Whole-genome sequence analyses of Western Central African Pygmy hunter-gatherers reveal a complex demographic history and identify candidate genes under positive natural selection

Abstract

African Pygmies practicing a mobile hunter-gatherer lifestyle are phenotypically and genetically diverged from other anatomically modern humans, and they likely experienced strong selective pressures due to their unique lifestyle in the Central African rainforest. To identify genomic targets of adaptation, we sequenced the genomes of four Biaka Pygmies from the Central African Republic and jointly analyzed these data with the genome sequences of three Baka Pygmies from Cameroon and nine Yoruba famers. To account for the complex demographic history of these populations that includes both isolation and gene flow, we fit models using the joint allele frequency spectrum and validated them using independent approaches. Our two best-fit models both suggest ancient divergence between the ancestors of the farmers and Pygmies, 90,000 or 150,000 yr ago. We also find that bidirectional asymmetric gene flow is statistically better supported than a single pulse of unidirectional gene flow from farmers to Pygmies, as previously suggested. We then applied complementary statistics to scan the genome for evidence of selective sweeps and polygenic selection. We found that conventional statistical outlier approaches were biased toward identifying candidates in regions of high mutation or low recombination rate. To avoid this bias, we assigned P-values for candidates using whole-genome simulations incorporating demography and variation in both recombination and mutation rates. We found that genes and gene sets involved in muscle development, bone synthesis, immunity, reproduction, cell signaling and development, and energy metabolism are likely to be targets of positive natural selection in Western African Pygmies or their recent ancestors.

Comparison of Single Genome and Allele Frequency Data Reveals Discordant Demographic Histories

“…We recommend employing other model-based types of demographic inference leveraging either SFS-based or other summary statistics in an ABC framework to test whether important demographic features suggested by PSMC or MSMC plots can be recapitulated using other features in the data. We also recommend, as done in Thornton and Andolfatto (2006) , Freedman et al (2014) , Cahill et al (2016) , Hsieh et al (2016) , and Song et al (2016) , that the PSMC or MSMC plots and TMRCA estimates be used themselves as summary statistics for model comparison, rather than the actual population size estimates. In other words, more complex demographic models can be simulated and tested to see whether they recapitulate the observed whole genome-based trajectories.…”

Tracing the peopling of the world through genomics

“…The characterization of genomes from individuals who lived in Africa more than 10 kyr ago is challenging because the environment of the samples from which DNA is extracted, including the local climatic conditions, is not favourable to the preservation of genetic material. However, the statistical analysis of whole-genome sequencing data from geographically diverse hunter-gatherer populations provides evidence of archaic human lineages that have undergone introgression (the exchange of genetic material through interbreeding) and that diverged from modern human lineages as long ago as 1.2 Myr or 1.3 Myr 25,27,28 or as recently as 35 kyr ago 26 . The degree of archaic admixture in Africa therefore remains controversial, and many ongoing efforts are aiming to resolve this question.…”

A Genomic Perspective on the Generation and Maintenance of Genetic Diversity in Herbivorous Insects

“…Robust, carefully-parameterized simulations may help further establish predicted genome-wide patterns of divergence under probable demographic scenarios, clarify the relative importance of divergent selection and other processes in generating observed patterns of divergence between host races in nature, and more accurately pinpoint genomic regions showing exceptional divergence due to adaptation (Hsieh et al 2016). …”