One size fits all? Direct evidence for the heterogeneity of genetic drift throughout the genome

Abstract

Effective population size (N e ) is a central parameter in population and conservation genetics. It measures the magnitude of genetic drift, rates of accumulation of inbreeding in a population, and it conditions the efficacy of selection. It is often assumed that a single N e can account for the evolution of genomes. However, recent work provides indirect evidence for heterogeneity in N e throughout the genome. We study this by examining genome-wide diversity in the Danish Holstein cattle breed. Using the differences in allele frequencies over a single generation, we directly estimated N e among autosomes and smaller windows within autosomes. We found statistically significant variation in N e at both scales. However, no correlation was found between the detected regional variability in N e , and proxies for the intensity of linked selection (local recombination rate, gene density), or the presence of either past strong selection or current artificial selection on traits of economic value. Our findings call for further caution regarding the wide applicability of the N e concept for understanding quantitatively processes such as genetic drift and accumulation of consanguinity in both natural and managed populations.

Invited review: Inbreeding in the genomics era: Inbreeding, inbreeding depression, and management of genomic variability

“…Hence the variation in the rate of recombination and the density of selected sites is expected to generate variation in Ne (Gossmann et al, 2011). The heterogeneity in livestock is scarce, although Jiménez-Mena et al (2016b) found the Ne to vary considerably across the genome (Ne = 40-250) in a Danish Holstein population. Thus, the accumulation of inbreeding is heterogeneous across the genome, such that certain regions are being inbred at a faster rate than other regions of the genome.…”

Natural selection does not affect the estimates of effective population size based on linkage disequilibrium

“…This negative result was attributed to the assumption of large genomic windows in order to have a large enough number of markers in each of them, or to the fact that the temporal method of estimation of N e was only based on a single-generation interval. 41–42…”

“…36–38 Ignoring the heterogeneity in N e may lead to biased estimates of past demography 39 and, in fact, a heterogeneity of N e across the genome has been found for different eukaryotic species. 40–42…”

Heterogeneity in effective size across the genome: effects on the Inverse Instantaneous Coalescence Rate (IICR) and implications for demographic inference under linked selection

“…For instance, Charlesworth (2009) notes that it is expected that an autosomal locus under positive selection will behave neutrally when s < 1/4N e , where s is the selection intensity at this locus. At the same time it is commonly assumed that selection will itself imply a variation of N e across the genome (Charlesworth, 2009, Gossmann et al, 2011, Jiménez-Mena et al, 2016b. For instance, Gossmann et al (2011) write that "The effective population size is expected to vary across the genome as a consequence of genetic hitchhiking (Smith and Haigh, 1974) and background selection (Charlesworth et al, 1993)".…”

“…Under these explicit or implicit modelling frameworks, genomic regions with limited genetic diversity are thus seen as regions of low N e as a result of selective sweeps (Smith and Haigh, 1974) or background selection (Charlesworth et al, 1993), whereas regions with very high levels of genetic diversity may be seen as regions of large N e and could be explained by balancing selection (Charlesworth, 2009) (see also Hill and Robertson (1966)). Following that rationale, Jiménez-Mena et al (2016b) suggested that different species might thus differ in the statistical distribution of N e across the genome and they presented such distributions for eleven species.…”