Inferring the selective history of CNVs using a maximum likelihood model

Abstract

Copy number variations (CNVs) - structural variations generated by deletion and/or duplication that result in change in DNA dosage - are prevalent in nature. CNVs can drastically affect the phenotype of an organism and have been shown to be both involved in genetic disorders and be used as raw material in adaptive evolution. Unlike single-nucleotide variations, the often large and varied effects of CNVs on phenotype hinders our ability to infer their selective advantage based on the population genetics data. Here, we present a likelihood-based approach, dubbed PoMoCNV, that estimates the evolutionary parameters of CNVs based on population genetics data. As a case study, we analyze the genomics data of 40 strains of Caenorhabditis elegans, representing four different populations. We take advantage of the data on chromatin accessibility to interpret the evolutionary parameters of CNVs inferred by PoMoCNV. We further test the reliability of PoMoCNV by estimating the evolutionary parameters of CNVs for mutation-accumulation experiments in C. elegans with varying levels of genetic drift. SignificanceInferring the evolutionary parameters of copy number variations (CNVs) based on population genetics data is crucial to understand their role in evolution. However, given the diversity in the size and effects of CNVs, such inference poses a challenge. We developed a likelihood-based approach called PoMoCNV to address this issue.