An evolutionary perspective on genetic load in small, isolated populations as informed by whole genome resequencing and forward-time simulations

Abstract

Small populations are vulnerable to increased genetic load and drift that can lead to reductions in fitness and adaptive potential. By analyzing 66 individual whole genomes of Montezuma Quail (Cyrtonyx montezumae) from multiple populations, we illustrate how genetic load is dynamic over evolutionary time. We show that Montezuma Quail are evolving like a ring species, where the terminal extant populations from Arizona and Texas have been separated for ~16,500 years. The Texas populations have remained small but stable since the separation, whereas the Arizona population is much larger today but has been contracting for thousands of years. Most deleterious mutations across the genome are young and segregating privately in each population and a greater number of deleterious alleles are present in the larger population. Our data indicate that ancestral load is purged during strong bottlenecks, but the reduced efficiency of selection in small populations means that segregating deleterious mutations are more likely to rise in frequency over time. Forward-time simulations indicate that severe population declines in historically large populations is more detrimental to individual fitness, whereas long-term small populations are more at risk for reduced adaptive potential and population-level fitness. Our study highlights the intimate connections among evolutionary history, historical demography, genetic load, and evolutionary potential in wild populations.

Phased genome assemblies reveal haplotype‐specific genetic load in the critically endangered Chinese Bahaba (Teleostei, Sciaenidae)

“…Following a previous study (Mathur et al, 2022), we also simulated a multiplicative fitness model with parameters inferred from human data, drawing s from a gamma distribution with a shape parameter of 0.186 and a mean of 0.03 (Kim et al, 2017). This skewed distribution was consisted of a large peak of slightly deleterious loci with a long tail of strongly deleterious variants up to s = 0.9.…”

Genetic diversity of lion populations in Kenya: Evaluating past management practices and recommendations for future conservation actions

“…While, the Nairobi NP population resides in a small NP (~117 km 2 ), sections of the park bordering urban areas are fenced but movement along the unfenced southern boundary is restricted by human settlements (Lesilau et al, 2021). Mathur et al, 2023).…”

The integration of whole‐genome resequencing and ecological niche modelling to conserve profiles of local adaptation

“…For economic reasons, WGR approaches are often conducted at low coverage in non-model species, and in this review, we refer primarily to such low-coverage WGR datasets. With the development of novel bioinformatics tools, falling prices for DNA sequencing, and enhanced computing infrastructure, large WGR projects are now feasible even in species with genomes >1 Gb (e.g., Andrews et al, 2023;Mathur, Mason, et al, 2023;Mathur, Tomeček, et al, 2023). Lou et al (2021) showed that the sequencing price of low-coverage WGR projects is comparable with that of reduced representation sequencing studies (RRS; e.g., genotyping-by-sequencing and restriction size-associated DNA sequencing).…”

“…Year Number of published articles ENM RRS WGR genomic regions (Lou et al, 2021;Lowry et al, 2017). For example, Mathur, Mason, et al (2023) and Mathur, Tomeček, et al (2023) have used WGR data to quantify both genetic load (the burden of deleterious alleles) or genetic thrust (the benefit of adaptive alleles) by leveraging annotations of protein-coding genes and their biochemical properties to categorize alleles into function bins that can be compared across populations. Annotated reference genomes and WGR datasets can be leveraged to identify genomic regions containing elevated (or reduced) variation that are indicative of strong selection (Hohenlohe et al, 2021).…”