Inferring the Selective History of CNVs Using a Maximum Likelihood Model

Area of Science:

• Genomics
• Evolutionary Biology
• Population Genetics

Background:

• Copy number variations (CNVs) are structural genomic alterations with significant phenotypic effects, implicated in both disease and adaptation.
• Inferring the selective advantage of CNVs is challenging due to their large and variable phenotypic impacts, unlike single-nucleotide variations.
• Understanding CNV evolution requires robust analytical tools to estimate evolutionary parameters.

Purpose of the Study:

• To develop a likelihood-based computational approach, PoMoCNV, for estimating evolutionary parameters of CNVs from population genetics data.
• To investigate the relationship between chromatin accessibility and CNV mutation rates and fitness.
• To validate the PoMoCNV model using experimental data from Caenorhabditis elegans.

Main Methods:

• Developed PoMoCNV, a phylogenetic model incorporating polymorphism data to estimate CNV mutation rates and fitness costs.
• Applied PoMoCNV to analyze genomics data from 40 Caenorhabditis elegans strains across four populations.
• Integrated chromatin accessibility data to interpret inferred CNV evolutionary parameters in open and closed chromatin regions.

Main Results:

• PoMoCNV successfully estimated evolutionary parameters, including mutation rates and fitness effects, for CNVs at genomic loci.
• Analysis revealed distinct mutation rate and fitness landscapes for CNVs in open versus closed chromatin regions.
• The model's reliability was confirmed through its application to mutation-accumulation experiments in C. elegans.

Conclusions:

• PoMoCNV provides a powerful framework for dissecting the evolutionary dynamics of copy number variations.
• Chromatin accessibility is a key factor influencing the evolutionary trajectory of CNVs.
• This approach advances our ability to study the role of CNVs in adaptation and disease.