Admixture Correction in the Outgroup-f3 Statistic

Date

2018-05

Authors

Tunga, Nita

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Abstract

Genetic inheritance can be studied within a purely genetic scope. However, this eliminates part of the picture. The field of genetics is often thought of as a natural science with little in common with fields of social science. However, in human genetics and the genetics of the organisms which humans impact, the role of cultural and societal forces cannot be ignored. For instance, lactase is an enzyme used to digest lactose in milk. As such, it is an enzyme whose activity reduces significantly after weaning. Nonetheless, as humans have begun to ingest more dairy products into adulthood, lactase persistence has evolved to enable humans to digest these dairy products. My research involves mathematically representing the genetic similarity of two populations accurately via the f3 statistic. The outgroup-f3 statistic is useful in understanding a population’s genetic history and how genetically related two populations are. It shows how close two populations are compared to a third population that is equally distant genetically from the first two. However, if two populations share a recent genetic interaction with another population, the outgroup-f3 statistic could show those two populations as being closer together than they truly are. This genetic interaction of two or more previously isolated populations interbreeding is referred to as admixture. Admixture skews, or even inhibits, an understanding of those populations’ genetic histories. To avoid this problem, I have attempted to devise a modified version of the outgroup-f3 statistic to ensure an accurate representation of genetic relatedness. For my project, artificial admixture was introduced in six unadmixed human populations. Depending on the relationship between increased contamination and the f3 statistic, we proposed and adjusted solutions for a corrected f3 accordingly. I tested my proposed corrections by applying it to populations that contain individuals with and without recent histories of genetic admixture. After correcting for the proportion of admixture in the population, I compared this corrected outgroup-f3 statistic to the outgroup-f3 value calculated for the original unadmixed population. The goal of this work is to have a corrected statistic that one can apply to two populations, independent of admixture proportions. Ultimately, this will help us to better understand the evolutionary histories of populations. Moreover, a corrected statistic will aid other researchers as they analyse demographic histories further in the past.

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