IDENTIFICATION OF GENETIC VARIANTS REGULATING FEMALE FERTILITY

During these 3 years I focused my work on genetics of fertile window in women life, contributing to the identification of genetic variants that regulate the onset of first menstruation in females, i.e \u201cage at menarche\u201d, and the end of fertile life in women, i.e. \u201cage of menopause\u201d. GWAS analyses, developed and applied in the last 10 years, provide a powerful approach for the discovery of variants and genes contributing to risk of complex diseases. In general the effect of common variants associated with complex traits highlighted in previous GWAS identified only a small proportion of the predicted genetic variation. My project aimed to define the genetic architecture of age at menarche, age at menopause and some reproduction behaviors, testing the genetic contribution of low-frequency and rare variants with several approaches in order to improve the understanding the genetics of women infertility. Thanks to 1000 Genome project and the possibility to impute our genotyping chip data to 1000G reference panel phase 3 we obtained a new resource that allowed to include also low frequency (1%< Minor allele frequency <5%) and rare variants in GWAS (Minor allele frequency <1%). In fact, from 142,722 variants with frequency <=5% in HapMap Phase 3 Release 2 we moved to 10,123,788 low frequency and rare variants in 1000 Genomes Project Phase 3. In addition it was possible to increase the number of samples analyzed and to replicate significant results in independent group of samples. Therefore we performed meta-analysis with two new important resources: larger sample size and the possibility to study low frequency coding variants for these traits. Thanks to the next generation technologies we whole genome sequenced (WGS) 947 samples from Italian Network Genetic Isolate (INGI): an extremely useful resource in order to build a custom reference panel to infer our genotypes. In comparison with 1000G reference panel, a custom panel using a denser scaffold of known haplotypes building with data of the same population, improves the imputation quality and specifically the low and rare frequency spectrum of variants. Very rare variants typical of our population could be lost with only 1000G reference panel due to the lack of some specific block of haplotypes. The analysis of these sequences also leads to the characterization of deleterious variants and specifically to the identification of knockout human genes in our population. Finally, since anti mullerian hormone (AMH) is a marker of ovarian reserve, I have also examined in depth this trait. We have performed a GWAS on the quantitative trait in INGI fertile women with genotype data imputed to Italian Reference Panel enriched in Italian rare variants and we have conducted an analysis in endometriosis patients. In summary, the first 4 chapters report our GWAS results that were already published on menarche (Lunetta et al., 2015) (Day et al., 2017), on menopause (Day et al., 2015) and on human behaviors correlated to fertility, such as age at first birth (AFB) and number of children ever born (NEB) (Barban et al., 2016). In chapter 5, I describe how Whole Genome Sequenced INGI data was obtained and the analyses on human knockouts. Finally, in the last two chapters the results on AMH in healthy and endometriosis affected women are reported