The deleterious mutation load is insensitive to recent population history

Abstract

Human populations have undergone dramatic changes in population size in the past 100,000 years, including recent rapid growth. How these demographic events have affected the burden of deleterious mutations in individuals and the frequencies of disease mutations in populations remains unclear. We use population genetic models to show that recent human demography has likely had little impact on the average burden of deleterious mutations. This prediction is supported by two exome sequence datasets showing that individuals of west African and European ancestry carry very similar burdens of damaging mutations. We further show that for many diseases, rare alleles are unlikely to contribute a large fraction of the heritable variation, and therefore the impact of recent growth is likely to be modest. However, for those diseases that have a direct impact on fitness, strongly deleterious rare mutations likely do play an important role, and recent growth will have increased their impact.

A model of compound heterozygous, loss-of-function alleles is broadly consistent with observations from complex-disease GWAS datasets

“…However, we show here that different models of gene action are qualitatively different with respect to the partitioning of genetic variance across the allele frequency spectrum. We also show that these conclusions hold under the more complex demographic models that have been proposed for human populations [21,40].…”

“…Further, the variance explained at any given frequency threshold increases asymptotically to unity as a function of increasing λ (S4 Fig). While the total heritability of a trait in the population is generally insensitive to population size changes (S1 Fig, see also [21,22,46]), rapid population growth increases the fraction of additive genetic variation due to rare alleles (Fig 1).…”

“…In addition we calculate the same distribution for dominance effects (V D;q x )/(V G ) using the orthogonal model of [27]. Methods based on summing effect sizes [29] or the site frequency spectrum [21] would not apply to the GBR model, because the effect of a variant is not independent of other variants (e.g., there is intralocus epistasis). Therefore, we resort to a regression-based approach, where we regress the genotypes of the population onto the total genetic value as defined in our disease trait models (see Material and Methods).…”

“…A complementary approach is to estimate the heritability explained by genotyped (and imputed) markers (SNPs) under different population sampling schemes [14,15]. Stratifying markers by minor allele frequency (MAF) prior to performing SNP-based heritability estimation allows the partitioning of genetic variation across the allele frequency spectrum to be estimated [16], which is an important summary of the genetic architecture of a complex trait [16][17][18][19][20][21][22][23]. This approach has inferred a contribution of rare alleles to genetic variance in both human height and body mass index (BMI) [16], consistent with theoretical work showing that rare alleles will have large effect sizes if fitness effects and trait effects are correlated [18,[20][21][22][23][24][25].…”

Health and population effects of rare gene knockouts in adult humans with related parents

“…The absolute values of the estimates for mutational load may be biased downwards in the population we are studying compared to outbred populations, due to purging of recessive lethal mutations by the long term endogamous marriage structure. We examined the consequences of this structure by using a method previously applied to examine the consequences of population bottlenecks (8)(9)(10). Controlling for other effects by comparing to synonymous mutations, we see a significant but moderate increase in purging of the rhLOF mutational load in our Pakistani heritage population dataset compared to outbred populations from the 1000 Genomes Project, although less than that caused by the historic bottleneck in the Finnish population (FIN in fig.…”