Anti-Mullerian Hormone As a Marker of Oocyte Quantity, Developmental

Anti-Mullerian Hormone as a Marker of

Oocyte Quantity, Developmental Potential, and Fetal Sex

by Anja Stojsin Carter

A Thesis Presented to The University of Guelph

In partial fulfillment of requirements for the degree of Doctor of Philosophy in Biomedical Sciences

Guelph, Ontario, Canada © Anja Stojsin Carter, December 2016

ABSTRACT

ANTI-MULLERIAN HORMONE AS A MARKER OF OOCYTE QUANTITY,

DEVELOPMENTAL POTENTIAL AND FETAL SEX

Anja Stojsin Carter Advisor: University of Guelph, 2016 Professor W. A. King

Delayed childbearing age, increased environmental pollutants accompanying modern life style, and an increase in inbreeding due to high demand for milk and meat yield have resulted in the decline in human and bovine reproduction respectively. Anti-Mullerian hormone (AMH) is expressed starting from 7-8 weeks of gestation in males and 20 weeks of gestation in females, in up to 100x higher concentration in males. AMH has been described as a non-invasive and accurate marker of ovarian quantitative fertility parameters in both humans and cattle. However, it is still unknown how AMH levels correlate to different fertility parameters in different cattle breeds; can AMH levels in the mother be used as a fetal sex marker during pregnancy in cows?

In humans, can AMH collected in the single follicular fluid (mono FF), as well as granulosa cell

(GC) AMH receptor 2 (AMHR2) be used as an embryo developmental potential marker? Here we present evidence of the higher levels of systemic and follicular AMH in Zebu compared to

European cattle, corresponding to higher levels of AFC and oocytes. Cows pregnant with a male fetus, as compared to a female fetus, were observed to have a significantly different change in plasma AMH between day 35 and 135 during gestation. The placenta and cotyledon were found to express AMHR2 between day 38 and 80, however not significantly different between

pregnancies with an opposite sex fetus. In the human study, systemic and average mono FF

AMH, and average mono GC AMHR2 expression were significantly negatively correlated with the patient’s blastocyst rate. When patients were divided into normal and high groups based on the their systemic AMH levels, the following was observed: normal systemic AMH level patients had a lower average FF AMH level and a higher blastocyst rate compared to the higher systemic

AMH level patients. Also, in normal systemic AMH patients, blastocysts corresponded to follicles with a lower level of AMH, while in high systemic AMH patients blastocysts corresponded to follicles with a higher level of AMH.

DECLARATION OF WORK PERFORMED

I declare that, with the exception of the items indicated below, all the work reported in the body of this thesis was performed by me.

Cattle ovaries and reproductive tracts were collected by Pradeep Blaraju, Steven Huang,

Heather Smale, Stephan Botha, and Brooklin Rushton during the course of these studies. Media used in Canada for oocyte in vitro maturation, in vitro fertilization, and in vitro culture were prepared by Liz St. John. Real time qPCR experiments in Chapter I were performed by Kiana

Mahboubi. Cell culture and DNA extraction were performed by Dr. Olutobi Oluwole. Antral follicle count, ovary diameter measurements, serum collections, slaughterhouse ovary collection, bovine anti-Mullerian hormone ELISA measurements, and fetal serum collection in Brazil were performed with the help of Dr. Moyses Miranda, Dr. Otavio Ohashi, Dr. Nathalia Nogueira, Dr.

Tiago de Bem, Rodrigo de Morais, Cinthia Lopes, Mayra Costa, Alessandra Ximenes, Tobias

Sovernigo, and Marcus Filho. ONE Fertility patient consents were obtained by Melody

Rasmussen and Maja Smrzlic. Human anti-Mullerian hormone ELISA measurements were performed by Alexandra Marinic-Cowden. Human follicular fluid collections were performed by

Michael Neal. Human in vitro fertilization, culture, embryo assessment and transfer were performed by Katie Willoughby, Lisa Deys, and Lindsay Moffatt. Daniel Gillis performed most of the statistical analysis.

ACKNOWLEDGEMENTS

First and foremost I would like to thank my supervisor Dr. Allan King. Allan provided me with the opportunity to work in his lab twice, doing a research project during the last year of my undergraduate degree, and then for my PhD, for which I was able to do a project highly relevant to my interests and goals. I was also given the opportunity to collaborate with a human fertility clinic and stay in close contact with the field in which my findings could have an impact.

I also have to thank Allan for the opportunity to go on a research exchange to Brazil, to work with his collaborators in Belem, Para. Last but not least, Allan has been incredibly understanding of my personal life; I got married and had a baby after the second year of my degree. Allan organized the baby shower and allowed me to pursue motherhood in parallel with work on my thesis. The people Allan gathered around himself are all brilliant and I had the honor of being part of his team.

I would like to thank Dr. Pavneesh Madan for his support throughout my project and his valuable input on the project progression and experiment planning. Dr. Madan also helped me troubleshoot through my immunofluorescence and confocal microscopy work, and was encouraging throughout my manuscript writing.

I would like to thank Dr. Neil MacLusky for guidance and support during my committee meetings and for his help with some of my statistics questions. Neil is a very sweet, approachable and genuine person, finding time to talk to students and allowing them to feel like one of his colleagues.

I would like to thank Mike Neal, ONE Fertility Burlington scientific director, for giving me the opportunity to collaborate, for his enthusiasm, for help with writing the ethics protocols, vi abstracts and manuscript, and for enabling me to collect valuable sample material, attend conferences, and extend my research opportunities by including a human study.

I would like to thank Dr. Julang Li, my external committee member, for kind words, support and guidance.

I would like to give a special Thank You to Dr. Laura Favetta. Dr. Favetta was my advisor, my friend, my sister, my parent. I met Laura during my undergraduate degree project and she has provided me with infinite help since then. It was an honor knowing Dr. Favetta, with her devoted and passionate approach to students and teaching. Dr. Favetta’s knowledge on qPCR and endocrinology kept me going in the right direction!

I would like to thank Dr. Daniel Gillis for his immense help and patience in performing majority of the statistical analysis in this thesis.

I would like to thank Liz St. John for her help with ovary and placenta collections, support in any lab related issues, and who, with her kindness, never intimidated the students around her.

I would like to thank Dr. Monica Antenos for sharing her knowledge, and providing incredible support in the lab, where she created a friendly, relaxed, but very stimulating atmosphere.

I would like to thank Ed Reyes and Allison MacKay for their technical support and patience, dealing with ordering supplies and questions at, often, inconvenient times.

I would like to thank Helen Coates for her patience and help with confocal microcopy. I would like to thank Dr. Tamas Ravay for his valuable input in qPCR and immunofluorescence and molecular troubleshooting. Dr. Ravay was also more than just a colleague; he was a friend and a support throughout this project. vii

I would like to thank Kiana Mahboube, a Masters student, who worked on part of my project and helped incredibly with qPCR work, and who has also been a close friend and support.

I would like to thank to Dr. Stalker, Kata Ozs, and Dr. Petrik for their help with troubleshooting experiments and cell material.

I would also like to thank our collaborators and extended family in Brazil, Dr. Miranda, Dr.

Ohashi, Dr. Costa, Dr. de Bem, and many others. Without your input this project would have been so much more boring. I loved my experience in Brazil, and thank you for providing me with so many opportunities to examine and learn so much about your beautiful cattle: Bos taurus indicus.

I would also like to extend my gratitude to the team at ONE Fertility, Burlington. Thank you to the embryologists: Katie, Lindsay, and Lisa for their patience to have me in the lab during their busy schedules, to have patients answer my questions, and to trust me to help them with some of their media preparations and case setups. I also would like to thank the andrology team: Tiffany and Leanne for allowing me to use some of their space to prepare research samples. I would like to thank the staff: Melody, Maja and Alexandra for their help with patient consent forms and running the human ELISA. Last but not least, I would like to thank Dr. Karnis, Dr. Amin, Dr.

Huges and Dr. Faghih for their trust and the opportunity to collaborate.

This research would have not been possible without the financial support from the OVC Doctoral

Scholarship, The Natural Sciences and Engineering Research Council of Canada (NSERC),

Canada Research Chair (CRC), and North/South Animal Biology and Reproductive

Biotechnology Consortium- Canada/Brazil Doctoral Student Research Exchange. viii

I would now like to thank my friends and family all around the world. I would like to thank my friends in Canada: Carolyn, Sarah, Jacky, Tobi, Kayla, Allison, Carmon, Leslie, Stewart,

Graham, Faz, Anh, Nayoung, Jyoti, Nina, Anuja, Moez, Ari and many others in the Biomedical

Sciences Department, including staff Kim Best and Frances Graziotto, for their friendship and support. I would like to thank especially my friend Gilan Abdelaal, who was there for me through the good, bad and the ugly. I would like to thank my former high school teacher Dragan

Gajic, for his love and passion for science that molded my undergrad and grad scientific path. I would like to thank my family in Canada, my in-laws Ludy and Ron, who provided me with support and kind words, lots of tasty food, and babysitting hours. I also owe a big Thank You to

Ludy who was kind enough to go through my thesis and correct all the grammar and spelling. I would like to thank my friends and colleagues outside of Canada: Sara, Tanja, Jelena, Vera,

Christina, Magda, Nathalia, Priscila, Cinthia, and many others for being there for me. Also, I would like to thank my past employer, Dr. Zorica Crnogorac-Ilic, for her passion in helping patients, the opportunity to work in her team, as well as her support in my idea to peruse a doctorate degree. I would like to thank my extended family, my aunts and uncles, my cousins, and my dad Radomir and his family for their support.

Now I would like to thank my close family, my grandpa, Bogomir, my mom, Vera and her partner Slobodan, my son Aleksandar and my husband Timothy for always being my rock and my inspiration. Hvala Vam!

TABLE OF CONTENTS

DECLARATION OF WORK PERFORMED ...... IV ACKNOWLEDGEMENTS ...... V LIST OF TABLES ...... XI LIST OF FIGURES ...... XII LIST OF ABBREVIATIONS ...... XV INTRODUCTION ...... 1 LITERATURE REVIEW ...... 5 HUMAN ASSISTED REPRODUCTION TECHNOLOGIES TODAY ...... 5 IN VIVO REPRODUCTION ...... 10 ESTROUS CYCLE ...... 11 ANTI-MULLERIAN HORMONE ...... 13 ANTI-MULLERIAN HORMONE RECEPTOR 2 ...... 15 AMH in males ...... 16 AMH in females ...... 17 AMH AS A CLINICAL MARKER OF OVARIAN RESERVE ...... 19 AMH AS AN OOCYTE AND EMBRYO DEVELOPMENTAL POTENTIAL MARKER ...... 21 From Human Serum ...... 21 From Human Follicular Fluid ...... 23 AMH AS A PCOS, DOR AND CANCER MARKER ...... 24 COW AS A MODEL FOR HUMAN REPRODUCTION ...... 25 DAIRY AND BEEF COW FERTILITY ...... 26 ANTI-MULLERIAN HORMONE IN CATTLE ...... 27 BOS TAURUS TAURUS VS. BOS TAURUS INDICUS ...... 28 AMH AS A FETAL SEX MARKER ...... 30 HUMAN VS. BOVINE PLACENTA ...... 33 RATIONALE, HYPOTHESIS, AND OBJECTIVES ...... 36 RATIONALE ...... 36 HYPOTHESIS ...... 37 OBJECTIVES ...... 37 CHAPTER I ...... 38 SYSTEMIC AND LOCAL ANTI-MULLERIAN HORMONE REFELCTS DIFFERENCES IN THE REPORDUCTION POTENTIAL OF ZEBU AND EUROPEAN CATTLE ...... 38 INTRODUCTION ...... 39 MATERIAL AND METHODS ...... 41 Animals and Experimental Design ...... 41 IVF ...... 42 ELISA ...... 43 RNA extraction and reverse transcription ...... 44 Real Time quantitative PCR ...... 45 Statistics ...... 46 RESULTS ...... 48 Study group 1 ...... 48 Study group 2 ...... 48 x

DISSCUSION ...... 53 CHAPTER II ...... 56 PREGNANCY ANTI-MULLERIAN HORMONE AS A FETAL SEX-DETERMINING FACTOR ...... 56 INTRODUCTION ...... 57 METHODS ...... 59 Animals and Experimental Design ...... 59 DNA extraction and sex confirmation using TSPY ...... 62 RNA extraction and reverse transcription ...... 63 Real time quantitative PCR ...... 63 ELISA ...... 63 Statistics ...... 64 RESULTS ...... 65 Study group 1 ...... 65 Study group 2 ...... 66 Study group 3 ...... 66 DISCUSSION ...... 69 CHAPTER III ...... 76 HUMAN MONOFOLLICULAR ANTI-MULLERIAN HORMONE IN RELATION TO OOCYTE DEVELOPMENT ...... 76 INTRODUCTION ...... 77 METHODS ...... 81 Patients and Experimental Design ...... 81 Monofollicular Sample Collection and IVF ...... 82 ELISA ...... 83 Cell culture ...... 83 RNA extraction and reverse transcription ...... 84 Real Time quantitative PCR ...... 84 RESULTS ...... 86 AMH per patient: ...... 86 AMH per individual follicles: ...... 86 DISCUSSION ...... 91 GENERAL DISCUSSION ...... 96 SUMMARY, CONCLUSIONS, AND FUTURE DIRECTIONS ...... 107 LITERATURE CITED ...... 110 APPENDIX ...... 129 APPENDIX I: DATA FROM CHAPTER II, STUDY GROUP 1 ...... 129 APPENDIX II: THE CONSENT FORM ...... 130 APPENDIX III: MONOFOLLICULAR SAMPLE COLLECTION INSTRUCTIONS ...... 133 APPENDIX IV: PROTOCOL FOR THE MONOFOLLICULAR OOCYTE COLLECTION ...... 135 APPENDIX V: MODIFIED CYCLE SHEET ...... 136

LIST OF TABLES

Table 1 Real Time PCR primers………………………………………………………………...46 Table 2 Summary of antral follicle count (AFC), ovary diameter (OD), plasma anti-Mullerian hormone (Pl AMH) from Study group 1, and follicular fluid AMH (FF AMH), oocyte, cleavage and blastocyst rate mean values (± SE) from Study group 2 for European type (E), Zebu (Z) and crossbred (C) cattle and the p-values from their average value comparisons. Significant difference (p<0.05) is indicated by the symbol (*)………………………………………………50 Table 3 Real Time PCR primers………………………………………………………………...61 Table 4 Real Time PCR primers………………………………………………………………...85

xii

LIST OF FIGURES

Figure 1 Correlations between anti-Mullerian hormone (AMH) and reproductive parameters in European type (E, light gray square), Zebu (Z, black triangle) and crossbred (C, dark grey diamond) cattle. The plots show simple linear regression trend lines for each of the breeds but that they do not reflect the model that was used in the statistical analysis. A) represented Study group 1 and B) represented Study group 2. Ai) Plasma AMH (Pl AMH) vs. antral follicle count (AFC) for E (n=7), Z (n=30) and C (n=6) animals. Z correlation, ρ=0.54, p=0.002; Z to E comparison, p=0.004; C to E comparison, p=0.049. Aii) Pl AMH concentration vs. ovarian diameter (OD) in E (n=6), Z (n=26) and C (n=6) animals. Z correlation, ρ=0.36, p=0.067; Z to E comparison, p=0.009; C to E comparison, p=0.094. Bi) Pl AMH vs. average number of oocytes per pair in Z (n=12; ρ=0.818, p=0.002); Bii) Follicular fluid AMH (FF AMH) concentration vs. number of oocytes in Z (n=24), and E (n=59) cattle. E correlation, ρ=0.37, p=0.005; Z to E comparison, p<0.0001. Biii) FF AMH concentration (ng/ml) vs. AFC in E (n=56; ρ=0.35, p=0.009)………………………………………………………………………………………….51

Figure 2 A) Relative granulosa cell anti-Mullerian hormone (GC AMH) mRNA expression in low vs. high oocyte producing ovaries for European type (grey, n=56) and Zebu (black, n=10) cattle. B) Relative GC AMH and anti-Mullerian hormone receptor 2 (AMHR2) mRNA expression in low (light gray) vs. high (dark gray) oocyte producing ovaries for European type cattle (n=56) was found to be significantly different (p=0.035). Glyceraldehyde 3-phosphate dehydrogenase housekeeping gene used to determine relative expression level, error bars denote the standard error of the mean (SEM) and significant difference (p<0.05) is indicated by the symbol (*)………………………………………………………………………………………..52

Figure 3 Visual representation of the three study groups for the Chapter 2. Horizontal line represents the time line of gestation divided into the three trimesters and each trimester into three months starting with artificial insemination (AI) of the cow and ending at birth. Literature based fetal expression of AMH is represented by either blue for male at 60 days or red for female at 150 days, with large and small arrows corresponding to the level of expression. In dark red: Study group I, collections at day 0, 35, 135 and 275 and study group II collections from 85 to 155 days of gestation and study group III collections from 38 to 80 days of gestation. In yellow: (Empey et al., 2012; Fanchin et al., 2007) detected significant difference in maternal blood AMH levels between male and female fetuses in humans in between 11th and 15th week of pregnancy, approximately corresponding to 77 and 105 days of gestation……………………………………………………………………………...…………. 61

Figure 4 Graphs representing plasma AMH (Pl AMH) values (pg/ml) measured using Ansh ELISA kit in cows Bos taurus indicus during gestation at 2 time periods, between day 35 and 135 (purple), and between day 135 and 275 (orange) carrying male (M; n=5) vs. female calves (F; n=3). A) Y-axis represents change in Pl AMH between M and F at two time periods, first time period found to be significantly different between M and F (p= 0.036), indicated by the symbol (*). B) Y-axis represents relative change in Pl AMH in terms of its previous value, example: Δ Pl AMH (day x - day y) / Pl AMH (day y). Error bars denote the standard error of the mean (SEM)………………………………………………………………………………….67 xiii

Figure 5 Graphs representing plasma AMH (Pl AMH) values (pg/ml) measured using Ansh ELISA kit in Bos taurus indicus cows (with male, n=10, in blue and with female, n=11, in red) and fetus (male, n=10, in green and female, n=11, in purple) at single time points throughout pregnancy, between day 85 and 155, fetus size from 15cm to 45 cm A) Graph represents average level of Pl AMH of pregnant cow and fetus for period from 85 to 155 days, sex denoted as male (M) and female (F). Difference between the cows was not significant (p=0.560), however differences that were significant were between the female fetuses and cows with those female fetuses (*, p<0.05), between the male fetuses and the cows with those male fetuses (**, p<0.05), and the male and female fetus (***, p<0.05). Error bars denote the standard error of the mean (SEM). B) Graph represents relationship between pregnant cow with male (green triangle) or female fetus (purple cross), or male (blue rhombus) or female fetus (red square) Pl AMH and fetus size in cm…………………………………………………………………………………...68

Figure 6 Graphs representing relative AMHR2 RNA expression from male (blue; n=6) and female (red; n=7) cotyledon (Cot.) and male (M. in blue; n=2) and female (F. in red; n=3) placenta (Plac.) during 1st trimester in Bos taurus taurus. A) Male vs. female relative AMHR2 RNA expression from cotyledon only, gestation days 38 to 76 for male, and 56 to 80 for female. B) Male vs. female cotyledon and placenta relative AMHR2 RNA expression. Gestation days from placenta samples 42 to 46 for males, and 70 to 80 for females. AMHR2 RNA was compared to two housekeeping genes Glyceraldehyde 3-phosphate dehydrogenase and Peptidylprolyl isomerase A to determine relative expression level. Error bars denote the standard error of the mean (SEM)…………………………………………………………………………68

Figure 7 Model describing the fetal testicular AMH secretion 1000x higher than the fetal ovarian AMH secretion and 100x higher than the cow’s ovarian secretion observed between day 85 and 155 of gestation. Model proposes that male fetal AMH crosses placenta and enters maternal circulation leading to the rise in the cow’s Pl AMH compared to the cows that carry female fetuses observed between day 35 and 135 of gestation……………………………….…………75

Figure 8 Anti-Mullerian hormone (AMH) per patient based approach. Correlations between AMH level, its relative receptor transcript amount and embryo development potential in six patients. Ai) Serum AMH (SE AMH) (pmol/l) vs. Average follicular fluid (FF) AMH (pmol/l) (p=0.017). Aii) SE AMH concentration (pmol/l) vs. Average relative GC AMHR2 RNA expression. Aiii) SE AMH (pmol/l) vs. Antral follicle count (AFC); Bi) SE AMH concentration (pmol/l) vs. Blastocyst rate (blast rate) (p=0.015). Bii) Average relative GC AMHR2 RNA expression vs. blast rate p=0.036. Biii) Average FF AMH concentration (pmol/l) vs. blast rate p=0.036…………………………………………………………………………………………..88

Figure 9 Comparisons between individual follicles serum (SE) AMH (pmol/l), average follicular fluid (FF) AMH (pmol/l), relative GC AMHR2 RNA expression, oocyte number and blastocyst (blast) rate between patients (n=3; blue) with “normal” 1.93-2.62 ng/ml and patients (n=3; red) with “high” between 4.21-6.79 ng/ml (x 7.14 to be converted to pmol/l). Significant difference was observed between “normal” and “high” groups for SE AMH, FF AMH and blast rate (p=0.048, p=0.038, and p=0.038, respectively). Glyceraldehyde 3-phosphate dehydrogenase and Peptidylprolyl isomerase A were used as housekeeping genes to determine relative expression xiv level. Error bars denote the standard error of the mean (SEM) and significant difference (P<0.05) is indicated by the symbol (*)……………………………………………………………………89

Figure 10 Comparisons between average of individual follicles that gave rise to blastocyst (red/blue) and non blastocyst (green) for each patient being from either “high” (i) or “normal” (ii) SE AMH groups, 4.21-6.79 ng/ml or 1.93-2.62 ng/ml respectively. Ai) Average Mono follicular fluid (FF) AMH (pmol/l) in “high” patient group from blast vs. non blast follicles respectively, patient 1 (n=1, n=2), patient 2 (n=2, n=3), patient 3 (n=5, n=2); Aii) Average Mono FF AMH (pmol/l) in “normal” patient group from blast vs. non blast follicles respectively, patient 4 (n=3, n=4), patient 5 (n=3, n=2), patient 6 (n=2, n=2). Bi) Average FF AMH/SE in “high” patient group from blast vs. non blast follicles respectively, patient 1 (n=1, n=2), patient 2 (n=2, n=3), patient 3 (n=5, n=2); Bii) Average FF AMH/SE in “normal” patient group from blast vs. non blast follicles respectively, patient 4 (n=3, n=4), patient 5 (n=3, n=2), patient 6 (n=2, n=2). Ci) Average relative GC AMHR2 RNA expression in “high” patient group from blast vs. non blast follicles respectively, patient 2 (n=1, n=1), patient 3 (n=3, n=1); Cii) Average relative GC AMHR2 RNA expression in “normal” patient group from blast vs. non blast follicles respectively, patient 4 (n=3, n=1), patient 5 (n=4, n=2). Glyceraldehyde 3-phosphate dehydrogenase and Peptidylprolyl isomerase A were used as housekeeping genes to determine relative expression level, and error bars denote the standard error of the mean (SEM)…………90

Figure 11 Ovaries from high and normal SE AMH patient groups with oocytes that developed to blastocysts corresponding to high FF AMH in red or low FF AMH in blue respectively, compared to oocytes that did not develop to blastocysts corresponding to FF AMH in green for both patient groups……………………………………………………………………………….95 Figure 12 “Size matters concept” representation of the ovary in which the ovarian size is positively correlated to: the ovarian reserve, the ovarian function (based on the oocyte developmental potential), and the systemic AMH level. However it is negatively correlated to the ovulatory follicular AMH level………………………………………………………………...106

LIST OF ABBREVIATIONS

AMH Anti-Mullerian Hormone

AFC Antral follicle count

IVP In vitro production

GC Granulosa cell

FF Follicular fluid

ART Assisted reproduction technologies

MOET Multiple ovulation and embryo transfer

AMHR2 Anti-Mullerian hormone receptor 2

SEF Social egg freezing

IVF In vitro fertilization

WHO World Health Organization

EDC Endocrine disrupting chemicals

HPG Hypothalamic-pituitary-gonadal axis

FSH Follicle stimulating hormone

LH Luteinizing hormone

FSHRc Follicle stimulating hormone receptor xvi

IGF Insulin growth factor cAMP Cyclic adenosine monophosphate

MII Metaphase II

MIS Mullerian inhibiting substance

TF Transcription factor

SF1 Sterioidogenic factor 1

WT1 Wilms’ tumor associated protein 1

TGF-beta Transforming growth factor beta

BMP Bone morphogenic proteins

GDF Growth and differentiation factor

GDNF Glial cell-derived neurotrophic factor

SBE Smad binding element

AMHR1 Anti-Mullerian receptor 1

Alk3 Activin-like kinase 3

Bmpr1a Bone morphogenic protein receptor 1a

SRY Sex determining region of Y chromosome

MMP Metalloproteinase xvii

PCOS Polycystic ovarian syndrome

OHSS Ovarian hyperstimulation syndrome

OPU Ovum pick-up

DOR Diminished ovarian reserve

KGN Ovarian granulosa-like tumor cell line

AI Artificial insemination

BCS Body condition score

Taurus/ European Bos taurus taurus

Indicus/ Zebu Bos taurus indicus

CL Corpus luteum

Pl Plasma

OD Ovarian diameter

COC Cumulus oocyte complex

IVM In vitro maturation

SOF Synthetic oviductal fluid

BSA Bovine serum albumin

ELISA Enzyme linked immunosorbent assay xviii dNTP Deoxyribonucleotide triphosphates qPCR Real time quantitative PCR

GAPDH Glyceraldehyde-3-Phosphate Dehydrogenase

H2A Histone 2A

YWHAZ Tyrosine 3-monooxygenase/tryptophan 5-monooxygenase

activation protein

HPRT1 Zeta hypoxanthine guanine phosphoribosyl transferase 1

SDHA Succinate dehydrogenase complex, subunit A

Glht General liner hypothesis test

PGD Preimplantation genetic diagnosis

AFP Alphafetoprotein

TSPY Testes-specific protein Y

PPIA Peptidylprolyl isomerase I hCG Human chorionic gonadotropin

TLM Time-lapse microscopy

Mono FF Monofollicular

SE Serum

2PN 2 pronucleus xix

REB Research Ethics Board

TESA Testicular sperm retrieval

ONE Ontario Network of Experts

FBA Fetal bovine serum eGFP Enhanced Green Fluorescent Protein

INTRODUCTION

Understanding ovarian physiology has both biological and economic importance. The ovary’s main role is to produce reproductive hormones and to house follicles, structures enclosing oocytes. Follicle number is established during embryogenesis and rapidly decreases towards birth and puberty. The time between puberty and menopause represents the reproductive life during which <1% of follicles will leave their dormant state and become recruited towards ovulation (Malek et al., 1998; Oktem and Oktay, 2008). The mechanism controlling this switch between dormancy and activation is under strict paracrine and endocrine control. Strict paracrine control ensures that individuals do not exhaust their ovarian reserve prematurely, allowing for maximized propagation of genetic material and survival of the species.

Anti-Mullerian hormone (AMH) is one of the paracrine factors involved in the regulation of follicle recruitment. In the female, AMH is secreted by the ovary and inhibits premature primordial follicle activation. It has been shown that ablation of this hormone causes premature menopause in mice (Durlinger et al., 1999; Pereira et al., 2013). In males, AMH is expressed earlier during embryogenesis in almost a hundred times higher concentration than in females, ensuring inhibition of Mullerian ducts that represent the embryological origin of the oviducts, uterus and upper part of the vagina (Sandvig and Llorente, 2012; Teixeira et al., 2001). In females, expression of AMH starts a few months later and in much lower concentration, reaching its peak in puberty. The levels in the female have been shown to reflect reproductive aging, ovarian reserve, number of growing follicles or antral follicle count (AFC), ability to respond to superovulation drugs, and number of oocytes retrieved during in vitro production (IVP)

(Anderson et al., 2012; J. J. Ireland et al., 2011; La Marca et al., 2009; Malek et al., 1998).

AMH function has been explored at cellular, follicular, ovarian, individual, population, subspecies, and species level. At the cellular level, AMH has been shown to be expressed by both Sertoli and granulosa cells (GCs) signaling in both an autocrine and paracrine fashion to cells of near proximity. Since AMH is expressed at highly different concentrations and times between sexes, it has been speculated that it might be utilized as a sex-determining marker during early pregnancy (Empey et al., 2012; Malek et al., 1998). At the follicular level, AMH is expressed by preantral growing follicles, keeping the remaining primordial follicles in a dormancy stage, and possibly reflecting the enclosed oocyte’s developmental potential

(Brownbill et al., 1995; Takahashi et al., 2008). At the ovarian level, AMH from pooled follicular fluid (FF) has been shown to correlate to overall pregnancy rates in humans (Duc-

Goiran et al., 2006; Wunder et al., 2008). Measured in serum and/or plasma, individual AMH levels have been shown to be consistent between estrous cycles, independent of the hypothalamic-pituitary-gonadal axis, and correlated to pooled FF levels (Morgan et al., 2011;

Rico et al., 2009; Wang et al., 2009; Wittmann and McLennan, 2011). When examined at the population level, AMH displays highly variable levels among individuals with different ovarian potential (Barker, 1944; J. L. H. Ireland et al., 2008). When examined between cattle subspecies

Bos taurus taurus and Bos taurus indicus, a specific AMH range has been shown to be characteristic of each subspecies (Batista et al., 2014; Firoozi et al., 2009; Hocher et al., 2009;

Walsh et al., 2015). At the species level, there are species specific average serum AMH levels

(Kumar et al., 2013; Stephen et al., 2002).

Human assisted reproduction technologies (ART) and cattle industry in vitro production

(IVP) have a common problem: decreasing fertility. Two of the main factors causing infertility in women are the increasing age of first time mothers and exposure to environmental stressors

related to a modern life style (Bushnik and Garner, 2008; Y. Nishi et al., 2000). As a consequence ARTs are acquiring increasing importance in the reproductive field, resulting in 5 million babies born worldwide from 1978 until 2012 (Brodin et al., 2013; Holte et al., 2011;

Kawamura et al., 2013; Sunkara et al., 2011; van Loendersloot et al., 2014). One of the main deficiencies of ART is the lack of markers of oocyte and embryo competence, which would allow for more accurate and consistent selection methods and increase in success rate. The lack of viability markers leads to problems such as multiple gestations and risk of preterm delivery, low gestational weight and long term post natal effects on the child’s development, and ethical issues with cryopreservation and creation of “excess” embryos (Grady et al., 2012; Keeton et al.,

1996).

Cattle industry IVP, responding to a declining fertility of 3-4% per decade, and has produced over 500,000 embryos per year (Lucy, 2001; Mapletoft, 2005; Ramsay et al., 2005;

Royal et al., 2000; Spencer, 2013). Dairy cattle particularly have been bred towards increased milk yield, that has been physiologically prioritized over fertility traits (Leroy et al., 2008;

Woodruff and Shea, 2010). Cattle IVP application has been improved due to the ability to cryopreserve genetically valuable embryos and transport them around the world. IVP also brought improvement in reproduction efficiency by retrieving up to hundred oocytes per single retrieval procedure from cattle using Multiple Ovulation, and Embryo Transfer to multiple recipients (MOET) (Gilchrist et al., 2008; Li and Albertini, 2013; Mapletoft, 2005). A better understanding of ovarian physiology, known to be highly similar between human and cow, could lead to individualized hormonal stimulation protocols and selection of the most viable oocytes and embryos, resulting in increased safety and efficiency of ART and IVP.

The aim of this thesis is to evaluate the correlation between granulosa cell AMH gene expression and plasma and follicular fluid AMH protein level on oocyte quantity, developmental potential, and fetal sex. AFC, ovarian diameter, oocyte number, blastocyst rate, FF and plasma

AMH levels, and GC AMH and AMH receptor 2 (AMHR2) expression were assessed in two cattle subspecies, Bos taurus taurus and Bos taurus indicus, with known fertility differences.

Secondly, pregnant maternal and fetal plasma AMH were compared in cattle carrying male vs. female fetuses. Finally, serum and monofollicular AMH levels and expression were compared to oocyte developmental potential in humans.

LITERATURE REVIEW

Human Assisted Reproduction Technologies Today

With over 5 million babies born worldwide and the imminent 40th anniversary of the birth of Louise Brown in 1978, the field of Assisted Reproduction Technologies (ART) went from being an experimental practice to a common clinical procedure to achieve the birth of a healthy singleton baby. One of the main reasons for the upsurge of ART in the last 4 decades is the increased age of first time mothers, as well as the negative influence of environmental stress on fertility. The number of 30 and over 35 year old first time moms grew from 15% to 26% and from 3% to 11% from 1987 to 2005 respectively (Bushnik and Garner, 2008; Norris et al., 2009;

Tsafriri et al., 1996; Webb et al., 2002). In addition, the mean of reproductive age moved from

24.6 to 29.1 between 1970 and 1999 (Berkholtz et al., 2006; Hsueh et al., 2015; Velde and

Pearson, 2002). The emancipation of women in the 1960s, leading to an increase in female education and participation in the labor force, an increase in the rate of divorce and remarriage, and the availability of more reliable forms of contraception contributed to a change in reproductive behavior. It resulted in delayed childbearing and a decreased number of children per couple in most Western-style societies (Agdi et al., 2010; Ortega-Hrepich et al., 2014; Velde and

Pearson, 2002). These sociological factors, together with a physiological decrease in female fertility with age, are reflected in the difference in infertility rates of 6% versus more than 30% between the 15-24 age group compared to the over 30 age group, making ART an indispensable and viable way to have biological children. The rise of “social egg freezing” (SEF) in the last couple of years allowed for reproductive autonomy for women and a way to arrest the biological clock (Argyle et al., 2016; La Marca et al., 2009). To illustrate the complex social issues surrounding the timing of conception, when companies such as Apple or Facebook took the

revolutionary step of offering SEF to their employees, women felt pressured to delay childbirth

(Baylis, 2015; Dunlop et al., 2016; Kawamura et al., 2013; Varghese et al., 2008; Xiao et al.,

2015).

SEF has been shown to represent 91% of non-oncological reasons for fertility preservation, compared to repetitive surgery (1%), endometriosis (6%) and other infertility causes (2%) (Donnez et al., 2011; Hsueh et al., 2015; Stoop et al., 2014). Using computer simulation, it was suggested that, with help of in vitro fertilization (IVF), a woman has a 90% chance of having a one-child family at age of 35 and a three-child family at the age of 28. If no

IVF was involved, the female age would drop to 32 and 23 respectively (Habbema et al., 2015;

Hu et al., 2014). Since 2009, the World Heath Organization (WHO) has recognized infertility as a disease of the reproductive system, defined by the failure to achieve a clinical pregnancy after

12 months or more of regular unprotected sexual intercourse (J. Johnson et al., 2005; 2004;

World Health Organization, 2011). Infertility is ranked as the 5th highest serious global disability of women under the age of 60, therefore deserving proper attention and treatment (Zegers-

Hochschild et al., 2009).

Besides maternal age being a contributor to infertility, environmental influences, especially rising levels of man-made endocrine disrupting chemicals (EDC), are affecting both humans and animals through eating, drinking, breathing, cosmetic application, and soil contact from waste, pesticide and fertilizer application (Krisher, 2013). EDC’s are stable and lipophilic compounds that accumulate over decades, causing both chronic and acute harm to female fertility (Ferris et al., 2015; Krisher, 2013). The direct effects on female reproduction are seen on oocyte maturation and blastocyst development, with Bisphenol A exposure during oocyte maturation in vitro resulting in spindle abnormalities, chromosome misalignment, decreased

embryo development, skewed sex ratio, and increased apoptosis in blastocysts (Ferris et al.,

2015). BPA is one of the highest volume synthetic chemicals produced worldwide, exceeding 5.4 million tons in 2015, and present in urine, blood, FF, and tissue of 92.6% of Americans and 90% of Canadians (Bushnik et al., 2010).

One of the major limiting factors of ART is financial. In the USA, for example, the cost is up to $15,771 per treatment, and $55, 450 per live birth. (Scheetz et al., 2012). In some countries, such as Canada, Belgium, the UK, Argentina, Uruguay, Israel, and Serbia, 1-3 cycles of ART are fully funded, while in others such as Australia, Brazil, and Germany treatment is partially funded. This assists patients to conceive without being limited by their economic status.

It has been estimated that this investment in ART by governments is highly justified in the long term due to an eight fold return of approximately $127,000US, in net tax revenue during a person’s lifetime (Connolly et al., 2008). There are two major ART cost factors: ovarian stimulation drugs and in vitro media culture systems. Both of these can be reduced with more precise patient selection, simpler patient diagnostic methods, correct ovarian stimulation, simplified procedures and equipment in the lab, and minimized complications caused by ART

(Maheshwari and Teoh, 2014).

The main drawback of ART is that the long-term effects are unknown, since the oldest child is not yet forty. One of the possible consequences of ART is that unfavorable reproductive traits are being carried from one generation to the next, with increasing chances that the children conceived by ART will also need assistance in reproducing. Regarding the effect of ART on developmental competencies of children, a well-conducted Canadian study examined children ages 0-5. This study provided evidence of increased risk of prenatal and birth-related risk factors associated with being conceived by mothers aged 35 and older. It was difficult to differentiate

between the negative effects due to the use of ARTs versus those due to preterm birth and low gestational weight. However, the children seemed to also have better outcomes in many of the tested cognitive, physical, and behavioral criteria compared to children from younger moms

(Bushnik and Garner, 2008). It was found that time spent with the child, relationship factors, and financial resources have significant impact on developmental milestones such as the age when the child first ate solid food, sat up, said the first word, or made the first step (Bushnik and

Garner, 2008). There are other potential long term epigenetic risks following ART procedures, such as Beckwith-Wiedemann syndrome, Angelman syndrome, and the more recently recognized maternal hypomethylation syndrome, and neurological risks such as cerebral palsy, that need to be evaluated further (Vulliemoz and Kurinczuk, 2012). Also, possible increased cancer risk due to ovarian stimulation drugs is still under investigation and long term data is necessary to remove all the confounding factors (Brinton et al., 2012).

Currently the in vitro parameters for women under 40 using ARTs are ~70% fertilization,

~30% blastocyst rate and ~20% pregnancy rate compared to ~90% fertilization and ~50% pregnancy success rate with natural conception and timed intercourse (Grodon, 2003; Leroy et al., 2012). One of the reasons for the lower ART pregnancy rate is the inability to select an embryo with the highest developmental potential. To compensate for the lowered pregnancy rate, transfer of more then one embryo is commonly performed, often resulting in multiple gestations.

Multiple gestations are associated with high rates of pregnancy-related and neonatal complications such as preterm delivery, decreased weight for gestational age, 7.4%, 21.6%, and

50% of twin, triplet, and quadruplet pregnancies respectively, and birth of at least one child with developmental disabilities. In addition, cost increases with multiple gestations, being 10 times higher for a triplet vs. singleton pregnancy (Maheshwari and Teoh, 2014). In the US, from 1980

to 1997 the number of live birth twin deliveries rose 52%, and high order multiple gestations increased 404% from 1,337 to 6,737 births (Hankins and Saade, 2005). It is estimated that twin pregnancies represented 1 in 44 births but accounted for 1 in 8 perinatal deaths. In Australia, the reduction in multiple births by half allowed for a 55% increase in availability of IVF services, by redirection of funding and resources. (Chambers et al., 2011).

The main concerns of IVF remain: how to improve our ability to detect oocytes and embryos with developmental potential that would lead to pregnancy and a healthy child, and how to mimic the in vivo environment to provide the optimal conditions for the oocyte and embryo to sustain its development in vitro (Chronopoulou and Harper, 2014)? These oocyte and embryo selection methods need to fulfill criteria such as being simple and rapid, inexpensive, to allow for high throughput and consistency, and, most importantly, to be non-invasive. Maybe a new hope in the future lies in microfluid platforms in which automated robots perform the entire IVF protocol without any human input; however these are still only a matter of science fiction

( Swain et al., 2013). Current methods of selection include the fields of transcriptomics, proteomics, metabolomics, but the most commonly used method is still morphology combined with kinetics-based assessment. There is a wide body of data showing that all currently existing methods lack precision and consistency to detect oocytes and embryos with the highest developmental potential (Balaban and Urman, 2006; Boni et al., 2002; Ebner, 2003; Maheshwari and Teoh, 2014; Rienzi et al., 2010; Robert et al., 2001; Sinclair, 2008; Stojkovic et al., 2001).

In vivo reproduction

The oocyte is one of the most unique cells in the mammalian body. It meiotically divides, resulting in cells with haploid genetic material, is able to give rise to all other cells of the body by being totipotent, reprograms somatic nuclei, and reprograms sperm chromatin to a functional pronucleus. It is also a cell that contains the distinctive combination of parental genes through the process of crossing over. Oocyte importance can be evidenced by the complex endocrine physiology that regulates its creation, storage, selection, maturation, ovulation and fertilization.

The creation of oocytes takes place during embryogenesis in which 1000-2000 primordial germ cells migrate to the genital ridges where they can start mitotically dividing, generating around

~7x106 oogonia, and populating an area that will develop into ovaries (Velde and Pearson, 2002).

Other mesodermal somatic cells come to “help” by providing a supporting and structural role in organ development. These cells are destined to become granulosa and theca cells, and have important roles in hormone secretion and regulation, ensuring proper oocyte storage and nurturing for up to 50 years in humans. The complexity and codependence of the interaction between these two cell types, germ and somatic, is just starting to be revealed by research (Eppig et al., 2002; Li and Albertini, 2013; Oktem and Oktay, 2008; Rodgers and Irving-Rodgers, 2010;

Webb et al., 2002).

At around 20 weeks of gestation in humans, somatic cells start to envelope oogonia and form structures called primordial follicles (Oktem and Urman, 2010). Surrounded by somatic cells, oogonia are ready to start their journey from the diplotene stage to the haploid oocyte. The process at first only progresses to prophase I of the first meiotic division, and gets arrested at this stage, mainly in the primary stage follicles that stay dormant until puberty. By the time of puberty, the follicle number is lessened by almost 80% of its starting quantity (Erickson, 1966).

Only a limited number of the remaining follicles are reawakened or recruited, in a strictly timed manner under the control of both direct paracrine and indirect endocrine factors, after having been arrested from 13-14 years, at puberty, or for as long as 45-50 years, at menopause (Oktem and Oktay, 2008).

Estrous cycle

Recurring time periods where the female hormone estrogen is produced by ovaries, in set patterns during reproductive life, is called the estrous cycle. Sexual maturity starts in puberty with the establishment of the hypothalamic-pituitary-gonadal axis (HPG). The hypothalamus secretes gonadotropin-releasing hormone that triggers the pituitary gland to produce follicle stimulating hormone (FSH) and luteinizing hormone (LH), that in turn leads to gonadal secretion of steroid hormones. Establishment of HPG results in reawakening, growth, maturation and ovulation of selected follicles, setting the stage for fertilization, implantation and pregnancy. If fertilization, implantation and pregnancy do not occur, HPG leads to another cycle of endocrine hormone secretion, triggering a new set of dormant follicles. Follicle number in an individual’s lifetime is considered an ovarian reserve. This paradigm can be challenged when new oocytes are generated from germ cells throughout an individual’s reproductive life (J. Johnson et al.,

2005; 2004). However, the vast majority of the available follicular pool comes from those generated during embryo development. The reawakening of follicles happens in cycles or

“waves” where a group of 5-10 follicles is triggered to enter the growth phase. Usually there are three of these waves per one estrogen cycle, and the last wave results in one ovulatory follicle

(Driancourt, 2001). The entire process of selection, growth and maturation of the follicle with

ovulation takes about 90 days and this process is governed by fluctuations of reproductive hormones depending on the follicle growth stage (Webb et al., 2004). Follicle growth is paracrine influenced stages for approximately 80 days, due to lack of presence of endocrine FSH receptor (FSHRc) and consist of: primordial, primary, and secondary. Following paracrine, are the endocrine influenced stages, of mainly FSH, that occur for only the next 7-9 days and consist of antral and ovulatory (Driancourt, 2001; Oktem and Oktay, 2008; Sirard, 2001). The stage of the follicle is defined based on the morphological appearance of the follicle and the cells enclosed in the follicle. The oocyte goes through complex cytoplasmic changes during maturation stages including organelle redistribution, cytoskeleton dynamics, molecular maturation, and zona pellucida acquisition (Ferreira et al., 2009). The primordial follicle,

~0.03mm in size, is defined as one with only one arrested oocyte, with one layer of flattened GC layer (Velde and Pearson, 2002). The primary follicle, 0.03-0.1mm in size, is one where the GCs start changing shape from flattened to more cuboidal. The ovary is mostly populated by primary follicles until puberty. The secondary follicle, 0.1-2mm in size, occurs when the number of GC layers change from one to two or more. The antral follicle, 3-8mm in size, is when there is a development of a cavity in the follicle as a result of apoptosis, and the follicular fluid (FF) fills the cavity. At this stage, under the influence of FSH, an aromatase enzyme starts being expressed by GCs, converting androgens produced by theca cells to estrogen. The GCs also produce activins, inhibins, follistatins, and insulin growth factors (IGF) (Webb et al., 2007). All of these paracrine factors have a role in proper follicle and oocyte growth. The ovulatory follicle, 8-

10mm in size, is a follicle where the membrane is thinning and GCs are starting to express LH receptors. Pulsatile action of LH is what causes the rupture and ovulation. The follicle that first obtains the highest number of LH receptors is the one selected for ovulation (Hamel et al., 2008).

The oocyte resumes meiosis approximately 24 hours prior to ovulation, initiated by a decline in the surge of cyclic adenosine monophosphate (cAMP) through the gap junction from GCs to oocyte. During these 24 hours, the oocyte reaches metaphase II (MII) of the second meiotic division (Norris et al., 2009). As long as the dominant follicle is present, there is no further recruitment. This process of dominance selection occurs randomly between the ovaries

(Driancourt, 2001). The majority of follicles are at the dormant stage with only less than 1% becoming selected to be ovulatory in a lifetime.

Anti-Mullerian Hormone

Alfred Jost in 1947 defined a second male determining factor besides testosterone, called

Mullerian Inhibiting Substance (MIS). As its name suggests, its function in the male embryo is to inhibit the Mullerian duct development. Later, the name more commonly used became Anti-

Mullerian Hormone (AMH). The human AMH gene is located on 19p13.2-13.3. This is a relatively short gene of 2.75kb, divided into 6 exons, giving rise to 1.7kb mRNA. Bovine and mouse promoters are a canonical TATA box, with a single transcription start site located 10bp upstream of the ATG. The human promotor is a degenerate TTAA motif at 26 bp, with the functional initiator element recognized by the transcription factor (TF) II-I. The proximal promoter displays a number of evolutionary conserved binding elements: steroidogenic factor 1

(SF1), two GATA, one SOX9, and Wilms’ tumor associated protein 1 (WT1), all indicating a common AMH expression in mammals (Lasala et al., 2004). Main regulators of AMH expression are Sf1, Gata4, Wt1, Dax1 and Fog2 (Salmon et al., 2004a). Without the binding of

SF1 and the pair of GATA4, no up regulation of AMH is initiated (Watanabe et al., 2000). AMH

mRNA is translated to a 140kDa disulfide linked glycoprotein homodimer, belonging to a transforming growth factor (TGF)-beta family of proteins. In humans it is synthesized as 560 amino acids with a half life of 3-5 days in serum (La Marca et al., 2009; Lasala et al., 2004).

TGF-beta family is composed of 33 related polypeptides that, beside AMH, also include bone morphogenic proteins (BMP), growth and differentiation factor (GDF), activin/inhibin subfamily, glial cell-derived neurotrophic factor (GDNF), and nodal (Knight, 2006). All of these are involved in injury repair, cellular proliferation, differentiation, adhesion, and immunity

(Morikawa et al., 2016). Disturbance in TGF-beta signaling leads to a variety of diseases such as connective tissue disorders, fibrosis, and cancer (Morikawa et al., 2016). Even with TGF-beta family being large, there are many fewer receptors and downstream intercellular effectors than signaling molecules. They all signal through trans-membrane serine/threonine kinases, consisting of seven type I receptors and five type II receptors, forming heteromeric type I/type II receptor complexes. Ligand binding to a tetrameric receptor complex stabilizes and activates their signaling capacities, further phosphorylating Smad proteins. Smads got their name from studies in Drosoplila and C. elegans proteins, in which Sma and Mad were identified respectively and found to be very similar to human, frog and mouse signaling molecules. The

Smad complex translocates to the nucleus where it binds to the promoter Smad Binding Element

(SBE) causing up regulation of metalloproteinases in males and down regulation of follicle recruitment and growth factors in females (La Marca et al., 2009).

140kDa AMH undergoes posttranslational proteolytic cleavage, starting from covalently bound prepropeptide and cleaving to become propeptide non-covalently linked between the N and C terminal domain. Each homodimer becomes 110kDa (pro region) and 30kDa (mature region) in size. The pro region is where main species-specific sequence differences are located,

and the mature region is where most biological activity resides. Unlike other TGF-beta members, these two regions remain non-covalently associated and bind to the receptor. The pro region is believed to be involved in proper folding and delivery of the mature region to the receptor

(Morikawa et al., 2016). The biological activity of the mature vs. combined promature version is enhanced by almost double, indicating that mature version contains hydrophobic properties and differential folding, decreasing its potency. The non-covalent promature complex is highly sensitive to heat and pH stress, making it difficult to construct a bioassay that is stable and consistent. Because the immature covalent version is non biologically active and present in a very low amount, ~4%, of the total AMH, the proteases serve as a regulatory mechanism reassuring the promature version is present at the site of action. After the promature complex binds to the receptor, the two regions dissociate, with the mature region bound to the receptor, and the pro region remaining loose in the proximity of the receptor (di Clemente et al., 2010;

Wilson et al., 1993). AMH is known to be a protein with highly conserved function throughout mammalian kingdom with homology between 74% and 68% to bovine, rat and mouse and 27% and 33% to chicken and alligator (Teixeira et al., 2001)

Anti-Mullerian Hormone Receptor 2

AMHR2 is a transmembrane receptor with serine/threonine kinase activity. It is highly specific, sharing 30% overall homology with other TGF-beta family type II receptors (Teixeira et al., 2001). It is expressed at day 15 in mouse embryo in both male and female in the mesenchymal cells of the gonads surrounding the Mullerian ducts. AMH binds AMHR2, which causes further phospohorilation of AMH receptor 1 (AMHR1), also known as activin-like kinase

3 (Alk3), or bone morphogenic protein receptor 1a (Bmpr1a). This heteromeric complex acts downstream, phosphorylating Smad proteins within the cytoplasm. AMHR2 is thought to have two splice variants, both with an inhibitory role on AMH (Imhoff et al., 2013). Monniaux et al. has shown that the AMHR2 expression pattern resembles AMH transcript levels during follicular maturation stages in the caprine species (Monniaux et al., 2011).

AMH in males

AMH was primarily discovered as a male determining factor crucial in male sex differentiation. Knock out of this hormone in males leads to a normal male phenotype but with

Mullerian duct persistence, formation of a uterus and fallopian tubes, azoospermia due to malformation of the ductus deferens and agenesis of epydidymus, with testes adhered to the uterine tubes or in the abdominal and inguinal region, and normal testicular histology with presence of spermatogonia (M. Y. Nishi et al., 2012). The internal genitalia possess the intrinsic tendency to feminize in the absence of the Y chromosome (Kuijper et al., 2013). AMH is one of the first genes to be expressed from the bipotential gonad, leading to differentiation of testes under the influence of the sex determining region of Y chromosome (SRY) (La Marca et al.,

2010; Teixeira et al., 2001). In males both Sertoli and mesenchymal cells express AMH that up regulates metalloproteinases (MMPs) in the surrounding epithelial duct cells. This leads to the breakdown of the extracellular matrix and ultimately the disappearance of Mullerian ducts

(Visser, 2003). AMH is also known as a male determining factor in different conditions of hermaphroditism and tumor growth. Aksglaede et al. studied the AMH serum levels and found

that they reach a peak of about 1082pmol/l (~150ng/ml) at 12 months after birth and then decline, being ~20% lower at the age of 7 and a further 3-4% during adulthood (Ebner, 2006).

AMH in females

Until the 1990s, AMH function and importance was more studied in males due to the fact that expression of AMH in the male embryo precedes that of the female embryo by ~3 months in utero, and is expressed in concentrations a few hundred times higher compared to the female embryo. In the female embryo AMH is secreted by GC cells and is dependent on the follicle stage, starting with expression in primary follicles and lasting to the antral stage, being highest in the preantral follicles (Themmen, 2005; Visser et al., 2006; Visser and Themmen, 2005). Knock out of AMH in the female mouse embryo causes premature exhaustion of ovarian follicle reserve and early menopause (Durlinger et al., 1999). In mono-ovular species such as the sheep, cow, monkey and human, AMH plays a key role in modulating follicle growth and development

(Campbell et al., 2012), inhibiting follicular growth, maturation, and dominant follicle selection during the gonadotropin responsive phase (Xu et al., 2016). In poly-ovular species, the function of AMH is to inhibit recruitment of primordial and primary follicles (Xu et al., 2016). In summary AMH could be defined as an intra- and inter- follicular “guardian” of follicle recruitment and development (Salmon et al., 2004b). Additional studies using bovine, mice and rat embryonic ovarian cortical pieces, in culture or placed in sham, or in ovariectomised chick embryos in ovo showed evidence that AMH inhibits follicular growth (Fortune et al., 2011;

Nilsson et al., 2007; 2011). In vitro, when recombinant AMH was added to the cortical ovarian pieces, the number of primordial follicles increased while the number of primary follicles

decreased with increasing AMH concentration (Fortune et al., 2011). As mentioned earlier, dormancy is the fate of the majority of follicles throughout female life. It is believed that this inhibition is achieved through suppression of steroidogenesis and differentiation of somatic cells in the gonads (di Clemente et al., 2003). AMH has been shown to down regulate expression of aromatase, LH receptor, and steroidogenic enzymes (Visser, 2003). The rate of dizygotic twinning increases with age and chances of twinning increase with every consecutive pregnancy

(from 1.3% in the first to 2.7% in the fourth pregnancy) (Hankins and Saade, 2005), suggesting that the decrease with age in the stringency of AMH’s ability to inhibit follicle recruitment might result in a higher rate of dizygotic twinning. In the presence of AMH, the effect of FSH as one of the necessary HPG factors for follicle growth is decreased. In addition, in vivo more follicles start to grow under the influence of exogenous FSH in AMH-deficient mice compared with the wild types (Durlinger et al., 2001). In a sheep study by Campbell et al., FSH addition caused an increase in the proportion of small antral follicles with no changes in the pattern or intensity of

AMH expression (Campbell et al., 2004). The AMH mRNA level was significantly lower after

10 days of culture without FSH. However, this decrease was not reflected in the number of growing follicles, which may suggest that AMH expression in vitro could be high enough to keep control over follicle recruitment (Sadeu et al., 2008). Even with prior evidence suggesting that FSH promotes while AMH inhibits follicular growth, in a AMH KO study FSH was shown to be unnecessary for initial recruitment of follicles, indicating predominantly paracrine control

(Oktem and Urman, 2010). IGF-I has been proposed to have a regulating paracrine role on both

AMH and FSH via a “break free” mechanism from the inhibitory influence of AMH on the growing follicles (Campbell et al., 2012). AMH was also reported to exhibit a dose responsive inhibitory effect on LH-stimulated androgen production by theca cells (Campbell et al., 2012).

This is particularly important in pathologies such as polycystic ovarian syndrome (PCOS) where this balance is disturbed.

AMH as a clinical marker of ovarian reserve

Being suppressive of follicle recruitment and reflecting ovarian reproductive aging, AMH gained clinical importance as a marker of 1) ovarian follicle reserve and 2) the number of gonadotropin sensitive follicles, also known as the antral follicle count (AFC) (J. J. Ireland et al.,

2011; Kevenaar et al., 2006). These two ovarian parameters, ovarian reserve and AFC, are interchangeably used in a clinical ART setting as a highly individually repeatable, as well as a non-invasive way to assess the current status and prognosis of patient outcome (Burns, 2005;

Chang et al., 1998; Sonigo et al., 2016). Ovarian reserve, estimated by AMH, in general reflects the total quantity of oocytes available in the ovary, while AFC is a measure of the number of growing follicles (Erickson, 1966; J. J. Ireland et al., 2011; J. L. H. Ireland et al., 2008).

Measured in serum at any stage of the estrous cycle, AMH is found not to have significant fluctuations, irrespective of the other reproductive endocrine and paracrine hormonal concentrations (La Marca et al., 2009). AMH is also found to be consistent in individuals and animals from one cycle to the next, making it an excellent marker of inter- and intra- cycle ovarian status (La Marca et al., 2006; La Marca and Volpe, 2006). This is very important when, in comparison, the individual inter-cycle AFC variation has been demonstrated to change by a factor of 5-7. To demonstrate the potential for AMH as a good prognostic tool for fertility, it could be used a cattle herd setting to identify the approximately 30% of cattle that end up producing 70% of total embryos (J. J. Ireland et al., 2007). One of the definite benefits of using

AMH over AFC is that it can be done offsite and it is not affected by the technical skills of personnel. The most concrete result linking AMH, AFC and ovary size shows that ovarian size is reflective of female fertility, a concept long known in the context of male fertility (Coulter and

Foote, 1979; J. J. Ireland et al., 2011; Keeton et al., 1996). AMH can more accurately predict occurrence of menopause within 4 years, with 0.87 stringency, than can AFC (Visser et al.,

2006). The latest study by Sonigo et al. provides the threshold values of AMH and AFC, being

3.7ng/ml and 20 respectively, for approval for oocyte crypreservation after in vitro maturation procedure in IVF patients (Sonigo et al., 2016).

In the ART setting, the number of growing follicles is an important estimate, since those follicles are sensitive to ovarian superovulation drugs, allowing for growth of more than one follicle and more than one mature oocyte. An incorrect estimate of the patient’s response can lead to ovarian hyperstimulation syndrome (OHSS), one of the major risks in ART. OHSS occurs when a patient is overdosed on gonadotropins, leading to ovarian hyper response and possibly resulting in: enlargement of the ovaries, abdominal pain, nausea, diarrhea, dehydration, rise in blood pressure, and even in rare cases: thrombosis, distention, oliguria, pleural effusion, and respiratory distress. This condition is considered life threating and it often requires hospitalization. Therefore, correct ovarian stimulation needs to be a balance between achieving an adequate oocyte yield without causing adverse effects. Current stimulation procedures are based on the monitoring of follicular growth using ultrasound and biochemical hormonal analysis. However these are still considered “without the predictive value of individual ovarian potential …. over simplistic and dangerous” (Maheshwari and Teoh, 2014).

Proper reserve assessment using AMH or AFC has the potential to improve type, dosage, and duration of ovarian stimulation to maximize the clinical goals of IVF treatment. It also

improves cost-effectiveness, considering that ovarian stimulation is the major cost of the IVF treatment (Maheshwari and Teoh, 2014). Recently, the literature has been defining and interpreting the cutoff and extreme levels of clinical AMH values: “more invasive or time- consuming methods of fertility preservation being appropriate for women with a low AMH”

(Anderson et al., 2012), or: “AMH measurement may be useful in the prediction of poor response and cycle cancellation and also of hyper-response and ovarian hyperstimulation syndrome” (La Marca et al., 2010). OHSS and multiple pregnancies are the two most common adverse effects of IVF and AMH has a potential to reduce both in its role of clinical marker at systemic and local levels.

AMH as an oocyte and embryo developmental potential marker

From Human Serum

AMH correlation to oocyte quantity is well established, and there is now evidence to suggest AMH levels could be a marker of oocyte quality. This has been investigated in both humans and bovines, and only a few human clinical studies have established a correlation.

Confounding variables in these studies could be the aging process which links decreasing quality of oocytes with lower AMH levels, or embryo numbers which could be an extrapolation of retrieved oocyte number (Fanchin, 2003). A study conducted on 141 patients, divided into three groups based on 25th and 75th percentile of day 3 serum AMH, showed that 50% of normal morphological oocytes were derived from the “normal” serum AMH patient group (1.66 and

4.52ng/ml), compared to 30% of normal morphological oocytes derived from the lower or higher serum AMH groups (Ebner, 2006). Silberstein et al., on the other hand, showed evidence that

serum AMH ≥2.7ng/ml measured on the hCG administration day could be correlated with embryo morphology and cleavage rate (Silberstein, 2005). EldarGeva et al. showed a correlation between serum AMH of 2.52ng/ml and ongoing pregnancy rates (Eldar-Geva, 2005). Further studies suggested that 0.69ng/ml could be a cut off between the ovum pick-up (OPU) procedure cancellation (Penarrubia et al., 2005), while 1.13ng/ml might be an indicator of poor ovarian reserve, with a specificity of 85% and a sensitivity of 80% (Tremellen et al., 2005). Another study by Nelson et al. showed the positive correlation between AMH values and live birth rate, as well as a correlation between AFC and AMH, when AFC values are between 15 and 25

(Nelson et al., 2007). Lakamge et al. defined 14pmol/l or 1.96ng/ml as the cut off for the cumulative pregnancy rates per cycle (Lakamge, 2007). Majumder et al. showed that serum

AMH and AFC predict oocyte and embryo potential, but both are better in predicting negative live birth outcome, with AMH being 84% specific (Majumder et al., 2010). LaMarca et al. showed that serum AMH (prior to gonadotropin stimulation) and age are predictors of live birth, with a sensitivity of 79.2% and a specificity of 44.2% (La Marca et al., 2011). AMH concentrations of below 0.4 and between 0.4 and 2.8ng/ml have a 44% and 86% live birth chance respectively. Even with the moderate ability to predict live birth, AMH was found superior to age, day 3 FSH, oestradiol, or inhibin B levels and similar to AFC (Hazout et al.,

2004). Brodin et al. provided evidence and set a foundation, supported by Sunkara et al., showing that AMH is positively correlated to both oocyte quantity and quality independent of age and number of oocytes retrieved (Brodin et al., 2013; Sunkara et al., 2011).

From Human Follicular Fluid

More recently, a few research groups have become interested in follicular AMH levels and have shown similar results as seen in serum. Fanchin et al. showed that ovarian preovulatory

FF AMH is correlated to serum AMH, and both are predictive of the implantation potential of embryos (Fanchin et al., 2007). In this study AMH concentration was adjusted to the total protein content of the FF, due to variability in the follicular size. FF AMH was stratified as low (up to

1ng/ml), average (1.1-2ng/ml) and high (above 2ng/ml). The prevoulatory FF AMH was approximately 2.5 times as concentrated compared to serum levels of AMH. This study used only one retrieved oocyte and one embryo per transfer. Another study successfully compared and correlated the pooled FF AMH to the maturation status of the oocyte (Cupisti et al., 2007).

Takahashi et al. explored the largest preovulatory FF and found a positive association to oocyte fertilization, showing that AMH was 3.42 times higher in the fertilized vs. non fertilized groups

(Takahashi et al., 2008). Wunder et al. showed evidence that pooled FF and serum AMH on the day of oocyte retrieval correlated to the pregnancy outcome (Wunder et al., 2008). There is a body of evidence showing the effect of other follicular components secreted by GCs that have an effect on oocyte competence (Mendoza et al., 2002), as well as research by Salmon et al. showing the effect of the oocyte on AMH expression in GC (Salmon et al., 2004b). These results clearly point to the fact that ovarian reserve, of which AMH is an obvious marker, is associated to the oocyte quality, independently of age and oocyte quantity.

AMH as a PCOS, DOR and cancer marker

By being representative of ovarian status, AMH has become a marker of ovarian pathologies such as PCOS, diminished ovarian reserve (DOR), and granulosa cell tumors. PCOS is caused by insensitivity of the follicular pool to signals that direct selection for dominance and inhibition of further recruitment and growth. The proportion of growing follicles is increased and the proportion of atretic follicles is decreased due to the lack of an ovulatory follicle that would otherwise act as inhibitory signal towards new recruitment. In addition, the number of androgen receptors in the follicle is increased resulting in constant initiation of growth. Imbalance in AMH, androgen receptors, FSHRc, estrogen, and progesterone causes the follicular cycle to be “frozen”, resulting in disruption of follicular maturation and ovulation, decreased oocyte quality, and infertility (Rice et al., 2006). AMH levels were found to be 3 times higher in PCOS patients than in controls and were significantly associated with AFC. Diagnostic predictability of AMH was found to be 0.851, with a threshold of 60pmol/l (8.4ng/ml), and with a specificity of 92% and a sensitivity of 67% (Pigny, 2005). AMH, AMHRc, FSHR, androgen receptors were all increased in PCOS patients (Catteau-Jonard et al., 2008). Stimulation response could not be predicted with

AMH in PCOS patients (Kim et al., 2013). Promising treatment lies in the use of suppressors or inhibitors of AMH to remove the block of the ovulatory signal, and allowing for a selection of a single ovulatory follicle. This principle extends to patients with DOR or poor responders to gonadotropin treatment, where AMH activity is insufficient, and where the addition of recombinant AMH could potentially have a therapeutic value (Campbell et al., 2012).

Levels of AMH in GC tumors were found to precede clinical detection by 16 months (La

Marca and Volpe, 2006). In experiments by Stephen et al., addition of 10g of recombinant AMH per day for 3 weeks caused inhibition of human cancer cell lines in vivo, under renal capsules

(Stephen et al., 2002). The AMH caused decreased neovascularization, necrosis, inflammation, and tumor size. The TGF-beta family has been shown to have an anti-proliferative response in different cell types. Inhibition of TGF-beta has been linked to enhanced tumorogenicity in vivo, and different types of mutations of TGF-beta have also been found in cancers (Morikawa et al.,

2016). Often a same protein can display suppressor properties in the initial stages of tumor growth, but switches to a pro-onco gene in the later stages (Tang et al., 2003). Anttonen et al. explored tumor growth using the ovarian granulosa-like cell line (KGN) developed by Nishi et al. and showed that AMH expression varies depending on the tumor size, while AMHR2 was unaffected. In addition, increasing levels of exogenous AMH in vivo and in vitro tumor cell number decreased by mean of apoptosis (Anttonen et al., 2011; Y. Nishi et al., 2000).

Cow as a model for human reproduction

The bovine model in studying human reproduction became popular with the realization that cattle have a very similar gestation length, endocrine hormone status and regulation, are monoovulatory, have a similar estrous cycle length, with 2-3 follicular waves, have individually repeatable AFC, and have similar pathologies such as PCOS and tumors. Because they are large animals, it is easier to assess the ovary in terms of ultrasound measurements and sampling, compared to rodents. Ovaries are readily available from slaughtered animals. AFC has been shown to impact fertility in cattle to the same extent as in human. Variation of AFC has been shown to differ 7 fold among animals, ranging from 8-56 follicles, but it is highly reproducible per animal (with an accuracy of 0.85-0.95), regardless of the breed, age, season, or management conditions. An AFC below 15 was correlated to an 80% smaller ovarian reserve, dramatically

different to cattle with an AFC above 25 (J. L. H. Ireland et al., 2008). In 12 month old heifers,

80% of their original oocyte reserve has been normally lost and the average conception rate after artificial insemination (AI) was found to decline from 56% at 15-16 months of age to 42% at 26-

27 months of age (Kuhn et al., 2006).

Dairy and beef cow fertility

The dairy and beef industries are of tremendous economic importance, and ART is immensely valuable tool to sustain production. Serious problems have been observed with decreasing fertility of up to 3-4% per decade (Spencer, 2013). To achieve a pregnancy rate of

40%, usually requires two AIs. The UK dairy industry defined its main problems in dairy and beef production as subfertility, mastitis, and lameness, with subfertility being the one with the highest economic impact and the most difficult to solve. The dairy industry is under constant selective pressure for high milk production (Royal et al., 2000). Several studies have been conducted on the effect of energy utilization towards increased milk production against body condition score (BCS) and the effect of prolactin on reproduction efficiency. It has been shown that fertility traits such as luteal activity postpartum are heritable, while calving interval and BCS heritability are under investigation (Leroy et al., 2008). Increasing milk yield has been shown to negatively impact the ART, as the oocyte number and embryo quality decreases. Up to 50% of modern dairy cows present abnormal estrous cycles postpartum, leading to prolonged calving to first insemination intervals (Opsomer et al., 2000), low conception rates, and high early embryonic mortality (Leroy et al., 2012). Luteal activity postpartum has been also shown to negatively correlate with milk yield, with estimates that lactation uses 75% of the cow’s

metabolic capacity. One of the ways to overcome this decreasing fertility issue is to utilize the

IVP or MOET method that includes in vivo fertilization (Mapletoft, 2005). It was found that IVP produces higher number of oocytes and embryos, 9.4 vs. 6.7, but that the pregnancy rates are lower, 33.5% vs. 41.5% respectively. After considering the efficiency of IVP over MOET, it was found that in a 15 day interval, IVP produced more pregnancies even with lower pregnancy rates

(Pontes et al., 2009).

Anti-Mullerian Hormone in cattle

The size of ovaries, ovarian reserve, and AFC have been shown to be highly similar in both humans and cattle, therefore AMH has also been a candidate parameter to identify cattle reproduction outcome and fertility (Erickson, 1966). AMH was defined as “an endocrine marker of gonadotropin responsive follicles” (Rico et al., 2009). Ireland et al. has shown, using the three largest follicles in low vs. high AFC groups of animals, that intrafollicular estradiol and mRNA for aromatase in GCs were greater and mRNA for AMH was lower respectively (J. J. Ireland et al., 2009). Serum AMH was found to be highly individually reproducible and variable between animals, corresponding to high variation of the number of oocytes in new born calves (10,000-

350,000) and 12 month old heifers (1,920- 40,960) (J. L. H. Ireland et al., 2008; Lo et al., 1998).

AMH half-life in the bovine is 2 days, with levels being static during the estrous cycle. It is believed that AMH has the ability to inhibit FSH dependent aromatase expression, resulting in an inverse AMH and estradiol17beta relationship, while AMH production is enhanced by BMP

(Novembri et al., 2015). AMH is regulated at the follicular, ovarian, and endocrine levels. At the follicular level it is regulated by the stage of follicle, at the ovarian level it is regulated by the

pool of small antral follicles, and at the endocrine level it is regulated by the effects of other endocrine hormones (Rico et al., 2011).

Bos taurus taurus vs. Bos taurus indicus

All domestic cattle belong to the family Bovidae, subfamily Bovinae. The subspecies studied here belong to two subspecies Bos taurus taurus (taurus) and Bos taurus indicus

(indicus). In Tibetan “Zen” or “Zeba” is the word for hump, which is one of the main physical features of indicus cattle. The common ancestor originated in Western Asia around 4500 BC.

Zebu cattle comprise more than half of the world’s cattle due to their multipurpose and hardy features. In the 1800’s, indicus was introduced to the American continent as Brangus, a cross between the Brahma and Angus breeds. Breeding is known to increase phenotypic superiority, or hybrid vigor, carrying better-adapted traits from both parents. However, the heritability of these traits is not linear and is easily influenced by environmental factors (Abeygunawardena and

Dematawewa, 2004). These different subspecies have adapted to diverse environmental conditions, which impacted overall reproduction physiology (Beatty et al., 2006; Driancourt,

2001). For example, Brahma (Bos taurus indicus) and Senepol (tropical Bos taurus taurus) have greater numbers of follicles in all size categories than Angus (temperate Bos taurus taurus)

(Alvarez et al., 2000). Bo et al. has described indicus as superior to taurus in terms of calving rates if both are kept in tropical or subtropical environments (Bó et al., 2003). Indicus has adapted to hot temperatures, humidity, parasites, and low quality forages. However, indicus reproduction is characterized by: 6-12 months delayed puberty until 60% of body weight is reached (compared to 30-55% in taurus); 2-4 follicular waves; lower LH secretion; estrous

length on average 20.9 days; smaller duration of estrous (10 hours, compared to 16.3 hours in taurus); decreased estrous intensity; smaller interval from estrous to ovulation; longer gestation length; extended post partum period of 17 months (compared to 12 months in taurus); higher number of AFC (41.5 vs. 21 in taurus); lower number of dominant follicles; smaller max diameter of dominant follicle (10-12mm vs. 16-20mm in taurus), smaller CL (24mm vs. 28mm in taurus); and lower twining rate (Sartori and Barros, 2011). Indicus cattle take 3 years to reach puberty and produce only a few liters of milk over a short lactation period, after which there is an extended postpartum anestrous. Variability to superovulation treatments and difficulty detecting estrous causes decreased efficiency in indicus ART. The dose for super ovulation drugs of indicus vs. taurus is usually reduced by 30% for gonadotropins, by 50% for progesterone, and by

40% for estradiol. The calving interval in the dry vs. wet season differs, from 19.9 months to

14.5 months. There is evidence that for every hour of daylight there is 0.5mm increase of the dominant follicle diameter, relating seasonal changes to fertility parameters. Baruselli et al. reported that follicular deviation of the ovulatory follicle is smaller in indicus breeds, and that estrous occurs more often during the night (Baruselli et al., 2006). Pontes et al. found that there is no difference in the number of primordial, primary, or secondary follicles in the ovaries of fetuses or heifers in both subspecies, therefore the initial number is not the reason for the difference in oocyte and embryo yield (Pontes et al., 2011). It is believed that the mechanism controlling the follicle development differs in each of the subspecies (Silva-Santos et al., 2011).

Therefore five main problems with ART in indicus were defined: 1) necessity to detect estrous;

2) necessity to start gonadotropin at the correct time; 3) necessity to perform AI at the correct time; 4) high variability of embryo production per donor; 5) high proportion of unresponsive donors. Pontes et al. examined a large number of animals belonging to three breeds, Gir,

Holstein, and Girolanda (Gir and Holstein in varying percentages of crossbreeding: ¼ Holstein and ¾ Gir and ½ Holstein Gir mix) (Pontes et al., 2010). It was found that pregnancy rates were

40%, 36%, 37%, and 37% respectively. However, there was a large variation in viable oocytes per retrieval 12.1, 8.0, 16.8 and 24.3, as well as in pregnancy per retrieval 1.2, 0.7, 1.3, 1.7 respectively.

Batista et al. examined AFC in Nelore and Holstein cattle at 3 different time points, 120 days, 60 days and 0 days before plasma AMH determination and found that at all time points

AFC correlated with AMH (Batista et al., 2014). Nelore heifers had overall higher AFC and

AMH compared to Holstein (Baldrighi et al., 2014; Batista et al., 2014). These authors defined serum AMH as a reliable phenotypic marker to predict relative number of follicles at any point of the cycle irrespective of genetic group. Guerreiro et al. also came to a similar conclusion, defining AMH as an accurate endocrine marker for the in vitro embryo yield but not for blastocyst yield (Guerreiro et al., 2014).

AMH as a fetal sex marker

AMH has been proposed as a potential sex-determining factor in early pregnancy, but current studies present contradictory findings. AMH is expressed at different sex specific time points during pregnancy (7 weeks for males and 20 weeks for females), but is an order of magnitude more concentrated in male fetal circulation. In male cord blood AMH levels are around 64 to 92ng/ml in the second trimester, while still undetectable in female fetus cord blood.

Lee and colleagues, in 1996, defined AMH as a “testis specific marker during infancy and early childhood” (Lee et al., 1996). A human clinical study by Empey et al. included over 100 women

carrying either male and female fetuses, and revealed a significant sex specific difference in maternal serum in the time period between 11 and 15 weeks of pregnancy, with the average male concentration being 2.0 ± 0.03ng/ml and the average female concentration being 0.94 ± 0.2ng/ml

(Empey et al., 2012). However, a study by LaMarca et al. showed an increase of maternal serum

AMH levels during second semester, but this increase was not found significant (La Marca,

2005). A study by Nelson et al. also examined serum AMH levels across trimesters, and found

AMH levels were significantly decreasing across trimesters (Nelson et al., 2010). Interestingly, pre-pregnancy and post-pregnancy serum AMH levels were found not to differ. Studies about the ability of AMH to cross the placenta have not yet been published. Studies on other proteins, such as alphafetoprotein (AFP), 70kDa in size, crossing from the fetal to the maternal circulation by passive transport through placental “leaks” have provided evidence of the ability of large proteins to cross the placenta (Malek et al., 1998). A recent study examined AMH and AMHR2 expression in the placenta and fetal membranes and found no difference in expression levels using qPCR in either the placenta or fetal membranes between male and female fetuses.

However the study did show significantly higher AMH antibody staining intensity of male fetal membranes vs. female fetal membranes (Novembri et al., 2015).

The effect of fetal AMH is illustrated in opposite fetal sex twins in the hermaphrodite condition in cattle called Free-Martin. First described in 1917, it was not until 1991 that AMH was proposed as a possible cause of Free-Martinism (Komisarek and Dorynek, 2002). This condition occurs in twin pregnancies with opposite sex fetuses that share circulation with vascular anastomoses, and results in a disturbed development of the female reproductive tract due to high male fetal AMH expression. It is the most common type of disorders of sex development in cattle and occurs in up to 90% of the female fetuses of surviving opposite sex

twin sets (Padula, 2005). These animals are described as having morphologically both female and male external genitalia, both Wolffian and Mullerian ducts, an enlarged clitoris, a shorter vagina length, an increased ano-vaginal distance, the presence of ovotestes, and the absence of a cervix (Hwang et al., 2001; Roberts and Greenwood, 1928). Newborn Free-Martin calf AMH levels were found to be similar to that of a new born male calf, >700ng/ml, compared to the normal female, <120ng/ml. However a decrease to female levels is observed in the Free-Martin calf after 2 weeks after birth, while in a normal male the decrease would occur over the first 5 months of life (Padula, 2005). Testosterone levels in the Free-Martin calf are similar to male levels, but other steroid hormones and gonadotropin levels are much lower, and they also have a heavier birth weight and higher marbling score. A similar condition was described in the sheep, deer, pig and horse by the same authors. It is interesting to observe that sheep and deer also belong to ruminant groups and share the same placenta type as cows, while the pig and horse placenta is of diffuse type. Another study looked at the effect of hormonal therapy on a Free-

Martin heifer, twin to a bull, and found that the heifer started lactating 9 days after the treatment and continued for one month, but the milk had low butterfat content. This animal was not able to conceive, but resumed a normal oestrual cycle after treatments with 20mg of diethylstilbestrol dipropionate (synthetic estrogen) over 22 days 8 injections (Barker, 1944). Both of these studies were unable to genotype the Free-Martin animals due to unavailable resources and knowledge at the time, therefore the sex was not determined with certainty. A more current case study in a human with a rare type of monochorionic dizygotic twinning with opposite sex twins described a healthy boy (XY) and girl (XX) born with no sign of hermaphroditism (Souter et al., 2003). In this study the placental barrier was not present and there was still no effect of male AMH on the female twin. Other human studies of similar pregnancies did see differences in length of

gestation, female behavior, and IQ (Derom et al., 2005; Luke et al., 2005). Other types of hermaphroditism have been discovered, however the etiologies of the condition are diverse. The most common condition is a true hemaphroditism due to chimerism or mix of male and female cells in the gonads during embryo development (Souter et al., 2006).

The newest data has shown that AMH expression is not only limited to the ovary and placenta but it is also expressed in the liver and brain (Novembri et al., 2015). Brain studies have shown differential expression between male and female mice and possible differential brain development and function leading to sex specific behavior (Wang et al., 2009; Wittmann and

McLennan, 2013).

Human vs. bovine placenta

In order to explore levels of fetal AMH in maternal circulation during pregnancy, the placenta has to be considered, as it is the main barrier between maternal and fetal circulation.

The placenta’s main function is to nurture the fetus and allow for selective transport of nutrients without compromising the mother’s survival. Simultaneously, fetal secretions, cells, proteins and

DNA are transported and diffused through the placenta to the maternal circulation (Lo et al.,

1998). The placenta produces AMH but with no difference in levels between the male and female fetus (Novembri et al., 2015).

Bovine placenta differs from the human placenta in morphology. It is epitheliochorial with cotyledonary morphology, while in the human it is hemochorial with discoid morphology

(Rawn and Cross, 2008). The epitheliochorial placenta is evolutionarily conserved among large species with increased gestation length, singleton pregnancies, and immature young, while the

hemochorial placenta is mostly found in smaller mammals, often with multiple offspring, among which the human is the largest example (Enders and Carter, 2004). Cotyledons, 100-140 in number, are the main sites of oxygen, nutrient, and CO2 exchange. In the discoid placenta, exchange is focused at the disk-specific area where the placenta attaches to the endometrium. In the epitheliochorial placenta, maternal and fetal vascular systems remain completely separated by intact epithelial cells with basal laminae and connective tissue on each side, causing minimal trauma to the uterus. In the hemochorial placenta, fetal chorionic epithelium is bathed in maternal blood, because chorionic villi erode through the maternal endothelium (Barreto et al.,

2011). This feature of the primate placenta, of being more invasive than in the ruminant placenta, possibly allows for a more facilitated nutrient transport and more rapid growth within a shorter gestation length. However, there is also an increased risk of microchimerism, immunological response, and excessive bleeding at parturition (Barreto et al., 2011; Enders and Carter, 2004;

Nelson et al., 2010).

The placenta is important not just as a barrier, but as an active “nutrient sensing” dynamic organ, allowing for constant adaptation to the continuously changing environment (Diaz et al.,

2014). For example, oxygen diffusion ability varies across species with different placenta thicknesses (6um in the cow compared to 1um in the pig and 3um in the horse) (Carter and

Enders, 2013; Kuijper et al., 2013). Another adaptation is the development of endocytosis, pinocytosis, and trinucleate cells to overcome the lack of direct maternal blood access. Interferon tau, placental lactogens, pregnancy associated glycoproteins, and growth hormones are a few of the many endocrine hormones produced by the ruminant placenta. AMH is a 140kDa glycoprotein dimer, quite a large protein, which needs to be transported across multiple cell membranes. Means of transport could potentially be either by a slow diffusion process of similar

size proteins (Malek et al., 1998) and/or by means of cytoplasmic vesicles such as exosomes

(Pereira et al., 2013; Rong et al., 2015; Sandvig and Llorente, 2012; Vargas et al., 2014).

Differing placenta structure and morphology could be the potential reason why the condition of

Free-Martinism does not occur in human dizygotic monochorionic twin pregnancies. High AMH levels could possibly move through the discoid placenta in human in a more localized fashion and not affect the second fetus of opposite sex to the extent that it happens in bovine cotyledonary placenta (Chen et al., 2013; Derom et al., 2005). In addition, it was interestingly observed that in humans, female fetuses have a slower rate of growth more in concert with the growth of the placenta, while male fetuses have a higher tendency to outgrow the capacity of the placenta to maintain their viability, described as “boys live dangerously in the womb” (Brett et al., 2014; Eriksson et al., 2009).

RATIONALE, HYPOTHESIS, AND OBJECTIVES

Rationale

There is an evident fall in human and bovine fertility in the last few decades. Assisted reproduction technologies (ART) and in-vitro production (IVP) have been employed to over come these raising issues. In order to provide safe and efficient ART and IVP there are many areas that are still in need of significant improvement. One main area in need of a better understanding is the endocrine and paracrine ovarian function behind creation, storage, selection and maturation of oocytes. These processes are all crucial in establishment of maximized oocyte yield and development potential. Anti-Mullerian hormone (AMH) has been established as a clinical marker of oocyte quantity and ovarian reserve however few studies presented evidence that these properties seem to be subspecies specific when measured systemically reflecting cattle fertility characteristics. There has also been some conflicting evidence on early pregnancy maternal circulation AMH in human as a possible be determinant of the fetal sex due to its differential expression between male and female fetus and its placenta. AMH has also been speculated to reflect oocyte quality measured from a single largest ovulatory follicle or pooled follicular fluid in human. We are interested to expand the evidence on AMH in different cattle subspecies by including local, granulosa cell and follicular fluid, AMH measurements and AMH results from their crossbreed. We are interested to see if the difference in AMH expression detected in early pregnant maternal and male/female fetal circulation; and placenta expression in order to use AMH as an early fetal sex-determining marker in cattle. Last but not least, we are interested to utilize human single follicular aspirates, monofollicular samples, and look at the correlation to oocyte developmental potential.

Hypothesis

The hypothesis of this study is as follows: AMH and AMHR2 gene expression and plasma and follicular fluid AMH protein level correlate with the oocyte quantity, developmental potential and fetal sex.

Objectives

To test this hypothesis, the following objectives were addressed:

Objective 1: Determine if AMH and granulosa cell AMHR2 mRNA content reflect Nelore (Bos taurus indicus) breed fertility in terms of oocyte and antral follicle number that differs compared to Angus and Holstein breeds (Bos taurus taurus).

Objective 2: Determine if plasma AMH, and placental and cotyledonary AMHR2 mRNA content, differ in pregnant cows carrying male vs. female fetuses.

Objective 3: Determine if monofollicular AMH protein and granulosa cell AMHR2 mRNA content correlates to oocyte developmental potential in human.

CHAPTER I

SYSTEMIC AND LOCAL ANTI-MULLERIAN HORMONE REFELCTS

DIFFERENCES IN THE REPORDUCTION POTENTIAL OF ZEBU AND EUROPEAN

CATTLE

* A portion of the material in this chapter has been published in Animal Reproduction Science (Stojsin-Carter et al., 2016)

INTRODUCTION

The genetic background of cattle significantly impacts their reproductive performance. It is believed that increased inbreeding to achieve maximal milk yield has negatively impacted reproductive efficiency in temperate, Bos taurus taurus (European type cattle) animals (Bachelot and Binart, 2007; Leroy et al., 2015). By comparison, the tropical and subtropical subspecies of cattle, Bos taurus indicus (Zebu), generally found in India and South America, are known for lower milk yields, but greater reproductive efficiency (Bó et al., 2003). In a direct in vitro production (IVP) comparison with European type cattle vs. Zebu cattle reported blastocyst rate was 25.6% and 32.1% respectively, which ultimately gave rise to two thirds more pregnancies

(Viana et al., 2010). However, Zebu were found to have lower breeding capacity due to delayed puberty, decreased estrous duration and intensity, longer gestation length and postpartum period, and lower twinning rate compared to European type cattle (Abeygunawardena and Dematawewa,

2004; Bó et al., 2003; Silva-Santos et al., 2011). Taken together, the greater embryo and pregnancy rate but lower breeding capacity make Zebu cattle an ideal candidate for in vitro embryo production (IVP). To date, there is an incomplete understanding of the underlying endocrine, molecular and physiological factors necessary to achieve optimal IVP protocols in

Zebu and European type cattle.

Anti-Mullerian hormone (AMH) is a 140kDa glycoprotein dimer member of the TGF- beta protein subfamily secreted by Sertoli cells in testes, and by granulosa cells (GC) in the ovary reviewed by (di Clemente et al., 2003). In females AMH is believed to inhibit premature follicular growth and maturation, making it the ovarian reserve “guardian” (Visser et al., 2006).

Its minimal intra and inter estrous variability makes it a useful predictor of ovarian reserve

(Fanchin, 2003; Ireland et al., 2007). The exact mechanism by which AMH acts in the ovary is

not certain, but it is believed to be through decreasing GC sensitivity to luteinizing hormone

(LH) and follicle stimulating hormone (FSH) (Visser and Themmen, 2005). Due to its link with ovarian reserve, AMH is used extensively as a quantitative marker of fertility in humans, and is also being increasingly examined as a potential biomarker of reproductive efficiency in other species, including cattle (Ireland et al., 2011; Monniaux et al., 2011; Rico et al., 2011). Various human studies have reported correlation of AMH concentration to a number of qualitative reproductive parameters, such as fertilization, implantation and pregnancy rates, however, this has not been previously shown in cattle (Fanchin et al., 2007; Majumder et al., 2010; Takahashi et al., 2008). In addition to several reports of AMH in European type cattle (Ireland et al., 2009;

Ireland et al., 2008) there are three published investigations involving Zebu cattle (Baldrighi et al., 2014; Batista et al., 2014; Guerreiro et al., 2014). These studies focused on comparing plasma AMH (Pl AMH) concentration between Zebu and European type cattle and correlating to the number of antral follicles (AFC) as a quantitative reproductive parameter. The findings of these studies provide evidence for plasma (Pl) AMH to AFC correlation with Zebu animals displaying greater AMH values for the same AFC compared to European type animals.

The aim of the current study was to investigate and compare the relationship between both systemic and local AMH and reproductive parameters: AFC, ovary diameter (OD), oocyte number, cleavage and blastocyst rate in both Zebu and European type cattle, as well as a small cohort of crossbred animals. It was hypothesized that irrespective of its source, AMH correlated to reproductive parameters with Zebu having greater AMH value compared to European type cattle.

MATERIAL AND METHODS

Animals and Experimental Design

Study group 1

Bos taurus indicus or Zebu (Nelore breed, n=30), Bos taurus taurus or European type cattle (Red Angus breed, n=10), and crossbred Bos taurus taurus × Bos taurus indicus (Brangus breed, n=10) cows of average reproductive age (mean ages 8.6, 7.8 and 7.1 years respectively) raised on pasture in Paraná state, Brazil were subjected to ovarian examination of AFC and OD with the 2-D trans-rectal Mindray adapted with a linear transductor ultrasound, and peripheral blood collection via puncture of the tail vein. Blood was collected in EDTA tubes (BD

Vacutaner®, BD Franklin Lakes NJ, USA) to allow for more consistent AMH ELISA measurement. The Bovine AMH ELISA kit AL-114 (Ansh Labs, Texas, USA) was used according to the manufacturer’s protocol with the exception of an overnight separation of plasma at room temperature following the MOFA® Minitube Canada protocol for AMH testing.

Samples were frozen at -20°C following collection until ELISA measurement was performed.

Study group 2

Post-mortem collection of ovaries from unsynchronized, non pregnant pasture raised

Zebu (Nelore breed, n=12) and European type cattle (Holstein breed, n=56) raised under standard dairy farming conditions, was performed in government-approved slaughterhouses in

Belem, Pará state, Brazil and Guelph, Ontario, Canada, respectively. For the Zebu cattle, each animal had a matching blood sample as well as a pair of ovaries. Blood was collected during exsanguination at the time of slaughter and was left overnight in EDTA tubes for separation of plasma from blood cells at room temperature. For European type cattle, AFC was determined by visual counting of the antral follicles per ovary. For both cattle subspecies, antral follicles, 5-

8mm in diameter, for each ovary were aspirated and pooled. After collection, pooled supernatant

FF was carefully removed without disturbing the cell pellet that has settled and frozen at -20°C until AMH ELISA measurement. The pooled pellet was re-suspended with HEPES-buffered

Ham's F-10 plus 2% steer serum (Cansera; Rexdale, ON, Canada). The cumulus-oocyte complexes (COC) were collected, counted and put into in vitro culture, while the rest of the cells were frozen for qPCR analysis.

For investigations into mRNA expression, the total number of oocytes per ovary or ovary pair was counted. Samples were grouped into “low” or “high” oocyte producing ovary if they contained less than 9 or more than 19 oocytes per ovary, respectively. These cut offs were determined by using 25th and 75th percentiles of the ovary that contained the highest number of oocytes in order to choose the samples with the potentially most obvious difference in AMH expression.

IVF

Bovine ovaries from the local abattoir were transported to the laboratory in a 0.9% saline solution at 33 to 37°C. IVP was preformed as described by Ashkar et al. for samples obtained in

Canada and by Costa et al. for samples obtained in Brazil with the exception that cumulus-oocyte complexes (COCs) were kept separate per each ovary (Ashkar et al., 2010; Costa et al., 2013). In brief, cumulus oocyte complexes (COCs) were aspirated from ovarian follicles for collection into

HEPES buffered Ham’s F-10 plus 2% steer serum (Cansera, Rexdale, ON, Canada). COCs were collected and in groups of 10 were matured in 80uL drops for in vitro maturation under mineral oil (Paisley Products, Toronto), for 22-24 hours at 38.5°C in 5% CO2. The in vtiro maturation

(IVM) drops consist of TCM199 medium + 2% FBS supplemented with 1µg/mL of E2,

0.5µg/mL of FSH and 1µg/mL of LH (NIH, Washington, DC, USA). Frozen-thawed Bos Taurus semen (EastGen, Guelph On) was used for in vitro fertilization. Semen was placed in 1.5mL of

HEPES Sperm TALP for 45 minutes at 38.5°C in 5% CO2 in order for swim up to occur. The swim up product (upper layer) was then centrifuged at 2000rpm for 7 minutes. Mature oocytes were washed twice in HEPES Sperm TALP, and twice in IVF TALP with 20µg/mL heparin, and transferred into 80µL IVF TALP droplets under mineral oil. Sperm was added to the oocytes and oocytes were incubated overnight with motile sperm at 38.5°C in 5% CO2. The next day presumptive zygotes were stripped using pipette-vortexing in a HEPES Sperm TALP wash.

Zygotes were then washed in HEPES Sperm TALP twice and then transferred to synthetic oviductal fluid (SOF) media supplemented with sodium pyruvate, non-essential and essential amino acids, gentamicin, 15% bovine serum albumin (BSA), and Cansera. They were then transferred to 30µL drops of SOF media under mineral oil and incubated at 38.5°C in 5% CO2. A maximum of 10 oocytes were matured, fertilized and cultured per medium drop. Number of oocytes was assessed at the time of collection, cleavage rate was assessed on Day 2, and blastocyst rate on Day 8.

ELISA

AMH was measured using the Bovine AMH enzyme linked immunosorbent assay

(ELISA) kit AL-114 (Ansh Labs, Texas, USA) according to the manufacturer’s protocol. Before measurement, FF was first diluted between 1:500 and 1:10,000 times using the supplied diluent and placed in EDTA tubes at 4°C overnight. AMH was measured using 50µL of Pl or diluted FF sample. The provided analytical range of the assay was 0.156 - 10ng/mL, and the analytical

sensitivity 0.011ng/mL. The intra-assay coefficients of variation were 2.92%, 2.54% and 3.65% for quality control plasma samples containing 0.611, 1.259 and 2.56ng/mL AMH, respectively.

RNA extraction and reverse transcription

RNA was extracted from the GC pellets using a TRIzol reagent (Invitrogen, Cincinnati,

OH, USA) according to the manufacturer’s instructions and previous publications (Favetta et al.,

2004; Scheetz et al., 2012). In brief, each pellet was homogenized in 0.5mL of TRIzol Reagent.

Phase separation was achieved by adding chloroform, and RNA was precipitated from the aqueous phase with isopropanol. Samples were incubated at -20°C overnight and centrifuged at

10,000g at 4°C. The RNA pellet was washed with 75% ethanol and dissolved in 20µL of sterile

RNase-free water. Contaminants were removed with DNase I treatment (Ambion, Huston, TX,

USA) and total RNA concentration was measured with a spectrophotometer. RNA samples were stored at -80°C until further use. Reverse transcription PCR was performed using the high- capacity complementary DNA (cDNA) reverse transcription kit (Applied Biosystems, Auckland,

New Zealand) following manufacturer’s protocol. Briefly, 500ng of oligo(dT) was first added to each RNA sample and incubated at 70°C for 2 minutes. A mixture of 4µL of RT buffer, 1µL of

0.1M dithiothreitol, 1µL of 10mM deoxyribonucleotide triphosphates (dNTPs) mix, 0.5µL of

RNasin (40U/µL; Promega, Madison, WI, USA), and 1µL of Superscript II (200U/µL;

Invitrogen) was then added and the reaction was incubated further at 42°C for 1 hour, followed by a final incubation at 70°C for 30 minutes. cDNA samples were stored at -20°C until further use.

Real Time quantitative PCR

Real-time quantitative PCR (RT-qPCR) was carried out to determine AMH and AMHR2 transcript levels using the BIO-RAD CFX96TM Real-Time PCR System and SsoFastTM

EvaGreen Supermix (Bio-Rad Laboratories, Hercules, CA, USA) according to a standard protocol that had been temperature optimized for the AMH, Glyceraldehyde-3-Phosphate

Dehydrogenase (GAPDH) and AMHR2 primers (Table 1). Prior to quantification, optimization procedures were performed by running qPCRs with and without the purified template to identify the melting temperatures of the primer dimers and specific product. Each reaction contained 5µL of SsoFastTM EvaGreen Supermix reaction mix, 1µL of a mix of the forward and reverse primers at a concentration of 5µmol, 2µL of the cDNA of interest and was adjusted to a total volume of 10µL using H2O. The standard curve was established using ovarian tissue cDNA template in five serial dilutions ranging from 1µg/µL to 0.03125µg/µL of cDNA. The amplification program was as follows: 95°C for 10 minutes, followed by 50 amplification cycles of 95°C for 10 seconds, 65°C for 10 seconds, 72°C for 10 seconds and acquisition of fluorescence for 10 seconds. After the end of the last cycle, a melting curve was generated by taking measurements every 0.5°C from 72°C to 95°C. GAPDH transcript was selected as the housekeeping gene, as it showed the most consistent levels of mRNA expression among the samples tested using geNorm software (Vandesompele et al., 2002). Other housekeeping genes tested were histone (H2A), tyrosine 3-monooxygenase/tryptophan 5-monooxygenase activation protein, zeta (YWHAZ), hypoxanthine guanine phosphoribosyl transferase 1 (HPRT1) and succinate dehydrogenase complex, subunit A (SDHA). Relative quantification of the transcripts of interest (Table 1) was calculated between two subspecies and between the low and high oocyte producing ovaries.

Table 1 Real Time PCR primers

Gene GenBank Sequence Reference Size (bp)

accession

number

AMH NM_173890.1 F-5’-CAGGGAAGAAGTCTTCAGCA-3’ (Ireland et 270

R-5’-AAGGTGGTCAAGTCACTCAG-3’ al., 2009;

Scheetz et

al., 2012)

GAPDH NM_001034034.2 F-5’-TTCCT GGTACGACAATGAATTTG-3’ (Hamilton 153

R-5’-GGAGATGGGG CAGGACTC-3’ et al.,

2011)

AMHR2 NM_001205328.1 F-5’-GTGCTTCTCCCAGGTCATAC-3’ (Monniau 163

R-5’-AATGTGGTCATGCTGTAGGC-3’ x et al.,

2011)

Statistics

For statistical investigation Student’s t-test was used to compare parameters between the subspecies, while Spearman correlation, and multivariable linear models were used to compare parameters within the subspecies with p<0.05 considered statistically significant. For example, referring to Figure 1 Part Ai which outlines the relationship between Plasma AMH and the AFC, the following linear model was considered: Pl AMH = Intercept + AFC + Breed. Here the Breed is a categorical variable. This allows us to model the Pl AMH for each breed, and compare the differences between them. To compare differences between breeds, we use a Tukey test that is an option within the general linear hypothesis test (glht) from the multcomp package in R (Team,

2009). The test allows us to estimate the differences in intercepts between the breeds, assuming

that the slope (related to the AFC) is constant for all breeds. This was done due to the available sample size. A similar modeling exercise was performed comparing Pl AMH to OD (Aii), and

FF AMH to oocyte # (Bii). Pl AMH numbers were calculated using GraphPad Prism (GraphPad

Software, San Diego, CA, USA).

RESULTS

Study group 1

Zebu and crossbred animals had significantly greater mean Pl AMH concentration than their European counterparts (p=0.010, p=0.018 respectively; Table 2). The Pl AMH mean concentration for Zebu, European type cattle and crossbred cattle were 0.77±0.09, 0.33±0.24 and

0.63±0.07ng/ml respectively (Table 2). The correlation between Pl AMH and AFC was significantly different when comparing either Zebu or crossbred to European type cattle

(p=0.004 and p=0.049 respectively; Figure 1Ai); the same result was observed for Pl AMH and

OD between Zebu and European type cattle (p=0.009; Figure 1Aii). The correlation between Pl

AMH and AFC in Zebu was significantly positive (p=0.002; Figure 1Ai). The European type cattle had significantly lower AFC compared to Zebu and crossbreed (p=0.006, p=0.027 respectively; Table 2) and larger OD (p=0.008; Table 2) compared to Zebu animals.

Study group 2

In a subset of Zebu animals, matched plasma samples and ovary samples were available and it was possible to observe a significant and positive correlation between Pl AMH and number of oocytes per ovary pair (p=0.002; Figure 1Bi), with the Pl AMH mean value and the mean oocyte number of 1.15±0.27ng/ml and 11.58±1.83, respectively.

Mean FF AMH concentration was found to be significantly greater in Zebu compared to

European type cattle (p<0.0001; Table 2). The FF AMH mean for Zebu and European type cattle was 4934.3±568.5ng/ml and 2977.9±214.1ng/ml respectively (Table 2). The correlation between

FF AMH and oocyte number per ovary was significantly different between Zebu and European type cattle (p<0.0001; Figure 1Bii), and only European type showed significantly positive

correlation (p=0.005; Figure 1Bii). A positive correlation was not observed between FF AMH and cleavage rate, however the mean cleavage rate of 70.92±4.55 for European and 76.77±5.99 for Zebu cattle (Table 2). A positive correlation was not observed between FF AMH and blastocyst rate, however the mean blastocyst rate of 18.94±2.96 for European and 25.05±6.34 for

Zebu cattle (Table 2). In a subset of European type animals where ovaries were collected post mortem, it was also possible to compare FF AMH concentration to AFC, and a significant positive correlation was observed (p=0.009; Figure 1Biii).

The expression of AMH GC mRNA was not found to be significantly different between either low or high oocyte producing ovary groups, or between European type and Zebu cattle

(Figure 2A). The expression of AMHR2 mRNA was found to be significantly different between low and high group for European type cattle (p=0.035; Figure 2B) and positively correlated to oocyte number in this subspecies (p=0.01).

Table 2 Summary of antral follicle count (AFC), ovary diameter (OD), plasma anti-Mullerian hormone (Pl AMH) from Study group 1, and follicular fluid AMH (FF AMH), oocyte, cleavage and blastocyst rate mean values (± SE) from Study group 2 for European type (E), Zebu (Z) and crossbred (C) cattle and the p-values from their average value comparisons. Significant difference (p<0.05) is indicated by the symbol (*). Study group 1 Study group 2

Pl AMH FF AMH Oocyte Cleavage Blastocyst AFC OD (mm) (ng/mL) (ng/mL) #/ovary rate/ovary rate/ovary 17.14 66.20 0.33 2977.9 17.5 70.92 18.94 European ± 1.82 ± 3.50 ± 0.24 ± 214.1 ± 1.60 ± 4.55 ± 2.96 (E) (n=7) (n=7) (n=8) (n=56) (n=56) (n=32) (n=32) 27.37 57.66 0.77 4934.3 11.58 76.77 25.05 Zebu ± 1.83 ± 1.17 ± 0.09 ± 568.5 ± 1.83 ± 5.99 ± 6.34 (Z) (n=30) (n=30) (n=30) (n=24) (n=24) (n=24) (n=24) 25.83 59.03 0.63 Crossbred ± 10.55 ± 3.45 ± 0.07 (C) (n=6) (n=6) (n=10) P-values E vs. Z *0.006 *0.008 *0.010 *<0.0001 0.064 E vs. C *0.027 0.138 *0.018 Z vs. C 0.782 0.581 0.532

DISSCUSION

The aim of the current study was to investigate and compare the relationship between both systemic and local AMH and reproductive parameters: antral follicle count, ovary diameter, oocyte number, cleavage and blastocyst rate in both Zebu and European type cattle, as well as a small cohort of crossbred animals. Preliminary research published by Batista et al. and Baldrighi et al. examined and revealed for the first time that plasma AMH and AFC relationship is greater in Zebu compared to European type cattle (Baldrighi et al., 2014; Batista et al., 2014). The current report expands their preliminary research by providing evidence that AMH, from both sources Pl and FF, is significantly different between Zebu and European type cattle for all examined parameters with Zebu displaying greater AMH values. Plasma and FF AMH was found correlated with two of the reproductive parameters examined, AFC and oocyte number.

Additionally for the first time in European type cattle GC AMHR2 RNA expression was examined and found positively correlated to oocyte number. The sequencing of the AMHR2 cDNA product was performed and confirmed 100% homology to the bovine AMHR2 (GenBank accession number NM_001205328.1). Plasma AMH concentration was also measured in crossbred cattle and found to more closely mirror their maternal Zebu concentration.

The European type cattle FF AMH concentration displayed a significant positive correlation to the quantitative reproductive markers: AFC and number of oocytes. A positive trend yet non-significant was also observed when comparing Pl AMH to AFC. Our results for

AMH in European type cattle are in general agreement with the current literature, however none of the published work to our knowledge directly compared AMH from both Pl and FF between two subspecies of cattle. In the current study, FF AMH in bovine subspecies was not found to have a significant correlation with cleavage nor blastocyst rate, which is in agreement with

previous bovine studies correlating reproductive parameters to oocyte quality (Guerreiro et al.,

2014; Ireland et al., 2007). Nevertheless in human studies, AMH from both FF and serum has been found to correlate to qualitative oocyte markers such as fertilization and implantation rates

(Fanchin et al., 2007; Majumder et al., 2010; Takahashi et al., 2008). The study by Kawamura et al. speculated that AFC as a quantitative marker has a direct effect on the ovarian structure and morphology and therefore should have an effect on the quality of oocytes within the ovary.

Further study looking at the oocyte quality parameters would be required to determine if the absence of the relationship between the quantitative and qualitative markers is the result of inherent species differences or factors related to in vitro culture conditions.

Granulosa expression measurements were performed in the low and high oocyte yielding ovaries where the difference in the protein and transcript amounts would be expected to be the greatest. GC AMH RNA expression measurements from low and high oocyte yielding ovaries did not appear to differ in the current study. Previously it has been demonstrated that even a

1mm size change in follicle is associated with an exponential expression difference in AMH level due to its crucial role in follicle growth and maturation (Rico et al., 2011). This would lead to variability of the AMH GC expression data within both high and low yielding groups, and possibly result in the absence of the expected difference. It could be speculated that other determinants beside follicle size also need to be measured and considered during comparison.

Significant positive correlation was observed between GC AMHR2 RNA levels and number of oocytes, as well as significant difference in levels between the low and high oocyte producing ovaries. The measured levels of AMHR2 transcript reported here are in accordance with previously published results in goat GCs (Monniaux et al., 2011).

Zebu cattle are known for their greater in vitro embryo and pregnancy rate but lower breeding capacity. Beyond their different IVP rates and estrous cycle characteristics, the underlying physiological and endocrine basis for their different reproductive potential is not clear.

In this study, Zebu Pl AMH concentration was significantly positively correlated with reproductive parameters: AFC and average number of oocytes per pair of ovaries, as well as FF

AMH and number of oocytes, which indicates that AMH irrespective of being systemic or local can be used as a quantitative reproductive marker. Overall this is in general agreement with the current AMH model and patterns reported in previous human, European type cattle and Zebu experiments by Baldraghi et al. and Batista et al. (Baldrighi et al., 2014; Batista et al., 2014;

Stojsin- Carter et al., 2016). Importantly, although Zebu and European type cattle appear to follow the same patterns of positive correlation, the AMH values and correlated parameters were significantly different in every case, with Zebu expressing significantly greater AMH concentrations compared to European type cattle at matched parameter values. This result demonstrates the importance of species and subspecies when interpreting AMH data.

The crossbred cattle included in this study appeared to be intermediate between the two subspecies, but more comparable to their Zebu counterparts. The crossbred cows were created using semen from European bulls to inseminate the Zebu cows despite being considered a 3/8

Zebu, 5/8 European type cattle cross on a genetic level. This also underscores the importance of considering the genetic background of animals when conducting and interpreting bovine AMH studies.

CHAPTER II

PREGNANCY ANTI-MULLERIAN HORMONE AS A FETAL SEX-DETERMINING

FACTOR

INTRODUCTION

In the bovine industry, the ability to influence and determine fetal sex enhances management of herd breeding, allows for faster genetic progress, has implications in sex-linked diseases, and improves conservation of superior and endangered animals. Preconception sex selection by means of sperm sex sorting, or pre-implantation genetic diagnosis (PGD) coupled with IVF, has been employed since late 1980’s (Andrabi and Maxwell, 2007; Bodo et al., 2001;

Choudhary et al., 2016). Even before 2005, over 30,000 cattle offspring had been produced using sexed spermatozoa, obtained mostly by flow cytometric sperm sorting (Armstrong et al., 2015; L.

A. Johnson et al., 2005). PGD has been shown to be highly accurate and efficient in sex selection even in field conditions, however, a major problem for PGD remains its dependence on the use of IVF (Lopes et al., 2001; Majumder et al., 2010; Nelson et al., 2007; Penarrubia et al., 2005;

Silberstein, 2005; Takahashi et al., 2008; Tremellen et al., 2005; Wunder et al., 2008).

At present, ultrasound starting from 8th week of pregnancy is the most widespread prenatal sex determination method in bovine industry, as it’s readily available and non-invasive

(Stroud, 2005). However most accurate results are achieved after 10th week of gestation (Ali and

Fahmy, 2008; Stroud, 2005). The downside of this diagnostic method is the lack of consistency due to variability in both technician skills and in the position of the fetus.

Although usually investigated as a marker for fertility and ovarian reserve, and as an infancy marker for testicular function, AMH has recently gained attention as a potential early pregnancy sex-determining marker due to its few hundred-fold concentration difference in expression by male vs. female fetuses. The increased rate of AMH expression by males starts from as early as the 7th week of gestation, which could theoretically place it as one of the earliest

measurable molecular markers for determining bovine fetal sex (Vigier et al., 1984). Despite this potential, only a few studies to date have investigated human maternal levels of AMH during gestation, without reference to fetal sex (La Marca, 2005; Nelson et al., 2010) or with reference to fetal sex (Empey et al., 2012). All of these studies showed a decline of maternal AMH levels during pregnancy, presumably due to inactivated follicle growth (Kuijper et al., 2013). The single study that considered the impact of fetal sex on maternal AMH did reveal a significant higher Pl AMH levels in mothers carrying a female vs. male fetus (Empey et al., 2012). An additional recent article by Novembri et al. investigated the placenta of fetuses of both sexes as a potential source of AMH at birth (Novembri et al., 2015). The authors reported that AMH expression was not different between the sexes, however the staining intensity of the AMH antibody appeared higher in the placenta of male pregnancies. These initial studies show the potential impact of pregnancy on maternal AMH biology, the possibility of AMH representing an actual marker of fetal sex and the need to consider the potential role of the placenta in the current and future studies.

The aim of this chapter is to investigate the association between the levels of plasma

AMH in cows carrying female and cows carrying male fetuses at four different time points, gestation day 0, 35, 135 and 275, for each animal. Also, plasma AMH was measured in single time points in cows carrying female and cows carrying male fetuses in the period between 85 and

155 days of gestation. Lastly, expression of AMHR2 was measured in the placenta and cotyledon of male and female fetus pregnancies between 38 and 80 days of gestation to determine if there is a placental derived sex linked difference. It was hypothesized that levels of plasma AMH between cows carrying a male vs. cows carrying a female fetus would differ, being higher in the cows carrying a male fetus, with neither the placenta or cotyledon having an additive effect.

METHODS

Animals and Experimental Design

Study group 1

B. taurus indicus or Zebu (n=13) cows of average reproductive age raised on the pasture in São Paulo state, Brazil were subjected to artificial insemination (AI) and peripheral blood collection via puncture of the tail vein at day 0 (AI), 35, 135 and 275 of gestation (Figure 3). Out of 13 animals, 4 animals aborted, 1 animal sample got damaged, and in 8 animals (n=8) pregnancy resulted in a birth of a healthy singleton calf with all samples successfully retrieved.

Fetal sex determination was assessed using 2-D trans-rectal Mindray adapted with a liner transductor ultrasound during the 2nd trimester and then was confirmed at birth. Out of 8 animals,

3 carried a female and 5 carried a male fetus. All blood sampling was done by the same person and blood was collected in EDTA tubes (BD Vacutaner®, BD Franklin Lakes NJ, USA). Plasma was centrifuged at 1.400rpm and the top layer was aspirated to a new 1.5ml tube and frozen at -

80°C. Samples were shipped on dry ice to the Pará state, Brazil for the ELISA measurements.

The Bovine AMH ELISA kit AL-114 (Ansh Labs, Texas, USA) was used according to the manufacturer’s protocol.

Study group 2

Post-mortem blood collection of singleton pregnant pasture raised B. taurus indicus or

Zebu cows (n=21) carrying 10 male and 11 female fetuses, was performed in a Para State

Surveillance Agency approved slaughterhouse located in Castanhal, Brazil (Figure 3). The cows’ ages were variable, however they were estimated to be between 6 and 10 years old. Cow’s blood was collected during exsanguination at the time of slaughter in EDTA tubes. Matching fetal

blood was collected in EDTA tubes via heart puncture with a 23-gauge butterfly infusion set attached to a 5mL syringe and 10ml syringe. Fetal crown to rump length was from 15 to 43 cm, estimated to represent a 2nd trimester, more specifically 85-155 days old (~3-5 month) fetus.

Fetal sex was determined visually based on the presence or absence of a scrotum and annogenital distance. Plasma samples were centrifuged at 3000rpm and the top layer was aspirated to a new 1.5ml tube and frozen at -20°C until the AMH ELISA measurements.

Study group 3

Post-mortem reproductive tracts of singleton pregnant B. taurus taurus of average reproductive age were collected from the government-approved slaughterhouses in Guelph,

Ontario Canada (Figure 3). Reproductive tracts were transported on ice and sampling was performed at the University of Guelph. Samples from 13 fetuses, 13 cotyledon and 13 non- cotyledon from each placenta were obtained and snap frozen in liquid nitrogen. Fetus age was determined based on the crown to rump length representing 1st trimester, specifically 3-4.5 months of pregnancy, 38 to 73 days for 7 male (2.2-12.5cm) and 56-80 days for 6 female (5.3-

14.5cm). Anogenital distance was used for sex determination. In order to confirm the sex of the fetus, DNA extraction and quantitative PCR using GAPDH and testes-specific protein Y encoded (TSPY) primers from Table 3 was performed from the epithelial fetus tissue samples.

Placenta samples were used to measure quantity of AMHR2 RNA expression via quantitative

PCR described in Chapter 1, using GAPDH and Peptidylprolyl Isomerase A (PPIA) as housekeeping genes, Table 3.

Table 3 Real Time PCR primers

Gene GenBank Sequence Reference Size

accession (bp)

number

GAPDH NM_001034034.2 F-5’-TTCCTGGTACGACAATGAATTTG-3’ (Hamilton et al., 153

R-5’-GGAGATGGGGCAGGACTC-3’ 2011)

TSPY NM_001244608.1 F-5’- CCCAGAATCGAACAGGATTG-3’ (Hamilton et al., 215

R-5’- TTGTCTCTCACGGACGAACC-3’ 2009)

AMHR2 NM_001205328.1 F-5’-GTGCTTCTCCCAGGTCATAC-3’ (Monniaux et 163

R-5’-AATGTGGTCATGCTGTAGGC-3’ al., 2011)

PPIA NM_178320.2 F-5’- TCTTGTCCATGGCAAATGCTG -3’ (Ferris et al., 111

R-5’- TTTCACCTTGCCAAAGTACCAC -3’ 2016)

DNA extraction and sex confirmation using TSPY

Each epithelial tissue sample was taken out of the liquid nitrogen and homogenized using a pestle. Homogenized tissue samples were immediately transferred to a tube containing 4ml of digestion buffer and vortexed to dissolve any clumps. Homogenized tissues were incubated in a water bath at 50°C for 5 hours. Samples were vortexed every hour for 10 seconds. After incubation, DNA was extracted using a phenol/savage solution (2ml sample: 1ml phenol: 1ml savage) and precipitated using ammonium acetate (4M) and isopropanol. The strands of DNA were scooped out of the solution with a sterile glass hook, washed with 70% alcohol, air dried for 30 sec to 1 min. The DNA obtained from each sample was resuspended in 100ul of nuclease free water and kept in the refrigerator overnight. After extraction was completed, DNA obtained from each tissue was quantified using a NanoDrop spectrophotometer. The TSPY primers (Table

3) amplified a 215bp product from genomic DNA. A 10ul reaction contained 5mM primers, 6ng of genomic DNA and 1X SsoFast EvaGreen Supermix (Bio-Rad) was carried out in a CFX96

Touch™ Real Time–PCR Detection System (Bio-Rad) with denaturation at 98°C for 2 minutes, followed by 50 cycles of 98°C for 5 seconds, 60°C for 5 seconds and 95°C for 10 seconds.

Melting curve was obtained starting at 72°C with measurements taken every 0.2°C until 95°C.

All biological replicates were run in triplicates. Since TSPY was used for male or female confirmation and not quantitative measurements, standard curve was not necessary. Male were identified as TSPY positive while female were TSPY negative samples.

RNA extraction and reverse transcription

RNA extraction was performed as described in Chapter 1 except the reverse transcription that was performed using qScriptTM cDNA SuperMix (Quanta Biosciences, Canada) according to the manufacturer’s instructions.

Real time quantitative PCR

Real time quantitative PCR was performed as described in Chapter 1 using primers from

Table 3. The amplification program was as follows: 95°C for 10 minutes, followed by 50 amplification cycles of 95°C for 10 seconds, 60°C for 10 second (and not 65°C as in Chapter 1),

72°C for 10 seconds and acquisition of fluorescence for 10 seconds. Standard curves for GAPDH and PPIA primers were generated using pooled male and female fetal placenta cotyledon and non-cotyledon cDNA samples in six serial dilutions ranging from 12.5 to 0.781ng/ul, while standard curve for the AMHR2 primers were generated using bovine adult testes cDNA sample in six serial dilutions ranging from 50 to 3.125ng/ul. Calibrator sample used to avoid inter plate variation was bovine adult testes.

ELISA

Procedure for AMH measurement using the ELISA kit are described in Chapter 1 and apply to Study group 1 and 2 from this chapter. Novel for the AMH ELISA kit in this Chapter is use of provided controls, Low and High, specific for each plate and AMH units were pg/ml and not ng/ml. Specific to Study group 1 and this Chapter is that all the samples from each animal were all sampled on the same ELISA plate and were done in triplicates. A few of the samples

were run more than once across all the plates and shown to be within allowed levels of variation.

Male fetal samples were diluted 100 times.

Statistics

Wilcoxon rank sum test was used to check statistical significance in the patterns of male vs. female AMH levels throughout pregnancy. Wilcoxon test and Spearman correlation test was performed to test difference and correlation between serum AMH levels of male fetus to cow and female fetus to cow during 2nd trimester of pregnancy, as well as AMHR RNA expression between female and male cotyledon and placenta samples during 1st trimester.

RESULTS

Study group 1

Based on the raw data was presented in Appendix I, the difference between day 35 and

135 in Pl AMH was found significant between cows Bos taurus indicus carrying a male, n=5, and a female fetus, n=3 (p=0.036; Figure 4A). The average change in the level of Pl AMH between these two time points for cows carrying a male fetus was 255.4±178.5pg/ml, while for cows carrying a female fetus was -181.3±146.1pg/ml. The difference between day 275 and 135 in Pl AMH were found not significant between cows carrying a male or a female fetus (p=0.786;

Figure 4A). The average change in the level of Pl AMH between these two time points for cows carrying a male fetus was 87.6±161.2pg/ml, while for cows carrying a female fetus was

59.5±54.3pg/ml.

The relative difference between day 35 and 135 in terms of the level at day 35 in Pl AMH was found not significant between cows carrying a male or female fetus (p=0.571; Figure 4B).

The average relative change in the level of Pl AMH between these two time points for cows carrying a male fetus was 0.432±0.260, while for cows carrying a female fetus was 0.160±0.067.

The relative difference between day 275 and 135 in terms of the level at day 135 in Pl AMH was found not significant between cows carrying a male or female fetus (p=0.549; Figure 4B). The average relative change in the level of Pl AMH between these two time points for cows carrying a male fetus was 0.294±0.062, while for cows carrying a female fetus was 0.220±0.190.

Study group 2

Pregnant cow Pl AMH for the period of 85 to 155 days of gestation in cows carrying a male or female fetus was not found significantly different (p=0.557; Figure 5A). The average Pl

AMH for the same period for a cow carrying a male fetus was 947.3±146.6pg/ml, and for a cow carrying a female fetus was 809.4±180.5pg/ml. The average fetus Pl AMH for males (n=10) was

175,309.9±16,903.7pg/ml and for females (n=11) was 154.1±22.3pg/ml. There was a significant difference between the levels of male and female fetuses Pl AMH (p<0.05); male fetus and cow pregnant with the male fetus (p<0.05); and female fetus and cow pregnant with the female fetus

(p<0.05) Figure 5A. The correlation between Bos taurus indicus pregnant cow Pl AMH and fetus size was not found significant for male fetus carrying cows (n=10; ρ=-0.16; p=0.650; Figure 5B) nor for female fetus carrying cows (n=11; ρ=-0.21; p=0.523; Figure 5B).

Study group 3

The correlation between days in utero and relative AMHR2 RNA expression from the cotyledon of Bos taurus taurus was not found significant in cows carrying a male (n= 6, ρ=-0.09, p=0.870; Figure 6A) or a female fetus (n=7, ρ=0.66, p=0.102; Figure 6A). Cotyledon and placenta samples were evaluated based on the fetal sex male vs. female and AMHR2 RNA expression and found not to be significantly different for the cotyledon (p=0.553; Figure 6B) and for the placenta (n=3 vs. n=4 respectively, p=0.660; Figure 6B). When comparing within each sex, cotyledon vs. placenta, results were found also not to be significant for the male samples

(p=0.381; Figure 6B), and for the female samples (p=0.927; Figure 6B). The average male cotyledon relative AMHR2 RNA expression was 0.015±0.004, and female was 0.017±0.001.

The average male placenta relative AMHR2 RNA expression was 0.050±0.030, and female was

0.081±0.060.

DISCUSSION

The aim of the current objective was to investigate the levels of Pl AMH in cows carrying female vs. cows carrying male fetuses at four different time points for each animal: gestation day

0, 35, 135 and 275. Additionally, Pl AMH levels were measured at time of slaughter in a separate cohort of cows and their respective female or male fetuses in the period between 85 and

155 days of gestation. Lastly, expression of AMHR2 was measured in the placenta and cotyledon of male and female pregnancies between 38 and 80 days of gestation to investigate possible sex differences in its expression. It was hypothesized that levels of Pl AMH between cows carrying a male fetus vs. cows carrying a female fetus would differ, being higher in the cows carrying a male fetus, and that the placenta and cotyledon would express AMHR2 at a comparable level in pregnancies of both sexes.

Here, for the first time in a bovine study, we present evidence that cows carrying a male fetus have significantly higher difference in Pl AMH levels than cows carrying a female fetus.

This observation is in general agreement with the previous humans studies (Empey et al., 2012;

La Marca, 2005). Beginning with Ebner et al. who characterized the range of non-pregnant systemic AMH level in humans associated with the optimal fertility (Ebner, 2006), Empey et al. observed women carrying a female fetus show a drop in systemic AMH levels and that those carrying a male fetus showed levels that were closer to those of the non-pregnant state. In the current study, we present evidence that in cows carrying a female fetus Pl AMH dropped by approximately 20% compared to the non-pregnant Pl AMH value, while in cows carrying a male fetus it increased by about 30%. The overall difference of approximately 50% is comparable to the findings in humans, which showed a doubling of Pl AMH levels of mothers carrying a fetus of the opposite sex (Empey et al., 2012). The range, defined by Empey et al., where the influence

of fetal sex can be observed on the maternal systemic AMH levels was between 11th and 15th week of gestation, which falls within the range identified by our current results. Although it did not consider fetal sex, the previous human study by LaMarca at al. presented evidence of increased levels of systemic AMH in the 2nd trimester, which can be seen to parallel our current findings in cattle (La Marca, 2005). The close overall agreement between the current bovine study and previous human results demonstrates the strong reproductive similarity between these two species.

Importantly, the observation of significant fetal sex influence on maternal difference in Pl

AMH levels in the current study provides additional evidence that it represents a potential marker for fetal sex during early pregnancy. As discussed in the Introduction, accurate detection of the fetus sex in the first trimester of pregnancy could facilitate planning for herd management and breeding programs. Interestingly, AMH receptors were shown not only expressed in the ovary, but also brain, lung and adrenal tissue (Imhoff et al., 2013). This opens the possibility that fetal sex could potentially influence broader aspects of maternal physiology or even mental state via AMH signaling pathways. Looking at previous reports, when they are carrying fetuses of the opposite sex, mothers with chronic health conditions have been shown to respond differently to medical treatment, implying that fetal sex does in some way have an impact on the mother

(Firoozi et al., 2009; Hocher et al., 2009; Walsh et al., 2015). Recognizing the small sample size of the current study, the future experiments with larger animal numbers and additional sampling times should be completed to confirm these results and further assess the utility, accuracy and feasibility of maternal AMH levels as a fetal sex marker.

While the current study found a significant difference in Pl AMH levels between cows carrying a female or male fetus when multiple measurements were made and considered for each

individual cow, a separate cohort consisting of animals that were sampled at only a single time point did not show a significant difference for the same variable. This can be explained by the large individual variation in baseline AMH levels shown in Chapter I and the fact that the single time point sampling, used for the second cohort, did not allow this variation to be normalized for or considered during analysis (Anderson et al., 2012; J. J. Ireland et al., 2011). Larger animal numbers are believed to reveal a significant difference even with the single time point measurements. However, in the current study, technical limitations did not allow for either the collection of multiple measurements or the inclusion of additional animals in the second cohort.

In addition to maternal Pl AMH, the current study also directly sampled fetuses to determine fetal Pl AMH levels. To our knowledge, this represents the first report of fetal Pl

AMH levels in cattle. The fetal samples were taken at between day 85 and 155 of gestation and the observed AMH levels were found to be significantly different compared to those of the carrying cow. Further, male fetal Pl AMH was found to be approximately 1000x higher than female fetal levels, and approximately 100x higher than in the Pl AMH levels of the carrying cows. Although novel as fetal measurements, the relationships and levels observed in each fetal sex agree with interpolations of published calf Pl AMH levels (Kitahara et al., 2012b; 2012a;

Rota et al., 2002). The current results also fit within previous literature describing a rise in male bovine and human fetal AMH expression at around 7 and 8 weeks of pregnancy respectively, and the suspected onset of female human fetal ovarian AMH expression at approximately 140 days of gestation (Matzuk and Lamb, 2002; Teixeira et al., 2001; Vigier et al., 1984).

Considering the above results and previous reports in combination, specifically the observations that cows carrying a female pregnancy show decreased Pl AMH compared to a non- pregnant state, and that male fetal Pl AMH levels were significantly higher than both female fetal

and maternal levels, suggests that fetal sex is a significant determinant of maternal AMH levels.

On this basis, we propose a working model of maternal and fetal AMH biology during pregnancy

(Figure 7). In this model, maternal ovarian AMH production decreases during pregnancy and this decrease is either compensated for, or not compensated for, by AMH produced by a male or female fetus respectively. The following three assumptions were made within this model and are considered further below: 1) maternal AMH production decreases during pregnancy; 2) the placenta, as the other major feature additional to the fetus during pregnancy, is neither a significant contributor to AMH levels nor complete barrier to fetal-maternal AMH transmission;

3) fetal AMH production falls within the necessary ranges to explain the observed maternal Pl

AMH values.

Both the current experiments and previous studies in humans also show decrease in maternal Pl AMH during pregnancy, which suggests AMH production by the maternal ovaries is affected by the pregnant state (La Marca, 2005; Nelson et al., 2010). Considering the physiology of pregnancy and our understanding of ovarian AMH biogenesis, this is not surprising. During pregnancy, high progesterone and human chorionic gonadotropin (hCG) values act to inhibit gonadotropins expressed by the pituitary, which in turn inhibits stimulation of the ovary and follicular development and cycling. This difference in the ovary between the pregnant compared to the non-pregnant state in the human and bovine species can be directly observed, with the pregnant-state ovary showing smaller follicular number and size, and premature follicular atresia

(Guilbault et al., 1986; 2012a; Pierson and Ginther, 1986; Westergaard, 1985). As AMH production in the ovary is directly tied to follicular development and ovarian cycling, the quieting of the ovary during pregnancy can be strongly linked to a decline in maternal AMH production (Kuijper et al., 2013).

The role of the placenta in AMH biology has not been extensively explored. A previous human study by Novembri et al. examined placenta and fetal membranes at birth and detected expression of both AMH and AMHR2 that did not differ between opposite sex fetuses

(Novembri et al., 2015). The current study is in agreement with their findings in terms of

AMHR2 expression, however, using the same technique we were unable to detect AMH expression in bovine cotyledon and placenta samples between gestation day 38 and 80 (data not shown). From these two studies, it can be proposed that placental differences between the species of each study, as well as time of sampling could be all possible reasons why AMH expression in the bovine placenta and cotyledon was not detected. Therefore, until additional studies are conducted, the possibility remains that placental AMH production may be contributing to maternal AMH levels; however, the results of this current study support the alternative hypothesis that the placenta expresses AMHR2, but not AMH itself. Although the observations of the current study are unlikely to represent subspecies differences, it is important to note that Pl

AMH levels in the current study were all measured in Bos taurus indicus, while the placenta and cotyledon samples were obtained from Bos taurus taurus.

In order to speculate about the increases in maternal Pl AMH due to fetal AMH production, one has to explore the ability of fetal AMH to cross the placenta and enter the maternal circulation. Larger charged molecules, such as peptide hormones like AMH, can move across the bovine placenta by means of active transport by either specialized receptor molecules within microvesicles (receptor mediated endocytosis) (Pereira et al., 2013; Sandvig and Llorente,

2012), or by pinocytosis of syncytiotrophoblast cells (Palmeira et al., 2012), or by passive transport at a very slow rate (Malek et al., 1998). Although the ability of AMH to cross the placenta by these methods has not been directly investigated, previous reports on molecules with

similar characteristics, such as IgG and alpha fetal protein (AFP) in human, and enhanced Green

Fluorescent Protein (eGFP) in cattle support the possibility (Brownbill et al., 1995; Duc-Goiran et al., 2006; Malek et al., 1998; Pereira et al., 2013; Sandvig and Llorente, 2012).

Lastly, assuming fetal AMH can cross through the placenta, the remaining question is whether this difference would be detectable in the mother, due to its dilution in the larger blood volume of the mother compared to the fetus. It was determined previously that the first trimester fetal blood volume in cattle is around 10 000 times lower (~4ml) than the mother (~40 000ml)

(Reynolds, 1953). We have presented evidence that in cattle, the male fetal plasma AMH is up to

500x more concentrated than in the maternal plasma. Considering these values, the overall rise of maternal AMH levels following dilution of male fetal AMH levels in the maternal blood volume could be expected to fall between 0.05 to 0.5ng/ml. In our study, we found the rise to be approximately 0.2ng/ml, which is in line with this rough prediction. Further, maternal Pl AMH in non-pregnant cows is on average only 0.33ng/ml, meaning this increase represents a significant proportion of their baseline values (Stojsin- Carter et al., 2016).

In summary, the current study provides evidence of fetal-sex linked differences in maternal AMH levels and proposes a model where they are driven by a decreases in maternal

AMH production coupled with sex-dependent fetal AMH production. The importance of these findings lies in their demonstration of the need to consider the potential impact of pregnancy and fetal sex in future studies of AMH, the potential to use maternal Pl AMH levels as a marker of fetal sex during early pregnancy and their contribution to our broader knowledge of AMH biology and ovarian function during pregnancy.

CHAPTER III

HUMAN MONOFOLLICULAR ANTI-MULLERIAN HORMONE IN RELATION TO

OOCYTE DEVELOPMENT

INTRODUCTION

Genomics, transcriptomics, proteomics and metabolomics based methods have all been employed in an attempt to determine what factors have the most influence on oocyte developmental potential. However, most of their currently proposed implementations failed to show sufficient non-invasiveness, consistency, reliability and cost effectiveness in order to be widely accepted and used. The gold standard in most of human and bovine IVF is still the morphokinetics approach. This is the morphological examination of the gamete and embryo, coupled with the monitoring of the speed of embryo development. If performed visually by individuals, it is found to be subjective and inconsistent (Bols et al., 2012). Standardizing the evaluation of embryos using morphokinetics has been employed using time-lapse microscopy

(TLM), which captures images of the developing embryo within the incubator and uses an algorithm to determine its viability. However, recently the Cochrane Database of Systematic

Reviews examined 3 randomized control trials, including 994 women and their IVF success rate based on use of time-lapse microscopy, and found that there is no difference in the rates of clinical pregnancy, live birth, miscarriage, and still birth, with or without the use of TLM

(Armstrong et al., 2015; Kaser and Racowsky, 2014). In summary, despite advances into new areas and the further development of existing methods, there is still a clear need for novel markers to help determine oocyte developmental potential and guide decision making during assisted reproduction.

In the scope of ovarian and follicular physiology, AMH has been proposed to have multiple important functions. In a clinical setting, the most commonly considered role of AMH is its function as the “guardian” of the ovarian reserve. In brief, AMH is expressed from the granulosa cells (GC) of preantral follicles and is recognized as being crucial for controlling

follicle recruitment towards growth and ovulation, as well as preventing premature ovarian depletion. As a result, AMH levels are now commonly measured to give potential insight into current and future ovarian status or fertility. Although less commonly considered in comparison, the expression of AMH by developing follicles and the critical role it plays in follicular recruitment and development suggests AMH levels may be reflective, and therefore also a prospective biomarker, of follicle health and oocyte developmental potential. To date, this concept of AMH as an oocyte quality biomarker has been mostly explored in human fertility clinics by examining AMH levels in serum or in single or pooled ovulatory follicular fluid, and comparing it to overall or specific oocyte and embryo development, pregnancy, and live birth rates (Cupisti et al., 2007; Ebner, 2006; Eldar-Geva, 2005; Hazout et al., 2004; La Marca et al.,

2011; Lakamge, 2007; Majumder et al., 2010; Nelson et al., 2007; Penarrubia et al., 2005;

Silberstein, 2005; Takahashi et al., 2008; Tremellen et al., 2005; Wunder et al., 2008). Evidence of a broader link or dual relationship between AMH at the levels of both individual fertility, represented by oocyte quantity, and individual oocyte quality can also be seen in studies by

Sunkara et al. and Brodin et al.; after controlling for both age and oocyte yield in 892 patients undergoing 1230 ART cycles, they observed that aspects of oocyte quantity and quality are codependent, due to their positive correlation to serum (SE) AMH as a common parameter

(Brodin et al., 2013; Sunkara et al., 2011). As the authors explained, “If age and oocyte yield would be the same, a patient with a high AMH level would have a greater likelihood of having a euploid oocyte retrieved than would a woman with a low AMH level”.

Despite its promise, so far the use of AMH as a marker of oocyte developmental potential has had mixed success. Looking at the designs of the past studies, they can generally be considered to be incomplete because they usually do not sufficiently consider the large variation

in AMH levels between separate follicles or the need to directly link primary and outcome measurements between each follicle and its oocyte. Although the specific compromises they make, like pooled follicular fluid, simplify and therefore facilitate study completion, their associated loss in study detail is likely hiding important links between AMH levels and oocyte potential and contributing to the inconclusive or negative study results. For example, extreme

AMH values in the fluid of only a few follicles may be averaged out in a pooled follicular fluid sample, and therefore would not be linked to an associated outcome in the matched oocyte during analysis. In short, without individually measuring each follicle and individually tracking each oocyte to allow pairing during analysis, it quickly becomes difficult or impossible to link specific characteristics, such as AMH level, between a given follicle and its oocyte.

Only one study to our knowledge has focused on examining each follicle individually, using monofollicular sampling (mono FF) and linking the observed status of the follicle to the outcomes of its oocyte (Hamel et al., 2008). This study considered ovulatory stage follicles in humans and tested the oocytes by a microarray assay. Although this study did not consider AMH directly, its results did suggest ties between AMH and individual oocyte quality. One of the factors differentially expressed between follicles that produced an oocyte that lead to pregnancy vs. one that did not was aromatase, which has been linked to AMH (Hamel et al., 2008). Also in this study, follicles selected for dominance were shown to be those that enter the luteinization process first, by having more LH receptors (Hamel et al., 2008). Durlinger et al., Themmen et al., and Scheetz et al. presented evidence of opposing concentrations between LH receptors and

AMH, so it could be speculated that a decrease in AMH might be associated with follicular dominance (Durlinger et al., 2001; Scheetz et al., 2012; Themmen, 2005).

Given this background, the aim of the current study was to evaluate SE and mono FF

AMH levels, as well as mono FF AMH receptor 2 (AMHR2) RNA expression at the ovulatory follicular stage, and to compare the ability of each corresponding oocyte to reach metaphase II

(MII) stage, the zygote to reach 2 pronucleus (2PN) stage, and embryo to reach blastocyst stage, in patients of similar age and non-AMH related causes of infertility. It was hypothesized that both SE, pooled average mono FF AMH, and pooled average mono FF AMHR2 RNA expression would positively correlate to the AFC, oocyte number, and overall blastocyst rates. At the mono FF level, it was also hypothesized both AMH level and AMHR2 receptor expression would positively correlate with the oocyte’s and embryo’s ability to reach MII, 2PN, and blastocyst stage respectively.

METHODS

Patients and Experimental Design

Patients (n=6) from age of 27 to 36 admitted to ONE Fertility, Burlington for infertility treatment by means of IVF. Causes of infertility were same sex couples, male factor, and increased BMI. All patients from which the samples were collected signed a Participation in

Research consent form outlining the purpose of the study, procedures necessary to obtain samples, potential risks and discomforts, potential benefits to participants and/or society, payment for participation, confidentiality, participation and withdrawal, and rights of research participants. The consent form (Appendix II) was approved by the University of Guelph

Research Ethics Board (REB) under number 13SE007. The title of the project was: “Molecular

Markers of Oocyte Health and Quality”. 16 patients signed the consent form, but patients number ended up being 6 due to the following research based exclusion criteria: 1) negative for all of the regular patient screening procedures; 2) screened for serum AMH; 3) not having any of the following: PCOS, ovarian insufficiency/low reserve, testicular sperm retrieval (TESA) (partner), a history of ovarian cancer. Logistics exclusion based criteria included: 1) at least 2 embryologists working; 2) use of the single lumen needle for aspiration; 3) not scheduled on the weekend; 4) not be scheduled with more than 2 other IVF cases; 5) flushing, if necessary, performed in a separate tube; 6) all the staff involved informed about modifications of the procedure.

Monofollicular Sample Collection and IVF

There was significant organization necessary to perform sample collection in order to minimize time of the IVF procedure. One day before the collection, IVF lab staff had to prepare media following “Monofollicular sample collection instructions” (Appendix III) in order to perform the collection of the oocytes in a single follicle fashion, being able to trace each oocyte to the follicle data, and without dilution of the follicular fluid with the flush media. “Protocol for the monofolliclular oocyte collection” (Appendix IV) was used to help the staff go through the preparation in a stepwise process. “Modified Cycle Sheet” (Appendix V) was used to record coded details on the number of follicles, volume, number of oocytes, and details about each sample and patient. IVF procedure, unless specified by the consent form, was performed in the same fashion as established by the Ontario Network of Experts (ONE) Fertility protocols for the

IVF procedure. Simplified modifications allowing for collection of the research material included: the gynecologist would have to aspirate each follicle separately instead of continuously going from one to the other. That would allow the embryologist to obtain a single follicle aspirate, search for the oocyte, and place the oocyte in the specifically prepared in vitro culture system. Therefore, the next modification was that the culture system allowed only a single oocyte, instead of multiple oocytes, to be placed per drop of culture media, in order to be able to trace which oocyte belonged to each follicle. The next modification was that one of the researchers would be present to obtain the monofollicular (mono FF) aspirate and place it in the -

20°C until all of the follicles were collected. After collection, aspirates would be spun in the centrifuge, on 1.400rpm, volume would be recorded, and top layer, at least 100ul, of follicular fluid would be removed and placed in the separate tube and frozen at -20°C for the AMH ELISA measurements. Pallets were resuspended in 10% PBS and frozen in liquid N2 until transportation

to the University of Guelph. Blastocyst rate per patient was determined based on the total number of blastocysts at day 5 divided by the total number of oocytes collected.

ELISA

AMH was measured in ONE Fertility, Burlington, using Automated Roche AMH assay on the cobas e electrochemiluminescence immunoassay platform for AMH, using Beckman

Coulter Gen II assay antibodies (Roche Diagnostics International Ltd, Rotkreuz, Switzerland) according to the manufacture’s instructions. 50ul of serum samples from each follicle were measured undiluted, in replicates of two. Each plate was checked against provided controls. The provided analytical range of the assay was 0.01-23ng/ml, with an analytical sensitivity of

0.01ng/ml. Repeatability and intermediate precision calculated on 14 serum samples ranged from

1.0 to 2.2% and 1.5 to 2.8% respectively.

Cell culture

Human Granulosa-Like Tumor Cell Line (KGN) were obtained from Queen’s University and used as a positive control. It has been shown that AMH and AMHR2 are both expressed in

KGN cells (Anttonen et al., 2011). The cells were cultured in Dulbecco’s Modified Eagle

Medium (DMEM)/F12, 10% fetal bovine serum (FBS) with a doubling time ~46 hours (Y. Nishi et al., 2000). They were frozen in FBS containing 10% DMSO at passage 4 and 5 and shipped to the University of Guelph where they were thawed and cultured until passage 8, followed by

RNA extraction as described in Chapter 1.

RNA extraction and reverse transcription

The same protocol was followed as described in Chapter 1 for KGN RNA extraction, while mono FF cell pellets RNA extraction was done using AllPrepTM DNA/RNA Micro Kit

(QIAGEN, Inc., Burlington, ON) following the manufacture’s protocol. Reverse transcription for both was performed using qScriptTM cDNA SuperMix (Quanta Biosciences, Canada) according to the manufacturer’s instructions.

Real Time quantitative PCR

The same protocol was followed as described in Chapter 1, except for the use of primers from Table 4. All RNA samples were normalized against GAPDH and PPIA. The amplification program was as follows: 95°C for 10 minutes, followed by 50 amplification cycles of 95°C for

10 seconds, 60°C for 10 seconds (and not 65°C as in Chapter 1), 72°C for 10 seconds, and acquisition of fluorescence for 10 seconds. Standard curves for all primers were generated using pooled pellet cDNA samples from a unrelated patient with a signed consent form in six serial dilutions ranging from 12.5 to 0.781ng/ul, The calibrator sample used to avoid inter plate variation was KGN cDNA.

Table 4 Real Time PCR primers

Gene GenBank Sequence Reference Size

accession (bp)

number hAMH NM_000479.3 F-5’- CGCCTGGTGGTCCTACAC-3’ (Anttonen et al., 60

R-5’-AAGGTGGTCAAGTCACTCAG-3’ 2011; Catteau-

Jonard et al.,

2008) hGAPDH NM_001256799.2 F-5’- GAAGGTGAAGGTCGGAGTC -3’ (Le et al., 2008; 226

R-5’- GAAGATGGTGATGGGATTTC-3’ Yoshimura et al.,

2003)

PPIA NM_178320.2 F-5’- TCTTGTCCATGGCAAATGCTG -3’ (Ferris et al., 111

R-5’- TTTCACCTTGCCAAAGTACCAC - 2016)

3’ hAMHR2 NM_001164690.1 F-5’-TGTGTTTCTCCCAGGTAATCCG-3’ (Anttonen et al., 164

R-5’-AATGTGGTCGTGCTGTAGGC-3’ 2011; Catteau-

Jonard et al.,

2008)

RESULTS

AMH per patient:

Average FF AMH per patient was positively correlated to SE AMH levels (n=6; ρ=0.94, p=0.017; Figure 8Ai). There was also a positive trend between SE AMH and relative AMHR2

RNA expression (ρ=0.60, p=0.242; Figure 8Aii), oocyte number (ρ=0.35, p=0.492) and AFC

(ρ=0.09, p=0.870; Figure 8Aiii). Average SE AMH, FF AMH, and relative AMHR2 RNA expression were all negatively correlated with the rate of blastocyst development (ρ=-0.90, p=0.015; Figure 8Bi; ρ=-0.84, p=0.036 Figure 8Bii and, ρ=-0.84, p=0.036; Figure 8Biii respectively) for individual patients. In all six patients transfer of embryos resulted in clinical pregnancy.

AMH per individual follicles:

Individually collected and grouped for all patients FF AMH was not found different between M2 oocytes and non M2 oocytes (n=41 vs. n=28, p=0.350), 2PN zygotes and non 2PN zygotes (n=30 vs. n=11, p=0.940) and blastocyst and non blastocyst group (n=17 vs. n=13, p=0.563). The average FF AMH for M2 was 34.08±6.66pmol/l vs. non M2 was

35.77±9.99pmol/l. The average FF AMH for 2PN was 36.13±8.29pmol/l vs. non 2PN was

28.50±10.67pmol/l. The average FF for blastocyst was 30.49±11.10pmol/l vs. non blastocyst was 27.87±7.64pmol/l. When the data was divided based on SE AMH level into two groups,

“normal” group being 1.93 to 2.62ng/ml and “high” group being 4.21 to 6.79ng/ml, each with n=3, SE AMH level and FF AMH level were found significantly lower in the first group vs. the second group (p=0.048, p=0.038, respectively). The blastocyst rate was found significantly higher in the first group vs. the second group (p=0.038) Figure 9. Average relative GC AMHR2

RNA expression and oocyte number were not found significantly different between the groups

(p=0.700, p=0.369) respectively. The average value of the SE AMH was 16.83±1.52pmol/l for the “normal” group 38.4±5.39pmol/l and for “high” group. The average value for the FF AMH was 10.89±2.62 pmol/l for the “normal” group, and 64.80±11.68pmol/l for the “high” group. The average relative GC AMHR2 RNA expression for the “normal” group was 0.18±0.04 and for the

“high” group was 0.20±0.03. The oocyte number for the “normal” group was 8.67±0.88 and for the “high” group was 11.34±1.86. The average blastocyst rate was 0.39±0.05 for the “normal” group, and 0.25±0.07 for the “high” group. If data between blastocyst and non blastocyst producing FF AMH (pmol/l) (n=6), FF AMH/SE AMH (n=6) and relative AMHR2 RNA expression (n=4) was examined per patient in “high” (i) and “normal” (ii) SE AMH groups, in

“high” patients follicles with higher values produced blastocyst while in “normal” patients follicles with lower values produced blastocyst, Figure 10.

Figure 9 Comparisons between individual follicles serum (SE) AMH (pmol/l), average follicular fluid (FF) AMH (pmol/l), relative GC AMHR2 RNA expression, oocyte number and blastocyst (blast) rate between patients (n=3; blue) with “normal” 1.93-2.62 ng/ml and patients (n=3; red) with “high” between 4.21-6.79 ng/ml (x 7.14 to be converted to pmol/l). Significant difference was observed between “normal” and “high” groups for SE AMH, FF AMH and blast rate (p=0.048, p=0.038, and p=0.038, respectively). Glyceraldehyde 3-phosphate dehydrogenase and Peptidylprolyl isomerase A were used as housekeeping genes to determine relative expression level. Error bars denote the standard error of the mean (SEM) and significant difference (P<0.05) is indicated by the symbol (*).

DISCUSSION

The aim of the current study was to investigate and compare potential relationships between both systemic, and mono FF AMH protein level, as well as mono FF GC AMHR2 RNA expression and the following human reproductive parameters: antral follicle count, oocyte number, oocyte maturity, zygote and blastocyst rate. The broader goal was to assess the utility of

AMH as a marker of oocyte developmental potential in assisted reproduction. To date, only one preliminary study published by Hamel et al., used a similar mono FF sampling and analysis method. Although it did not consider AMH levels, it used a microarray approach, and was successful in identifying a number of differentially expressed factors in relation to pregnancy outcome, some of which are known to be part of AMH regulatory function (Hamel et al., 2008).

The current study provides evidence in support of a significant positive correlation between SE AMH and average mono FF AMH, and a positive trend between SE AMH and average mono FF GC AMHR2 RNA expression when examined on a per patient basis. This finding is in agreement with previous studies showing a correlation between average FF and SE

AMH (Fanchin et al., 2007), including our own previous bovine study, which showed average

FF AMH and GC AMHR2 RNA expression to have a significantly positively correlation to SE

AMH (Stojsin- Carter et al., 2016). A positive correlation was not observed between AMH and

AFC or AMH and oocyte number, however this may also be due to the low patient numbers available for the current study.

Examined on a per patient bases, we found a significant negative correlation between SE

AMH, average FF AMH, average relative GC AMHR2 RNA expression and blastocyst rate. This finding is contrary to the three previous reports reporting a positive correlation between AMH and embryo developmental potential (Fanchin et al., 2007; Majumder et al., 2010; Takahashi et

al., 2008). However, looking closer, all of these previous studies only measured and considered the AMH level of single largest ovulatory follicle and did not examine all subsequent follicles per patient. In contrast, the negative correlation observed in the current study includes these additional values in the analysis and therefore reaches a separate conclusion. In general, the interpretation of studies relying on single largest follicle values are problematic due to the strong impact between absolute follicle size and AMH levels, and the fact that the characteristic of largest follicle is not standardized across all patients, but rather may vary significantly from one patient to the next. Additionally, there is evidence the largest or dominant follicle is unique compared to the other follicles with respect to multiple factors related to development, such as

AMH (Scheetz et al., 2012). Considering this trend, where a developing follicle becomes depleted in factors involved in dormancy, a negative relationship between localized or follicle specific AMH and blastocyst rate becomes justified.

In order to further explore the observed negative relationship between AMH and embryo developmental outcome, patients were divided into two groups based on their SE AMH levels.

These levels were drawn from previous literature that defined the normal human SE AMH range as being 1.66-4.52ng/ml which is the 25th to 75th percentile of the population (Ebner, 2006).

Additionally, we considered reports describing levels of 2.52 and 2.7 to be correlated with a positive developmental outcome, and that 1.96ng/ml represents a lower limit associated with negative developmental outcomes (Eldar-Geva, 2005; La Marca et al., 2011; Lakamge, 2007;

Silberstein, 2005). In this context, the SE AMH level of or two patient groups were 1.93-

2.62ng/ml for the first group, which we considered to fall into the normal AMH range, and 4.21-

6.79ng/ml for the second group, which we considered to represent a higher than normal AMH range. In addition to the statistically significant difference in both SE and average FF AMH

levels, the blastocyst rate was also significantly different with higher levels in the “normal” group compared to the “high” group. These finding provides evidence, to our knowledge for the first time, of a potential association between negative blastocyst outcomes in patients with higher

AMH levels, excluding those linked to an identified and specific ovarian pathology such PCOS

(Pigny, 2005). While the specific definition of the “high” SE AMH range used in this analysis has not been explicitly defined previously in the literature, it falls above 75% of the normal range

(>4.52ng/ml) and bellow the values associated with ovarian dysfunction or defined pathologies

(<8.40ng/ml) (Pigny, 2005). Based on our observations, the possibility of a threshold beyond which increasing levels of systemic and follicular AMH are no longer associated with a good

IVF prognosis should be considered, even in the absence of an identified ovarian pathology. A potential mechanism associates increased levels of AMH to decreased oocyte quality and poor reproductive outcomes due to the lack of follicular selection and maturation. This is a novel concept and requires further verification.

Looking further using the greater detail provided by the use of a mono FF approach, reveals an additional relationship. Oocytes showing increased developmental potential in “high”

SE AMH patients were associated with higher AMH and GC AMHR2 RNA expression, while the opposite relationship was observed in the “normal” SE AMH group with oocytes showing increased developmental potential were associated with lower AMH and GC AMHR2 RNA expression (Figure 11). If it is assumed local AMH levels need to drop to a critical point to allow for the follicle to be recruited and matured properly allowing for increased stereogenic synthesis and gonadotropin receptor expression as seen in normal SE AMH patient on the local level (Visser, 2003), it is unclear how can this opposing trend be explained in the high SE AMH patients. It might be speculated that alterations in the local AMH level in the high SE AMH

group remaining high at the ovulatory level could be a reason why the overall blastocyst rate in the high SE AMH patients is lower compared to the normal SE AMH patients. However, understanding how few of these follicles still progress and mature producing a blastocyst is unclear, the current result clearly demonstrates the utility and importance of using paired mono

FF and serum measurements when investigating follicular level AMH biology.

In summary, the findings of the current study provide strong evidence that AMH biology is not as simple as one measurement or interpretation. Specifically, this study identified two groups of individuals on the basis of different SE AMH levels that had apparently contrasting physiology and observed further differences and alternative trends within these groups when considering AMH measurements of individual follicles and oocytes. These observations suggest potential relationships between AMH values and reproductive outcomes and parameters should be investigated at the organism, ovary and individual follicle level. As a general recommendation, systemic AMH should be considered to provide an overall indication of ovarian function and context for the interpretation of local AMH values, while the local AMH levels should be considered reflective of their specific follicular environment and the associated oocyte.

Additionally, although it may be possible to find associations between the AMH level of the largest follicle and outcomes within a given study or a defined clinical setting extrapolation of these findings is not recommended. Instead, there should be more investigations exploring the follicular AMH effects and outcomes such as the current experiment method, but including larger number of patients, where individual follicles and their oocytes are measured and can be compared directly to rule out potential confounding variables, such as absolute follicle size.

Further research and implementation of these concepts has the potential to increase the utility

AMH in a clinical setting by allowing it to not only serve as an established marker of general fertility, but also a novel potential marker for in vitro embryo selection.

GENERAL DISCUSSION

The main objective of this thesis was to examine the correlation between systemic and ovarian AMH levels and various parameters of fertility in the bovine and human species, as well as a possible association between the cow’s systemic AMH levels and fetal sex during pregnancy.

AMH was proposed to be a marker of ovarian function in both non-pregnant bovine and human, as well as in a pregnant bovine model.

Rising levels of infertility have a large impact on the bovine industry and human reproduction. However, our understanding of ovarian function and biology, which should be thorough in order to overcome this issue, is still vastly lacking. AMH has been used as a marker of quantitative ovarian parameters such as AFC and oocyte number in humans and European cattle. In the Zebu cattle breeds, which occupies a majority of the tropical and subtropical areas of the planet, and therefore also has great economic importance, AMH has not been extensively studied. The ability to identify fetal sex in early pregnancy based on the differentially expressed fetal sex factors and/or their effects on the mother and her ovary is unknown. Only three human studies have looked at AMH during pregnancy, and only one of those has studied higher levels of AMH in mothers carrying a male vs. female fetus. The link between AMH and quantitative fertility parameters has been established in both species, but only a few human IVF studies and no bovine ones have made the link between AMH and qualitative fertility parameters, such as successful fertilization and pregnancy rate. In this thesis, it was hypothesized that 1) Zebu cattle would have higher systemic and ovarian AMH levels compared to European cattle, and in both breeds AMH levels would be correlated to fertility parameters; that 2) cows carrying a male fetus would have higher Pl AMH compared to cows carrying a female fetus; and that, 3) in women

undergoing IVF, systemic and ovarian AMH would positively correlate with the oocyte developmental potential outcome.

Species or breed adaptation to various environmental conditions arises though the combination of genetic differences and evolutionary or breeding pressures. Here we provide evidence that two cattle breeds with differing reproductive abilities also have underlying physiological difference in terms of levels of AMH in serum, and follicular fluid. These observations possibly represent specific adaptations to their environments, as Zebu and European cattle have been bred for generations to adapt to a more tropical/subtropical vs. a more temperate climate respectively. Zebu has adapted to using its energy primarily to overcome heat, humidity, disease, and scarce nutrient availability. In comparison, European cattle have been grown in optimal surroundings, without heat and nutrient stressors, but with added stress caused by artificially induced human inbreeding methods for increasing milk and meat yield (Leroy et al.,

2008). These differing environments and pressures may also have resulted in the characteristics of their reproduction to also differ. In Zebu, reproduction is more “inaccessible”, characterized by delayed puberty, shorter and more “quiet” estrous, longer gestation, and lengthier postpartum anestrous, but higher ovarian reserve and AMH. European cattle exhibit more “accessible” reproduction, characterized by shorter puberty, easier estrous detection and monitoring, shorter gestation and postpartum anestrous, but lower ovarian reserve and AMH (Butler, 2003;

Koufariotis et al., 2014; O'Brien et al., 2014). Findings from our experiments have came to the similar conclusion where Zebu has been found to have superior fertility parameters, such as AFC and oocyte number, that correlated to their systemic and follicular AMH compared to the

European cattle (Stojsin- Carter et al., 2016). Interestingly, Silva-Santos et al. has shown similar fetal ovarian reserves between the two breeds in terms of primordial follicles, with higher rates

of follicular depletion in European cows, which leads to lower reserve in the adult females compared to Zebu (Silva-Santos et al., 2011). It could be speculated that the slower rate of follicular depletion and higher AMH levels in Zebu are a consequence of seasonal pressure on ovarian function. In a broader context, the associated fertility, milk production and genetic characteristics of European versus Zebu cattle can also be interpreted as a potential cautionary example of a failure to consider the links and potential trade-offs between traits during long-term and high pressure animal selection and breeding. Specifically, an overly strong selective focus on milk production has been implicated as a major source of the growing infertility problems observed in European cattle. Recognizing the Zebu breed is currently less inbred and does not yet appear to suffer from infertility traits, Zebu breeders and husbandry programs may wish to try to avoid a similar limitation and take a more holistic or multi-trait approach during animal selection. If this action is taken now before the species is further bred out and genetic variability lost it may preserve the genetics necessary to achieve a more optimal balance between fertility and production outcomes.

Besides exploring ovarian state of non-pregnant cows and how it relates to their systemic and follicular AMH levels, this thesis also explored plasma AMH of pregnant cows and how it relates to their fetal sex and their fetal plasma AMH levels (Chapter 2). Building on what has already been discussed, additional details related to male fetal AMH expression, maternal ovary status and potential AMH production, AMH crossing the placental barrier and the potential effects of increased AMH levels in developing fetuses on the maternal organism were also considered. The male fetal Pl AMH, not previously published to our knowledge, was in our study found to be 1000x higher than female fetal Pl AMH levels, and 100x higher than the Pl AMH levels of pregnant cows. Previous bovine studies showed afterbirth AMH levels up to a hundred

times higher in the of male vs. female calves (Kitahara et al., 2012b; 2012a; Rota et al., 2002).

Matzuk et al. and Teixeira et al. also described a higher AMH expression in the human male fetus at around 8 weeks of pregnancy relating it to its role in development of the male reproductive system (Matzuk and Lamb, 2002; Teixeira et al., 2001).

Evidence of a maternal ovarian AMH contribution as a response to the pregnancy seems unlikely based on the following literature findings. The ovary is known to enter a partly quiescent state during pregnancy in terms of folliculogenesis, due to the lack of gonadotropin signals from the pituitary gland, which is inhibited by: progesterone, estradiol, and relaxin, secreted from the corpus luteum; and by hCG, relaxin, prolactin, and progesterone, secreted from the placenta. Some follicular growth and recruitment still occurs, but follicles do not reach an ovulatory size and number, and have an increased amount of atresia (Guilbault et al., 1986;

Pierson and Ginther, 1986; Westergaard, 1985). Govan et al. described stunted follicular development during pregnancy, where follicles would reach a preantral stage, with a size of up to

6mm, and not progress further (Govan, 1968). They proposed that the action of progesterone, indirectly through inhibition of gonadotropin, is responsible for the inability of follicles to continue further development. Driancourt et al. presented evidence of follicular cycling during the first 7 months of pregnancy, but none of the follicles reached an ovulatory state (Driancourt,

2001). Ovarian production of progesterone is crucial in the first two months of gestation. It has been shown that oophorectomy after 9th week of gestation does not have an effect on pregnancy, while any disturbance prior to 9th week leads to pregnancy loss (Villaseca, 2004). Also, the urine of pregnant women was shown to able induce luteinization in the ovaries of hypophysectomized rats (Leonard and Smith, 1934). Overall, the ovary might be important due to progesterone

synthesis, however dormant in terms of folliculogenesis, and therefore an unlikely contributor of maternal systemic AMH during pregnancy.

Considering the possible contribution of fetal AMH to maternal Pl AMH levels, one has to explore the potential ability of fetal AMH to cross the placenta and enter the maternal circulation. There are four anatomical barriers between maternal and fetal circulation: syncytiotrophoblast, trophoblastic and capillary basement membranes, and fetal capillary endothelium. It is known that CO2 and steroid compounds move by passive diffusion in the direction of the equilibration of the concentration gradient. Larger charged molecules, such as peptide hormones, move across the placenta by means of: active transport by either specialized receptor molecules within microvesicles (receptor mediated endocytosis) (Pereira et al., 2013;

Sandvig and Llorente, 2012), or by pinocytosis of syncitiothrophoblast cells (Palmeira et al.,

2012); and passive transport at a very slow rate (Malek et al., 1998). Examples of maternal to fetal active transfer via receptor molecules on the membrane are IgGs, 160kDa in size, which ensure that her passive immunity is transferred to the fetus towards the end of pregnancy.

Another protein, transferrin, 80kDa in size, is transferred by means of pinocytosis, which ensures proper supply of oxygen to the fetus. Examples of fetal to maternal active transfer via microvesicles in a cloned cattle model are transgenic enhanced Green Fluorescent Protein

(eGFP), 32kDa in size, and fetal DNA (Pereira et al., 2013), with an upper limit for a microvesicle transfer defined as 150kDa (Sandvig and Llorente, 2012). Alpha fetal protein (AFP),

70kDa in size, is an example of a protein transferred by means of diffusion from the fetus to the mother. AFP is found at a 100x smaller concentration in the mother compared to the fetus, the levels correlating to placental size and week of pregnancy, starting from the end of the first trimester (Malek et al., 1998). It is speculated that this passive diffusion occurs not directly

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through the membranes but through placental “leaks” or defects, as occurs with the fetal cells found in the maternal circulation (Malek et al., 1998). It is was found that AFP passes through

“the villous core ross the fibrinoid deposits at sites of discontinuity of the syncytiotrophoblast or from decidua basalis by entering the vessels that traverse the basal plate” without passing through the cytoplasm (Brownbill et al., 1995). The author argued that, in normal pregnancies, even with the much higher concentration of AFP in fetal blood, it is difficult to detect evidence of AFP transfer to the mother due to dilution of AFP in the much higher volume of maternal blood. This is probably similar to what we observed with AMH. AFP and its receptor have been shown to be expressed by the placenta (Duc-Goiran et al., 2006), similar to AMH. Therefore, based on the examples of IgG, eGFP and AFP it could be speculated that AMH could pass through the placenta from the fetus to the mother, utilizing both passive and active transport.

Further studies are necessary to confirm these speculations.

The potential effects of increased AMH levels during pregnancy, such as those possibly produced and transferred from the male fetus, may possibly manifest in differences in developmental between male vs. female brains and associated behaviors, the Free-Martin effect being one such example, the response of pregnant mothers to chronic illness, and in oncogenesis.

The effect of the absence of AMH on brain and motor development can be seen in the KO mice studies. AMHR2 is shown to be expressed differently in the brains of male and female mice, leading to higher levels of motor neuron development and increased novelty preference in the male mice (Morgan et al., 2011; Wang et al., 2009; Wittmann and McLennan, 2011). Increased levels of AMH in bovine twin pregnancies with fetuses of opposite sex led to increased levels of aggression and masculinization of the reproductive tract in the female twin, called a Free-Martin, due to high levels of male AMH from the male twin (Barker, 1944). It has been shown that

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mothers carrying a male fetus differ by have a higher risk of needing acute care and medication if diagnosed with chronic asthma, have decreased blood pressure, and have increased insulin resistance (Firoozi et al., 2009; Hocher et al., 2009; Walsh et al., 2015). The effect of excess

AMH has been explored in experiments by Stephen et al., where the addition of 10g of recombinant AMH per day for 3 weeks caused an inhibition of human cancer cell lines in vivo, and decreased neovascularization, necrosis, inflammation and tumor size (Stephen et al., 2002).

Nishi et al. showed that AMH expression varied depending on the tumor size, while AMHR2 is unaffected. They also showed that, with increasing levels of exogenous AMH, there was a tumor cell number decrease, by means of apoptosis, in vivo and in vitro (Y. Nishi et al., 2000). It can also be speculated that women who carry a male fetus might have delayed subsequent ovulation, could exhibit more masculine behaviors, and could have a decreased risk of oncogenesis due to the additive AMH effect.

In this thesis the monofollicular collection (mono FF) method was used to closely examine and investigate links between AMH and reproductive outcomes in an IVF patient population. Importantly, this detailed approach allowed for the novel identification of a number of potential unexpected trends in subsets of individuals or follicles that appear to display opposing relationships between AMH levels and outcomes. These results show that only understanding both systemic and follicular levels of AMH, is possible to correctly predict the capacity of the entire ovary, as well as the potential of the individual follicle. The ovarian capacity as a whole, and the follicle as a localized environment both have an effect on the developing oocyte. Fertility, in general, is a property of codependent quantitative and qualitative parameters, with the ultimate goal of having both a large and healthy oocyte reserve (Brodin et al., 2013; Holte et al., 2011; Kawamura et al., 2013; Sunkara et al., 2011). This thesis begins to

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look beyond AMH as either a qualitative or quantitative marker alone and on towards a scenario where it can be seen to represents both these parameters together. In a general sense, Chapter 1 represents and demonstrates clear evidence AMH is a marker of quantity, and Chapter 3 represents and demonstrates clear evidence AMH is a marker of quality. Perhaps the most obvious way to begin to tie these two characteristics together is through the “size matters” concept, where the organ’s size and the quantity of cells positively correlates to its function,

Figure 12. For example, smaller ovarian reserve could directly imply lowered oocyte quality within the reserve, and vice versa, irrespective of the age. This relationship can also be seen and has been assessed in other organs such as testes, where size was found to be proportional to the amount of Sertoli cells, which further correlated to male fertility (Keeton et al., 1996; Velde and

Pearson, 2002). Unlike testes, mammaries and their size were not correlated to the ability of the secretory cells to produce milk (Ramsay et al., 2005).

On the tissue level, this relationship of quantity and quality codependence is demonstrated by the complex interplay between cellular interactions. How structure or size can affect the function or the quality can be seen in the ovarian morphology and factors that disrupt this equilibrium within the tissue. The ovary has a firm cortex on the outer layer, where the follicles enclosing the oocytes reside, and a softer medulla in the inner layer. As they mature, follicles move from the outer firm layers of the ovary towards the inner softer layers. This “out to in” direction of follicular growth is a fairly novel concept, and provides the link to the codependence between the physical characteristics of the ovarian reserve and its functional property, which is to produce a healthy oocyte (Woodruff and Shea, 2010). The physical interactions between the supporting cells in the follicle (granulosa) with the oocytes, which are facilitated through the gap and adherent junctions between the cells, ensure follicular arrest and

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dormancy in the outer layer, or detachment, growth, and proper maturation in the inner layers of the ovary (Gilchrist et al., 2008; Li and Albertini, 2013). Detachment of these two cell types is dependent on the decreased amount of cAMP, Ca2+, and AMH, allowing for the increased expression of gonadotropin receptors, and stereogenesis (Norris et al., 2009; Tsafriri et al., 1996;

Webb et al., 2002). Also, during the follicular recruitment process, physical changes are evidenced by perturbation in the extracellular matrix and cytoskeleton of the oocyte and granulosa cells (Berkholtz et al., 2006; Hsueh et al., 2015). Another proof of the codependence between structure and function are ovarian pathologies and their treatment methods, with AMH being an indicator of both, as presented in all chapters. One treatment method is ovarian drilling, where an ovarian injury is deliberately induced, leading to increased ovarian function due to the disturbance in the ovarian structure (Ortega-Hrepich et al., 2014). A small inaccessible reserve of follicles unresponsive to gonadotropins is thus reawakened by the structural disturbance. Women who specifically benefit from this method are those with diminished ovarian reserve (DOR), or polycystic ovarian syndrome (PCOS) patients both known to have lowered and increased systemic AMH respectively (La Marca et al., 2009). Second method where ovarian structural integrity is disturbed is ovarian fragmentation, coupled with oocyte maturation in vitro, or with crypreservation of the ovarian pieces and in vivo oocyte maturation (Dunlop et al., 2016;

Kawamura et al., 2013; Varghese et al., 2008; Xiao et al., 2015). Patients benefiting are those with premature ovarian failure (POF), due to cancer diagnosis, who need their gametes preserved prior to cytotoxic therapy. In both of these methods, the birth of healthy children was achieved by the disturbance of ovarian structure, leading to a decrease in the paracrine signals that inhibit follicular recruitment (Donnez et al., 2011; Hsueh et al., 2015). It could be speculated that ovarian injury may be associated with the lowering of local AMH, and that both may increase

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the ovarian ability to reacquire its “stemness” or capacity to regenerate ovarian reserve, supported by Hu et al. (Hu et al., 2014). This concept challenges the dogma that a fixed germ cell population is determined in utero for the female lifetime (J. Johnson et al., 2005; 2004). A balance between renewal capacity and dormancy of follicles throughout the reproductive years is crucial for proper species reproduction and propagation of its genetic material.

The broader importance of these findings lies in strengthening of evidence that AMH represents consistent, reliable, and inexpensive ovarian function marker during non-pregnant and pregnant state. In this way, it can provide key insights into fertility potential and be used to improve ovarian stimulation protocols, breeding program efficiency, determination of fetal sex, and ovarian pathologies. In specific relation to human ART, development of AMH as a marker will continue to facilitate individualized ovarian reserve estimates and optimized stimulation protocols and treatments that increase the safety of patients.

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Figure 12 “Size matters concept” representation of the ovary in which the ovarian size is positively correlated to: the ovarian reserve, the ovarian function (based on the oocyte developmental potential), and the systemic AMH level. However it is negatively correlated to the ovulatory follicular AMH level.

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SUMMARY, CONCLUSIONS, AND FUTURE DIRECTIONS

AMH measured from serum/plasma, from pooled or averaged follicular fluid, or as its receptor RNA transcript from granulosa cells were correlated to the number of antral follicles, number of oocytes and blastocyst rate. Zebu cattle were found to have a higher level of plasma and follicular AMH. Crossbred animals were found to more closely mirror Zebu cattle in their fertility parameters. Differences in AMH, if measured in the serum of pregnant cows between day 35 and 135 of gestation, were found to reflect the sex of the fetus, with cows carrying a male fetus having higher AMH level difference compared to cows carrying a female fetus. AMHR2

RNA expression measured in the placenta and cotyledon in pregnancies with male and female fetuses was not found to be different. AMH levels measured from human serum, averaged follicular fluid, and AMHR2 transcript levels from averaged pooled granulosa cells showed a negative correlation to blastocyst rate. If patients were divided into two groups based on their serum AMH, the group with normal levels was found to have a significantly higher blastocyst rate compared to the group with a higher serum AMH. When measured in single follicles in high and normal serum AMH patients, blastocysts developed from follicles with higher AMH levels in high serum AMH patients, and from follicles with lower AMH levels in normal serum AMH patients, compared to the AMH levels in follicles of arrested embryos. Therefore, high systemic and low ovulatory follicular AMH might indicate high ovarian reserve, AFC, and oocyte numbers, and a good prognosis in infertility treatment; however, if it leaves the realm of biologically optimal values it might become a marker of a poor prognosis, or lose its value as a marker.

From the current studies, we can say that AMH is a valid indicator of ovarian structure and function, being a marker of oocyte number and AFC in cattle, and being a marker of

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blastocyst rate in humans. We can also say that through measured from serum/plasma, follicular fluid or granulosa cell transcript levels, it can also represent ovarian activity. These correlations and relationships can be highly dependent on: species, human or bovine; stage of follicles, antral or ovulatory; the way follicles are collected, by pooling the follicular fluid or by measuring each follicle separately and then averaging the value for all; ovarian status; current serum or plasma and these factors should be considered in investigations and data interpretation. During pregnancy AMH levels appear to be impacted by the fetal sex in the bovine species and therefore have a potential use in early sex detection.

Future studies should continue to build on the present results to further increase our understanding of AMH biology and the potential power and utility of AMH as a marker of ovarian function. Improved characterization of AMH use within assisted reproduction assays could be accomplished by including larger number of patients in studies and further exploring the relationship between AMH and oocyte developmental potential, and other factors involved in

AMH signaling and their transcripts. Also the specific inclusion of patients with different diagnoses of infertility should be included in future studies to explore changes in AMH biology or prognostic value in these conditions. In cattle studies, AMH levels should be further explored at additional time points throughout pregnancy, on a larger sample number, and whenever possible include corresponding fetus plasma AMH values. Also, specific experiments exploring the potential transport of AMH across the placenta are important in explaining the relationship between fetal and maternal AMH levels during pregnancy. Similarly, the possible effects of increased AMH on mothers carrying a male fetus should be directly investigated. In bovine experiments, it would be beneficial when possible to control for genetic variability of an oocyte donor and embryo recipient, in order to more accurately follow up on the pregnancy outcomes of

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all the oocytes from each animal. Last but not least, our understanding of the specific mechanisms behind AMH’s ability to arrest follicular selection and maturation remains incomplete and achieving a greater understanding of these pathways would certainly be useful in understanding infertility and its treatment.

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LITERATURE CITED

Abeygunawardena, H., Dematawewa, C.M.B., 2004. Pre-pubertal and postpartum anestrus in tropical Zebu cattle. Animal Reproduction Science 82-83, 373–387.

Agdi, M., Zarei, A., Al-Sannan, B., Tulandi, T., Tan, S.L., 2010. Effects of ovarian puncture for in vitro maturation on subsequent in vitro fertilization cycle in women with polycystic ovaries. Fertility and Sterility 94, 381–383.

Aksglaede, L., Sørensen, K., Boas, M., Mouritsen, A., Hagen, C.P., Jensen, R.B., Petersen, J.H., Linneberg, A., Andersson, A.M., Main, K.M., Skakkebæk, N.E., Juul, A., 2010. Changes in Anti-Müllerian Hormone (AMH) throughout the Life Span: A Population-Based Study of 1027 Healthy Males from Birth (Cord Blood) to the Age of 69 Years. The Journal of Clinical Endocrinology & Metabolism 95, 5357–5364.

Ali, A., Fahmy, S., 2008. Ultrasonographic fetometry and determination of fetal sex in buffaloes (Bubalus bubalis). Animal Reproduction Science 106, 90–99.

Alvarez, P., Spicer, L.J., Chase, C.C., Payton, M.E., Hamilton, T.D., Stewart, R.E., Hammond, A.C., Olson, T.A., Wettemann, R.P., 2000. Ovarian and endocrine characteristics during an estrous cycle in Angus, Brahman, and Senepol cows in a subtropical environment. Journal of Animal Science 1291–1302.

Anderson, R.A., Nelson, S.M., Wallace, W.H.B., 2012. Measuring anti-Müllerian hormone for the assessment of ovarian reserve: When and for whom is it indicated? Maturitas 71, 28–33.

Andrabi, S.M.H., Maxwell, W.M.C., 2007. A review on reproductive biotechnologies for conservation of endangered mammalian species. Animal Reproduction Science 99, 223–243.

Anttonen, M., auml, A.F.A.R., Tauriala, H., Kauppinen, M., MacLaughlin, D.T., Unkila-Kallio, L., tzow, R.B.U., Heikinheimo, M., 2011. Anti-Mullerian hormone inhibits growth of AMHtype II receptor-positive human ovarian granulosacell tumor cells by activating apoptosis. Laboratory Investigation 91, 1605–1614.

Argyle, C.E., Harper, J.C., Davies, M.C., 2016. Oocyte cryopreservation: where are we now? Human Reproduction Update dmw007.

Armstrong, S., Arroll, N., Cree, L.M., Jordan, V., Farquhar, C., 2015. Time-lapse systems for embryo incubation and assessment in assisted reproduction. John Wiley & Sons, Ltd, Chichester, UK.

Ashkar, F.A., Semple, E., Schmidt, C.H., St John, E., Bartlewski, P.M., King, W.A., 2010. Thyroid hormone supplementation improves bovine embryo development in vitro. Human Reproduction 25, 334–344.

Balaban, B., Urman, B., 2006. Effect of oocyte morphology on embryo development and

110

implantation. RBM Online 12, 608–615.

Baldrighi, J.M., Sá Filho, M.F., Batista, E., Lopes, R., Visintin, J.A., Baruselli, P.S., Assumpção, M., 2014. Anti-Mullerian Hormone Concentration and Antral Ovarian Follicle Population in Murrah Heifers Compared to Holstein and Gyr Kept Under the Same Management. Reproduction in Domestic Animals 49, 1015–1020.

Barker, C.A.V., 1944. Lactation in a Free Martin Heifer Following Hormone Therapy. Canadian Journal of Comparative Medicine 8, 216–208.

Barreto, R.S.N., Bressan, F.F., Oliveira, L.J., Pereira, F.T.V., Perecin, F., Ambrósio, C.E., Meirelles, F.V., Miglino, M.A., 2011. Gene expression in placentation of farm animals: An overview of gene function during development. Theriogenology 76, 589–597.

Baruselli, P.S., de Sá Filho, M.F., Martins, C.M., Nasser, L.F., Nogueira, M.F.G., Barros, C.M., Bó, G.A., 2006. Superovulation and embryo transfer in Bos indicus cattle. Theriogenology 65, 77–88.

Batista, E., Macedo, G.G., Sala, R.V., Ortolan, M., Sá Filho, M.F., Del Valle, T.A., Jesus, E.F., Lopes, R., Rennó, F.P., Baruselli, P.S., 2014. Plasma Antimullerian Hormone as a Predictor of Ovarian Antral Follicular Population in Bos indicus(Nelore) and Bos taurus(Holstein) Heifers. Reproduction in Domestic Animals 49, 448–452.

Baylis, F., 2015. Left Out in the Cold: Arguments AgainstNon-Medical Oocyte Cryopreservation. Journal of Obstetrics and Gynaecology Canada 37, 64–67.

Beatty, D.T., Barnes, A., Taylor, E., Pethick, D., McCarthy, M., Maloney, S.K., 2006. Physiological responses of Bos taurus and Bos indicus cattle to prolonged, continuous heat and humidity. Journal of Animal Science 84, 972–985.

Berkholtz, C.B., Shea, L.D., Woodruff, T.K., 2006. Extracelllar matrix functions in follicle maturation. Seminars in Reproductive Medicine 24, 262–269.

Bodo, S., Baranyai, B., Gocza, E., Dohy, J., Markkula, M., 2001. Preimplantation Genetic Diagnosis in Cattle: A Review. Acta Veterianaria Hungarica 49, 99–109.

Bols, P.E.J., Jorssen, E.P.A., Goovaerts, I.G.F., Langbeen, A., Leroy, J.L.M.R., 2012. High throughput non-invasive oocyte quality assessment: the search continues. Animal Reproduction Science 9, 420–425.

Boni, R., Cuomo, A., Tosti, E., 2002. Developmental Potential in Bovine Oocytes Is Related to Cumulus-Oocyte Complex

Grade, Calcium Current Activity, and Calcium Stores. Biology of Reproduction 66, 836–842.

Bó, G.A., Baruselli, P.S., Martı́nez, M.F., 2003. Pattern and manipulation of follicular

111

development in Bos indicus cattle. Animal Reproduction Science 78, 307–326.

Brett, K., Ferraro, Z., Yockell-Lelievre, J., Gruslin, A., Adamo, K., 2014. Maternal–Fetal Nutrient Transport in Pregnancy Pathologies: The Role of the Placenta. International Journal of Molecular Sciences 15, 16153–16185.

Brinton, L., Sahasrabuddhe, V., Scoccia, B., 2012. Fertility Drugs and the Risk of Breast and Gynecologic Cancers. Seminars in Reproductive Medicine 30, 131–145.

Brodin, T., Hadziosmanovic, N., Berglund, L., Olovsson, M., Holte, J., 2013. Antimüllerian Hormone Levels Are Strongly Associated With Live-Birth Rates After Assisted Reproduction. The Journal of Clinical Endocrinology & Metabolism 98, 1107–1114.

Brownbill, P., Edwards, D., Jones, C., Mahendran, D., Owen, D., Sibley, C., Johnson, R., Sanson, P., Nelson, M., 1995. Mechanisms of alphafetoprotein transfer in the perfused human placental cotyledon from uncomplicated pregnancy. Journal of Clinical Investigations 96, 2220–2226.

Burns, D.S., 2005. Numbers of Antral Follicles During Follicular Waves in Cattle: Evidence for High Variation Among Animals, Very High Repeatability in Individuals, and an Inverse Association with Serum Follicle-Stimulating Hormone Concentrations. Biology of Reproduction 73, 54–62.

Bushnik, T., Garner, R., 2008. The Children of Older First-time Mothers in Canada: Their Health and Development. Children and Youth research Paper Series- Ottawa, Statistics Canada 1– 58.

Bushnik, T., Haines, D., Levallois, P., Levesque, J., Oostdam, J.V., Viau, C., 2010. Lead and bisphenol A concentrations in the Canadian population. Statistics Canada Catalogue Health Reports 1–13.

Butler, W.R., 2003. Energy balance relationships with follicular development, ovulation and fertility in postpartum dairy cows. Livestock Production Science 83, 211–218.

Campbell, B.K., Clinton, M., Webb, R., 2012. The Role of Anti-Müllerian Hormone (AMH) During Follicle Development in a Monovulatory Species (Sheep). Endocrinology 153, 4533– 4543.

Campbell, B.K., Telfer, E.E., Webb, R., Baird, D.T., 2004. Evidence of a Role for Follicle- Stimulating Hormone in Controlling the Rate of Preantral Follicle Development in Sheep. Endocrinology 145, 1870–1879.

Carter, A.M., Enders, A.C., 2013. The Evolution of Epitheliochorial Placentation. Annu. Rev. Anim. Biosci. 1, 443–467.

Catteau-Jonard, S., Jamin, S.P., Leclerc, A., Gonzales, J., Dewailly, D., di Clemente, N., 2008.

112

Anti-Mullerian Hormone, Its Receptor, FSH Receptor, and Androgen Receptor Genes Are Overexpressed by Granulosa Cells from Stimulated Follicles in Women with Polycystic Ovary Syndrome. Journal of Clinical Endocrinology & Metabolism 93, 4456–4461.

Chambers, G.M., Illingworth, P.J., Sullivan, E.A., 2011. Assisted reproductive technology: public funding and the voluntary shift to single embryo transfer in Australia. Med J Aust 195, 594–598.

Chang, M.-Y., Chiang, C.-H., Hsieh, T.-T., Soong, Y.-K., Hsu, K.-H., 1998. Use of the antral follicle count to predict the outcome of assisted reproductive technologies. Fertility and Sterility 69, 505–510.

Chen, K., Chmait, R.H., Vanderbilt, D., Wu, S., Randolph, L., 2013. Chimerism in monochorionic dizygotic twins: Case study and review. Am. J. Med. Genet. 161, 1817–1824.

Choudhary, K.K., Kavya, K.M., Jerome, A., Sharma, R.K., 2016. Advances in reproductive biotechnologies. Vet World 9, 388–395.

Chronopoulou, E., Harper, J.C., 2014. IVF culture media: past, present and future. Human Reproduction Update 21, 39–55.

Connolly, M.P., Pollard, M.S., Hoorens, S., Kaplan, B.R., Oskowitz, S.P., Silber, S.J., 2008. Long-term economic bene ts Attributed to IVF-conceived Children: A Lifetime tax Calculation. American Journal of Menaged Care 14, 598–604.

Costa, N.N., Cordeiro, M.S., Silva, T.V.G., Sastre, D., Santana, P.P.B., Sá, A.L.A., Sampaio, R.V., Santos, S.S.D., Adona, P.R., Miranda, M.S., Ohashi, O.M., 2013. Theriogenology. Theriogenology 80, 295–301.

Coulter, G.H., Foote, R.H., 1979. Bovine testicular measurements as indicators of reporoductive performance and their relationship to productive traits in cattle, a review. Theriogenology 297-311, 297–311.

Cupisti, S., Dittrich, R., Mueller, A., Strick, R., Stiegler, E., Binder, H., Beckmann, W., Strissel, P., 2007. Correlations between anti-Mullerian hormone, inhibin B, and activin A in follicular fluid in IVF/ICSI patents for assesing the maturation and developmental potential of oocyte. European Journal of Medical Research 12, 604–608.

Derom, R., Derom, C., Loos, R.J.F., Thiery, E., Vlietinck, R., Fryns, J.-P., 2005. Gender mix: does it modify birthweight – outcome association? Paediatric and Perinatal Epidemiology 19, 37–40. di Clemente, N., Jamin, S.P., Lugovskoy, A., Carmillo, P., Ehrenfels, C., Picard, J.-Y., Whitty, A., Josso, N., Pepinsky, R.B., Cate, R.L., 2010. Processing of Anti-Müllerian Hormone Regulates Receptor Activation by a Mechanism Distinct from TGF-β. Molecular Endocrinology 24, 2193–2206.

113

di Clemente, N., Josso, N., Gouédard, L., Belville, C., 2003. Components of the anti-Müllerian hormone signaling pathway in gonads. Molecular and Cellular Endocrinology 211, 9–14.

Diaz, P., Powell, T.L., Jansson, T., 2014. The Role of Placental Nutrient Sensing in Maternal- Fetal Resource Allocation. Biology of Reproduction 91, 82–82.

Donnez, J., Silber, S., Andersen, C.Y., Demeestere, I., Piver, P., Meirow, D., Pellicer, A., Dolmans, M.-M., 2011. Children born after autotransplantation of cryopreserved ovarian tissue. A review of 13 live births. Annals of Medicine 43, 437–450.

Driancourt, M.A., 2001. Regulation of ovarian follicular dynamics in farm animals. Implications for manimulation of reproduction. Theriogenology 55, 1211–1239.

Duc-Goiran, P., Mignot, T.M., Robert, B., Machaboine, F., Mondon, F., Hagnere, A.M., Vacher- Laveny, M.C., Danan, J.L., Vaiman, D., Benassayag, C., Ferre, F., 2006. Expression and Localization of Alpha-fetoprotein mRNA and Protein in Human Early Villous Trophoblasts. Placenta 27, 812–821.

Dunlop, C.E., Brady, B.M., McLaughlin, M., Telfer, E.E., White, J., Cowie, F., Zahra, S., Wallace, W.H.B., Anderson, R.A., 2016. Re-implantation of cryopreserved ovarian cortex resulting in restoration of ovarian function, natural conceptionand successful pregnancy after haematopoietic stemcell transplantation for Wilms tumour. Journal of Assisted Reproduction and Genetics 1–6.

Durlinger, A.L., Gruijters, M.J.G., Kramer, P., Karels, B., Kumar, R.T., Matzuk, M.M., Rose, U.M., de Jong, F.H., Uilenbroek, J.T.J., Grootegoed, A.J., Themmen, A.P.N., 2001. Anti- Mullerian Hormone Attenuates the Effects of FSH on Follicle Development in the Mouse Ovary. Endocrinology 142, 4891–4899.

Durlinger, A.L., Kramer, P., Karels, B., de Jong, F.H., Uilenbroek, J.T.J., Grootegoed, J.A., Themmen, A.P.N., 1999. Control of Primordial Follicle Recruitment by Anti-Mullerian Hormone in the Mouse Ovary*. Endocrinology 140, 5789–5796.

Ebner, T., 2003. Selection based on morphological assessment of oocytes and embryos at different stages of preimplantation development: a review. Human Reproduction Update 9, 251–262.

Ebner, T., 2006. Basal level of anti-Mullerian hormone is associated with oocyte quality in stimulated cycles. Human Reproduction 21, 2022–2026.

Eldar-Geva, T., 2005. Dynamic assays of inhibin B, anti-Mullerian hormone and estradiol following FSH stimulation and ovarian ultrasonography as predictors of IVF outcome. Human Reproduction 20, 3178–3183.

Empey, R., Santillan, D., Santiillan, M., Tyler, E., Hunter, S., Smith, E., Stegman, B., 2012. The influence of fetal sex on patterns of change in anti-Mullerian hormone during pregnancy.

114

Proceedings in Obstertrics and Gynecology 2, 1–2.

Enders, A.C., Carter, A.M., 2004. What Can Comparative Studies of Placental Structure Tell Us?—A Review. Placenta 25, S3–S9.

Eppig, J.J., Wigglesworth, K., Pendola, F.L., 2002. The mammalian oocyte orchestrates the rate of ovarian follicular development. PNAS 99, 2890–2894.

Erickson, B.H., 1966. Development and senescence of the postnatal bovine ovary. J Anim Sci 25, 800–805.

Eriksson, J.G., Kajantie, E., Osmond, C., Thornburg, K., Barker, D.J.P., 2009. Boys live dangerously in the womb. Am. J. Hum. Biol. 22, 330–335.

Fanchin, R., 2003. Serum anti-Mullerian hormone is more strongly related to ovarian follicular status than serum inhibin B, estradiol, FSH and LH on day 3. Human Reproduction 18, 323– 327.

Fanchin, R., Mendez Lozano, D.H., Frydman, N., Gougeon, A., di Clemente, N., Frydman, R., Taieb, J., 2007. Anti-Mullerian Hormone Concentrations in the Follicular Fluid of the Preovulatory Follicle Are Predictive of the Implantation Potential of the Ensuing Embryo Obtained by in Vitro Fertilization. Journal of Clinical Endocrinology & Metabolism 92, 1796–1802.

Ferreira, E.M., Vireque, A.A., Adona, P.R., Meirelles, F.V., Ferriani, R.A., Navarro, P.A.A.S., 2009. Cytoplasmic maturation of bovine oocytes: Structural and biochemical modifications and acquisition of developmental competence. Theriogenology 71, 836–848.

Ferris, J., Favetta, L.A., King, W.A., 2015. Bisphenol A Exposure during Oocyte Maturation in vitro Results in Spindle Abnormalities and Chromosome Misalignment in Bos taurus. Cytogenet Genome Res 145, 50–58.

Firoozi, F., Ducharme, F.M., LemiEre, C., Beauchesne, M.-F., Perreault, S., Forget, A., Blais, L., 2009. Effect of fetal gender on maternal asthma exacerbations in pregnant asthmatic women. Respiratory Medicine 103, 144–151.

Fortune, J.E., Yang, M.Y., Muruvi, W., 2011. In vitro and in vivo regulation of follicular formation and activation in cattle. Reprod. Fertil. Dev. 23, 15.

Gilchrist, R.B., Lane, M., Thompson, J.G., 2008. Oocyte-secreted factors: regulators of cumulus cell function and oocyte quality. Human Reproduction Update 14, 159–177.

Govan, A., 1968. The human ovary in early pregnancy. Journal of Endocrinology 40, 421–428.

Grady, R., Alavi, N., Vale, R., Khandwala, M., McDonald, S.D., 2012. Elective single embryo transfer and perinatal outcomes: a systematicreview and meta-analysis. Fertility and Sterility

115

97, 324–331.

Grodon, I.R., 2003. Laboratory Production of Cattle Embryos, 2nd Edition, 2nd ed. CABI Publishing.

Guerreiro, B.M., Batista, E.O.S., Vieira, L.M., Filho, M.F.S., Rodrigues, C.A., Netto, A.C., Silveira, C.R.A., Bayeux, B.M., Dias, E.A.R., Monteiro, F.M., Accorsi, M., Lopes, R.N.V.R., Baruselli, P.S., 2014. Plasma anti-mullerian hormone: an endocrine marker for in vitro embryo production from Bos taurus and Bos indicus. Domestic Animal Endocrinology 49, 96–104.

Guilbault, L.A., Dufour, J.J., Thatcher, W.W., Drost, M., Haibel, G.K., 1986. Ovarian follicular development during early pregnancy in cattle. Journal of Reproduction and Fertility 78, 127– 135.

Habbema, J.D.F., Eijkemans, M.J.C., Leridon, H., Velde, te, E.R., 2015. Realizing a desired family size: when should couples start? Human Reproduction 30, 2215–2221.

Hamel, M., Dufort, I., Robert, C., Gravel, C., Leveille, M.C., Leader, A., Sirard, M.A., 2008. Identification of differentially expressed markers in human follicular cells associated with competent oocytes. Human Reproduction 23, 1118–1127.

Hankins, G.V.D., Saade, G.R., 2005. Factors influencing twins and zygosity. Paediatric and Perinatal Epidemiology 19, 8–9.

Hazout, A., Bouchard, P., Seifer, D.B., Aussage, P., Junca, A.M., Cohen-Bacrie, P., 2004. Serum antimüllerian hormone/müllerian-inhibiting substance appears to be a more discriminatory marker of assisted reproductive technology outcome than follicle-stimulating hormone, inhibin B, or estradiol. Fertility and Sterility 82, 1323–1329.

Hocher, B., Chen, Y.-P., Schlemm, L., Burdack, A., Li, J., Halle, H., Pfab, T., Kalk, P., Lang, F., Godes, M., 2009. Fetal sex determines the impact of maternal PROGINS progesterone receptor polymorphism on maternal physiology during pregnancy. Pharmacogenetics and Genomics 19, 710–718.

Holte, J., Brodin, T., Berglund, L., Hadziosmanovic, N., Olovsson, M., Bergh, T., 2011. Antral follicle counts are strongly associated with live-birth rates after assisted reproduction, with superior treatment outcome in women with polycystic ovaries. Fertility and Sterility 96, 594–599.

Hsueh, A.J.W., Kawamura, K., Cheng, Y., Fauser, B.C.J.M., 2015. Intraovarian Control of Early Folliculogenesis. Endocrine Reviews 36, 1–24.

Hu, R., Wang, F.-M., Yu, L., Luo, Y., Wu, X., Li, J., Zhang, X.-M., Oehninger, S., D, S.B.M.D.P., 2014. Antim€ullerian hormone regulatesstem cell factor expression in humangranulosa cells. Fertility and Sterility 102, 1742–1750.e1.

116

Hwang, W.-S., Cho, J.-K., Kim, K.-Y., Shin, S.-J., Kim, S.-K., Park, J.-I., Kim, D.-Y., Lee, J.-K., Lim, J.M., Lee, B.-C., 2001. Births of Freemartins Derived from Embryos Reconstructed with Ear Fibroblasts. Theriogenology 63, 577–578.

Imhoff, F.M., Yang, D., Mathew, S.F., Clarkson, A.N., Kawagishi, Y., Tate, W.P., Koishi, K., McLennan, I.S., 2013. The type 2 anti-Müllerian hormone receptor has splice variants that are dominant-negative inhibitors. FEBS Letters 587, 1749–1753.

Ireland, J.J., Smith, G.W., Scheetz, D., Jimenez-Krassel, F., Folger, J.K., Ireland, J.L.H., Mossa, F., Lonergan, P., Evans, A.C.O., 2011. Does size matter in females? An overview of the impact of the high variation in the ovarian reserve on ovarian function and fertility, utility of anti-Müllerian hormone as a diagnostic marker for fertility and causes of variation in the ovarian reserve in cattle. Reprod. Fertil. Dev. 23, 1.

Ireland, J.J., Ward, F., Jimenez-Krassel, F., Ireland, J.L.H., Smith, G.W., Lonergan, P., Evans, A.C.O., 2007. Follicle numbers are highly repeatable within individual animals but are inversely correlated with FSH concentrations and the proportion of good-quality embryos after ovarian stimulation in cattle. Human Reproduction 22, 1687–1695.

Ireland, J.J., Zielak-Steciwko, A.E., Jimenez-Krassel, F., Folger, J., Bettegowda, A., Scheetz, D., Walsh, S., Mossa, F., Knight, P.G., Smith, G.W., Lonergan, P., Evans, A.C.O., 2009. Variation in the Ovarian Reserve Is Linked to Alterations in Intrafollicular Estradiol Production and Ovarian Biomarkers of Follicular Differentiation and Oocyte Quality in Cattle. Biology of Reproduction 80, 954–964.

Ireland, J.L.H., Scheetz, D., Jimenez-Krassel, F., Themmen, A.P.N., Ward, F., Lonergan, P., Smith, G.W., Perez, G.I., Evans, A.C.O., Ireland, J.J., 2008. Antral Follicle Count Reliably Predicts Number of Morphologically Healthy Oocytes and Follicles in Ovaries of Young Adult Cattle. Biology of Reproduction 79, 1219–1225.

Johnson, J., Bagley, J., Skaznik-Wikiel, M., Lee, H.-J., Adams, G.B., Niikura, Y., Tschudy, K.S., Tilly, J.C., Cortes, M.L., Forkert, R., Spitzer, T., Iacomini, J., Scadden, D.T., Tilly, J.L., 2005. Oocyte Generation in Adult Mammalian Ovaries by Putative Germ Cells in Bone Marrow and Peripheral Blood. Cell 122, 303–315.

Johnson, J., Canning, J., Kaneko, T., Pru, J.K., Tilly, J.L., 2004. Germline stem cells and follicular renewal in the postnatal mammalian ovary. Nature 428, 145–150.

Johnson, L.A., Rath, D., Vazquez, J.M., Maxwell, W.M.C., Dobrinsky, J.R., 2005. Preselection of sex of offspring in swine for production: current status of the process and its application. Theriogenology 63, 615–624.

Kaser, D.J., Racowsky, C., 2014. Clinical outcomes following selection of human preimplantation embryos with time-lapse monitoring: a systematic review. Human Reproduction Update 20, 617–631.

117

Kawamura, K., Cheng, Y., Suzuki, N., Deguchi, M., Sato, Y., Takae, S., Ho, C.H., Kawamura, N., Tamura, M., Hashimoto, S., Sugishita, Y., Morimoto, Y., Hosoi, Y., Yoshioka, N., Ishizuka, B., Hsueh, A.J., 2013. Hippo signaling disruption and Akt stimulation of ovarian follicles for infertility treatment. PNAS 110, 17474–17479.

Keeton, L.L., Green, R.D., Golden, B.L., Anderson, K.J., 1996. Estimation of Variance Components and Prediction of Breeding Values for Scrotal Circumference and Weaning Weight in Limousin Cattle. Journal of Animal Science 74, 31–36.

Kevenaar, M.E., Meerasahib, M.F., Kramer, P., van de Lang-Born, B.M.N., de Jong, F.H., Groome, N.P., Themmen, A.P.N., Visser, J.A., 2006. Serum Anti-Müllerian Hormone Levels Reflect the Size of the Primordial Follicle Pool in Mice. Endocrinology 147, 3228– 3234.

Kim, J.Y., Yi, G., Kim, Y.R., Chung, J.Y., Ahn, J.H., Uhm, Y.K., Jee, B.C., Suh, C.S., Kim, S.H., 2013. Association between serum anti-Müllerian hormone level and ovarian response to mild stimulation in normoovulatory women and anovulatory women with polycystic ovary syndrome. Clin Exp Reprod Med 40, 95.

Kitahara, G., El-Sheikh Ali, H., Sato, T., Kobayashi, I., Hemmi, K., Shirao, Y., Kamimura, S., 2012a. Anti-Müllerian Hormone (AMH) Profiles as a Novel Biomarker to Evaluate the Existence of a Functional Cryptorchid Testis in Japanese Black Calves. Journal of Reproduction and Development 58, 310–315.

Kitahara, G., Nambo, Y., El-Sheikh Ali, H., Kajisa, M., Tani, M., 2012b. Anti-Müllerian Hormone Profiles as a Novel Biomarker to Diagnose Granulosa-theca Cell Tumors in Cattle. Journal of Reproduction and Development 58, 98–104.

Knight, P.G., 2006. TGF- superfamily members and ovarian follicle development. Reproduction 132, 191–206.

Komisarek, J., Dorynek, Z., 2002. Genetic aspects of twinning in cattle. Journal of Applied Genetics 43, 55–68.

Koufariotis, L., Chen, Y.-P.P., Bolormaa, S., Hayes, B.J., 2014. Regulatory and coding genome regions are enriched for trait associated variants in dairy and beef cattle. BMC Genomics 15, 1–16.

Krisher, R.L., 2013. In Vivo and In Vitro Environmental Effects on Mammalian Oocyte Quality. Annu. Rev. Anim. Biosci. 1, 393–417.

Kuhn, M.T., Hutchison, J.L., Wiggans, G.R., 2006. Characterization of Holstein Heifer Fertility in the United States. Journal of Dairy Science 89, 4907–4920.

Kuijper, E.A.M., Ket, J.C.F., Caanen, M.R., Lambalk, C.B., 2013. Reproductive hormone concentrations in pregnancy and neonates: a systematic review. Reproductive BioMedicine

118

Online 27, 33–63.

Kumar, A., Kalra, B., Patel, A.S., Shah, S., 2013. New Sensitive Anti-Müllerian Hormone (AMH) ELISAs for Non-Human Primate, Rodent, Equine, Bovine, Canine and Other Species 1–1.

La Marca, A., 2005. Anti-Mullerian hormone concentrations in maternal serum during pregnancy. Human Reproduction 20, 1569–1572.

La Marca, A., Broekmans, F.J., Volpe, A., Fauser, B.C., Macklon, N.S., on behalf of the ESHRE Special Interest Group for Reproductive Endocrinology - AMH Round Table, 2009. Anti- Mullerian hormone (AMH): what do we still need to know? Human Reproduction 24, 2264– 2275.

La Marca, A., Nelson, S.M., Sighinolfi, G., Manno, M., Baraldi, E., Roli, L., Xella, S., Marsella, T., Tagliasacchi, D., D’Amico, R., Volpe, A., 2011. Anti-Müllerian hormone-based prediction model for a live birth in assisted reproduction. Reproductive BioMedicine Online 22, 341–349.

La Marca, A., Sighinolfi, G., Radi, D., Argento, C., Baraldi, E., Artenisio, A.C., Stabile, G., Volpe, A., 2010. Anti-Mullerian hormone (AMH) as a predictive marker in assisted reproductive technology (ART). Human Reproduction Update 16, 113–130.

La Marca, A., Stabile, G., Artenisio, A.C., Volpe, A., 2006. Serum anti-Mullerian hormone throughout the human menstrual cycle. Human Reproduction 21, 3103–3107.

La Marca, A., Volpe, A., 2006. Anti-Mullerian hormone (AMH) in female reproduction: is measurement of circulating AMH a useful tool? Clin Endocrinol 64, 603–610.

Lakamge, D.N., 2007. Anti-Müllerian hormone as a predictor of IVF outcome. RBM Online 14, 1–9.

Lasala, C., Carre-Eusebe, D., Picard, J.-Y., Rey, R., 2004. Subcellular and molecular mechanisms regulating anti-Müllerian hormone gene expression in mammalian and nonmammalian species. DNA and Cell Biology 23, 572–585.

Lee, M.M., Donahoe, P.K., Hasegawa, T., Silverman, B., Crist, G.B., Best, S., Hasegawa, Y., Noto, R.A., Schoenfeld, D., MacLaughlin, D.T., 1996. Mullerian inhibiting substance in humans: normal levels from infancy to adulthood. Journal of Clinical Endocrinology & Metabolism 81, 571–576.

Leonard, S.L., Smith, P.E., 1934. Responses of the reproductive system of hypophysectomized rats to injections of pregnancy-urine extracts. The anatomical record 58, 175–203.

Leroy, J., Vanholder, T., Van Knegsel, A., Garcia-Ispierto, I., Bols, P., 2008. Nutrient Prioritization in Dairy Cows Early Postpartum: Mismatch Between Metabolism and

119

Fertility? Reproduction in Domestic Animals 43, 96–103.

Leroy, J.L.M.R., Rizos, D., Sturmey, R., Bossaert, P., Gutierrez-Adan, A., Van Hoeck, V., Valckx, S., Bols, P.E.J., 2012. Intrafollicular conditions as a major link between maternal metabolism and oocyte quality: a focus on dairy cow fertility. Reprod. Fertil. Dev. 24, 1.

Li, R., Albertini, D.F., 2013. The road to maturation: somatic cell interaction and self- organization of the mammalian oocyte. Nature Reviews Molecular Cell Biology 14, 141– 152.

Lo, Y.M.D., Tein, M.S.C., Lau, T.K., Haines, C.J., Leung, T.N., Poon, P.M.K., Wainscoat, J.S., Johanson, P.J., Chang, A.M.Z., Hjelm, N.M., 1998. Quantitative Analysis of Fetal DNA in Maternal Plasma and Serum: Implications for Noninvasive Prenatal Diagnosis. American Journal of Human Genetics 62, 768–775.

Lopes, R.F.F., Forell, F., Oliveira, A.T.D., ROdrigues, J.L., 2001. Splitting and Biopsy for Bovine Embryo Sexing Under FIeld Conditions. Theriogenology 56, 1383–1392.

Lucy, M.C., 2001. ADSA Foundation Scholar Award. Journal of Dairy Science 84, 1277–1293.

Luke, B., Hediger, M., Min, S.-J., Brown, M.B., Misiunas, R.B., Gonzalez-Quintero, V.H., Nugent, C., Witter, F.R., Newman, R.B., Hankins, G.D.V., Grainger, D.A., Macones, G.A., 2005. Gender mix in twins and fetal growth, length of gestation and adult cancer risk. Paediatric and Perinatal Epidemiology 19, 41–47.

Maheshwari, A., Teoh, P.J., 2014. Low-cost in vitro fertilization: current insights. IJWH 817.

Majumder, K., Gelbaya, T.A., Laing, I., Nardo, L.G., 2010. The use of anti-Müllerian hormone and antral follicle count to predict the potential of oocytes and embryos. European Journal of Obstetrics & Gynecology and Reproductive Biology 150, 166–170.

Malek, A., Sager, R., Schneider, H., 1998. Transport of Proteins Across the Human Placenta. American Journal of Reproductive Immunology 40, 343–351.

Mapletoft, R.J., F, H.J., 2005. Assisted reproductive technologies in cattle: a review. Rev. sci. tech. Off. int. Epiz. 24, 393–403.

Matzuk, M.M., Lamb, D.J., 2002. Genetic dissection of mammalian fertility pathways. Nat Cell Biol s41–49.

Mendoza, C., Ruiz-Requena, E., Ortega, E., Cremades, N., Martinez, F., Bernabeu, R., Greco, E., Tesarik, J., 2002. Follicular fluid markers of oocyte developmental potential. Human Reproduction 17, 1017–1022.

Monniaux, D., Baril, G., Laine, A.L., Jarrier, P., Poulin, N., Cognie, J., Fabre, S., 2011. Anti- Mullerian hormone as a predictive endocrine marker for embryo production in the goat.

120

Reproduction 142, 845–854.

Morgan, K., Meredith, J., Kuo, J.Y.A., Bilkey, D.K., McLennan, I.S., 2011. Behavioural Brain Research. Behavioural Brain Research 221, 304–306.

Morikawa, M., Derynck, R., Miyazono, K., 2016. TGF-β and the TGF-β Family: Context- Dependent Roles in Cell and Tissue Physiology. Cold Spring Harb Perspect Biol 8, a021873.

Nelson, S.M., Stewart, F., Fleming, R., Freeman, D.J., 2010. Longitudinal assessment of antimulerian hormone during pregnancy- relationship with maternal adiposity, insulin, and adiponectin. Fertility and Sterility 93, 1356–1358.

Nelson, S.M., Yates, R.W., Fleming, R., 2007. Serum anti-Mullerian hormone and FSH: prediction of live birth and extremes of response in stimulated cycles implications for individualization of therapy. Human Reproduction 22, 2414–2421.

Nilsson, E., Rogers, N., Skinner, M.K., 2007. Actions of anti-Mullerian hormone on the ovarian transcriptome to inhibit primordial to primary follicle transition. Reproduction 134, 209–221.

Nilsson, E.E., Schindler, R., Savenkova, M.I., Skinner, M.K., 2011. Inhibitory Actions of Anti- Müllerian Hormone (AMH) on Ovarian Primordial Follicle Assembly. PLoS ONE 6, e20087.

Nishi, M.Y., Domenice, S., Maciel-Guerra, A.T., Neto, A.Z., da Silva, M.A.C.P., Costa, E.M.F., Guerra-Junior, G., de Mendonca, B.B., 2012. Analysis of anti-Müllerian hormone (AMH) and its receptor (AMHR2) genes in patients with persistent Müllerian duct syndrome. Arq Bras Endocrinol Metab 56, 473–478.

Nishi, Y., Yanese, T., Mu, Y.-M., Oba, K., Ichino, I., Saito, M., Nomura, M., Mukasa, C., Okabe, T., Goto, K., Takayanagi, R., Kashimura, Y., Haji, M., Nawata, H., 2000. Establishment and Characterization of a Steroidogenic Human Granulosa-Like Tumor Cell Line, KGN, That Expresses Functional Follicle-StimulatingHormone Receptor. Endocrinology 142, 437–445.

Norris, R.P., Ratzan, W.J., Freudzon, M., Mehlmann, L.M., Krall, J., Movsesian, M.A., Wang, H., Ke, H., Nikolaev, V.O., Jaffe, L.A., 2009. Cyclic GMP from the surrounding somatic cells regulates cyclic AMP and meiosis in the mouse oocyte. Development 136, 1869–1878.

Novembri, R., Funghi, L., Voltolini, C., Belmonte, G., Vannuccini, S., Torricelli, M., Petraglia, F., 2015. Placenta expresses anti-Müllerian hormone and its receptor: Sex-related difference in fetal membranes. Placenta 36, 731–737.

O'Brien, A.M.P., Utsunomiya, Y., Meszaros, G., Bickhart, D.M., Liu, G.E., Van Tassell, C.P., Sonstegard, T.S., Da Silva, M.V., Garcia, J.F., Solkner, J., 2014. Assessing signatures of selection through variation in linkage disequilibrium between taurine and indicine cattle. Genetics Selection Evolution 46, 1–14.

Oktem, O., Oktay, K., 2008. The Ovary. Annals of the New York Academy of Sciences 1127, 1–

121

Oktem, O., Urman, B., 2010. Understanding follicle growth in vivo. Human Reproduction 25, 2944–2954.

Opsomer, G., Grohn, Y.T., Hertl, J., Coryn, M., Deluyker, H., Kruif, A. de, 2000. Risk Factors for Post Partum Ovarian Dysfunction in High Producing Dairy Cows in Belgium: A Field Study. Theriogenology 53, 841–857.

Ortega-Hrepich, C., Polyzos, N.P., Anckaert, E., Guzman, L., Tournaye, H., Smitz, J., De Vos, M., 2014. The effect of ovarian puncture on the endocrine profile of PCOS patients who undergo IVM. Reproductive Biology and Endocrinology 12, 1–6.

Padula, A.M., 2005. The freemartin syndrome: an update. Animal Reproduction Science 87, 93– 109.

Palmeira, P., Quinello, C., Silveira-Lessa, A.L., Zago, C.A., Carneiro-Sampaio, M., 2012. IgG Placental Transfer in Healthy and Pathological Pregnancies. Clinical and Developmental Immunology 2012, 1–13.

Penarrubia, J., Fabregues, F., Manau, D., Creus, M., Casals, G., Casamitjana, R., Carmona, F., Vanrell, J.A., Balasch, J., 2005. Basal and stimulation day 5 anti-Mullerian hormone serum concentrations as predictors of ovarian response and pregnancy in assisted reproductive technology cycles stimulated with gonadotropin-releasing hormone agonist-gonadotropin treatment. Human Reproduction 20, 915–922.

Pereira, F.T.V., Oliveira, L.J., Barreto, R.D.S.N., Mess, A., Perecin, F., Bressan, F.F., Mesquita, L.G., Miglino, M.A., Pimentel, J.R., Neto, P.F., Meirelles, F.V., 2013. Fetal-Maternal Interactions in the Synepitheliochorial Placenta Using the eGFP Cloned Cattle Model. PLoS ONE 8, e64399.

Pierson, R.A., Ginther, O.J., 1986. Ovarian follicular populations during early pregnancy in heifers. Theriogenology 26, 1–11.

Pigny, P., 2005. Serum Anti-Mullerian Hormone as a Surrogate for Antral Follicle Count for Definition of the Polycystic Ovary Syndrome. Journal of Clinical Endocrinology & Metabolism 91, 941–945.

Pontes, J.H.F., Nonato-Junior, I., Sanches, B.V., Ereno-Junior, J.C., Uvo, S., Barreiros, T.R.R., Oliveira, J.A., Hasler, J.F., Seneda, M.M., 2009. Comparison of embryo yield and pregnancy rate between in vivo and in vitro methods in the same Nelore (Bos indicus) donor cows. Theriogenology 71, 690–697.

Pontes, J.H.F., Silva, K.C.F., Basso, A.C., Rigo, A.G., Ferreira, C.R., Santos, G.M.G., Sanches, B.V., Porcionato, J.P.F., Vieira, P.H.S., Faifer, F.S., Sterza, F.A.M., Schenk, J.L., Seneda, M.M., 2010. Large-scale. Theriogenology 74, 1349–1355.

122

Pontes, J.H.F., Sterza, F.A.M., Basso, A.C., Ferreira, C.R., Sanches, B.V., Rubin, K.C.P., Seneda, M.M., 2011. Ovum pick up. THE 75, 1640–1646.

Ramsay, D.T., Kent, J.C., Hartmann, R.A., Hartmann, P.E., 2005. Anatomy of the lactating human breast redefined withultrasound imaging. Journal of Anatomy 206, 525–534.

Rawn, S.M., Cross, J.C., 2008. The Evolution, Regulation, and Function of Placenta-Specific Genes. Annu. Rev. Cell Dev. Biol. 24, 159–181.

Reynolds, M., 1953. Plasma and blood volume in the cow using the T-1824 hematocrit method. American Journal of Physiology 173, 421–427.

Rice, S., Ojha, K., Whitehead, S., Mason, H., 2006. Stage-Specific Expression of Androgen Receptor, Follicle-Stimulating Hormone Receptor, and Anti-Mullerian Hormone Type II Receptor in Single, Isolated, Human Preantral Follicles: Relevance to Polycystic Ovaries. Journal of Clinical Endocrinology & Metabolism 92, 1034–1040.

Rico, C., Fabre, S., Medigue, C., Clemente, N.D., Clement, F., Bontoux, M., Touze, J.L., Dupont, M., Briant, E., Remy, B., Beckers, J.F., Monniaux, D., 2009. Anti-Mullerian Hormone Is an Endocrine Marker of Ovarian Gonadotropin-Responsive Follicles and Can Help to Predict Superovulatory Responses in the Cow. Biology of Reproduction 80, 50–59.

Rico, C., Medigue, C., Fabre, S., Jarrier, P., Bontoux, M., Clement, F., Monniaux, D., 2011. Regulation of Anti-Mullerian Hormone Production in the Cow: A Multiscale Study at Endocrine, Ovarian, Follicular, and Granulosa Cell Levels. Biology of Reproduction 84, 560–571.

Rienzi, L., Vajta, G., Ubaldi, F., 2010. Predictive value of oocyte morphology in human IVF: a systematic review of the literature. Human Reproduction Update 17, 34–45.

Robert, C., Gagne, D., Bousquet, D., Barnes, F., Sirard, M.A., 2001. Differential Display and Suppressive Subtractive Hybridization Used to Identify Granulosa Cell Messenger RNA Associated with Bovine Oocyte Developmental Competence. Biology of Reproduction 64, 1812–1820.

Roberts, J.A.F., Greenwood, A.W., 1928. An Extreme Free-Martin and a Free-Martin like codition in the Sheep. Journal of Anatomy 63, 87–94.

Rodgers, R.J., Irving-Rodgers, H.F., 2010. Formation of the Ovarian Follicular Antrum and Follicular Fluid. Biology of Reproduction 82, 1021–1029.

Rong, L., Li, R., Li, S., Luo, R., 2015. Immunosuppression of breast cancer cells mediated by transforming growth factor-β in exosomes from cancer cells. Oncol Lett.

Rota, A., Ballarin, C., Vigier, B., Cozzi, B., Rey, R., 2002. Age dependent changes in plasma anti-Mu€llerian hormone concentrations in the bovine male, female, and freemartin from

123

birth to puberty: relationship betweentestosterone production and influence on sex differentiation. General and Comparative Endocrinology 129, 39–44.

Royal, M., Mann, G.E., Flint, A.P.F., 2000. Strategies for Reversing the Trend Towards Subfertility in Dairy Cattle. The Veterinary Journal 160, 53–60.

Sadeu, J.C., Adriaenssens, T., Smitz, J., 2008. Expression of growth differentiation factor 9, bone morphogenetic protein 15, and anti-Mullerian hormone in cultured mouse primary follicles. Reproduction 136, 195–203.

Salmon, N.A., Handyside, A.H., Joyce, I.M., 2004a. Expression ofSox8, Sf1, Gata4, Wt1, Dax1, andFog2 in the mouse ovarian follicle: Implications for the regulation ofAmh expression. Mol. Reprod. Dev. 70, 271–277.

Salmon, N.A., Handyside, A.H., Joyce, I.M., 2004b. Oocyte regulation of anti-Müllerian hormone expression in granulosa cells during ovarian follicle development in mice. Developmental Biology 266, 201–208.

Sandvig, K., Llorente, A., 2012. Proteomic Analysis of Microvesicles Released by the Human Prostate Cancer Cell Line PC-3. Molecular & Cellular Proteomics 11, M111.012914– M111.012914.

Sartori, R., Barros, C.M., 2011. Animal Reproduction Science. Animal Reproduction Science 124, 244–250.

Scheetz, D., Folger, J.K., Smith, G.W., Ireland, J.J., 2012. Granulosa cells are refractory to FSH action in individuals with a low antral follicle count. Reprod. Fertil. Dev. 24, 327.

Silberstein, T., 2005. Mullerian inhibiting substance levels at the time of HCG administration in IVF cycles predict both ovarian reserve and embryo morphology. Human Reproduction 21, 159–163.

Silva-Santos, K.C., Santos, G.M.G., Siloto, L.S., Hertel, M.F., Andrade, E.R., Rubin, M.I.B., Sturion, L., Melo-Sterza, F.A., Seneda, M.M., 2011. Estimate of the population of preantral follicles in the ovaries of. THE 76, 1051–1057.

Sinclair, K.D., 2008. Amino acid and fatty acid composition of follicular fluid as predictors of in-vitro embryo development. RBM Online 16, 859–868.

Sirard, M.A., 2001. Resumption of meiosis: mechanism involved in meiotic progression and its relation with developmental competence. Theriogenology 55, 1241–1254.

Sonigo, C., Simon, C., Boubaya, M., Benoit, A., Sifer, C., Sermondade, N., Grynberg, M., 2016. What threshold values of antral follicle count and serum AMH levels should be considered for oocyte cryopreservation after in vitromaturation? Human Reproduction dew102.

124

Souter, V.L., Kapur, R.P., Nyholt, D.R., Skogerboe, K., Myerson, D., Ton, C.C., Opheim, K.E., Easterling, T.R., Shields, L.E., Monthomery, G.W., Glass, I.A., 2003. A Report of Dizygous Monochorionic Twins. The New England Journal of Medicine 349, 1–5.

Souter, V.L., Parisi, M.A., Nyholt, D.R., Kapur, R.P., Henders, A.K., Opheim, K.E., Gunther, D.F., Mitchell, M.E., Glass, I.A., Montgomery, G.W., 2006. A case of true hermaphroditism reveals an unusual mechanism of twinning. Hum Genet 121, 179–185.

Spencer, T.E., 2013. Early pregnancy: Concepts, challenges, and potential solutions. Animal Frontiers 3, 48–55.

Stephen, A.E., Pearsall, L.A., Christian, B.P., Danahoe, P.K., Vacanti, J.P., MacLaughlin, D.T., 2002. Highly Purified Mullerian Inhibiting Substance Inhibits Human Ovarian Cancer. Clinical Cancer Research 8, 2640–2646.

Stojkovic, M., Machado, S.A., Stojkovic, P., Zakhartchenko, V., Hutzler, P., Goncalves, P.B., Wolf, E., 2001. Mitochondrial Distribution and Adenosine Triphosphate Content of Bovine Oocytes Before and After In Vitro Maturation: Correlation with Morphological Criteria and Developmental Capacity After In Vitro Fertilization and Culture. Biology of Reproduction 64, 904–909.

Stojsin- Carter, A., Mahboubi, K., Costa, N.N., Gillis, D.J., Carter, T.F., Neal, M.S., Miranda, M.S., Ohashi, O.M., Favetta, L.A., King, W.A., 2016. Animal Reproduction Science. Animal Reproduction Science 1–8.

Stoop, D., Cobo, A., MD, S.S., 2014. Fertility preservation 3Fertility preservation for age-related fertility decline. The Lancet 384, 1311–1319.

Stroud, B., 2005. Bovine Fetal Sexing Using Ultrasound. Proceedings, Applied Reproductive Strategies in Beef Cattle 1–10.

Sunkara, S.K., Rittenberg, V., Raine-Fenning, N., Bhattacharya, S., Zamora, J., Coomarasamy, A., 2011. Association between the number of eggs and live birth in IVF treatment: an analysis of 400 135 treatment cycles. Human Reproduction 26, 1768–1774.

Swain, J.E., Lai, D., Takayama, S., Smith, G.D., 2013. Thinking big by thinking small: application of microfluidic technology to improve ART. Lab Chip 13, 1213.

Takahashi, C., Fujito, A., Kazuka, M., Sugiyama, R., Ito, H., Isaka, K., 2008. Anti-Müllerian hormone substance from follicular fluid is positively associated with success in oocyte fertilization during in vitro fertilization. Fertility and Sterility 89, 586–591.

Tang, B., Vu, M., Booker, T., Santner, S.J., Miller, F.R., Anver, M.R., Wakefield, L.M., 2003. TGF-β switches from tumor suppressor to prometastatic factor in a model of breast cancer progression. J. Clin. Invest. 112, 1116–1124.

125

Teixeira, J., Maheswaran, S., Donehoe, P.K., 2001. Mullerian Inhibiting Substance: An Instructive Developmental Hormone with Diagnostic and Possible Therapeutic Applications. Endocrine Reviews 22, 657–674.

Themmen, A.P.N., 2005. Anti-Mullerian Hormone: Its Role in Follicular Growth Initiation and Survival and as an Ovarian Reserve Marker. Journal of the National Cancer Institute Monographs 2005, 18–21.

Tremellen, K.P., Kolo, M., Gilmore, A., Lekamge, D.N., 2005. Anti-müllerian hormone as a marker of ovarian reserve*. Australian and New Zealand Journal of Obstetrics and Gynaecology 45, 20–24.

Tsafriri, A., Chun, S.-Y., Zhang, R., Hsueh, A., Conti, M., 1996. Oocyte Maturation Involves Compartmentalization and Opposing Changes of cAMP Levels in Follicular Somatic and Germ Cells: Studies Using Selective Phosphodiesterase Inhibitors 178, 393–402. van Loendersloot, L., Repping, S., Bossuyt, P.M.M., van der Veen, F., van Wely, M., 2014. Prediction models in in vitro fertilization; where are we? A mini review. Journal of Advanced Research 5, 295–301.

Vargas, A., Zhou, S., Ethier-Chiasson, M., Flipo, D., Lafond, J., Gilbert, C., Barbeau, B., 2014. Syncytin proteins incorporated in placenta exosomes are important for cell uptake and show variation in abundance in serum exosomes from patients with preeclampsia. The FASEB Journal 28, 3703–3719.

Varghese, A.C., Plessis, du, S.S., Falcone, T., Agarwal, A., 2008. Cryopreservation/transplantation of ovarian tissue and in vitro maturation of follicles and oocytes: Challenges for fertility preservation. Reproductive Biology and Endocrinology 6, 47.

Velde, E.R.T., Pearson, P.L., 2002. The variability of female reproductive ageing. Human Reproduction Update 8, 141–154.

Vigier, B., Tran, D., Legeai, L., Bezard, J., Josso, N., 1984. Origin of anti-Mullerian hormone in bovine freemartin fetuses. Journal of Reproduction and Fertility 70, 473–479.

Villaseca, P., 2004. Bilateral oophorectomy in a pregnant woman: hormonal profile from late gestation to post-partum: Case report. Human Reproduction 20, 397–401.

Visser, J.A., 2003. AMH signaling: from receptor to target gene. Molecular and Cellular Endocrinology 211, 65–73.

Visser, J.A., de Jong, F.H., Laven, J.S.E., Themmen, A.P.N., 2006. Anti-Mullerian hormone: a new marker for ovarian function. Reproduction 131, 1–9.

Visser, J.A., Themmen, A.P.N., 2005. Anti-Müllerian hormone and folliculogenesis. Molecular

126

and Cellular Endocrinology 234, 81–86.

Vulliemoz, N.R., Kurinczuk, J., 2012. In vitro fertilisation: perinatal risks and early childhood outcomes. Human Fertility 15, 62–68.

Walsh, J.M., Segurado, R., Mahony, R.M., Foley, M.E., McAuliffe, F.M., 2015. The Effects of Fetal Gender on Maternal and Fetal Insulin Resistance. PLoS ONE 10, e0137215.

Wang, J., Dicken, C., Lustbader, J.W., Tortoriello, D.V., 2009. Evidence for a Mullerian- inhibitng substance autocrine/paracrine system in adult human endometrium. Fertility and Sterility 91, 1195–1203.

Watanabe, K., Clarke, T.R., Lane, A.H., Wang, X., Donahoe, P.K., 2000. Endogenous expression of Mullerian inhibiting substance in early postnatal rat Sertoli cells requires multiple steroidogenic factor-1and GATA-4-binding sites. PNAS 97, 1624–1629.

Webb, R., Bains, H., Cruttwell, C., Carroll, J., 2002. Gap-junctional communication in mouse cumulus-oocyte complexes: implications for the mechanism of meiotic maturation. Reproduction 123, 41–52.

Webb, R., Garnsworthy, P.C., Gong, J.-G., Armstrong, D.G., 2004. Control of follicular growth: Local interactions and nutritional influences. Journal of Animal Science 82, E63-E74.

Webb, R., Garnsworthy, P.C., Campbell, B.K., Hunter, M.G., 2007. Intra-ovarian regulation of follicular development and oocyte competence in farm animals. Theriogenology 68, S22– S29.

Westergaard, L., 1985. Follicular stresia in relation to oocyte morphology in non-pregnant and pregnant women. Journal of Reproduction and Fertility 74, 113–118.

Wilson, C.A., di Clemente, N., Ehrenfels, C., Pepinsky, R.B., Josso, N., Vigier, B., Cate, R.L., 1993. Mullerian Inhibiting SubstanceRequires Its N-Terminal Domain for Maintenance of Biological Activity, a Novel Finding within theTransforming Growth Factor-beta Superfamily. Molecular Endocrinology 7, 247–257.

Wittmann, W., McLennan, I.S., 2011. The Male Bias in the Number of Purkinje Cells and the Size of the Murine Cerebellum may Require Müllerian Inhibiting Substance/Anti-Müllerian Hormone. Journal of Neuroendocrinology 23, 831–838.

Wittmann, W., McLennan, I.S., 2013. Anti-Mullerian hormone may regulate the number of calbindin-positive neurons in the sexually dimorphic nucleus of the preoptic area of male mice. Biology of Sex Differences 4, 1–1.

Woodruff, T.K., Shea, L.D., 2010. A new hypothesis regarding ovarian follicle development: ovarian rigidity as a regulator of selection and health. Journal of Assisted Reproduction and Genetics 28, 3–6.

127

World Health Organization, 2011. WORLD REPORT ON DISABILITY 1–24.

Wunder, D.M., Guibourdenche, J., Birkhäuser, M.H., Bersinger, N.A., 2008. Anti-Müllerian hormone and inhibin B as predictors of pregnancy after treatment by in vitro fertilization/intracytoplasmic sperm injection. Fertility and Sterility 90, 2203–2210.

Xiao, S., Zhang, J., Romero, M.M., Smith, K.N., Shea, L.D., Woodruff, T.K., 2015. follicle growth supports human oocyte meiotic maturation. Nature Publishing Group 1–5.

Xu, J., Bishop, C.V., Lawson, M.S., Park, B.S., Xu, F., 2016. Anti-Müllerian hormone promotes pre-antral follicle growth, but inhibits antral follicle maturation and dominant follicle selection in primates. Human Reproduction dew100.

Zegers-Hochschild, F., Adamson, G.D., de Mouzon, J., Ishihara, O., Mansour, R., Nygren, K., Sullivan, E., van der Poel, S., on behalf of ICMART and WHO, 2009. The International Committee for Monitoring Assisted Reproductive Technology (ICMART) and the World Health Organization (WHO) Revised Glossary on ART Terminology, 2009. Human Reproduction 24, 2683–2687.

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APPENDIX

Appendix I: Data from Chapter II, study group 1

Plasma AMH (Pl AMH) values (pg/ml), y-axis, measured using Ansh ELISA kit in cows Bos taurus indicus during gestation at 4 time points, x-axis, day of artificial insemination (day 0), day 35, day 135, day 275 and approximately one month after calving (last point). Red lines represent samples taken from animals carrying female calf (n=3) while blue lines represent animals carrying male calf (n=5), verified by ultrasound and confirmed at birth. A) Raw data of Pl AMH in pregnant cows. B) Change in Pl AMH (Δ) between time points. C) Relative change in Pl AMH in terms of its previous value, example: Δ Pl AMH (day x - day y) / Pl AMH (day y).

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Appendix II: The consent form

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Appendix III: Monofollicular sample collection instructions

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Appendix IV: Protocol for the monofollicular oocyte collection

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Appendix V: Modified Cycle Sheet

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