of the items indicated below, all work reported in the body of this thesis was performed by me:
Dr. Jenny Lymer performed the ovariectomy surgeries in chapter 2.
Dr. Sergio Pereira at The Centre for Applied Genomics (TCAG) at the Hospital for Sick
Children, Toronto, Ontario performed the small RNA library preparations and next- generation sequencing in chapters 2 and 3.
Dr. Daniele Meircio and Thomas Nalpathamkalam at TCAG performed the bioinformatics analyses of sequencing reads in chapters 2 and 3.
v TABLE OF CONTENTS
ABSTRACT ...... ii
ACKNOWLEDGEMENTS …………………………………………………………...... iv
DECLARATION OF WORK PERFORMED ……………………………………………….. v
TABLE OF CONTENTS …………………………………………………………………….. vi
LIST OF TABLES ……………………………………………………………………………. ix
LIST OF FIGURES ………………………………………………………………………….… x
LIST OF ABBREVIATIONS ………………………………………………………...... xiI
CHAPTER 1: REVIEW OF THE LITERATURE …………………………………………… 1 General Introduction ………………...... 1 Hormonal Effects in the Central Nervous System …………………………………. 2 Gonadal Hormone Regulation and Mechanism of Action ………………………… 3 Estrogen synthesis and metabolism ………………………………………… 3 Estrogens and the HPG axis ………………………………………………… 5 Estrogen receptors ……………………………………………………………. 6 Mechanisms of estrogen action ……………………………………………... 9 Stress Hormone Regulation and Mechanisms of Action ………………………… 15 Stress and the HPA axis ……………………………………………………. 15 Cellular mechanisms of stress ……………………………………………... 17 Structural and Functions Responses to Hormones ……………………………… 19 Estradiol actions within the central nervous system ……………………... 19 Responses to stress within the central nervous system ………………… 23 Neurobehavioural disorders connected to estrogens and stress ………. 30 Interactions between gonadal and stress hormones …………………………….. 30 Gonadal regulation of the HPA axis ……………………………………….. 30 Stress regulation of the HPG axis …………………………………………. 34 The Hippocampus …………………………………………………………………… 35 Hippocampal structure, connectivity and function ……………………….. 35 Hippocampal plasticity ………………………………………………………. 38 MicroRNAs …………………………………………………………………………… 40 MicroRNA biogenesis and degradation …………………………………… 40 MicroRNA targeting and functions …………………………………………. 43 MicroRNA involvement in the central nervous system …………………... 45 Hormonal Regulation of MicroRNAs ………………………………………………. 48 Estrogen-microRNA connections ………………………………………….. 48 Stress-microRNA connections ……………………………………………... 53 Hypothesis and Objectives ………………………………………………….……… 55
vi CHAPTER 2 ………………………………………………………………………………….. 57 Introduction …………………………………………………………………………… 57 Materials and Methods ……………………………………………………………… 59 Animals ……………………………………………………………………….. 59 Treatments …………………………………………………………………… 60 RNA Isolation and Quality …………………………………………………... 61 Small RNA Library Preparation & Next Generation Sequencing ……….. 61 Bioinformatic Analysis ………………………………………………………. 61 CDNA synthesis and qPCR ………………………………………………… 62 Statistical Analysis …………………………………………………………… 64 Predicted Target Cluster Analysis …………………………………………. 64 Results ………………………………………………………………………………... 64 MicroRNA Detection ………………………………………………………… 64 Quantitative PCR Validation of MicroRNAs ………………………………. 67 Quantitative PCR of MicroRNA Biogenesis Components ………………. 69 Predicted microRNA Target Cluster Analysis ……………………………. 71 Detection of Predicted Targets …………………………………………….. 72 Discussion ……………………………………………………………………………. 72
CHAPTER 3 ………………………………………………………………………………….. 80 Introduction …………………………………………………………………………… 80 Materials and Methods ……………………………………………………………… 81 Animals ……………………………………………………………………….. 81 Treatments …………………………………………………………………… 82 RNA Isolation and Quality …………………………………………………... 83 Small Library Preparation & NGS ………………………………………….. 84 Bioinformatic Analysis ………………………………………………………. 84 CDNA Synthesis and qPCR ………………………………………………... 85 Statistical Analysis …………………………………………………………… 86 Results ………………………………………………………………………………... 87 MicroRNA detection …………………………………………………………. 87 Differential Expression ………………………………………………………. 89 Quantitative PCR validation of microRNAs ……………………………….. 92 Quantitative PCR analysis of miR-216b and miR-217 …………………... 96 Quantitative PCR of corticosterone receptors ……………………………. 98 Discussion ……………………………………………………………………………. 99
CHAPTER 4 ………………………………………………………………………………… 106 Introduction …………………………………………………………………………. 106 Materials and Methods …………………………………………………………….. 107 Cell Culture …………………………………………………………………. 107 Treatment & Sample Collection …………………………………………... 108 RNA Isolation & Quality ……………………………………………………. 109 cDNA Synthesis & qPCR ………………………………………………….. 109 Statistical Analysis …………………………………………………………. 110
vii Results ………………………………………………………………………………. 110 Effects of CRH on miR-34c-5p expression ……………………………… 110 Effects of dexamethasone on miR-34c-5p expression ………………… 111 Discussion …………………………………………………………………………... 112
CHAPTER 5: SUMMARY AND FUTURE DIRECTIONS ……………………………… 116 Introduction …………………………………………………………………………. 116 Summary of Work Performed …………………………………………………….. 116 Future Directions …………………………………………………………………… 118
BIBLIOGRAPHY …………………………………………………………………………… 122
APPENDIX ………………………………………………………………………………….. 164 Supplemental Table 1 ……………………………………………………………… 165 Supplemental Table 2 ……………………………………………………………… 173 Supplemental Table 3 ……………………………………………………………… 179 Supplemental Table 4 ……………………………………………………………… 185 Supplemental Table 5 ……………………………………………………………… 191 Supplemental Table 6 ……………………………………………………………… 199 Supplemental Table 7 ……………………………………………………………… 207
viii LIST OF TABLES
CHAPTER 2
Table 2.1. Table of qPCR primer sequences and sources
CHAPTER 3
Table 3.1. Table of qPCR primer sequences and sources
ix LIST OF FIGURES
CHAPTER 1
Figure 1.1. Biogenesis of major steroid hormones
Figure 1.2. The rodent estrous cycle
Figure 1.3. The HPA axis
Figure 1.4. The hippocampus and trisynaptic circuit
Figure 1.5. The canonical microRNA biogenesis pathway
CHAPTER 2
Figure 2.1. Distribution of sequencing reads
Figure 2.2. MicroRNA differential expression analysis
Figure 2.3. Quantitative PCR for mature microRNAs
Figure 2.4. Quantitative PCR for components of the microRNA biogenesis pathway
Figure 2.5. Functional clusters of predicted microRNA targets
Figure 2.6. Quantitative PCR for potential microRNA targets
CHATPER 3
Figure 3.1. Read distribution
Figure 3.2. MicroRNA differential expression analysis in females
Figure 3.3. MicroRNA differential expression analysis in males
Figure 3.4. Quantitative PCR validation of mature microRNAs
Figure 3.5. Quantitative PCR validation of mature microRNAs
Figure 3.6. Quantitative PCR validation of mature microRNAs
x Figure 3.7. Quantitative PCR for individual animals for miR-448 and miR-1298
Figure 3.8. Quantitative PCR analysis of miR-216b and miR-217
Figure 3.9. Quantitative PCR validation of the corticosterone receptors
CHAPTER 4
Figure 4.1. Quantitative PCR for miR-34c-5p expression
Figure 4.2. Quantitative PCR for miR-34c-5p expression
xi LIST OF ABBREVIATIONS
3’-UTR 3’ untranslated region
ACTH Adrenocorticotropic hormone
AD Alzheimer disease
AMPA α-amino-3-hydroxy-5-methyl-4-isoxazole
AMPAR α-amino-3-hydroxy-5-methyl-4-isoxazole receptor
ANOVA Analysis of variance
AR Androgen receptor
ARE Androgen response element
ASD Autism spectrum disorder
BDNF Brain-derived neurotrophic factor
BnST Bed nucleus of the stria terminalis
CA1 Cornu ammonis 1
CA2 Cornu ammonis 2
CA3 Cornu ammonis 3
CA4 Cornu ammonis 4 cAMP Cyclic adenosine monophosphate
CDS Coding DNA sequence
CNS Central nervous system
CRE cAMP response element
CREB cAMP response element-binding protein
CRF Corticotropin-releasing factor
xii CRH Corticotropin-releasing hormone
DG Dentate gyrus
Dgcr8 DiGeorge critical region 8
E1 Estrone
E2 17β-Estradiol
E3 Estriol
ER Estrogen receptor
ERα Estrogen receptor alpha
ERβ Estrogen receptor beta
ERE Estrogen response element
ERK Extracellular signal-regulated kinase
FSH Follicle stimulating hormone
GABA Gamma-aminobutyric acid
GC Glucocorticoid
GDX Gonadectomized
GnRH Gonadotropin releasing hormone
GPCR G-protein coupled receptor
GPER1 G-protein estrogen receptor
GPR30 G-protein coupled receptor 30
Gq-mER Gq-coupled membrane estrogen receptor
GR Glucocorticoid receptor
HPA Hypothalamo-pituitary-adrenal
HPG Hypothalamo-pituitary-gonadal
xiii HPRT Hypoxanthine-guanine phosphoribosyl transferase
HRE Hormone response element
IGF-1R Insulin-like growth factor 1 receptor
LC Locus coeruleus
LTD Long-term depression
LTP Long-term potentiation
MAPK Mitogen-activated protein kinase
MDD Major depressive disorder miRNA MicroRNA miRISC MicroRNA-induced silencing complex mGluR Metabotropic glutamate receptor
MR Mineralocorticoid receptor
NGS Next generation sequencing
NMDA N-methyl-D-aspartate
NMDAR N-methyl-D-aspartate receptor
NSE Neuron-specific enolase
OP Object placement
OR Object recognition
OVX Ovariectomy pCREB Phosphorylated CREB
PFC Prefrontal cortex
PI3K Phosphatidylinositol 3 kinase
PKA Protein kinase A
xiv PKC Protein kinase C
PR Progesterone receptor
Pre-miRNA Precursor microRNA
Pri-miRNA Primary microRNA
PVN Periventricular nucleus
RAM Radial arm maze
SEM Standard error of the mean
SERT Serotonin transporter
SGZ Subgranular zone
SSRI Selective serotonin reuptake inhibitor
StAR Steroidogenic acute regulatory protein
SVZ Subventricular zone
TrkB Tropomyosin receptor kinase B/Tyrosine receptor kinase B
WT Wild type
xv CHAPTER 1: REVIEW OF THE LITERATURE
General Introduction
Hormonal changes, like those seen in the female reproductive cycle and during responses to stress, have profound effects on the structure and function of the central nervous system. Hormonal changes can regulate mood, alter learning and memory, and can play an important role in the development of neurological disorders ranging from anxiety and depression to Alzheimer disease (reviewed in Bangasser & Valentino,
2014; Frick, 2009). Their effects are especially dramatic within the hippocampus, a brain region well known for its roles in learning and memory processes (Bliss & Collingridge,
1993). Importantly, sex steroids and stress hormones interact with one another in a sex- dependent fashion to control hippocampal structure and function (reviewed in Handa &
Weiser, 2014). While current knowledge can explain some of the interactions, the underlying mechanisms are incompletely understood. There has been extensive research on the receptors and some of the possible cellular signaling pathways involved, however, how these signals are translated into the overall behavioural and neuroendocrine responses that are observed currently remains uncertain. Recently, epigenetic modulators have been linked with mood, learning and memory processes
(reviewed in Colciago et al., 2015), and one possible player involved in gonadal/stress hormone interactions is microRNAs (miRNAs). MiRNAs are involved in a number of the effects of gonadal and stress hormones in non-neural target tissues, where they are regulated by hormones and in turn control aspects of hormone signalling (estrogen and miRNA reviewed in Klinge, 2015). This literature review discusses the effects and
1 interactions between sex steroids and stress hormones, with a focus on how these hormones regulate hippocampal structure and function in the hippocampus in both males and females. The review concludes with a focus on microRNAs, their role within the central nervous system, and the current understanding of their interaction with both gonadal and stress hormones.
Hormonal Effects in the Central Nervous System
The basic cellular mechanisms by which steroids affect the function of the central nervous system have been extensively explored since the 1960s, when steroid receptors were first identified by their ability to bind steroid hormones with high affinity
(Beato et al, 1969; Herman et al., 1968; Noteboom & Gorski, 1965). Certain fundamental principles have been established as common to the actions of most, if not all, steroids on the brain. First, steroid action is extensively modulated by local metabolism of the hormones within the brain itself (Prange-Kiel et al., 2006). Moreover, the actions of circulating steroid interact with effects mediated via locally formed
“neurosteroids”, synthesized by neurons and glia either de novo or via modification of circulating hormones (Baulieu et al., 2001). Second, the cellular effects of steroids appear to be mediated via intracellular receptors, many of which are members of the nuclear receptor superfamily (Carson-Jurica et al., 1990), but also include membrane associated G-protein, such as the membrane associated estrogen receptor, GPR-30 or
GPER (Pedram et al., 2006). Finally, and of particular relevance to the present study, while brief exposure to steroids in adulthood induces transient “activational” changes in neuroendocrine function and behaviour, long-term or developmental exposure to the
2 same hormones may induce “organizational” responses that permanently alter the sensitivity of the brain to subsequent hormone exposure. The best characterized of these organizational effects is the phenomenon of sexual differentiation, in which early exposure of the brain to testosterone in the male permanently shifts the development of the brain towards the masculine phenotype, so that subsequent exposure to gonadal hormones induces a completely different sexually differentiated set of neuroendocrine and behavioural responses (MacLusky & Naftolin, 1981; Baulieu et al., 2001). Perhaps the major challenge that remains in this field is understanding how short-term cellular effects of steroids are translated into longer term, or permanent, shifts in the responsiveness of the brain to subsequent steroid exposure.
Gonadal Hormone Regulation and Mechanism of Action
Estrogen synthesis and metabolism
The estrogens are a class of steroid hormones consisting of 18 carbon cholesterol derivatives, first characterized for their actions in the reproductive tract of females. The estrogen family consists of three members: estrone (E1), estradiol (E2), and estriol (E3).
Estradiol, specifically the 17β isomer, is the most prominent and potent form of estrogen in women of reproductive age, and the focus of most research looking into the effects of estrogens (Kuiper et al., 1997). The other estrogens display different expression profiles with estrone being highest following menopause and estriol levels peaking during pregnancy (De Hertogh et al, 1975). Estradiol is synthesized via steroidogenesis from cholesterol precursors (Figure 1.1). The final step in the process involves the conversion of testosterone to estradiol via aromatization. This involves the removal of
3 the C19 methyl group allowing for aromatization of the A ring. The process is catalyzed by the cytochrome P450, CYP19A1, also known as aromatase.
Cholesterol
P450scc
3β-HSD 21-OHase 11Β-OHase Pregnenalone Progesterone Deoxycorticosterone Corticosterone
17α-OHase 17α-OHase 17α-OHase 17α-OHase
3β-HSD 21-OHase 11β-OHase 17α-hydroxypregnenalone 17α-hydroxyprogestone 11-deoxycortisol Cortisol
17,20 Lyase 17, 20 Lyase
3β-HSD Aromatase Dehydroepiandrosterone (DHEA) Androstenedione Estrone
17β-HSD 17β-HSD 17β-HSD Estriol
3β-HSD Aromatase Androstenediol Testosterone Estradiol ENZYME 5α-reductase PROGESTOGEN/GLUCOCORTICOID ANDROGEN Dihydrotestosterone (DHT) ESTROGEN
Figure 1.1. Biosynthesis of major steroid hormones. All steroid hormones are synthesized from a cholesterol precursor. To produce estradiol, cholesterol is cleaved by P450scc (cholesterol side-chain cleavage enzyme) to yield pregnenolone. Pregnenolone can be converted to 17α-hydroxypregnenolone by 17α-hydroxylase (17α- OHase) or to progesterone by 3β-hydroxysteroid dehydrogenase (3β-HSD). Progesterone is further converted to 17α-hydroxyprogesterone by 17α-OHase. Both 17α precursors are converted by 17,20 lyase to dehydroepiandrosterone (DHEA) and androstenedione, respectively. Following conversions by 17β-hydroxysteroid dehydrogenase (17β-HSD) and/or 3β-HSD, both DHEA and androstenedione are converted to testosterone. Testosterone is further converted to estradiol by aromatase. Based off figure by Mendell (2014 –Thesis).
Estradiol is synthesized primarily in the ovaries; however, estradiol can also be synthesized in a number of brain regions including the hippocampus (Furukawa et al.,
1998). All of the major enzymes in the estrogen synthesis pathway have been detected
4 in the hippocampus including cholesterol side-chain cleavage enzyme (P450scc)
(Mellon & Deschepper, 1993; Hojo et al., 2004), 17α-hydroxylase/17,20-lyase (P450-
17α) (Hojo et al., 2004), 17β-hydroxysteroid dehydrogenase (17β-HSD) (Beyenburg et al., 2000; Hojo et al., 2004), 3β-hydroxysteroid dehydrogenase (3β-HSD) (Furukawa et al., 1998; Ibanez et al., 2003), and aromatase (Hojo et al., 2004; 2009). Estrogen synthesis within the hippocampus appears to be under the control of gonadotropin releasing hormone (GnRH) (Prange-Kiel et al., 2008) and fluctuates throughout the estrous cycle (Kato et al., 2013). Synthesis can also be driven by activity as N-methyl-
D-aspartate (NMDA) receptor activation increases estradiol in slice culture (Hojo et al.,
2004). The roles of gonadal and hippocampal-derived estradiol will be discussed later
(Mechanisms of estrogen action).
Estrogens and the HPG Axis
Estradiol is an important component of the hypothalamic-pituitary-gonadal (HPG) axis.
This axis, in females, is responsible for controlling the rodent 4-day estrous cycle as well as the menstrual cycle in women. GnRH, a 10 amino acid peptide hormone, is produced and released in a pulsatile manner from the hypothalamus (Miller &
Takahashi 2014). Depending on the rate of pulsatile secretion, GnRH stimulates greater release of follicle stimulating hormone (FSH) or luteinizing hormone (LH) from the anterior pituitary. Slow pulses lead to greater FSH release, which then acts on the ovary to stimulate follicle production. As an ovarian follicle matures, it produces more estradiol.
Generally, the system is under negative feedback control, as estradiol can inhibit further production of GnRH. However, as estradiol levels rise they instead initiate positive
5 feedback on the hypothalamus leading to the LH surge responsible for inducing ovulation. Consequently, the highest levels of estradiol are seen the morning of proestrus after which they rapidly decrease to their lowest levels in estrus (Figure 1.2).
While estradiol is not considered the major male sex steroid, it is still produced at levels comparable to females (Kato et al., 2013) and has important roles in male reproductive function such as sexual arousal and the production of sperm (reviewed in Schulster et al., 2016).
Figure 1.2. The rodent estrous cycle. Estradiol levels (blue dotted line) slowly climb during metestrus and diestrus, reaching a peak the morning of proestrus. Estradiol levels then rapidly decline and remain low throughout estrus. (Adapted from Miller & Takahashi, 2013)
The estrogen receptors
ERα and ERβ
Multiple receptors have been discovered for the estrogens. The first class of estrogen receptors characterized was the classical estrogen receptors. These receptors are members of the nuclear receptor superfamily, and are characterized by a zinc-finger containing DNA binding domain and a ligand-binding domain. The first to be discovered was estrogen receptor alpha (ERα) by Elwood Jensen in 1958 (Jensen, 2012). The second classical estrogen receptor, ERβ was first characterized in rat prostate tissue in
6 1996 (Kuiper et al., 1996). ERβ is structurally similar to ERα with ~95% sequence homology in the DNA-binding domain and 55 to 60% sequence homology in the ligand- binding domain (Kuiper et al., 1996; Hewitt & Korach, 2002).
The expression of ERα and ERβ in the brain has been extensively examined in rodent models. The earliest studies involved mRNA in situ hybridization. Estrogen receptors are found throughout the brain and brain stem with highest expression found in regions controlling sexual behaviour and gonadotropin release (Simerly et al., 1990). These regions include the bed nucleus of the stria terminalis, multiple amygdaloid nuclei, and a number of hypothalamic areas including the preoptic area, paraventricular nucleus, supraoptic nucleus, and arcuate nucleus (Simerly et al., 1990; Shughrue et al., 1997).
Interestingly, some of these regions show a specificity for which receptor is expressed with only ERβ present in the paraventricular and supraoptic nuclei, and ERα expressed in the arcuate nucleus (Shughrue et al., 1997). Within the hippocampus, mRNA levels for both receptors were found to be lower than the previously mentioned regions, and
ERβ was more abundantly expressed than ERα (Shughrue et al., 1997). Studies of ERα and ERβ protein have found expression levels to correlate well with the previous mRNA studies (Shughrue & Merchenthaler, 2001; Mitra et al., 2003). Within the hippocampus,
ERα expression is more restricted with the highest levels seen in the CA1 and CA3 regions, whereas ERβ expression is more diffuse throughout the hippocampus with evidence of extranuclear localization in some regions (Mitra et al., 2003). More recently, the ultrastructural localization of both ERα and ERβ has been examined in both rat and mouse hippocampus. While both ERα and ERβ are classically thought of as nuclear
7 receptors and therefore exert their effects by controlling transcription, both receptors have been found in the cytoplasm and cell membrane of axons and dendrites of pyramidal cells and interneurons, as well as in glial cells suggesting the possibility of mechanisms of action that do not rely on transcription alone (Milner et al., 2001; 2005;
Mitterling et al., 2010).
G-protein coupled estrogen receptor (GPER/GPR30)
Another important receptor in estrogen signaling is the G-protein coupled receptor,
GPR30, also referred to as the G-protein estrogen receptor (GPER). GPER was first cloned from the MCF-7 breast cancer cell line and its levels correlated with ER expression in tumours (Carmeci et al., 1997). It was not until 2005, that two research groups showed that GPR30 is capable of binding estradiol with high affinity (Revankar et al., 2005; Thomas et al., 2005). Within the brain, GPER has been detected at high levels in the hypothalamic-pituitary axis, hippocampus, and multiple brain stem nuclei
(Brailoiu et al., 2007). Within the hippocampal formation of mice, GPER expression has been found in the plasma membrane and endoplasmic reticulum of cell bodies, dendrites and axons (Waters et al., 2015). In rat, GPER expression has been limited to the Golgi apparatus with no cell surface detection (Matsuda et al., 2008). It is possible that GPER can activate intracellular signaling while localized to the endoplasmic reticulum or Golgi apparatus, however evidence suggest that in the presence of estradiol, GPER can translocate to the plasma membrane in pyramidal cells (Funakoshi et al., 2006).
8 Other receptors for estradiol
The presence of other receptors for estradiol has been suggested. Toran-Allerand and colleagues proposed a novel, plasma membrane-associated estrogen receptor, termed
ER-X (Toran-Allerand et al., 2002). A Gq-protein coupled receptor, Gq-mER, has been suggested to play an important role in the hypothalamic regulation of energy homeostasis (Qiu et al., 2003; 2006). Furthermore, multiple splice variants of ERα and
ERβ have been identified, and are thought to be involved in plasma membrane initiated signaling. One such splice variant is ERα46, an N-terminal truncated form of ERα, believed to function as a transmembrane receptor (Kim et al., 2011).
Mechanism of estrogen action
Classical genomic signaling
One important characteristic of all steroid hormones is their lipophilic nature, allowing them to freely diffuse across cell membranes. Estradiol, as a steroid hormone, is able to influence gene transcription through hormone-receptor complex interactions with DNA
(reviewed in Nilsson et al., 2001). This allows estradiol to interact with the classical estrogen receptors (ERα and ERβ) in the cytoplasm and nucleus of neurons. Binding of estradiol induces a conformational change that allows the hormone-receptor complex to dimerize and bind with genomic DNA within the nucleus. The hormone-receptor complex binds to sequences known as hormone response elements (HREs) located within the promoter region of genes (reviewed in Truss & Beato, 1993). Following the recruitment of coactivators or corepressors, the hormone-receptor complex can either
9 facilitate or inhibit transcription. This process occurs on an hours to day timescale, and may be important for some of estrogen’s long term effects in the central nervous system.
Rapid, non-genomic signaling
While it was originally believed that estrogens were only able to exert their effects through the genomic pathway, many responses to estrogen occur on a minutes to hour timescale that cannot be explained by the genomic pathway. Evidence of extranuclear localization of estrogen receptors provided support to the idea that estrogens may be able to stimulate cell signaling rapidly (Funakoshi et al., 2006; Mitra et al., 2003). On a basic level, estradiol can bind with estrogen receptors at or near the plasma membrane and lead to an induction of a number of cellular signaling cascades. These cellular cascades lead to a number of changes in transcription, epigenetics, and protein synthesis, which in turn promote changes in dendritic morphology, plasticity and ultimately behaviour (reviewed in Frick, 2015). While we know that activation of certain estrogen receptors can lead to cell signaling cascade activation, how the receptors and intracellular cascades are coupled to one another is still poorly understood, outside of a couple well-defined pathways.
Receptor Involvement
All three of the major estrogen receptors (ERα, ERβ, GPER) have been shown to be able to elicit effects on a minute to hour timescale. There is still debate as to whether
ERα and ERβ are able to act as transmembrane receptors themselves or simply interact with other receptors at the membrane. ERα and ERβ can be targeted to the
10 membrane by S-palmitoylation (Meitzen et al., 2013). ERα and ERβ have been found to interact with metabotropic glutamate receptors through caveolin proteins (Boulware et al., 2005; 2013). Interaction with mGlu1a is mediated by caveolin-1 and leads to cyclic
AMP response element-binding protein (CREB) phosphorylation, whereas interaction with mGlu2 is mediated by caveolin-3 and leads to decreased CREB phosphorylation
(Boulware et al., 2005). The classical estrogen receptors can also interact with insulin- like growth factor 1 receptor (IGF-1R) to stimulate phosphatidyl-inositol 3 kinase
(PI3K)/Akt signaling (Cardona-Gómez et al., 2000; Cardona-Gomez et al., 2002).
Estrogens can also modulate the activity of NMDA receptors (Weiland, 1992; Woolley et al., 1997), as well as increase the synthesis and release of brain-derived neurotrophic factor (BDNF) which in turn activates TrkB receptors (Sohrabji et al., 1995; Briz et al.,
2015).
For the G-protein coupled receptors, GPER and Gq-mER, signaling is determined by the different Gα subunits that localize to the receptor. Evidence suggests that GPER can co-localize with a number of different Gα subunits, but Gq-mER specifically interacts with Gαq (Qiu et al., 2003). Activation of q-mER leads to the activation of a signaling cascade including phospholipase C (PLC), protein kinase C δ (PKCδ), and protein kinase A (PKA) which can go on to phosphorylate any number of targets (Qiu et al., 2003). GPER can also stimulate Gβγ-mediated transactivation of the epidermal growth factor (EGF) receptors, leading to extracellular signal-regulated kinase (ERK) phosphorylation (Filardo et al., 2000).
11 Cell Signaling Cascades
Estradiol can activate a number of signaling cascades and second messengers. The activation of these cascades can facilitate epigenetic modifications, stimulate transcription and increase local protein synthesis. Which cascades are activated will be dependent on the coupling of receptors and/or G-proteins and may be cell and context- dependent. Two effectors of upstream signaling pathways that have been implicated in estrogen signaling, ERK and CREB, will be discussed further.
Activation of the extracellular signal-regulated kinase/mitogen-activated protein kinase
(ERK/MAPK) cascade is important for a number of estrogen’s effects within the central nervous system. ERK can also be activated by a variety of upstream signaling effector including PKA, PKC and PI3K, and is upstream of a number of factors including CREB.
Both ERK1 and ERK2 can be rapidly activated by estradiol. In cortical explant cultures and cultured hippocampal neurons, estradiol activated both ERKs with 5 to 15 minutes
(Singh et al., 1999; Yokomaku et al., 2003). Activation of ERK signaling is important for spinogenesis within the hippocampus, prefrontal cortex, and somatosensory cortex
(Srivastava et al., 2010; Khan et al., 2013; Hasegawa et al., 2015). Blocking ERK prior to estradiol treatment also inhibited CA1 long-term potentiation (LTP) (Hasegawa et al.,
2015). Behaviourally, activation of ERK signaling is essential for both estradiol-induced object recognition and object placement memory consolidation (Fernandez et al., 2008;
Boulware et al., 2013; Fortress et al., 2013). This memory consolidation could be regulated through ERK-induced epigenetic modifications since dorsal hippocampal ERK activation is necessary for estradiol-induced histone H3 acetylation, and H3 acetylation
12 is necessary for object recognition memory consolidation (Zhao et al., 2010; 2012).
Estradiol-driven memory consolidation also relies on DNA methylation, and it has been suggested that ERK may regulate this as well (Zhao et al., 2010). ERK can also enhance gene expression through activation of the transcription factor CREB which has also been linked to learning and memory.
CREB is a nuclear transcription factor, that when phosphorylated at Ser133 can facilitate transcription of a number of genes, including brain-derived neurotrophic factor
(bdnf) (Tao et al., 1998). CREB is an important regulator of cell function as it is positioned to act as a convergence point for a number of signaling cascades. CREB has been implicated in the formation of new dendritic spines and long-term memory (Murphy
& Segal, 1997; Segal & Murphy, 1998; Silva et al., 1998). A link between estradiol and
CREB phosphorylation was first discovered in GnRH neurons of the hypothalamus. An increase in CREB phosphorylation was seen 15 minutes following estradiol exposure
(Abrahám et al., 2003). This link was expanded to include other regions of the brain, such as the hippocampus, and shown to be dependent upon expression of ERα and
ERβ (Abrahám et al., 2004). Interestingly, the ability of estradiol to activate CREB appears to be sex and region-specific, as estradiol was able to increase pCREB in the medial septum, CA1, preoptic area, and ventromedial nucleus in gonadectomized
(GDX) female mice, but only in the medial septum and CA1 of GDX male mice
(Ábrahám & Herbison, 2005). While a number of pathways can activate CREB signaling cascades, evidence suggests that one way estradiol can regulate pCREB is through ER interactions with metabotropic glutamate receptors. ERα interactions with mGluR1a can
13 activate a phospholipase C (PLC)-MAPK cascade enhancing phosphorylation
(Boulware et al., 2005). Conversely, ERα and ERβ can interact with mGluR2/3 to decrease adenylyl cyclase activity and inhibit L-type calcium channel driven phosphorylation (Boulware et al., 2005).
Gonadal versus hippocampal-derived estradiol
It is important to note that hippocampal concentrations of estradiol are considerably higher than serum concentrations, 8.4 nM compared to 0.014 nM respectively in males
(Hojo et al., 2009) and 4.3 nM in proestrus and 0.5-1.0 nM in estrus, diestrus and ovariectomized (OVX) compared to <0.1 nM respectively in females (Kato et al., 2013).
Because of this stark contrast in concentrations, researchers have attempted to understand what role each pool of estradiol has on hippocampal morphology and activity. In cell culture, treatment with the aromatase inhibitor letrozole decreased dendritic spine density, spine synapses, presynaptic boutons, as well as expression of synaptic marker proteins synaptophysin (synaptic vesicle marker) and spinophilin (spine marker) (Kretz et al., 2004; Prange-Kiel et al., 2006). LTP was impaired in hippocampal slices prepared from letrozole-treated male and female mice (Vierk et al., 2012).
Behaviourally, bilateral hippocampal infusion of letrozole impaired object recognition and object placement memory in OVX rats (Tuscher et al., 2016). While these studies establish an important role for locally synthesized estradiol in hippocampal function, they do not elucidate the different contributions of both pools. Gonadal estrogens are still important as evidenced by changes in dendritic spine and spine synapse density following OVX (Gould et al., 1990; Woolley & McEwen, 1992). Understanding the
14 relative contributions and synergies between gonadal and local estrogens will be important moving forward in this field.
Stress Hormone Regulation and Mechanisms of Action
Stress and the HPA axis
The stress response is controlled by the hypothalamo-pituitary-adrenal (HPA) axis
(Figure 1.3). Parvocellular neurons on the paraventricular nucleus (PVN), a sub-region of the hypothalamus, produce and release corticotropin-releasing hormone (CRH) (also known as corticotropin-releasing factor (CRF)) and arginine vasopressin (AVP). CRH is a 41 amino acid peptide hormone that activates two receptors, CRH receptor 1 (CRH-
R1) and CRH receptor 2 (CRH-R2). AVP is a 9 amino acid peptide hormone that binds to a number of receptors including arginine vasopressin receptor 1b (AVPR1B) in the brain and pituitary. Receptors for both CRH and AVP are present within the pituitary.
Binding stimulates the release of adrenocorticotropic hormone (ACTH), a 39 amino acid peptide hormone synthesized as part of the polypeptide pre-pro-opiomelanocortin (pre-
POMC). While CRH is the primary driving force behind ACTH release, the release can be further potentiated by AVP stimulation (Rivier & Vale, 1983). ACTH binds to melanocortin receptor 2 (MCR2) within the adrenal cortex to stimulate the production and release of glucocorticoids (GCs). The main circulating GC in humans is cortisol, whereas corticosterone is the main GC in rodents. Glucocorticoids then exhibit negative feedback on the axis through direct regulation of the hypothalamus and anterior pituitary, as well as indirectly through structures like the hippocampus and amygdala (reviewed in
Handa & Weiser, 2014). Under basal (or unstressed) conditions, HPA axis activity
15 exhibits both circadian and ultradian rhythms (Walker et al., 2010). HPA axis activity and GC levels are highest just prior to the beginning of the wake phase in all species, corresponding to dawn in humans and dusk in rodents. At the same time, pulsatile secretion of CRH and ACTH leads to fluctuations of GC levels over the span of approximately 1 hour. It is changes in the amplitude and frequency of the CRH pulses that lead to the circadian rhythm seen (Walker et al., 2010).
Figure 1.3. The hypothalamo-pituitary-adrenal (HPA) axis.
While CRH is primarily known for its role within the HPA axis, CRH can also act as an excitatory neuromodulator (Aldenhoff et al., 1983; Baram & Hatalski, 1998). In the rat,
CRH-immunoreactivity has been seen throughout the cerebral cortex and hippocampus
(Swanson et al. 1983), as well as the central amygdala (Sawchenko et al., 1993). Within the rat hippocampus, CRH expression peaks at postnatal day 18 with two distinct populations of CRH-immunoreactive neurons, glutamate decarboxylase-expressing
16 GABAergic neurons, as well as a transient population of Cajal-Retzius (CR)-like cells
(Chen et al., 2001). In adult rats, the expression is limited to GABAergic interneurons
(Chen et al., 2001; 2004).
GCs are able to elicit effects throughout the body through binding to mineralocorticoid receptors (MR) and glucocorticoid receptors (GR). Both receptors are members of the nuclear receptor subfamily that includes the estrogen, progesterone and androgen receptors. GRs are expressed throughout the body and nervous system with highest expression seen in regions involved in stress responses including the amygdala, hippocampus, lateral septum, PVN and locus coeruleus (LC) (Reul & de Kloet, 1985).
While MR localization follows a similar pattern to GR, its expression is generally much lower than GR with the exception of the hippocampus (Reul & de Kloet, 1985; Arriza et al., 1988; Ahima et al., 1991). Structurally both receptors are similar, however, cortisol and corticosterone have approximately 10-fold greater affinity for the MR than GR (Reul
& de Kloet, 1985). Therefore, at unstressed levels, GCs primarily interact with MRs.
Following a stressor, GC levels rise and bind to both MR and GR. Because of the differences in receptor affinity, it has been suggested that changes in the ratio of
MR/GR activation may be important for determining the effects of GCs (de Kloet et al.,
1999).
Cellular mechanisms of stress
CRH binds to two G-protein coupled receptors, CRH receptor type 1 (CRHR1) and type
2 (CRHR2), with a higher affinity for CRHR1. Furthermore, expression differences in the
17 receptor subtypes have suggested that CRHR1 plays a larger role in stress and HPA axis mediation than CRHR2. As a G-protein coupled receptor (GPCR), CRHR1 interacts with a number of Gα as well as Gβγ subunits, leading to the activation of various cellular cascades. A number of studies have supported the activation of Gαs leading to increases in cAMP, activation of PKA, and phosphorylation of CREB (Chen et al., 1986;
Dautzenberg et al., 2000), as well as Gαq which activates the PLC-PKC pathway
(Grammatopoulos et al., 2001). Interestingly, mouse strains show different preferences for subunit coupling within the hippocampus with Gαs predominating in C57BL/6N mice and Gαq/11 coupling in BALB/c mice (Blank et al., 2003). CRHR1 can also lead to ERK
1/2 activation within hippocampal CA1 and CA3 regions, as well as thebasolateral complex of the amygdala (Refojo et al., 2005).
Similar to estrogens, GCs are mostly known for their genomic effects, mediated through
MR and GR. However, evidence suggests that GCs can also act via non-genomic rapid mechanisms (reviewed in Groeneweg et al., 2012). While the understanding of the pathways is still limited, parallels to rapid estrogen signaling can be drawn. Both MR and GR have been found to localize to the plasma membrane, however debate exists over whether they are integrated into the plasma membrane or not. It is currently believe that MR and GR are targeted to the plasma membrane through binding with caveolae proteins, similar to ERα and ERβ. Binding of MR and GR to caveolin-1 has been demonstrated in non-neuronal systems (Matthews et al., 2008; Pojoga et al.,
2010). ER-caveoli-1 binding occurs through S-palmitoylation of a conserved cysteine residue within the ER (Acconcia et al., 2005). While the site is conserved in GR, it is lost
18 in MR, suggesting either another site or a different mechanism for receptor-caveolin interaction. Once the receptors are at the plasma membrane, they interact with other receptors, such as GPCRs, to activate different cell signaling cascades. Current studies provide evidence of PLC-PKC, cAMP-PKA, and ERK 1/2 pathway activation, as well as further downstream activation of CREB in response to corticosterone (Liu & Chen,
1995; Olijslagers et al., 2008; Barsegyan et al., 2010; Roozendaal et al., 2010). It is likely that these pathways are differentially activated depending on the brain region of study. The corticosteroid receptors may also be able to interact with receptor tyrosine kinases, similar to ER, but no evidence of such an interaction has been found yet.
Another important consideration in rapid corticosterone effects is the possibility of a novel corticosteroid receptor. A series of corticosterone-driven effects are not blocked by inhibition of MR and GR, suggesting a novel receptor may be mediating some of these effects. The identity of this receptor is currently unknown, however, current research suggests a GPCR as its likely form (reviewed in Groeneweg et al., 2012).
Structural and Functional Responses to Hormones
Responses to Estradiol
Dendritic morphology and synapse formation
How the cellular effects of steroids are translated into integrated neuroendocrine and behavioural responses is not well understood. Beginning in the 1970s, however, it gradually became clear that steroids actually alter the structure of the neuronal circuitry mediating these responses both rapidly and long-term, explaining at least in part how
19 developmental effects of steroids can become effectively permanent (Raisman & Field,
1973).
In adulthood, estradiol has been shown to modulate the density of dendritic spines, the post-synaptic structure where the majority of excitatory synapses are formed (Calabrese et al., 2006). Work in the early 1990’s showed that changes in hippocampal CA1 stratum radiatum dendritic spine density mirrored the changes in estradiol levels throughout the estrous cycle in female rats (Woolley, Gould, Frankfurt, et al., 1990).
CA1 pyramidal cell apical dendritic spines were the highest at proestrus (high estradiol) with a significant decrease seen during estrus (low estradiol). Furthermore, ovariectomy decreased CA1 dendritic spine density, and this could be reversed by treatment with estradiol or estradiol and progesterone in combination (Gould et al., 1990). Further work showed the importance of progesterone in facilitating the quick decrease in spine density seen during the estrous cycle compared to the gradual decrease seen following ovariectomy (Woolley & McEwen, 1993). More recent work has shown that these changes within the CA1 extend throughout the full length of the apical dendrite and are also seen within the proximal and distal regions of CA3 apical dendrites (Mendell et al.,
2016). Similar effects of estradiol on spine density have been shown in the medial amygdala (de Castilhos et al., 2008) and prefrontal cortex (PFC) (Wallace et al., 2006;
Velázquez-Zamora et al., 2012; Khan et al., 2013). Changes in hippocampal dendritic spine density are mirrored by changes in spine synapse density in the cycling female rat
(Woolley & McEwen, 1992). In ovariectomized females rats, injection of estradiol can rapidly induce spine synapse formation (MacLusky et al., 2005). Interestingly, estradiol
20 treatment in gonadectomized male rats does not have the same enhancing effect on spine synapse density as seen in females, as males only show increased synapse density in response to testosterone or dihydrotestosterone (DHT) (Leranth et al., 2003).
Changes in estradiol do not appear to affect the overall structure of the dendritic tree in female rats (Mendell et al., 2016). Similar to rodents, non-human primate species show increases in dendritic spine number and spine synapse density after estrogen treatment in the CA1 (Leranth et al., 2002; Hao et al., 2003) and PFC (Tang et al., 2004; Hao et al., 2007) and spine synapse density.
Neurogenesis
Neurogenesis, or the production of new neurons, is limited in the adult brain to the subgranular zone (SGZ) of the dentate gyrus and the subventricular zone (SVZ)
(Altman, 1963; Altman & Das 1965). Neurogenesis involves two important steps: cell proliferation and cell survival. Estradiol enhanced SGZ cell proliferation in the short term
(2-4 hours) (Tanapat et al., 1999; Ormerod & Galea, 2001) but decreased cell proliferation after 48 hours in female rats and meadow vole (Ormerod & Galea, 2001;
Ormerod et al., 2003). The effects of long-term estradiol replacement may be dependent on the method of administration as chronic, continuous administration
(pellets) did not increase cell proliferation (Tanapat et al., 2005), but daily injections did
(Barker & Galea, 2008). The effect of estradiol on new cell survival has been less studied, but evidence suggests that long-term exposure to estradiol decreases new cell survival (Barker & Galea, 2008).
21 Neuronal excitability and long-term potentiation
Estrogens are able to modulate the intrinsic excitability of neurons as well as LTP (a persistent increase in synaptic strength following high-frequency stimulation that is often studied as an experimental surrogate for learning). In hippocampal slices, application of
17β-estradiol led to reversible depolarization of CA1 neurons and spontaneous action potential generation (Wong & Moss, 1991). Estradiol can also reduce the size of the afterhyperpolarization (AHP) seen after an action potential by decreasing calcium influx and reducing the slow calcium-activated K+ current (Kumar & Foster, 2002; Carrer et al.,
2003). Consistent with these changes, application of estradiol enhanced basal synaptic currents, as measured by field excitatory post-synaptic currents (fEPSPs) throughout the hippocampus (Fugger et al., 2001; Kim et al., 2006). Furthermore, application of estradiol benzoate to hippocampal slices facilitated LTP in response to high-frequency stimulation (Cordoba Montoya & Carrer, 1997; Foy et al., 1999). Interestingly, in acute slices from female rats treated with letrozole, an aromatase inhibitor, induction of LTP was impaired suggesting an important role for locally produced estradiol on hippocampal excitability (Vierk et al., 2012).
Learning & Memory
A number of studies have looked at the effects of estrogens on learning and memory, and generally, higher levels of estrogen lead to enhancements in cognition. Studies of cognition in cycling animals have found Morris water maze performance to be impaired in estrus (when estradiol levels are at their lowest point in the cycle) compared to proestrus, when serum estradiol peaks (Frick & Berger-Sweeney, 2001). Similar cyclical
22 changes were found for both object recognition (OR) memory (Walf et al., 2006) and object placement (OP) memory (Frye et al., 2007) with significantly better performance on both tasks in proestrus and estrus compared to diestrus. In ovariectomized animals, chronic, continuous estradiol replacement via Silastic capsules enhanced both acquisition and memory on the radial arm maze (RAM) task (Luine & Rodriguez, 1994;
Daniel et al., 1997; Luine et al., 1998). For OR and OP, long-term OVX impairs performance on both tasks relative to intact controls (Wallace et al., 2006). Impairments following OVX can be reversed following treatment with 17β-estradiol or estradiol benzoate, an estradiol ester with an extended release rate into the circulation
(McLaughlin et al., 2008; Jacome et al., 2010). Improvements in OR and OP can be exhibited shortly after acute treatment with estradiol (Luine et al., 2003; Phan et al.,
2012). A number of studies of acute estradiol have focused on its effects on memory consolidation. Both OR and OP are enhanced when estradiol is administered just following the learning trial (Luine et al., 2003; Lewis et al., 2008; Inagaki et al., 2010).
However, this enhancement is lost when treatment is delayed following the learning trial
(Luine et al., 2003; Inagaki et al., 2010).
Responses to Stress
Dendritic morphology
The majority of studies focusing on the effects of stress and/or GCs on dendritic morphology have focused on chronic stress paradigms, and generally looked for responses in the male rat hippocampus with relatively fewer studies in females.
Treatment with corticosterone for 21 days or daily 6-hour restraint stress for 21 days
23 resulted in significant decreases in both total dendritic length and number of branch points in CA3 apical dendrites, with no changes seen in CA3 basal dendrites, CA1 or
DG in male rats (Woolley, Gould, & McEwen, 1990; Watanabe et al., 1992). Importantly, the hippocampus recovered following a stress-free period. Similar changes to CA3 dendritic structure were seen with exposure to chronic unpredictable stress paradigms accompanied by dendritic retraction in DG and CA1 (Sousa et al., 2000). However, female rats do not show the same responses to chronic stress. Chronic restraint stress did not induce CA3 apical dendrite retraction in intact, cycling females or OVX females supplemented with estradiol (Galea et al., 1997; McLaughlin et al., 2010). A similar sex difference has been observed in the medial prefrontal cortex of rats undergoing chronic restraint stress; males showed apical dendritic retraction whereas females showed increased dendritic length (Garrett & Wellman, 2009). Responses within the amygdala to chronic stress are diametrically opposite to those in the hippocampus. Thus, in male rats, chronic immobilization stress results in increased dendritic arborisation in the basolateral amygdala (Vyas et al., 2002), and this increase is sustained even after the stress is terminated (Vyas et al., 2004).
In contrast to chronic stress, acute tail shock stress enhances CA1 dendritic spine density in males, whereas it decreases spine density in females 24 hours after stress exposure (Shors et al., 2001). Interestingly, while males and females respond in different directions, the effects are NMDA-dependent in both sexes (Shors et al., 2004).
The response in males is GR-dependent (Komatsuzaki et al., 2012), and the directionality of the effect is differentiated during development by the surge of
24 testosterone secretion occurring normally in males, just after birth (Dalla et al., 2009). In
CA3, acute stress (5h restraint stress) appears to rapidly reduce dendritic spine density specifically on third and fourth-order dendritic branches, corresponding to inputs from associational fibers (Chen et al., 2008). This response is mediated by CRH through a
CRH-R1-NMDA receptor-calpain pathway (Chen et al., 2008; Andres et al., 2013).
Neurogenesis
Adrenal steroids have also been found to impact neurogenesis within the SGZ of the hippocampus. Treatment with corticosterone for two days led to a significant decrease in [H3]thymidine-labeled cells (a marker of cell proliferation) in the granule cell layer, whereas adrenalectomy (ADX) led to an increase in [H3]thymidine-labeled, neuron specific enolase (NSE, a neuron marker) immunoreactive cells (Cameron & Gould,
1994). This effect of corticosterone on cell proliferation could be inhibited by blocking
NMDA receptor activation, suggesting an important role for glutamate signaling
(Cameron et al., 1998). A study examining the effects of acute and chronic restraint stress on cell proliferation and survival found no effect of acute stress, but 3 weeks of chronic stress reduced cell proliferation by 24%, and 6 weeks reduced cell proliferation, survival, total granule cell number, and volume of the granule cell layer (Pham et al.,
2003). All studies were performed in male rodents. It is unclear if similar effects are seen in females.
25 Synaptic Transmission & Plasticity
Studies on the effects of stress on synaptic plasticity have focused on its effects on three main events: 1) glutamate release, 2) suppression of LTP, and 3) induction of long-term depression (LTD). As these studies have been performed in male rats, it is unclear if similar responses occur in females.
Acute stress can elevate extracellular glutamate levels within the hippocampus and levels return to baseline within an hour after stress is terminated (Lowy et al., 1993).
Furthermore, ADX prevents the stress-induced rise in glutamate, suggesting a role for adrenal steroids (Lowy et al., 1993). In fact, injection of corticosterone induces a rapid increase in extracellular glutamate that peaks 15 minutes following treatment, and returns to baseline by 45 minutes (Venero & Borrell, 1999). A more recent study has shown that increases in glutamate release following stress are not specific to the hippocampus with increases also found in the cerebral cortex, however, cortical increases were maintained for over an hour unlike the hippocampus (Kim et al., 2012).
Overall, these studies point to a change in glutamatergic transmission following stress.
Studies examining the effects of stress on hippocampal LTP have produced mixed results, illustrating the importance of time between stressor and induction of LTP. The majority of studies looking at stress effects on LTP have found stress to impair LTP. In response to high frequency stimulation, hippocampal slices from stressed male rats either exhibited no LTP or significantly reduced potentiation compared to controls (Foy et al., 1987; Shors & Thompson, 1992; Kim et al., 1996; Cazakoff & Howland, 2010;
26 MacDougall & Howland, 2013), and LTP induction is still impaired 2 days after stress ended (Shors et al., 1997). LTP within the DG is similarly impaired, however the impairment is more transient and recovers after 24 hours (Shors & Dryver, 1994). A study by Wiegert and others examined the relationship between timing of corticosterone exposure and high-frequency stimulation in determining whether or not LTP occurred.
Corticosterone delivered just prior to and during high-frequency stimulation enhanced synaptic potentiation, whereas delivery of corticosterone 30 minutes prior to or just after stimulation had no effect (Wiegert et al., 2006). Another important factor influencing LTP and synaptic plasticity is CRH. CRH is excitatory within the hippocampus and stimulates action potential firing and reduces afterhyperpolarization (Aldenhoff et al., 1983; Refojo et al., 2011). Intrahippocampal infusion of CRH has been found to facilitate long-lasting potentiation within the DG (Wang et al., 1998; 2000) and LTP of population spikes within the CA1 (Blank et al., 2002). The above results suggest that just following exposure to stress, the hippocampus is highly plastic; however, this plasticity is quickly lost and LTP is impaired. These temporal changes in plasticity may be responsible for facilitating learning following an emotional experience (Diamond et al., 2007). Studies have also explored the ability of stress to influence LTD. Kim and others (Kim et al.,
1996) found that restraint plus tail shock could enhance LTD in the CA1. Similar results were found following exposure to other stressors (exposure to a novel chamber or elevated platform stress) (Xu et al., 1997). This effect on LTD is dependent on NMDA receptor activation (Kim et al., 1996).
27 Learning and memory
Studies on the effects of stress on learning and memory have focused generally on the hippocampal-dependent tasks examining spatial memory (i.e. radial arm maze and object location), recognition memory, and fear conditioning. Effects of stress on these tasks are dependent on both the length of the stressor, the age of the animals, and the sex of the animal being tested.
Chronic stress in males (generally restraint for 6 hours/day over 21 days) consistently produces deficits in a variety of tasks including the Y maze (Conrad et al., 1996; 2003;
McLaughlin et al., 2007; Orsetti et al., 2007), radial arm maze (Luine et al., 1994;
Srikumar et al., 2006; 2007), object placement (Beck & Luine, 2002), object recognition
(Beck & Luine, 2002; Orsetti et al., 2007), and Morris water maze (Sousa et al., 2000).
Interestingly, studies looking at shorter stress paradigms (7 to 13 days) either do not find deficits, or in fact find small but significant improvements (Luine et al., 1996). These impairments are found at the same time that CA3 dendritic retraction is found suggesting the loss of dendritic complexity may play a role. In contrast to spatial and recognition memory tasks, chronically stressed males show enhanced contextual and cued fear conditioning (Conrad et al., 1999). Comparatively, chronically stressed females do not show the same deficits and in some cases show enhanced performance following chronic stress. Females show enhanced performance on the Y maze
(McLaughlin et al., 2005), radial arm maze (Bowman et al., 2001), and object placement
(Beck & Luine, 2002), whereas they showed no changes in performance on object recognition (Beck & Luine, 2002). It has been suggested that this difference in males
28 and females is due to a shift in time to enhancement or impairment, and that over time the sex difference in performance would be lost (Luine, 2002). Currently, this hypothesis has not been explored further.
Similar to studies on chronic stress, the effects of acute stress on learning and memory have been primarily examined in male rodents. Acute stressors have been found to impair memory retrieval on the Morris water maze (de Quervain et al., 1998; Kim et al.,
2005; Wong et al., 2007), radial arm water maze (Diamond et al., 1999; Woodson et al.,
2003; Diamond et al., 2006; Park et al., 2008), Y maze (Conrad et al., 2004; Wagner et al., 2013), objection location recognition (Howland & Cazakoff, 2010; Wagner et al.,
2013), and OR (Howland & Cazakoff, 2010) with no impairments in learning. However, two studies indicate the importance of time in these effects. Stressors can have negative effects on memory when delivered before learning or after learning. Exposure to short predator stress just prior to learning in the radial-arm water maze have been found to enhance spatial memory, consistent with the effects of acute stress on LTP induction (Diamond et al., 2007). For exposure to stress after learning, the relation to the test phase appears to be important as rats stressed 30 minutes prior, but not 2 minutes or 4 hours prior to the test phase, show memory deficits in the Morris water maze (de Quervain et al., 1998). In females, acute stress both before or after learning or before testing has been found to impair radial-arm water maze performance both 30 minutes and 24 hours after training (Park et al., 2008), but acute restraint two hours prior to the first trial enhance Y maze performance (Conrad et al., 2004).
29 Neurobehavioural disorders correlated to estrogens and stress
Estrogen/stress interactions have also been linked to the prevalence of neurological disorders such as anxiety, post-traumatic stress disorder (PTSD), and depression.
Inappropriate activation and persistent activation of the stress response is believed to underlie many psychiatric disorders. Cortisol levels falling outside of normal ranges
(both high and low) have been correlated to PTSD and depression (reviewed in
Bangasser & Valentino, 2014). Furthermore, sex differences in prevalence and presentation are found for anxiety-related disorders and depression. Women are 1.7 times as likely to experience major depression, and this sex difference begins around puberty and continues until the mid-50s (Kessler et al., 1993). Further studies found this sex difference to be greatest in major depression comorbid with anxiety (Breslau et al.,
1995). For PTSD, women have an average two-fold higher prevalence than males
(Ditlevsen & Elklit, 2010). Due to evidence that gender differences appear in early adolescence around the onset of puberty, many have speculated a role for estrogen.
Plasma estradiol levels have also been found to be lower in depressed women than health controls (Young et al., 2000). Within the rodent literature, evidence supports a role for estradiol in reducing anxiety and depression (reviwed in Walf & Frye, 2006).
Interactions Between Gonadal and Stress Hormones
Gonadal regulation of the HPA axis
Sex differences in HPA axis function were first described in the 1960’s and have been consistently shown in rodents. These differences appear at all levels of the axis affecting all hormone levels, MR and GR levels as well as corticosterone binding
30 globulin (CBG) expression. Overall, it appears that female rodents have higher baseline plasma total corticosterone levels, and a faster, greater, and longer response to stressful stimuli with many of these differences being attributed to gonadal steroids
(Iwasaki-Sekino et al., 2009; Goel & Bale, 2010). While the majority of research has focused on the presence or absence of estradiol in mediating these differences, studies looking at testosterone have found it suppresses the activity of the HPA axis (Handa et al., 1994; Viau & Meaney, 1996). Testosterone is important for the development of sex difference within the HPA axis. While these sex differences are not fully established until after puberty, the neonatal testosterone surge and subsequent local conversion to estradiol seen in males, plays an organizational role in its development. Treatment of neonatal females with estradiol benzoate leads to a more male-typical diurnal pattern of corticosterone in adulthood (Patchev et al., 1995; 1999). Conversely, males that undergo neonatal gonadectomy show elevated basal corticosterone levels in adulthood as well as a greater corticosterone response to acute restraint stress (McCormick et al.,
1998; Patchev et al., 1999).
The CRH promoter is under the control of both estrogens and androgens. ERE half sites were first discovered in the CRH promoter in 1993 (Vamvakopoulos & Chrousos,
1993). However, it appears that interaction of either ERα or ERβ with a cAMP regulatory element (CRE) is necessary for estrogenic control (Lalmansingh & Uht, 2008). It follows then that CRH mRNA levels are found to fluctuate throughout the estrous cycle. CRH mRNA in the PVN is found to peak the morning of proestrus and fall by afternoon, corresponding with the estradiol surge just prior to ovulation (Hiroshige & Wada-Okada,
31 1973; Bohler et al., 1990). While estrogen activates the promoter, testosterone appears to repress promoter activity through binding of AR to an androgen-response element
(ARE) (Bao et al., 2006). Estrogens can also impact the activity of hypothalamic CRH neurons through the Gq-mER. Activation of this receptors leads to suppression of M- currents, which allows for greater glutamatergic neurotransmission in these neurons, leading to increased corticosterone levels (Hu et al., 2016). It is currently unknown if similar responses to estradiol are seen in other CRH-expressing neuron populations.
ACTH levels have also been examined in males and females at rest and following stress. While ACTH levels varied throughout the day (elevated during wake), no differences were seen on any day of the estrous cycle (Viau & Meaney, 1991). However, following stress sex differences in ACTH reactivity appear. Following a psychological stressor (three minutes in a well-ventilated jar), plasma ACTH concentrations were 3 times higher in female than male rats (Le Mevel et al., 1979). In male rats, gonadectomy lead to increased ACTH release in response to stress that could be prevented by testosterone replacement (Kitay, 1963). In female rats, the response was opposite; gonadectomy inhibited ACTH synthesis and release while estradiol replacement led to an increase in both (Kitay, 1963). Furthermore, studies examining ACTH release in female rats following stress throughout the estrous cycle found responses to be the greatest in proestrus alone (restraint stress) or proestrus & estrous
(intracerebroventricular ethanol) (Viau & Meaney, 1991; Larkin et al., 2010). However, not all studies have found estradiol to enhance ACTH release in rats (Young et al.,
2001). This may in part be due to differences in estradiol replacement doses.
32 Most studies of HPA axis activity have focused on the effect of gonadal steroids on corticosterone levels as it is considered the main effector of the axis. A foundational study from the 1960’s found that intact male and female rats showed a circadian rhythm in corticosterone production and release, and that the peak in its expression was significantly greater in females than males, and this difference in peak corticosterone could be abolished by GDX (Critchlow et al., 1963). GDX with hormone replacement
(testosterone or DHT in males and estradiol in females) restores the cyclicity and levels to those seen in intact animals (Seale et al., 2004). Furthermore, the peak in corticosterone appears to vary by estrous cycle day with the highest peak seen in proestrus when estradiol is highest (Raps et al., 1971). Changes in corticosterone in response to stress also appear to be sexually differentiated. Another study found the same differences in basal corticosterone levels, but also found that females responded more strongly to a stressor, in this case ether anesthesia, than males (Kitay, 1961).
This effect could be replicated by ACTH injection. Since then, numerous studies have replicated these findings with a number of different stressors including restraint (Viau et al., 2005; Goel & Bale, 2010), cold swim stress (Bohacek et al., 2015), psychological stress (Le Mevel et al., 1979; Iwasaki-Sekino et al., 2009), and footshock stress
(Iwasaki-Sekino et al., 2009). Similarly, OVX females show a blunted response to stress that can be recovered with estradiol injection (Burgess & Handa, 1992; Seale et al.,
2004) and castrated males show an elevated response that can be prevented with testosterone or DHT injection (Seale et al., 2004).
33 One important consideration in the differences in corticosterone levels is that most corticosterone travels through the circulation bound to corticosteroid-binding globulin
(CBG), similar to other steroid hormones. CBG levels are two fold higher in female rats than male rats (Gala & Westphal, 1965a; 1965b). While GDX in females had no effect on CBG activity, castrated males showed a significant increase in CBG activity (Gala &
Westphal, 1965b). Consequently, free corticosterone levels in male and females rats were not significantly different.
Stress regulation of the HPG axis
The ability of HPA axis hormones to affect the HPG axis has long been known. CRH and GCs, both natural and synthetic, have been implicated in this regulation.
Administration of CRH has been found to dose-dependently inhibit LH in GDX females and at higher doses can inhibit the LH surge in cycling females (Rivier & Vale, 1984).
This is believed to occur by blocking the release of GnRH from the hypothalamus
(Gambacciani et al., 1986; Petraglia et al., 1987). Both CRH-R1 and CRH-R2 appear to be involved in this inhibition, but which receptor(s) are involved appears to be stressor dependent (Li et al., 2006). Furthermore, whether CRH acts directly or indirectly on
GnRH neurons is still unclear (MacLusky et al., 1988; Hahn et al., 2003). More recent research has shown CRH treatment to inhibit steroidogenesis and estradiol production in particular (Dinopoulou et al., 2013; Yu et al., 2016). Effects of GCs have been demonstrated since the 1960s. Administration of ACTH to pregnant rats impairs implantation and fetal development by increasing GC levels (Yang et al., 1969).
Treatment with dexamethasone, a synthetic GC with high affinity for GR, delayed
34 ovulation in intact rats (Baldwin & Sawyer, 1974). In cycling females undergoing 5 days of footshock stress, 50% of the rats showed desynchronized estrous cycles (Pollard et al., 1975). A further study by Baldwin (Baldwin, 1979) further examined how GCs may exert their effects on the HPG axis. Exposure to high levels of GCs appears to decreased pituitary responsiveness to GnRH.
The Hippocampus
One major region influenced by gonadal and stress hormones and their interactions is the hippocampus. The hippocampus is an important structure within the medial temporal lobe, well known for its roles in learning and memory. The first study to establish a function for the hippocampus involved the examination of patient H.M., a man who underwent a bilateral temporal lobe resection in an attempt to control epilepsy
(Scoville & Milner, 1957). While H.M. showed no deficits in general intelligence or marked changes in personality, he showed a complete loss of memory for recent events and incapability to form new declarative memories (Scoville & Milner, 1957). Since then, hippocampal structure and function have been extensively studied in rodents, non- human primates and humans. The hippocampus plays a role in a variety for forms of memory including episodic memory, spatial memory and contextual fear (Fanselow &
Dong, 2010).
The structure and major connections within the hippocampus are well conserved across studied species. The hippocampal formation consists of the DG, the cornu ammonis
(CA) that is divided into four subregions, CA1, CA2, CA3, and CA4, and the subiculum.
35 The CA1 and CA3 regions are the largest and best-defined CA regions and have consequently been studied in more depth than CA2 and CA4. The main input to the hippocampus comes from the entorhinal cortex (EC), the cortical tissue overlying the hippocampus. The EC in turn receives inputs from other cortical regions as well as the medial septum, hypothalamus, raphe nuclei and LC, acting as a site of integration for a variety of stimuli (reviewed in Canto et al., 2008). The hippocampus and the surrounding EC are connected via the perforant pathway. The perforant pathway extends from layers II and III of the EC to the granule cells of the DG. From here, granule cells project axons via the mossy fiber system to the dendrites of CA3 pyramidal cells. These CA3 pyramidal cells project to CA1 pyramidal cells via the
Schaffer collateral pathway. The perforant pathway, mossy fibres and Schaffer collaterals are together known as the trisynaptic circuit (Figure 1.4). The CA1 finally projects back to the EC either directly or via the subiculum generally to the deeper layers (layer VI) with some axons projecting to layer III as well. Hippocampal projections also travel to regions such as the PFC, lateral septal area, and amygdala (Fanselow &
Dong, 2010). While these are the primary connections within the hippocampal formation, other important internal connections exist: EC projections are sent to all regions of the hippocampus (Canto et al., 2008), and the CA3 axon connect with neighbouring pyramidal cells and interneurons building an associative network within CA3 (reviewed in Le Duigou et al., 2014).
36
Figure 1.4. The hippocampus and trisynaptic circuit. The perforant pathway projects from the entorhinal cortex (EC) to the dentate gyrus (DG). Axons from the DG form the mossy fibre system that projects to the CA3. CA3 pyramidal neurons project to CA1 pyramidal neurons forming the Schaffer collaterals. Adapted from “Drawing of the neural circuitry of the rodent hippocampus” (1911) by Ramón y Cajal.
The hippocampus can also be subdivided by location along its long axis: dorsal-ventral in rodents and rostro-caudal in humans and non-human primates. While structurally, both the dorsal and ventral hippocampus exhibit the same tri-synaptic pathway, functionally, studies of synaptic connectivity, hippocampal lesions, and gene expression have provided evidence that the dorsal and ventral hippocampi may function as distinct regions and are responsible for different tasks. The dorsal hippocampus has been primarily implicated in spatial learning and memory (Strange et al., 2014). Dorsal CA1 and subicular projections travel to cortical regions such as the retrosplenial and anterior cingulate cortices, mammillary nuclei and the lateral septum (Fanselow & Dong, 2010).
Conversely, the ventral hippocampus is more involved in emotional memory tasks, including stress, emotion and affect (Strange et al., 2014). The ventral hippocampus is
37 strongly interconnected with the amygdala with both regions sending projections to the other, as well as indirectly to the hypothalamus via the bed nucleus of the stria terminalis (BnST) allowing for regulation of the HPA axis (Fanselow & Dong, 2010).
Hippocampal Plasticity
The hippocampus is a highly plastic region that can exhibit both structural and functional changes in response to gonadal and stress hormones. Structural plasticity can involve changes in the dendritic tree, such as the amount of branching or total length of dendrites, as well as the density of spines and synapses within a given region. The complexity of the dendritic tree can be impacted by a number of factors. One well established effector of change in dendritic tree complexity is chronic restraint stress
(Watanabe et al., 1992). Another form of plasticity involves dendritic spines. Dendritic spines can change shape and numbers in response to a variety of stimuli (reviewed in
Calabrese et al., 2006). It is important to consider the impact of both changes on the system level and individual synapse level together. For example, while loss of androgens decreases dendritic spine density and spine synapse density in males, it also increases the complexity of the dendritic tree (Mendell et al., 2016). While this results in a negligible change in total synapse number, the distribution of input has changed (Mendell et al., 2016). This may help to explain why the effects of androgen deprivation on cognition are mixed. The SGZ of the hippocampus is also one of two brain regions that continue to produce new neurons into adulthood. These newborn neurons integrate into the DG and send projections to CA3, and have been implicated in
38 hippocampal-dependent behaviours including contextual fear conditioning, pattern separation and memory formation (Gu et al., 2013; Yau & So, 2014).
Synaptic plasticity describes the ability of synaptic connections between neurons to change in strength in response to a variety of stimuli. Stimuli include, but are not limited to, activity and experience (Zhao et al., 2015), neurotrophins such as BDNF, multiple hormones, including gonadal steroids and stress hormones (Scharfman & MacLusky,
2014), as well as drugs of addiction (Fole et al., 2015). Synaptic plasticity is thought to play an important role in memory formation, as studies where plasticity is impaired show impairments in memory (He et al., 2014). Plasticity encompasses both increases and decreases in synaptic strength termed potentiation and depression, respectively.
Plasticity can also occur on different time scales from milliseconds (short) to days (long).
One of the best-studied forms of synaptic plasticity is LTP, a process thought to underlie learning and memory (Bliss & Collingridge, 1993). One of the best-understood mechanisms of synaptic plasticity is NMDA receptor (NMDAR) dependent plasticity within the hippocampus. In brief, activation of NMDAR allows for Ca+2 to flow into the neuron and increase intracellular Ca+2 levels. Ca+2 can then complex with calmodulin
(CaM) to facilitate either potentiation or depression through modifications to both A- amino-3-hydroxy-5-methyl-4-isoxazole propionic acid receptor (AMPAR) number and ion channel conductance (He et al., 2014). In this mechanism, NMDAR works as a
“coincidence detector”, in that two events must happen simultaneously for LTP or LTD to occur. These events are 1) sufficient postsynaptic membrane depolarization to remove the Mg+2 block from the NMDAR channel, and 2) binding of glutamate to
39 NMDAR to open the channel (Bliss & Collingridge, 1993). Whether or not LTP or LTD occurs is dependent upon how much Ca+2 enters the neuron. Low frequency of stimulation causes a moderate increase in Ca+2 leading to LTD, whereas high frequency stimulation causes a large increase in Ca+2 leading to LTP (He et al., 2014).
MicroRNAs
From the preceding review, it is clear that the hippocampus is a major potential target for integration of the effects of sexual differentiation, sex hormones and stress on neuroendocrine function and behaviour. We also have evidence that the hippocampus is a direct target for the effects of both gonadal and stress hormones because receptors for both classes of hormones have been identified in cells of the hippocampal formation
(Mitra et al., 2003; van Pett et al., 2000; Reul & de Kloet 1985). A major remaining puzzle, however, is how the actions of hormones are translated into the rapid changes in neuronal structure and function that are observed –in some cases with latencies in minutes, as opposed to hours or days (Phan et al., 2011; 2012; Gabor et al., 2015). One possible mechanism is via the regulation of miRNA synthesis. This potential mechanism has so far received very little attention in the literature, despite evidence that it is involved in the actions of steroids in non-neural tissues, and of considerable importance in the regulation of neuronal plasticity.
MicroRNA Biogenesis and Degradation
The miRNAs are a family of small (20 to 24 nucleotide), non-coding RNAs that have the ability to regulate gene expression post-transcriptionally (Lee & Ambros, 2001). Most
40 miRNAs are produced via the canonical biogenesis pathway (reviewed in (Winter et al.,
2009)) (Figure 1.5). MiRNAs are first transcribed as primary miRNAs (pri-miRNAs) by
RNA polymerase II (Lee et al., 2004). These primary transcripts are often 5’ capped and polyadenylated. Pri-miRNAs can either exist within the introns of coding genes (intronic or intragenic miRNAs) and utilize the promoter of the host gene or can be intergenic, having their own promoter and enhancer sequences (Gromak 2012). Some miRNAs are transcribed together as part of one primary transcript, such as the miR-17-92 cluster.
The pri-miRNA transcript undergoes further processing within the nucleus to produce an
~70-nt hairpin miRNA precursor (pre-miRNA). This process is undertaken by the RNase
III Drosha in concert with the DiGeorge critical region 8 (Dgcr8) protein (Lee et al., 2003;
Landthaler et al., 2004). Drosha is responsible for the cleavage, whereas Dgrc8 guides
Drosha to the appropriate cleavage site (Han et al., 2006). From there, pre-miRNAs are exported from the nucleus to the cytoplasm via the Exportin-5/Ran-GTP complex (Yi et al., 2003; Bohnsack et al., 2004; Lund et al., 2004). Within the cytoplasm, pre-miRNAs are further processed by Dicer to remove the loop and yield a miRNA duplex (Grishok et al., 2001; Ketting et al., 2001). Following separation of the miRNA strands, the mature miRNA is incorporated in the miRNA-induced silencing complex (miRISC). The miRISC is comprised of a number of proteins, including the Argonaute family, the main effector protein within the RISC (Liu et al., 2004).
Some miRNAs do not follow the canonical pathway. One such group of miRNAs bypass
Drosha/Dgcr8-mediatated cleavage only to re-join the pathway to undergo Dicer- mediated cleavage. These miRNAs are known as mirtrons, and are found in short
41 intronic sequences of mRNA. The short introns are spliced from the transcript and yield pre-miR like hairpin structures (Berezikov et al., 2007; Okamura et al., 2007; Ruby et al.,
2007). Other non-canonical miRNA pathways have been discovered and reviewed by
Abdelfattah and others (Abdelfattah et al., 2014).
Figure 1.5. The canonical microRNA biogenesis pathway. Primary microRNA are transcribed and cleaved by a Drosha/Dgcr8 complex to produce precursor microRNA (pre-miRNA). Following export from the nucleus, pre-miRNA are cleaved by Dicer to yield mature miRNA. Reproduced with author’s permission. (Winter et al., 2009)
Despite how much is known about the production of miRNA, comparatively little is known about their turnover and decay. MiRNA half-lives appear to be variable and dependent on the tissue and specific miRNA being studied. A genome-wide study performed in mouse fibroblasts found populations of miRNAs with fairly long half-lives
(T1/2 > 24 h) as well as miRNAs will comparatively rapid turnover (T1/2 ~ 4-14 h) (Marzi et al., 2016). Neurons present an interesting model for studies of miRNA turnover. In
42 general, it appears that half-lives of miRNAs are shorter in neurons. Some miRNAs are activity-dependent and turnover can be inhibited by blocking action potentials (Krol et al.,
2010). Others, such as miR-219, show faster turnover in the absence of glutamatergic activity (Kocerha et al., 2009). Recent research has found that mRNAs with high complementarity to both the 5’ and 3’ regions of miRNAs can destabilize these miRNAs
(Ameres et al., 2010). This path for miRNA decay, known as target RNA-directed miRNA degradation (TDMD), appears to be important in neuronal cells in particular (la
Mata et al., 2015). While the exact mechanism of this decay is not fully known, miRNAs loaded into the RISC appear to be tailing and then undergo 3’ to 5’ trimming (Ameres et al., 2010; la Mata et al., 2015). Studies have begun to explore the proteins involved in the process with DIS3L2 implicated in TDMD of miR-27 (Haas et al., 2016).
MicroRNA Targeting and Functions
Upon incorporation of the mature miRNA in the miRISC, the complex is guided to bind to the 3’ untranslated region (3’-UTR) of target mRNA transcripts. Identification of targets by miRNAs is determined by base complementarity to the 5’ region of the miRNA (Brennecke et al., 2005). Specifically, the minimum requirement for base paring consists of nucleotide 2 through 7 (6mer), with regulation strengthened by base pairing at the 1 and/or 8 positions (7mer and 8mer) (Brennecke et al., 2005; Grimson et al.,
2007). While it is generally accepted that the majority of miRNA-mRNA binding occurs in the 3’-UTR, evidence suggests the presence of non-traditional binding sites in other regions of mRNA including the 5’-UTR and the coding DNA sequence (CDS) (Khorshid et al., 2013).
43 MiRISC post-transcriptional regulation can occur via a number of mechanisms including endonucleolytic cleavage, translational repression or mRNA destabilization/decay
(reviewed in (Filipowicz et al., 2008)). The endonucleolytic cleavage of target mRNAs requires a high degree of base complementarity (reviewed in (Ameres & Zamore,
2013)). In mammals, cleavage can only be performed by Ago2 as it has slicer activity
(Liu et al., 2004; Meister et al., 2004). Cleavage is not the predominant path in mammals, with mRNA destabilization/decay and translational repression responsible for the majority of post-transcriptional control. The destabilization and decay of target mRNAs requires the recruitment of a variety of factors including deadenylases and decapping enzymes, as well as the displacement of poly(A)-binding protein (PABP) from the poly(A) tail (Behm-Ansmant et al., 2006; Moretti et al., 2012; Nishihara et al.,
2013). GW182 is responsible for the recruitment of deadenylase complexes CCR4-NOT and PAN2-PAN3 as well as decapping enzymes and activators DCP1, Me31P and HPat to the RISC (Behm-Ansmant et al., 2006; Nishihara et al., 2013). Removal of the poly(A) tail and m7G cap allow for the 5’ to 3’ degradation of the mRNA to occur (Iwakawa &
Tomari, 2015). MiRNAs have been suggested to inhibit the initiation of translation through a variety of mechanisms (Kiriakidou et al., 2007). The importance and relative contribution of each pathway in animals is still not fully understood. Recent evidence has suggested that while translational repression may be active earlier, mRNA destabilization accounts for the majority of miR-related repression (Guo et al., 2010;
Béthune et al., 2012; Djuranovic et al., 2012; Eichhorn et al., 2014).
44 MicroRNA involvement in the nervous system
Lagos-Quintana and others first detected miRNAs in the brain in 2002. In the following years, other studies suggested an important role for miRNAs in neuronal development and differentiation (Lagos-Quintana et al., 2002; Krichevsky, 2003; Sempere et al.,
2004). Since then, miRNAs have been implicated in a number of cellular processes, learning & memory, as well as many disorders of the nervous system. Many miRNAs are known to be significantly enriched in the nervous system including miR-9, miR-124, miR-125, miR-127, miR-128, miR-132, and miR-138 (Bak et al., 2008; Juhila et al.,
2011).
MicroRNAs in neuronal plasticity
MiRNAs have been implicated in a number of processes underlying neuronal and synaptic plasticity. Several miRNAs are thought to play a role in dendritic spine maturation and density. Most miRNAs have been found to negatively regulate dendritic spines. MiRNAs 134 and 138 have both been shown to decrease the size of dendritic spines (Schratt et al., 2006; Siegel et al., 2009), and overexpression of miR-125b produces long, thin dendritic spine in hippocampal neurons with a related decrease in miniature excitatory post-synaptic currents (eMPSCs) (Edbauer et al., 2010).
Conversely, miR-132 appears to have a positive affect on dendritic spine density as well as an increase in stubby/mushroom type spines, thought to be related to the strength of the related synapse (Edbauer et al., 2010; Hansen et al., 2010; Impey et al., 2010;
Magill et al., 2010). MiRNAs have also been shown to influence dendritic outgrowth and complexity. MiRNAs 26a, 124, 132 and 134 have all been shown to increase neurite
45 extension (Vo et al., 2005; Yu et al., 2008; Fiore et al., 2009; Magill et al., 2010; Li &
Sun, 2013). Involvement in dendritic complexity has been less clear, with miR-132 increasing dendritic arborisation (Magill et al., 2010) and conflicting reports for the effects of miR-124 with both increases and decreases seen (Xu et al., 2008; Franke et al., 2012). Axonal development and branching are regulated by miRNAs. Expression of miR-9 has been shown to increase axon branching and decrease axon length (Dajas-
Bailador et al., 2012). MiR-124 is also able to positively regulate axonal branching through inhibition of RhoG (Franke et al., 2012) as well as play a role in axon guidance
(Baudet et al., 2011). The miR-17-92 cluster and miR-132 both promote axonal outgrowth (Vo et al., 2005; Zhang et al., 2013). Overall, miRNA are extensively involved in the regulation of neuronal development and plasticity.
MicroRNAs in learning and memory
Concurrent with the understanding that miRNAs can influence underlying dendritic and axonal processes, multiple studies have examined the role of miRNAs in learning and memory. A 2010 study by Konopka and others, examined the effects of widespread miRNA loss with a Dicer1 conditional knockout in the mouse forebrain (Konopka et al.,
2010). These animals showed an enhancement in memory at 12 weeks post-Dicer1 knockout followed by neurodegeneration, highlighting the importance of miRNAs in learning and memory. Since then, studies have focused on multiple individual miRNAs and their relation to learning and memory processes. Two miRNAs highly implicated include miR-124 and miR-132. Inhibition of miR-124 has been shown to enhance LTP formation and spatial learning (Zhao et al., 2013; Malmevik et al., 2016), whereas
46 overexpression of miR-124 impairs LTP, as well as spatial learning and social preferences (Yang et al., 2012). The increased or decreased expression of miR-132 appear to impair learning and memory, with over- and under-expression impairing novel object recognition, spatial memory, and trace fear conditioning (Scott et al., 2012;
Hansen et al., 2013; Wang et al., 2013; Hansen et al., 2016). Other miRNAs implicated in learning and memory include miRs 9, 34, 128b, 134, 182, 195 & 204 (Aksoy-Aksel et al., 2014; Malmevik et al., 2016; Mohammed et al., 2016).
MicroRNAs in disorders of the nervous system
Dysregulation of miRNAs has been implicated in a variety of neurological disorders including autism spectrum disorders (ASDs), depression, schizophrenia, and AD. Two studies have looked at miRNA expression in ASD. Abu-Elneel and others found 28 miRs to be dysregulated in the cerebellum in at least one ASD case compared to healthy controls (Abu-Elneel et al., 2008). Another study found 43 miRs dysregulated
(20 down regulated, 23 up regulated) in lymphoblasts of autistic individuals compared to their unaffected siblings (Sarachana et al., 2010). Researchers looking at miRNAs in depression have shown miR-16 to be an important regulator of the serotonin transporter
(SERT) and in the action of selective serotonin reuptake inhibitor (SSRIs) antidepressant medications (Baudry et al., 2010; Launay et al., 2011). A polymorphism in miR-30e has been significantly associated with susceptibility to major depressive disorder (MDD) (Xu et al., 2010), and depression and suicide are also associated with a global down regulation of miRNA production with 21 miRs found to be significantly reduced (Smalheiser et al., 2012). MiRNA involvement in schizophrenia has been
47 extensively studied with a number of miRNAs shown to be altered in the PFC and superior temporal gyrus (Beveridge & Cairns, 2012). Specifically, increases in miR-181b and decreases in miR-219 levels have been implicated in altered glutamatergic signalling (Beveridge et al., 2008; Kocerha et al., 2009). Schizophrenic susceptibility has also been associated with a single nucleotide polymorphism within the primary transcript of miR-137 (Schizophrenia Psychiatric Genome-Wide Association Study
(GWAS) Consortium, 2011). MicroRNA involvement in AD pathology is also well studied.
Several miRs have been consistently implicated in AD including downregulation of miR-
9, 29, 106, 107, and 181 and upregulation of miR-34 and 146a (Femminella et al., 2015).
Hormonal Regulation of MicroRNAs
Estrogen-microRNA connections
The role of miRNA in estrogen production and receptor function, as well as the involvement of estrogens in miRNA expression have been studied in a wide variety of tissues and cell lines including the classically hormone responsive tissues of the breast, ovary and uterus, as well as bone, liver, spleen and brain. The majority of research to date has focused on the reciprocal relationships in breast cancer pathogenesis in both breast cancer cells lines (i.e. MCF-7 and T47D) and human tissue samples.
Breast and breast cancer
MiRNA regulation of ERα has been well characterized with over 15 suspected and confirmed miRNAs targeting its 3’-UTR. The first miRNA found to target ERα was miR-
206 (Adams et al., 2007). Not only does miR-206 decrease ERα expression, but ERα is
48 able to inhibit the expression of miR-206, and this reciprocal relationship is mirrored in breast cancer tumours (Adams et al., 2007; Kondo et al., 2008). Two other miRNAs have been found to have a similar negative feedback loop with ERα: miR-221 and miR-
222 (Zhao et al., 2008; Cochrane et al., 2010). Other miRs shown to regulate ERα expression include the let-7 family members 7a, 7b and 7i (Zhao et al., 2011), miR-9
(Pillai et al., 2014), the miR-17-92 cluster members miR-18a and 18b (Castellano et al.,
2009; Leivonen et al., 2009), miR-22 (Pandey & Picard, 2009), miR-193b and miR-302c
(Leivonen et al., 2009), and miR-4728 (Newie et al., 2014). To date, only one miR has been found to regulate ERβ: miR-92 (Al-Nakhle et al., 2010), although, ERβ status in breast cancer cells has been found to alter the miRNA-ome (Nassa et al., 2014).
A number of profiling studies have been done in breast cancer cell lines to assess the effect of estradiol on miRNA expression. The majority of these studies have been performed in MCF-7 cells with limited study in ZR-75.1 and T47D cells utilizing estradiol concentrations ranging from 1 to 10 nM with treatment times ranging from 0 to 72 hours.
Results from these studies have been inconsistent. An extensive microarray study in
MCF-7 and ZR-75.1 cells over 4 time points, found 230 miRNAs to be significantly regulated at at least one time point (Ferraro et al., 2012). Of these miRNAs, 110 were regulated in both cell lines and 52 were regulated in the same direction. The study in
T47D cells found no miRNAs to be significantly regulated 24 hours after estradiol exposure (Katchy et al., 2012). The inconsistencies in these studies could be due to differences in hormone deprivation prior to estradiol treatment, the length of estradiol treatment, and the methods used to normalize microarray and qPCR data. However,
49 some miRNAs have been shown to be consistently regulated by estradiol such as miR-
21 (Wickramasinghe et al., 2009; Tilghman et al., 2012).
Estradiol has also been shown to regulate components of the biogenesis pathway.
Regulation of biogenesis machinery by estrogen could alter global miRNA expression levels. Work by Yamagata and others suggested that Drosha could be inhibited by a
ERα/p68 complex, however, this work was recently retracted (Yamagata et al., 2009).
However, another group has shown that Drosha can be co-purified with ERα, suggesting that this regulation is possible (Paris et al., 2012). Dicer has been shown to be inducible by estradiol in MCF-7 cells (Bhat-Nakshatri et al., 2009) and Ago2 expression has been shown to be inhibited by estradiol exposure (Adams et al., 2009).
Ovary
Within the ovary, limited studies have been done looking at ER/miRNA interactions.
Similar to breast cancer, miR-206 expression was found to be negatively correlated with
ERα levels (Li et al., 2014). The majority of work done in ovarian tissue has focused on the role of miRNAs in estradiol synthesis and release. A study by Sirotkin and others examined the ability of 80 miRNAs to suppress or facilitate estradiol release from granulosa cells. Of the 80 tested, 51 miRNAs suppressed estradiol release and none enhanced it (Sirotkin et al., 2009). Studies looking at specific miRNAs have found miR-
133b is able to stimulate estradiol production through indirect regulation of the steroidogenic acute regulatory protein (StAR) and aromatase (Cyp19a1) (Dai et al.,
50 2013). Aromatase can also be positively regulated by miR-132 through suppression of
Nurr1 (Wu et al., 2015) and negatively regulated directly by miR-378 (Xu et al., 2011).
Uterine tissue
Within the uterus, studies of estrogens and miRNA have focused on endometrium and myometrium, as well as a variety of states including healthy cycling and ovariectomized tissues, endometriosis, and endometrial cancer. In endometrial cancer cell lines, the level of miR-222-3p was found to negatively correlate with ERα expression, similar to what had been observed in breast cancer studies (Liu et al., 2014). Seven studies have examined estradiol or ERα status-mediated miRNA expression. MiRNAs showing estrogen-dependent regulation include: miRs-20a, 21, & 26a (Pan et al., 2007; 2008), miRs-155, 181b, 204, 429 & 451 (Nothnick & Healy, 2010), miR-199a and 214 (Williams et al., 2012), and the let-7 family, miR-27a, 320 and 425 (Zhang et al., 2012). One microarray study comparing the high ERα/PR Ishikawa cell line to low ERα/PR KLE cells, found 126 miRNAs to be differentially regulated (Zhou et al., 2010). One study has examined the ability of estradiol to regulate the biogenesis pathway. Estradiol increased exportin-5 mRNA expression at 4 and 8 hours and protein expression 8 hours post- treatment (Nothnick et al., 2010). Dgcr8 mRNA levels were also increased 8 hours post injection.
Other tissues
Estrogens and their receptors have been shown to regulate miRNA expression in a variety of other tissues, including bone, colon, heart, liver and spleen. The brain will be
51 discussed separately. In healthy bone, 9 miRNAs were altered 4 weeks following OVX and hypothesized to play a role in estrogen deficiency-related osteoporosis (An et al.,
2014). In osteosarcoma, estradiol increased the production of miR-9, inhibiting cell proliferation, colony formation, and invasiveness while promoting apoptosis (Fang et al.,
2015). In the colon cancer cell line SW480, expression of ERβ in the presence of estradiol altered the expression of 27 miRNAs (24 downregulated, 3 upregulated)
(Edvardsson et al., 2013). In female cardiac fibroblasts, miRs-21, 24, 27a, 27b, 106a and 106b are inhibited by estradiol or loss of ERβ, whereas their regulation in males is mixed, suggesting a sex/hormone interaction in their regulation (Queirós et al., 2013). In the liver cancer cell line SNU-387, treatment with estradiol increase the expression of
25 and decreased 10 apoptosis-related miRNAs (Huang et al., 2015). In splenic lymphocytes isolated from placebo and E2 treated male mice, 4 miRNAs were found to be upregulated and 6 downregulated (Dai et al., 2008).
The nervous system
To date, studies of miRNA expression with respect to estrogen in the nervous system have been limited. In a study of miRNA involvement in neuroblastoma progression, miR-18a and 19a were shown to repress the expression of ERα (Lovén et al., 2010). A study looking at estrogen-dependent neuroprotection in motor neurons, found estrogen and WAY200070, an ERβ agonist, increased the expression of miR-7-1, 17 and 206, and overexpression of these miRNAs could promote neuroprotection (Chakrabarti et al.,
2014). The first microarray study profiling miRNA expression in the brain, examined interactions between age and estrogen in 3 and 18-month female 344 Fischer rats. This
52 study found 34 miRNAs to be altered by E2 status, 21 miRNAs altered by age, and 9 altered by estradiol in an age-dependent way (Rao et al., 2013). In follow up to this study, Rao and others examined the expression of the estrogen and age regulated miRNAs in aged females animals with varying lengths of hormone deprivation (1 to 12 weeks) (Rao et al., 2015). While the role of miRNAs in estrogen-dependent processes in the brain is beginning to be elucidated, there is still a large gap in knowledge.
Stress-microRNA connections
The effects on stress and GCs on miRNA expression have been examined in a number of tissues including the thymus (Belkaya et al., 2011) as well as serum (Duan et al.,
2016). With contrast to investigations with estrogen, a number of studies have examined the effects of stress on miRNA expression within the brain. MiRNA profiling following both acute and chronic stressors has been performed in a number of brain regions including the hippocampus and cerebellum, but the majority of studies have focused on the amygdala and PFC. These studies have illuminated the importance of both the length of the stressor (acute vs. chronic) as well as the region being studied. A study by Meerson and others addressed the importance of both factors by examining changes in miRNA expression following both acute and chronic restraint stress in the central amygdala and hippocampal CA1 (Meerson et al., 2010). Within the amygdala,
10 miRNAs were changed after acute stress and 28 following chronic stress. Only miR-
7a-1 was similarly affected at both times. By comparison, changes in the CA1 were often temporally and regionally distinct from the amygdala (i.e. miR-22 was upregulated in the amygdala following chronic stress, but downregulated in CA1). Another study
53 further illuminated these differences, as let-7a, miR-9, and miR-26a/b were upregulated in the frontal cortex following acute restraint stress, but not within the hippocampal formation (Rinaldi et al., 2010). Some miRNAs have been specifically studied for potential roles in the regulation of the HPA axis or in mediating neuronal responses to stress. These microRNAs include the mir-34 family, miR-18, miR-124, miR-135a, miR-
449a and others.
The miR-34 family has been implicated in the control of stress responses. MiR-34c has been found to be upregulated in the amygdala by both acute and chronic stress
(Haramati et al., 2011; Andolina et al., 2016), and miR-34a is upregulated in the amygdala following fear conditioning (Dias et al., 2014) and the medial PFC following acute stress (Andolina et al., 2016). Behaviourally, the miR-34 family may be important in the ability to mount an appropriate stress response. Overexpression of miR-34c in the amygdala has anxiolytic effects, and loss of amygdalar miR-34a inhibits fear memory consolidation (Haramati et al., 2011; Dias et al., 2014). A study of acute stress in a miR-
34 triple knockout (TKO) model found TKO mice exhibit reduced anxiety and increased fear extinction compared to wild type (WT) controls, suggesting a role for miR-34 in stress resilience (Andolina et al., 2016). The miR-34 family also appears to be the target of combined treatment with lithium and valproic acid (Zhou et al., 2009; Hunsberger et al., 2013). While the mechanism of miR-34 action is not fully understood, two targets for miR-34 have been identified, Crhr1 and Notch1. Both miR-34a and miR-34c have been shown to interact with the Crhr1 3’-UTR (Haramati et al., 2011; Shenoda et al., 2016), and miR-34a can interact with the Notch1 3’UTR (Dias et al., 2014).
54 Another miRNA implicated in stress responses is brain-specific miR-124. Following six weeks of chronic ultra-mild stress, miR-124 were significantly decreased within the hippocampus (Higuchi et al., 2016); however, an upregulation of miR-124 was found in the DG following forced swim stress (Mifsud et al., 2016). A single, two-hour restraint stress decreased amygdalar miR-124 (Mannironi et al., 2013). MiR-124 has been found to negatively regulate expression of both GR and MR through interactions with the 3’-
UTR (Vreugdenhil et al., 2009; Sõber et al., 2010). GR expression is also indirectly regulated by miR-18 (Vreugdenhil et al., 2009), and MR is directly regulated by miR-
135a (Sõber et al., 2010; Mannironi et al., 2013). Other miRNAs implicated in stress responses include miR-29c, miR-132, miR-134, miR-182, miR-183, as well as miR-449a through regulation of Crhr1 (Nemoto et al., 2013).
Hypothesis and Objectives
Overall, the hippocampus is a complex region within the brain responsible for a variety of response mechanisms. This literature review has highlighted three factors that can influence the function of the hippocampus; estrogens, stress and miRNAs. This thesis asks how these three factors might interplay to control hippocampal synaptic function.
We hypothesize that hormones that regulate hippocampal synaptic plasticity and function, such as gonadal and stress hormones, can regulate hippocampal miRNA levels. Changes in miRNA expression in response to hormonal changes could therefore play a role in hippocampal plasticity. To begin to address this hypothesis, this thesis explored the following three objectives.
55 Objective 1: Evaluate the expression of miRNAs in female mouse hippocampus in
the presence or absence of 17β-estradiol.
Objective 2: Evaluate the expression of miRNAs in male and female mouse
hippocampus in response to a short restraint stress in the presence or absence
of 17β-estradiol.
Objective 3: Determine a role for corticotropin release hormone (CRH) and
dexamethasone in the regulation of selected miRNAs.
56 CHAPTER 2: EFFECTS OF 17β-ESTRADIOL ON HIPPOCAMPAL MICRORNA
EXPRESSION IN THE FEMALE MOUSE
Introduction
Estrogens, in particular 17β-estradiol, have long been known to influence the structural and functional plasticity of the hippocampus. Estradiol increases dendritic spine and spine synapse density (Gould et al., 1990; Woolley, Gould, Frankfurt, et al., 1990;
Woolley & McEwen, 1992), neurogenesis (Tanapat et al., 1999; Barker & Galea, 2008),
LTP (Foy et al., 1999), and learning and memory (reviewed in Luine, 2014) in females.
The hippocampus appears to be directly targeted by estradiol, as all of the major estrogen receptors are present (Maggi et al., 1989; Shughrue & Merchenthaler, 2001;
Mitra et al., 2003; Brailoiu et al., 2007). Estrogens can also indirectly target the hippocampus via innervation from estrogen-sensitive subcortical regions including the basal forebrain cholinergic system, median raphe, and supramammillary area (Leranth et al. 2000, Prange-Kiel et al. 2004). Estrogens exert their effects through two major mechanisms, classical genomic signaling and rapid non-genomic signaling. Classical genomic signaling involves dimerization of ERα and/or ERβ, which can then act as a transcription factor through binding with ERE, such as in the case of BDNF (Sohrabji et al., 1995). Conversely, non-genomic signaling involves connections between the estrogen receptors and intracellular signaling cascades that can lead to changes in transcription and translation, as well as epigenetic changes (reviewed in Arevalo et al.,
2015; Frick, 2015). While many factors involved are known, our understanding of rapid estrogen signaling is still incomplete.
57 We hypothesize that rapid effects of estrogens on the hippocampus may be mediated, at least in part, via changes in miRNA expression. MiRNAs are short, 20 to 24 nucleotide, non-coding RNAs that have the ability to regulate gene expression post- transcriptionally. Following production of mature miRNA, they are incorporated in the miRISC. MiRISCs exert their effects on mRNAs through a number of different mechanisms including cleavage, translational repression or mRNA destabilization
(Filipowicz et al., 2008).
MiRNAs were first found in the brain by Lagos-Quintana and other and have since been hypothesized to be involved in a number of processes including neuronal development, dendritic spine development, axonal outgrowth and long-term plasticity (Lagos-Quintana et al., 2002; Schratt et al., 2006; Rajasethupathy et al., 2009; Magill et al., 2010).
Dysregulation of neuronal miRNAs has been implicated in a number of neurological disorders including autism spectrum disorder (ASD), depression and AD (Abu-Elneel et al., 2008; Smalheiser et al., 2012; Femminella et al., 2015).
Many studies have examined the regulation of miRNAs by estradiol and conversely the regulation of estradiol signaling by miRNAs, with the majority of studies performed in tissues and cell lines derived from the breast and uterus. The results of these studies have frequently been conflicting, potentially due to differences in methodology. For example, two studies using different ER+ breast cancer cell lines (MCF-7, T47D, and
ZR-75.1) found different miRNA expression profiles following estradiol treatment
(Ferraro et al., 2012, Katchy et al., 2012). Very little is currently known about estrogenic
58 regulation of miRNAs within the brain. In a study of the effects of estradiol on hippocampal miRNA expression in young and aged female rats, 34 miRNAs were found to be altered by estrogen regardless of age (Rao et al., 2013). This study, however, used three daily injections of a fairly high dose of estradiol (2.5µg/d; approximately
10 µg/kg) and so was probably not looking specifically at miRNAs that may be rapidly modulated by physiological changes in estradiol levels.
We hypothesized that estradiol can rapidly influence hippocampal miRNA expression.
To test this hypothesis we evaluated the expression of miRNAs and mRNA expression of miRNA biogenesis components in ovariectomized female mice in the first few hours after treatment with a low, physiological dose of estradiol.
Materials and Methods
Animals
Animals were 43 female CD1 mice (Mus musculus), purchased at ~2 months of age
(Charles River, QC). Mice were housed three per cage (with corncob bedding and environmental enrichment in polyethylene cages, 16 cm X 12 cm X 26 cm) and provided water and rodent chow (Teklad Global 14% protein rodent maintenance diet, Harlan
Teklad, WI) ad libitum. Mice were on a reverse 12-hour light/dark cycle, lights off at 7am.
The University of Guelph animal care and use committee approved all animal utilization protocols and ensured the guidelines of the Canadian Council on Animal Care were followed. All mice were ovariectomized (OVX). Briefly, mice were anesthetized using isoflurane (5% induction, 1-2% maintenance), and subcutaneously injected with an
59 analgesic and anti-inflammatory (Carpofen, 10 mg/kg). Their back was shaved and cleaned, and then a small incision was made along the midline. Incisions were made in the dorsal muscles overlying the ovaries through which the ovaries were drawn out. The uterus was then clamped just below the ovary, and the ovary was cut above the clamp.
The uterus was returned to the body cavity and the incision in the skin was closed with
1 or 2 surgical clips (9 mm wound clips). Mice were single housed following surgery and allowed to recover for 7 to 10 days before treatment.
Treatments
Mice were either left untreated (control) or subcutaneously injected with 3µg/kg estradiol suspended in sesame oil or sesame oil alone (vehicle), delivered at 1% body weight.
This estradiol dosage has been shown to produce plasma estradiol levels within the physiological range similar to those found at proestrus when estradiol levels peak during the estrous cycle (Scharfman et al., 2007; Phan et al., 2012). The injection site was sealed with instant drying glue to prevent leakage from the injection site. Mice were then euthanized by deep anesthesia with carbon dioxide followed by decapitation, 40 minutes, 6 hours or 12 hours following treatment. Time points were selected based on previous studies of estradiol on miRNA expression as well as knowledge that estradiol can alter dendritic structure by 40 minutes (Phan et al. 2012) The brains were extracted as quickly as possible and chilled (<1 minute), and the hippocampus was removed on ice and flash-frozen in liquid nitrogen. Final storage was at -80°C.
60 RNA Isolation & Quality
Total RNA was isolated from hippocampal samples using the miRNeasy Mini Kit
(Qiagen –Toronto, ON, Canada) following the manufacturer’s protocol including the optional on-column DNase digestion (RNase-free DNase –Qiagen). RNA was eluted in the provided RNase-free water and stored at -80°C. RNA sample quality was assessed by NanoDrop spectrophotometer ratios and RNA integrity analysis (Agilent Bioanalyzer
2100 –Advance Analysis Centre, University of Guelph). For samples undergoing next- generation sequencing, an RNA integrity number (RIN) of equal to or greater than 8.0 was necessary.
Small RNA Library Preparation & Next-Generation Sequencing (NGS)
Hippocampal total RNA from 6 hour estradiol-treated (n=3) and 6 hour vehicle-treated
(n=3) mice were sent to The Centre for Applied Genomics (TCAG) at The Hospital for
Sick Children (Toronto, ON, Canada) for small RNA library preparation and Illumina small RNA sequencing. Briefly, small RNA libraries were prepared using the NEBNext
Multiplex Small RNA Library Prep Set for Illumina (New England BioLabs –Whitby, ON).
Next-generation sequencing (NGS) was performed on an Illumina HiSeq 2500 system with single read sequences of 50 bases.
Bioinformatic Analysis
Raw reads were preprocessed for adapter trimming and quality control using trim_galore version 0.3.7. Adapter trimmings were performed with stringency 5, and low quality ends were trimmed if they fell below the minimum Phred (Q-score) of 20.
61 Preprocessed reads were analyzed using a stand-alone version of sRNAbench. The minimum read length parameter was set at the default setting of 15. Reads were first mapped to the mm9 genome and coordinates extracted. Reads were then classified as microRNA, RefSeq genes, RefSeq coding regions, and other libraries. Differential expression analysis of microRNAs was performed using an edgeR package with E2 as the baseline for comparison. Raw counts were normalized and expressed as a log2 fold change. Statistically significant changes in microRNA expression between treatments were those with a log2 fold change greater than 1 and a false discovery rate (FDR) corrected p-value < 0.05.
cDNA synthesis and qPCR
RNA for validation of microRNAs detected by NGS (all time points) was reverse transcribed using the qScript microRNA cDNA Synthesis Kit (Quanta Biosciences –
Gaithersburg, MD, USA), following the manufacturer’s protocol with the following addition. To prevent inhibition of qPCR by Poly(A) reaction components, 2ng of tRNA
(Sigma) were added to each reaction (per correspondence with Quanta). Quantitative
PCR was carried out in a BioRad CFX96TM (BioRad) instrument. Each sample was run in triplicate in 10 µl reaction volumes containing 5 µl of PerfeCTa SYBY Green Super
Mix (Quanta Biosciences), 0.2 µl of 10 µM universal primer (Quanta Biosciences), 0.2 µl of 10 µM microRNA specific primer (Quanta Biosciences), 2.6 µl of nuclease-free water, and 2 µl of cDNA. The qPCR program consisted of 95°C for 2 min, and 45 cycles of either 95°C for 10 sec and 60°C for 30 sec (miR-30d-5p) or 95°C for 10 sec, 60°C for 15 sec, and 70°C for 15 sec (miR-216b-5p, mir-217-5p), followed by a melt curve gradient.
62 All qPCR analysis for miRNA was normalized to miR-30d-5p expression. Its expression was found to be stable from both NGS and qPCR.
For analysis of mRNA, total RNA was reverse transcribed using qScript cDNA Supermix
(Quanta Biosciences), following the manufacturer’s protocol. Quantitative PCR was carried out in a BioRad CFX96TM (BioRad) instrument. Each sample was run in triplicate in 10 µl reaction volumes containing 5 µl of PerfeCTa SYBY Green Super Mix (Quanta
Biosciences), 0.2 µl (Hprt, Drosha, Dgcr8) or 0.3 µL (Dicer1, Syn2b) of 10 µM forward and reverse primers each, either 2.6 µL or 2.4 µL of nuclease-free water, and 2 µL of cDNA. The qPCR program consisted of 95°C for 2 min, and 40 cycles of either 95°C for
10 sec and 61°C for 30 sec (Dicer1, Syn2b), 95°C for 10 sec, 60°C for 15 sec, and 72°C for 15 sec (Hypoxanthine-guanine phosphoribosyl transferase, HPRT), or 95°C for 10 sec, 61.4°C for 15 sec, and 72°C for 15 sec (Drosha, Dgcr8) followed by a melt curve gradient.
Table 2.1. Table of qPCR primer sequences and sources. Primer Name Sequence (5’-3’) Source HPRT Forward TGACACTGGCAAAACAATGCA Gilsbach et al., 2006 HPRT Reverse GGTCCTTTTCACCAGCAAGCT Drosha Forward GGACCATCACGAAGGACACTT García-López et al., 2012 Drosha Reverse ATGCCCAGTTCCTCTGCTACCT Dgcr8 Forward CCTAAAGACAGTGAAGAACTGGAGTA García-López et al., 2012 Dgcr8 Reverse CATGGAGGATCTGATATGGAGAC Dicer1 Forward CAGCTCTGGACCATAACACAATTG Nothnick et al., 2010 Dicer1 Reverse AGGTCGCCCCTGATCTGAT Syn2b Forward CAGCAAGACCCCTCCTCAG Nesher et al., 2015 Syn2b Reverse AAGAAGCTTGGACTTGTTTTGG miR-30d-5p MIMAT0000245 (*) miR-216b-5p MIMAT0004959 (*) miR-217-5p MIMAT0000679 (*) (*) Commercial primers (Quanta Biosciences) used for qPCR of mature miRNAs along with universal PCR primer
63 Statistical Analysis
A two-way ANOVA (treatment x time) was performed for each microRNA or mRNA of interest. Data displaying inhomogeneity of variance was LN transformed prior to statistical analysis. A significance level of p < 0.05 was used for all statistical analysis.
The Tukey-Kramer method was used for all post-hoc analysis. All data are presented as mean ± SEM.
Predicted Target Cluster Analysis
The targets of miR-216b-5p and miR-217-5p were determined using TargetScanMouse v7.1 software (Agarwal et al. 2015). The resulting list of putative targets was analyzed in
Cytoscape v3.3.0 with the GluGO v.2.2.5 plugin application (Cline et al., 2007; Bindea et al., 2009). Within ClueGO, the target lists were clustered based on Mus musculus
“GO Biological Processes” with evidence restrictions set to “All_without_IEA” and a required pathway significance of p < 0.05.
Results
MicroRNA detection
To identify the microRNA population in samples from 6 hour vehicle and estradiol- treated animals, sequencing of small RNAs was performed on total RNA extracted from the hippocampus, generating an average of 20.3 million reads from vehicle samples and 20.1 million reads from E2 samples. Reads were trimmed and mapped to the mm9 genome and coordinates extracted. Reads were aligned to known sequences for mature microRNAs (miRBase v21), RefSeq genes, tRNA, RFam, and other classes of
64 RNAs. Of reads mapped to the genome, 60-67% of reads mapped to known mature microRNAs (average of 63.97%, shown in Figure 2.1 A). Consistent with a microRNA population, read lengths clustered around 20 to 22 nucleotides (Figure 2.1 B). This pool of miR represented 945 distinct miRNAs within these samples. The expression of microRNAs was variable with expression levels varying from <1 count per million (CPM) to over 170,000 CPM from the most abundantly expressed miRNA. A total of 695 were expressed at 1 CPM or greater.
Following differential expression analysis, 4 miRNAs were found to be significantly different in vehicle-treated mice relative to E2-treated mice with all 4 more abundantly expressed in vehicle-treated mice (false discovery rate (FDR)-corrected p-value < 0.05); mmu-miR-217-5p (log2 FC 2.89, FDR p-value 0.00026), mmu-miR-3547-3p (log2 FC
3.18, FDR p-value 0.0039), mmu-mir-216b-5p (log2 FC 2.42, FDR p-value 0.0039), and mmu-miR-216a-3p (log2 FC 3.80, FDR p-value 0.0041).
65 A 63.97% Mature miRs 0.13% Precursor 18.26% Refseq 0.32% tRNA 1.53% Rfam 2.54% chrM 0.65% MtrRNA 5.59% Nuc45A 7.01% Unmapped
B 5×106
4×106 Vehicle 3×106 Estradiol
2×106 Read Count
1×106
0
15 16 17 18 19 20 21 22 23 24 25 Read Length
Figure 2.1. –Distribution of Sequencing reads. A. The classification distribution of next-generation sequencing reads mapped to the genome, pooled from both vehicle and estradiol-treated samples. B. The read length distribution of classified microRNA in vehicle and estradiol-treated samples. No significant differences existed between sample groups (n = 3 for each group).
66 4
2
0
-2 Differential expression of microRNA Vehicle (+) relative to Estradiol (-) (Log2 Fold Change) Fold (Log2 (-) Estradiol to relative (+) Vehicle -4 MicroRNAs
Figure 2.2 – MicroRNA Differential Expression Analysis. Only miRs with expression greater than 1 CPM are depicted. MicroRNAs are ordered from highest to lowest expression.
Quantitative PCR validation of microRNAs
Detection of the differentially expressed microRNAs with quantitative PCR (qPCR) was attempted. Due to its low expression level (CPM ~ 1), mmu-miR-216a-3p could not be reliably detected via qPCR. Mmu-miR-3547-3p, a predicted miRtron, could not be reliably detected as well. Both mmu-miR-216b-5p and mmu-miR-217-5p were detected and the qPCR study was expanded to include untreated control samples as well as two additional time points (40 minutes and 12 hours following treatment). The data is presented in Figure 2.3. For mmu-miR-216b, two-way ANOVA found a significant effect of treatment (p=0.0284, F(2,33)=3.975), but not time (p=0.7525, F(2,33)=0.2868) or an interaction effect (p=0.1580, F(4,33)=1.772). At the 6 hour time point, multiple comparisons showed a significant difference between vehicle and E2-treated animals
(p=0.0364) and a trend towards a difference between control and vehicle-treated
67 animals (p=0.0741). At 40 minutes, multiple comparisons showed a trend towards a significant difference between vehicle and E2-treated animals (p=0.0664).
A miR-216b-5p 4 *
3
2
Control 1 Relative Expression Vehicle Estradiol 0 40 minutes 6 hours 12 hours
B miR-217-5p 4 *
3 *
2
Control 1 Relative Expression Vehicle Estradiol 0 40 minutes 6 hours 12 hours
Figure 2.3. –Quantitative PCR (qPCR) for mature microRNAs miR-216b-5p (A) and miR-217-5p (B). Expression relative to untreated ovariectomized controls. Expression was normalized to miR-30d. Statistical significance of (*) indicates p < 0.05 between indicated groups. n = 3 for Control, 5-6 for Vehicle & Estradiol
For mmu-miR-217, two-way ANOVA found a significant effect of treatment (p=0.0251,
F(2,33)=4.13), but not time (p=0.7770, F(2,33)=0.2542) or an interaction effect
(p=0.1236, F(4,33)=1.96). At both 40 minutes and 6 hours, multiple comparisons
68 showed a significant difference between vehicle and E2-treated animals (p=0.0302 for
40 minutes and p=0.0215 for 6 hours). Attempts were made to detect primary transcripts for miR-216b-5p and miR-217-5p, but expression could not be reliably detected.
Quantitative PCR of miRNA biogenesis components
Three members of the canonical miRNA biogenesis pathway were examined by qPCR,
Drosha, Dgcr8, and Dicer1. The data is presented in Figure 2.4. For Drosha, two-way
ANOVA found no significant effect of treatment (p=0.9180, F(2,34)=0.0858), time
(p=0.7988, F(2,34)=0.2261), or an interaction effect (p=0.7934, F(4,34)=0.4195). For
Dgrc8, two-way ANOVA found no significant effect of treatment (p=0.2026,
F(2,34)=1.674), time (p=0.3080, F(2,34)=1.219), or an interaction effect (p=0.6905,
F(4,34)=0.5638). For Dicer1, two-way ANOVA found no significant effect of treatment
(p=0.9987, F(2,34)=0.001299), time (p=0.6306, F(2,34)=0.4673), or an interaction effect
(p=0.5999, F(4,34)=0.6962).
69 A Drosha 2.0
1.5
1.0
Control 0.5
Relative Expression Vehicle
0.0 Estradiol 40 minutes 6 hours 12 hours
B Dgcr8 2.0
1.5
1.0
Control 0.5
Relative Expression Vehicle
0.0 Estradiol 40 minutes 6 hours 12 hours
C Dicer1 2.0
1.5
1.0
Control 0.5
Relative Expression Vehicle
0.0 Estradiol 40 minutes 6 hours 12 hours
Figure 2.4. –Quantitative PCR (qPCR) for components of the microRNA biogenesis pathway. Expression relative to untreated ovariectomized controls. Expression was normalized to HPRT. n = 3 for Control, 5-6 for Vehicle & Estradiol
70 Prediction miRNA Target Cluster Analysis
To determine a potential role for miR-216b and miR-217 within the hippocampus, functional target cluster analysis was performed to identify over-represented pathways.
For both miRNAs, important neuronal processes were identified, positive regulation of synapse assembly for miR-216b, and neurotransmitter transport & regulation of synapse structure or activity for miR-217.
A Cell division Positive regulation of synapse assembly Kidney development Columnar/cubodial epithelial cell differentiation Cell junction organization miR-216b Regulation of macroautophagy Regulation of actin filament depolymerization Pattern recognition receptor signaling pathway Fibroblast growth factor receptor signaling pathway Chromatin assembly Cellular polysaccharide metabolic process Embyronic skeletal system development Histone H3-K4 methylation B Neurotransmitter transport Regulation of cellular response to growth factor stimulus DNA replication Pallium development miR-217 Regulation of synapse structure or activity Protein modification by small protein removal Regulation of fibroblast proliferation Protein deacylation Protein methylation
Figure 2.5. – Functional clusters of predicted microRNA targets. Functional clustering of predicted microRNA targets of miR-216b (A) and miR-217 (B), as clustered by Cytoscape and ClueGO analysis with pathway significant of p < 0.05. The size of each group is proportional to the number of clustered GO:Biological Processes terms within that group.
71 Detection of Predicted Targets
Following predicted target cluster analysis, genes of interest were determined from neuronally significant terms. Synapsin2 (Syn2) is a gene potentially targeted by miR-
217, involved in neurotransmitter transport with two isoforms, Syn2a and Syn2b. RT- qPCR for Syn2b showed no changes in mRNA expression with time (p=0.6071,
F(2,34)=0.5064) or treatment (p=0.6112, F(2,34)=0.4996).
Syn2b
1.5
1.0
0.5 Control
Relative Expression Vehicle
0.0 Estradiol 40 minutes 6 hours 12 hours Figure 2.6. Quantitative PCR (qPCR) for potential miRNA target synapsin 2b. Expression relative to untreated ovariectomized controls and normalized to HPRT. n = 3 for Control, 5-6 for Vehicle & Estradiol
Discussion
MicroRNAs are important regulators of gene expression, and have been implicated in a number of neuronal processes in both normal and dysfunctional states. Regulation of miRNA expression by estradiol has also been examined in a number of hormonally responsive tissues, however, our knowledge of the effects of estrogen on miRNA expression in the brain is much more limited. By utilizing next-generation sequencing
72 (NGS) of small RNAs, we can examine the hippocampal complement of miRNAs as well as any changes in expression following estradiol treatment. Approximately 60% of annotated reads mapped to known miRNA sequences. This is consistent with other
NGS studies performed in mice (Juhila et al., 2011). Within this study, 945 distinct mature miRNAs were detected at widely varying levels of expression. Consistent with previous microarray and NGS studies within the mouse central nervous system, miR-9, miR-124a, miR-125b, miR-127, miR-128, and members of the let-7 family were highly expressed (Bak et al., 2008; Juhila et al., 2011). Many of these brain-enriched miRNAs have been implicated in a number of important neuronal functions including miR-124 in axonal and dendritic development and branching (Baudet et al., 2011; Franke et al.,
2012).
Differential expression analysis was performed using an edgeR package within the sRNAbench program. Four miRNAs were determined as differentially expressed with expression higher in vehicle-treated animals than estradiol-treated animals: miR-216a-
3p, miR-216b-5p, miR-217-5p, and miR-3547-3p. Interestingly, three of these miRNAs are clustered within a 17.6-kb segment on chromosome 11. Furthermore, miR-216a and miR-217 are both located within intron 2 of the long non-coding RNA (lncRNA)
Gm12082-001. While it is likely that miR-216a and miR-217 are located within the same primary transcript, it is unknown if miR-216b is also a member. Based on the expression of the mature microRNAs and relative closeness of the transcripts within the genome, it is possible they are transcribed together. Attempts to detect primary transcripts for either miR-216b or miR-217 using qPCR were unsuccessful. This could be in part due
73 to relatively low expression of the mature miRNAs. Missing from the differential expression analysis was comparisons to untreated control animals. It is possible that some miRNAs may differ from control following both treatments.
Overall the microRNA-ome appears fairly stable with only 53 mature miRNAs of 695 with a CPM greater than 1 showing a log2 fold change ± 1. Methodology could play a role in this result. Most previous studies examining estrogen regulation of miRNAs have been performed in cell lines, which may not accurately model responses expected in vivo. Compared to the previous study conducted in the hippocampus by Rao and others
(Rao et al., 2013), two considerations must be taken. First, Rao was primarily focused on microRNAs that were altered by estradiol dependent upon age (3 months versus 18 months). However, Rao did find 34 miRNAs with high signal intensity to be altered by estradiol treatment regardless of age. Second, the dosing regimens were different. The
Rao study used a dose approximately equivalent to 10µg/kg each day for three days, compared to a single 3µg/kg dose. Rao’s dosing produced plasma estradiol concentrations greater than 70 pg/mL, 24 hours after the final injection. This level is higher than that seen at the estrous cycle peak in proestrus morning (40-50 pg/mL in rats (Smith et al., 1975), ~35 pg/mL in mice (Nilsson et al., 2015)). Given the high estradiol level 24 hours after the final injection, circulating levels of estradiol would be expected to be much higher just following injections. Supraphysiological doses of estradiol can be non-specific, and may act on other steroid receptors, such as the progesterone receptor. For example, high doses of estradiol can elicit progesterone- dependent reproductive behaviours in female rats (Parsons et al., 1984). By comparison,
74 our single dose produces a serum estradiol level of around 60 pg/mL 2 hours following injection in rats (Scharfman et al., 2007) and is much more similar to physiological levels. This difference in dosing could explain the differences in miRNA expression found in Rao’s study and ours. Rao’s study also divided the hippocampus into dorsal and ventral regions and found different patterns of miRNA expression. It is possible that some miRNAs may display a more regional distribution along either the dorsal-ventral pole or within certain cell types (i.e. dentate granule neurons versus pyramidal neurons).
Future studies could examine the regional expression of miRNAs identified in this study to determine if their expression is regionally limited or expressed across the hippocampus.
Another important consideration is the presence of isomiRs. IsomiRs are non-canonical miRNAs that differ from the reference miRNA sequence. IsomiRs can involve additions or deletions at either the 5’ or 3’ prime end, as well as changes in internal nucleotide composition. Importantly, isomiRs may not have the same affinity for certain transcripts or could have an entirely different seed region and interact with a different set of 3’-
UTR’s than the canonical sequence. Preliminary study of miRNAs with larger fold changes (significant or not) did not suggest an effect of treatment on isomiR complements. However, in many cases, the predominant isomiR was not the canonical sequence. Any future research should consider what effect different isomiRs might have.
Expanding the qPCR analysis to look at control animals as well as multiple time points suggests a trend towards upregulation of miR-216b and miR-217 following injection,
75 and that estradiol can oppose this increase. This is opposite to the originally expected result that vehicle-treated animals would be more similar to untreated controls, and that estradiol would downregulate miRNA expression. While the difference between control and vehicle-treated animals did not reach significance, this could be due to the difference in animal number reducing the power of the statistical tests used. These results open up the possibility of another factor regulating miRNA expression in this study. Two possible factors could be at play here. First, while vehicles are selected with the hope that they will not affect the results, vehicles are rarely truly inert. Previous studies using sesame oil as a vehicle have found it to affect behaviour (Curtis & Wang,
2005; Clipperton-Allen et al., 2010, 2011). Second, while steps are taken to limit the exposure to stress during the procedure, injections are invariably stressful. It is possible that estradiol is acting to counteract the effects of stress on expression of miR-216b and miR-217. Stress could also explain the degree of variability of miRNA expression between samples within each treatment group.
To date, very little is known about what role miR-216b and miR-217 could have in the hippocampus. Within the current literature, most research on miR-216b and miR-217 has focused on their roles in a variety of cancers including pancreatic, hepatocellular, colorectal, osteosarcoma, ovarian and breast cancer. Both miRNAs are believed to act as tumour suppressors, and a growing body of research has focused on their roles in pancreatic cancer progression (Rachagani et al., 2015; Visani et al., 2015; Azevedo-
Pouly et al., 2016). In addition, Azevdeo-Pouly and others found that germ line deletion of the miR-216/miR-217 cluster was embryonic lethal, suggesting either an important
76 role for this miRNA cluster or the lncRNA host gene in development (Azevedo-Pouly et al., 2016). One study looking at receptor status in breast cancer identified miR-217 as one of 6 miRNAs that together could predict ER status (Lowery et al., 2009).
Interestingly, TargetScan predictions suggest Esr1 (ERα) is a predicted target of both miR-216b and miR-217. In epithelial ovarian cancer, miR-217 levels are inversely correlated with cancer progression (Li et al., 2016). With respect to the brain, miR-216b has been found to negatively regulate the brain-specific tyrosine receptor kinase B
(TrkB)-T-Shc transcript in SH-SY5Y cells (Wong, 2014). This truncated TrkB receptor may act as a negative regulator of TrkB signaling as it can bind BDNF, but is not phosphorylated (Stoilov et al., 2002). Changes in the balance of TrkB receptor isoforms could influence BDNF signaling.
To investigate possible biological roles of miR-216b and miR-217 related to the CNS, predicted target mRNAs were clustered using Cytoscape and ClueGO. While a number of the enriched pathways are not pertinent to neuronal function (i.e. kidney development), both miRNAs can influence important neuronal processes including positive regulation of synapse assembly (miR-216b), neurotransmitter transport (miR-
217), and regulation of synapse structure or activity (miR-217). Possible miR-216b targets include the neurotrophin-3 receptor (Ntrk3) involved in neuronal differentiation, axon & dendritic outgrowth and plasticity (Ramos-Languren & Escobar, 2013), the low- density lipoprotein receptor-related protein (Lrp8) also known as ApoE receptor 2 involved in reelin signalling (Hirota et al., 2015), septin 7 (Sept7), involved in dendrite and axon development (Ageta-Ishihara et al., 2013), and synapse-associated protein 97
77 (Sap97/Dlg1), involved in trafficking of glutamate receptors (Howard et al., 2010).
Possible miR-217 targets include brain angiogenesis inhibitor 3 (Adgrb3/Bai3), involved in dendritic arborisation (Lanoue et al., 2013), the ionotropic kainate receptor 2 (Grik2), a subtype of the glutamate receptor, the GABA transporter (Slc6a1), responsible for uptake of GABA from the extracellular environment, and synapsin 2 (Syn2), involved in synaptic vesicle trafficking (Bogen et al., 2011).
Further studies will be required to determine if miR-216b or miR-217 can directly regulate any of the above putative targets. Examination of synapsin 2b mRNA levels by qPCR showed no changes in expression between treatments or over time, however, this result provides no conclusive evidence for or against miR-217 regulation of Syn2b for a variety of reasons. It is possible that miR-217 levels are not high enough throughout the hippocampus to lead to regulation. If regulation is possible, the miR-
217/RISC may act to inhibit translation with no effect on mRNA levels. Within mammalian systems, only Ago2 has slicer activity so cleavage of target mRNAs is not the main mechanism (Liu, 2004; Meister et al., 2004). Further work to examine protein levels for Syn2 would help in determining which outcome is occurring. It is also possible that expression of miR-217 is restricted to a certain region within the hippocampus.
Examination of levels of Syn2 across the entire hippocampus may not provide an accurate representation of its regulation. Analysis of Syn2 protein expression by western blotting or proteomics will be essential to determine a role for miR-217 is the regulation of Syn2 in the hippocampus.
78 In conclusion, the results of this study demonstrate that miR-216b-5p and miR-217-5p are upregulated following vehicle injection and that this increase can be prevented by estradiol. The following chapter will address potential factors responsible for this pattern of expression.
79 CHAPTER 3: EFFECTS OF 17β-ESTRADIOL AND HANDLING STRESS ON
HIPPOCAMPAL MICRORNA EXPRESSION IN MALE AND FEMALE MICE
Introduction
In the previous study, small RNA sequencing identified 4 miRNAs that were differentially expressed between vehicle and estradiol-treated females. Extension of the study suggested that estradiol-treated animals were more similar to untreated controls than the vehicle-treated mice were; a result that indicated the vehicle injection mediated the changes in miR-216b and miR-217. One possible explanation is an effect of stress due to handling and injection. While precautions are taken to reduce stress, these procedures could induce a stress response in the mice. A number of studies have examined miRNA expression following both acute and chronic stress with most studies looking in the prefrontal cortex and amygdala, rather than the hippocampus. This is of importance as regional and temporal differences in miRNA expression have been found in response to stress (Meerson et al., 2010; Rinaldi et al., 2010). Therefore, the effect of our handling procedure on miRNA expression in mouse hippocampus was examined.
Functionally, stress, like estrogen, is an important mediator of hippocampal activity
(reviewed in McEwen 2015). Studies of neuronal responses to stress have primarily been performed in male rats. However, this does not take into account the differences in reactivity of the male and female stress response. Females have a higher total corticosterone at baseline, and responded faster and with a greater rise in corticosterone than males (Iwasaki-Sekino et al., 2009; Goel & Bale, 2010). Studies that
80 have looked at responses in both sexes have found important differences. Chronic stress paradigms or chronic treatment with corticosterone leads to dendritic retraction of
CA3 neurons in males (Woolley, Gould, & McEwen, 1990; Watanabe et al., 1992), but not in females (Galea et al., 1997; McLaughlin et al., 2010). In contrast to chronic stress, acute stress leads to increased dendritic spine density in males and decreased spine density in females (Shors et al., 2001). Gonadal steroids are believed to play an important role in these sex differences, with estrogens generally activating HPA activity and androgens suppressing activity (Goel et al., 2011). For this reason, it is important to consider any potential effects of stress on miRNA expression in both males and females, as responses may not be the same.
We hypothesized that stress and estradiol will interact to regulate microRNA expression is a sex-dependent fashion. To test this hypothesis we evaluated the expression of miRNAs in GDX male and female mice following a short handling stress with or without physiological estradiol treatment.
Materials and Methods
Animals
Animals were 24 female and 23 male CD1 mice (Mus musculus), purchased at ~2 months of age (Charles River, QC). Mice were housed three per cage (with corncob bedding and environmental enrichment in polyethylene cages, 16 cm X 12 cm X 26 cm) and provided water and rodent chow (Teklad Global 14% protein rodent maintenance diet, Harlan Teklad, WI) ad libitum. Mice were on a reverse 12-hour light/dark cycle,
81 lights off at 7am. The University of Guelph animal care and use committee approved all animal utilization protocols and ensured the guidelines of the Canadian Council on
Animal Care were followed. All mice were either ovariectomized (OVX) or castrated
(CAST). Briefly, for ovariectomy, mice were anesthetized using isoflurane (5% induction,
1-2% maintenance), and subcutaneously injected with an analgesic and anti- inflammatory (Carpofen, 10 mg/kg). Their back was shaved and cleaned, and then a small incision was made along the midline. Incisions were made in the dorsal muscles overlying the ovaries through which the ovaries were drawn out. The uterus was then clamped just below the ovary, and the ovary was cut above the clamp. The uterus was returned to the body cavity and the incision in the skin was closed with 1 or 2 surgical clips (9 mm wound clips). For castration, mice were similarly anesthetized using isoflurane, and received an analgesic and anti-inflammatory. The scrotum was shaved and cleaned, and then a small midline incision was made in the skin. Another incision was made in the tunica, and each testis was removed from the sac one at a time. The vas deferens and spermatic cord were then cauterized to allow for testis removal. The procedure was repeated for the second testis. The incision in the skin was close with 1 or 2 surgical clips. All mice were single housed following surgery and allowed to recover for 7 to 10 days before treatment.
Treatments
Animals were placed into one of four treatment groups, Control, Handled, handled with vehicle injection (Vehicle) or handled with estradiol injection (Estradiol) (n = 5-6 per group). Control animals were left untreated and unhandled. Handled animals were
82 weighed and restrained as if they were to receive an injection, but no injection was given to model the stress of handling. Vehicle animals were weighed, handled, and received a subcutaneous injection of sesame oil. Estradiol animals were weighed, handled, and received a subcutaneous injection of 3µg/kg estradiol suspended in sesame oil (delivered at 1% body weight). The injection site was sealed with instant drying glue to prevent leakage. Males were also injected with estradiol instead of testosterone or dihydrotestosterone to maintain consistency between the treatments.
Furthermore, some of the actions of testosterone within the brain are due to local aromatization to estradiol, especially during development (reviewed in McCarthy 2008).
Six hours following treatment, animals were euthanized by deeply anaesthetizing with carbon dioxide followed by decapitation. The brains were extracted as quickly as possible, chilled, and the hippocampi were rapidly removed. Tissues were flash frozen in liquid nitrogen and final storage was at -80°C.
RNA Isolation & Quality
Total RNA was isolated from hippocampal samples using the miRNeasy Mini Kit
(Qiagen –Toronto, ON, Canada) following the manufacturer’s protocol including the optional on-column DNase digestion (RNase-free DNase –Qiagen). RNA was eluted in the provided RNase-free water and stored at -80°C. RNA sample quality was assessed by NanoDrop spectrophotometer ratios and RNA integrity analysis (Agilent Bioanalyzer
2100 –Advance Analysis Centre, University of Guelph). For samples undergoing next- generation sequencing, a RIN greater than 8.0 was necessary.
83 Small Library Preparation & Next-Generation Sequencing (NGS)
Sixteen hippocampal total RNA samples (n=1 for female treatment groups, n=3 for male treatment groups) were sent to The Centre for Applied Genomics at the Hospital for
Sick Children (Toronto, ON, Canada) for small RNA library preparation and Illumina small RNA sequencing. Small RNA libraries were prepared using the NEBNext
Multiplex Small RNA Library Prep Set for Illumina (New England BioLabs –Whitby, ON) following the manufacturers protocol. Next-generation sequencing (NGS) was performed on an Illumina HiSeq 2500 system with single read sequences of 50 bases.
Bioinformatic Analysis
Raw reads were preprocessed for adapter trimming and quality control using trim-galore version 0.4.1. Adapter trimming was performed with stringency 5, and low quality reads were removed if they fell below the minimum Phred score of 20. Preprocessed reads were analyzed using a stand-alone version of sRNAbench. Minimum read length was set at the default of 15. Analysis was performed in library mapping mode. Reads were first mapped to miRNA sequences, then remaining reads were mapped to other sequence libraries (order: RefSeq cds sequences, tRNA, rRNA, mitochondrial RNA,
Rfam and RefSeq genes). Read counts for each miRNA were compiled and normalized using DESeq. For the male samples, differential expression analysis was performed using edgeR with control as baseline. Only miRNAs with at least 2 reads counts in all samples were included in this analysis. For the female samples, the tissue analyzed from 1 mouse did not allow for differential expression analysis to be performed.
Differences in miRNA expression were detected using the DESeq-normalized counts.
84 Only miRNAs with at least 10 normalized read counts in all samples were included in this analysis.
cDNA Synthesis and qPCR
For validation of miRNAs detected by NGS, total RNA was reverse transcribed using the qScript microRNA cDNA Synthesis Kit (Quant Biosciences –Gaithersburg, MD,
USA), following the manufacturer’s protocol with the following addition. To prevent inhibition of qPCR by Poly(A) reaction components, 2ng of tRNA (Sigma) were added to each reaction (per correspondence with Quanta). Quantitative PCR (qPCR) was carried out in a BioRad CFX96TM (BioRad) instrument. Each sample was run in triplicate in 10µL reaction volumes containing 5µL of PerfeCTa SYBR Green Supermix (Quanta
Biosciences), 0.2µL of 10µM universal primer (Quanta Biosciences), 0.2µL of 10µM microRNA-specific primer (Quanta Biosciences, Table 3.1.), 2.6µL of nuclease-free water, and 2µL of cDNA template (4ng/µL). The qPCR program consisted of 95°C for 2 min, and 40 cycles of either 95°C for 10 sec and 60°C for 30 sec (miR-30d-5p, miR-34b-
3p, miR-148a-3p, miR-200a-3p, miR-448-3p, and miR-1298-5p) or 95°C for 10 sec and
61°C for 30 sec (miR-34c-5p and miR-219a-2-3p), followed by a melt curve gradient.
For analysis of mRNA transcripts, total RNA was reverse transcribed using qScript cDNA Supermix (Quanta Biosciences), following the manufacturer’s protocol.
Quantitative PCR was carried out in a BioRad CFX96TM (BioRad) instrument. Each sample was run in triplicate in 10µL reaction volumes containing 5µL of PerfeCTa SYBR
Green Supermix (Quanta Biosciences), 0.3µL of each 10µM mRNA-specific primer (5’
85 and 3’, Table 3.1.), 2.4µL of nuclease-free water, and 2µL of cDNA template (4ng/µL).
The qPCR program consisted of 95°C for 2 min, and 40 cycles of either 95°C for 15 sec and 60°C for 30 sec (GR and MR, designed using Primer3 (Untergasser et al., 2012)) or
95°C for 15 sec, 60°C for 15 sec, and 72°C for 15 sec (Hprt), followed by a melt curve gradient.
Table 3.1. Primer Name Sequence (5’ – 3’) Source HPRT Forward TGACACTGGCAAAACAATGCA Gilsbach et al., 2006 HPRT Reverse GGTCCTTTTCACCAGCAAGCT GR Forward CAATAGTTCCTGCCGCGCTG Designed using Primer3 GR Reverse GGCGCCCACCTAACATGTTG MR Forward CAAGGTCACACAGCCCCGTA Designed using Primer3 MR Reverse GAGGAGCGCAGAGGGACATT miR-30d-5p MIMAT0000245 (*) miR-34b-3p MIMAT0004581 (*) miR-34c-5p MIMAT0000686 (*) miR-148a-3p MIMAT0000243 (*) miR-200a-3p MIMAT0000682 (*) miR-204-5p MIMAT0000265 (*) miR-219a-2-3p MIMAT0004675 (*) miR-448-3p MIMAT0001532 (*) miR-1298-5p MIMAT0005800 (*) (*) Commercial primers (Quanta Biosciences) used for qPCR of mature miRNAs along with universal PCR primer
Statistical Analysis
A two-way ANOVA (treatment x sex) was performed for each microRNA and mRNA of interest. Data displaying inhomogeneity of variance was LN transformed prior to statistical analysis. A significance level of p < 0.05 was used for all statistical analysis.
The Tukey-Kramer method (treatment comparisons) or Holm-Sidak method (sex comparisons) was used for all post-hoc analysis. All data are presented as mean ± SEM.
86 Results
MicroRNA Detection
To identify miRNAs, small RNA sequencing was performed on total RNA extracted from the hippocampus. Reads were trimmed and mapped to the mm9 genome and coordinates extracted. Following quality control, an average of 21.3 million reads for females (n=4) and an average of 20.6 million reads for males (n=12) were used for analysis. Reads were aligned to known sequences for mature and hairpin miRNA sequences (miRBase v21), RefSeq genes, tRNA, RRNA, Rfam sequences and mitochondrial sequences. Of reads mapped to the genome, 48-55% of reads mapped to known mature microRNAs with significantly greater percentage in females compared to male samples (Figure 3.1; two-way ANOVA (RNA type x sex) showed a significant effect of RNA (p < 0.0001, (F(8,126)=4244) and an interaction effect (p < 0.0001,
F(8,126)=15.29), and post-hoc analysis showed a significant difference between male and female microRNA reads (p < 0.0001)). In males, more reads mapped to gene coding regions (6.43% compared to 5.49%), rRNA sequences (11.10% compared to
9.85%), and mm9 genes (18.11% compared to 16.95%). On average, 1172 distinct miRNA species were detected in female samples and 1166 distinct miRNA species were detected in males.
87 A
54.02% Mature Reads 0.09% Hairpin Reads 5.49% Gene Coding Regions Females 2.01% tRNA Sequences Reads: 9.85% rRNA Sequences 21,342,413 4.14% Mitochondrial Sequences 0.15% Rfam Sequences 16.95% mm9 Genes 7.29% Unmapped Reads
B 49.02% Mature Reads 0.10% Hairpin Reads 6.43% Gene Coding Regions Males 2.54% tRNA Sequences Reads: 11.10% rRNA Sequences 20,635,831 4.96% Mitochondrial Sequences 0.17% Rfam Sequences 18.11% mm9 Genes 7.57% Unmapped Reads
Figure 3.1. Read Distributions. The percentage of reads mapped to different RNA families following annotation in female samples (A, n=4) and males (B, n=12).
88 Differential Expression
For females, differential expression analysis was done by looking at log2 fold change
(Log2 FC) between treatment (handled, vehicle, estradiol) and control. A total of 606 miRNAs met the minimum expression requirements for analysis. A threshold of +/- 1 was set. In the handled female (Figure 3.2 A), 33 miRNAs were downregulated and 16 were upregulated. In the vehicle-treated female (Figure 3.2 B), 16 miRNAs were downregulated and 11 were upregulated. In the estradiol-treated female (Figure 3.2 C),
31 miRNAs were downregulated and 18 were upregulated. Eighteen miRNAs were consistently regulated in all three treatments with 10 downregulated and 8 upregulated.
From these differentially expressed miRNAs, 8 were chosen for follow-up via qPCR
(miR-34b-3p, miR-34c-5p, miR-148a-3p, miR-200a-3p, miR-204-5p, miR-219a-2-3p, miR-448-3p, and miR-1298-5p).
In males, differential expression analysis was performed using EdgeR software. A total of 807 miRNAs were included in the analysis. In estradiol-treated males (Figure 3.3. C), miR-217-5p was significantly downregulated (log2 FC -1.536, FDR p-value = 0.0064). In handled and vehicle-treated males (Figure 3.3 A-B, respectively), no miRNAs were significantly changed from untreated controls.
89 A 4
2
0
-2
-4 Differential expression of microRNA
-6 Handled (+) relative to Control (-) (Log2 Fold Change)
B 4
2
0
-2
-4 Differential expression of microRNA
-6 Vehicle (+) relative to Control (-) (Log2 Fold Change) Fold (Log2 (-) Control to relative (+) Vehicle C 4
2
0
-2
-4 Differential expression of microRNA
-6
Estradiol (+) relative to Control (-) (Log2 Fold Change) Figure 3.2. MicroRNA differential expression analysis in females. Differential expression analysis of miRNA populations in Handled and Control (A), Vehicle and Control (B), and Estradiol and Control (C). Each point represents the fold change of the individual miRNAs listed from highest to lowest expression in Control.
90 A 4
2
0
-2
-4 Differential expression of microRNA
-6 Handled (+) relative to Control (-) (Log2 Fold Change) B 4
2
0
-2
-4 Differential expression of microRNA
-6 Vehicle (+) relative to Control (-) (Log2 Fold Change) Fold (Log2 (-) Control to relative (+) Vehicle C 4
2
0
-2
-4 Differential expression of microRNA
-6
Estradiol (+) relative to Control (-) (Log2 Fold Change) Figure 3.3. MicroRNA differential expression in males. Differential expression analysis of miRNA populations in Handled and Control (A), Vehicle and Control (B), and Estradiol and Control (C). Each point represents the fold change of an individual miRNA listed from highest to lowest expression in Control.
91 A miR-34b-3p 1.5 *
1.0
0.5 Female Relative Expression Male 0.0 Control Handled Vehicle Estradiol
B miR-34c-5p 1.5
1.0
0.5 Female Relative Expression Male 0.0 Control Handled Vehicle Estradiol
Figure 3.4. Quantitative PCR (qPCR) validation of mature microRNAs. Quantitative PCR validation of mature miRNAs in female and male mice following treatment. Expression relative to female and male controls (1.0.). Expression was normalized to mmu-miR-30d-5p. Statistical significant of (*) indicates p < 0.05 between specified groups. n = 5-6 animals per group
Quantitative PCR validation of microRNAs
For miR-34b-3p (Figure 3.4 A), two-way ANOVA showed a significant effect of treatment (p=0.0380, F(3,38)=3.101), but not sex (p=0.6159, F(1,38)=0.256) or an interaction effect (p=0.8309, F(3,38)=0.292). Post hoc analysis showed a significant difference between control and estradiol-treated animals (p=0.0490). For miR-34c-5p
(Figure 3.4 B), two-way ANOVA suggested a weak trend towards an effect of treatment
(p=0.1034, F(3,38)=2.205), but no effect of sex (p=0.3508, F(1,38)=0.892) or an interaction effect (p=0.8392, F(3,38)=0.280).
92 A miR-148a-3p 1.5
1.0
0.5 Female Relative Expression * Male 0.0 Control Handled Vehicle Estradiol
B miR-200a 2.0
1.5
1.0
0.5 Female Relative Expression Male 0.0 Control Handled Vehicle Estradiol
C miR-204-5p 1.5 **
1.0
0.5 Female Relative Expression Male 0.0 Control Handled Vehicle Estradiol
Figure 3.5. Quantitative PCR (qPCR) validation of mature miRNAs. Quantitative PCR validation of mature miRNAs in female and male mice following treatment. Expression relative to female and male controls (1.0). Expression was normalized to mmu-miR-30d-5p. Statistical significance of (*) indicated p < 0.05 and (**) indicates p < 0.01 between specified groups. n = 5-6 animals per group
93 A miR-219a-2 1.5
1.0
0.5 Female Relative Expression Male 0.0 Control Handled Vehicle Estradiol
B miR-448-3p 2.0
1.5
1.0
0.5 Female Relative Expression Male 0.0 Control Handled Vehicle Estradiol
C miR-1298-5p 2.0
1.5
1.0
0.5 Female Relative Expression Male 0.0 Control Handled Vehicle Estradiol
Figure 3.6. Quantitative PCR (qPCR) validation of mature miRNAs. Quantitative PCR validation of mature miRNAs in female and male mice following treatment. Expression relative to female and male controls (1.0). Expression was normalized to mmu-miR-30d-5p. n = 5-6 animals per group
94 For miR-148a (Figure 3.5 A), two-way ANOVA showed a significant effect of sex
(p=0.0146, F(1,38)=6.554), but not treatment (p=0.4973, F(3,38)=0.808) or an interaction effect (p=0.5014, F(3,38)=0.800). For miR-200a (Figure 3.5 B), two-way
ANOVA showed no significant effect of treatment (p=0.5420, F(3,38)=0.727), time
(p=0.5272, F(1,38)=0.407), or an interaction effect (p=0.4982, F(3,38)=0.806). For miR-
204 (Figure 3.5 C), two-way ANOVA showed a significant effect of treatment (p=0.0077,
F(3,38)=4.599), but not sex (p=0.8491, F(1,38)=0.037) or an interaction effect (p=8068,
F(3,38)=0.326). Post hoc analysis showed a significant difference between control and estradiol-treatment animals (p=0.0046). For miR-219a-2 (Figure 3.6 A), two-way
ANOVA showed no effect of treatment (p=0.3815, F(3,38)=1.050), sex (p=0.1253,
F(1,38)=2.457) or an interaction effect (p=0.7017, F(3,38)=0.475). For miR-448 (Figure
3.6 B), two-way ANOVA suggested a trend towards an effect of treatment (p=0.0794,
F(3,38)=2.438), and no effect of sex (p=0.6698, F(1,38)=0.185) or an interaction effect
(p=0.4754, F(3,38)=0.850). For miR-1298 (Figure 3.6 C), two-way ANOVA suggested a trend towards an effect of treatment (p=0.0985, F(3,38)=2.248), and no effect of sex
(p=0.8296, F(1,38)=0.047) or an interaction effect (p=0.7310, F(3,38)=0.432).
Further analysis of qPCR results for miR-448 and miR-1298 showed evidence of clustering of animals within treatment groups (Figure 3.7). Estradiol-treated animals show a group with similar expression to control and a second cluster with decreased expression. Similar expression patterns are also seen for handled and vehicle-treated females for both miR-448 (Figure 3.7 A) and miR-1298 (Figure 3.7 C).
95 A miR-448 Females B miR-448 Males
3 3
2 2
1 1 Relative Expression Relative Expression
0 0 Control Handled Vehicle Estradiol Control Handled Vehicle Estradiol
C miR-1298 Females D miR-1298 Males 2.0 3
1.5 2
1.0
1 0.5 Relative Expression Relative Expression
0.0 0 Control Handled Vehicle Estradiol Control Handled Vehicle Estradiol
Figure 3.7. Quantitative PCR (qPCR) for individual animals for miR-448 (A, B) and miR-1298 (C, D). Each data point represents a single animal. Average and SEM for each treatment group are indicated by the bars. n = 5-6 animals per group
Quantitative PCR analysis of miR-216b and miR-217
For analysis of miR-216b and miR-217, samples from the previous objective and this study were grouped together. For miR-216b (Figure 3.8 A), two-way ANOVA showed a significant effect of sex (p=0.0029, F(1,53)=9.737), a trend towards an effect of treatment (p=0.0569, F(3,53)=2.669), but no interaction effect (p=0.1843,
F(3,53)=1.671). Post-hoc analysis showed a significant difference in miR-216b expression between vehicle-treated males and females (p=0.0283). For miR-217
(Figure 3.8 B), two-way ANOVA showed a significant effect of treatment (p=0.0282,
96 F(3,53)=3.27), but not sex (p=0.2420, F(1,53)=1.4), or an interaction effect (p=0.4820,
F(3,53)=0.8324). Post-hoc analysis showed a significant difference between handled females and estradiol-treated females (p=0.0174) and a trend towards a difference between vehicle-treated females and estradiol-treated females (p=0.0731).
A miR-216b 2.0 *
1.5
1.0
0.5 Female Relative Expression Male 0.0 Control Handled Vehicle Estradiol
B miR-217 * 2.0
1.5
1.0
0.5 Female Relative Expression Male 0.0 Control Handled Vehicle Estradiol
Figure 3.8. Quantitative PCR (qPCR) for miR-216b and miR-217. Samples from objective 1 and 2 were grouped for analysis. Expression relative to female and male controls (1.0). Expression was normalized to miR-30d-5p. Statistical significance of (*) indicates p < 0.05 between indicated groups. n = 5-6 for male groups, 6-12 for female groups
97 Quantitative PCR of corticosterone receptors
For the GR (Figure 3.9 A), two-way ANOVA showed no significant effect of treatment
(p=0.7458, F(3,38)=0.4113), sex (p=0.5935, F(1,38)=0.2896), or an interaction effect
(p=0.8653, F(3,38)=0.2436). For the MR (Figure 3.9 B), two-way ANOVA showed no significant effect of treatment (p=0.5890, F(3,38)=0.6481), sex (p=0.4916,
F(1,38)=0.4822), or an interaction effect (p=0.9756, F(3,38)=0.06994).
A Glucocorticoid Receptor 1.5
1.0
0.5 Female Relative Expression Male 0.0 Control Handled Vehicle Estradiol
B Mineralocorticoid Receptor 2.0
1.5
1.0
0.5 Female Relative Expression Male 0.0 Control Handled Vehicle Estradiol
Figure 3.9. Quantitative PCR (qPCR) of the receptors for corticosterone. Expression relative to female and male controls (1.0). Expression was normalized to HPRT. n = 5-6 animals per group
98 Discussion
MicroRNAs are involved in the regulation of gene expression, and within neurons, have been found to regulate processes that are also under the regulation of estrogens and stress hormones. How estrogens and stress interact to regulate the microRNA-ome of the hippocampus has not been examined before. By utilizing NGS for small RNAs, we were able to assess changes in hippocampal miRNA expression in response to handling stress with or without vehicle or estradiol treatment. Between 48 and 55% of annotated reads mapped to known miRNAs, with more mapping to miRNAs in females than males. Males showed a greater percentage of reads mapped to gene coding regions, mm9 genes and rRNA sequences. This resulted in for 1172 unique miRNAs in males and 1166 unique miRNAs in females. Expression of miR-9, miR-127, miR-128, and members of the let-7 family were highly expressed in both males and females, consistent with previous studies of neuronal miRNA populations (Bak et al., 2008).
Differential expression analysis was performed using 606 miRNAs in female samples and 807 miRNAs in male samples, based on limits set for each analysis. Overall, the female miRNA-ome appears more variable than that seen in males. However, it is important to consider the analysis was only performed on an n of 1 in females, compared to an n of 3 in males, and this could account for this variation. For differential analysis, female counts were normalized using DESeq and males were normalized using a reads per million (rpm) method (reads per million normalized by the total number of reads mapped to a miRNA). Normalizing each sample group with the other method did not appreciably alter Log2 fold changes for given miRNAs.
99 For the males, differential analysis was performed using an edgeR package within sRNAbench, and performed three comparisons, stressed versus control, vehicle versus control, and estradiol versus control. Only one miRNA was found to be differentially expressed, miR-217-5p between estradiol and control. One potential issue for this analysis is the variability between samples from a given treatment group. Such variability could diminish the power of the statistical tests used for differential expression.
This variation could possibly be explained by differences in basal HPA axis activity as well as variations in the stress reactivity. One way to examine this would be to assay serum corticosterone levels. However, this approach also has complications, as both tail vein collection and the use of CO2 can cause corticosterone levels to rise quickly, not allowing for accurate levels to be detected during or after treatment.
For the females, differential expression was determined by changes in DESeq normalized counts. MicroRNAs showing a log2 fold change greater than 1 or less than -1 were considered for further analysis. This analysis found 18 miRNAs to be changed from control following all three treatments, and another 19 to be altered from control in both the stressed and estradiol samples. From these populations, 8 miRNAs were selected across a number of expression levels and patterns for analysis by RT-qPCR, and the analysis was expanded to males.
Following qPCR analysis, three miRNAs were found to be differentially expressed; miR-
34b and miR-204 were significantly reduced in estradiol-treated mice compared to controls, and miR-148a showed a significant effect of sex on expression with higher
100 expression in treated males than females. MiR-148a-3p was one of the most abundantly expressed miRNAs in both males and females based on small RNA sequencing.
Considering its overall high expression, very little is known about what roles miR-148a could play in the brain outside of its involvement in neurological cancers including neuroblastoma, medulloblastoma and glioblastoma. However, considering the tumor suppressor potential of miR-148a with lower levels associate with increased proliferation and migration (Zhou et al., 2012; Gong et al., 2016), it would make sense that expression is high in an area with a large number of postmitotic cells. One study using a quantitative proteomic approach, suggested that miR-148a might play an important role in neuronal development through regulation of proteins such as enabled homologue
(Enah), syntaxin-3 (Stx3), and others (Hu, Tseng, et al., 2013). Stx3 is a predicted target for miR-148a and is known for its role in neurite development (Darios & Davletov,
2006). With respect to the sex difference in miR-148a expression, this miRNA appears to be regulated by gonadal steroids. Treatment of LNCaP prostate cancer cells with
R1881, an androgen receptor agonist, increased expression of miR-148a (Murata et al.,
2010). Conversely, treatment with estradiol downregulated miR-148a expression in both
MCF-7 and triple-negative breast cancer cells (MDA-MB-231), and this effect is mediated through GPER (Tao et al., 2014). Esr1 (ERα) is also a predicted target of miR-
148a, based on TargetScan predictions, perhaps allowing for reciprocal regulation.
Behaviourally, a miR-148a single nucleotide polymorphism (SNP) has been associated with age of onset for panic disorder (Muiños-Gimeno et al., 2011). Given the sex differences seen in stress and anxiety-related disorders, differential expression of miR-
148a could be important.
101 MiR-204-5p is an intronic microRNA located within the sixth intron of the transient receptor potential cation channel subfamily M member 3 (Trpm3) gene. As such, it is believed that miR-204 transcription is under the control of the Trpm3 promoter. Trpm3 expression is positively regulated through binding the transcription factor, Pax6 (Xie et al., 2013). It is of note that Pax6 is known to be involved in both embryonic and adult neurogenesis (reviewed in Osumi et al., 2008). Studies have suggested a role for miR-
204 in neurogenesis and axon guidance within the eye (Conte et al., 2014). Whether or not miR-204 has a similar role in other regions is currently unknown. MiR-204 is also known for its tumor suppressive effects. In gliomas, loss of miR-204 promotes cell migration and invasion (Ying et al., 2013; Mao et al., 2014; Xia et al., 2015). Neuronal apoptosis can also be regulated by miR-204 through repression of Bcl2 and neuritin
(Nrn1) (Gao et al., 2014; Wang et al., 2016). Overall, it appears that appropriate regulation of miR-204 levels is important for proper neuronal function. In relation to hormones, lower miR-204 expression in MCF-7 and MDA-MB-231 breast cancer cells is correlated with increased ERα expression (Liu & Li, 2015). Based on TargetScan predictions, Esr1 is a potential target for miR-204. Consistent with our results, treatment of hormone-responsive ZR-75.1 breast cancer cells with estradiol decreased miR-204 expression (Ferraro et al., 2012). MiR-204 is also predicted to regulate the expression of both GR (Nr3c1) and MR (Nr3c2). Examination of mRNA levels for both receptors showed no changes, however it is possible that miR-204 could regulate receptor expression through post-transcriptional repression.
102 The miR-34 family is a group of miRNAs that are under control by p53. The family contains three members, 34a, 34b, and 34c, and miR-34b and miR-34c are transcribed together in one primary miRNA. MiR-34b-3p is a mature miRNA that is generally considered to be from the passenger strand of pre-miR-34b. However, it this study, miR-34b-3p expression was higher than that of miR-34b-5p. Compared to the 5p species from the miR-34 family, miR-34b-3p has not been well studied. One recent study found miR-34b-3p to be downregulated in neuroblastomas (Maugeri et al., 2016).
MiR-34b is a member of the miR-34 family, and it co-transcribed along with miR-34c.
While not reaching significance, miR-34c-5p showed a similar pattern of expression to miR-34b-3p. The 5p miRNAs of the miR-34 family are well-known tumour suppressors and are also suspected of playing important roles within the brain. The miR-34 family has been found to be important for stress responses in the amygdala with increases in miR-34c following acute and chronic stress (Haramati et al., 2011), and resilience to stress-induced anxiety in an amygdalar miR-34 family triple knock out (Andolina et al.,
2016).
While analyses of miR-448 and miR-1298 did not reach significance, the expression of these two miRNAs showed large variability within treatment groups (Figure 3.7). While data transformation was able to remove much of the variability, it could not completely account for differences in variance or skew in the distribution. Looking specifically at the expression of both miRNAs in females, there appears to be two separate groups within the stress, vehicle and estradiol treatments. This could be related to the variance seen within the NGS results for the males. Variability in the stress response could play a role,
103 perhaps a difference in coping styles to stress. Extending this analysis to look at the other miRNAs, a subset show a trend towards decreased expression in stressed animals (miR-34b, miR-34c, miR-448, and miR-1298). Further study is necessary to determine what effect stress hormones, if any, have with respect to this trend.
Extension of the previous study’s results for miR-216 and miR-217 showed a similar trend in females –both miRNAs are higher in vehicle than estradiol treated mice.
However, this result was not mirrored in males with a significant sex difference in miR-
216b expression in vehicle treated animals. Furthermore, stressed and vehicle-treated females showed similar levels of expression, suggesting that the vehicle effect seen in the first objective could be due to stress.
An important consideration moving forward is the cellular localization of the miRNAs of interest. The hippocampus is not purely made up of neurons and contains astrocytes and endothelial cells that line the blood-brain barrier. Furthermore, within neurons evidence suggests that miRNAs can be localized to specific areas, including the synapto-dendritic compartment (Schratt et al., 2006). Future research could determine the synaptic localization of these miRNAs and others by isolating synaptosomes.
Future studies will need to be undertaken to determine what roles miR-34b-3p, miR-
148a and miR-204 could have in gonadal and stress hormone interactions. This could be done through studies of potential targets of the miRNAs of interest. Another useful follow-up would be the addition of an aromatase inhibitor, such as letrozole, to block the
104 local hippocampal synthesis of estradiol. This would allow for a better understanding of the relative contributions of local and systemic estradiol. It is possible that local production could compensate for the loss of system estradiol seen following ovariectomy.
In conclusion, the study provides new miRNA candidates that may be involved in stress and/or estrogen processes.
105 CHAPTER 4: ROLE FOR CORTICOTROPIN-RELEASING HORMONE (CRH) AND
THE SYNTHETIC GLUCOCORTICOID DEXAMETHASONE IN REGULATING
CHANGES IN MICRORNA EXPRESSION
Introduction
In the previous study, a subset of miRNAs (miR-34b-3p, miR-34c-5p, miR-448-3p, and miR-1298-5p) displayed a trend towards decreased expression compared to control following the stress treatment. The miR-34 family, including miR-34c-5p, has been implicated in the regulation of CRHR1 expression and in the response to stress and antidepressant therapy with a focus on its effects in the amygdala (Haramati et al.,
2011; Bocchio-Chiavetto et al., 2013; Dias et al., 2014; Andolina et al., 2016) (Shenoda et al., 2016). No role for miR-448 or miR-1298 in stress has been determined yet.
While a number of studies have examined the effects of multiple stress protocols on miRNA expression, comparatively little is known about the roles of CRH or GCs in this regulation. One study in porcine ovary found CRH increased the expression of miR-375, allowing for regulation of CRHR1 (Yu et al., 2016). No studies have examined the effects of CRH on neuronal miRNAs. A recent study examined the effect of long-term corticosterone exposure on miRNA expression in the PFC of rats. Treatment with 50 mg/kg corticosterone for 21 days altered the expression of 26 miRNAs including the upregulation of neuronal miR-124 (Dwivedi et al., 2015). Another study looking at hormonal regulation of miRNAs in the adrenal gland found a single injection of the
106 synthetic GC, dexamethasone, altered the expression of 33 miRNAs (Hu, Shen, et al.,
2013).
We hypothesized that CRH and/or corticosterone could regulate the expression of selected microRNAs. To test this hypothesis, human female SH-SY5Y neuroblastoma cells were treated with agonists and antagonists for either the CRH receptors or GR, and microRNA expression was examined. SH-SY5Y neuroblastoma cells have been widely used in studies of neural development (since they are somewhat neuroblast-like and can be differentiated into cells with neuronal phenotypes (Agholme et al. 2010).
They have also been used in studies of the mechanisms involved in neurodegenerative disease (Xie et al. 2010, Arora et al. 2015), and they are known to be sensitive to hormones involved in mediating stress responses in the brain (CRH, β-endorphin, and
GCs) (Ward et al. 2007).
Materials and Methods
Cell Culture
SH-SY5Y human female neuroblastoma cells (ATCC) were grown at 37°C/5% CO2 in
Dulbecco’s modified Eagle medium (DMEM, Invitrogen) containing 10% fetal bovine serum (FBS, Invitrogen) and 1% pen-strep (100 units penicillin + 100 µg streptomycin,
Invitrogen). For experimental procedures, cells were transferred to media containing
10% charcoal-stripped FBS (Invitrogen) 24 hours before plating. Cells were plated onto
60mm plates at 2.0 x 106 cells per plate with charcoal-stripped FBS media used. Cells
107 were left to grow for 24 to 48 hours before treatment to become sufficiently confluent
(70-80%).
Treatment & Sample Collection
To determine a role for CRH in microRNA regulation, plated cells were treated with
CRH, final concentration 10 nM (Sigma) with or without α-helical CRH pre-treatment, final concentration 100 nM (a non-selective, competitive CRH receptor antagonist,
Sigma), or left untreated as a control. Stock solutions of CRH and the antagonist were made in sterile unsupplemented DMEM and stored at -20°C, and treatments were applied directly to the media in the plates. Pre-treatment with α-helical CRH occurred 30 minutes prior to CRH treatment. Four treatment courses were run using both CRH and the antagonist with an additional run using only CRH.
To determine a role for GR activation in microRNA regulation, plated cells were treated with dexamethasone (Dex), final concentration 10 nM (Sigma) with or without pre- treatment with the antagonist RU-38486, final concentration 10 nM (Mifepristone,
Sigma-Aldrich) or left untreated as a control. Stock solutions of Dex and RU-38486 were made in charcoal-stripped FBS (500 µM) and stored at -20°C until use. Stocks were diluted to 10 µM in sterile unsupplemented DMEM prior to use, and treatments were applied directly to the media in the plates. Pre-treatment with RU-38486 occurred 30 minutes prior to Dex treatment. Three treatment courses were run.
108 For both treatment conditions, cells were harvested at 0, 15, 30, 60, 120 and 360 minutes after CRH or Dex treatment by direct cell lysis on the plates with Qiazol
(Qiagen). Cells were homogenized by vortexing for 1 minute and then stored at -80°C until completion of the RNA isolation.
RNA Isolation & Quality
Total RNA was isolated from cell culture lysates by continuing with the miRNeasy Mini
Kit (Qiagen –Toronto, ON, Canada) following the manufacturer’s protocol including the optional on-column DNase digestion (RNase-free DNase –Qiagen). RNA was eluted in the provided RNase-free water and stored at -80°C. RNA sample quality was assessed by NanoDrop spectrophotometer ratios.
cDNA Synthesis & qPCR
For microRNA detection, total RNA was reverse transcribed using the qScript microRNA cDNA Synthesis Kit (Quanta Biosciences –Gaithersburg, MD, USA), following the manufactures protocol with the following addition. To prevent inhibition of qPCR by
Poly(A) reaction components, 2ng of tRNA (Sigma) were added to each reaction (per correspondence with Quanta). Following reverse transcription, cDNA was diluted in TE buffer (pH 8.0, EDTA 0.1 mM) to a final concentration of 4 ng/µL. Quantitative PCR was carried out in a BioRad CFX96TM (BioRad) instrument. Each sample was run in triplicate in 10 µl reaction volumes containing 5 µl of PerfeCTa SYBY Green Super Mix (Quanta
Biosciences), 0.2 µl of 10µM universal primer (Quanta Biosciences), 0.2 µl of 10µM microRNA specific primer (Quanta Biosciences), 0.6 µl of nuclease-free water, and 4 µl
109 of cDNA. The qPCR program consisted of 95°C for 2 min, and 40 cycles of either 95°C for 10 sec and 60°C for 30 sec (miR-30d-5p) or 95°C for 10 sec, 61°C for 30 sec (miR-
34c-5p) followed by a melt curve gradient. See Table 3.1 for primers used.
Statistical Analysis
A two-way ANOVA (treatment x time) was performed for miR-34c-5p expression. A significant level of p < 0.05 was used for all statistical analysis. All data are presented as mean ± SEM.
Results
Effects of CRH on miR-34c expression
1.5
1.0 * *
0.5 CRH Alone Relative Expression * CRH + Antagonist 0.0
1 hour 2 hours 6 hours 0 minutes 15 minutes30 minutes Figure 4.1. Quantitative PCR (qPCR) for miR-34c-5p expression. SH-SY5Y cells were treated with 10 nM CRH with or without CRH receptor antagonist pre-treatment. Expression relative to untreated controls (1.0). Expression was normalized to hsa-miR- 30d-5p. Statistical significance of (*) indicates p < 0.05 between treatments at a given time point. n = 4-5 samples/group with except of 0 minute CRH + antagonist (n = 2)
110 Two-way ANOVA showed a significant effect of treatment (p=0.0045, F(1,39)=9.117), but not time (p=0.3629, F(5,39)=1.126), and a trend towards an interaction effect
(p=0.0522, F(5,39)=2.428). Because the data represent ratios, which are both abnormally distributed and non-homoscedastic a non-parametric test (the Mann-
Whitney U test) was used to compare each set of results back to the results in the presence of CRH alone at each time point. Significant differences between treatments were found at 15 minutes and 1 hour (p < 0.05).
Effects of dexamethasone on miR-34c expression
Two-way ANOVA found no significant effect of treatment (p=0.1686, F(1.24)=2.015), time (p=0.4759, F(5,24)=0.9354), or an interaction effect (p=0.3949, F(5,24)=1.083).
1.5
1.0
0.5 Dex Alone Relative Expression Dex + RU-486 0.0
1 hour 2 hours 6 hours 0 minutes 15 minutes30 minutes Figure 4.2. Quantitative PCR (qPCR) for miR-34c-5p expression. SH-SY5Y cells were treated with 10 nM dexamethasone with or without pre-treatment with 10 nM RU- 38486. Expression relative to untreated controls (1.0). Expression was normalized to hsa-miR-30d-5p. n = 3 samples/group
111 Discussion
CRH and GCs are important mediators of the stress response, however their roles in regulating neuronal miRNA expression have not been fully examined. This study aimed to determine if either hormone could regulate the expression of previously identified miRNAs in SH-SY5Y neuroblastoma cells.
To examine the effects of CRH-CRH receptor signaling on miRNA expression, SH-
SY5Y cells were treated with CRH or CRH in combination with the non-selective, competitive antagonist α-helical CRH. A significant effect of treatment was observed with a decrease in miR-34c expression at 15 minutes and 1 hour in the CRH/CRH antagonist treated cells. This time points correspond to 45 minutes and 1 ½ hours after treatment with the antagonist. These effects are likely through activation/inhibition of
CRHR1, as SH-SY5Y cells are known to express CRHR1 with little or no expression of
CRHR2 (Schoeffter et al., 1999). The exact mechanism of these effects remains unknown. The inclusion of a CRH antagonist alone branch in future experiments would help to determine if the results are due to inhibition of the stimulatory effects of CRH or whether the antagonist acting via another pathway.
One important role of GCs is the fast feedback onto the hypothalamus and pituitary to inhibit further activation of the HPA axis (Dallman et al. 1987). Attenuation of HPA axis activity could also occur through inhibition of CRH receptors, as this would prevent further ACTH release. If attenuation of CRH signaling reduced miR-34c levels, it is possible that miR-34c could play a role in stress resiliency. This possibility is supported
112 by other studies. A miR-34 family triple knockout showed resilience to stress-induced anxiety as well as fear extinction (Andolina et al., 2016). Furthermore, treatment with escitalopram, an SSRI, decreased serum miR-34c-5p levels compared to untreated controls with major depression (Bocchio-Chiavetto et al., 2013).
One factor in this study relates to the endogenous levels of CRH in the system. While the regular serum was replaced with charcoal-stripped serum, the charcoal-stripping process removes steroid hormones and not necessarily peptide hormones. No data is published on the concentration of CRH found in fetal bovine serum. There are also a number of other CRH receptor ligands that could be present in fetal bovine serum
(urocortin I, II and III), which are known to activate CRH receptors in SH-SY5Y cells
(Schoeffter et al., 1999). Therefore, although there are no data in the literature indicating that SH-SY5Y cells are themselves capable of synthesizing CRH, it is possible that the background level of CRHR1 activation from factors in the bovine serum was sufficient to obscure any response to our dose of 10 nM CRH. Addition of the CRH antagonist induced a rapid (within 15 minutes) and significant decrease in miR-34c-5p expression, which may have reflected blockade by the CRH antagonist of the effects of the CRH ligands present in the medium. The inclusion of a CRH antagonist alone treatment would have been a useful addition to this experiment, to determine what effect endogenous CRH peptides could have. A previous study looking at CRHR1 activation by CRH in SH-SY5Y cells serum deprived the cells for 24 hours prior to treatment (Schoeffter et al., 1999). However, SH-SY5Y cells do not respond well to serum starvation with a 38% loss in cell number following 48 hours in serum-free
113 media (Kim et al., 2008), raising the possibility that any effects of either steroids or CRH observed under such circumstances might represent an interaction with the mechanisms mediating serum-starvation induced cell stress and apoptosis.. Moving forward in a cell culture model, it would be essential to know whether CRH ligands are present in the media or not, and whether alternate cell models might provide a better defined culture system in which to examine the effects of CRH.
To examine the effects of GR activation on miRNA expression, SH-SY5Y cells were treated with dexamethasone, a GR-specific agonist, or dexamethasone in combination with RU-36486. No significant differences in miR-34c expression were detected at any time point or treatment.
While attempts were made to detect miR-34b-3p, miR-448-3p, and miR-1298-5p, their expression was very low and reliable detection via qPCR was not possible. While SH-
SY5Y cells are a useful model for the analysis of stress responses due to the expression of both CRHR1 (Schoeffter et al., 1999) and GR (Glick et al., 2000), these results would suggest that miRNA expression patterns in this cell line are not similar to the hippocampus. As many of the identified miRNAs are known for tumour suppressor roles, in a neuroblastoma cell line expression of these miRNAs may well be reduced.
Two possible models exist for future work. Primary cell culture of hippocampal neurons would provide a more accurate representation of the in vivo system, however primary culture presents problems such as a short life span and heterogeneous and varied neuronal and glial cell populations. To counteract the problems associated with primary
114 neuron culture, embryonic hippocampal neurons have been immortalized (Gingerich et al., 2010). These cell lines exhibit neuronal morphology and responses, and are known to express receptors for estrogen and glutamate. However, whether or not they express receptors for CRH or GCs is currently not known, nor has miRNA profiling been performed in these cells.
In conclusion, the CRH-CRH receptor system may regulate the expression of miR-34c-
5p in SH-SY5Y cells. Further work is necessary to better define the contributions of endogenous CRH receptor ligands in bovine fetal serum, as well as to understand the potential functional consequences of CRH regulation of miR-34c-5p.
115
CHAPTER 5: SUMMARY AND FUTURE DIRECTIONS
Introduction
The purpose of the work described in this thesis was to examine how the gonadal steroid, estradiol, and stress regulate the expression of miRNAs within the hippocampus.
The overall hypothesis on which these studies were based is that regulation of hippocampal miRNAs is an important mechanism for synaptic plasticity as well as learning and memory processes, and therefore rapid modulation of miRNA expression could contribute to the hormonal modulation of these processes. Although we initially sought to characterize the effects of estradiol on miRNA expression, we rapidly found that the effects of even the mild stress associated with hormone injection was itself sufficient to alter miRNA expression patterns and, therefore, the effects of estradiol had to be considered in the context of their interactions with stress.
Summary of Work Performed
The first objective sought to examine changes in hippocampal miRNA expression following estradiol treatment. Prior to this work, one study had examined hippocampal miRNA in response to estrogen (Rao et al., 2013). However, the treatment used produced supraphysiological concentrations of estradiol, and examined the effects of the hormone after three days of treatment. The study performed here is therefore the first assessment of rapid effects of estrogen on miRNA expression within the brain. Two miRNAs were identified, miR-216-5p and miR-217-5p, with decreased expression after
116 estradiol counteracted the effects of the vehicle injection. However, the results suggested an interaction effect between an unknown factor and estrogen. We hypothesized that the stress associated with handling and injection could be responsible for the changes seen in miRNA expression, and that, in fact, estradiol’s main effect was to oppose the changes induced by handling stress.
The second objective sought to expand on these results and specifically test the role that the stress associated with handling had on changes in microRNA expression. This study identified three further candidate miRNAs, miR-34b-3p, miR-148a-3p and miR-
204-5p. MiR-34b-3p and miR-204-5p were significantly decreased following estradiol treatment, and miR-148a-3p was decreased in females compared to males.
The third objective sought to determine if CRH or dexamethasone could regulate the expression of selected microRNAs. Most studies examining stress-related hormone effects have focused on either the natural rodent corticosteroid, corticosterone or the synthetic GC, dexamethasone, and on the effects of chronic exposure, not an acute model. We chose to try to define the rapid effects of dexamethasone and CRH using an in vitro tissue culture model, utilizing the well-characterized neuroblastoma cell line, SH-
SY5Y. While dexamethasone did not alter miR-34c-5p expression, this miRNA may be regulated by CRH-CRH receptor signaling, since the α-helical CRH antagonist prevents the stimulatory effects of CRH.
117 Future Directions
The work presented in this thesis represents a first step in attempting to define the effects of circulating steroids on hippocampal expression of miRNAs in the mouse brain.
We identified several microRNAs that were regulated by estrogen and/or stress. Initially, we underestimated how powerful the effects of the stress associated with handling and injecting of the mice might be, which confounded our first attempts to define specific effects of estradiol on rapid miRNA expression. To better understand the regulation of these miRNAs and to determine what role they have in hormone-mediated plasticity additional studies need to be conducted.
Studies completed in this thesis have presented microRNAs that could be involved in gonadal and/or stress pathways including miR-148a-3p, miR-204-5p, miR-216b-5p, miR-217-5p, as well as members of the miR-34 family. While neuronal roles have been observed for miR-34 and miR-204, very little is known about miR-148a, miR-216b or miR-217. Multiple approaches could be taken to determine what role each miRNA could play within the hippocampus. On a broader level, each microRNA could be overexpressed or inhibited in either an in vivo or in vitro model to allow for analysis of differentially regulated mRNA transcripts and/or proteins through next-generation sequencing or microarray. This would allow for a list of candidates that could be examined further. Another way to determine potential candidates is through the use of target prediction programs such as miRanda and TargetScan (Betel et al., 2010;
Agarwal et al., 2015). These programs predict targets of miRNA through base pairing with the seed region and a number of other parameters. One downside to this approach
118 is the number of targets identified. For example, TargetScan predict 645 targets for miR-148a and over 3000 for miR-34b-3p, and many of these targets will not play important roles in a neuronal system. Strategies need to be developed to reduce the number of potential targets to a more reasonable number. Interestingly, one target shared by four of the miRNAs (148a, 204, 216b, and 217) is Esr1 (ERα). Following identification of possible target mRNAs, regulation can be examined through the use of luciferase reporter assays (Jin et al., 2012).
One potentially very important factor limiting our ability to detect hormone-induced changes in miRNA expression is the “background” level of endogenous hormones. This was evident in our attempts, using tissue culture, to better define the effects of GCs and
CHR on miRNA expression in SH-SY5Y cells. The data with the CRH antagonist suggest that (an) endogenous ligand(s) present in the SH-SY5Y cultures may maintain miR-34c-5p expression, which was rapidly blocked by α-helical CRH. Similar issues could have affected the sensitivity of the hippocampus in vivo to the administration of estradiol. It is well established that the hippocampus contains aromatase, and dendritic spine synapse formation is inhibited in hippocampal neurons from female (but not male) rats by inhibition of local estrogen biosynthesis. Although we ovariectomized the mice used in the present studies prior to hormone administration, this does not necessarily mean that the hippocampus is devoid of estradiol. Even following ovariectomy, hippocampal levels of estradiol are similar to that seen in estrus and diestrus, approximately 0.7 nM (Kato et al., 2013; Fester & Rune, 2015). Importantly, this concentration is still higher than that seen in serum during proestrus. As previously
119 suggested, one way to address this in the future would be to determine the effects of the aromatase inhibitor, letrozole. By inhibiting local estradiol synthesis, it is possible that other estrogen-regulated miRNAs could be identified within the hippocampus.
Another very important consideration for future studies is regional differences within the hippocampus. In the studies presented here, we have examined the effects of estradiol administration and handling stress on miRNA expression in the entire hippocampus, in part because of the quantitative constraints imposed by the need to obtain sufficient
RNA for analysis of miRNA expression. However, the hippocampus is not a homogenous structure and different hippocampal cell fields are known to respond differentially to hormone exposure. For example, in female rats, dendritic spine density was decreased in estrus on CA1 apical dendrites with no significant changes seen in
CA3 (Woolley, Gould, Frankfurt, et al., 1990). Conversely, in male rats, 21 days of corticosterone treatment reduced apical dendrite branch points in CA3, but not in CA1
(Woolley, Gould, & McEwen, 1990). Furthermore, the SGZ within the DG is one of two regions to maintain the ability to produce new neurons in adults. It is therefore possible that miRNAs will exhibit regional differences in expression. Another regional distinction that could effect miRNA expression is the longitudinal axis. The dorsal and ventral hippocampi receive inputs and send projections to different areas of the brain
(Fanselow & Dong, 2010). Consequently, different behavioural roles have been assigned to each region with the dorsal hippocampus involved in spatial learning and memory and the ventral hippocampus involved in emotional memory (reviewed in
(Strange et al., 2014)). This distinction raises two possibilities. First, that miRNAs are
120 expressed differently in each region, and second, interactions with stress could be more profound within the ventral hippocampus given its connectivity with the amygdala and role in emotion.
In summary, the data presented in this thesis suggest that the principal ovarian estrogen, estradiol, and hormones produced in response to stress may both rapidly affect expression of a sub-set of miRNAs in the hippocampus. While the only previous study of estrogen action on miRNA expression in the brain identified a much larger number of regulated miRNAs, this study focused on longer term changes, after three days of high dose estradiol administration (Rao et al., 2013). The present data suggest that detectable effects on miRNA expression may occur much more rapidly, in response to physiological changes in hormone levels. A great deal remains to be done in terms of characterizing these responses – particularly in terms of defining the contributions of changes in circulating hormone levels as opposed to the effects of locally synthesized steroids and CRH. However, given what is already known about the roles played by miRNA expression in regulating anatomical and behavioral responses in the brain
(Konopka et al., 2010; Magill et al., 2010; Franke et al., 2012) it seems possible that continued work in this area may lead to a better understanding of the mechanisms mediating the rapid effects of steroids on brain function.
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163
APPENDIX
164 Supplemental Table 1. Differential expression of miRNA between Vehicle and Estradiol treated animals Vehicle (+) relative to Estradiol (-)
ID (Mmu-) Log2 FC P-value ID (Mmu-) Log2 FC P-value miR-3547-3p 3.184 0.0039 miR-325-3p 0.881 0.7172 miR-217-5p 2.894 0.0003 miR-483-3p 0.875 0.7172 miR-216b-5p 2.423 0.0039 miR-219c-5p 0.861 0.7648 miR-1251-5p 1.726 0.2477 miR-199a-5p 0.849 0.6931 miR-653-5p 1.603 0.3159 miR-200b-5p 0.806 0.7172 miR-224-5p 1.577 0.2472 miR-1249-3p 0.765 0.7016 miR-3552 1.519 0.4343 miR-8114 0.754 0.9962 miR-211-5p 1.513 0.2472 miR-219a-2-3p 0.737 0.5730 miR-448-5p 1.483 0.4343 miR-1a-3p 0.718 0.4343 miR-10b-5p 1.470 0.4612 miR-199ab-3p 0.706 0.7016 miR-448-3p 1.450 0.7763 miR-1224-5p 0.705 0.7763 miR-1912-3p 1.433 0.8205 miR-299a-5p 0.699 1.0000 miR-1298-5p 1.365 0.9270 miR-669ap-5p 0.694 0.7172 miR-204-5p 1.295 0.4035 miR-338-5p 0.679 0.7016 miR-1264-5p 1.280 0.7016 miR-145a-3p 0.675 0.7016 miR-1264-3p 1.268 0.7016 miR-490-3p 0.667 0.8205 miR-34b-3p 1.249 0.7016 miR-1964-3p 0.666 0.7130 miR-34c-3p 1.205 0.7203 miR-7052-3p 0.664 0.9157 miR-375-3p 1.203 0.4035 miR-34b-5p 0.638 1.0000 miR-206-3p 1.141 0.4035 miR-449a-5p 0.621 1.0000 miR-204-3p 1.128 0.6931 miR-298-5p 0.610 0.9270 miR-10a-5p 1.126 0.4035 miR-1224-3p 0.609 0.9157 miR-490-5p 1.125 0.4868 miR-466g 0.601 0.9962 miR-34c-5p 1.124 0.7172 miR-486a-3p 0.588 0.9877 miR-214-3p 1.123 0.7016 miR-486b-3p 0.588 0.9877 miR-133a-3p 1.123 0.3481 miR-881-3p 0.577 1.0000 miR-135a-2-3p 1.121 0.3694 miR-20b-5p 0.567 1.0000 miR-669l-5p 1.101 0.4657 miR-15b-3p 0.561 0.9815 miR-7043-3p 1.081 0.5141 miR-6900-3p 0.547 1.0000 miR-1298-3p 1.063 0.7016 miR-150-3p 0.543 1.0000 miR-135a-5p 1.049 0.4035 miR-1982-3p 0.542 0.9913 miR-483-5p 1.045 0.7016 miR-200b-3p 0.541 0.9157 miR-758-3p 1.023 0.4343 miR-135b-5p 0.538 0.9962 miR-764-5p 0.975 0.7016 miR-145a-5p 0.534 0.8718 miR-34a-5p 0.972 0.5141 miR-33-3p 0.527 1.0000 miR-133b-3p 0.944 0.7016 miR-199b-5p 0.514 1.0000 miR-223-3p 0.919 0.5141 miR-466c-5p 0.499 1.0000 miR-135b-3p 0.906 0.7016 miR-505-3p 0.498 0.9647
165 Supplemental Table 1. Differential expression of miRNA between Vehicle and Estradiol treated animals Vehicle (+) relative to Estradiol (-)
ID (Mmu-) Log2 FC P-value ID (Mmu-) Log2 FC P-value miR-7068-3p 0.496 1.0000 miR-100-5p 0.330 1.0000 miR-499-5p 0.491 0.9962 miR-3093-5p 0.325 1.0000 miR-501-5p 0.487 1.0000 miR-3099-3p 0.320 1.0000 miR-143-3p 0.486 0.9056 miR-877-5p 0.316 1.0000 miR-152-3p 0.475 0.9398 miR-25-3p 0.313 1.0000 miR-143-5p 0.472 0.9962 miR-1943-5p 0.307 1.0000 miR-155-5p 0.455 1.0000 miR-669o-5p 0.302 1.0000 miR-429-3p 0.449 1.0000 miR-3057-5p 0.293 1.0000 miR-200a-5p 0.443 1.0000 miR-182-5p 0.292 1.0000 miR-350-5p 0.432 1.0000 miR-190b-5p 0.282 1.0000 miR-134-5p 0.427 1.0000 miR-146a-5p 0.280 1.0000 miR-6989-3p 0.424 1.0000 miR-3064-5p 0.275 1.0000 miR-598-3p 0.421 0.9157 miR-26b-5p 0.273 1.0000 miR-700-5p 0.414 1.0000 miR-574-3p 0.272 1.0000 miR-344f-3p 0.408 1.0000 miR-320-3p 0.268 1.0000 miR-700-3p 0.408 1.0000 miR-149-5p 0.253 1.0000 miR-338-3p 0.407 1.0000 miR-130b-5p 0.242 1.0000 miR-382-5p 0.407 0.9962 miR-152-5p 0.236 1.0000 miR-200c-3p 0.401 1.0000 miR-200a-3p 0.234 1.0000 miR-451a 0.398 1.0000 miR-770-3p 0.231 1.0000 miR-6481 0.397 1.0000 miR-194-2-3p 0.227 1.0000 miR-669d-5p 0.390 1.0000 miR-344b-3p 0.226 1.0000 miR-24-2-5p 0.386 1.0000 miR-382-3p 0.219 1.0000 miR-6945-3p 0.379 1.0000 miR-7226-3p 0.215 1.0000 miR-5100 0.373 1.0000 miR-667-5p 0.212 1.0000 miR-92a-3p 0.371 1.0000 miR-455-5p 0.209 1.0000 miR-183-5p 0.365 1.0000 miR-6896-5p 0.208 1.0000 miR-8103 0.361 1.0000 miR-125b-1-3p 0.194 1.0000 miR-21a-5p 0.360 1.0000 miR-326-3p 0.191 1.0000 miR-1191a 0.355 1.0000 miR-301a-5p 0.190 1.0000 miR-210-5p 0.351 1.0000 miR-652-3p 0.188 1.0000 miR-467e-5p 0.350 1.0000 miR-384-3p 0.182 1.0000 miR-6516-3p 0.346 1.0000 miR-150-5p 0.181 1.0000 miR-3084-3p 0.343 1.0000 miR-205-5p 0.179 1.0000 miR-467d-5p 0.341 1.0000 miR-455-3p 0.176 1.0000 miR-296-3p 0.341 1.0000 miR-423-3p 0.171 1.0000 miR-210-3p 0.336 1.0000 miR-144-5p 0.170 1.0000 miR-760-3p 0.334 1.0000 miR-129-1-3p 0.169 1.0000
166 Supplemental Table 1. Differential expression of miRNA between Vehicle and Estradiol treated animals Vehicle (+) relative to Estradiol (-)
ID (Mmu-) Log2 FC P-value ID (Mmu-) Log2 FC P-value miR-126a-5p 0.168 1.0000 miR-345-3p 0.113 1.0000 miR-3087-3p 0.167 1.0000 miR-3068-3p 0.111 1.0000 miR-330-5p 0.162 1.0000 miR-383-5p 0.110 1.0000 miR-140-3p 0.158 1.0000 miR-215-5p 0.104 1.0000 miR-330-3p 0.158 1.0000 miR-669c-5p 0.103 1.0000 miR-6979-3p 0.158 1.0000 miR-350-3p 0.100 1.0000 miR-1839-3p 0.157 1.0000 miR-187-5p 0.100 1.0000 miR-20a-5p 0.154 1.0000 miR-296-5p 0.098 1.0000 miR-126a-3p 0.154 1.0000 miR-532-5p 0.098 1.0000 miR-146b-3p 0.152 1.0000 miR-467a-3p 0.097 1.0000 miR-433-5p 0.151 1.0000 miR-467d-3p 0.097 1.0000 miR-770-5p 0.147 1.0000 miR-146b-5p 0.091 1.0000 miR-384-5p 0.147 1.0000 miR-410-3p 0.090 1.0000 miR-702-3p 0.146 1.0000 miR-32-5p 0.090 1.0000 miR-466bcp-3p 0.141 1.0000 miR-24-1-5p 0.090 1.0000 miR-466ae-3p 0.141 1.0000 miR-26b-3p 0.090 1.0000 miR-433-3p 0.139 1.0000 miR-181b-5p 0.088 1.0000 miR-181b-1-3p 0.139 1.0000 miR-27b-3p 0.082 1.0000 miR-187-3p 0.133 1.0000 miR-3069-3p 0.081 1.0000 miR-3963 0.131 1.0000 miR-181a-5p 0.080 1.0000 miR-28a-3p 0.129 1.0000 miR-365-3p 0.079 1.0000 miR-3082-3p 0.128 1.0000 miR-30c-1-3p 0.078 1.0000 miR-6928-3p 0.127 1.0000 miR-7a-5p 0.076 1.0000 miR-5121 0.127 1.0000 miR-27b-5p 0.073 1.0000 miR-15a-5p 0.126 1.0000 miR-93-5p 0.070 1.0000 miR-192-5p 0.125 1.0000 miR-23a-3p 0.069 1.0000 miR-378a-5p 0.124 1.0000 miR-3535 0.067 1.0000 miR-8112 0.123 1.0000 miR-106b-5p 0.067 1.0000 miR-378a-3p 0.122 1.0000 miR-6988-3p 0.067 1.0000 miR-7689-3p 0.121 1.0000 miR-431-3p 0.065 1.0000 miR-322-3p 0.121 1.0000 miR-19b-3p 0.065 1.0000 miR-185-3p 0.120 1.0000 miR-1968-5p 0.064 1.0000 miR-141-3p 0.120 1.0000 miR-539-5p 0.063 1.0000 miR-1258-3p 0.119 1.0000 miR-346-5p 0.063 1.0000 miR-3102-3p 0.117 1.0000 miR-501-3p 0.062 1.0000 miR-323-5p 0.117 1.0000 miR-423-5p 0.062 1.0000 miR-297abc-3p 0.115 1.0000 miR-134-3p 0.060 1.0000 miR-331-5p 0.114 1.0000 let-7e-3p 0.058 1.0000
167 Supplemental Table 1. Differential expression of miRNA between Vehicle and Estradiol treated animals Vehicle (+) relative to Estradiol (-)
ID (Mmu-) Log2 FC P-value ID (Mmu-) Log2 FC P-value miR-15b-5p 0.058 1.0000 miR-26a-2-3p 0.002 1.0000 miR-122-5p 0.058 1.0000 miR-3093-3p 0.002 1.0000 miR-17-5p 0.056 1.0000 miR-30b-3p 0.000 1.0000 miR-3068-5p 0.054 1.0000 miR-129-5p -0.001 1.0000 miR-99a-3p 0.049 1.0000 miR-29b-2-5p -0.001 1.0000 miR-582-3p 0.046 1.0000 miR-362-3p -0.004 1.0000 miR-872-3p 0.043 1.0000 miR-378c -0.007 1.0000 miR-543-3p 0.042 1.0000 miR-672-5p -0.009 1.0000 miR-376a-5p 0.042 1.0000 let-7d-3p -0.012 1.0000 miR-140-5p 0.041 1.0000 miR-505-5p -0.012 1.0000 miR-127-3p 0.038 1.0000 miR-30d-5p -0.015 1.0000 miR-467c-5p 0.037 1.0000 miR-664-3p -0.016 1.0000 miR-219a-1-3p 0.035 1.0000 miR-151-5p -0.017 1.0000 miR-325-5p 0.034 1.0000 miR-3060-3p -0.019 1.0000 miR-185-5p 0.034 1.0000 miR-99a-5p -0.020 1.0000 miR-194-5p 0.033 1.0000 miR-677-5p -0.020 1.0000 miR-3962 0.032 1.0000 miR-340-3p -0.022 1.0000 miR-380-3p 0.031 1.0000 miR-495-3p -0.023 1.0000 miR-7047-3p 0.031 1.0000 miR-341-5p -0.025 1.0000 miR-532-3p 0.030 1.0000 miR-666-5p -0.025 1.0000 miR-99b-3p 0.029 1.0000 miR-378b -0.025 1.0000 let-7b-3p 0.026 1.0000 miR-92b-3p -0.027 1.0000 miR-129-2-3p 0.025 1.0000 miR-873a-3p -0.027 1.0000 miR-106b-3p 0.024 1.0000 miR-339-5p -0.028 1.0000 miR-181a-1-3p 0.023 1.0000 miR-6952-3p -0.028 1.0000 miR-6516-5p 0.020 1.0000 miR-99b-5p -0.031 1.0000 miR-3072-3p 0.017 1.0000 miR-30c-5p -0.032 1.0000 miR-362-5p 0.015 1.0000 miR-380-5p -0.033 1.0000 miR-467a-5p 0.014 1.0000 miR-27a-5p -0.034 1.0000 miR-130a-3p 0.013 1.0000 miR-322-5p -0.035 1.0000 miR-151-3p 0.012 1.0000 miR-6540-5p -0.036 1.0000 miR-28a-5p 0.011 1.0000 miR-32-3p -0.038 1.0000 miR-28c 0.011 1.0000 miR-148a-5p -0.041 1.0000 miR-667-3p 0.009 1.0000 miR-7075-3p -0.043 1.0000 let-7g-5p 0.008 1.0000 miR-361-5p -0.046 1.0000 miR-351-5p 0.006 1.0000 miR-329-5p -0.048 1.0000 miR-6911-3p 0.005 1.0000 miR-324-5p -0.049 1.0000 miR-744-5p 0.003 1.0000 miR-3077-3p -0.050 1.0000
168 Supplemental Table 1. Differential expression of miRNA between Vehicle and Estradiol treated animals Vehicle (+) relative to Estradiol (-)
ID (Mmu-) Log2 FC P-value ID (Mmu-) Log2 FC P-value miR-1197-3p -0.050 1.0000 miR-181a-2-3p -0.097 1.0000 miR-23b-3p -0.053 1.0000 miR-5621-3p -0.098 1.0000 miR-340-5p -0.055 1.0000 let-7a-5p -0.098 1.0000 miR-503-3p -0.055 1.0000 miR-1947-5p -0.100 1.0000 miR-3086-5p -0.055 1.0000 miR-872-5p -0.101 1.0000 miR-144-3p -0.056 1.0000 miR-1188-5p -0.102 1.0000 miR-378d -0.058 1.0000 miR-339-3p -0.104 1.0000 miR-6906-3p -0.059 1.0000 miR-374c-5p -0.105 1.0000 miR-195a-3p -0.061 1.0000 miR-374b-5p -0.105 1.0000 miR-27a-3p -0.063 1.0000 miR-26a-5p -0.105 1.0000 miR-1843a-3p -0.064 1.0000 miR-503-5p -0.105 1.0000 let-7f-5p -0.065 1.0000 let-7c-5p -0.106 1.0000 miR-98-5p -0.068 1.0000 miR-16-5p -0.107 1.0000 miR-344h-3p -0.068 1.0000 miR-592-5p -0.107 1.0000 miR-3059-5p -0.070 1.0000 miR-6944-3p -0.107 1.0000 miR-203-3p -0.075 1.0000 miR-103-3p -0.109 1.0000 miR-542-3p -0.076 1.0000 miR-1306-5p -0.109 1.0000 miR-484 -0.076 1.0000 miR-361-3p -0.111 1.0000 miR-582-5p -0.077 1.0000 miR-193b-3p -0.111 1.0000 miR-101b-3p -0.077 1.0000 miR-1291 -0.114 1.0000 miR-30a-5p -0.078 1.0000 miR-181d-5p -0.115 1.0000 miR-5099 -0.079 1.0000 miR-107-3p -0.115 1.0000 let-7f-2-3p -0.079 1.0000 miR-1843a-5p -0.116 1.0000 miR-6977-3p -0.080 1.0000 miR-541-5p -0.121 1.0000 miR-181c-3p -0.083 1.0000 miR-877-3p -0.121 1.0000 miR-1839-5p -0.083 1.0000 miR-324-3p -0.123 1.0000 miR-379-3p -0.084 1.0000 miR-30c-2-3p -0.123 1.0000 miR-125b-5p -0.084 1.0000 miR-125a-5p -0.123 1.0000 miR-30b-5p -0.087 1.0000 miR-191-5p -0.124 1.0000 miR-434-3p -0.089 1.0000 miR-345-5p -0.127 1.0000 miR-450a-5p -0.091 1.0000 let-7a-1-3p = -0.128 1.0000 miR-300-3p -0.092 1.0000 let-7c-2-3p miR-29a-5p -0.094 1.0000 miR-7b-5p -0.129 1.0000 miR-500-3p -0.095 1.0000 let-7b-5p -0.130 1.0000 miR-30e-5p -0.095 1.0000 miR-125b-2-3p -0.130 1.0000 miR-7a-2-3p -0.095 1.0000 miR-29c-5p -0.134 1.0000 miR-487b-5p -0.096 1.0000 miR-17-3p -0.134 1.0000 miR-188-5p -0.096 1.0000 miR-3061-3p -0.134 1.0000
169 Supplemental Table 1. Differential expression of miRNA between Vehicle and Estradiol treated animals Vehicle (+) relative to Estradiol (-)
ID (Mmu-) Log2 FC P-value ID (Mmu-) Log2 FC P-value miR-379-5p -0.136 1.0000 miR-29c-3p -0.184 1.0000 let-7f-1-3p -0.137 1.0000 miR-6946-3p -0.184 1.0000 miR-301a-3p -0.140 1.0000 let-7d-5p -0.188 1.0000 miR-195a-5p -0.140 1.0000 let-7i-5p -0.192 1.0000 miR-24-3p -0.142 1.0000 miR-29b-1-5p -0.193 1.0000 miR-148a-3p -0.144 1.0000 miR-421-3p -0.195 1.0000 miR-879-5p -0.145 1.0000 miR-9-3p -0.195 1.0000 miR-1843b-3p -0.148 1.0000 miR-335-5p -0.196 1.0000 miR-93-3p -0.149 1.0000 miR-7a-1-3p -0.197 1.0000 miR-485-5p -0.149 1.0000 miR-491-5p -0.201 1.0000 miR-664-5p -0.149 1.0000 miR-344-3p -0.202 1.0000 miR-181c-5p -0.152 1.0000 miR-7240-5p -0.202 1.0000 miR-30a-3p -0.152 1.0000 miR-412-3p -0.202 1.0000 miR-148b-5p -0.153 1.0000 miR-6239 -0.205 1.0000 miR-486a-5p = -0.153 1.0000 miR-411-5p -0.208 1.0000 miR-486b-5p miR-3475-3p -0.212 1.0000 miR-425-3p -0.154 1.0000 miR-331-3p -0.213 1.0000 miR-30d-3p -0.155 1.0000 miR-16-1-3p -0.215 1.0000 miR-374c-3p -0.155 1.0000 miR-299b-5p -0.217 1.0000 miR-666-3p -0.157 1.0000 miR-101c -0.219 1.0000 miR-25-5p -0.158 1.0000 miR-101a-3p -0.219 1.0000 miR-434-5p -0.159 1.0000 miR-154-5p -0.220 1.0000 miR-30e-3p -0.160 1.0000 miR-466d-3p -0.220 1.0000 miR-29b-3p -0.161 1.0000 miR-3102-3p.2- -0.223 1.0000 miR-425-5p -0.161 1.0000 3p let-7i-3p -0.163 1.0000 miR-376c-3p -0.228 1.0000 miR-540-3p -0.164 1.0000 miR-3970 -0.234 1.0000 let-7e-5p -0.167 1.0000 miR-488-5p -0.238 1.0000 miR-1198-5p -0.168 1.0000 miR-341-3p -0.238 1.0000 miR-148b-3p -0.168 1.0000 miR-376b-3p -0.239 1.0000 miR-142a-5p -0.170 1.0000 miR-1306-3p -0.241 1.0000 miR-665-3p -0.171 1.0000 miR-124-3p -0.241 1.0000 miR-29a-3p -0.172 1.0000 miR-299a-3p -0.244 1.0000 miR-190a-5p -0.173 1.0000 miR-299b-3p -0.245 1.0000 miR-3968 -0.178 1.0000 miR-191-3p -0.245 1.0000 miR-671-5p -0.179 1.0000 miR-31-5p -0.247 1.0000 miR-328-3p -0.180 1.0000 miR-671-3p -0.248 1.0000 miR-125a-3p -0.181 1.0000 miR-674-5p -0.248 1.0000
170 Supplemental Table 1. Differential expression of miRNA between Vehicle and Estradiol treated animals Vehicle (+) relative to Estradiol (-)
ID (Mmu-) Log2 FC P-value ID (Mmu-) Log2 FC P-value miR-186-5p -0.250 1.0000 miR-22-3p -0.330 1.0000 miR-377-5p -0.252 1.0000 miR-5129-3p -0.330 1.0000 miR-138-1-3p -0.253 1.0000 miR-33-5p -0.338 1.0000 miR-673-3p -0.253 1.0000 miR-487b-3p -0.339 1.0000 miR-376b-5p -0.255 1.0000 miR-551b-3p -0.339 1.0000 miR-6236 -0.256 1.0000 miR-212-3p -0.343 1.0000 miR-329-3p -0.258 1.0000 miR-873a-5p -0.346 1.0000 let-7j -0.260 1.0000 miR-344d-3-5p -0.348 1.0000 miR-1927 -0.260 1.0000 miR-1981-5p -0.351 1.0000 miR-7b-3p -0.261 1.0000 miR-138-2-3p -0.353 1.0000 miR-411-3p -0.261 1.0000 miR-7224-3p -0.354 1.0000 miR-136-5p -0.263 1.0000 miR-3066-5p -0.359 1.0000 miR-370-3p -0.264 1.0000 miR-335-3p -0.369 1.0000 miR-6240 -0.266 1.0000 miR-3078-5p -0.370 1.0000 let-7k -0.268 1.0000 miR-7015-3p -0.370 1.0000 miR-485-3p -0.270 1.0000 miR-127-5p -0.377 1.0000 miR-6395 -0.272 1.0000 miR-676-3p -0.377 1.0000 miR-323-3p -0.277 1.0000 miR-679-5p -0.378 1.0000 miR-124-5p -0.283 1.0000 miR-543-5p -0.384 1.0000 miR-673-5p -0.290 1.0000 miR-9-5p -0.384 0.9815 miR-1843b-5p -0.292 1.0000 miR-412-5p -0.384 1.0000 miR-541-3p -0.293 1.0000 miR-381-3p -0.386 1.0000 miR-98-3p -0.293 1.0000 miR-1981-3p -0.386 1.0000 miR-370-5p -0.299 1.0000 miR-219a-5p -0.390 1.0000 miR-668-3p -0.307 1.0000 miR-218-5p -0.393 1.0000 miR-874-3p -0.308 1.0000 miR-488-3p -0.393 1.0000 miR-497a-5p -0.308 1.0000 miR-2137 -0.402 1.0000 miR-369-5p -0.310 1.0000 miR-7070-3p -0.406 1.0000 miR-496a-3p -0.314 1.0000 miR-6769b-3p -0.432 1.0000 miR-136-3p -0.315 1.0000 miR-6238 -0.435 1.0000 miR-704 -0.317 1.0000 miR-409-5p -0.435 0.9815 miR-676-5p -0.319 1.0000 miR-153-3p -0.441 1.0000 miR-369-3p -0.319 1.0000 miR-377-3p -0.453 0.9815 let-7c-1-3p -0.321 1.0000 miR-344g-3p -0.454 1.0000 miR-744-3p -0.324 1.0000 miR-409-3p -0.455 0.9441 miR-3083-5p -0.325 1.0000 miR-494-3p -0.466 0.9815 miR-1983 -0.325 1.0000 miR-504-5p -0.469 0.9877 miR-300-5p -0.325 1.0000 miR-154-3p -0.474 0.9962
171 Supplemental Table 1. Differential expression of miRNA between Vehicle and Estradiol treated animals Vehicle (+) relative to Estradiol (-)
ID (Mmu-) Log2 FC P-value ID (Mmu-) Log2 FC P-value miR-674-3p -0.478 0.9798 miR-221-3p -0.716 0.7172 miR-376a-3p -0.479 0.9815 miR-7080-5p -0.722 0.9270 miR-708-3p -0.483 0.9120 miR-222-5p -0.730 0.7545 miR-22-5p -0.485 0.9670 miR-7044-3p -0.736 0.7130 miR-493-5p -0.510 0.9588 let-7g-3p -0.744 0.8246 miR-493-3p -0.512 1.0000 miR-547-3p -0.750 0.7648 miR-142a-3p -0.513 0.9647 miR-337-3p -0.784 0.5991 miR-6899-3p -0.513 0.9815 miR-137-5p -0.809 0.7016 miR-874-5p -0.516 1.0000 miR-672-3p -0.814 0.7130 miR-540-5p -0.524 0.9815 miR-7236-3p -0.842 0.9815 miR-138-5p -0.530 0.7801 miR-128-1-5p -0.911 0.7130 miR-344d-3p -0.533 0.8718 miR-431-5p -0.940 0.4046 miR-410-5p -0.533 0.9441 miR-6982-3p -1.099 0.4035 miR-193b-5p -0.534 1.0000 miR-467b-5p -1.118 1.0000 miR-23b-5p -0.547 0.9913 miR-7079-3p -1.298 0.3192 miR-212-5p -0.554 0.9120 miR-184-3p -1.853 0.3481 miR-344c-3p -0.558 0.8706 miR-135a-1-3p -0.558 1.0000 miR-218-2-3p -0.568 1.0000 miR-7080-3p -0.569 1.0000 miR-128-2-5p -0.570 0.9815 miR-1193-3p -0.598 0.7430 miR-337-5p -0.601 0.7172 miR-5615-5p -0.607 0.9815 miR-3085-3p -0.616 0.9120 miR-221-5p -0.626 0.7801 miR-139-3p -0.627 0.7172 miR-137-3p -0.636 0.7545 miR-128-3p -0.638 0.7172 miR-139-5p -0.641 0.7016 miR-132-3p -0.645 0.7459 miR-708-5p -0.655 0.7172 miR-3081-3p -0.672 0.7172 miR-222-3p -0.703 0.7130 miR-342-3p -0.706 0.9141 miR-342-5p -0.709 0.7172 miR-92b-5p -0.714 0.7016 miR-132-5p -0.715 0.7172
172 Supplemental Table 2. Differential expression of miRNA between Control and Handled female animals Handled (+) relative to Control (-)
ID (Mmu-) Log2 FC ID (Mmu-) Log2 FC ID (Mmu-) Log2 FC miR-1298-5p -4.038 miR-298-5p -0.924 miR-6540-5p -0.508 miR-1912-3p -3.905 miR-483-3p -0.886 miR-499-5p -0.504 miR-448-3p -3.615 miR-1927 -0.880 miR-1964-3p -0.497 miR-1264-3p -3.149 miR-325-3p -0.874 miR-3093-5p -0.493 miR-1264-5p -2.643 miR-503-5p -0.858 miR-466g -0.492 miR-448-5p -2.466 miR-3087-3p -0.839 miR-31-3p -0.484 miR-216b-5p -2.229 miR-325-5p -0.822 miR-92a-3p -0.465 miR-653-5p -2.168 miR-375-3p -0.817 miR-21c -0.462 miR-34c-3p -2.083 miR-350-5p -0.797 miR-666-5p -0.460 miR-217-5p -2.081 miR-1249-3p -0.780 miR-301a-5p -0.445 miR-204-3p -2.069 miR-1968-5p -0.752 let-7a-2-3p -0.442 miR-3552 -2.024 miR-3084-3p -0.749 miR-3473f -0.442 miR-34b-5p -1.978 miR-3061-3p -0.735 miR-192-5p -0.442 miR-204-5p -1.924 miR-338-3p -0.731 miR-3069-3p -0.440 miR-34c-5p -1.905 miR-32-5p -0.719 miR-296-5p -0.431 miR-34b-3p -1.816 miR-700-5p -0.712 miR-879-3p -0.414 miR-1298-3p -1.742 miR-450a-5p -0.698 miR-210-3p -0.403 miR-133b-3p -1.671 miR-1197-3p -0.695 miR-6945-3p -0.399 miR-764-5p -1.464 miR-193b-5p -0.694 miR-7689-3p -0.391 miR-206-3p -1.411 miR-6481 -0.690 miR-7043-3p -0.386 miR-224-5p -1.384 miR-466i-3p -0.677 miR-3470a -0.383 miR-338-5p -1.349 miR-505-5p -0.642 miR-193b-3p -0.380 miR-219a-5p -1.336 miR-758-3p -0.641 miR-125b-1-3p -0.379 miR-450b-5p -1.311 miR-700-3p -0.628 miR-455-5p -0.374 miR-211-5p -1.292 miR-7226-3p -0.609 miR-490-5p -0.374 miR-449a-5p -1.262 miR-3061-5p -0.601 miR-187-5p -0.372 miR-10a-5p -1.255 miR-2137 -0.595 miR-296-3p -0.365 miR-344h-3p -1.239 miR-3968 -0.588 miR-1982-3p -0.361 miR-503-3p -1.216 miR-17-5p -0.585 miR-16-1-3p -0.361 miR-219a-2-3p -1.216 miR-1a-3p -0.562 miR-340-3p -0.350 miR-10b-5p -1.172 miR-7224-3p -0.555 miR-185-3p -0.349 miR-1251-5p -1.024 miR-669p-5p -0.552 miR-26b-3p -0.346 miR-34a-5p -1.002 miR-21a-5p -0.548 miR-497b -0.346 miR-133a-3p -0.974 miR-412-5p -0.537 miR-19b-3p -0.342 miR-8112 -0.955 miR-1306-3p -0.519 miR-27b-5p -0.341 miR-344f-3p -0.934 miR-100-3p -0.513 miR-330-3p -0.337 miR-6977-3p -0.934 miR-24-1-5p -0.512 miR-135a-5p -0.328 miR-365-1-5p -0.924 miR-455-3p -0.510 miR-351-5p -0.326
173 Supplemental Table 2. Differential expression of miRNA between Control and Handled female animals Handled (+) relative to Control (-)
ID (Mmu-) Log2 FC ID (Mmu-) Log2 FC ID (Mmu-) Log2 FC miR-505-3p -0.325 miR-181b-5p -0.227 miR-98-5p -0.157 miR-322-3p -0.322 miR-27b-3p -0.224 miR-7a-5p -0.152 miR-193a-5p -0.320 miR-23b-5p -0.213 miR-423-5p -0.152 miR-6911-3p -0.320 miR-1981-3p -0.211 miR-501-5p -0.150 miR-3057-5p -0.317 miR-704 -0.207 let-7e-3p -0.150 miR-144-3p -0.316 miR-215-5p -0.205 miR-30d-3p -0.150 miR-1981-5p -0.312 miR-340-5p -0.203 miR-669c-5p -0.147 miR-466e-3p -0.306 miR-3099-3p -0.202 miR-547-3p -0.147 miR-466p-3p -0.306 miR-384-5p -0.201 miR-126a-3p -0.146 miR-433-3p -0.303 miR-541-3p -0.201 miR-380-5p -0.143 miR-330-5p -0.295 miR-7236-3p -0.200 miR-344c-3p -0.143 miR-433-5p -0.295 miR-668-3p -0.199 miR-3084-5p -0.143 miR-151-3p -0.291 miR-30c-5p -0.199 miR-466a-3p -0.139 miR-1188-5p -0.290 miR-543-3p -0.198 miR-345-3p -0.139 miR-130b-5p -0.288 miR-339-5p -0.197 miR-93-5p -0.136 miR-20a-5p -0.286 miR-344-3p -0.196 miR-148b-3p -0.136 miR-152-5p -0.285 miR-3572-3p -0.191 miR-1198-5p -0.135 miR-219c-5p -0.279 miR-383-5p -0.187 miR-466f-3p -0.132 miR-879-5p -0.275 miR-181a-5p -0.181 miR-574-3p -0.132 miR-93-3p -0.274 miR-467c-5p -0.179 miR-384-3p -0.131 miR-466i-5p -0.262 miR-760-3p -0.174 miR-410-3p -0.130 miR-135a-2-3p -0.262 miR-484 -0.174 miR-6896-5p -0.129 miR-92b-5p -0.262 miR-3093-3p -0.174 miR-434-5p -0.129 miR-344b-3p -0.260 miR-467b-5p -0.173 let-7a-5p -0.128 miR-190b-5p -0.255 miR-467a-5p -0.173 miR-431-3p -0.126 miR-362-5p -0.251 miR-666-3p -0.172 miR-5620-5p -0.124 miR-152-3p -0.249 miR-365-3p -0.172 miR-669o-5p -0.124 miR-410-5p -0.246 miR-181a-1-3p -0.171 miR-423-3p -0.112 miR-1191a -0.245 miR-1224-5p -0.168 miR-98-3p -0.111 miR-15b-5p -0.243 miR-744-3p -0.168 miR-3074-5p -0.107 miR-194-5p -0.242 miR-7080-5p -0.168 let-7f-2-3p -0.107 let-7f-1-3p -0.240 miR-877-3p -0.168 let-7c-2-3p -0.107 miR-382-5p -0.240 miR-31-5p -0.165 miR-872-5p -0.107 miR-1943-5p -0.234 miR-466c-5p -0.165 miR-1957a -0.106 miR-181b-1-3p -0.233 miR-100-5p -0.162 let-7a-1-3p -0.106 miR-345-5p -0.232 miR-24-2-5p -0.161 miR-376a-5p -0.102 miR-342-5p -0.229 miR-140-5p -0.161 miR-542-3p -0.098 miR-322-5p -0.227 miR-134-5p -0.160 miR-135b-3p -0.098
174 Supplemental Table 2. Differential expression of miRNA between Control and Handled female animals Handled (+) relative to Control (-)
ID (Mmu-) Log2 FC ID (Mmu-) Log2 FC ID (Mmu-) Log2 FC miR-214-5p -0.098 miR-30b-3p -0.038 miR-150-5p 0.020 miR-341-5p -0.095 miR-199b-5p -0.037 miR-3963 0.022 miR-210-5p -0.095 miR-219a-1-3p -0.037 miR-212-5p 0.023 miR-431-5p -0.093 miR-652-3p -0.037 miR-106b-3p 0.033 miR-15b-3p -0.092 miR-3473b -0.036 miR-136-3p 0.033 miR-487b-5p -0.089 miR-136-5p -0.031 miR-188-5p 0.033 miR-380-3p -0.087 miR-23b-3p -0.031 miR-467d-5p 0.035 miR-130b-3p -0.086 miR-6412 -0.030 miR-140-3p 0.036 miR-194-2-3p -0.083 miR-106b-5p -0.025 miR-672-5p 0.036 miR-467e-5p -0.077 miR-6944-3p -0.024 miR-300-3p 0.036 miR-3474 -0.072 miR-501-3p -0.023 miR-3473e 0.039 miR-21b -0.072 miR-1843b-3p -0.020 miR-337-3p 0.039 miR-335-3p -0.070 miR-411-5p -0.018 miR-323-5p 0.040 miR-7021-5p -0.069 miR-8103 -0.015 miR-598-3p 0.042 miR-1947-5p -0.069 miR-26b-5p -0.015 miR-125a-3p 0.042 miR-412-3p -0.068 let-7j -0.009 miR-3970 0.044 miR-665-3p -0.066 let-7b-3p -0.008 miR-378b 0.045 miR-669o-3p -0.066 miR-490-3p -0.008 mir-5098-3p_n 0.045 miR-872-3p -0.066 miR-130a-3p -0.005 miR-1193-3p 0.046 miR-6966-3p -0.063 let-7g-5p -0.003 miR-8114 0.050 miR-320-3p -0.062 miR-17-3p 0.002 miR-335-5p 0.052 miR-6540-3p -0.060 miR-191-3p 0.002 miR-379-3p 0.052 miR-466h-3p -0.057 miR-3066-5p 0.002 miR-185-5p 0.052 miR-148b-5p -0.057 miR-7080-3p 0.002 miR-409-5p 0.052 miR-24-3p -0.057 miR-5100 0.002 miR-3081-3p 0.052 miR-5099 -0.056 mir-1954-3p_n 0.002 miR-181a-2-3p 0.055 miR-362-3p -0.056 miR-29b-2-5p 0.002 miR-138-1-3p 0.058 miR-7b-5p -0.053 miR-361-5p 0.002 miR-411-3p 0.059 miR-6952-3p -0.053 miR-199b-3p 0.003 miR-7068-5p 0.060 miR-30c-1-3p -0.052 miR-299a-3p 0.006 miR-27a-3p 0.066 miR-30a-3p -0.048 miR-3072-3p 0.009 miR-5615-5p 0.069 miR-770-3p -0.048 miR-132-5p 0.012 miR-770-5p 0.070 miR-25-3p -0.046 let-7d-3p 0.014 miR-421-3p 0.074 miR-434-3p -0.045 miR-126a-5p 0.016 miR-92b-3p 0.079 miR-329-5p -0.045 miR-3078-5p 0.016 miR-3068-3p 0.080 miR-190a-5p -0.041 miR-361-3p 0.017 miR-103-3p 0.081 miR-135b-5p -0.039 miR-744-5p 0.017 miR-145a-3p 0.081 miR-3068-5p -0.039 let-7f-5p 0.019 miR-1291 0.084
175 Supplemental Table 2. Differential expression of miRNA between Control and Handled female animals Handled (+) relative to Control (-)
ID (Mmu-) Log2 FC ID (Mmu-) Log2 FC ID (Mmu-) Log2 FC miR-28a-3p 0.089 miR-679-5p 0.152 miR-370-3p 0.203 let-7d-5p 0.093 miR-323-3p 0.152 miR-540-3p 0.205 miR-3470b 0.095 miR-674-5p 0.153 miR-331-5p 0.206 mir-3473d-3p_n 0.095 miR-3059-5p 0.153 miR-23a-3p 0.207 miR-369-5p 0.096 miR-3962 0.154 miR-488-3p 0.209 miR-30e-5p 0.097 miR-99b-5p 0.157 miR-149-5p 0.210 miR-153-3p 0.099 miR-493-5p 0.159 miR-344g-3p 0.211 miR-486b-5p 0.101 miR-425-3p 0.159 miR-487b-3p 0.211 miR-532-5p 0.101 miR-300-5p 0.162 miR-676-5p 0.214 miR-29c-5p 0.104 miR-151-5p 0.169 miR-132-3p 0.216 miR-377-3p 0.106 miR-344d-3p 0.169 miR-125b-5p 0.219 miR-30e-3p 0.108 miR-9-3p 0.170 miR-496a-3p 0.222 miR-181d-5p 0.111 miR-652-5p 0.171 let-7c-1-3p 0.223 miR-6914-3p 0.113 miR-667-3p 0.172 miR-381-3p 0.223 miR-297b-3p 0.113 miR-485-3p 0.172 miR-378a-3p 0.228 miR-297c-3p 0.113 let-7g-3p 0.174 miR-142a-5p 0.228 let-7i-5p 0.113 miR-494-3p 0.175 miR-324-3p 0.230 miR-212-3p 0.114 miR-582-3p 0.175 miR-1843b-5p 0.230 miR-30a-5p 0.115 miR-142a-3p 0.176 miR-6240 0.232 miR-486a-5p 0.115 miR-676-3p 0.176 miR-671-3p 0.232 miR-425-5p 0.123 miR-125a-5p 0.178 miR-137-5p 0.233 miR-346-5p 0.125 miR-127-3p 0.179 miR-337-5p 0.234 miR-331-3p 0.126 miR-378a-5p 0.180 miR-500-3p 0.234 miR-674-3p 0.134 miR-199a-5p 0.181 miR-6239 0.237 miR-541-5p 0.136 miR-543-5p 0.182 miR-139-5p 0.237 miR-107-3p 0.137 miR-30d-5p 0.183 miR-376b-3p 0.237 miR-124-5p 0.139 miR-181c-3p 0.183 miR-299a-5p 0.238 miR-7a-2-3p 0.140 miR-350-3p 0.185 miR-22-3p 0.242 miR-186-5p 0.140 miR-669d-5p 0.186 miR-30b-5p 0.245 miR-339-3p 0.140 miR-26a-2-3p 0.187 miR-667-5p 0.246 mir-6240-3p_n 0.140 miR-382-3p 0.189 miR-101c 0.247 miR-341-3p 0.142 miR-495-3p 0.190 miR-378d 0.249 miR-1843a-3p 0.146 miR-15a-5p 0.190 miR-3085-3p 0.258 miR-374b-5p 0.146 miR-99b-3p 0.191 miR-5121 0.261 miR-129-5p 0.147 miR-138-2-3p 0.194 miR-146b-5p 0.262 miR-27a-5p 0.149 miR-532-3p 0.196 miR-101b-3p 0.263 miR-144-5p 0.151 miR-6516-5p 0.199 miR-3473a 0.265 miR-539-5p 0.151 miR-122-5p 0.203 miR-1966-3p 0.265
176 Supplemental Table 2. Differential expression of miRNA between Control and Handled female animals Handled (+) relative to Control (-)
ID (Mmu-) Log2 FC ID (Mmu-) Log2 FC ID (Mmu-) Log2 FC miR-409-3p 0.270 miR-326-3p 0.359 miR-874-5p 0.454 miR-127-5p 0.271 miR-7a-1-3p 0.361 miR-33-3p 0.457 miR-6937-5p 0.273 miR-664-5p 0.363 let-7b-5p 0.459 miR-181c-5p 0.274 miR-26a-5p 0.363 miR-150-3p 0.461 miR-6236 0.277 miR-329-3p 0.364 miR-671-5p 0.462 miR-191-5p 0.278 miR-7073-5p 0.364 miR-195a-3p 0.463 miR-369-3p 0.279 miR-1843a-5p 0.366 miR-221-3p 0.474 miR-3086-5p 0.279 miR-128-3p 0.368 miR-342-3p 0.491 miR-1194 0.279 miR-16-5p 0.368 miR-324-5p 0.492 miR-664-3p 0.281 miR-379-5p 0.371 miR-139-3p 0.492 miR-184-3p 0.282 miR-3535 0.371 miR-3102-3p 0.495 miR-328-3p 0.285 miR-9-5p 0.371 miR-143-5p 0.507 miR-672-3p 0.285 miR-6238 0.373 miR-146a-5p 0.508 let-7c-5p 0.286 miR-3064-5p 0.376 miR-1193-5p 0.508 miR-99a-3p 0.287 miR-8120 0.380 miR-488-5p 0.510 miR-30c-2-3p 0.287 miR-673-5p 0.380 miR-218-5p 0.510 miR-497a-5p 0.293 miR-504-5p 0.383 miR-124-3p 0.510 miR-148a-3p 0.293 miR-491-5p 0.383 miR-7240-5p 0.511 miR-376a-3p 0.295 miR-22-5p 0.384 miR-29a-3p 0.513 miR-1258-3p 0.297 miR-101a-3p 0.389 miR-154-5p 0.518 miR-483-5p 0.301 miR-7664-3p 0.394 miR-125b-2-3p 0.523 miR-218-1-3p 0.301 miR-29c-3p 0.394 miR-6395 0.543 miR-187-3p 0.305 miR-25-5p 0.397 miR-708-5p 0.547 miR-677-5p 0.310 miR-145a-5p 0.400 miR-708-3p 0.550 miR-33-5p 0.315 miR-370-5p 0.402 miR-222-3p 0.559 miR-154-3p 0.316 miR-28a-5p 0.408 miR-486a-3p 0.562 miR-3082-3p 0.322 miR-99a-5p 0.412 mir-3535-3p_n 0.564 miR-7015-3p 0.323 miR-6418-3p 0.417 miR-5129-3p 0.564 miR-7047-3p 0.323 miR-5621-3p 0.417 miR-1306-5p 0.566 let-7e-5p 0.324 miR-540-5p 0.423 miR-877-5p 0.577 miR-138-5p 0.326 miR-592-5p 0.423 miR-669l-5p 0.586 miR-344d-3-5p 0.329 miR-582-5p 0.435 miR-467a-3p 0.622 miR-673-3p 0.333 let-7k 0.439 miR-467d-3p 0.622 miR-574-5p 0.342 miR-137-3p 0.443 miR-6516-3p 0.623 miR-485-5p 0.348 miR-493-3p 0.446 miR-377-5p 0.634 miR-155-5p 0.349 miR-148a-5p 0.447 miR-129-2-3p 0.657 miR-376b-5p 0.350 miR-143-3p 0.454 miR-129-1-3p 0.668 let-7i-3p 0.359 miR-702-3p 0.454 miR-29a-5p 0.681
177 Supplemental Table 2. Differential expression of miRNA between Control and Handled female animals Handled (+) relative to Control (-)
ID (Mmu-) Log2 FC miR-221-5p 0.683 miR-29b-3p 0.693 miR-6390 0.699 miR-6948-3p 0.702 miR-218-2-3p 0.708 miR-6899-3p 0.715 miR-222-5p 0.730 miR-6948-5p 0.761 miR-146b-3p 0.809 miR-1195 0.811 miR-128-2-5p 0.816 miR-195a-5p 0.827 miR-203-3p 0.828 miR-874-3p 0.829 miR-466d-3p 0.833 miR-214-3p 0.840 miR-881-3p 0.850 miR-376c-3p 0.917 miR-134-3p 0.921 miR-544-3p 0.956 miR-128-1-5p 1.026 miR-3083-5p 1.053 miR-200c-3p 1.066 miR-935 1.110 miR-223-3p 1.224 miR-153-5p 1.224 miR-200a-5p 1.243 mir-6236-5p_n 1.272 miR-135a-1-3p 1.318 miR-200b-3p 1.335 miR-429-3p 1.485 miR-182-5p 1.530 miR-551b-3p 1.584 miR-96-5p 1.586 miR-183-5p 1.816 miR-200a-3p 1.946
178 Supplemental Table 3. Differential expression of miRNA between Control and Vehicle-treated female animals Vehicle (+) relative to Control (-)
ID (Mmu-) Log2 FC ID (Mmu-) Log2 FC ID (Mmu-) Log2 FC miR-1912-3p -2.621 miR-98-3p -0.643 miR-1964-3p -0.436 miR-1298-5p -2.556 miR-764-5p -0.641 let-7f-1-3p -0.426 miR-448-3p -2.388 miR-1193-5p -0.640 miR-666-5p -0.424 miR-1264-3p -1.931 miR-6395 -0.631 miR-1981-5p -0.414 miR-3061-5p -1.612 miR-1968-5p -0.616 miR-673-5p -0.411 miR-483-3p -1.601 miR-466a-3p -0.613 miR-17-5p -0.406 miR-1264-5p -1.421 miR-449a-5p -0.598 miR-7021-5p -0.406 miR-653-5p -1.324 miR-350-5p -0.598 miR-322-3p -0.402 miR-6977-3p -1.266 miR-1927 -0.595 let-7f-2-3p -0.397 miR-450b-5p -1.226 miR-337-3p -0.580 miR-412-5p -0.392 miR-1298-3p -1.192 miR-133b-3p -0.579 miR-412-3p -0.392 miR-204-5p -1.130 miR-1197-3p -0.568 miR-335-3p -0.389 miR-34b-5p -1.094 miR-219a-5p -0.563 miR-130a-3p -0.388 miR-204-3p -1.084 miR-217-5p -0.554 miR-338-5p -0.386 miR-34c-5p -1.079 miR-3087-3p -0.554 miR-6540-5p -0.384 miR-1943-5p -1.045 miR-342-3p -0.539 miR-3064-5p -0.381 miR-448-5p -0.983 miR-212-3p -0.532 miR-187-5p -0.378 miR-466i-3p -0.977 miR-466e-3p -0.530 miR-106b-5p -0.375 miR-1982-3p -0.977 miR-466p-3p -0.530 miR-325-3p -0.368 miR-224-5p -0.966 miR-152-5p -0.515 miR-345-5p -0.368 miR-3552 -0.962 miR-331-5p -0.509 miR-592-5p -0.367 miR-34c-3p -0.929 miR-219a-2-3p -0.507 miR-1258-3p -0.366 miR-211-5p -0.925 miR-450a-5p -0.501 miR-100-5p -0.358 miR-3061-3p -0.920 miR-6540-3p -0.491 miR-16-1-3p -0.358 miR-3069-3p -0.839 miR-15b-3p -0.491 miR-297b-3p -0.357 let-7a-2-3p -0.801 miR-547-3p -0.486 miR-297c-3p -0.357 miR-34b-3p -0.795 miR-3473f -0.479 miR-27b-5p -0.356 miR-93-3p -0.778 miR-219c-5p -0.479 miR-3081-3p -0.354 miR-503-5p -0.770 miR-296-5p -0.479 miR-31-3p -0.351 miR-7226-3p -0.764 miR-503-3p -0.478 miR-193b-3p -0.351 miR-2137 -0.736 miR-383-5p -0.456 miR-181b-1-3p -0.343 miR-154-3p -0.727 miR-5100 -0.451 miR-362-3p -0.337 miR-344h-3p -0.692 miR-6911-3p -0.451 miR-21c -0.335 miR-487b-5p -0.671 miR-665-3p -0.447 miR-3474 -0.335 miR-298-5p -0.669 miR-322-5p -0.445 miR-3057-5p -0.333 miR-1249-3p -0.663 miR-539-5p -0.441 miR-542-3p -0.332 miR-1981-3p -0.645 miR-190b-5p -0.439 miR-466c-5p -0.325 miR-342-5p -0.644 miR-351-5p -0.437 miR-3093-3p -0.319
179 Supplemental Table 3. Differential expression of miRNA between Control and Vehicle-treated female animals Vehicle (+) relative to Control (-)
ID (Mmu-) Log2 FC ID (Mmu-) Log2 FC ID (Mmu-) Log2 FC miR-505-3p -0.317 miR-20a-5p -0.235 miR-700-3p -0.154 miR-574-5p -0.314 miR-339-5p -0.234 miR-410-5p -0.154 miR-365-3p -0.312 miR-299a-3p -0.233 miR-377-3p -0.154 miR-540-5p -0.312 miR-1188-5p -0.230 miR-500-3p -0.152 miR-30c-1-3p -0.309 miR-122-5p -0.228 miR-541-3p -0.151 miR-10b-5p -0.308 miR-190a-5p -0.222 miR-679-5p -0.150 miR-344f-3p -0.305 miR-877-3p -0.221 miR-6952-3p -0.147 miR-668-3p -0.300 miR-139-3p -0.219 miR-30b-5p -0.146 miR-7068-5p -0.299 miR-431-3p -0.218 miR-341-3p -0.142 miR-8112 -0.299 miR-700-5p -0.213 miR-15a-5p -0.142 miR-744-3p -0.299 miR-652-3p -0.212 miR-142a-3p -0.141 miR-1193-3p -0.293 miR-466f-3p -0.210 miR-136-3p -0.141 miR-409-5p -0.291 miR-32-5p -0.207 miR-350-3p -0.140 miR-210-3p -0.290 miR-3473e -0.207 miR-1191a -0.139 miR-10a-5p -0.290 miR-7b-5p -0.203 miR-192-5p -0.136 miR-19b-3p -0.282 miR-484 -0.199 miR-30b-3p -0.130 miR-181a-1-3p -0.281 miR-497b -0.199 miR-770-3p -0.127 miR-380-5p -0.278 miR-375-3p -0.197 miR-300-3p -0.127 miR-8114 -0.274 miR-674-5p -0.185 miR-132-3p -0.123 miR-106b-3p -0.274 miR-300-5p -0.183 miR-496a-3p -0.122 miR-3099-3p -0.273 miR-466g -0.180 miR-23b-3p -0.121 miR-3072-3p -0.270 miR-491-5p -0.180 miR-320-3p -0.121 miR-193a-5p -0.270 miR-667-3p -0.178 miR-7080-5p -0.118 miR-466h-3p -0.270 miR-423-5p -0.175 miR-369-3p -0.117 miR-6914-3p -0.270 miR-21b -0.171 miR-329-3p -0.116 miR-206-3p -0.265 miR-331-3p -0.169 miR-3084-3p -0.116 miR-3963 -0.258 miR-421-3p -0.168 let-7d-3p -0.112 miR-338-3p -0.257 miR-664-3p -0.167 miR-299a-5p -0.111 miR-212-5p -0.255 miR-362-5p -0.165 miR-378b -0.109 miR-3968 -0.255 miR-188-5p -0.161 miR-337-5p -0.108 miR-15b-5p -0.253 miR-431-5p -0.160 miR-486b-5p -0.107 miR-137-5p -0.253 miR-125b-1-3p -0.159 miR-7080-3p -0.104 miR-34a-5p -0.248 miR-151-5p -0.159 miR-467e-5p -0.103 miR-335-5p -0.246 miR-582-3p -0.157 miR-486a-5p -0.102 miR-3085-3p -0.245 miR-194-2-3p -0.156 miR-323-3p -0.101 miR-361-5p -0.242 miR-134-5p -0.155 miR-1198-5p -0.098 miR-296-3p -0.237 miR-27b-3p -0.155 miR-532-3p -0.096 miR-92a-3p -0.235 miR-148b-3p -0.155 let-7i-3p -0.095
180 Supplemental Table 3. Differential expression of miRNA between Control and Vehicle-treated female animals Vehicle (+) relative to Control (-)
ID (Mmu-) Log2 FC ID (Mmu-) Log2 FC ID (Mmu-) Log2 FC miR-669c-5p -0.093 miR-30c-2-3p -0.053 miR-92b-3p -0.005 miR-379-3p -0.091 miR-138-5p -0.048 mir-1954-3p_n -0.003 miR-185-3p -0.090 miR-23b-5p -0.048 miR-3970 -0.002 miR-758-3p -0.088 miR-3962 -0.047 miR-574-3p 0.000 miR-345-3p -0.086 miR-181b-5p -0.047 let-7e-3p 0.001 miR-374b-5p -0.086 miR-103-3p -0.047 miR-410-3p 0.001 miR-186-5p -0.085 miR-384-3p -0.046 let-7b-3p 0.002 miR-21a-5p -0.085 miR-194-5p -0.042 miR-494-3p 0.004 miR-138-2-3p -0.082 miR-138-1-3p -0.041 miR-154-5p 0.005 let-7c-1-3p -0.081 miR-455-3p -0.041 miR-346-5p 0.008 miR-344-3p -0.079 miR-92b-5p -0.041 miR-152-3p 0.009 miR-672-5p -0.079 miR-23a-3p -0.039 miR-8103 0.013 miR-215-5p -0.076 miR-3086-5p -0.039 miR-676-3p 0.015 miR-7a-5p -0.076 miR-151-3p -0.039 miR-132-5p 0.015 miR-409-3p -0.074 miR-191-3p -0.039 miR-376a-5p 0.016 miR-669p-5p -0.074 miR-325-5p -0.038 miR-30c-5p 0.016 miR-127-5p -0.074 miR-8120 -0.036 miR-181a-5p 0.017 miR-708-5p -0.072 miR-3068-5p -0.034 miR-31-5p 0.017 miR-344b-3p -0.070 miR-466d-3p -0.031 miR-467c-5p 0.021 miR-872-3p -0.069 miR-467a-3p -0.031 miR-361-3p 0.022 miR-669o-3p -0.069 miR-467d-3p -0.031 miR-1957a 0.022 miR-340-5p -0.069 miR-1291 -0.030 miR-124-5p 0.023 miR-101c -0.068 miR-324-3p -0.030 miR-466i-5p 0.023 miR-3473b -0.068 miR-26b-3p -0.029 let-7j 0.023 miR-532-5p -0.066 miR-323-5p -0.028 miR-3068-3p 0.024 miR-543-5p -0.066 miR-382-5p -0.027 miR-434-3p 0.025 miR-380-3p -0.066 miR-326-3p -0.026 miR-493-3p 0.028 miR-541-5p -0.065 miR-673-3p -0.022 miR-301a-5p 0.028 miR-133a-3p -0.063 miR-181c-3p -0.022 miR-676-5p 0.029 miR-140-3p -0.063 miR-6239 -0.022 miR-879-5p 0.030 miR-93-5p -0.062 miR-382-3p -0.021 miR-148b-5p 0.032 miR-455-5p -0.061 miR-150-5p -0.020 miR-329-5p 0.034 miR-467b-5p -0.060 miR-744-5p -0.014 miR-144-3p 0.034 miR-467a-5p -0.060 miR-1224-5p -0.011 miR-379-5p 0.035 miR-1306-3p -0.058 miR-487b-3p -0.011 miR-30a-3p 0.036 miR-874-5p -0.055 miR-6412 -0.007 miR-219a-1-3p 0.038 miR-107-3p -0.054 miR-185-5p -0.005 miR-344g-3p 0.041 miR-433-3p -0.054 miR-485-3p -0.005 miR-370-5p 0.041
181 Supplemental Table 3. Differential expression of miRNA between Control and Vehicle-treated female animals Vehicle (+) relative to Control (-)
ID (Mmu-) Log2 FC ID (Mmu-) Log2 FC ID (Mmu-) Log2 FC miR-29c-3p 0.042 miR-485-5p 0.091 let-7e-5p 0.137 miR-98-5p 0.043 miR-140-5p 0.092 miR-99b-5p 0.139 miR-148a-3p 0.046 miR-3083-5p 0.092 miR-199b-3p 0.140 miR-433-5p 0.048 miR-16-5p 0.093 miR-543-3p 0.141 miR-137-3p 0.049 miR-501-3p 0.093 miR-677-5p 0.142 miR-1a-3p 0.050 miR-544-3p 0.094 miR-5099 0.143 miR-872-5p 0.052 miR-879-3p 0.094 miR-191-5p 0.146 miR-5121 0.054 miR-376b-3p 0.095 miR-27a-3p 0.149 miR-127-3p 0.055 miR-3078-5p 0.096 miR-3074-5p 0.149 miR-101b-3p 0.055 miR-153-3p 0.096 miR-411-5p 0.149 miR-30d-3p 0.056 miR-136-5p 0.096 let-7a-5p 0.150 miR-148a-5p 0.057 mir-5098-3p_n 0.097 miR-378a-3p 0.151 miR-495-3p 0.059 miR-144-5p 0.098 miR-376a-3p 0.153 miR-29c-5p 0.059 miR-582-5p 0.099 miR-672-3p 0.155 let-7g-3p 0.060 miR-411-3p 0.102 miR-130b-5p 0.158 miR-135a-1-3p 0.060 miR-423-3p 0.102 let-7f-5p 0.158 miR-330-3p 0.060 miR-24-1-5p 0.104 miR-124-3p 0.163 miR-25-3p 0.060 miR-344c-3p 0.105 miR-129-5p 0.164 miR-135a-5p 0.060 let-7i-5p 0.112 miR-1843b-5p 0.168 miR-6481 0.064 miR-425-3p 0.114 miR-24-3p 0.168 miR-704 0.066 miR-1843a-3p 0.115 miR-125a-3p 0.169 miR-181a-2-3p 0.066 miR-101a-3p 0.117 miR-9-5p 0.173 miR-760-3p 0.067 miR-99b-3p 0.117 miR-666-3p 0.173 miR-6240 0.068 miR-378a-5p 0.117 miR-770-5p 0.175 miR-490-3p 0.070 miR-135a-2-3p 0.117 miR-28a-3p 0.177 miR-139-5p 0.071 miR-598-3p 0.118 miR-708-3p 0.181 mir-3535-3p_n 0.073 let-7a-1-3p 0.118 miR-671-5p 0.184 miR-488-3p 0.076 let-7c-2-3p 0.119 miR-146a-5p 0.184 miR-467d-5p 0.077 miR-877-5p 0.120 miR-149-5p 0.190 miR-126a-5p 0.078 miR-328-3p 0.120 let-7d-5p 0.192 miR-540-3p 0.078 miR-674-3p 0.124 miR-9-3p 0.193 miR-381-3p 0.079 miR-1251-5p 0.124 miR-3572-3p 0.193 miR-5621-3p 0.080 miR-384-5p 0.124 let-7g-5p 0.195 miR-340-3p 0.083 miR-3082-3p 0.125 miR-425-5p 0.196 miR-7236-3p 0.085 miR-6937-5p 0.129 miR-30a-5p 0.197 miR-3093-5p 0.087 miR-30e-3p 0.131 miR-30d-5p 0.202 miR-142a-5p 0.089 miR-181d-5p 0.134 miR-128-1-5p 0.203 miR-493-5p 0.091 miR-7224-3p 0.134 miR-6896-5p 0.205
182 Supplemental Table 3. Differential expression of miRNA between Control and Vehicle-treated female animals Vehicle (+) relative to Control (-)
ID (Mmu-) Log2 FC ID (Mmu-) Log2 FC ID (Mmu-) Log2 FC miR-330-5p 0.205 miR-135b-5p 0.271 miR-143-3p 0.400 miR-6390 0.206 miR-5620-5p 0.286 miR-3059-5p 0.411 miR-26b-5p 0.208 miR-218-2-3p 0.286 miR-29a-5p 0.413 miR-100-3p 0.212 miR-501-5p 0.286 miR-26a-2-3p 0.418 miR-30e-5p 0.212 miR-1194 0.286 miR-3535 0.425 miR-6516-5p 0.214 miR-6516-3p 0.286 miR-7a-1-3p 0.425 miR-369-5p 0.216 miR-1966-3p 0.286 miR-365-1-5p 0.431 miR-7073-5p 0.216 miR-221-5p 0.289 miR-1843b-3p 0.436 miR-129-2-3p 0.221 miR-3102-3p 0.289 miR-3473a 0.445 miR-27a-5p 0.223 miR-222-3p 0.292 miR-125b-2-3p 0.448 miR-1306-5p 0.224 miR-1947-5p 0.303 let-7c-5p 0.450 miR-22-3p 0.224 miR-24-2-5p 0.313 miR-22-5p 0.452 miR-221-3p 0.225 miR-135b-3p 0.318 miR-6944-3p 0.453 miR-434-5p 0.225 miR-370-3p 0.321 miR-377-5p 0.456 mir-6240-3p_n 0.230 miR-3470a 0.323 miR-497a-5p 0.462 miR-341-5p 0.230 miR-6945-3p 0.329 let-7b-5p 0.468 miR-125b-5p 0.232 miR-99a-3p 0.331 miR-3470b 0.476 miR-376c-3p 0.233 miR-199a-5p 0.339 miR-218-1-3p 0.493 miR-667-5p 0.233 miR-146b-5p 0.340 miR-203-3p 0.500 miR-7a-2-3p 0.234 miR-26a-5p 0.343 miR-505-5p 0.500 miR-125a-5p 0.234 miR-128-3p 0.344 miR-490-5p 0.507 miR-216b-5p 0.238 miR-6966-3p 0.348 miR-128-2-5p 0.512 miR-210-5p 0.239 miR-129-1-3p 0.349 miR-339-3p 0.521 miR-193b-5p 0.243 miR-669d-5p 0.351 miR-874-3p 0.522 miR-33-3p 0.245 miR-17-3p 0.353 miR-134-3p 0.527 miR-29b-3p 0.246 miR-3084-5p 0.353 miR-187-3p 0.528 miR-1843a-5p 0.250 miR-146b-3p 0.357 miR-195a-5p 0.531 miR-324-5p 0.253 miR-145a-3p 0.359 miR-7047-3p 0.534 miR-222-5p 0.253 miR-6236 0.360 miR-99a-5p 0.537 miR-181c-5p 0.257 miR-126a-3p 0.361 miR-214-5p 0.549 miR-378d 0.257 miR-199b-5p 0.361 miR-669o-5p 0.559 miR-664-5p 0.262 miR-6418-3p 0.364 miR-702-3p 0.562 miR-29a-3p 0.263 miR-7664-3p 0.374 miR-488-5p 0.563 miR-3066-5p 0.265 let-7k 0.374 miR-218-5p 0.573 miR-29b-2-5p 0.270 miR-184-3p 0.375 miR-483-5p 0.586 miR-145a-5p 0.270 miR-7015-3p 0.386 miR-6948-5p 0.586 miR-376b-5p 0.270 miR-486a-3p 0.391 miR-33-5p 0.600 miR-671-3p 0.271 miR-504-5p 0.394 miR-344d-3p 0.600
183 Supplemental Table 3. Differential expression of miRNA between Control and Vehicle-treated female animals Vehicle (+) relative to Control (-)
ID (Mmu-) Log2 FC miR-7689-3p 0.601 miR-143-5p 0.605 miR-935 0.620 miR-5129-3p 0.632 miR-130b-3p 0.658 miR-195a-3p 0.661 miR-1195 0.661 miR-28a-5p 0.669 miR-652-5p 0.679 miR-7240-5p 0.715 miR-669l-5p 0.727 miR-7043-3p 0.743 miR-344d-3-5p 0.743 miR-5615-5p 0.752 miR-499-5p 0.760 mir-3473d-3p_n 0.772 miR-25-5p 0.793 miR-214-3p 0.797 miR-551b-3p 0.823 miR-6948-3p 0.871 miR-6899-3p 0.890 miR-6238 0.899 miR-150-3p 0.911 miR-155-5p 0.914 miR-223-3p 0.924 miR-153-5p 1.071 mir-6236-5p_n 1.117 miR-881-3p 1.334 miR-200b-3p 1.648 miR-200a-5p 1.745 miR-429-3p 1.842 miR-200c-3p 1.987 miR-200a-3p 2.341 miR-182-5p 2.373 miR-96-5p 2.585 miR-183-5p 2.733
184 Supplemental Table 4. Differential expression of miRNA between Control and Estradiol-treated female animals Estradiol (+) relative to Control (-)
ID (Mmu-) Log2 FC ID (Mmu-) Log2 FC ID (Mmu-) Log2 FC miR-1912-3p -5.822 miR-2137 -0.913 miR-503-5p -0.607 miR-1298-5p -4.478 miR-193a-5p -0.904 miR-193b-3p -0.579 miR-448-3p -4.329 miR-338-3p -0.886 miR-365-3p -0.572 miR-1264-3p -3.114 miR-3057-5p -0.875 miR-15b-5p -0.570 miR-34b-5p -2.953 miR-187-5p -0.874 miR-3087-3p -0.557 miR-34c-3p -2.945 miR-10b-5p -0.858 miR-6540-5p -0.544 miR-653-5p -2.803 miR-34a-5p -0.832 miR-3078-5p -0.538 miR-34c-5p -2.702 miR-342-5p -0.821 miR-505-3p -0.534 miR-34b-3p -2.685 miR-483-3p -0.806 miR-6390 -0.531 miR-448-5p -2.592 miR-700-3p -0.805 miR-7080-5p -0.529 miR-1264-5p -2.591 miR-26b-3p -0.794 miR-27b-5p -0.527 miR-764-5p -2.381 miR-6914-3p -0.788 miR-20a-5p -0.524 miR-204-5p -2.123 miR-92a-3p -0.771 miR-6540-3p -0.523 miR-216b-5p -1.968 miR-466g -0.771 miR-467e-5p -0.518 miR-217-5p -1.967 miR-133a-3p -0.760 miR-6911-3p -0.515 miR-3552 -1.905 miR-337-3p -0.758 miR-21b -0.512 miR-204-3p -1.811 miR-501-5p -0.752 miR-3061-3p -0.504 miR-211-5p -1.766 miR-1968-5p -0.747 miR-6977-3p -0.497 miR-1298-3p -1.636 miR-547-3p -0.743 miR-155-5p -0.497 miR-219a-2-3p -1.605 miR-5620-5p -0.729 miR-433-3p -0.494 miR-224-5p -1.600 miR-487b-5p -0.719 miR-7224-3p -0.489 miR-6481 -1.537 miR-344h-3p -0.717 miR-297b-3p -0.489 miR-219a-5p -1.411 miR-210-5p -0.711 miR-297c-3p -0.489 miR-449a-5p -1.342 miR-100-3p -0.707 miR-879-5p -0.478 miR-338-5p -1.324 miR-21c -0.707 miR-92b-5p -0.478 miR-206-3p -1.320 miR-23b-5p -0.703 miR-17-5p -0.474 miR-375-3p -1.289 miR-362-3p -0.702 miR-219c-5p -0.473 let-7a-2-3p -1.232 miR-8114 -0.683 let-7f-1-3p -0.473 miR-1197-3p -1.229 miR-466h-3p -0.681 miR-98-3p -0.466 miR-133b-3p -1.125 miR-3061-5p -0.679 miR-672-3p -0.461 miR-190b-5p -1.023 miR-466c-5p -0.672 miR-6966-3p -0.461 miR-93-3p -0.999 miR-325-5p -0.653 miR-700-5p -0.447 miR-298-5p -0.994 miR-342-3p -0.650 miR-144-5p -0.445 miR-8112 -0.982 miR-669p-5p -0.643 miR-666-5p -0.438 miR-1249-3p -0.976 miR-301a-5p -0.639 miR-7689-3p -0.438 miR-1927 -0.974 miR-702-3p -0.633 miR-362-5p -0.435 miR-350-5p -0.970 miR-1251-5p -0.631 miR-1982-3p -0.430 miR-8103 -0.966 miR-758-3p -0.620 miR-15b-3p -0.430
185 Supplemental Table 4. Differential expression of miRNA between Control and Estradiol-treated female animals Estradiol (+) relative to Control (-)
ID (Mmu-) Log2 FC ID (Mmu-) Log2 FC ID (Mmu-) Log2 FC miR-3069-3p -0.430 miR-3963 -0.330 miR-188-5p -0.207 miR-6952-3p -0.430 miR-423-3p -0.323 miR-320-3p -0.206 miR-6945-3p -0.430 miR-412-3p -0.321 miR-30b-3p -0.204 miR-665-3p -0.430 miR-135a-5p -0.319 miR-339-5p -0.204 miR-431-5p -0.422 miR-6418-3p -0.314 let-7b-3p -0.196 miR-652-3p -0.420 miR-1957a -0.313 miR-466f-3p -0.194 miR-1191a -0.412 miR-1306-5p -0.312 miR-382-5p -0.194 miR-450b-5p -0.411 miR-423-5p -0.303 miR-98-5p -0.194 miR-877-3p -0.403 miR-494-3p -0.303 miR-151-3p -0.193 miR-194-2-3p -0.403 miR-345-3p -0.303 miR-497b -0.193 miR-181b-5p -0.403 miR-541-3p -0.301 miR-340-3p -0.193 miR-1943-5p -0.391 miR-484 -0.296 miR-384-3p -0.189 miR-450a-5p -0.389 miR-92b-3p -0.295 miR-874-5p -0.186 miR-3099-3p -0.388 miR-3072-3p -0.291 miR-344b-3p -0.186 miR-760-3p -0.387 miR-185-5p -0.286 miR-467c-5p -0.185 miR-3572-3p -0.385 miR-25-5p -0.285 miR-192-5p -0.179 miR-412-5p -0.374 miR-323-3p -0.282 miR-466a-3p -0.178 miR-1a-3p -0.372 miR-130b-5p -0.276 miR-425-3p -0.176 miR-32-5p -0.366 miR-3093-3p -0.274 miR-142a-5p -0.174 miR-21a-5p -0.365 miR-455-3p -0.270 miR-500-3p -0.174 miR-296-5p -0.363 miR-100-5p -0.268 miR-151-5p -0.172 miR-6239 -0.359 miR-31-5p -0.266 miR-351-5p -0.171 miR-486b-5p -0.359 miR-185-3p -0.259 miR-215-5p -0.167 miR-296-3p -0.357 miR-330-3p -0.254 miR-27a-3p -0.165 miR-486a-5p -0.357 miR-669c-5p -0.249 miR-1193-3p -0.161 miR-7a-5p -0.357 miR-365-1-5p -0.235 miR-7080-3p -0.159 miR-350-3p -0.357 miR-16-1-3p -0.234 miR-25-3p -0.157 miR-138-1-3p -0.353 miR-134-3p -0.234 miR-135a-2-3p -0.156 miR-3473f -0.347 miR-503-3p -0.229 miR-23b-3p -0.155 miR-501-3p -0.347 miR-543-5p -0.228 miR-410-3p -0.154 miR-210-3p -0.346 miR-667-3p -0.225 miR-212-3p -0.143 miR-344f-3p -0.345 miR-3968 -0.222 miR-532-5p -0.140 miR-669o-5p -0.342 miR-125b-1-3p -0.220 miR-106b-3p -0.139 miR-27b-3p -0.338 let-7d-3p -0.218 miR-433-5p -0.137 miR-668-3p -0.337 miR-383-5p -0.216 miR-181a-5p -0.137 miR-7b-5p -0.335 miR-1188-5p -0.214 miR-93-5p -0.137 miR-539-5p -0.333 miR-30c-1-3p -0.210 miR-421-3p -0.136 miR-31-3p -0.330 miR-135b-3p -0.207 miR-543-3p -0.134
186 Supplemental Table 4. Differential expression of miRNA between Control and Estradiol-treated female animals Estradiol (+) relative to Control (-)
ID (Mmu-) Log2 FC ID (Mmu-) Log2 FC ID (Mmu-) Log2 FC let-7g-3p -0.134 let-7e-3p -0.056 miR-324-3p 0.010 miR-212-5p -0.128 miR-669o-3p -0.056 miR-3084-5p 0.011 miR-495-3p -0.124 miR-1258-3p -0.056 miR-7047-3p 0.013 miR-344-3p -0.121 miR-26b-5p -0.053 miR-380-5p 0.016 miR-199b-5p -0.119 miR-667-5p -0.052 miR-1981-3p 0.028 miR-5100 -0.116 miR-331-3p -0.051 miR-322-5p 0.029 miR-666-3p -0.113 miR-770-3p -0.050 miR-194-5p 0.031 miR-134-5p -0.111 miR-431-3p -0.050 miR-1291 0.032 miR-664-3p -0.108 miR-5121 -0.050 let-7a-5p 0.033 miR-369-3p -0.105 miR-3473e -0.048 let-7c-2-3p 0.034 miR-26a-2-3p -0.104 miR-674-5p -0.044 miR-770-5p 0.034 miR-23a-3p -0.098 miR-1964-3p -0.042 let-7a-1-3p 0.034 miR-505-5p -0.096 mir-1954-3p_n -0.041 miR-384-5p 0.035 miR-125a-5p -0.096 miR-434-3p -0.039 miR-138-5p 0.036 miR-672-5p -0.093 miR-19b-3p -0.038 let-7i-3p 0.041 miR-106b-5p -0.090 miR-6944-3p -0.034 miR-380-3p 0.044 miR-328-3p -0.088 miR-1194 -0.031 miR-6395 0.045 miR-181a-1-3p -0.086 miR-30c-2-3p -0.027 let-7f-2-3p 0.052 miR-872-3p -0.083 miR-99b-3p -0.027 miR-541-5p 0.056 miR-872-5p -0.082 miR-361-3p -0.022 miR-214-5p 0.056 miR-487b-3p -0.082 miR-532-3p -0.022 miR-138-2-3p 0.057 miR-361-5p -0.081 miR-3473b -0.022 miR-345-5p 0.058 miR-493-5p -0.080 miR-148b-5p -0.021 miR-335-5p 0.058 miR-346-5p -0.080 miR-376a-5p -0.020 miR-337-5p 0.059 miR-486a-3p -0.079 miR-466p-3p -0.016 miR-598-3p 0.066 miR-181b-1-3p -0.079 miR-329-3p -0.015 miR-582-3p 0.066 miR-3064-5p -0.076 miR-129-2-3p -0.012 miR-24-3p 0.068 miR-340-5p -0.073 miR-3084-3p -0.010 miR-190a-5p 0.069 miR-149-5p -0.073 miR-99b-5p -0.009 miR-191-5p 0.071 miR-3093-5p -0.071 miR-574-5p -0.007 miR-140-3p 0.072 miR-1198-5p -0.069 miR-219a-1-3p -0.005 miR-409-5p 0.072 miR-186-5p -0.069 miR-466e-3p -0.003 miR-137-5p 0.074 miR-330-5p -0.069 miR-326-3p 0.000 miR-409-3p 0.074 miR-3970 -0.066 miR-181a-2-3p 0.001 miR-124-5p 0.076 miR-6412 -0.063 miR-103-3p 0.004 miR-125a-3p 0.076 miR-455-5p -0.062 miR-144-3p 0.005 miR-107-3p 0.083 miR-485-3p -0.059 miR-140-5p 0.009 miR-28a-3p 0.085 let-7j -0.058 miR-379-3p 0.009 let-7g-5p 0.089
187 Supplemental Table 4. Differential expression of miRNA between Control and Estradiol-treated female animals Estradiol (+) relative to Control (-)
ID (Mmu-) Log2 FC ID (Mmu-) Log2 FC ID (Mmu-) Log2 FC miR-877-5p 0.092 miR-24-1-5p 0.171 miR-130b-3p 0.238 miR-150-5p 0.093 miR-322-3p 0.171 miR-181c-3p 0.239 miR-299a-5p 0.094 miR-1195 0.173 miR-199b-3p 0.240 let-7i-5p 0.094 miR-30d-5p 0.175 miR-214-3p 0.240 let-7d-5p 0.095 miR-744-3p 0.178 miR-3068-3p 0.246 miR-7240-5p 0.099 miR-574-3p 0.180 let-7e-5p 0.248 miR-335-3p 0.102 miR-410-5p 0.180 miR-673-5p 0.248 miR-496a-3p 0.103 miR-3074-5p 0.181 miR-3059-5p 0.250 miR-7226-3p 0.105 miR-1224-5p 0.183 miR-30b-5p 0.255 miR-378a-5p 0.105 miR-411-3p 0.186 miR-1981-5p 0.259 miR-540-3p 0.105 miR-377-3p 0.187 miR-221-3p 0.259 miR-376b-3p 0.107 let-7c-1-3p 0.189 miR-329-5p 0.261 miR-125b-5p 0.108 miR-129-5p 0.190 miR-6948-5p 0.262 miR-30c-5p 0.108 miR-1843a-3p 0.199 let-7b-5p 0.264 miR-382-3p 0.112 miR-344g-3p 0.200 miR-341-5p 0.266 miR-146b-3p 0.119 miR-6896-5p 0.200 miR-9-3p 0.270 miR-411-5p 0.124 miR-673-3p 0.202 miR-7068-5p 0.271 miR-3068-5p 0.125 miR-122-5p 0.203 miR-370-3p 0.271 miR-323-5p 0.126 miR-378b 0.203 miR-126a-3p 0.272 miR-6516-5p 0.127 miR-136-3p 0.205 miR-1843b-5p 0.273 miR-300-3p 0.128 miR-30d-3p 0.208 let-7f-5p 0.274 miR-3102-3p 0.128 miR-3082-3p 0.208 miR-139-5p 0.274 miR-16-5p 0.128 miR-300-5p 0.208 miR-341-3p 0.274 miR-490-5p 0.129 miR-485-5p 0.210 miR-671-3p 0.276 miR-504-5p 0.133 miR-3470a 0.210 miR-499-5p 0.278 miR-582-5p 0.141 miR-27a-5p 0.216 miR-22-3p 0.280 miR-299a-3p 0.144 miR-324-5p 0.220 miR-129-1-3p 0.286 miR-154-5p 0.146 miR-466d-3p 0.221 miR-7073-5p 0.286 miR-374b-5p 0.147 miR-146a-5p 0.224 miR-592-5p 0.287 miR-331-5p 0.155 miR-874-3p 0.224 miR-676-3p 0.288 miR-1306-3p 0.155 miR-10a-5p 0.225 miR-145a-5p 0.289 miR-3066-5p 0.155 miR-15a-5p 0.226 miR-30a-3p 0.290 mir-5098-3p_n 0.155 miR-26a-5p 0.227 miR-3085-3p 0.292 miR-7664-3p 0.155 miR-744-5p 0.227 miR-378a-3p 0.292 miR-132-3p 0.160 miR-24-2-5p 0.231 miR-369-5p 0.296 miR-7043-3p 0.169 miR-467a-3p 0.233 miR-130a-3p 0.300 miR-145a-3p 0.170 miR-467d-3p 0.233 miR-467b-5p 0.304 let-7k 0.170 miR-488-3p 0.234 miR-467a-5p 0.304
188 Supplemental Table 4. Differential expression of miRNA between Control and Estradiol-treated female animals Estradiol (+) relative to Control (-)
ID (Mmu-) Log2 FC ID (Mmu-) Log2 FC ID (Mmu-) Log2 FC miR-126a-5p 0.308 miR-142a-3p 0.409 miR-28a-5p 0.548 miR-3086-5p 0.310 miR-5099 0.413 miR-325-3p 0.550 miR-490-3p 0.313 miR-664-5p 0.418 miR-218-2-3p 0.551 miR-191-3p 0.313 miR-425-5p 0.420 miR-203-3p 0.552 miR-370-5p 0.314 miR-30a-5p 0.422 miR-101b-3p 0.569 miR-30e-5p 0.314 miR-136-5p 0.423 miR-1966-3p 0.570 miR-154-3p 0.315 miR-99a-5p 0.430 miR-3081-3p 0.572 miR-193b-5p 0.316 miR-6236 0.431 miR-3474 0.588 miR-29c-5p 0.316 miR-181d-5p 0.434 miR-339-3p 0.591 miR-378d 0.317 miR-381-3p 0.434 miR-125b-2-3p 0.598 miR-124-3p 0.318 miR-669l-5p 0.435 miR-99a-3p 0.598 miR-466i-5p 0.325 miR-671-5p 0.438 miR-6899-3p 0.599 miR-3962 0.328 miR-1843b-3p 0.441 miR-5129-3p 0.613 miR-676-5p 0.329 miR-127-5p 0.453 miR-181c-5p 0.615 miR-139-3p 0.337 miR-344d-3p 0.454 miR-101c 0.618 miR-669d-5p 0.340 miR-30e-3p 0.458 miR-143-3p 0.619 miR-148b-3p 0.341 miR-222-3p 0.458 miR-153-3p 0.628 miR-187-3p 0.343 miR-135b-5p 0.463 miR-3535 0.642 miR-704 0.351 miR-17-3p 0.463 miR-128-3p 0.650 miR-127-3p 0.357 miR-137-3p 0.468 miR-1193-5p 0.662 miR-33-5p 0.359 miR-150-3p 0.477 miR-152-3p 0.685 miR-708-5p 0.360 miR-542-3p 0.479 miR-29b-3p 0.706 miR-434-5p 0.362 miR-33-3p 0.485 miR-5621-3p 0.708 miR-146b-5p 0.368 miR-376b-5p 0.490 mir-3473d-3p_n 0.708 let-7c-5p 0.370 miR-22-5p 0.493 miR-222-5p 0.711 miR-344c-3p 0.373 miR-377-5p 0.506 miR-540-5p 0.723 miR-152-5p 0.374 miR-6937-5p 0.507 miR-344d-3-5p 0.725 miR-879-3p 0.378 miR-184-3p 0.518 miR-544-3p 0.740 miR-488-5p 0.381 miR-379-5p 0.520 miR-7015-3p 0.740 miR-1843a-5p 0.381 miR-466i-3p 0.524 miR-29a-5p 0.740 miR-29c-3p 0.381 miR-679-5p 0.530 miR-7a-1-3p 0.743 miR-29a-3p 0.382 miR-132-5p 0.531 miR-7236-3p 0.761 miR-491-5p 0.383 miR-1947-5p 0.531 miR-6240 0.762 miR-3473a 0.387 miR-376c-3p 0.535 miR-7021-5p 0.763 miR-467d-5p 0.387 miR-218-1-3p 0.542 miR-101a-3p 0.771 miR-29b-2-5p 0.392 miR-6516-3p 0.542 miR-935 0.776 miR-7a-2-3p 0.398 miR-674-3p 0.546 miR-483-5p 0.777 miR-677-5p 0.407 miR-9-5p 0.546 miR-128-2-5p 0.783
189 Supplemental Table 4. Differential expression of miRNA between Control and Estradiol-treated female animals Estradiol (+) relative to Control (-)
ID (Mmu-) Log2 FC miR-3470b 0.793 miR-199a-5p 0.796 miR-6948-3p 0.799 miR-493-3p 0.809 miR-708-3p 0.811 miR-148a-5p 0.812 mir-3535-3p_n 0.812 miR-195a-3p 0.814 miR-6238 0.823 miR-221-5p 0.839 miR-652-5p 0.856 miR-143-5p 0.860 miR-128-1-5p 0.891 miR-153-5p 0.892 miR-218-5p 0.893 miR-497a-5p 0.897 miR-195a-5p 0.934 miR-200c-3p 0.944 miR-8120 1.003 miR-5615-5p 1.030 miR-148a-3p 1.070 miR-3083-5p 1.082 miR-223-3p 1.115 mir-6240-3p_n 1.118 mir-6236-5p_n 1.139 miR-376a-3p 1.141 miR-183-5p 1.503 miR-96-5p 1.511 miR-182-5p 1.528 miR-551b-3p 1.590 miR-200b-3p 1.633 miR-135a-1-3p 1.650 miR-881-3p 1.803 miR-429-3p 1.911 miR-200a-5p 1.953 miR-200a-3p 2.172
190 Supplemental Table 5. Differential expression of miRNAs between Control and Handled male animals Handled (+) relative to Control (-)
ID (Mmu-) Log2 FC ID (Mmu-) Log2 FC ID (Mmu-) Log2 FC miR-1247-3p -2.316 miR-3070-2-3p -0.571 miR-1981-5p -0.431 miR-3473e -1.362 miR-452-5p -0.570 miR-139-5p -0.426 miR-1929-5p -1.246 miR-668-5p -0.568 miR-1957a -0.425 miR-301b-5p -1.188 miR-344-3p -0.561 miR-669n -0.425 miR-6962-5p -1.141 miR-219c-5p -0.558 miR-467b-5p -0.424 miR-3473f -1.130 miR-216a-3p -0.553 miR-467a-5p -0.424 miR-344h-3p -1.069 miR-669o-3p -0.550 miR-344d-3-5p -0.417 miR-5106 -0.934 miR-6932-3p -0.549 miR-425-5p -0.416 miR-764-5p -0.925 miR-511-5p -0.547 miR-8094 -0.413 mir-5127-5p_n -0.918 miR-7237-3p -0.544 miR-6540-3p -0.411 miR-1195 -0.915 miR-7656-5p -0.540 miR-26a-1-3p -0.409 miR-344c-5p -0.912 miR-7073-5p -0.534 miR-6948-3p -0.409 miR-6390 -0.906 miR-770-5p -0.528 miR-344d-3p -0.406 miR-1895 -0.900 miR-383-3p -0.527 miR-223-5p -0.403 miR-6947-5p -0.893 miR-466n-5p -0.522 miR-1264-5p -0.403 miR-1264-3p -0.857 miR-466d-5p -0.522 miR-132-5p -0.398 miR-193a-5p -0.829 miR-6989-3p -0.518 miR-193b-3p -0.396 miR-5113 -0.819 miR-1298-5p -0.517 miR-466h-3p -0.393 miR-9769-3p -0.774 miR-669l-5p -0.517 miR-34b-5p -0.390 miR-30f -0.730 miR-669e-5p -0.504 miR-540-3p -0.387 miR-6964-3p -0.699 miR-5128 -0.500 miR-32-5p -0.386 miR-3473b -0.690 miR-298-3p -0.496 miR-217-5p -0.380 miR-491-3p -0.683 miR-335-3p -0.476 miR-153-3p -0.375 miR-431-5p -0.674 miR-544-3p -0.476 miR-28c -0.375 miR-7048-3p -0.670 miR-467e-5p -0.469 miR-6944-3p -0.375 miR-6973b-3p -0.668 mir-1187-5p_n -0.465 miR-216a-5p -0.370 miR-5119 -0.648 miR-410-5p -0.463 miR-764-3p -0.370 miR-344c-3p -0.635 miR-31-3p -0.459 miR-32-3p -0.369 miR-3552 -0.628 miR-466f-3p -0.459 miR-669c-5p -0.368 mir-6239-5p_n -0.618 miR-184-3p -0.456 miR-297b-5p -0.367 miR-6979-3p -0.610 miR-344g-3p -0.453 miR-551b-5p -0.366 miR-670-3p -0.607 miR-216b-5p -0.451 miR-24-2-5p -0.365 miR-466g -0.600 miR-467c-5p -0.447 miR-7093-3p -0.364 miR-6966-3p -0.593 miR-33-5p -0.447 miR-3097-3p -0.364 miR-497b -0.585 miR-142a-3p -0.447 miR-34b-3p -0.362 miR-3062-5p -0.577 mir-1946b-5p_n -0.442 miR-136-5p -0.359 miR-1912-3p -0.574 miR-148a-3p -0.433 miR-466p-3p -0.359 miR-101b-5p -0.574 miR-380-3p -0.433 miR-365-1-5p -0.357
191 Supplemental Table 5. Differential expression of miRNAs between Control and Handled male animals Handled (+) relative to Control (-)
ID (Mmu-) Log2 FC ID (Mmu-) Log2 FC ID (Mmu-) Log2 FC miR-106a-5p -0.356 miR-376b-3p -0.271 miR-130b-3p -0.210 miR-466e-3p -0.355 miR-369-5p -0.269 miR-186-5p -0.210 miR-129-2-3p -0.349 miR-204-3p -0.263 miR-222-3p -0.209 miR-211-5p -0.349 miR-29c-5p -0.262 miR-147-3p -0.209 miR-299b-3p -0.347 miR-467d-5p -0.261 miR-27a-5p -0.208 miR-331-3p -0.338 miR-1191a -0.259 miR-190b-5p -0.207 miR-7033-5p -0.338 miR-331-5p -0.258 miR-449a-5p -0.204 miR-3074-5p -0.336 miR-6945-3p -0.256 miR-491-5p -0.203 miR-7080-5p -0.335 miR-148a-5p -0.256 miR-669b-5p -0.202 miR-434-5p -0.329 miR-466i-5p -0.255 miR-135a-5p -0.202 miR-6994-3p -0.324 miR-3085-5p -0.254 miR-466i-3p -0.200 miR-383-5p -0.323 miR-3080-5p -0.254 miR-188-5p -0.200 miR-31-5p -0.321 miR-1251-5p -0.245 miR-344b-3p -0.198 miR-486b-3p -0.315 miR-6925-3p -0.245 miR-337-3p -0.195 miR-130a-5p -0.315 miR-3572-3p -0.243 miR-138-5p -0.193 miR-495-3p -0.314 miR-381-3p -0.241 miR-770-3p -0.190 miR-335-5p -0.313 miR-370-3p -0.240 miR-186-3p -0.189 miR-3547-3p -0.313 miR-98-3p -0.237 miR-330-5p -0.189 miR-137-5p -0.312 miR-467d-3p -0.236 miR-219a-5p -0.187 miR-376b-5p -0.312 miR-190a-3p -0.235 miR-30a-5p -0.187 miR-6997-5p -0.311 miR-467a-3p -0.234 miR-1943-5p -0.186 miR-187-3p -0.310 miR-466m-3p -0.232 miR-216b-3p -0.185 miR-3098-3p -0.309 miR-34c-5p -0.230 miR-6900-3p -0.184 miR-8115 -0.307 miR-218-5p -0.229 miR-448-3p -0.183 miR-664-5p -0.298 miR-126a-3p -0.229 miR-29b-3p -0.182 miR-345-5p -0.292 miR-30e-5p -0.228 miR-7004-5p -0.180 miR-344f-3p -0.290 miR-671-5p -0.226 miR-505-5p -0.180 miR-92b-5p -0.290 miR-466a-3p -0.225 miR-7224-3p -0.179 miR-24-1-5p -0.288 miR-6240 -0.225 miR-132-3p -0.179 miR-1298-3p -0.287 miR-7068-5p -0.223 miR-410-3p -0.178 miR-224-5p -0.285 miR-6537-3p -0.222 miR-1957b -0.176 mir-6240-3p_n -0.283 miR-669f-5p -0.221 miR-151-3p -0.173 miR-137-3p -0.282 miR-212-3p -0.221 miR-6903-3p -0.173 miR-6952-3p -0.281 miR-344e-3p -0.220 miR-143-5p -0.172 miR-708-3p -0.278 miR-22-3p -0.219 miR-411-5p -0.171 miR-3093-3p -0.274 miR-135a-1-3p -0.215 mir-1954-3p_n -0.170 miR-147-5p -0.272 miR-709 -0.213 miR-26b-3p -0.170 miR-152-5p -0.271 miR-15a-5p -0.213 miR-145a-3p -0.169
192 Supplemental Table 5. Differential expression of miRNAs between Control and Handled male animals Handled (+) relative to Control (-)
ID (Mmu-) Log2 FC ID (Mmu-) Log2 FC ID (Mmu-) Log2 FC miR-493-3p -0.169 miR-466d-3p -0.130 miR-7055-3p -0.094 mir-5098-3p_n -0.167 miR-324-5p -0.128 miR-6928-3p -0.094 miR-1947-5p -0.166 miR-106b-5p -0.128 miR-500-3p -0.091 mir-6398-5p_n -0.166 miR-6540-5p -0.128 miR-673-5p -0.090 mir-3471-2- -0.164 miR-758-3p -0.127 miR-3057-5p -0.090 3p_n miR-760-3p -0.126 miR-7043-3p -0.090 miR-218-2-3p -0.163 miR-138-1-3p -0.125 miR-541-5p -0.089 miR-22-5p -0.163 miR-700-3p -0.124 miR-448-5p -0.088 miR-1843b-3p -0.163 miR-329-5p -0.123 miR-488-3p -0.087 miR-667-5p -0.163 miR-210-3p -0.123 miR-181d-5p -0.087 miR-377-3p -0.161 miR-1247-5p -0.122 miR-337-5p -0.087 miR-5099 -0.161 miR-26b-5p -0.119 miR-29c-3p -0.086 miR-3099-3p -0.158 miR-127-5p -0.118 miR-146b-5p -0.085 miR-433-5p -0.158 miR-674-3p -0.117 miR-16-1-3p -0.083 miR-676-5p -0.156 miR-148b-5p -0.117 miR-450b-3p -0.083 miR-21b -0.156 miR-677-5p -0.115 miR-540-5p -0.082 miR-676-3p -0.153 miR-154-3p -0.115 miR-1197-3p -0.082 miR-340-3p -0.152 miR-338-3p -0.115 miR-702-3p -0.082 let-7g-3p -0.152 miR-214-3p -0.114 miR-1966-3p -0.080 miR-544-5p -0.150 miR-6238 -0.112 miR-148b-3p -0.076 miR-187-5p -0.150 miR-431-3p -0.112 miR-340-5p -0.076 miR-365-3p -0.150 miR-190a-5p -0.112 miR-223-3p -0.075 miR-191-3p -0.145 miR-551b-3p -0.109 miR-9-3p -0.074 miR-6896-5p -0.145 let-7f-2-3p -0.109 miR-181b-1-3p -0.074 miR-376a-5p -0.144 miR-466o-5p -0.108 miR-6901-3p -0.072 miR-500-5p -0.142 miR-376c-5p -0.107 miR-542-5p -0.072 miR-3963 -0.141 miR-3059-5p -0.107 miR-7b-3p -0.071 miR-541-3p -0.140 miR-704 -0.106 miR-7080-3p -0.071 miR-421-3p -0.139 miR-1306-3p -0.106 miR-20b-5p -0.070 miR-673-3p -0.139 miR-384-5p -0.105 miR-872-5p -0.070 miR-369-3p -0.138 mir-6236-5p_n -0.104 miR-6953-3p -0.069 miR-339-3p -0.138 miR-466c-5p -0.102 miR-30b-5p -0.068 miR-143-3p -0.138 miR-134-3p -0.102 miR-152-3p -0.068 miR-21a-5p -0.137 miR-708-5p -0.100 miR-30d-5p -0.067 miR-145b -0.136 miR-212-5p -0.100 miR-134-5p -0.065 miR-100-3p -0.132 miR-125b-1-3p -0.099 miR-338-5p -0.064 let-7f-1-3p -0.131 miR-341-3p -0.098 miR-409-3p -0.064 miR-1258-3p -0.130 miR-679-5p -0.097 miR-24-3p -0.064
193 Supplemental Table 5. Differential expression of miRNAs between Control and Handled male animals Handled (+) relative to Control (-)
ID (Mmu-) Log2 FC ID (Mmu-) Log2 FC ID (Mmu-) Log2 FC miR-300-3p -0.063 miR-744-3p -0.034 miR-7a-1-3p -0.007 miR-503-3p -0.062 miR-1198-5p -0.034 miR-325-5p -0.007 miR-3474 -0.060 miR-539-5p -0.033 miR-592-5p -0.007 miR-877-5p -0.059 miR-326-3p -0.032 miR-8120 -0.007 miR-346-5p -0.059 miR-128-3p -0.032 let-7a-1-3p -0.005 miR-466f-5p -0.059 miR-667-3p -0.032 miR-879-5p -0.005 miR-1191b-5p -0.059 miR-26a-5p -0.032 miR-1224-5p -0.003 miR-652-5p -0.059 miR-10a-5p -0.031 let-7c-2-3p -0.003 miR-139-3p -0.057 miR-615-3p -0.030 miR-669h-5p -0.003 miR-34a-5p -0.057 miR-204-5p -0.029 miR-350-5p -0.001 miR-379-5p -0.056 let-7f-5p -0.028 miR-3064-5p 0.000 miR-455-5p -0.055 miR-99a-5p -0.027 miR-300-5p 0.000 mir-3535-3p_n -0.055 miR-27a-3p -0.027 miR-30c-1-3p 0.001 miR-136-3p -0.055 miR-129-1-3p -0.026 miR-33-3p 0.002 miR-342-5p -0.054 miR-128-1-5p -0.023 miR-149-5p 0.002 miR-215-5p -0.054 miR-221-3p -0.022 miR-133a-3p 0.002 miR-192-5p -0.053 miR-669f-3p -0.022 miR-181c-5p 0.005 miR-542-3p -0.052 miR-125b-2-3p -0.020 miR-879-3p 0.007 miR-3473g -0.052 miR-7a-5p -0.020 miR-301a-5p 0.008 miR-669d-5p -0.051 miR-7236-3p -0.019 miR-9-5p 0.009 miR-3535 -0.050 miR-101b-3p -0.019 miR-138-2-3p 0.009 miR-125a-3p -0.049 miR-6940-3p -0.018 miR-3072-3p 0.010 miR-221-5p -0.046 miR-193b-5p -0.017 miR-574-5p 0.010 miR-29a-3p -0.045 miR-652-3p -0.017 miR-7115-5p 0.012 miR-496a-3p -0.043 miR-1981-3p -0.016 miR-412-3p 0.012 miR-488-5p -0.043 miR-1843b-5p -0.016 miR-140-5p 0.014 miR-297b-3p -0.042 miR-6914-3p -0.016 miR-5709-5p 0.015 miR-297c-3p -0.042 miR-3085-3p -0.016 miR-145a-5p 0.016 miR-135b-5p -0.041 miR-374b-5p -0.015 miR-130a-3p 0.017 miR-7b-5p -0.041 miR-181b-5p -0.015 miR-6516-3p 0.017 miR-141-3p -0.041 miR-377-5p -0.014 miR-6946-3p 0.018 miR-380-5p -0.037 miR-450a-5p -0.013 miR-378d 0.019 miR-6970-5p -0.037 miR-199a-5p -0.012 let-7k 0.021 miR-1843a-5p -0.037 miR-345-3p -0.012 miR-378a-3p 0.022 miR-574-3p -0.036 miR-487b-3p -0.011 miR-1193-3p 0.022 miR-3473a -0.036 miR-29a-5p -0.010 miR-34c-3p 0.023 miR-6911-3p -0.035 miR-1194 -0.009 miR-361-5p 0.023 miR-378b -0.035 miR-362-5p -0.008 miR-185-3p 0.023
194 Supplemental Table 5. Differential expression of miRNAs between Control and Handled male animals Handled (+) relative to Control (-)
ID (Mmu-) Log2 FC ID (Mmu-) Log2 FC ID (Mmu-) Log2 FC miR-674-5p 0.023 miR-126a-5p 0.051 miR-412-5p 0.078 miR-679-3p 0.024 miR-98-5p 0.051 miR-409-5p 0.078 miR-30e-3p 0.026 miR-1936 0.052 miR-1291 0.078 miR-3084-5p 0.027 miR-3068-3p 0.052 miR-342-3p 0.080 miR-323-5p 0.027 miR-382-5p 0.053 miR-361-3p 0.080 miR-375-3p 0.027 miR-92b-3p 0.054 miR-425-3p 0.082 miR-298-5p 0.027 miR-103-3p 0.054 miR-666-5p 0.083 miR-653-5p 0.028 miR-665-3p 0.055 miR-219a-2-3p 0.083 miR-485-5p 0.028 miR-339-5p 0.055 miR-6906-5p 0.085 miR-700-5p 0.028 miR-5100 0.055 miR-1231-3p 0.085 miR-450b-5p 0.028 miR-3068-5p 0.056 miR-543-5p 0.085 miR-19a-3p 0.029 miR-93-5p 0.056 miR-5132-5p 0.088 miR-744-5p 0.032 miR-7068-3p 0.058 miR-490-3p 0.088 miR-455-3p 0.032 miR-3058-5p 0.059 miR-150-5p 0.089 miR-3102-3p 0.033 miR-153-5p 0.059 miR-222-5p 0.089 miR-3095-5p 0.034 miR-107-3p 0.060 miR-154-5p 0.089 miR-2137 0.034 miR-5126 0.062 let-7e-3p 0.090 miR-30c-5p 0.034 miR-669e-3p 0.063 miR-191-5p 0.091 miR-362-3p 0.035 miR-672-5p 0.063 miR-3093-5p 0.093 miR-499-5p 0.035 miR-3061-3p 0.064 miR-155-5p 0.093 miR-350-3p 0.036 miR-1306-5p 0.064 miR-1198-3p 0.093 miR-100-5p 0.037 miR-666-3p 0.065 miR-376c-3p 0.094 miR-297a-5p 0.037 miR-433-3p 0.065 miR-185-5p 0.094 miR-669p-5p 0.037 miR-296-5p 0.067 miR-23a-3p 0.095 miR-411-3p 0.037 miR-127-3p 0.067 miR-322-3p 0.097 miR-7a-2-3p 0.038 miR-5121 0.068 miR-30d-3p 0.097 miR-7689-3p 0.038 miR-532-5p 0.068 miR-199b-3p 0.100 miR-181a-5p 0.039 miR-199b-5p 0.068 let-7e-5p 0.103 mir-3472-5p_n 0.039 miR-379-3p 0.069 miR-6418-3p 0.103 miR-668-3p 0.041 miR-320-3p 0.069 mir-467g-5p_n 0.104 miR-140-3p 0.041 miR-3082-3p 0.072 miR-135b-3p 0.109 miR-6966-5p 0.041 miR-3086-5p 0.073 miR-493-5p 0.110 miR-151-5p 0.042 miR-299a-3p 0.074 miR-496a-5p 0.110 miR-1193-5p 0.043 miR-142a-5p 0.074 miR-1934-5p 0.111 miR-376a-3p 0.044 miR-423-3p 0.074 miR-129-5p 0.111 miR-434-3p 0.047 miR-1964-3p 0.076 miR-1843a-3p 0.112 miR-146a-5p 0.049 miR-3470b 0.077 miR-10b-5p 0.112 miR-3962 0.050 miR-384-3p 0.078 miR-3066-5p 0.112
195 Supplemental Table 5. Differential expression of miRNAs between Control and Handled male animals Handled (+) relative to Control (-)
ID (Mmu-) Log2 FC ID (Mmu-) Log2 FC ID (Mmu-) Log2 FC miR-23b-5p 0.113 miR-7059-5p 0.151 miR-5615-5p 0.202 miR-23b-3p 0.113 miR-3968 0.151 miR-6715-5p 0.205 miR-25-5p 0.114 miR-3084-3p 0.151 miR-101c 0.208 let-7a-5p 0.114 miR-7015-3p 0.152 miR-669o-5p 0.209 miR-487b-5p 0.115 miR-30b-3p 0.152 miR-16-5p 0.214 miR-323-3p 0.115 miR-378a-5p 0.158 miR-7047-3p 0.215 miR-324-3p 0.116 miR-322-5p 0.158 miR-423-5p 0.215 miR-122-5p 0.117 let-7d-3p 0.159 miR-3078-5p 0.218 miR-299a-5p 0.118 miR-9768-5p 0.159 miR-429-3p 0.218 miR-351-3p 0.121 miR-5620-5p 0.160 miR-7079-3p 0.221 miR-370-5p 0.121 miR-3083-5p 0.160 miR-20a-5p 0.221 miR-3081-3p 0.121 miR-6906-3p 0.160 miR-6937-5p 0.223 miR-296-3p 0.122 let-7c-5p 0.163 let-7b-5p 0.227 let-7d-5p 0.123 miR-130b-5p 0.163 miR-874-5p 0.228 miR-133a-5p 0.126 miR-99b-3p 0.165 let-7j 0.231 miR-3095-3p 0.129 let-7i-3p 0.165 miR-26a-2-3p 0.237 miR-330-3p 0.130 miR-194-5p 0.165 miR-124-5p 0.238 miR-27b-3p 0.130 miR-128-2-5p 0.167 miR-329-3p 0.241 miR-485-3p 0.131 miR-1982-3p 0.169 miR-99a-3p 0.241 miR-872-3p 0.132 miR-19b-3p 0.170 miR-27b-5p 0.241 miR-6481 0.132 miR-1960 0.171 miR-351-5p 0.242 miR-501-3p 0.133 mir-8093-3p_n 0.172 miR-935 0.244 miR-664-3p 0.133 miR-543-3p 0.174 miR-1a-3p 0.244 miR-200b-5p 0.133 miR-1968-5p 0.176 miR-6929-3p 0.248 miR-341-5p 0.134 miR-214-5p 0.177 miR-1945 0.249 let-7g-5p 0.139 miR-219a-1-3p 0.178 miR-490-5p 0.249 miR-125b-5p 0.140 miR-29b-1-5p 0.183 miR-532-3p 0.249 miR-877-3p 0.141 miR-200a-5p 0.185 miR-106b-3p 0.251 miR-144-3p 0.141 miR-382-3p 0.186 miR-101a-3p 0.252 miR-1188-5p 0.141 miR-6988-3p 0.187 miR-504-5p 0.252 let-7i-5p 0.142 miR-598-3p 0.188 miR-671-3p 0.253 miR-135a-2-3p 0.142 miR-301a-3p 0.189 miR-694 0.253 miR-17-5p 0.143 miR-1927 0.189 miR-181a-1-3p 0.255 miR-25-3p 0.144 miR-29b-2-5p 0.189 miR-181c-3p 0.256 miR-30a-3p 0.144 miR-124-3p 0.197 miR-181a-2-3p 0.257 miR-6899-3p 0.145 miR-494-3p 0.197 miR-466h-5p 0.257 miR-28a-3p 0.149 miR-7083-5p 0.201 miR-200a-3p 0.261 miR-5621-3p 0.150 miR-328-3p 0.202 miR-3061-5p 0.261
196 Supplemental Table 5. Differential expression of miRNAs between Control and Handled male animals Handled (+) relative to Control (-)
ID (Mmu-) Log2 FC ID (Mmu-) Log2 FC ID (Mmu-) Log2 FC miR-195a-3p 0.262 miR-467c-3p 0.351 miR-6970-3p 0.543 miR-1224-3p 0.262 miR-669c-3p 0.353 miR-486a-5p 0.544 miR-1188-3p 0.263 miR-1930-5p 0.356 miR-1b-3p 0.548 miR-6977-3p 0.267 miR-5129-3p 0.359 miR-486b-5p 0.551 miR-3076-3p 0.268 miR-1961 0.364 miR-101a-5p 0.553 miR-501-5p 0.269 miR-210-5p 0.366 miR-466e-5p 0.563 miR-194-2-3p 0.270 miR-17-3p 0.368 miR-6538 0.567 miR-874-3p 0.270 miR-484 0.368 miR-7044-3p 0.575 miR-7240-5p 0.271 miR-672-3p 0.369 miR-7021-5p 0.576 miR-125a-5p 0.272 miR-7019-3p 0.383 miR-503-5p 0.581 let-7b-3p 0.274 miR-5129-5p 0.386 miR-144-5p 0.596 miR-218-1-3p 0.274 miR-6236 0.394 miR-6959-5p 0.615 miR-28a-5p 0.277 miR-467e-3p 0.394 miR-381-5p 0.621 miR-670-5p 0.282 miR-483-5p 0.394 miR-6948-5p 0.623 miR-7664-3p 0.288 miR-6395 0.394 miR-5617-5p 0.625 miR-150-3p 0.289 miR-325-3p 0.397 miR-182-5p 0.628 let-7c-1-3p 0.294 miR-497a-5p 0.400 miR-183-5p 0.645 miR-21c 0.295 miR-7220-5p 0.403 miR-3087-3p 0.645 miR-3970 0.297 miR-146b-3p 0.403 miR-6901-5p 0.650 miR-5617-3p 0.301 miR-3104-3p 0.404 miR-547-3p 0.727 miR-6516-5p 0.301 miR-6958-3p 0.424 miR-93-3p 0.743 miR-7226-3p 0.302 miR-582-5p 0.424 miR-483-3p 0.761 miR-6239 0.302 miR-881-3p 0.424 miR-195a-5p 0.761 let-7a-2-3p 0.303 miR-92a-3p 0.428 miR-6380 0.777 miR-30c-2-3p 0.305 miR-486a-3p 0.432 miR-7022-5p 0.795 miR-3091-3p 0.306 miR-181d-3p 0.433 mir-1960-3p_n 0.810 miR-15b-5p 0.309 miR-18a-5p 0.448 miR-200c-3p 0.820 miR-3069-3p 0.311 miR-363-3p 0.453 miR-181b-2-3p 0.825 miR-18a-3p 0.313 miR-8103 0.460 miR-5621-5p 0.827 miR-3470a 0.314 miR-203-3p 0.462 miR-1948-5p 0.832 mir-3473d-3p_n 0.314 miR-8112 0.463 miR-1941-3p 0.850 miR-200b-3p 0.317 miR-1249-3p 0.467 miR-871-3p 0.877 miR-7013-3p 0.323 miR-3089-3p 0.474 miR-466m-5p 0.900 miR-15b-3p 0.324 miR-3103-3p 0.476 miR-1969 0.901 miR-6412 0.332 miR-96-5p 0.492 miR-511-3p 0.966 miR-3083-3p 0.337 miR-133b-3p 0.496 miR-495-5p 0.998 miR-99b-5p 0.338 miR-505-3p 0.503 miR-6933-5p 1.026 miR-582-3p 0.344 miR-3070-5p 0.511 miR-696 1.029
197 Supplemental Table 5. Differential expression of miRNAs between Control and Handled male animals Handled (+) relative to Control (-)
ID (Mmu-) Log2 FC miR-205-5p 1.037 miR-3078-3p 1.039 miR-15a-3p 1.084 miR-16-2-3p 1.142 miR-7015-5p 1.181 miR-7235-3p 1.183 miR-6932-5p 1.297 miR-3057-3p 1.603 miR-206-3p 1.718 miR-7032-3p 1.759
198 Supplemental Table 6. Differential expression of miRNA between Control and Vehicle-treated male animals Vehicle (+) relative to Control (-)
ID (Mmu-) Log2 FC ID (Mmu-) Log2 FC ID (Mmu-) Log2 FC miR-1247-3p -2.316 miR-3070-2-3p -0.571 miR-1981-5p -0.431 miR-3473e -1.362 miR-452-5p -0.570 miR-139-5p -0.426 miR-1929-5p -1.246 miR-668-5p -0.568 miR-1957a -0.425 miR-301b-5p -1.188 miR-344-3p -0.561 miR-669n -0.425 miR-6962-5p -1.141 miR-219c-5p -0.558 miR-467b-5p -0.424 miR-3473f -1.130 miR-216a-3p -0.553 miR-467a-5p -0.424 miR-344h-3p -1.069 miR-669o-3p -0.550 miR-344d-3-5p -0.417 miR-5106 -0.934 miR-6932-3p -0.549 miR-425-5p -0.416 miR-764-5p -0.925 miR-511-5p -0.547 miR-8094 -0.413 mir-5127-5p_n -0.918 miR-7237-3p -0.544 miR-6540-3p -0.411 miR-1195 -0.915 miR-7656-5p -0.540 miR-26a-1-3p -0.409 miR-344c-5p -0.912 miR-7073-5p -0.534 miR-6948-3p -0.409 miR-6390 -0.906 miR-770-5p -0.528 miR-344d-3p -0.406 miR-1895 -0.900 miR-383-3p -0.527 miR-223-5p -0.403 miR-6947-5p -0.893 miR-466n-5p -0.522 miR-1264-5p -0.403 miR-1264-3p -0.857 miR-466d-5p -0.522 miR-132-5p -0.398 miR-193a-5p -0.829 miR-6989-3p -0.518 miR-193b-3p -0.396 miR-5113 -0.819 miR-1298-5p -0.517 miR-466h-3p -0.393 miR-9769-3p -0.774 miR-669l-5p -0.517 miR-34b-5p -0.390 miR-30f -0.730 miR-669e-5p -0.504 miR-540-3p -0.387 miR-6964-3p -0.699 miR-5128 -0.500 miR-32-5p -0.386 miR-3473b -0.690 miR-298-3p -0.496 miR-217-5p -0.380 miR-491-3p -0.683 miR-335-3p -0.476 miR-153-3p -0.375 miR-431-5p -0.674 miR-544-3p -0.476 miR-28c -0.375 miR-7048-3p -0.670 miR-467e-5p -0.469 miR-6944-3p -0.375 miR-6973b-3p -0.668 mir-1187-5p_n -0.465 miR-216a-5p -0.370 miR-5119 -0.648 miR-410-5p -0.463 miR-764-3p -0.370 miR-344c-3p -0.635 miR-31-3p -0.459 miR-32-3p -0.369 miR-3552 -0.628 miR-466f-3p -0.459 miR-669c-5p -0.368 mir-6239-5p_n -0.618 miR-184-3p -0.456 miR-297b-5p -0.367 miR-6979-3p -0.610 miR-344g-3p -0.453 miR-551b-5p -0.366 miR-670-3p -0.607 miR-216b-5p -0.451 miR-24-2-5p -0.365 miR-466g -0.600 miR-467c-5p -0.447 miR-7093-3p -0.364 miR-6966-3p -0.593 miR-33-5p -0.447 miR-3097-3p -0.364 miR-497b -0.585 miR-142a-3p -0.447 miR-34b-3p -0.362 miR-3062-5p -0.577 mir-1946b-5p_n -0.442 miR-136-5p -0.359 miR-1912-3p -0.574 miR-148a-3p -0.433 miR-466p-3p -0.359 miR-101b-5p -0.574 miR-380-3p -0.433 miR-365-1-5p -0.357
199 Supplemental Table 6. Differential expression of miRNA between Control and Vehicle-treated male animals Vehicle (+) relative to Control (-)
ID (Mmu-) Log2 FC ID (Mmu-) Log2 FC ID (Mmu-) Log2 FC miR-106a-5p -0.356 miR-376b-3p -0.271 miR-130b-3p -0.210 miR-466e-3p -0.355 miR-369-5p -0.269 miR-186-5p -0.210 miR-129-2-3p -0.349 miR-204-3p -0.263 miR-222-3p -0.209 miR-211-5p -0.349 miR-29c-5p -0.262 miR-147-3p -0.209 miR-299b-3p -0.347 miR-467d-5p -0.261 miR-27a-5p -0.208 miR-331-3p -0.338 miR-1191a -0.259 miR-190b-5p -0.207 miR-7033-5p -0.338 miR-331-5p -0.258 miR-449a-5p -0.204 miR-3074-5p -0.336 miR-6945-3p -0.256 miR-491-5p -0.203 miR-7080-5p -0.335 miR-148a-5p -0.256 miR-669b-5p -0.202 miR-434-5p -0.329 miR-466i-5p -0.255 miR-135a-5p -0.202 miR-6994-3p -0.324 miR-3085-5p -0.254 miR-466i-3p -0.200 miR-383-5p -0.323 miR-3080-5p -0.254 miR-188-5p -0.200 miR-31-5p -0.321 miR-1251-5p -0.245 miR-344b-3p -0.198 miR-486b-3p -0.315 miR-6925-3p -0.245 miR-337-3p -0.195 miR-130a-5p -0.315 miR-3572-3p -0.243 miR-138-5p -0.193 miR-495-3p -0.314 miR-381-3p -0.241 miR-770-3p -0.190 miR-335-5p -0.313 miR-370-3p -0.240 miR-186-3p -0.189 miR-3547-3p -0.313 miR-98-3p -0.237 miR-330-5p -0.189 miR-137-5p -0.312 miR-467d-3p -0.236 miR-219a-5p -0.187 miR-376b-5p -0.312 miR-190a-3p -0.235 miR-30a-5p -0.187 miR-6997-5p -0.311 miR-467a-3p -0.234 miR-1943-5p -0.186 miR-187-3p -0.310 miR-466m-3p -0.232 miR-216b-3p -0.185 miR-3098-3p -0.309 miR-34c-5p -0.230 miR-6900-3p -0.184 miR-8115 -0.307 miR-218-5p -0.229 miR-448-3p -0.183 miR-664-5p -0.298 miR-126a-3p -0.229 miR-29b-3p -0.182 miR-345-5p -0.292 miR-30e-5p -0.228 miR-7004-5p -0.180 miR-344f-3p -0.290 miR-671-5p -0.226 miR-505-5p -0.180 miR-92b-5p -0.290 miR-466a-3p -0.225 miR-7224-3p -0.179 miR-24-1-5p -0.288 miR-6240 -0.225 miR-132-3p -0.179 miR-1298-3p -0.287 miR-7068-5p -0.223 miR-410-3p -0.178 miR-224-5p -0.285 miR-6537-3p -0.222 miR-1957b -0.176 mir-6240-3p_n -0.283 miR-669f-5p -0.221 miR-151-3p -0.173 miR-137-3p -0.282 miR-212-3p -0.221 miR-6903-3p -0.173 miR-6952-3p -0.281 miR-344e-3p -0.220 miR-143-5p -0.172 miR-708-3p -0.278 miR-22-3p -0.219 miR-411-5p -0.171 miR-3093-3p -0.274 miR-135a-1-3p -0.215 mir-1954-3p_n -0.170 miR-147-5p -0.272 miR-709 -0.213 miR-26b-3p -0.170 miR-152-5p -0.271 miR-15a-5p -0.213 miR-145a-3p -0.169
200 Supplemental Table 6. Differential expression of miRNA between Control and Vehicle-treated male animals Vehicle (+) relative to Control (-)
ID (Mmu-) Log2 FC ID (Mmu-) Log2 FC ID (Mmu-) Log2 FC miR-493-3p -0.169 miR-466d-3p -0.130 miR-7055-3p -0.094 mir-5098-3p_n -0.167 miR-324-5p -0.128 miR-6928-3p -0.094 miR-1947-5p -0.166 miR-106b-5p -0.128 miR-500-3p -0.091 mir-6398-5p_n -0.166 miR-6540-5p -0.128 miR-673-5p -0.090 mir-3471-2- -0.164 miR-758-3p -0.127 miR-3057-5p -0.090 3p_n miR-760-3p -0.126 miR-7043-3p -0.090 miR-218-2-3p -0.163 miR-138-1-3p -0.125 miR-541-5p -0.089 miR-22-5p -0.163 miR-700-3p -0.124 miR-448-5p -0.088 miR-1843b-3p -0.163 miR-329-5p -0.123 miR-488-3p -0.087 miR-667-5p -0.163 miR-210-3p -0.123 miR-181d-5p -0.087 miR-377-3p -0.161 miR-1247-5p -0.122 miR-337-5p -0.087 miR-5099 -0.161 miR-26b-5p -0.119 miR-29c-3p -0.086 miR-3099-3p -0.158 miR-127-5p -0.118 miR-146b-5p -0.085 miR-433-5p -0.158 miR-674-3p -0.117 miR-16-1-3p -0.083 miR-676-5p -0.156 miR-148b-5p -0.117 miR-450b-3p -0.083 miR-21b -0.156 miR-677-5p -0.115 miR-540-5p -0.082 miR-676-3p -0.153 miR-154-3p -0.115 miR-1197-3p -0.082 miR-340-3p -0.152 miR-338-3p -0.115 miR-702-3p -0.082 let-7g-3p -0.152 miR-214-3p -0.114 miR-1966-3p -0.080 miR-544-5p -0.150 miR-6238 -0.112 miR-148b-3p -0.076 miR-187-5p -0.150 miR-431-3p -0.112 miR-340-5p -0.076 miR-365-3p -0.150 miR-190a-5p -0.112 miR-223-3p -0.075 miR-191-3p -0.145 miR-551b-3p -0.109 miR-9-3p -0.074 miR-6896-5p -0.145 let-7f-2-3p -0.109 miR-181b-1-3p -0.074 miR-376a-5p -0.144 miR-466o-5p -0.108 miR-6901-3p -0.072 miR-500-5p -0.142 miR-376c-5p -0.107 miR-542-5p -0.072 miR-3963 -0.141 miR-3059-5p -0.107 miR-7b-3p -0.071 miR-541-3p -0.140 miR-704 -0.106 miR-7080-3p -0.071 miR-421-3p -0.139 miR-1306-3p -0.106 miR-20b-5p -0.070 miR-673-3p -0.139 miR-384-5p -0.105 miR-872-5p -0.070 miR-369-3p -0.138 mir-6236-5p_n -0.104 miR-6953-3p -0.069 miR-339-3p -0.138 miR-466c-5p -0.102 miR-30b-5p -0.068 miR-143-3p -0.138 miR-134-3p -0.102 miR-152-3p -0.068 miR-21a-5p -0.137 miR-708-5p -0.100 miR-30d-5p -0.067 miR-145b -0.136 miR-212-5p -0.100 miR-134-5p -0.065 miR-100-3p -0.132 miR-125b-1-3p -0.099 miR-338-5p -0.064 let-7f-1-3p -0.131 miR-341-3p -0.098 miR-409-3p -0.064 miR-1258-3p -0.130 miR-679-5p -0.097 miR-24-3p -0.064
201 Supplemental Table 6. Differential expression of miRNA between Control and Vehicle-treated male animals Vehicle (+) relative to Control (-)
ID (Mmu-) Log2 FC ID (Mmu-) Log2 FC ID (Mmu-) Log2 FC miR-300-3p -0.063 miR-744-3p -0.034 miR-7a-1-3p -0.007 miR-503-3p -0.062 miR-1198-5p -0.034 miR-325-5p -0.007 miR-3474 -0.060 miR-539-5p -0.033 miR-592-5p -0.007 miR-877-5p -0.059 miR-326-3p -0.032 miR-8120 -0.007 miR-346-5p -0.059 miR-128-3p -0.032 let-7a-1-3p -0.005 miR-466f-5p -0.059 miR-667-3p -0.032 miR-879-5p -0.005 miR-1191b-5p -0.059 miR-26a-5p -0.032 miR-1224-5p -0.003 miR-652-5p -0.059 miR-10a-5p -0.031 let-7c-2-3p -0.003 miR-139-3p -0.057 miR-615-3p -0.030 miR-669h-5p -0.003 miR-34a-5p -0.057 miR-204-5p -0.029 miR-350-5p -0.001 miR-379-5p -0.056 let-7f-5p -0.028 miR-3064-5p 0.000 miR-455-5p -0.055 miR-99a-5p -0.027 miR-300-5p 0.000 mir-3535-3p_n -0.055 miR-27a-3p -0.027 miR-30c-1-3p 0.001 miR-136-3p -0.055 miR-129-1-3p -0.026 miR-33-3p 0.002 miR-342-5p -0.054 miR-128-1-5p -0.023 miR-149-5p 0.002 miR-215-5p -0.054 miR-221-3p -0.022 miR-133a-3p 0.002 miR-192-5p -0.053 miR-669f-3p -0.022 miR-181c-5p 0.005 miR-542-3p -0.052 miR-125b-2-3p -0.020 miR-879-3p 0.007 miR-3473g -0.052 miR-7a-5p -0.020 miR-301a-5p 0.008 miR-669d-5p -0.051 miR-7236-3p -0.019 miR-9-5p 0.009 miR-3535 -0.050 miR-101b-3p -0.019 miR-138-2-3p 0.009 miR-125a-3p -0.049 miR-6940-3p -0.018 miR-3072-3p 0.010 miR-221-5p -0.046 miR-193b-5p -0.017 miR-574-5p 0.010 miR-29a-3p -0.045 miR-652-3p -0.017 miR-7115-5p 0.012 miR-496a-3p -0.043 miR-1981-3p -0.016 miR-412-3p 0.012 miR-488-5p -0.043 miR-1843b-5p -0.016 miR-140-5p 0.014 miR-297b-3p -0.042 miR-6914-3p -0.016 miR-5709-5p 0.015 miR-297c-3p -0.042 miR-3085-3p -0.016 miR-145a-5p 0.016 miR-135b-5p -0.041 miR-374b-5p -0.015 miR-130a-3p 0.017 miR-7b-5p -0.041 miR-181b-5p -0.015 miR-6516-3p 0.017 miR-141-3p -0.041 miR-377-5p -0.014 miR-6946-3p 0.018 miR-380-5p -0.037 miR-450a-5p -0.013 miR-378d 0.019 miR-6970-5p -0.037 miR-199a-5p -0.012 let-7k 0.021 miR-1843a-5p -0.037 miR-345-3p -0.012 miR-378a-3p 0.022 miR-574-3p -0.036 miR-487b-3p -0.011 miR-1193-3p 0.022 miR-3473a -0.036 miR-29a-5p -0.010 miR-34c-3p 0.023 miR-6911-3p -0.035 miR-1194 -0.009 miR-361-5p 0.023 miR-378b -0.035 miR-362-5p -0.008 miR-185-3p 0.023
202 Supplemental Table 6. Differential expression of miRNA between Control and Vehicle-treated male animals Vehicle (+) relative to Control (-)
ID (Mmu-) Log2 FC ID (Mmu-) Log2 FC ID (Mmu-) Log2 FC miR-674-5p 0.023 miR-126a-5p 0.051 miR-412-5p 0.078 miR-679-3p 0.024 miR-98-5p 0.051 miR-409-5p 0.078 miR-30e-3p 0.026 miR-1936 0.052 miR-1291 0.078 miR-3084-5p 0.027 miR-3068-3p 0.052 miR-342-3p 0.080 miR-323-5p 0.027 miR-382-5p 0.053 miR-361-3p 0.080 miR-375-3p 0.027 miR-92b-3p 0.054 miR-425-3p 0.082 miR-298-5p 0.027 miR-103-3p 0.054 miR-666-5p 0.083 miR-653-5p 0.028 miR-665-3p 0.055 miR-219a-2-3p 0.083 miR-485-5p 0.028 miR-339-5p 0.055 miR-6906-5p 0.085 miR-700-5p 0.028 miR-5100 0.055 miR-1231-3p 0.085 miR-450b-5p 0.028 miR-3068-5p 0.056 miR-543-5p 0.085 miR-19a-3p 0.029 miR-93-5p 0.056 miR-5132-5p 0.088 miR-744-5p 0.032 miR-7068-3p 0.058 miR-490-3p 0.088 miR-455-3p 0.032 miR-3058-5p 0.059 miR-150-5p 0.089 miR-3102-3p 0.033 miR-153-5p 0.059 miR-222-5p 0.089 miR-3095-5p 0.034 miR-107-3p 0.060 miR-154-5p 0.089 miR-2137 0.034 miR-5126 0.062 let-7e-3p 0.090 miR-30c-5p 0.034 miR-669e-3p 0.063 miR-191-5p 0.091 miR-362-3p 0.035 miR-672-5p 0.063 miR-3093-5p 0.093 miR-499-5p 0.035 miR-3061-3p 0.064 miR-155-5p 0.093 miR-350-3p 0.036 miR-1306-5p 0.064 miR-1198-3p 0.093 miR-100-5p 0.037 miR-666-3p 0.065 miR-376c-3p 0.094 miR-297a-5p 0.037 miR-433-3p 0.065 miR-185-5p 0.094 miR-669p-5p 0.037 miR-296-5p 0.067 miR-23a-3p 0.095 miR-411-3p 0.037 miR-127-3p 0.067 miR-322-3p 0.097 miR-7a-2-3p 0.038 miR-5121 0.068 miR-30d-3p 0.097 miR-7689-3p 0.038 miR-532-5p 0.068 miR-199b-3p 0.100 miR-181a-5p 0.039 miR-199b-5p 0.068 let-7e-5p 0.103 mir-3472-5p_n 0.039 miR-379-3p 0.069 miR-6418-3p 0.103 miR-668-3p 0.041 miR-320-3p 0.069 mir-467g-5p_n 0.104 miR-140-3p 0.041 miR-3082-3p 0.072 miR-135b-3p 0.109 miR-6966-5p 0.041 miR-3086-5p 0.073 miR-493-5p 0.110 miR-151-5p 0.042 miR-299a-3p 0.074 miR-496a-5p 0.110 miR-1193-5p 0.043 miR-142a-5p 0.074 miR-1934-5p 0.111 miR-376a-3p 0.044 miR-423-3p 0.074 miR-129-5p 0.111 miR-434-3p 0.047 miR-1964-3p 0.076 miR-1843a-3p 0.112 miR-146a-5p 0.049 miR-3470b 0.077 miR-10b-5p 0.112 miR-3962 0.050 miR-384-3p 0.078 miR-3066-5p 0.112
203 Supplemental Table 6. Differential expression of miRNA between Control and Vehicle-treated male animals Vehicle (+) relative to Control (-)
ID (Mmu-) Log2 FC ID (Mmu-) Log2 FC ID (Mmu-) Log2 FC miR-23b-5p 0.113 miR-7059-5p 0.151 miR-5615-5p 0.202 miR-23b-3p 0.113 miR-3968 0.151 miR-6715-5p 0.205 miR-25-5p 0.114 miR-3084-3p 0.151 miR-101c 0.208 let-7a-5p 0.114 miR-7015-3p 0.152 miR-669o-5p 0.209 miR-487b-5p 0.115 miR-30b-3p 0.152 miR-16-5p 0.214 miR-323-3p 0.115 miR-378a-5p 0.158 miR-7047-3p 0.215 miR-324-3p 0.116 miR-322-5p 0.158 miR-423-5p 0.215 miR-122-5p 0.117 let-7d-3p 0.159 miR-3078-5p 0.218 miR-299a-5p 0.118 miR-9768-5p 0.159 miR-429-3p 0.218 miR-351-3p 0.121 miR-5620-5p 0.160 miR-7079-3p 0.221 miR-370-5p 0.121 miR-3083-5p 0.160 miR-20a-5p 0.221 miR-3081-3p 0.121 miR-6906-3p 0.160 miR-6937-5p 0.223 miR-296-3p 0.122 let-7c-5p 0.163 let-7b-5p 0.227 let-7d-5p 0.123 miR-130b-5p 0.163 miR-874-5p 0.228 miR-133a-5p 0.126 miR-99b-3p 0.165 let-7j 0.231 miR-3095-3p 0.129 let-7i-3p 0.165 miR-26a-2-3p 0.237 miR-330-3p 0.130 miR-194-5p 0.165 miR-124-5p 0.238 miR-27b-3p 0.130 miR-128-2-5p 0.167 miR-329-3p 0.241 miR-485-3p 0.131 miR-1982-3p 0.169 miR-99a-3p 0.241 miR-872-3p 0.132 miR-19b-3p 0.170 miR-27b-5p 0.241 miR-6481 0.132 miR-1960 0.171 miR-351-5p 0.242 miR-501-3p 0.133 mir-8093-3p_n 0.172 miR-935 0.244 miR-664-3p 0.133 miR-543-3p 0.174 miR-1a-3p 0.244 miR-200b-5p 0.133 miR-1968-5p 0.176 miR-6929-3p 0.248 miR-341-5p 0.134 miR-214-5p 0.177 miR-1945 0.249 let-7g-5p 0.139 miR-219a-1-3p 0.178 miR-490-5p 0.249 miR-125b-5p 0.140 miR-29b-1-5p 0.183 miR-532-3p 0.249 miR-877-3p 0.141 miR-200a-5p 0.185 miR-106b-3p 0.251 miR-144-3p 0.141 miR-382-3p 0.186 miR-101a-3p 0.252 miR-1188-5p 0.141 miR-6988-3p 0.187 miR-504-5p 0.252 let-7i-5p 0.142 miR-598-3p 0.188 miR-671-3p 0.253 miR-135a-2-3p 0.142 miR-301a-3p 0.189 miR-694 0.253 miR-17-5p 0.143 miR-1927 0.189 miR-181a-1-3p 0.255 miR-25-3p 0.144 miR-29b-2-5p 0.189 miR-181c-3p 0.256 miR-30a-3p 0.144 miR-124-3p 0.197 miR-181a-2-3p 0.257 miR-6899-3p 0.145 miR-494-3p 0.197 miR-466h-5p 0.257 miR-28a-3p 0.149 miR-7083-5p 0.201 miR-200a-3p 0.261 miR-5621-3p 0.150 miR-328-3p 0.202 miR-3061-5p 0.261
204 Supplemental Table 6. Differential expression of miRNA between Control and Vehicle-treated male animals Vehicle (+) relative to Control (-)
ID (Mmu-) Log2 FC ID (Mmu-) Log2 FC ID (Mmu-) Log2 FC miR-195a-3p 0.262 miR-467c-3p 0.351 miR-6970-3p 0.543 miR-1224-3p 0.262 miR-669c-3p 0.353 miR-486a-5p 0.544 miR-1188-3p 0.263 miR-1930-5p 0.356 miR-1b-3p 0.548 miR-6977-3p 0.267 miR-5129-3p 0.359 miR-486b-5p 0.551 miR-3076-3p 0.268 miR-1961 0.364 miR-101a-5p 0.553 miR-501-5p 0.269 miR-210-5p 0.366 miR-466e-5p 0.563 miR-194-2-3p 0.270 miR-17-3p 0.368 miR-6538 0.567 miR-874-3p 0.270 miR-484 0.368 miR-7044-3p 0.575 miR-7240-5p 0.271 miR-672-3p 0.369 miR-7021-5p 0.576 miR-125a-5p 0.272 miR-7019-3p 0.383 miR-503-5p 0.581 let-7b-3p 0.274 miR-5129-5p 0.386 miR-144-5p 0.596 miR-218-1-3p 0.274 miR-6236 0.394 miR-6959-5p 0.615 miR-28a-5p 0.277 miR-467e-3p 0.394 miR-381-5p 0.621 miR-670-5p 0.282 miR-483-5p 0.394 miR-6948-5p 0.623 miR-7664-3p 0.288 miR-6395 0.394 miR-5617-5p 0.625 miR-150-3p 0.289 miR-325-3p 0.397 miR-182-5p 0.628 let-7c-1-3p 0.294 miR-497a-5p 0.400 miR-183-5p 0.645 miR-21c 0.295 miR-7220-5p 0.403 miR-3087-3p 0.645 miR-3970 0.297 miR-146b-3p 0.403 miR-6901-5p 0.650 miR-5617-3p 0.301 miR-3104-3p 0.404 miR-547-3p 0.727 miR-6516-5p 0.301 miR-6958-3p 0.424 miR-93-3p 0.743 miR-7226-3p 0.302 miR-582-5p 0.424 miR-483-3p 0.761 miR-6239 0.302 miR-881-3p 0.424 miR-195a-5p 0.761 let-7a-2-3p 0.303 miR-92a-3p 0.428 miR-6380 0.777 miR-30c-2-3p 0.305 miR-486a-3p 0.432 miR-7022-5p 0.795 miR-3091-3p 0.306 miR-181d-3p 0.433 mir-1960-3p_n 0.810 miR-15b-5p 0.309 miR-18a-5p 0.448 miR-200c-3p 0.820 miR-3069-3p 0.311 miR-363-3p 0.453 miR-181b-2-3p 0.825 miR-18a-3p 0.313 miR-8103 0.460 miR-5621-5p 0.827 miR-3470a 0.314 miR-203-3p 0.462 miR-1948-5p 0.832 mir-3473d-3p_n 0.314 miR-8112 0.463 miR-1941-3p 0.850 miR-200b-3p 0.317 miR-1249-3p 0.467 miR-871-3p 0.877 miR-7013-3p 0.323 miR-3089-3p 0.474 miR-466m-5p 0.900 miR-15b-3p 0.324 miR-3103-3p 0.476 miR-1969 0.901 miR-6412 0.332 miR-96-5p 0.492 miR-511-3p 0.966 miR-3083-3p 0.337 miR-133b-3p 0.496 miR-495-5p 0.998 miR-99b-5p 0.338 miR-505-3p 0.503 miR-6933-5p 1.026 miR-582-3p 0.344 miR-3070-5p 0.511 miR-696 1.029
205 Supplemental Table 6. Differential expression of miRNA between Control and Vehicle-treated male animals Vehicle (+) relative to Control (-)
ID (Mmu-) Log2 FC miR-205-5p 1.037 miR-3078-3p 1.039 miR-15a-3p 1.084 miR-16-2-3p 1.142 miR-7015-5p 1.181 miR-7235-3p 1.183 miR-6932-5p 1.297 miR-3057-3p 1.603 miR-206-3p 1.718 miR-7032-3p 1.759
206 Supplemental Table 7. Differential expression of miRNA between Control and Estradiol-treated male animals Estradiol (+) relative to Control (-)
ID (Mmu-) Log2 FC ID (Mmu-) Log2 FC ID (Mmu-) Log2 FC miR-6390 -1.838 miR-1264-3p -0.743 miR-670-5p -0.538 miR-1957b -1.715 miR-1231-3p -0.731 miR-669n -0.531 miR-216a-3p -1.604 miR-10a-5p -0.716 miR-32-3p -0.518 miR-217-5p -1.536** mir-1187-5p_n -0.704 miR-669b-5p -0.518 miR-147-3p -1.474 miR-141-3p -0.694 miR-342-3p -0.514 miR-1195 -1.447 miR-452-5p -0.690 miR-211-5p -0.502 miR-3547-3p -1.442 miR-6903-3p -0.689 miR-219a-5p -0.498 miR-7048-3p -1.421 miR-1934-5p -0.673 miR-1291 -0.497 miR-615-3p -1.408 miR-224-5p -0.670 miR-3473e -0.494 miR-216b-5p -1.392 miR-21b -0.659 miR-669f-5p -0.490 miR-3552 -1.345 miR-101b-5p -0.657 miR-7013-3p -0.489 miR-216a-5p -1.327 miR-6946-3p -0.656 miR-505-5p -0.488 miR-653-5p -1.324 miR-669o-3p -0.645 miR-365-3p -0.486 miR-190a-3p -1.279 miR-28c -0.636 miR-7224-3p -0.483 miR-6953-3p -1.223 miR-100-3p -0.630 miR-3061-3p -0.480 miR-448-5p -1.207 miR-365-1-5p -0.627 miR-1a-3p -0.475 miR-133b-3p -1.169 miR-297b-3p -0.615 miR-495-3p -0.464 miR-764-3p -1.108 miR-297c-3p -0.615 miR-1298-3p -0.449 miR-1969 -1.102 miR-7079-3p -0.607 miR-6481 -0.444 miR-6947-5p -1.082 miR-3084-3p -0.606 miR-491-3p -0.438 miR-10b-5p -1.081 miR-466f-5p -0.605 miR-31-5p -0.435 miR-467c-3p -1.032 miR-376c-5p -0.602 miR-204-3p -0.432 miR-193b-3p -1.013 miR-206-3p -0.602 miR-337-3p -0.430 miR-106a-5p -0.981 miR-466e-3p -0.594 miR-380-3p -0.427 miR-133a-3p -0.978 miR-466h-5p -0.589 miR-466d-3p -0.424 miR-709 -0.963 miR-466p-3p -0.583 miR-758-3p -0.421 miR-5128 -0.957 miR-338-3p -0.580 miR-186-3p -0.413 miR-8094 -0.939 miR-376b-3p -0.576 miR-344f-3p -0.412 miR-1b-3p -0.916 miR-1224-3p -0.572 miR-669l-5p -0.402 miR-34a-5p -0.914 miR-6540-3p -0.570 miR-30b-5p -0.398 miR-1251-5p -0.913 miR-702-3p -0.563 miR-700-3p -0.394 mir-6398-5p_n -0.904 miR-135a-5p -0.563 miR-6970-5p -0.393 miR-764-5p -0.848 miR-1197-3p -0.562 miR-881-3p -0.393 miR-216b-3p -0.808 miR-449a-5p -0.555 miR-193b-5p -0.392 miR-31-3p -0.807 miR-551b-5p -0.553 miR-219a-2-3p -0.391 miR-1264-5p -0.784 miR-700-5p -0.552 mir-1946b-5p_n -0.391 miR-1929-5p -0.770 miR-466o-5p -0.547 miR-467e-5p -0.388 miR-487b-5p -0.766 miR-466a-3p -0.542 miR-130b-3p -0.385
207 Supplemental Table 7. Differential expression of miRNA between Control and Estradiol-treated male animals Estradiol (+) relative to Control (-)
ID (Mmu-) Log2 FC ID (Mmu-) Log2 FC ID (Mmu-) Log2 FC miR-6906-5p -0.374 miR-3473f -0.309 miR-377-3p -0.259 miR-448-3p -0.374 miR-325-3p -0.308 miR-384-5p -0.259 miR-466m-3p -0.373 miR-7043-3p -0.306 mir-5127-5p_n -0.254 miR-210-5p -0.372 miR-8103 -0.300 miR-21a-5p -0.251 miR-490-5p -0.370 miR-467d-3p -0.296 miR-1936 -0.248 miR-670-3p -0.369 miR-491-5p -0.295 miR-425-5p -0.247 miR-6997-5p -0.367 miR-669d-5p -0.295 miR-3099-3p -0.246 miR-344h-3p -0.366 miR-340-5p -0.295 miR-384-3p -0.245 miR-297b-5p -0.364 miR-130a-5p -0.292 miR-15a-5p -0.245 miR-33-3p -0.360 miR-297a-5p -0.291 miR-181b-1-3p -0.235 miR-466e-5p -0.359 miR-467a-3p -0.291 miR-369-3p -0.233 miR-544-3p -0.351 miR-770-5p -0.290 miR-3070-5p -0.232 miR-3963 -0.350 miR-467b-5p -0.289 miR-376a-5p -0.231 miR-9768-5p -0.349 miR-383-5p -0.289 miR-190a-5p -0.230 miR-376c-3p -0.345 miR-376b-5p -0.289 miR-18a-3p -0.229 miR-7068-5p -0.344 miR-467a-5p -0.289 miR-5106 -0.226 miR-3089-3p -0.342 miR-96-5p -0.286 miR-1249-3p -0.226 miR-194-5p -0.340 miR-129-2-3p -0.285 miR-3473b -0.222 miR-1961 -0.339 miR-410-3p -0.285 miR-500-3p -0.221 miR-671-5p -0.339 miR-33-5p -0.284 miR-874-5p -0.221 miR-298-5p -0.339 miR-871-3p -0.280 miR-344b-3p -0.219 miR-338-5p -0.337 miR-126a-5p -0.280 miR-129-1-3p -0.219 miR-540-5p -0.333 miR-466d-5p -0.278 let-7i-3p -0.217 miR-342-5p -0.332 miR-466n-5p -0.278 miR-223-3p -0.217 miR-298-3p -0.331 miR-7664-3p -0.278 miR-29c-5p -0.214 miR-335-5p -0.330 miR-192-5p -0.275 miR-210-3p -0.213 miR-345-5p -0.329 miR-3093-5p -0.275 miR-344g-3p -0.213 miR-466g -0.329 miR-1298-5p -0.275 miR-544-5p -0.212 miR-6940-3p -0.323 miR-879-5p -0.274 miR-190b-5p -0.211 mir-1954-3p_n -0.321 mir-5098-3p_n -0.273 miR-26b-3p -0.211 miR-879-3p -0.319 miR-9769-3p -0.269 miR-324-3p -0.210 miR-204-5p -0.318 miR-15b-3p -0.268 miR-652-3p -0.210 miR-431-5p -0.316 miR-378a-5p -0.268 miR-3059-5p -0.209 miR-6994-3p -0.314 miR-20b-5p -0.268 miR-323-5p -0.208 let-7f-1-3p -0.314 miR-496a-5p -0.265 miR-1191a -0.204 miR-350-3p -0.313 miR-363-3p -0.262 miR-7b-3p -0.201 miR-26b-5p -0.312 miR-154-3p -0.261 miR-296-5p -0.199 miR-344-3p -0.311 miR-466i-5p -0.259 miR-3057-5p -0.197
208 Supplemental Table 7. Differential expression of miRNA between Control and Estradiol-treated male animals Estradiol (+) relative to Control (-)
ID (Mmu-) Log2 FC ID (Mmu-) Log2 FC ID (Mmu-) Log2 FC miR-6966-3p -0.196 miR-133a-5p -0.163 miR-143-5p -0.118 miR-664-3p -0.195 miR-3104-3p -0.162 let-7a-2-3p -0.117 miR-539-5p -0.194 miR-300-5p -0.162 mir-6239-5p_n -0.117 miR-574-5p -0.193 miR-331-3p -0.161 miR-374b-5p -0.117 miR-6896-5p -0.190 miR-136-5p -0.160 miR-3572-3p -0.115 miR-1912-3p -0.190 miR-106b-5p -0.158 miR-193a-5p -0.113 miR-361-5p -0.189 miR-669f-3p -0.153 miR-134-3p -0.113 miR-326-3p -0.189 miR-24-1-5p -0.152 miR-496a-3p -0.110 miR-669p-5p -0.189 miR-760-3p -0.150 miR-344c-3p -0.109 miR-425-3p -0.188 miR-21c -0.150 miR-181a-5p -0.107 miR-7093-3p -0.187 miR-223-5p -0.148 miR-153-3p -0.106 miR-1895 -0.187 miR-466f-3p -0.143 miR-98-3p -0.105 miR-574-3p -0.187 miR-467d-5p -0.143 miR-145a-5p -0.103 miR-152-5p -0.187 miR-212-3p -0.143 miR-34b-5p -0.103 miR-3069-3p -0.186 miR-126a-3p -0.142 miR-665-3p -0.102 miR-490-3p -0.186 miR-15b-5p -0.140 miR-299a-3p -0.101 miR-1957a -0.184 miR-15a-3p -0.140 miR-330-5p -0.101 miR-1193-5p -0.180 miR-669e-5p -0.140 miR-139-5p -0.101 miR-499-5p -0.179 miR-667-3p -0.139 miR-6901-3p -0.098 miR-592-5p -0.178 miR-410-5p -0.139 miR-340-3p -0.097 miR-674-5p -0.177 miR-543-5p -0.136 miR-3473g -0.096 miR-16-5p -0.176 miR-6973b-3p -0.135 miR-324-5p -0.095 miR-466c-5p -0.175 miR-1224-5p -0.134 miR-27a-3p -0.093 miR-30e-5p -0.175 miR-30a-5p -0.133 miR-93-5p -0.091 miR-181b-5p -0.174 miR-134-5p -0.132 miR-142a-3p -0.088 miR-186-5p -0.172 miR-5621-3p -0.129 miR-1966-3p -0.087 miR-135b-5p -0.171 miR-187-3p -0.128 miR-29c-3p -0.086 miR-140-5p -0.171 miR-381-3p -0.128 miR-23a-3p -0.086 miR-296-3p -0.169 miR-3064-5p -0.127 miR-411-5p -0.086 miR-3062-5p -0.168 miR-3074-5p -0.127 miR-138-1-3p -0.085 miR-6240 -0.168 miR-16-1-3p -0.127 miR-151-5p -0.085 miR-3102-3p -0.167 miR-547-3p -0.126 miR-350-5p -0.085 miR-325-5p -0.167 miR-154-5p -0.125 miR-362-3p -0.083 miR-7a-1-3p -0.166 miR-132-3p -0.125 miR-138-5p -0.081 miR-5121 -0.166 miR-383-3p -0.124 miR-3057-3p -0.079 miR-299a-5p -0.166 miR-450a-5p -0.123 miR-346-5p -0.078 miR-744-3p -0.165 miR-455-3p -0.121 miR-1960 -0.077 miR-1306-5p -0.164 miR-32-5p -0.118 miR-34c-3p -0.076
209 Supplemental Table 7. Differential expression of miRNA between Control and Estradiol-treated male animals Estradiol (+) relative to Control (-)
ID (Mmu-) Log2 FC ID (Mmu-) Log2 FC ID (Mmu-) Log2 FC miR-433-5p -0.075 miR-7047-3p -0.035 miR-669c-5p 0.000 miR-300-3p -0.074 miR-3095-3p -0.035 miR-6948-3p 0.000 miR-22-5p -0.073 let-7k -0.033 miR-150-5p 0.002 miR-24-2-5p -0.072 miR-497b -0.033 miR-339-3p 0.002 miR-7033-5p -0.070 miR-137-3p -0.032 miR-377-5p 0.003 miR-135a-2-3p -0.069 miR-6540-5p -0.032 miR-3093-3p 0.003 miR-9-3p -0.068 miR-329-5p -0.031 miR-34b-3p 0.003 miR-132-5p -0.068 miR-124-3p -0.026 miR-181d-5p 0.004 miR-872-3p -0.065 miR-5709-5p -0.026 let-7d-3p 0.006 miR-666-3p -0.064 miR-872-5p -0.023 miR-1943-5p 0.008 miR-30c-1-3p -0.063 miR-677-5p -0.023 miR-5126 0.008 miR-29b-3p -0.063 miR-155-5p -0.023 miR-421-3p 0.008 let-7g-3p -0.063 miR-6989-3p -0.021 miR-669c-3p 0.011 miR-664-5p -0.062 miR-542-5p -0.021 miR-26a-1-3p 0.012 miR-467c-5p -0.061 miR-30d-5p -0.020 miR-466i-3p 0.013 miR-3070-2-3p -0.061 miR-30b-3p -0.019 miR-3068-5p 0.015 miR-30f -0.060 miR-203-3p -0.016 miR-877-3p 0.016 miR-26a-5p -0.060 miR-8120 -0.016 let-7c-2-3p 0.016 miR-149-5p -0.059 miR-136-3p -0.014 miR-669h-5p 0.017 miR-22-3p -0.058 miR-450b-5p -0.012 miR-484 0.018 miR-466h-3p -0.056 miR-598-3p -0.012 miR-380-5p 0.018 miR-331-5p -0.055 miR-3470b -0.012 let-7a-1-3p 0.019 miR-19b-3p -0.049 miR-185-3p -0.010 miR-6979-3p 0.019 let-7f-2-3p -0.047 miR-369-5p -0.010 miR-23b-3p 0.019 miR-301b-5p -0.046 miR-92b-5p -0.009 miR-770-3p 0.020 miR-667-5p -0.046 miR-191-5p -0.008 miR-17-5p 0.021 miR-146b-5p -0.046 miR-99a-3p -0.008 miR-100-5p 0.022 miR-345-3p -0.045 miR-218-2-3p -0.006 miR-487b-3p 0.024 miR-434-5p -0.045 miR-143-3p -0.004 miR-5617-3p 0.025 miR-148a-5p -0.044 miR-540-3p -0.004 miR-542-3p 0.025 miR-29a-5p -0.042 miR-29a-3p -0.003 miR-6932-3p 0.025 miR-505-3p -0.041 miR-582-5p -0.002 miR-29b-2-5p 0.025 miR-7689-3p -0.040 miR-130a-3p -0.002 miR-1843a-5p 0.026 miR-148b-5p -0.039 miR-7226-3p -0.002 miR-7236-3p 0.026 miR-145a-3p -0.039 miR-1843b-5p -0.002 miR-673-3p 0.026 miR-455-5p -0.039 miR-148a-3p -0.001 miR-431-3p 0.027 miR-188-5p -0.037 miR-181c-5p 0.000 miR-3086-5p 0.027 miR-125b-1-3p -0.036 miR-5113 0.000 mmu-let-7e-3p 0.029
210 Supplemental Table 7. Differential expression of miRNA between Control and Estradiol-treated male animals Estradiol (+) relative to Control (-)
ID (Mmu-) Log2 FC ID (Mmu-) Log2 FC ID (Mmu-) Log2 FC miR-541-3p 0.033 miR-341-3p 0.064 mir-6240-3p_n 0.113 miR-140-3p 0.034 miR-301a-5p 0.067 miR-1193-3p 0.114 miR-708-5p 0.035 miR-127-3p 0.069 miR-669o-5p 0.115 miR-148b-3p 0.035 let-7b-3p 0.071 miR-214-3p 0.118 miR-152-3p 0.036 miR-1306-3p 0.072 miR-103-3p 0.118 miR-3072-3p 0.037 miR-199a-5p 0.073 miR-541-5p 0.118 miR-433-3p 0.037 miR-107-3p 0.074 miR-1194 0.118 miR-6962-5p 0.038 miR-129-5p 0.075 miR-344d-3p 0.119 miR-337-5p 0.039 miR-1258-3p 0.077 miR-26a-2-3p 0.121 miR-382-5p 0.040 miR-3076-3p 0.078 miR-137-5p 0.122 miR-125a-3p 0.040 mir-6236-5p_n 0.081 miR-150-3p 0.122 miR-1947-5p 0.041 miR-27b-3p 0.082 miR-98-5p 0.123 miR-30c-5p 0.042 miR-215-5p 0.083 miR-877-5p 0.124 miR-3962 0.042 miR-361-3p 0.084 miR-3474 0.125 miR-34c-5p 0.044 miR-146a-5p 0.084 miR-370-3p 0.125 miR-92b-3p 0.045 miR-339-5p 0.086 miR-668-3p 0.125 miR-8112 0.045 miR-322-3p 0.087 miR-362-5p 0.125 miR-382-3p 0.046 miR-299b-3p 0.088 miR-27a-5p 0.126 miR-151-3p 0.046 miR-330-3p 0.090 miR-3084-5p 0.128 miR-142a-5p 0.046 miR-5099 0.090 miR-6516-5p 0.133 miR-127-5p 0.047 miR-3473a 0.093 miR-378d 0.135 miR-497a-5p 0.047 miR-6945-3p 0.094 miR-7080-5p 0.135 miR-335-3p 0.048 miR-666-5p 0.095 miR-543-3p 0.136 miR-652-5p 0.051 miR-185-5p 0.097 miR-181a-1-3p 0.138 miR-3087-3p 0.052 miR-1981-3p 0.102 miR-199b-3p 0.138 miR-24-3p 0.053 miR-708-3p 0.102 miR-30e-3p 0.140 miR-1981-5p 0.053 miR-485-3p 0.104 miR-30d-3p 0.140 miR-218-5p 0.053 miR-199b-5p 0.105 miR-532-3p 0.141 miR-6959-5p 0.056 miR-551b-3p 0.105 miR-1198-5p 0.141 miR-3068-3p 0.056 miR-423-3p 0.105 miR-379-5p 0.141 miR-434-3p 0.056 miR-101b-3p 0.106 miR-3066-5p 0.144 miR-6966-5p 0.057 miR-378a-3p 0.109 miR-1945 0.146 miR-187-5p 0.058 miR-6958-3p 0.109 miR-138-2-3p 0.148 miR-7a-2-3p 0.060 miR-99a-5p 0.109 miR-106b-3p 0.149 miR-18a-5p 0.061 miR-6952-3p 0.109 miR-92a-3p 0.150 miR-379-3p 0.063 miR-344e-3p 0.110 miR-5100 0.151 miR-378b 0.064 miR-411-3p 0.111 let-7d-5p 0.152 miR-320-3p 0.064 miR-20a-5p 0.113 miR-6238 0.153
211 Supplemental Table 7. Differential expression of miRNA between Control and Estradiol-treated male animals Estradiol (+) relative to Control (-)
ID (Mmu-) Log2 FC ID (Mmu-) Log2 FC ID (Mmu-) Log2 FC miR-341-5p 0.155 miR-3083-3p 0.188 miR-16-2-3p 0.247 miR-679-5p 0.159 miR-222-3p 0.189 miR-375-3p 0.247 miR-672-5p 0.159 miR-5615-5p 0.190 miR-500-5p 0.250 miR-181a-2-3p 0.161 miR-676-3p 0.191 miR-7115-5p 0.250 miR-25-3p 0.162 miR-195a-3p 0.191 miR-99b-5p 0.250 miR-503-3p 0.165 miR-153-5p 0.191 miR-7656-5p 0.250 miR-494-3p 0.165 miR-9-5p 0.192 miR-3080-5p 0.251 miR-3078-5p 0.166 miR-3470a 0.194 miR-412-3p 0.252 miR-501-3p 0.167 miR-676-5p 0.199 miR-6944-3p 0.254 miR-328-3p 0.167 miR-125b-5p 0.199 miR-1198-3p 0.254 let-7g-5p 0.168 miR-704 0.200 miR-101c 0.255 miR-135b-3p 0.169 let-7a-5p 0.201 miR-6395 0.256 miR-322-5p 0.170 miR-1843b-3p 0.202 miR-1941-3p 0.256 miR-28a-5p 0.170 miR-124-5p 0.202 miR-6516-3p 0.266 miR-6964-3p 0.171 miR-1843a-3p 0.203 miR-191-3p 0.269 miR-501-5p 0.172 miR-7004-5p 0.206 miR-3058-5p 0.269 miR-6901-5p 0.172 miR-376a-3p 0.206 miR-3098-3p 0.270 miR-450b-3p 0.172 miR-27b-5p 0.209 miR-128-3p 0.272 miR-6537-3p 0.173 miR-483-3p 0.209 miR-344c-5p 0.278 miR-181c-3p 0.173 miR-99b-3p 0.210 let-7b-5p 0.278 miR-19a-3p 0.174 miR-744-5p 0.212 miR-182-5p 0.279 miR-511-3p 0.174 miR-483-5p 0.213 miR-467e-3p 0.280 miR-486b-3p 0.175 miR-6418-3p 0.213 miR-6911-3p 0.281 miR-125b-2-3p 0.176 miR-214-5p 0.213 miR-30c-2-3p 0.283 miR-532-5p 0.176 miR-7073-5p 0.214 miR-7044-3p 0.287 miR-3535 0.178 miR-30a-3p 0.214 miR-409-3p 0.288 miR-673-5p 0.179 miR-130b-5p 0.216 miR-679-3p 0.296 miR-329-3p 0.179 miR-6538 0.218 mir-3535-3p_n 0.297 miR-674-3p 0.179 miR-212-5p 0.219 miR-7240-5p 0.304 miR-668-5p 0.180 miR-194-2-3p 0.220 miR-93-3p 0.304 miR-423-5p 0.181 miR-195a-5p 0.223 miR-3097-3p 0.305 miR-1930-5p 0.182 miR-122-5p 0.227 let-7c-5p 0.305 miR-301a-3p 0.183 miR-344d-3-5p 0.229 miR-3081-3p 0.307 let-7e-5p 0.184 let-7f-5p 0.229 miR-17-3p 0.310 miR-409-5p 0.184 miR-874-3p 0.233 miR-221-5p 0.312 miR-200c-3p 0.184 miR-412-5p 0.234 miR-429-3p 0.313 miR-6914-3p 0.186 miR-1191b-5p 0.238 mir-3471-2- 0.314 miR-485-5p 0.187 miR-1188-5p 0.244 3p_n
212 Supplemental Table 7. Differential expression of miRNA between Control and Estradiol-treated male animals Estradiol (+) relative to Control (-)
ID (Mmu-) Log2 FC ID (Mmu-) Log2 FC ID (Mmu-) Log2 FC miR-7080-3p 0.321 miR-139-3p 0.415 miR-5129-3p 0.558 miR-323-3p 0.321 let-7j 0.417 miR-1247-5p 0.559 miR-29b-1-5p 0.328 miR-144-5p 0.419 miR-466m-5p 0.560 miR-493-3p 0.330 miR-6239 0.420 miR-1927 0.560 miR-370-5p 0.330 miR-219a-1-3p 0.423 miR-1982-3p 0.561 miR-671-3p 0.330 miR-6925-3p 0.424 miR-6380 0.561 miR-125a-5p 0.331 miR-3091-3p 0.425 miR-672-3p 0.573 let-7i-5p 0.331 miR-218-1-3p 0.427 miR-6929-3p 0.593 mir-467g-5p_n 0.332 miR-3085-5p 0.427 miR-5129-5p 0.595 miR-694 0.333 miR-935 0.432 miR-7022-5p 0.602 miR-3083-5p 0.334 miR-381-5p 0.435 mir-8093-3p_n 0.604 miR-144-3p 0.336 miR-503-5p 0.440 miR-1188-3p 0.608 miR-6412 0.337 miR-101a-3p 0.440 miR-7220-5p 0.608 miR-582-3p 0.337 miR-486a-3p 0.441 miR-181b-2-3p 0.611 miR-488-3p 0.342 miR-7015-3p 0.442 miR-7055-3p 0.621 miR-200a-3p 0.343 miR-128-2-5p 0.451 miR-1948-5p 0.622 miR-221-3p 0.344 miR-6899-3p 0.454 miR-7059-5p 0.629 miR-3082-3p 0.345 miR-3970 0.458 miR-3103-3p 0.640 miR-1968-5p 0.356 miR-3095-5p 0.462 miR-669e-3p 0.640 miR-146b-3p 0.360 miR-184-3p 0.463 miR-504-5p 0.640 miR-145b 0.361 miR-222-5p 0.468 miR-135a-1-3p 0.640 miR-3968 0.361 miR-200b-3p 0.471 miR-7021-5p 0.645 miR-5620-5p 0.366 miR-7b-5p 0.479 miR-6236 0.646 miR-183-5p 0.367 miR-5119 0.485 miR-2137 0.647 miR-6970-3p 0.370 let-7c-1-3p 0.504 miR-6937-5p 0.653 miR-28a-3p 0.371 miR-7015-5p 0.511 mir-1960-3p_n 0.654 miR-3085-3p 0.372 miR-181d-3p 0.515 miR-25-5p 0.685 miR-351-3p 0.377 miR-128-1-5p 0.526 miR-5132-5p 0.688 miR-23b-5p 0.382 miR-6977-3p 0.526 miR-6715-5p 0.697 miR-200a-5p 0.383 miR-7237-3p 0.534 mir-3472-5p_n 0.734 miR-200b-5p 0.389 miR-511-5p 0.537 miR-147-5p 0.752 miR-351-5p 0.391 miR-6948-5p 0.539 miR-6900-3p 0.782 miR-486a-5p 0.392 mir-3473d-3p_n 0.541 miR-1247-3p 0.784 miR-7a-5p 0.392 miR-219c-5p 0.542 miR-7068-3p 0.821 miR-1964-3p 0.402 miR-7083-5p 0.547 miR-7235-3p 0.829 miR-493-5p 0.404 miR-5617-5p 0.549 miR-6932-5p 0.865 miR-488-5p 0.406 miR-3061-5p 0.553 miR-6988-3p 0.896 miR-486b-5p 0.410 miR-6928-3p 0.555 miR-7019-3p 0.897
213 Supplemental Table 7. Differential expression of miRNA between Control and Estradiol-treated male animals Estradiol (+) relative to Control (-)
ID (Mmu-) Log2 FC miR-696 0.908 miR-205-5p 0.939 miR-3078-3p 1.028 miR-495-5p 1.029 miR-6933-5p 1.034 miR-5621-5p 1.062 miR-8115 1.087 miR-6906-3p 1.087 miR-101a-5p 1.282 miR-7032-3p 1.463
214