Microrna and Mrna Profiles in the Amygdala Are Associated with Stress-Induced Depression and Resilience in Juvenile Mice

Psychopharmacology (2019) 236:2119–2142 https://doi.org/10.1007/s00213-019-05209-z

ORIGINAL INVESTIGATION microRNA and mRNA profiles in the amygdala are associated with stress-induced depression and resilience in juvenile mice

1,2,3 Mengmeng Shen1 & Zhenhua Song1 & Jin-Hui Wang

Received: 3 November 2018 /Accepted: 25 February 2019 /Published online: 21 March 2019 # Springer-Verlag GmbH Germany, part of Springer Nature 2019

Abstract Objectives Major depressive disorder characterized as recurrent negative mood is one of the prevalent psychiatric diseases. Chronic stress plus lack of reward may induce long-term imbalance between reward and penalty circuits in the brain, leading to persistent negative mood. Numerous individuals demonstrate resilience to chronic mild stress. Molecular mechanisms for major depression and resilience in the brain remain unclear. Methods After juvenile mice were treated by the chronic unpredictable mild stress (CUMS) for 4 weeks, they were screened by sucrose preference, Y-maze and forced swimming tests to examine whether their behaviors were depression-like or not. mRNA and miRNA profiles were quantified by high-throughput sequencing in amygdala tissues harvested from control, CUMS- susceptible, and CUMS-resilience mice. Results 1.5-fold ratio in reads per kilo-base per million reads was set to be the threshold to judge the involvement of mRNAs and miRNAs in the CUMS, major depression, or resilience. In the amygdala from CUMS-susceptible mice, the expression of genes relevant to GABAergic, cholinergic, glutamatergic, dopaminergic, and serotonergic synapses was changed, as well as the expression of genes that encoded signal pathways of PI3K-Akt, calcium, cAMP, MAPK, and drug addiction was imbalanced. The expression of these genes in the amygdala form CUMS-resilience mice was less changed. Conclusions The downregulation of genes relevant to synaptic functions and the imbalance of intra-signaling pathway in the amygdala are associated with major depression. Consistent results through sequencing mRNA and miRNA and using different methods validate our finding and conclusion.

Keywords Depression . Resilience . Neuron . Synapse and amygdala

Introduction by both chronic stress and genetic vulnerability (Alex et al. 2013; Camp and Cannon-Albright 2005;Hamiltonetal.2013; Major depressive disorder (MDD) characterized as recurrent Jabbi et al. 2010;Lohoff2010;Moylanetal.2013; Robert and anhedonia, interest loss, and low self-esteem is likely caused Rudolf 2012; Torsten and Binder 2013). Interactions between chronic stress and genetic susceptibility deteriorate Mengmeng Shen and Zhenhua Song contribute to this work equally. hypothalamus-pituitary-adrenal axis and brain-derived neuro- Electronic supplementary material The online version of this article trophic factor (Brunoni and Lopes 2008; Elhwuegi 2004; (https://doi.org/10.1007/s00213-019-05209-z) contains supplementary Nicolas et al. 2011; Olivier et al. 2012;Strekalovaetal. material, which is available to authorized users. 2011), which weaken monoamine synapses and neurons in the reward circuits, such as ventral tegmental area, nucleus * Zhenhua Song accumbens, and prefrontal cortex, as well as impair neuronal [email protected] activity in the amygdala of depressive patients and depression- * Jin-Hui Wang like animals (Banasr et al. 2011; Bellani et al. 2011; Bennett [email protected]; [email protected] et al. 2008; Christopher and Duman 2008;Duman2010; Elizalde et al. 2008;Maetal.2016b; Monk et al. 2008; 1 School of Pharmacy, Qingdao University, 38 Dengzhou, Qingdao 266021, Shandong, China Sandi and Haller 2015;Whalenetal.2002;Xuetal.2016; Zhu et al. 2017). In addition to the effect of stress hormones on 2 University of Chinese Academy of Sciences, Beijing 100049, China neurons and synapses (Gunn et al. 2011; Skilbeck et al. 2010; 3 Institute of Biophysics, Chinese Academy of Sciences, 15 Datun Wang et al. 2016; Wen et al. 2010), the pathology of major Road, Chaoyang District, Beijing 100101, China 2120 Psychopharmacology (2019) 236:2119–2142 depression may be caused by lack of reward, that is, the brain figure out comprehensive molecular profiles and signaling reward circuits are not activated well (Wang and Cui 2015; pathways in the amygdala relevant to stress-induced depres- Zhu et al. 2017). On the other hand, numerous individuals sion versus resilience, which should help to address molecular may not suffer from depressive mood in response to the mechanisms underlying major depression and endogenous stress. The resistance to chronic stress is called as resil- anti-depression and to develop new therapeutic strategies. ience (Southwick and Charney 2012). The elucidation of endogenous mechanisms underlying the resilience to chronic stress should shed light on developing therapeutic Materials and methods strategies for major depression (Zhu et al. 2017). A few molecules are presumably involved in major depression Experiments were performed in accordance with the guideline versus resilience (Bergstrom et al. 2007; Christensen and regulation by Administration Office of Laboratory et al. 2011;Friedmanetal.2014; Manji et al. 2003; Animals at Beijing China, in which all procedures were ap- Minghuietal.2014; Vialou et al. 2010); however, com- proved by Institutional Animal Care and Use Committee in prehensive molecular profiles in the brain circuits for re- this office (B10831). In terms of living condition for normal ward and negative mood remain to be systemically ad- life and control group, mice were housed in cages (32 × 16 × dressed in terms of resilience and susceptibility to the 16 cm) with free access water and food pellets under. The chronic stress for major depression. circadian was 12 h in the light (7:00 am~7:00 pm) and the rest The amygdala has been thought to be an important struc- of 12 h in the dark. Ambient temperature was 22 ± 2 °C. ture to regulate the mood and emotional reactions (Amy and Relative humidity was 55 ± 5%. These conditions were set Kiki 2008;Hastingsetal.2004;Keele2005; Lebow and Chen in the specific pathogen free (SPF). 2016; Price 2010). For instance, the abnormality of the amygdala is found to be relevant to anxiety disorder (Anand and Mouse model for major depressive disorder (MDD) induced Shekhar 2010;Bishop2007;Davis1992; Miles Gregory et al. by chronic unpredictable mild stress (CUMS) All of the exper- 2009; Rauch et al. 2010; Stein and Dan 2008; Zhang et al. iments were performed in strain C57BL/6J male mice and 2012). On the other hand, changes about cellular events and started at postnatal week 4, when the accommodation was molecules in the amygdala are presumably involved in major given for a week. Their body weight, locomotion, sucrose depression (Choi et al. 2015;Guillouxetal.2012;Karolewicz preference, and Y-maze tests were measured to have self- et al. 2009; Kim et al. 2016; Tasan et al. 2010;Wangetal. control data. Mice with mean ± 2SD in these measurements 2016). In this regard, the imbalance of cellular functions and at postnatal day 28 were classified into two groups, control their molecular profiles in the amygdala hypothetically leads and CUMS treatment (Sun et al. 2018). Control mice lived to emotional disorders. In terms of the involvement of the without chronic stresses. The application of juvenile mice to amygdala in major depressive disorder versus its resilience, study occurrences of major depression versus resilience is how the functions of neurons and synapses as well as their based on a fact that young individuals show high prevalence relevant molecules in individuals are susceptible or resilient to to suffer from major depression in response to chronic stresses chronic stress needs to be examined, such that our focus is to (Xu et al. 2016; Zhu et al. 2017). elucidate molecular profiles in the amygdala underlying major The risk factors of major depression include weaknesses in depression and resilience, i.e., the susceptibility and resilience cognition, emotional reaction, social interaction, circadian, and to chronic stress. stressful response (Southwick and Charney 2012). The CUMS In present study, we aim to examine molecule profiles in- applied to mice was based on the following principles. Mice in volved in major depression versus resilience at the amygdala. the CUMS would challenge stress conditions and experience Mice were divided into the groups of control and chronic defeat outcomes. Memory to these negative outcomes induced unpredictable mild stress (CUMS), in which the CUMS in- by the CUMS drove mice to feel cognitive and emotional dis- duces mice to express depression-like behaviors or CUMS- ability as well as to fall into anhedonia and low self-esteem resilience. Our study is based on the following literatures. (Wang and Cui 2017;WangandCui2018). Paradigms in the Animals are thought to be a desirable system of gene analyses CUMS included social isolation, tilted cage, empty cage, damp in the brain to reveal molecules relevant to this disorder sawdust cage, restraint space, white noise, strobe light, and (Crowley and Irwin 2005; Urani et al. 2005). Different cellular circadian disturbance (Ma et al. 2016a, b;Xuetal.2016;Zhu changes were clearly detected in the limbic system from et al. 2017). Except for social isolation, other stresses were CUMS-induced depression and resilience mice (Zhu et al. randomly chosen to treat mice in either separation or combina- 2017). The analysis of genes was performed by high- tion every day. These treatments in detail were presented in throughput sequencing miRNA and mRNA in the amygdala Table 1 of reference (Xu et al. 2016)aswellasTableS1.The of CUMS-induced depression, CUMS-resilience, and control CUMS was persistently given for 4 weeks until certain mice mice. Through joint analyses and comparisons, we expect to demonstrated anhedonia and lack of motivation, similar to low Psychopharmacology (2019) 236:2119–2142 2121

Table 1 CUMS-induced behavioral changes in the mice susceptible mice, which were placed into CUMS-susceptible Number Percentage (%) subgroup for statistical analysis. Mice with less than 5% change in all three tests were named as CUMS-resistant mice, which CUMS-susceptible mice 20 31.25 were placed into CUMS-resilience subgroup for statistical anal- CUMS-resilience mice 9 14.06 ysis. As indicated in Table 1, mice treated by the CUMS in Atypical mice 35 54.69 4 weeks met the criterion of CUMS-susceptible about 31.25%, Total CUMS-treated mice 64 100 and CUMS-resilience mice were about 14.06%. In addition, mice with significant changes in one or two tests but not all three tests were named as atypical mice with CUMS-susceptibility self-esteem in humans. Extreme stresses were not given in a (Ma et al. 2016b;Xuetal.2016; Zhu et al. 2017), whose mo- single pattern, such as learned hopelessness, electrical shock, lecular profiles in the amygdala were not analyzed in our study. social defeat, and tail clamp, since these protocols might induce The tissues including the entire amygdala from each group of fear memory that might lead to anxiety and posttraumatic control mice, CUMS-susceptible mice, and CUMS-resilience stressful disorder (Xu et al. 2016;Zhuetal.2017). mice (n = 3 mice from each group) were harvested for the Whether CUMS-treated mice for 4 weeks fell into anhedo- high-throughput sequencing of miRNA and mRNA. Since nia and lack of motivation was tested in postnatal week nine. 31.25% mice that experienced chronic unpredicted mild stress Sucrose preference test (SPT) was used to estimate anhedonia. expressed depression-like behaviors, the strength of the stress Y-maze test (YMT) was used to evaluate loss of interest to paradigm used in our study is mild in nature (Ma et al. 2016b; their partners. Forced swimming test (FST) was used to assess Xu et al. 2016). motivation-like behavior (Dellu et al. 1992;Overstreet2012; Porsolt et al. 1978; Willner et al. 1987;Xuetal.2016). The RNA purification from the amygdala After confirmed to be SPT was operated with 1% sucrose water versus water in 4 h. CUMS-susceptible or CUMS-resilience in 24 h, these mice Its value was showed to be the ratio of ingested sucrose water and control mice were anesthetized by using isoflurane, per- to ingested sucrose water plus pure water. In the repeated fused by normal saline (4 °C) through left atrium and decap- measurement of the SPT, bottles for water and sucrose were itated by a guillotine. Both sides of the amygdala were quickly switched in their positions randomly, such that memory- isolated and dissected on ice-cold glass slide. Total RNAs related place preference was presumably reduced or even re- were extracted from the amygdala with a TRIzol Kit (Life moved. The YMT was performed by monitoring the stay time Technology, Carlsbad, CA, USA) as stated (Ma et al. of each mouse in three arms for 2 min, one end of which was 2016a). RNA samples in dry ice were sent to Beijing placed in a female mouse (named as M-arm). M-arm stay time Genomics Institute (BGI) for high-throughput sequencing. was presented by the ratio of stay time in M-arm to that in all The concentration of total RNAs, the value of RNA integrity three arms. The FST was conducted by recording immobile number (RIN), and the ratios of 28S to 18S ribosomal RNAs time in a water cylinder (10 cm in diameter and 19 cm in depth were measured by 2100 Bioanalyzer (Agilent Technology, at 25 ± 1 °C). The SPT, the YMT, and the FST were given USA) with RNA 6000 nano Reagents Port 1 for their quality before and after the CUMS. Before the SPT, the deprivation of control. Samples with total RNA amount larger than 10 μg, food and water to mice in 3 h was given for driving their the concentration larger than 200 ng/μl, the RIN larger than 8, intention to drink water. In the YMT, all arms were cleaned and the ratio of 28S to 18S larger than 1.5 were selected for the by 70% ethanol and water after each test to reduce the effect of construction of transcriptome and small RNA libraries. odor on the test. Carefulness was also taken by operating these Amygdala tissues of three mice from each of groups including tests in a quiet room, no additional stresses, identical circadian control, CUMS-susceptible, and CUMS-resilience groups circle for all mice, and their adaptation in the test environment. were used for high-throughput sequencing with correlation Depression-like behaviors were admitted if the CUMS-treated coefficient above 0.8, in which the amygdala tissue from each mice appeared decreases in the SPT and the YMT as well as an mouse was set up as individual sample. increase in the FST’s immobile time at the end of the CUMS, compared to these values in self-control period (the first week for RNA sequencing mRNAs were extracted from total RNA and adaption) and in control mice. Changes in each of mice would be randomly sheared into 200 bp fragment by oligo (dT) beads. considered to be significant if values in the SPT and the YMT Fragments were reversely transcribed to cDNA by random decreased above 20% of its self-control values as well as the oligonucleotides. These cDNAs were purified by QiaQuick immobile time of the FST increased 15% above its self-control PCR extraction kit and ligated by sequencing adaptors after values. These standards were based on averaged values in our end repair. To select and purify cDNAs by agarose gel elec- previous studies (Ma et al. 2016b;Xuetal.2016; Zhu et al. trophoresis, the amplifications were done with Illumina PCR 2017). Mice with significant change in all three tests were de- Primer Cocktail in 15 PCR reaction cycles. cDNAs between fined as CUMS-induced depression-like mice or CUMS- 200 and 300 bp were used for library construction. 2122 Psychopharmacology (2019) 236:2119–2142

18–30 nt RNAs were isolated from total RNAs by poly- sequencing were removed. The remained credible clean reads acrylamide gel electrophoresis. They were applied to con- were aligned to Genebank database and Rfam database with blast struct microRNA sequencing library. RNAs ligated to 5′- or bowtie softwares to further remove reads of noncoding RNA, RNA adapter by T4 RNA ligase were size-fractionated and such as ribosomal RNAs, transfer RNAs, small nuclear RNAs, 36–50 nucleotide fractions were excised. The precipitated small nucleolar RNAs, and repeat RNA. To obtain miRNA RNAs were ligated to 3′-RNA adapter by T4 RNA ligase count, high-quality clean reads ranging in 18–25 nt were and size-fractionated, and then 62–75 nucleotide fraction matched to the known miRNA precursor of corresponding spe- (small RNA + adaptors) was excised. To produce templates cies in miRBase. miRNAs, which were the tags aligned to enough for the sequencing, small RNAs ligated with adaptors miRNA precursor in miRBase with no mismatch as well as were subjected to RT-PCR. Products were purified and col- mature miRNA in miRBase with at least 16 nt overlap allowing lected by gel purification for high-throughput sequencing. offset, would be counted to get the expression of identified Qualities of mRNA and miRNA libraries were evaluated miRNAs. For the remained reads without any annotation, by 2100 Bioanalyzer (Agilent Technologies, CA USA). Their Miredp was used to predict potential novel miRNAs and its stem quantities were verified by ABI StepOnePlus Real-Time PCR loop structure (Friedlander et al. 2014; Friedlander et al. 2012). System. Their sequencings were done by Illumina HiseqTM To correct biased results from low expression, miRNAs with read 2500 platform (Illumina Inc., San Diego, CA USA). In two counts less than 5 were discarded in differential expression libraries, average reading length was about 100 bp (pair-end) analysis. and 49 bp (single-end), respectively. DESeq software algorithm based on negative binomial distribution and biology duplicate samples was used to compare Bioinformatics for mRNA Original image data was transformed the known or novel miRNA expression in control versus into raw data or raw reads by base calling. Dynamic Trim Perl CUMS-susceptible mice, control versus CUMS-resilience script implemented in SolexaQA package was done to control mice, and CUMS-susceptible versus CUMS-resilience mice. the quality of raw sequencing data. The reads with adapters, Threshold used to identify different expressions of miRNAs unknown bases more than 10% as well as 50% bases with was fold-change larger than 1.5 and p value less than 0.05. low-quality score (PHRED score 5) were removed. The Three miRNA target prediction softwares (RNAhybrid, remained Bclean reads^ were mapped to mouse genome refer- Targetscan, and miRanda) were used to predict gene targets ence sequence (UCSC mm10) by TopHat v1.0.12 incorporated of differentially expressed miRNAs. Bowtie v0.11.3 software to perform alignments. The maximum of allowable mismatch was set to three for each read in the Integrated miRNA/mRNA network analysis Bioinformatics alignment and mapping. To calculate gene expression level, sole analyses were conducted to find the correlations between differ- reads uniquely aligned to genes were used. Reads per kilo-base entially expressed miRNAs and their target mRNAs. miRNAs per million reads (RPKM) were used for gene expression. Genes were negatively correlated with their targeted mRNAs in theory, in low expression level (RPKM < 0.5) were removed for further despite a few exceptions (He et al. 2016). The differentially analysis. expressed miRNAs and transcripts were integrated to identify The NOIseq package method was used to screen differential potential miRNA-regulated target genes. (1) miRNAs and expressed genes (DEGs) between two groups with biological mRNAs should be simultaneously and reversely changed in replicates, e.g., control versus CUMS-susceptible mice, control our analyses. (2) mRNAs should be predicted by miRNAs from versus CUMS-resilience mice, and CUMS-susceptible versus RNAhybrid, Targetscan, and miRanda. Interactive networks CUMS-resilience mice. A threshold to identify DEGs was fold- from differentially expressed miRNAs and simultaneously change above 1.5. Pathway enrichment analysis in DEGs asso- expressed target mRNAs were visualized by using Cytoscape ciation with physiological or biochemical processes was con- software (San Diego, CA USA). ducted. Hypergeometric test implemented in tool WebGestalt (version 2) and canonical pathways from the Kyoto Quantitative RT-PCR for the validations of miRNA and mRNA Encyclopedia of Genes and Genomes (KEGG) database were Quantitative real-time RT-PCR (qRT-PCR) by SYBR Green used in these enrichment analyses. Compared to whole genome technique was used to analyze 16 mRNAs and 13 miRNAs that background, the enriched metabolic pathways or signal transduc- were involved in cell function and significantly different among tion pathways in DEGs would be identified in the analyses. p- control, CUMS-resilience, and CUMS-susceptible mice (n =3 values in hypergeometric tests were adjusted by Benjamini- each group). Supplementary Table 2 (Table S2)presentedthe Hochberg method. Pathways with adjusted p values less than used primers. Briefly, real-time PCR was conducted with a 0.05 were thought to be significant enrichments. Bio-Rad CFX96Touch. Total RNA was extracted from the amygdala with a TRIzol Kit. cDNA was synthesized by Bioinformatics for microRNA (miRNA) Adaptor sequences, low- PrimeScript RT Reagent Kit (TaKaRa, RR037A, Kusatsu, quality reads, and contaminant in 49 nt-tags from Hiseq Japan) and Mir-X miRNA First-Strand Synthesis Kit Psychopharmacology (2019) 236:2119–2142 2123

(Clontech, 638315, CA, USA) for mRNA and miRNA, respec- PCR was initiated at 94 °C for 2 min, followed by 45 cycles of tively. mRNAs were amplified in a 20-μl reaction with 1 μl denaturation for 15 s at 94 °C, annealing and elongation for 30 s sample cDNA (500 ng/μl), 0.5 μl of each primer (10 nmol/l), at 60 °C and melt curve 65 to 95 °C increment 0.5 °C for 5 s. For

10 μl 2×qPCR Mastermix (Green) and 8 μl ddH2O. Real-time miRNAs, qRT-PCR was performed in a 20-μl reaction with

Fig. 1 Chronic unpredictable mild stress (CUMS) leads mice to express g SPT, ratios of stay time in M-arm to stay time in three arms by the YMT depression-like behaviors or resilience. a The procedures produced and immobile time of staying in the water cylinder by the FST in the mice CUMS-susceptible mice and CUMS-resilience mice including adapta- from CUMS-susceptible (blue bar, n = 20), CUMS-resilience (yellow bar, tion, behavioral tests, CUMS treatment, and group criteria based on be- n = 9) and control group (white bar, n = 13) after CUMS treatment. Three havior. b–d Sucrose preference test (SPT) values (%), ratios of stay time asterisks show p < 0.001, in which one-way ANOVA was used for the in M-arm to stay time in three arms by the YMT, immobile time of staying comparisons among CUMS-susceptible, CUMS-resilience, and control in the water cylinder by the FST in the mice from control (n =13)and mice, while paired t test was for the comparisons before and after the CUMS group (n = 64) before (black) and after CUMS treatment (blue). e– CUMS 2124 Psychopharmacology (2019) 236:2119–2142

1.6 μl sample cDNA, 0.4 μlmRQ3′Primer, 0.4 μl miRNA- XhoI/NotI and fused into luciferase vector psiCHECK2 (Ma specific Prime (10 μM), 10 μl 2 × SYBR Advantage Premix, et al. 2016a, b). The site-directed mutation of the detected and 7.6 μlddH2O. The program was set to 95 °C for 10 s, miRNA-targeted site was performed with QuikChange followed by 40 cycles of denaturation for 5 s at 95 °C, annealing Lighting Site-Directed Mutagenesis Kit (Stratagene, La and elongation for 20 s at 60 °C and melt curve 65 to 95 °C Jolla, CA USA) based on manufacturer’s instructions. increment 0.5 °C for 5 s. The relative expression level of mRNAs Luciferase reporter detection assays were conducted as de- in the tissue was normalized to an internal reference gene scribed (Ma et al. 2016b). HEK293T cells were planted at GAPDH. The relative expression level of miRNAs in the tissue 5×104 cells per well in 24-well plates and maintained in was normalized to U6 small nucleolar RNA. qRT-PCR runs were DMEM containing 10% FBS. After 24 h, these cells were repeated in three replications. The results were calculated with co-transfected with 50 ng psiCHECK2-wild-type or mutant the 2−ΔΔCt method. reporter plasmids, 50 nM miRNAs mimic or miRNA-NC by Lipofectamine 2000 transfection reagent (Invitrogen, Dual luciferase reporter assay The sequence containing the Carlsbad, CA USA). After 48 h, activities of firefly and targeted sites of targeted gene was amplified, digested by Renilla luciferase were assessed by Dual-Glo® Luciferase

Table 2 Signaling pathways identified by KEGG function analysis based on DEGs data in control versus CUMS-susceptible mice

Pathway DEGs with pathway All genes with pathway Contributing genes Pathway annotation (161) annotation (18697) ID

PI3K-Akt signaling pathway 8 (4.97%) 316 (1.69%) Creb3l3↑,Tnn↑, Pdgfd↓, Fgf17↑, Gng8↓, ko04151 Fgf3↓, Itga11↑,Lamc2↑ Neuroactive ligand-receptor inter- 7 (4.35%) 255 (1.36%) Trhr↑,P2ry2↑,Adora2a↓,Chrnb3↓,Drd2↓, ko04080 action Adora2b↓,Galr1↑ Metabolic pathways 6 (3.73%) 1146 (6.13%) Acss3↓,Ido1↓,Xdh↓,Acox2↓, Alas2↑, ko01100 Chdh↓ Regulation of actin cytoskeleton 4 (2.48%) 208 (1.11%) Pdgfd↓,Fgf17↑,Fgf3↓,Itga11↑ ko04810 Calcium signaling pathway 3 (1.86%) 177 (0.95%) Trhr↑,Adora2a↓,Adora2b↓ ko04020 cAMP signaling pathway 3 (1.86%) 186 (0.99%) Creb3l3↑,Adora2a↓,Drd2↓ ko04024 Cocaine addiction 3 (1.86%) 48 (0.26%) Creb3l3↑,Drd2↓,Rgs9↓ ko05030 Cytokine-cytokine receptor 3 (1.86%) 197 (1.05%) Tnfrsf8↑,Pdgfd ↓,Ccl28↓ ko04060 interaction Dopaminergic synapse 3 (1.86%) 124 (0.66%) Creb3l3↑,Drd2↓,Gng8↓ ko04728 Glutamatergic synapse 3 (1.86%) 111 (0.59%) Slc17a6↑,Gng8↓,Slc17a8↓ ko04724 MAPK signaling pathway 3 (1.86%) 249 (1.33%) Fgf17↑,Fgf3↓,Dusp9↑ ko04010 Retrograde endocannabinoid 3 (1.86%) 100 (0.53%) Slc17a6↑,Gng8↓,Slc17a8↓ ko04723 signaling Cholinergic synapse 2 (1.24%) 110 (0.59%) Creb3l3↑,Gng8↓ ko04725 Glycine, serine, and threonine 2 (1.24%) 37 (0.20%) Alas2↑,Chdh↓ ko00260 metabolism Hippo signaling pathway 2 (1.24%) 147 (0.79%) Tead2↓,Id1↓ ko04390 Nicotine addiction 2 (1.24%) 40 (0.21%) Slc17a6↑,Slc17a8↓ ko05033 Synaptic vesicle cycle 2 (1.24%) 61 (0.33%) Slc17a6↑,Slc17a8↓ ko04721 Amphetamine addiction 1 (0.62%) 62 (0.33%) Creb3l3↑ ko05031 GABAergic synapse 1 (0.62%) 84 (0.45%) Gng8↓ ko04727 Huntington’s disease 1 (0.62%) 177 (0.95%) Creb3l3↑ ko05016 Inflammatory mediator regulation 1 (0.62%) 100 (0.53%) P2ry2↑ ko04750 of TRP channels Long-term depression 1 (0.62%) 59 (0.32%) Ppp1r17↑ ko04730 Melanogenesis 1 (0.62%) 94 (0.50%) Creb3l3↑ ko04916 Morphine addiction 1 (0.62%) 90 (0.48%) Gng8↓ ko05032 Olfactory transduction 1 (0.62%) 105 (0.56%) Olfr1393↓ ko04740 Protein digestion and absorption 1 (0.62%) 74 (0.40%) Col22a1↑ ko04974 Serotonergic synapse 1 (0.62%) 111 (0.59%) Gng8↓ ko04726

Note: ↑ indicates upregulation in the tissue of amygdala from CUMS-susceptible versus control mice, whereas ↓ represents downregulation Psychopharmacology (2019) 236:2119–2142 2125

Assay System (Promega, Cat. E2920, USA) based on manu- profiles were performed, respectively. Data in behavior tests, facturer guides. Each treatment was done in the triplicates luciferase activity, and gene analyses are presented as mean ± from three independent experiments. SEM. Relationships between miRNAs and their target prediction were assessed by Pearson’s correlation coefficients. The unpaired Different expression and biological indication In the compar- Student t test was used to make statistic comparison between isons of the data from the amygdala between control and control and CUMS-susceptible, control and CUMS-resilience, CUMS-susceptible, control and CUMS-resilience as well as and CUMS-susceptible and CUMS-resilience in the data of mo- CUMS-susceptible and CUMS-resilience groups, the 1.5-fold lecular biology. As the data from emotional behavior tasks shows ratio of RPKM values in differential expressions was set as the relatively large variation, one-way ANOVAwas used to compare involvement of CUMS, CUMS-susceptible, or resilience. If the data from behavioral tests among groups. Student t test was mRNAs were differentially expressed between control and used for the comparison of the data before and after the CUMS. CUMS-susceptible mice, these mRNAs were presumably as- In the meantime, two-way repeated ANOVA measures with post sociated with CUMS treatment or CUMS-susceptible. hoc comparison by Student-Newman-Keuls test were used for mRNAs that were differentially expressed between control among groups with before and after treatments. p <0.05values and CUMS-resilience were presumably associated with are thought to be statistically significant (Ma et al. 2016a, b). CUMS treatment or resilience. mRNAs that were differential- Figure styles were made based on the Guidelines for preparing ly expressed between CUMS-susceptible and CUMS- color figures for everyone including the colorblind (Jr 2017). resilience were likely associated with CUMS-susceptible versus CUMS-resilience. If mRNAs were differentially expressed between control and CUMS-susceptible as well as Results between control and CUMS-resilience but showed similar expression between CUMS-susceptible and CUMS-resilience, Chronic unpredictable mild stress to mice leads these mRNAs were likely associated with CUMS treatment. to either depression-like behaviors or resilience

Statistical analyses By NOIseq and DESeq software algorithm, After given chronic unpredictable mild stress (CUMS) or control the initial processing raw data of mRNA and miRNA expression in 4 weeks, mice showing depression-like behaviors were

Table 3 Signaling pathways identified by KEGG function analysis based on DEGs data in control versus CUMS-resilience mice

Pathway DEGs with pathway All genes with pathway Contributing genes Pathway annotation (87) annotation (18690) ID

Neuroactive ligand-receptor in- 6 (6.90%) 253 (1.35%) Gpr50↑,Glra3↑, Gpr156↓,Npffr1↑, ko04080 teraction Gabrq↑,F2rl2↑ Metabolic pathways 4 (4.60%) 1140 (6.10%) Nmrk1↓,Acox2↓,Bdh2↓,Ptgis↓ ko01100 PI3K-Akt signaling pathway 4 (4.60%) 317 (1.70%) Efna4↓, Gng8↓,Itga11↑,Il6ra↓ ko04151 Retrograde endocannabinoid 3 (3.25%) 99 (0.53%) Gabrq↑,Gng8↓,Slc17a6↑ ko04723 signaling GABAergic synapse 2 (2.30%) 83 (0.44%) Gabrq↑,Gng8↓ ko04727 Glutamatergic synapse 2 (2.30%) 110 (0.59%) Gng8↓,Slc17a6↑ ko04724 Morphine addiction 2 (2.30%) 89 (0.48%) Gabrq↑,Gng8↓ ko05032 Nicotine addiction 2 (2.30%) 39 (0.21%) Gabrq↑,Slc17a6↑ ko05033 Tight junction 2 (2.30%) 134 (0.72%) Myh2↑,Cldn22↓ ko04530 Axon guidance 1 (1.15%) 128 (0.68%) Efna4↓ ko04360 Cholinergic synapse 1 (1.15%) 110 (0.59%) Gng8↓ ko04725 Cytokine-cytokine receptor 1 (1.15%) 192 (1.03%) Il6ra↓ ko04060 interaction Dopaminergic synapse 1 (1.15%) 124 (0.66%) Gng8↓ ko04728 Long-term depression 1 (1.15%) 59 (0.32%) Ppp1r17↑ ko04730 Serotonergic synapse 1 (1.15%) 111 (0.59%) Gng8↓ ko04726 Synaptic vesicle cycle 1 (1.15%) 62 (0.33%) Slc17a6↑ ko04721 Valine, leucine, and isoleucine 1 (1.15%) 53 (0.28%) Oxct2b↑ ko00280 degradation

Note: ↑ indicates upregulation in the tissue of amygdala from CUMS-resilience versus control mice, whereas ↓ represents downregulation 2126 Psychopharmacology (2019) 236:2119–2142

Fig. 2 The validation of differentially expressed mRNAs in the amygdala which unpaired t test was used for the comparisons between CUMS- from control mice versus CUMS-susceptible mice. Three asterisks show susceptible (n = 3) and control (n =3)mice p < 0.001, two asterisks show p < 0.01, one asterisk show p <0.05,in assessed by sucrose preference test (SPT), Y-maze test (YMT), CUMS-susceptible mice is 52.58 ± 2.74% after the CUMS in and forced swimming test (FST). CUMS-treated mice appear 4 weeks (n = 20), in comparison with this value at 71.51 ± significant changes in all three tests (CUMS-susceptible), no 2.38% in control mice (n = 13; p < 0.001, one-way ANOVA; change in anyone (resilience) or changes in one or two of these Fig. 1f). This value in CUMS-resilience mice is 73.62 ± 3.93% tests (atypical). Compared with control group mice (n = 13), the after the CUMS for 4 weeks (n = 9), in comparison with this SPT values in CUMS group mice are 79.48 ± 1.56% after the value at 52.58 ± 2.74% in CUMS-susceptible mice (n =20, CUMS and 88.22 ± 0.77% before the CUMS (p < 0.001, n = 64, p < 0.001, one-way ANOVA; Fig. 1f). The FST value in paired t test; Fig. 1b). Compared with control group mice (n = CUMS-susceptible mice is 213.4 ± 8.42% after the CUMS in 13), the ratios of stay time in M-arm to stay time in total arms 4 weeks (n = 20), in comparison with this value at 136.8 ± from CUMS group mice are 63.99 ± 2.01% after the CUMS and 8.37% in control mice (n = 13; p < 0.001, one-way ANOVA; 76.53 ± 1.33% before the CUMS (p < 0.001, n =64,pairedt test; Fig. 1 g). This value in CUMS-resilience mice is 122 ± 18.62% Fig. 1c). Compared with control mice (n = 13), the values of after the CUMS for 4 weeks (n = 9), in comparison with this FST’s immobile time in CUMS group mice are 178.2 ± 7.70% value at 213.4 ± 8.42% in CUMS-susceptible mice (n =20, after the CUMS and 143.5 ± 4.41% before the CUMS p < 0.001, one-way ANOVA; Fig. 1g). The chronic unpredict- (p < 0.001, n =64,paired t test; Fig. 1d). The SPT value in able mild stress induces depression-like behaviors in some mice CUMS-susceptible mice is 68.28 ± 2.24% after the CUMS in versus resilience in others. 4 weeks (n = 20), in comparison with this value at 90.15 ± Taken our data with the fact that acute or chronic stress 1.57% in control mice (n = 13; p < 0.001, one-way ANOVA; influences the amygdala to induce a depressed mood Fig. 1e). This value in CUMS-resilience mice is 89.6 ± 1.60% (Walsh and Han 2014), we studied molecular mechanisms after the CUMS for 4 weeks (n = 9), in comparison with this underlying major depression and resilience by analyzing value at 68.28 ± 2.24% in CUMS-susceptible mice (n =20, miRNAs and mRNAs with the high-throughput sequenc- p < 0.001, one-way ANOVA; Fig. 1e). The YMT value in ing to quantify their expression levels in the amygdala Psychopharmacology (2019) 236:2119–2142 2127

Fig. 3 The validation of differentially expressed mRNAs in the amygdala for the comparisons between CUMS-resilience (n =3)andcontrol(n =3) from control mice versus CUMS-resilience mice. Three asterisks show mice p < 0.001, two asterisks show p < 0.01, in which unpaired t test was used

from CUMS-susceptible, CUMS-resilience, and control (Table S4). The distribution of clean small RNA reads varied in mice. a range of 10 to 44 nucleotides each library. The most abundant lengths were 22 nucleotides (Fig. S1). All high-quality clean Overall qualities of RNA-sequencing dataset reads larger than 18 nucleotides were mapped to the mouse genome. Genome-matched reads were divided into different cate- High-throughput sequencing was used to analyze mRNA and gories of small RNAs based on their biogenesis and annotation miRNA profiles in each of amygdala tissues from CUMS-sus- (Fig. S2). The most abundant RNA category from each library ceptible, CUMS-resilience, and control mice (three mice for each was miRNA. The high qualities of transcriptome and small RNA group). RNAs in 55.02~57.16 Mb raw sequence reads about sequencing data were used for further analysis. 100 bp were obtained from mRNA library Illumina sequencing. After reads that contained N with adaptor sequence and low mRNA differential expression in the amygdala quality were filtered, 44.20~45.24 Mb clean reads from each among CUMS-susceptible, CUMS-resilience, library were gotten and mapped, which were about and control mice 78.84~82.22% of total reads from the mouse genome (UCSC mm10) equivalently for all samples (Table S3). In addition, totals mRNAs in the amygdala were quantified by sequencing total about 29,217,620~31,356,338 raw tag counts were produced in RNAs. Their RPKM values were calculated. Genes in lower small RNA library. After filtering reads with low quality and expression level (RPKM < 0.5) were removed. Others were adaptor, we got clean tag counts in 25,281,852~28,176,071 used for differential expression analyses by NOISeq. By 2128 Psychopharmacology (2019) 236:2119–2142

Fig. 4 Venn diagram showed the differently expression genes (DEGs) specifically involved in CUMS-resilience. CUMS (yellow) indicates the between control versus CUMS-susceptible and control versus CUMS- genes changed in both CUMS-susceptible and CUMS-resilience mice, resilience. Susceptible (blue) shows the certain genes specifically in- which are likely involved in the CUMS treatment volved in CUMS-susceptible. Resilience (red) shows the certain genes mapping reads referred to the mouse genome, 20,131 (20,131) GABAergic synapses), metabolic pathways, and calcium sig- mRNAs from clean read sequences with high quality included naling pathway appear to be downregulated in CUMS- 9958 (9716) of upregulated mRNAs and 10,173 (10,415) of susceptible mice (Table 2). In contrast, the high expressions downregulated mRNAs by comparing CUMS-susceptible of mRNAs in the amygdala from CUMS-susceptible mice versus control (CUMS-resilience versus control). The criteri- mainly include Adcyap1, Creb3l3, Fabp7, Fezf1, Fgf17, on to make sure differential expression of genes was the ratio Galr1, Mab21l1, P2ry2, Ppp1r17, Qrfpr, Slc17a6, Trhr, of their RPKM values above 1.5-fold (Biggar and Storey Col22a1, and so on. Based on bioinformatics for mRNA- 2011; Dwivedi et al. 2015;Maetal.2016a, b). If the ratio of guided protein translation (KEGG), PI3K-Akt signaling path- their expression altered above 1.5 folds between control and way, long-term depression, amphetamine addiction, and TRP CUMS-susceptible, between control and CUMS-resilience as channel signaling pathways appear upregulated in CUMS- well as between CUMS-susceptible and CUMS-resilience susceptible mice (Table 2). It is noteworthy that the molecules (probability ≥ 0.8) in all of three mice, the differential expres- in some intra-signaling pathways are imbalanced, i.e., down- sion of mRNAs was warranted. regulated or upregulated in CUMS-susceptible mice, e.g., Taken out genes in low expression (i.e., the single digit of neuroactive ligand-receptor interaction, regulation of actin cy- RPKM value), 161 mRNAs expressions altered above 1.5- toskeleton, and synapse signaling pathway (Table 2). In addi- fold in CUMS-susceptible mice (n = 3) versus control mice tion to the imbalance among genes in a single signaling path- (n = 3), where 94 mRNAs were downregulated and 67 way, the upregulated and downregulated multiple signaling mRNAs were upregulated (Table S5). The involved signaling pathways make entire molecular networks in the amygdala pathways are listed in Table 2 and Table S6.Thelowexpres- to be imbalance, which lead to neuronal dysfunction in the sions of mRNAs in the amygdala from CUMS-susceptible amygdala for major depressive disorder. mice mainly include Adora2a, Adora2b, Ccl28, Chrnb3, In addition, 87 mRNAs had the 1.5-fold ratio of CUMS- Drd2, Gng8, Hif3a, Ido1, Plin4, Slc17a8, Xdh, and so on. resilience mice (n = 3) to control mice (n =3)inRPKM Based on bioinformatics for mRNA-guided protein translation values, in which 50 mRNAs are downregulated and 37 (KEGG database), dopaminergic type-II receptor, G protein mRNAs are upregulated (Table S7). The decreased expres- coupled synapses (dopaminergic, serotonergic, and sions of mRNAs in the amygdala of CUMS-resilience mice Psychopharmacology (2019) 236:2119–2142 2129

Table 4 The changed miRNAs predict target mRNAs in control versus CUMS-susceptible mice miRNA id The predicted target mRNAs that match DEGs in miRNA id The predicted target mRNAs that match DEGs in transcriptome transcriptome miR-187-3p↓ Alas2↑, Adam33↑ miR-7662-3p↓ Pappa2↑,Dusp9↑,Adam33↑ miR-187-5p↓ Adamts7↑,Qrfpr↑ miR-8103↓ Adamts7↑,Itga11↑ miR-1b-5p↓ Ebf2↑ miR-135b-5p↑ Musk↓,Myof↓,St14↓ miR-193b-5p↓ Adam33↑, 4930426D05Rik↑ miR-137-5p↑ Ifitm1↓,Gpr88↓,Klhdc7a↓ miR-195a-5p↓ Pappa2↑, Fbxo48↑, Adam33↑ let-7b-3p↓ P2ry2↑ miR-2137↓ Slc17a6↑, Edaradd↑ let-7i-3p↓ Pappa2↑,Galr1↑ miR-219a-2-3p↓ Stat4↑, Edaradd↑, Itga11↑ miR-10b-5p↓ Adamts7↑,Fgf17↑,Adam33↑ miR-219b-3p↓ Klf14 ↑,Adcyap1↑ miR-1199-5p↓ 4930426D05Rik↑, Fabp7↑ miR-21a-3p↓ Ccdc42↑,Qrfpr↑ miR-124-3p↓ Casr↑,Rrad↑, 4931408D14Rik↑ miR-21a-5p↓ Stat4↑ miR-200b-5p↑ Tead2↓, Hif3a↓,Rassf9↓ miR-3070-3p↓ Abca17↑,Adam33↑,Adamts7↑ miR-3099-3p↑ Hif3a↓ miR-3074-5p↓ Pcdh12↑,Adam33↑ miR-370-5p↑ Ankk1↓,Fbxw15↓ miR-3095-3p↓ Lamc2↑,Fbxo48↑ miR-344f-3p↑ Dio2↓ miR-3106-5p↓ Vmn2r1↑, A730046J19Rik↑ miR-3547-3p↑ Rgs9↓,Mafa↓, Oas1b↓ miR-341-3p↓ Adamts7↑,Klf14↑ miR-429-3p↑ Mpp7↓,Mmp19↓ miR-341-5p↓ Alas2↑, Adamts7↑ miR-433-3p↑ Acox2↓,Mmp19↓,Chrnb3↓ miR-34a-3p↓ P2ry2↑,Mab21l1↑ miR-434-3p↑ Mettl11b↓,Tead2↓,Acss3↓ miR-466b-5p↓ Rrad↑, A730046J19Rik↑ miR-466b-3p↑ Acss3↓ miR-466p-3p↓ Klf14↑,Mab21l1↑,Vmn2r1↑ miR-466o-5p↑ Fgf3↓,Gpr88↓ miR-6715-3p↓ Pappa2↑, Dusp9↑,Ccdc158↑ miR-467a-3p↑ Mmp19↓, Slc17a8↓ miR-7032-3p↓ Bpifb1↑, Fam159b↑ miR-582-3p↑ Otx2↓ miR-467b-5p↑ Best3↓,Hif3a↓, Prph↓, Slc2a12↓ miR-6481↑ Mpp7↓,Xdh↓,Zcchc5↓ miR-486b-5p↑ Chdh↓,Strc↓, Klc3↓, Ppp1r3b↓ miR-669c-5p↑ Myof ↓,Chdh↓ miR-487b-5p↑ Lrrc10b↓,Smim5↓ miR-7226-3p↑ Dio2↓,Sdc4↓ miR-495-3p↑ Id1↓,Mmp19↓ miR-764-3p↑ Strc↓, Zcchc5↓ miR-532-3p↑ Scn4b↓,Sh3rf2↓ miR-211-5p↑ Klc3↓,Otx2↓, Gdnf↓ miR-532-5p↑ St14↓,Rhpn2↓ miR-673-5p↑ Ccl9↓,Myof↓,Plin4↓, Rbks↓ let-7a-1-3p↓ Vmn2r1↑,Slc17a6↑, Gm19757↑,P2ry2↑ miR-543-3p↑ Musk↓,Sh3rf2↓,Mmp19↓,Strc↓ miR-188-3p↓ Pappa2↑, Ebf2↑, Col22a1↑, Itga11↑, Gm2721↑ miR-133a-3p↓ Adamts7↑,P2ry2↑,Alas2↑,Tnn↑,Adam33↑ miR-193b-3p↓ Adamts7↑,Fezf1↑, Itga11↑, 4931408D14Rik↑ miR-144-3p↑ Adora2b↓,F5↓,St14↓,Sdc4↓, Rassf9↓ miR-338-3p↓ Hbb-bs↑,Lamc2↑,Dusp9↑,Il1rl2↑, Adam33↑ miR-146b-5p↑ Musk↓,Mpp7↓,Paqr5↓,Ppp1r3g↓ miR-34a-5p↓ Lgr6↑,Zfp541↑,P2ry2↑, Adamts7↑,Tnfrsf8↑ miR-182-5p↑ Drd2↓, Irx5↓,Asb11↓,Sh3rf2↓ miR-490-5p↓ Adamts7↑, Zfp541↑,Alas2↑, Adcyap1↑ miR-183-5p↑ Sh3rf2↓, Slc17a8↓,Drd2↓,Plin4↓,Strc↓ miR-540-5p↓ A230065H16Rik↑,Pcdh12↑, Gm2721↑ let-7c-2-3p↑ Tead2↓, Dok1 ↓,Sdc4↓, Rassf9↓ miR-7052-3p↓ Gm5796↑, Casr↑,Misp↑,Itga11↑ miR-1197-3p↑ Musk↓,Slc12a8↓,Ido1↓,Id1↓ miR-8114↓ Tmem196↑,Col22a1↑, 4931408D14Rik↑ miR-135a-1-3p↑ Gm7120↓, Slc17a8↓,Ccl6↓ miR-200b-3p↑ Mgp↓, Dio2↓,Mmp19↓,Rassf9↓ miR-135b-3p↑ Chdh↓, Acss3↓,Sh3rf2↓,Myof↓,Sh3rf2↓,Zcchc5↓ miR-200c-3p↑ Myof↓,Dio2↓,Rhpn2↓,Cldn22↓,Acox2↓, Agbl2↓ miR-335-3p↑ Myof↓,Adora2a↓,Prph↓,Rbks↓ miR-219b-5p↑ Chdh↓,Enpp2↓,Irx5↓,Zcchc5↓ miR-344h-5p↑ Gdnf↓,Irx5↓,Mfsd7c↓,Chdh↓ miR-378c↑ Best3↓,Musk↓, Gdnf↓,Tead2↓ miR-3547-5p↑ Scn4b↓,Hif3a↓,Tmem52↓,Tead2↓,Mmp19↓,Slc12a8↓ miR-3060-3p↑ Ccdc152↓,Dok1↓,Gng8↓,Slc17a8↓,Myof↓ miR-376a-5p↑ Sh3rf2↓,Acox2↓, Otx2↓,Myof↓, Frrs1↓, Dio2↓,Acss3 miR-7a-5p↑ Musk↓,Mpp7↓,Hif3a↓, Agbl2↓ miR-381-5p↑ Otx2↓, Hif3a↓, Paqr5↓,Sh3rf2↓ miR-7b-5p↑ Rgs9↓, Tekt4↓, Rassf9↓,Chrnb3↓, Agbl2↓ miR-384-5p↑ Musk↓,Gdnf↓, Gdnf↓, Klhdc7a↓,Slc17a8↓ miR-504-5p↑ Musk↓,Cdh19↓, Ifitm1↓, Abhd15↓,Slc2a12↓ miR-409-3p↑ Ccl9↓, Acss3↓, Rgs9↓,Musk↓, Slc12a8↓,Kirrel2↓ miR-466n-5p↑ Frrs1↓, Pdgfd↓,Slc17a8↓, A730020M07Rik↓ miR-412-5p↑ Ankub1↓,Asb11↓, Tead2↓,Fbxw15↓,Oas1b↓ miR-547-3p↑ Enpp2↓, Acss3↓,Prph↓, Dio2↓,St14↓ miR-421-3p↑ Ccl9↓,Asb11↓,F5↓,Kirrel2↓ miR-669f-5p↑ Lrrc10b↓, Prph↓, Hist1h2be↓, Slc17a8↓ miR-679-3p↑ Oas1b↓,Mpp7↓,Otx2↓,Sdc4↓,Chdh↓, Klhdc7a↓ miR-669h-5p↑ Gm7120↓,Mpp7 ↓, Dok1↓,Rrh↓,Drd2↓,Musk↓ miR-6944-3p↑ Ccdc152↓, Rgs9↓, Hif3a↓, Gpr88↓ 2130 Psychopharmacology (2019) 236:2119–2142

Table 4 (continued) miRNA id The predicted target mRNAs that match DEGs in miRNA id The predicted target mRNAs that match DEGs in transcriptome transcriptome miR-141-3p↑ Gm7120↓, Ccl9↓, Dio2↓,Asb11↓, Pdgfd↓,Strc↓, miR-96-5p↑ Lrrc38↓, Adora2a↓,Spata9↓ Smim5↓ miR-879-5p↓ Bpifb1↑, Tmem196↑, Fam159b↑, miR-15b-5p↓ Adamts7↑,Lamc2↑,P2ry2↑, Ifltd1↑,Edaradd↑,Adam33↑ Adam33↑,Edaradd↑, A730046J19Rik↑ miR-200a-3p↑ Id1↓, Tead2↓, Irx5↓,Abhd15↓,Ppp1r3g↓,Ppp1r3b↓, miR-206-3p↓ Abca17↑, Col22a1↑, Adam33↑,Tnn↑, 1700030C10Rik↑, Smim5↓ Adam33↑ miR-451a↑ Scn4b↓,Cdh19↓,Slc17a8↓,Rhpn2 ↓,Smim5↓, miR-219a-5p↓ Grxcr2↑,Pappa2↑,Samd3↑,Tmem196↑, Ebf2↑, Oas1b↓ Tmem196↑, Adcyap1↑ miR-344f-5p↑ Ccdc152↓,Enpp2↓, Dio2↓, Oca2↓,Kirrel2↓, miR-378d↑ Cdh19↓, St14↓,Mmp19↓,Abhd15↓,Asb11↓, Osgin1↓, 3110070M22Rik↓ Slc2a12↓ miR-298-3p↑ Best3↓,Musk↓, Hif3a↓, Hist1h2be↓,Myof↓,Mmp19↓ miR-487b-3p↑ Sh3rf2↓, Tmem52↓,Drd2↓,Gpr88↓,Strc↓,Ppp1r3b↓ miR-7037-5p↑ Ankub1↓,Slc12a8↓,Sh3rf2↓, Rgs9↓, Gpr88↓,Strc↓, miR-466f ↑ Ankub1↓,Mpp7↓,Sh3rf2↓, Acox2↓,Asb11↓,F5↓,Drd2↓, Olfr1393↓ Gpr88↓,Ppp1r3b↓ miR-7a-2-3p↑ Cdh19↓,Chdh↓, Hist1h2be↓, Rgs9↓,Ccl28↓, Acox2↓, Rassf9↓

Note: ↑ indicates upregulation in the tissue of amygdala from CUMS-susceptible versus control mice, whereas ↓ represents downregulation mainly include Acox2, Cldn22, Efna4, Gng8, Gpr156, Mia, the expression changes of certain genes are specifically in- Ninj2, Nrl, Twist1, Rtn4r, and so on. According to the bioin- volved in CUMS-susceptible or CUMS-resilience (Fig. 4), formatics of mRNA-guided protein translation (KEGG), the except for Acox2, Barhl2, Ccdc42, Cldn22, Fezf1, Gng8, downregulated signal pathways in CUMS-resilience include Irx5, Itga11, Klf14, Lrrc38, Mab21l1, Mettl11b, Misp, Myof, metabolic pathway, PI3K-Akt signaling pathway, and synapse Osgin1, Oxct2b, Pappa2, Ppp1r17, Rspo1, Slc17a6, pathway (Tables 3 and S8). On the other hand, the raised Tmem52, Zfp541, A730046J19Rik, A230065H16Rik, expressions of mRNAs in the amygdala from CUMS- 4933429O19Rik,and1700030C10Rik in both groups. These resistant mice mainly include Gpr50, Gabrq, Mab21l1, results will help to figure out the genes related to major de- Ppp1r17, Sim1, Gabrq, Fezf1, Npffr1, Glra3, and so on. pression or resilience. The genes changed in the amygdala of According to the KEGG, the upregulated signal pathways in both CUMS-susceptible and CUMS-resilience mice, e.g., CUMS-resilience include neuroactive ligand-receptor interac- Gng8-related G protein coupled dopaminergic, serotonergic, tion, synaptic vesicle cycle, and nicotine addiction (Tables 3 and GABAergic synapses, are likely involved in the CUMS and S8). Interestingly, compared to CUMS-susceptible, syn- treatment (Table S9). apse signaling pathway also shows that some genes, such as In principle, the level of mRNAs in cells is affected by Gabrq-mediated GABAergic synapse, express increasingly, miRNAs, through which the bindings of miRNAs with their and others, such as Gng8-related G protein coupled synapses dicers degrade mRNAs and weaken their translations (dopaminergic, serotonergic, and GABAergic synapses) in (Afonso-Grunz and Müller 2015; Beilharz et al. 2010; CUMS-resilience. Therefore, compared to CUMS-suscepti- Dalmay 2013; Valinezhad et al. 2014). If mRNAs downregu- ble, less changes of signaling pathways in CUMS-resilience. lated in the amygdala from CUMS-susceptible mice are In order to validate our data above, we ran quantitative RT- caused by miRNAs, their correspondent miRNAs should be PCR (qRT-PCR) from tissues that were used for mRNA se- upregulated, or vice versa. If mRNAs upregulated in the quencing. The expressions of Adora2a, Chrnb3, Drd2, Gng8, amygdala from CUMS-resilience mice are caused by Rgs9, Slc17a8,andXdh are decreased, as well as the expressions miRNAs, correspondent miRNAs will be downregulated, or of Creb3l3, P2ry2,andTrhr are raised in CUMS-susceptible vice versa. To examine this hypothesis and validate our data mice, compared to control mice (Fig. 2). Moreover, the expres- about mRNA changes, we analyzed the changes of miRNAs sions of Gabrq, Glra3,andNpffr1 are increased as well as the by their sequencings in the amygdala from control, CUMS- expressions of Gng8, Gpr156 , Sfrp4,andWas are decreased in susceptible, and CUMS-resilience mice. CUMS-resilience mice, compared with control mice (Fig. 3). Consistent results achieved by mRNA sequencing and qRT- Changes of miRNA expression in the amygdala PCR confirm the validation of our study. among control, CUMS-susceptible, and CUMS-resilience mice By comparing the changes of mRNAs above 1.5-fold among groups of control, CUMS-susceptible, and CUMS- The expression profile of miRNAs is presented in Table S10 if resilience in their separation and overlapping, we find that their expressions change above 1.5-fold in all CUMS-susceptible Psychopharmacology (2019) 236:2119–2142 2131

Table 5 The changed mRNAs predict target miRNAs in control versus CUMS-susceptible mice mRNA The predicted target miRNAs that match mRNA The predicted target miRNAs that match DEGs in DEGs in transcriptome transcriptome

Tnn↑ miR-133a-3p↓, miR-206-3p↓ Spata9↓ miR-96-5p↑ Zfp541↑ miR-34a-5p↓, miR-490-5p↓ Tekt4↓ miR-7b-5p↑ Ankk1↓ miR-370-5p↑ Xdh↓ miR-6481↑ Adora2b↓ miR-144-3p↑ 1700030C10Rik↑ miR-206-3p↓ Ccl28↓ miR-7a-2-3p↑ 4930426D05Rik↑ miR-1199-5p↓, miR-193b-5p↓ Ccl6↓ miR-135a-1-3p↑ A230065H16Rik↑ miR-540-5p↓ Chrnb3↓ miR-433-3p↑,miR-7b-5p↑ Abca17↑ miR-206-3p↓, miR-3070-3p↓ Cldn22↓ miR-200c-3p↑ Bpifb1↑ miR-7032-3p↓, miR-7032-3p↓ Fbxw15↓ miR-370-5p↑, miR-412-5p↑ Casr↑ miR-124-3p↓, miR-7052-3p↓ Fgf3↓ miR-466o-5p↑ Ccdc158↑ miR-6715-3p↓ Frrs1↓ miR-376a-5p↑, miR-466n-5p↑ Ccdc42↑ miR-21a-3p↓ Gng8↓ miR-3060-3p↑ Fabp7↑ miR-1199-5p↓ Ido1↓ miR-1197-3p↑ Fam159b↑ miR-7032-3p↓,miR-879-5p↓ Ifitm1↓ miR-137-5p↑, miR-504-5p↑ Fbxo48↑ miR-195a-5p↓, miR-3095-3p↓ Klc3↓ miR-211-5p↑, miR-486b-5p↑ Fezf1↑ miR-193b-3p↓ Lrrc10b↓ miR-487b-5p↑,miR-669f-5p↑ Fgf17↑ miR-10b-5p↓ Lrrc38↓ miR-96-5p↑ Galr1↑ let-7i-3p↓ Mafa↓ miR-3547-3p↑ Gm19757↑ let-7a-1-3p↓ Mettl11b↓ miR-434-3p↑ Gm2721↑ miR-188-3p↓, miR-540-5p↓ Mfsd7c↓ miR-344h-5p↑ Gm5796↑ miR-7052-3p↓ Mgp↓ miR-200b-3p↑ Grxcr2↑ miR-219a-5p↓ Oca2↓ miR-344f-5p↑ Hbb-bs↑ miR-338-3p↓ Olfr1393↓ miR-7037-5p↑ Ifltd1↑ miR-15b-5p↓ Osgin1↓ miR-378d↑ Il1rl2↑ miR-338-3p↓ paqr5↓ miR-146b-5p↑,miR-381-5p↑ Lgr6↑ miR-34a-5p↓ pdgfd↓ miR-141-3p↑, miR-466n-5p↑ Mab21l1↑ miR-34a-3p↓, miR-466p-3p↓ plin4↓ miR-183-5p↑, miR-673-5p↑ Misp↑ miR-7052-3p↓ ppp1r3g↓ miR-146b-5p↑,miR-200a-3p↑ 3110070M22Rik↓ miR-344f-5p↑ Rbks↓ miR-335-3p↑, miR-673-5p↑ A730020M07Rik↓ miR-466n-5p↑ Rrh↓ miR-669h-5p↑ Samd3↑ miR-219a-5p↓ pcdh12↑ miR-3074-5p↓,miR-540-5p↓ Slc17a6↑ let-7a-1-3p↓, miR-2137↓ Qrfpr↑ miR-187-5p ↓, miR-21a-3p↓ Stat4↑ miR-21a-5p↓, miR-219a-2-3p↓ Rrad↑ miR-124-3p↓, miR-466b-5p↓ Tnfrsf8↑ miR-34a-5p↓ Acox2↓ miR-376a-5p↑, miR-433-3p↑,miR-466f↑, Hist1h2be↓ miR-298-3p↑, miR-669f-5p↑, miR-7a-2-3p↑ miR-200c-3p↑, miR-7a-2-3p↑ Best3↓ miR-298-3p↑,miR-378c↑, miR-467b-5p↑ Id1↓ miR-1197-3p↑, miR-200a-3p↑, miR-495-3p↑ Ccdc152↓ miR-3060-3p↑,miR-344f-5p↑, Irx5↓ miR-182-5p↑, miR-200a-3p↑, miR-219b-5p↑, miR-344h-5p↑ miR-6944-3p↑ Ccl9↓ miR-141-3p↑, miR-409-3p↑, miR-421-3p↑, Kirrel2↓ miR-183-5p↑, miR-344f-5p↑, miR-409-3p↑, miR-421-3p↑ miR-673-5p↑ Cdh19↓ miR-378d↑, miR-451a ↑, miR-504-5p↑, Oas1b↓ miR-679-3p↑, miR-3547-3p↑, miR-412-5p↑,miR-451a↑ miR-7a-2-3p↑ Dok1↓ miR-669h-5p↑,let-7c-2-3p↑, miR-3060-3p↑ Otx2↓ miR-381-5p↑,miR-679-3p↑,miR-211-5p↑,miR-376a-5p↑,miR-582-3p↑ Drd2↓ miR-182-5p↑, miR-183-5p↑, miR-466f↑, ppp1r3b↓ miR-200a-3p↑, miR-466f↑, miR-486b-5p↑, miR-487b-3p↑ miR-487b-3p↑,miR-669h-5p↑ Gdnf↓ miR-344h-5p↑,miR-384-5p↑, miR-384-5p↑, prph↓ miR-547-3p↑, miR-669f-5p↑, miR-335-3p↑, miR-467b-5p↑ miR-211-5p↑, miR-378c↑ Gm7120↓ miR-135a-1-3p↑,miR-141-3p↑, Tmem196↑ miR-219a-5p↓, miR-8114↓, miR-219a-5p↓, miR-879-5p↓ miR-669h-5p↑ Adora2a↓ miR-335-3p↑,miR-96-5p↑ Vmn2r1↑ let-7a-1-3p↓, miR-3106-5p↓, miR-466p-3p↓ Agbl2↓ miR-200c-3p↑, miR-7a-5p↑,miR-7b-5p↑ Col22a1↑ miR-188-3p↓, miR-206-3p↓, miR-8114↓ 2132 Psychopharmacology (2019) 236:2119–2142

Table 5 (continued) mRNA The predicted target miRNAs that match mRNA The predicted target miRNAs that match DEGs in DEGs in transcriptome transcriptome

Ankub1↓ miR-412-5p↑,miR-466f↑, miR-7037-5p↑ Dusp9↑ miR-338-3p↓, miR-6715-3p↓, miR-7662-3p↓ Enpp2↓ miR-547-3p↑, miR-219b-5p↑, miR-344f-5p↑ Ebf2↑ miR-188-3p↓, miR-1b-5p↓, miR-219a-5p↓ F5↓ miR-144-3p↑, miR-421-3p↑, miR-466f 4931408D14Rik↑ miR-124-3p↓, miR-193b-3p↓, miR-8114↓ Scn4b↓ miR-3547-5p↑,miR-451a↑, miR-532-3p↑ A730046J19Rik↑ miR-3106-5p↓, miR-466b-5p↓, miR-879-5p↓ Klhdc7a↓ miR-137-5p↑, miR-384-5p↑, miR-679-3p↑ Tmem52↓ miR-487b-3p↑, miR-3547-5p↑, miR-487b-3p↑ Klf14↑ miR-15a-3p↓, miR-219b-3p↓,miR-341-3p↓, Abhd15↓ miR-200a-3p↑, miR-378d ↑, miR-504-5p↑ miR-466p-3p↓ p2ry2↑ miR-34a-3p↓, miR-34a-5p↓, let-7b-3p↓, Rhpn2↓ miR-200c-3p↑, miR-451a↑, miR-532-5p↑ miR-133a-3p↓, miR-15b-5p↓ Zcchc5↓ miR-135b-3p↑,miR-219b-5p↑, miR-6481↑, Sdc4↓ let-7c-2-3p↑, miR-144-3p↑, miR-679-3p↑, miR-7226-3p↑ miR-764-3p↑ Adcyap1↑ miR-219a-5p↓, miR-219b-3p↓, miR-490-5p↓ Slc2a12↓ miR-378d↑, miR-467b-5p↑, miR-504-5p↑ Alas2↑ miR-341-5p↓, miR-490-5p↓, miR-133a-3p↓, Smim5↓ miR-141-3p↑, miR-200a-3p↑, miR-451a↑,miR-487b-5p↑ miR-187-3p↓ Edaradd↑ miR-15b-5p↓,miR-2137↓,miR-219a-2-3p↓, Lamc2↑ miR-15b-5p↓, miR-3095-3p↓, miR-338-3p↓ miR-879-5p↓ Acss3↓ miR-135b-3p↑,miR-409-3p↑, Asb11↓ miR-412-5p↑, miR-421-3p↑, miR-466f↑, miR-141-3p↑, miR-182-5p↑, miR-466b-3p↑,miR-547-3p↑, miR-378d↑ miR-434-3p↑,miR-376a-5p↑ Slc12a8↓ miR-1197-3p↑, miR-7037-5p↑, St14↓ miR-135b-5p↑,miR-144-3p↑, miR-378d↑, miR-532-5p↑, miR-3547-5p↑,miR-409-3p↑ miR-547-3p↑ Rassf9↓ let-7c-2-3p↑, miR-144-3p↑, miR-200b-3p↑, Rgs9↓ miR-409-3p↑, miR-3547-3p↑, miR-7037-5p↑, miR-6944-3p↑, miR-200b-5p↑,miR-7a-2-3p↑, miR-7a-2-3p↑, miR-7b-5p↑ miR-7b-5p↑ Itga11↑ miR-188-3p↓, miR-193b-3p↓, pappa2↑ let-7i-3p↓,miR-188-3p↓, miR-195a-5p↓, miR-219a-5p↓, miR-219a-2-3p↓, miR-7052-3p↓, miR-6715-3p↓, miR-7662-3p↓ miR-8103↓ Mmp19↓ miR-433-3p↑, miR-467a-3p↑, Dio2↓ miR-141-3p↑, miR-200b-3p↑, miR-200c-3p↑, miR-344f-3p↑, miR-200b-3p↑,miR-298-3p↑, miR-344f-5p↑, miR-376a-5p↑, miR-547-3p↑, miR-7226-3p↑ miR-3547-5p↑, miR-378d↑, miR-429-3p↑, miR-495-3p↑,miR-543-3p↑ Mpp7↓ miR-429-3p↑,miR-466f↑, miR-6481↑, Gpr88↓ miR-137-5p↑, miR-466f↑, miR-466o-5p↑, miR-487b-3p↑, miR-7a-5p↑, miR-146b-5p↑, miR-6944-3p↑, miR-7037-5p↑ miR-669h-5p↑,miR-679-3p↑ Strc↓ miR-141-3p↑, miR-183-5p↑, miR-486b-5p↑, Hif3a↓ miR-298-3p↑, miR-3547-5p↑, miR-467b-5p↑, miR-200b-5p↑, miR-487b-3p↑,miR-543-3p↑, miR-3099-3p↑, miR-381-5p↑, miR-6944-3p↑,miR-7a-5p↑ miR-7037-5p↑,miR-764-3p↑ Myof↓ miR-200c-3p↑, miR-3060-3p↑, Musk↓ miR-378c, miR-543-3p↑, miR-135b-5p↑, miR-146b-5p↑, miR-7a-5p↑, miR-669c-5p↑, miR-135b-3p↑, miR-1197-3p↑, miR-298-3p↑,miR-384-5p↑, miR-504-5p↑, miR-135b-5p↑,miR-298-3p↑, miR-409-3p↑, miR-669h-5p↑ miR-335-3p↑,miR-376a-5p↑, miR-673-5p↑, miR-3060-3p↑ Adam33↑ miR-193b-5p↓,miR-3070-3p↓, Adamts7↑ miR-15b-5p↓, miR-341-3p↓, miR-490-5p↓, miR-495-3p↓, miR-8103↓, miR-206-3p↓,miR-879-5↓, miR-10b-5p↓, miR-133a-3p↓, miR-3070-3p↓, miR-490-5p↓, miR-10b-5p↓, miR-133a-3p↓, miR-15b-5p↓, miR-193b-3p↓, miR-341-3p↓, miR-341-5p↓, miR-187-5p↓, miR-187-3p↓,miR-195a-5p↓, miR-34a-5p↓ miR-206-3p↓, miR-3074-5p↓, miR-338-3p↓, miR-7662-3p↓ Tead2↓ miR-200b-5p↑,miR-200a-3p↑, Chdh↓ miR-679-3p↑, miR-344h-5p↑, miR-669c-5p↑, miR-135b-3p↑, miR-3547-5p↑,miR-378↑,miR-412-5p↑, miR-219b-5p↑, miR-486b-5p↑, miR-7a-2-3p↑ miR-434-3p↑, let-7c-2-3p↑ Sh3rf2↓ miR-135b-3p↑,miR-183-5p↑, Slc17a8↓ miR-135a-1-3p↑, miR-183-5p↑, miR-451a↑,miR-669f-5p↑, miR-376a-5p↑, miR-466f↑, miR-3060-3p↑, miR-384-5p↑, miR-466n-5p↑, miR-467a-3p↑ miR-487b-3p↑,miR-532-3p↑, miR-543-3p↑, miR-7037-5p↑, miR-135b-3p↑,miR-182-5p↑, miR-381-5p↑

Note: ↑ indicates upregulation in the tissue of amygdala from CUMS-susceptible versus control mice, whereas ↓ represents downregulation Psychopharmacology (2019) 236:2119–2142 2133

Fig. 5 MicroRNA-mRNA network in control versus CUMS-susceptible miRanda databases. Blue symbols present the elevated expression of mice. microRNA/mRNA networks were constructed between the 111 miRNAs or mRNAs. Yellow symbols present the downregulated genes miRNAs and 132 overlapped mRNAs with using transcriptome expres- or mRNAs sion data and predicted target genes from RNAhybrid, Targetscan, and mice (n = 3) versus control mice (n = 3), in which some miRNAs expression data and predicted target genes from three data- are upregulated or downregulated. Their predicted target bases. In Tables 6, 7, and S13, the regulations of mRNAs mRNAs match the measures by mRNA sequencing based on and the regulations of miRNAs are well matched. Consistent the databases (RNAhybrid, Targetscan, and miRanda) about results through jointly sequencing both mRNAs and miRNAs complex interactions between miRNAs and mRNAs. Table 4 validate our analyses and strengthen our conclusion. shows the altered miRNAs and their predicted target mRNAs. In order to validate the finding by sequencing miRNA Table 5 shows the altered mRNAs and their correspondent analysis, we selected certain miRNAs to do qRT-PCR, includ- miRNAs. Interactive networks about the miRNAs and over- ing miR-133a-3p, miR-183-5p, miR-219a-5p, miR-3074-5p, lapped mRNAs, which were based on transcriptome expression miR-335-3p, miR-34a-5p, miR-451a, and miR-487b-3p in data and predicted target genes from these three databases, were CUMS-susceptible versus control mice as well as miR- made in the Cytoscape (Fig. 5). By reading Tables 4, 5,andS11, 1188-5p, miR-132-5p, miR-187-5p, miR-194-3p, miR-34a- we can find that the regulations of mRNAs and the regulations of 5p, let-7i-3p, and miR-206-3p in CUMS-resilience versus miRNAs are matched well. control mice. Consistent with high-throughput sequencing, The expression profile of miRNAs is illustrated in these miRNAs are significantly changed in qRT-PCR from Table S12 if their expressions change above 1.5-fold in all CUMS-susceptible versus control mice as well as CUMS- CUMS-resilience mice versus control, where some miRNAs resilience versus control mice (Fig. 7). Their predicted target are upregulated or downregulated. Their predicted target mRNAs match the actually altered miRNAs (Tables 4, 5, 6, 7, mRNAs match the measures by mRNA sequencing based S11, and S13). Consistent results from analyses by miRNA on RNAhybrid, Targetscan, and miRanda about the complex sequencing and qRT-PCR validate our study. interactions between miRNAs and mRNAs. Table 6 shows the altered miRNAs and their predicted target mRNAs. Table 7 P2ry2 and Npffr1 mRNA are the targets of miRNA-34a-5p shows the altered mRNAs and their correspondent miRNAs. Interactive networks about miRNAs and overlapped mRNAs To validate silico prediction (Tables 4, 5, 6,and7), we selected are made in the Cytoscape (Fig. 6), based on transcriptome miRNA-34a-5p to examine whether it targeted to P2ry2 and 2134 Psychopharmacology (2019) 236:2119–2142

Table 6 The changed miRNAs predict target mRNAs in control versus CUMS-resilience mice miRNAs The predicted target mRNAs that match DEGs in miRNAs The predicted target mRNAs that match DEGs in transcriptome transcriptome miR-6988-3p↑ St18↓,Efna4↓ let-7b-3p↓ F2rl2↑,Nxph4↑ miR-7069-3p↑ St18↓ let-7e-3p↓ Pi15↑ miR-669h-5p↑ Dsp↓ let-7i-3p↓ Pappa2↑, Npffr1↑ miR-673-5p↑ Myof↓,Mia↓ miR-101c↓ Il27ra↑ miR-7a-2-3p↑ Acox2↓ miR-106b-5p↓ Tmem40↑,Sim1↑ miR-7a-5p↑ Gm38666↓, Twist1↓ miR-1199-5p↓ Fgl1↑ miR-7b-5p↑ Efna4↓, Sntn↓ miR-124-3p↓ Fgl1↑ miR-1188-5p↑ Asb16↓, Gpr156↓ miR-1264-3p↓ Pgr15l↑,Pappa2↑ miR-1251-3p↑ Gm3704↓ miR-129-1-3p↓ Itga11↑ miR-132-5p↑ Fmo2↓,St18↓ miR-1298-3p↓ Gabrq↑ miR-219b-5p↑ St18↓, Irx5↓,St18↓ miR-129b-5p↓ Gm19897↑ miR-344f-3p↑ Dsp↓,Txlnb↓ miR-1306-5p↓ Npffr1↑ miR-344h-5p↑ Irx5↓ miR-133a-3p↓ Myh2↑ miR-3544-3p↑ Osgin1↓, Olfml2b↓ miR-142a-3p↓ C920025E04Rik↑ miR-409-3p↑ Bdh2↓ miR-15a-3p↓ Klf14↑, Gm19897↑ miR-412-5p↑ Bdh2↓, Gm13293↓ miR-186-5p↓ Barhl2↑ miR-434-3p↑ Mettl11b↓,Gpr156↓ miR-187-5p↓ Gabrq↑ miR-451a↑ Nrl↓,Nmrk1↓ let-7d-3p↑ Trim65↓ miR-466e-5p↑ St18↓ miR-188-5p↓ Nxph4↑ miR-467b-5p↑ Gm38666↓,St18↓ miR-190a-5p↓ Sim1↑ miR-487b-5p↑ Trim65↓ miR-193a-3p↓ Gm19897↑ miR-146b-5p↑ Nrl↓,Dsp↓ miR-19a-3p↓ Itga11↑ miR-183-5p↑ Cabp7↓ miR-1b-5p↓ Il27ra↑ miR-1843b-5p↑ Acox2↓ miR-204-3p↓ C920025E04Rik↑ miR-448-3p↓ Myh2↑ miR-2137↓ Slc17a6↑ miR-466d-3p↓ Gabrq↑, Slc17a6↑ miR-216a-5p↓ Pappa2 miR-466f-3p↓ Gpr50↑,Sycp2↑ miR-219a-2-3p↓ Tmem40↑, Itga11 ↑ miR-467a-3p↓ Klf14↑ miR-219a-5p↓ F2rl2↑,Klf14↑ miR-483-5p↓ A730046↑, J19Rik↑ miR-219b-3p↓ Klf14↑ miR-539-5p↓ Fezf1↑ miR-219c-3p↓ Gpr50↑ miR-669o-3p↓ Slc17a6↑ miR-21a-3p↓ Ccdc42↑ miR-7662-3p↓ Pappa2↑,Nxph4↑ miR-24-3p↓ Oxct2b↑ miR-8112↓ Sim1↑ miR-3059-5p↓ Slc17a6↑,Itga11↑ miR-8114↓ Sim1↑ miR-3074-2-3p↓ C920025E04Rik↑,F2rl2↑ miR-874-3p↓ Itga11↑ miR-3074-5p↓ Fgl1↑, LOC106740↑ miR-879-5p↓ A730046J19Rik↑ miR-3093-5p↓ Kir3dl2↑ miR-194-5p↑ Pi15↓, Il16↓ miR-30a-5p↓ Fgl1↑ miR-370-5p↑ Tmem232↓,Krt5↓,Gm3704↓ miR-322-3p↓ Sim1↑ miR-378d↑ Was↓, Fmo2O↓,sgin1↓,Ccbe1↓ miR-324-3p↓ C920025E04Rik↑ miR-466f↑ Acox2↓,Cpn1↓,St18↓ miR-32-5p↓ F2rl2↑ miR-495-5p↑ Nrl↓,Twist1 ↓, Pi15↓ miR-337-3p↓ Myh2↑,Itga11↑ miR-221-5p↑ Nrl↓,Sntn↓ miR-338-3p↓ H2-Q2↑ miR-29c-5p↑ Bdh2↓,St18↓ miR-342-3p↓ Bdh2↑, Pi15↑ miR-592-5p↑ Tmem52↓, Tspan18↓ miR-34a-3p↓ Mab21l1↑ miR-665-3p↑ Itga11↓ miR-3552↓ Myh2↑ miR-138-1-3p↓ Npffr1↑, C920025E04Rik↑, Il27ra↑ miR-362-3p↓ Pappa2↑,Slc17a6↑ miR-140-3p↓ Gpr50↑,Sim1↑, Il27ra↑ miR-378c↓ Ccdc42↑ miR-188-3p↓ Pappa2↑,Sim1↑, Itga11↑ miR-423-5p↓ Tmem40↑ Psychopharmacology (2019) 236:2119–2142 2135

Table 6 (continued) miRNAs The predicted target mRNAs that match DEGs in miRNAs The predicted target mRNAs that match DEGs in transcriptome transcriptome miR-193b-3p↓ Gpr50↑,Fezf1↑,Itga11↑ miR-540-5p↓ A230065H16Rik↑, C920025E04Rik↑ miR-195a-5p↓ Pappa2↑, Il27ra↑ miR-671-3p↓ Tmem40↑, Rspo1↑, Gm19897↑ miR-206-3p↓ Gabrq↑, 1700030C10Rik↑, Gm19897↑ miR-7052-3p↓ Sim1↑,Misp↑,Itga11↑ miR-210-3p↓ C920025E04Rik↑,Itga11↑ miR-135b-3p↑ Myof↓, Il6ra↓,Olfml2b↓,St18↓ miR-30e-5p↓ Pappa2↑,Mab21l1↑,Rspo1↑ miR-135b-5p↑ St18↓,Tmem232↓,Myof↓ miR-3106-5p↓ Gabrq↑, A730046J19Rik↑ miR-668-5p↑ Gm38666↓, Tspan18↓, LOC100503496↓ miR-341-3p↓ Klf14↑, Gpr50 ↑,Sim1↑,Nxph4↑ miR-669f-5p↑ St18↓, Bdh2↓, Trim65↓ miR-34a-5p↓ Zfp541↑,Npffr1↑, Tmem40↑ miR-6964-3p↑ Osgin1↓, Tmem232↓,Was↓,Sntn↓ miR-344-3p↑ St18↓,Tmem232↓,Fmo2↓ miR-7226-3p↑ Twist1↓,Txlnb↓,Olfml2b↓,St18↓ miR-3547-5p↑ St18↓,Tmem52↓,Efna4↓,Txlnb↓, Gpr156↓ miR-5617-3p↑ Tmem52↓,Dsp↓,Cpn1↓, Txlnb↓,Tspan18↓ miR-5134-3p↑ Bdh2↓,Tmem52↓,Il6ra↓, Efna4↓, Il6ra↓, miR-374b-5p↓ Barhl2↑, Pappa2↑,Sim1↑ D630039A03Rik↓ miR-377-3p↓ Sim1↑, LOC106740↑ miR-466p↓-3p↓ Klf14↑,Mab21l1↑,Sim1↑

Note: ↑ indicates upregulation in the tissue of amygdala from CUMS-resilience versus control mice, whereas ↓ represents downregulation

Npffr1 by qRT-PCR and dual luciferase reporter assay. There are neural processes about neuroactive ligand-receptor interac- inverse correlations between them from qRT-PCR analysis tion, synaptic vesicle cycle, and nicotine addiction. Our data (Fig. 8). In dual luciferase report assay, we constructed luciferase suggest that the impairments of dopaminergic receptors and reporter plasmids, which contained the wild-type or mutant of the calcium signaling in the amygdala may be involved in predicted binding sites of the miRNAs in P2ry2 and Npffr1. CUMS-induced depression that the upregulations in genes These reporter constructs were transfected into HEK293T cells. relevant to neuroactive ligand-receptor interaction, synaptic The relative activities of luciferase reporter for P2ry2 and Npffr1 vesicle cycle, and nicotine addiction in the amygdala may be mRNA are significantly lowered by the mimics of miRNA-34a- involved in mouse resilience to the CUMS and that the 5p, but not negative control (Fig. 8), which are reversed by mu- downregulations of genes relevant to G protein coupled dopa- tating the binding sites of miRNA-34a-5p. These results support minergic serotonergic and GABAergic synapses as well as that P2ry2 and Npffr1 mRNA are the direct targets of miRNA- metabolic pathways may be involved in CUMS treatment. 34a-5p, which is consistent to our bioinformatics analyses in the In addition to the downregulation or upregulation of all prediction of miRNA target genes. genes in some signaling pathways, the imbalanced expression of genes in other signaling pathways may play role in depression versus resilience. As indicated in Table 2,somegenesin Discussion the given signaling pathways increase, whereas others in these pathways decrease in the amygdala of CUMS-induced depres- Using the high-throughput sequencing of mRNAs and sion mice, such as PI3K-Akt signaling pathway, neuroactive miRNAs, we have analyzed quantitative changes of mRNAs ligand-receptor interaction, regulation of actin cytoskeleton, and miRNAs in the amygdala from control, CUMS-suscepti- and synapse vesicle cycle. In comparison to CUMS-induced ble, and CUMS-resilience mice. The downregulated mRNAs depression mice, there is only retrograde endocannabinoid in CUMS-susceptible mice include the genes that encode neu- signaling that shows the increase of one gene and the decrease ral processes about dopaminergic type-II receptor, G protein of another one in CUMS-resilience (Table 3). Therefore, an coupled dopaminergic/serotonergic/GABAergic synapse, imbalanced expression among genes in intra-signaling path- metabolic pathway and calcium signal pathway, whereas the ways may be responsible for major depression, while less upregulated mRNAs are those genes that encode PI3K-Akt bidirectional change of genes in intra-signaling pathway signaling pathway, long-term depression, amphetamine addic- may help mice to be resistant to the CUMS, i.e., the prevention tion, and inflammatory-mediated regulation of TRP channels. of mice from CUMS-susceptible. The upregulation and down- To the amygdala in resilience mice, the downregulated regulation among genes relevant to multiple signaling path- mRNAs include genes that encode neural events about meta- ways as well as among genes in intra-signaling pathway make bolic pathway, PI3K-Akt signaling pathway, and G protein molecular networks in the amygdala to be imbalance, which coupled dopaminergic/serotonergic/GABAergic synapse, lead to neuronal dysfunction in the amygdala for major de- whereas the upregulated mRNAs are those genes that encode pressive disorder. 2136 Psychopharmacology (2019) 236:2119–2142

Table 7 The changed mRNAs predict target miRNAs in control versus CUMS-resilience mice mRNAs The predicted target miRNAs that match DEGs in mRNAs The predicted target miRNAs that match DEGs in transcriptome transcriptome

Asb16↓ miR-1188-5p↑ Barhl2↑ miR-186-5p↓,miR-374b-5p↓ Cabp7↓ miR-183-5p↑ Ccdc42↑ miR-21a-3p↓, miR-378c↓ Ccbe1↓ miR-378d↑ Fezf1↑ miR-193b-3p↓, miR-539-5p↓ Cpn1↓ miR-466f↑, miR-5617-3p↑ H2-Q2↑ miR-338-3p↓ D630039A03Rik↓ miR-5134-3p↑ Kir3dl2↑ miR-3093-5p↓ Gm13293↓ miR-412-5p↑ LOC106740↑ miR-3074-5p↓, miR-377-3p↓ Gm3704↓ miR-1251-3p↑, miR-370-5p↑ Misp↑ miR-7052-3p↓ Il16↓ miR-194-5p↑ Oxct2b↑ miR-24-3p↓ Krt5↓ miR-370-5p↑ Pgr15l↑ miR-1264-3p↓ LOC100503496↓ miR-668-5p↑ Rspo1↑ miR-30e-5p↓, miR-671-3p↓ Mettl11b↓ miR-434-3p↑ Sycp2↑ miR-466f-3p↓ Mia↓ miR-673-5p↑ Zfp541↑ miR-34a-5p↓ Nmrk1↓ miR-451a↑ Was↓ miR-378d↑, miR-6964-3p↑ 1700030C10Rik↑ miR-206-3p↓ Fmo2↓ miR-132-5p↑,miR-344-3p↑, miR-378d↑ A230065H16Rik↑ miR-540-5p↓ Gm38666↓ miR-467b-5p↑, miR-668-5p↑, miR-7a-5p↑ Irx5↓ miR-219b-5p↑, miR-344h-5p↑ Gpr156↓ miR-1188-5p↑, miR-3547-5p↑, miR-434-3p↑ Myof↓ miR-135b-3p↑, miR-135b-5p↑, miR-673-5p↑ Il6ra↓ miR-135b-3p↑, miR-5134-3p↑, miR-5134-3p↑ Olfml2b↓ miR-135b-5p↑, miR-3544-3p↑, miR-7226-3p↑ Osgin1↓ miR-3544-3p↑, miR-378d↑miR-6954-3p↑ Pi15↓ let-7e-3p↑, miR-194-5p↑,miR-342-3p↑, miR-495-5p↑ Trim65↓ let-7d-3p↑, miR-487b-5p↑,miR-669f-5p↑ Sntn↓ miR-221-5p↑, miR-6964-3p↑, miR-7b-5p↑ Tspan18↓ miR-5617-3p↑, miR-592-5p↑, miR-668-5p↑ Tmem232↓ miR-135b-5p↑, miR-344-3p↑, miR-370-5p↑, Twist1↓ miR-495-5p↑,miR-7226-3p↑, miR-7a-5p↑ miR-6964-3p↑ Fgl1↑ miR-1199-5p↓,miR-124-3p↓, miR-3074-5p↓, Acox2↓ miR-1843b-5p↑, miR-466f↑, miR-7a-2-3p↑ miR-30a-5p↓ Tmem52↓ miR-3547-5p↑, miR-5134-3p↑, miR-5617-3p↑, Dsp↓ miR-146b-5p↑, miR-344f-3p↑, miR-5617-3p↑, miR-592-5p↑ miR-669h-5p↑ Txlnb↓ miR-344f-3p↑, miR-3547-5p↑, miR-5617-3p↑, Efna4↓ miR-3547-5p↑, miR-5134-3p↑, miR-6988-3p↑, miR-7226-3p↑ miR-7b-5p↑ Npffr1↑ let-7i-3p↓, miR-1306-5p↓, miR-138-1-3p↓, Mab21l1↑ miR-377-3p↓,miR-30e-5p↓, miR-34a-3p↓, miR-34a-5p↓ miR-466p-3p↓ Nxph4↑ let-7b-3p↓, miR-188-5p↓, miR-341-3p↓, miR-7662-3p↓ Myh2↑ miR-133a-3p↓, miR-337-3p↓,miR-3552↓, miR-448-3p↓ F2rl2↑ let-7b-3p↓,miR-219a-5p↓, miR-3074-2-3p↓, Klf14↑ miR-15a-3p↓, miR-219b-3p↓,miR-341-3p↓, miR-32-5p↓ miR-466p-3p↓, miR-467a-3p↓ Nrl↓ miR-146b-5p↑, miR-221-5p↑, miR-451a↑, Gm19897↑ miR-129b-5p↓, miR-15a-3p↓,miR-193a-3p↓, miR-495-5p↑,miR-495-5p↑ miR-206-3p↓,miR-671-3p↓ Gabrq↑ miR-1298-3p↓, miR-187-5p↓, miR-206-3p↓, Gpr50↑ miR-140-3p↓,miR-193b-3p↓,miR-219c-3p↓, miR-3106-5p↓, miR-466d-3p↓ miR-341-3p↓,miR-466f-3p↓ Il27ra↑ miR-101c↓, miR-138-1-3p↓,miR-140-3p↓, Tmem40↑ miR-106b-5p↓, miR-219a-2-3p↓, miR-34a-5p↓, miR-195a-5p↓,miR-1b-5p↓ miR-423-5p↓,miR-671-3p↓ Slc17a6↑ miR-2137↓, miR-3059-5p↓, miR-362-3p↓, Bdh2↓ miR-29c-5p↑, miR-342-3p↑,miR-409-3p↑, miR-466d-3p↓, miR-669o-3p↓ miR-412-5p↑,miR-5134-3p↑,miR-669f-5p↑ C920025E04Rik↑ miR-138-1-3p↓, miR-142a-3p↓, miR-204-3p↓, Pappa2↑ let-7i-3p ↓, miR-1264-3p↓, miR-188-3p↓, miR-210-3p↓,miR-3074-2-3p↓, miR-324-3p↓, miR-195a-5p↓, miR-216a-5p↓, miR-219a-5p↓, miR-540-5p↓ miR-30e-5p↓, miR-362-3p↓, miR-374b-5p↓, miR-7662-3p↓ Itga11↑ miR-129-1-3p↓, miR-188-3p↓, miR-193b-3p↓, Sim1↑ miR-106b-5p↓, miR-140-3p↓, miR-188-3p↓, miR-19a-3p↓, miR-210-3p↓,miR-219a-2-3p↓, miR-190a-5p↓, miR-322-3p↓,miR-341-3p↓, miR-3059-5p↓, miR-337-3p↓, miR-665-3p↓, miR-374b-5p↓, miR-377-3p↓, miR-466p-3p↓, miR-7052-3p↓, miR-874-3p↓ miR-7052-3p↓,miR-8112↓, miR-8114↓ St18↓ miR-132-5p↑, miR-135b-5p↑, miR-219b-5p↑, miR-219b-5p↑, miR-29c-5p↑,miR-344-3p↑, miR-3547-5p↑, miR-466e-5p↑, miR-466e-5p↑, Psychopharmacology (2019) 236:2119–2142 2137

Table 7 (continued) mRNAs The predicted target miRNAs that match DEGs in mRNAs The predicted target miRNAs that match DEGs in transcriptome transcriptome

miR-466f↑,miR-467b-5p↑,miR-669f-5p↑, miR-669f-5p↑, miR-6988-3p↑, miR-7069-3p↑, miR-7226-3p↑

Note: ↑ indicates upregulation in the tissue of amygdala from CUMS-resilience versus control mice, whereas ↓ represents downregulation

The genes and their translated proteins are presumably re- low type-II dopamine receptor and G protein subunit-γ in the lated to the CUMS if their expressions alter in the same direc- amygdala leads to major depression by the CUMS. However, tion in CUMS-susceptible and CUMS-resilience mice, com- if this downregulation is associated to the elevated expression pared to control. This hypothesis is based on a fact that mice of Grbrq and Slc17a6 (Table 3), the upregulation of genes to receive the CUMS, but their consequences differ in mood their translated proteins to GABAergic, serotonergic, and do- states. By comparing the altered mRNAs among control, paminergic synapses prevents the suffering of major depres- CUMS-resilience, and CUMS-susceptible mice in their sepa- sion, i.e., resilience. Why the CUMS leads to the decrease of ration and overlapping, we find that certain genes are specif- Drd2 and the increase of Grbrq and Slc17a6 to have different ically changed in CUMS-susceptible or CUMS-resilience consequences remains to be examined. These data help us to (Fig. 4). However, Acox2, Barhl2, Ccdc42, Cldn22, Fezf1, figure out genes related to major depression and resilience. Gng8, Irx5, Itga11, Klf14, Lrrc38, Mab21l1, Mettl11b, Misp, Relationships between signal pathway versus neural impair- Myof, Osgin1, Oxct2b, Pappa2, Ppp1r17, Rspo1, Slc17a6, ment or resilience to the CUMS are interpreted below. The Tmem52, Zfp541, A730046J19Rik, A230065H16Rik, CUMS-induced downregulations of genes relevant to dopami- 4933429O19Rik,and1700030C10Rik are changed in the nergic type-II receptor, G protein coupled synapses (such as do- same direction between these two groups. For instance, paminergic, serotonergic, and GABAergic synapses), metabolic Gng8 encodes G protein subunit-γ (Downes et al. 1999)that pathways, and calcium signaling pathways in the amygdala from couples with synaptic receptors in dopaminergic, serotoner- CUMS-induced depression mice weaken the functions of neuro- gic, and GABAergic synapses. Gng8 is downregulated in nal responsiveness and driving force from the reward circuit. The CUMS-susceptible and CUMS-resilience (Tables 2 and 3). If CUMS-induced upregulation of genes relevant to PI3K-Akt sig- this downregulation is associated with the lowered expression naling pathway, amphetamine addiction, and TRP channels may of Drd2 (Table 2), the decreased dopaminergic synapse due to strengthen negative output in the amygdala. Both processes in

Fig. 6 MicroRNA-mRNA network in control versus CUMS-resilience miRanda databases. Blue symbols present the elevated expression of mice. microRNA/mRNA networks were constructed between the 120 miRNAs or mRNAs. Yellow symbols present the downregulated genes miRNAs and 68 overlapped mRNAs with using transcriptome expression or mRNAs data and predicted target genes from RNAhybrid, Targetscan, and 2138 Psychopharmacology (2019) 236:2119–2142

Fig. 7 The validation of differentially expressed microRNAs in the amygdala. a The validation of differentially expressed microRNAs in the amygdala from control (n =3) versus CUMS-susceptible (n =3) mice. b The validation of differentially expressed microRNAs in the amygdala from control (n =3) versus CUMS-resilience (n =3) mice

the amygdala may lead to low mood in major depressive disor- and nicotine addiction will benefit neuron response and synapse der. On the other hand, the upregulation of genes relevant to transmission in the amygdala for positive emotion in resilience neuroactive ligand-receptor interaction, synaptic vesicle cycle, mice, which counterbalances CUMS-induced depressed mood. Psychopharmacology (2019) 236:2119–2142 2139

In terms of the validation of our study, we have conducted molecules that are involved in depression, resilience, or stress the high-throughput sequencing of mRNAs and miRNAs, the treatment. Second, the amygdala is assumed to be an area quantitative RT-PCR of some RNAs changed in major depres- involved in the negative mood that is regulated by the reward sion or resilience, as well as the analysis of the interaction circuit including the ventral tegmental area and nucleus ac- between mRNAs and mRNA. Our results indicate that the cumbens. If major depression is due to lack of reward that will changed expression of mRNAs matches the changed expres- shift the balance to the negative mood, the analysis of molec- sion of miRNAs well in high-throughput sequencing ular profiles in the amygdala from CUMS-induced depression (Tables 4, 5, 6,and7). Some genes with their altered expres- and resilience should help to figure out the role of the amyg- sions in the high-throughput sequencing have been confirmed dala in major depression and resilience based on molecules by quantitative RT-PCR analysis (Figs. 2 and 3). Moreover, analyzed. The changes of certain genes have not been ob- interactions between P2ry2/Npffr1 mRNA and miRNA-34a- served in previous analyses (Bin-Bin et al. 2015; Jun et al. 5p are confirmed by dual luciferase report assay. Taken these 2013; Mei et al. 2014;Moreauetal.2011; Natalia et al. analyses together, we are confident to our results, which is 2010; Rajkowska et al. 2015; Smalheiser et al. 2014; better than previous analyses in either miRNAs or mRNAs, Smalheiser et al. 2011; Smalheiser et al. 2012), including and so on. Adora2b, Gng8, Hif3a, Plin4, Slc17a8, Fezf1, Mab21l1, A few advantages in our study are presented below. We Qrfpr,Acox2,Creb3l3, P2ry2, Trhr, Cldn22, Fgf3, Dusp9, paid attention to analyze and compare the profiles of mRNA Tead2, Efna4,andNinj2. These genes in the amygdala may and miRNAs in the amygdala from CUMS-induced depres- be newly working for major depression or resilience. It is sion and CUMS-resilience mice, which helps to figure out noteworthy that differences between our study and previous

Fig. 8 The miRNAs targeted mRNAs were validated by qRT- PCR and Luciferase reporter assay. Correlation between miRNAs and its prediction target expression by qRT-PCR in amygdala tissue. a The correlation between P2ry2 and miR-34a- 5p (r = − 0.959; p <0.05).b Luciferase reporter assay performed by the co-transfection of luciferase reporter containing wild or mutant of P2ry2 mRNA with miR-34a-5p mimic or negative control (NC) into HEK293T cells. c The correlation between Npffr1 and miR-34a-5p (r = − 0.976; p <0.05).d Luciferase reporter assay performed by the co- transfection of luciferase reporter containing wild or mutant of Npffr1 mRNA with miR-34a-5p mimic or negative control (NC) into HEK293T cells. Data are the mean ± SEM 2140 Psychopharmacology (2019) 236:2119–2142 studies may be due to a fact that our study was conducted in Beilharz TH, Humphreys DT, Preiss T (2010) miRNA effects on mRNA juvenile mice versus previous data from adult rodents. The closed-loop formation during translation initiation. Prog Mol Subcell Biol 50:99–112 reason for using juvenile mice is based on a fact that young Bellani M, Baiano M, Brambilla P (2011) Brain anatomy of major de- individuals stay in high prevalence to suffer from major depression II. Focus on amygdala. Epidemiol Psychiatr Sci 20:33–36 pression in response to chronic stresses (Xu et al. 2016;Zhu Bennett P et al (2008) Psychological factors associated with emotional et al. 2017). responses to receiving genetic risk information. J Genet Couns 17: 234–241 Amygdala has been indicated to be an important structure Bergstrom A, Jayatissa MT, Wiborg O (2007) Molecular pathways asso- for depressed mood in recent studies (Amy and Kiki 2008; ciated with stress resilience and drug resistance in the chronic mild Choi et al. 2015;Guillouxetal.2012;Hastingsetal.2004; stress rat model of depression: a gene expression study. J Mol – Karolewicz et al. 2009;Keele2005; Kim et al. 2016;Lebow Neurosci 33:201 215 Biggar KK, Storey KB (2011) The emerging roles of microRNAs in the and Chen 2016; Price 2010; Tasan et al. 2010;Wangetal. molecular responses of metabolic rate depression. J Mol Cell Biol 3: 2016). miRNAs are related to stress-induced mood disorders 167–175 (Orna and Alon 2015; Sharon et al. 2011;Volketal.2014). Bin-Bin L, Liu L, Xiao-Long L, Di G, Qing L, Li-Tao Y (2015) 7- For instance, amygdala miRNA-15a is essential for coping Chlorokynurenic acid (7-CTKA) produces rapid antidepressant- like effects: through regulating hippocampal microRNA expressions with chronic stress (Volk et al. 2016). miRNA-135 is essential involved in TrkB-ERK/Akt signaling pathways in mice exposed to for chronic stress resiliency, antidepressant efficacy, and intact chronic unpredictable mild stress. Psychopharmacology 232:541 serotonergic activity (Orna et al. 2014). 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