Statistical evaluation of alternative models of human evolution

Abstract

An appropriate model of recent human evolution is not only important to understand our own history, but it is necessary to disentangle the effects of demography and selection on genome diversity. Although most genetic data support the view that our species originated recently in Africa, it is still unclear if it completely replaced former members of the Homo genus, or if some interbreeding occurred during its range expansion. Several scenarios of modern human evolution have been proposed on the basis of molecular and paleontological data, but their likelihood has never been statistically assessed. Using DNA data from 50 nuclear loci sequenced in African, Asian and Native American samples, we show here by extensive simulations that a simple African replacement model with exponential growth has a higher probability (78%) as compared with alternative multiregional evolution or assimilation scenarios. A Bayesian analysis of the data under this best supported model points to an origin of our species Ϸ141 thousand years ago (Kya), an exit out-of-Africa Ϸ51 Kya, and a recent colonization of the Americas Ϸ10.5 Kya. We also find that the African replacement model explains not only the shallow ancestry of mtDNA or Y-chromosomes but also the occurrence of deep lineages at some autosomal loci, which has been formerly interpreted as a sign of interbreeding with Homo erectus.Bayesian analysis ͉ DNA nuclear data ͉ multiregional hypothesis ͉ out of Africa hypothesis

Effects of Linked Selective Sweeps on Demographic Inference and Model Selection

“…Under our constant population size model, a recent selective sweep with s = 0.05 has a marked effect on genetic polymorphism at the site of the sweep ( Figure 1A Exponential growth is often used to model recent population expansions in lieu of instantaneous population size change, and indeed such growth appears to be a key feature of human population history (Fagundes et al 2007;Gravel et al 2011;Tennessen et al 2012). We therefore examined a model based on the same parameterization of strong growth from Gravel et al (2011)'s estimated European model but omitting the population contractions and most ancient expansion ( Figure 1C).…”

“…Finally, we examined a three-epoch model with a population contraction and then subsequent exponential growth. Currently, this contractionthen-growth model is used to represent non-African human population size histories (e.g., Fagundes et al 2007;Gutenkunst et al 2009;Gravel et al 2011;Tennessen et al 2012). Our parameterization shown in Figure 1D is a simplified version of the European model from Gravel et al (2011).…”

“…In particular, genomescale variation data allows for inference of demographic factors such as population size changes, the timing and ordering of population splits, migration rates between populations, and the founding of admixed populations (Pool et al 2010;Pickrell and Pritchard 2012;Sousa and Hey 2013). Such efforts can refine our picture of demographic events inferred from the archaeological record (e.g., Fagundes et al 2007;Goebel et al 2008), or reveal such events in species where no archaeological data are available, and can aid conservation efforts by complementing census data (e.g., Hájková et al 2007;Garrick et al 2015).Population genomic data sets are well suited for this task simply because demographic changes leave their mark on patterns of genetic variation. Recent population growth, for example, will result in an excess of rare variation compared to equilibrium expectations (Fu 1997), while population contraction will result in an excess of intermediate frequency alleles (Maruyama and Fuerst 1985).…”

“…In addition, C and D of Figure S8 suggest that the extent of exponential growth during the recovery phase is underestimated when very recent sweeps have occurred. Thus, we find that positive selection can dramatically skew population size histories deduced by PSMC.Positive selection produces spurious support for nonequilibrium demographic historiesDemographic inference methods are often used not only to infer parameters of a model, but increasingly to select the best fitting among several competing models (e.g., Adams and Hudson 2004;Fagundes et al 2007;Duchen et al 2013).To ask whether positive selection might affect the outcome of demographic model selection, we simulated genomes with constant population size, again sampling loci for which some fraction, f, is located within c/s # 1 of a selective sweep. We then performed model selection among our four demographic histories ( Figure 1) using both @a@i and ABC (Methods).…”

“…For each model, the selection coefficient, s, for each sweep was set to 0.05, and selection was modeled as a "hard" sweep involving the single origin of an advantageous mutation going to fixation (Methods). In Figure 1, we show the mean values of these two statistics at increasing distances from a selective sweep (where distance is measured by the total crossover rate, c, over s) under each of the four demographic models examined.Under our constant population size model, a recent selective sweep with s = 0.05 has a marked effect on genetic polymorphism at the site of the sweep ( Figure 1A Exponential growth is often used to model recent population expansions in lieu of instantaneous population size change, and indeed such growth appears to be a key feature of human population history (Fagundes et al 2007;Gravel et al 2011;Tennessen et al 2012). We therefore examined a model based on the same parameterization of strong growth from Gravel et al (2011)'s estimated European model but omitting the population contractions and most ancient expansion ( Figure 1C).…”