Ariad, D. | Search bioRxiv

bioRxiv2021

Strict adherence to Mendel's First Law across a large sample of human sperm genomes

Mendels Law of Segregation states that the offspring of a diploid, heterozygous parent will inherit either allele with equal probability. While the vast majority of loci adhere to this rule, research in model and non-model organisms has uncovered numerous exceptions whereby "selfish" alleles are disproportionately transmitted to the next generation. Evidence of such "transmission distortion" (TD) in humans remains equivocal in part because scans of human pedigrees have been under-powered to detect small effects. Recently published single-cell sequencing data from individual human sperm (n = 41,189; 969-3,377 cells from each of 25 donors) offer an opportunity to revisit this question with unprecedented statistical power, but require new methods tailored to extremely low-coverage data ([~]0.01 x per cell). To this end, we developed a method, named rhapsodi, that leverages sparse gamete genotype data to phase the diploid genomes of the donor individuals, impute missing gamete genotypes, and discover meiotic recombination breakpoints, benchmarking its performance across a wide range of study designs. After applying rhapsodi to the sperm sequencing data, we then scanned the gametes for evidence of TD. Our results exhibited close concordance with binomial expectations under balanced transmission, in contrast to tenuous signals of TD that were previously reported in pedigree-based studies. Together, our work excludes the existence of even weak TD in this sample, while offering a powerful quantitative framework for testing this and related hypotheses in other cohorts and study systems.

genomics↗

bioRxiv2021

Haplotype-aware inference of human chromosome abnormalities

Extra or missing chromosomes--a phenomenon termed aneuploidy--frequently arises during human meiosis and embryonic mitosis and is the leading cause of pregnancy loss, including in the context of in vitro fertilization (IVF). While meiotic aneuploidies affect all cells and are deleterious, mitotic errors generate mosaicism, which may be compatible with healthy live birth. Large-scale abnormalities such as triploidy and haploidy also contribute to adverse pregnancy outcomes, but remain hidden from standard sequencing-based approaches to preimplantation genetic testing (PGT-A). The ability to reliably distinguish meiotic and mitotic aneuploidies, as well as abnormalities in genome-wide ploidy may thus prove valuable for enhancing IVF outcomes. Here, we describe a statistical method for distinguishing these forms of aneuploidy based on analysis of low-coverage whole-genome sequencing data, which is the current standard in the field. Our approach overcomes the sparse nature of the data by leveraging allele frequencies and linkage disequilibrium (LD) measured in a population reference panel. The method, which we term LD-informed PGT-A (LD-PGTA), retains high accuracy down to coverage as low as 0.05x and at higher coverage can also distinguish between meiosis I and meiosis II errors based on signatures spanning the centromeres. LD-PGTA provides fundamental insight into the origins of human chromosome abnormalities, as well as a practical tool with the potential to improve genetic testing during IVF. Significance StatementWhole chromosome gains and losses--termed aneuploidies--are the leading cause of human pregnancy loss and congenital disorders. Recent work has demonstrated that in addition to harmful meiotic aneuploidies, mitotic aneuploidies (which lead to mosaic embryos harboring cells with different numbers of chromosomes) may also be common in preimplantation embryos but potentially compatible with healthy birth. Here we developed and tested a method for distinguishing these forms of aneuploidy using genetic testing data from 8154 IVF embryos. We re-classified embryos based on signatures of meiotic and mitotic error, while also revealing lethal forms of chromosome abnormality that were hidden to existing approaches. Our method complements standard protocols for preimplantation and prenatal genetic testing, while offering insight into the biology of early development.

genomics↗