In human genetics, studying mutations is like trying to find the parts of a warplane that cause it to crash when shot in a dogfight. If we only looked to see where bullet holes were found on returning planes, we’d be ignoring all the places that were so important to the plane that any damage would cause a crash and thus be unable to return. This survivorship bias would thus prevent engineers from including the most essential parts of the plane in their analysis. So, the engineers use the absence of bullet holes in surviving planes to infer which sections of the plane are most important. We plan on using this same principle to help us identify essential segments of DNA on the X and Y chromosomes, with the goal of better understanding sex differences in human disease.
Many diseases are caused or influenced by changes in the DNA inherited from your parents. Although humans share most of their DNA with each other, everyone has a unique combination of nucleotides, the individual letters of DNA, that differ from everyone else. This variation causes people to get different diseases, have different symptoms, and respond differently to treatments. One cause of this variation is biological sex, determined by the makeup of sex chromosomes. Biological females usually have two copies of the X chromosome, whereas biological males usually have one X, one Y. Having different sets of sex chromosomes and different mutations on those chromosomes causes males and females to have different genes and activate them differently too.
To study the genetic causes of sex-biased disease, we plan on using human genomes given with patient permission to the UK BioBank to scan the X and Y chromosomes and calculate how often each nucleotide of DNA is mutated in the population. Much like the example with the warplanes, we will identify essential genes and regulatory regions of DNA that can help explain sex differences in disease by looking for nucleotides with very low mutation rates. Due to the sheer amount of DNA sequences we will be aggregating, combining, and computing, we expect this project to take 2-3 years to complete. Above all, this research will expand our understanding of the genetic causes of sex biases in disease and contribute to better treatments for sex-biased disorders.