Omic characterisation of placental development and phenotype

Abstract

Gene expression is influenced by precise epigenetic mechanisms. In the context of pregnancy proper placental development and pregnancy outcome are dependent upon these mechanisms. These are poorly understood in the placenta and historically have not been investigated. In many biomedical research fields epigenetic modifications such as DNA methylation have been proven to be an effective biomarker. However, this has yet to be shown in the reproduction research field. The overall aim of this thesis was to investigate new epigenetic mechanisms in placental development and to identify novel biomarkers for phenotype prediction. This thesis firstly focuses on sex-biased gene expression in multiple human tissues to identify targets of sexual dimorphism. Secondly, it investigates novel transcripts in the placenta and finally focuses on using DNA methylation as a biomarker. Firstly, the research has identified potential new gene targets and mechanisms which may explain sexual dimorphism in many phenotypic traits and diseases. These results suggest that sex-biased gene expression is dynamic and tissue specific. It also highlights the need to consider sex as a biological variable in biomedical research and to address the lack of female representation in many studies. Secondly, by performing a de novo transcript analysis on the placenta this thesis has identified new non-coding RNAs. These placental transcripts were also found to be specific to the placenta and were differentially expressed across gestation and in preeclampsia compared to uncomplicated pregnancies. This suggests these transcripts may be involved in placental development and may have roles in the pathogenesis of preeclampsia. Identifying novel placenta specific transcripts has uncovered new research opportunities involving the placenta. There are potentially hundreds of other unannotated transcripts in the placenta which may have roles in placental development and may be crucial to a successful pregnancy outcome. Thirdly, using DNA methylation as a biomarker has led to the development of two key prediction models. The first one used the level of methylation at 62 cytosine-phosphate-guanosine (CpG) sites to determine the gestational age of a placenta. This computational tool was also used to identify placental aging in placentas from women with early onset preeclampsia. This tool points to potential mechanisms underpinning placental aging which may have an impact on pregnancy complications. The second prediction tool has identified 84 methylated sites in the methylome of maternal circulating leukocytes which can distinguish five pregnancy outcomes. This tool has potential clinical application to identify women at risk of a pregnancy complication. This would enable clinicians to intervene and potentially prevent or reduce morbidity and mortality for mother and child. In summary, this thesis has focused on sex differences in gene expression and DNA methylation in placental development. It has also shown that DNA methylation has potential as an effective biomarker in the field of reproduction research.