Effects of Gestational Nutrition on Post-Natal Fertility in Sheep Peter Smith A thesis submitted for the degree of Doctor of Philosophy at the University of Otago, Dunedin, New Zealand January 2017 ii Abstract Changes to feed availability resulting from global climate change have the potential to exacerbate fertility issues already facing the NZ livestock industry. Appropriate feeding levels during gestation is gaining more attention as a number of studies have illustrated that underfeeding during gestation can have negative impacts on the fertility of female offspring. However, the mechanisms underlying this relationship remain obscure. Therefore, the aims of this study were to firstly establish a model in sheep whereby restricted gestational nutrition influenced fertility of the female offspring. A second aim was to identify potential mechanisms underlying the relationship between restricted gestational nutrition and postnatal fertility. Ewes were provided with either a maintenance diet, or a 0.6 of maintenance diet for the first 55 days of gestation. Thereafter, all ewes were fed ad-lib for the remainder of gestation. Fetuses were collected at days 55 and 75 of gestation to examine fetal ovarian development using stereology, and RNAseq was used to examine gene expression. Steroid profiles were generated from both maternal and fetal (day 75 only) plasma samples. Female offspring were monitored from birth until 19 months of age. From these offspring, the time of onset of puberty was recorded, indicators of fertility (ovulation rate and antral follicle counts) were assessed at 8 and 19 months of age, and key hormone profiles were generated at 19 months of age. Surprisingly, female offspring at 19 months of age, but not 8 months of age, showed increases in key indicators of fertility: ovulation rate (p < 0.05) and antral follicle count (AFC, p < 0.01). Additionally, these animals showed an increase in plasma progesterone concentrations (p < 0.05) indicative of increased embryo survival. Changes to the pattern of FSH secretion (p < 0.05) were also observed. Fetal ovaries exposed to restricted nutrition contained more germ cells at day 75 but not at day 55 of gestation (p < 0.01). RNAseq identified 69 sequences differentially expressed in fetal ovaries at day 55, and 145 sequences at day 75. Fold changes observed at day 75 were less than those observed at day 55. Amongst differentially expressed genes, germ cell specific genes were prominent at both ages. Prominent Gene Ontology categories at both ages were ion transport and protease inhibitors. Pathways identified as affected using IPA analysis included some related to the metabolism of arginine to nitric oxide and citrulline, LXR/RXR and FXR/RXR activation, quantity of germ cells, GADD45 signalling, and acute phase response signalling. i Taken together, the data supports increased indicators of fertility in female offspring whose dams were exposed to restricted nutrition during gestation. The observed differences appear to originate within the ovary. The results are consistent with the concept that it is not the restricted nutrition alone, but the change in nutrition from restricted to ad-lib which may be generating the observed changes in the offspring. Further, the data offers insights into potential mechanisms underlying the phenotype observed with both nitric oxide and protease inhibitors being possible candidates for involvement. The results open new avenues of research to either address current fertility issues in livestock, or to improve livestock fertility through manipulating gestational nutrition. ii Acknowledgments While working with sheep is a joy, it has its challenges: a long estrus cycle, a long gestation, and a long time to reach reproductive maturity. This made the project a busy, three and a bit year adventure. The time spent with animals creates a special bond between researchers and the animals, and therefore the first acknowledgement must go to those animals who sacrificed so much, and were such fun to work with. Aspects of this work such as feeding, fetal collections, and blood sampling required the assistance of many. Additionally, the wide range of techniques used required some patient and knowledgeable teachers, so thanks go to all those who taught and helped: Sara Edwards, Alexia Kauff, Di Sebelin, Shirley Martin, and Michelle French. Specific thanks go to David Handlesman and Rena Desai for their LCMS expertise, Axel Heiser for his Nanostring expertise, Paul Maclean for his bioinformatics expertise, and Peter Johnstone for his expert statistical advice. These last two in particular have had to suffer through numerous questions and animated discussions on the merits and appropriateness of the application of their field to this study. Their time and assistance has been greatly appreciated. Extra special thanks must go to Christy Rand and Laurel Quirke. Christy, the RNAseq guru, blessed with amazing patience, knowledge and skill, who managed to explain and teach the complexities of RNAseq to someone who thought RNAseq was a game played at kid’s birthday parties. Laurel, for her amazing skill with the laparoscope and ultrasound scanner, aspects that were so demanding (particularly follicle counts), yet so critical to the outcome of this project. Combined with her expertise in the lab, and willingness to help and troubleshoot with everything from assays to PCR made her an invaluable contributor. Without these two, this project would not have happened. As Laurel also happens to be my wife, her contribution has extended beyond the lab. I thank her for her patience and her contributions to long whiteboard discussions, planning sessions over a Pinot Gris (or two), and help with editing of this thesis. Long has she suffered the absences from home life, the forgetfulness of everyday things while the brain focused on genes and hormones, the frustrations, and the excited narratives in the good times. We did survive. To my committee members Greg Anderson and Peter Hurst, a thank you for keeping me on track and on time. Peter especially has been a long-time colleague and mentor; his thoughts and inputs have been greatly appreciated. Thanks to AgResearch, (particularly Sara Edwards and iii Ian Sutherland) for seeing the merits of this project (and me?), and saving me from the unemployment line and allowing this study to go forward. To my supervisors, Jo-Ann Stanton and Jenny Juengel, what can I say? I know I have presented you two with some special challenges at times. However, through your knowledge, patience and perseverance you have seen me through, kept me focused, and taught me so much, not just about the science, but also about planning, writing, and philosophy… Okams razor will never be forgotten. Finally, I would like to dedicate this thesis to my late mother and father. They always had faith in my ability, even if I did not. It may have taken 30 years to get around to this, but it is done. I hope I have made you both proud. iv Table of Contents Abstract i Acknowledgments iii Table of Contents v List of Figures x List of Tables xii List of Abbreviations xiv Chapter 1 . Introduction 1 1.1 Fetal ovarian development 2 1.2 Postnatal fertility in the female sheep 10 1.3 Gestational nutrition and postnatal fertility 20 1.4 Overview and aims 24 Chapter 2 . Establishment and Validation of the Animal Model 27 2.1 Introduction 27 2.2 Materials and methods 29 2.2.1 Pre-treatment, selection and mating of animals 30 2.2.2 Body weights and body condition scores 34 2.2.3 Blood sampling 34 2.2.4 Diet calculations 36 2.2.5 Housing and feeding 38 2.2.6 Ultrasound scanning 38 2.2.7 Laparoscopy 38 2.2.8 Euthanasia and fetal sampling 39 2.2.9 Lambing 39 2.2.10 Onset of puberty in female offspring 39 2.2.11 Superovulation of female offspring 40 2.2.12 Statistics 42 2.3 Results 44 2.3.1 Maternal weights during gestation 44 2.3.2 Fetal weights 46 2.3.3 Lambing and postnatal growth 48 2.3.4 Onset of puberty 49 2.3.5 Superovulation of female offspring 49 v 2.3.6 Indicators of fertility: OR and AFC 50 2.4 Discussion 52 Chapter 3 . Measurement of Hormones and Metabolic Factors 57 3.1 Introduction 57 3.2 Materials and methods 59 3.2.1 Theoretical basis of assays used in this study 59 3.2.1.1 Sandwich enzyme-linked immunosorbent assay for the determination of AMH 59 3.2.1.2 Competitive enzyme-linked immunosorbent assay for the determination of testosterone 60 3.2.1.3 Competitive radioimmunoassay for measurement of progesterone and FSH 61 3.2.1.4 Displacement radioimmunoassay for measurement of leptin and LH 61 3.2.2 Assay procedures and indicators of assay performance 63 3.2.3 Analysis of pulsatile secretion of LH 64 3.2.4 Source of assays 65 3.3 Results 67 3.3.1 Optimisation and validation of assays for sheep samples 67 3.3.1.1 Validation procedures 67 3.3.1.2 Maternal leptin 68 3.3.1.3 Maternal testosterone 68 3.3.1.4 Maternal progesterone 68 3.3.1.5 Female offspring AMH 70 3.3.1.6 Female offspring progesterone 70 3.3.1.7 Female offspring FSH 71 3.3.1.8 Female offspring LH 71 3.3.2 Assay results 72 3.3.2.1 Maternal metabolic factors 72 3.3.2.2 Day 75 fetal metabolic factors 74 3.3.2.3 Maternal leptin 75 3.3.2.4 Maternal steroids 76 3.3.2.5 Day 75 fetal steroids 78 3.3.2.6 Female offspring progesterone 78 3.3.2.7 Female offspring LH 80 3.3.2.8 Female offspring FSH 81 3.4 Discussion 83 vi Chapter 4 .