Open AccessLearning the properties of adaptive regions with functional data analysis
Author(s) -
Mehreen R. Mughal,
Hillary Koch,
Jing Huang,
Francesca Chiaromonte,
Michael DeGiorgio
Publication year - 2020
Publication title -
plos genetics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.587
H-Index - 233
eISSN - 1553-7404
pISSN - 1553-7390
DOI - 10.1371/journal.pgen.1008896
Subject(s) - biology , selection (genetic algorithm) , natural selection , introgression , evolutionary biology , population , population genetics , divergence (linguistics) , genetics , mutation , range (aeronautics) , artificial intelligence , computer science , gene , linguistics , philosophy , demography , materials science , sociology , composite material
Identifying regions of positive selection in genomic data remains a challenge in population genetics. Most current approaches rely on comparing values of summary statistics calculated in windows. We present an approach termed SURFDAWave , which translates measures of genetic diversity calculated in genomic windows to functional data. By transforming our discrete data points to be outputs of continuous functions defined over genomic space, we are able to learn the features of these functions that signify selection. This enables us to confidently identify complex modes of natural selection, including adaptive introgression. We are also able to predict important selection parameters that are responsible for shaping the inferred selection events. By applying our model to human population-genomic data, we recapitulate previously identified regions of selective sweeps, such as OCA2 in Europeans, and predict that its beneficial mutation reached a frequency of 0.02 before it swept 1,802 generations ago, a time when humans were relatively new to Europe. In addition, we identify BNC2 in Europeans as a target of adaptive introgression, and predict that it harbors a beneficial mutation that arose in an archaic human population that split from modern humans within the hypothesized modern human-Neanderthal divergence range.