A genome-wide association study of human transmission distortion
Approved Research ID: 64662
Approval date: September 16th 2020
During reproduction, a parent passes on a single copy of a given gene: either a copy from their mother, or a copy from their father. However, what are referred to as "selfish" genetic elements can stack the deck in their favor, increasing odds of being passed on. While selfish genetic elements are described for a variety of organisms, their evidence in humans has been inconclusive. We aim to test for the presence of such non-randomly inherited genetic elements in the human genome, particularly with respect to variation predisposing a parent to having boys versus girls. Researching such "selfish" elements can inform us of the role genes play with regard to difficulty conceiving, sterility, miscarriage, and developmental disorders.
There are multiple examples in animal systems demonstrating how the inheritance of sex can be biased from the expected 1:1 ratio. One mechanism leading to sex ratio bias can be unequal transmission of sex-determining chromosomes. For example, a man who produces more mature sperm bearing Y chromosomes than X chromosomes would present as a bias toward having sons. Alternatively, sex ratios could be biased due to differences in the survival (or viability) or male or female embryos. A mother passing on an X chromosome mutation that makes it less likely for male embryos to implant or survive through pregnancy, for example, would manifest as a bias toward having daughters. One specific case of reduced viability, the "Mother's Curse" hypothesis, predicts an accumulation of mitochondrial mutations that only are harmful to males.
We will test for the above biased transmission mechanisms, leveraging the sample size within the UKBiobank. By investigating genetic factors related to biased sex ratios, this project aims to shed light on heritable factors related to sex-specific developmental disorders or sterility. This project should be completed within two years from the date of data acquisition.