PT  - JOURNAL ARTICLE
AU  - Simon Gravel
TI  - When is selection effective?
AID  - 10.1101/010934
DP  - 2014 Jan 01
TA  - bioRxiv
PG  - 010934
4099  - http://biorxiv.org/content/early/2014/10/30/010934.short
4100  - http://biorxiv.org/content/early/2014/10/30/010934.full
AB  - Deleterious alleles are more likely to reach high frequency in small populations because of chance fluctuations in allele frequency. This may lead, over time, to reduced average fitness in the population. In that sense, selection is more ‘effective’ in larger populations. Many recent studies have considered whether the different demographic histories across human populations have resulted in differences in the number, distribution, and severity of deleterious variants, leading to an animated debate. This article seeks to clarify some terms of the debate by identifying differences in definitions and assumptions used in these studies and providing an intuitive explanation for the observed similarity in genetic load among populations. The intuition is verified through analytical and numerical calculations. First, even though rare variants contribute to load, they contribute little to load differences across populations. Second, the accumulation of non-recessive load after a bottleneck is slow for the weakly deleterious variants that contribute much of the long-term variation among populations. Whereas a bottleneck increases drift instantly, it affects selection only indirectly, so that fitness differences can keep accumulating long after a bottleneck is over. Third, drift and selection tend to have opposite effects on load differentiation under dominance models. Because of this competition, load differences across populations depend sensitively and intricately on past demographic events and on the distribution of fitness effects. A given bottleneck can lead to increased or decreased load for variants with identical fitness effects, depending on the subsequent population history. Because of this sensitivity, both classical population genetic intuition and detailed simulations are required to understand differences in load across populations.