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The genetic basis of small stature in African Pygmies

The genetic basis of small stature in African Pygmies

Martin Sikora (ORCID: )
  • Grant DOI 10.55776/J3375
  • Funding program Erwin Schrödinger
  • Status ended
  • Start January 1, 2013
  • End February 28, 2014
  • Funding amount € 78,507

Disciplines

Biology (100%)

Keywords

    Genomics, Population genetics, Pygmies, Natural selection, Height, Demographic history

Abstract Final report

The Pygmy populations of Central Africa are some of the last remaining hunter-gatherers among present-day human populations. Compared to their neighboring populations of predominantly Bantu origin, Pygmy populations show distinct cultural and physical characteristics, most notably short stature, often referred to as the "Pygmy phenotype". Given their distinct physical characteristics, the questions of their demographic history and the origin of the Pygmy phenotype have attracted much attention. Previous genetic studies have shown an ancient divergence (around 60,000 years ago) of the ancestors of modern-day Pygmies from non-Pygmies. However, these studies were generally based on a relatively small set of markers, precluding an accurate estimation of demographic parameters. Furthermore, to date there is still little known about the genetic basis of the small stature phenotype of Pygmy populations. In order to address these questions, we will analyze whole genome sequence data from 40 individuals of two neighboring populations from Cameroon, Western Central Africa: The Baka, a Pygmy hunter-gatherer population from to the Western subgroup of the African Pygmies; as well as the Nzebi, a neighboring non-Pygmy agriculturist population from the Bantu ethnolinguistic group. We will use recently developed computational methods to infer the demographic history of the studied populations from whole genome sequencing data and produce accurate estimates of the associated demographic parameters. Following the demographic inference, we will perform a scan for population-specific adaptations in order to identify candidate regions putatively evolving under positive selection in the studied populations. For this analysis we will use the best-fit demographic model inferred beforehand as a realistic null model of neutral evolution in those populations. Finally, we will perform an in-depth analysis of the identified candidate regions, in order to identify causal alleles implicated in the small stature Pygmy phenotype. We will employ functional annotation algorithms such as PolyPhen and GERP++ to identify variants with potential functional consequences within those candidate regions. The results of the proposed study will allow us to elucidate the evolutionary history of these populations with unprecedented detail, and will shed light on a classical problem of human genetics, the genetic basis for the small stature of the Pygmy people.

The Pygmy populations of Central Africa are some of the last remaining hunter-gatherers among present-day human populations. Compared to their neighboring populations, Pygmies show distinct cultural and physical characteristics, most notably short stature. Given their distinct physical characteristics, the questions of their demographic history and the genetic basis of their short stature have attracted much scientific attention. In order to address these questions, we analyzed the genomes of 47 individuals from two Pygmy and one non-Pygmy populations.Our results show a strong overall differentiation of Pygmies in genomic regions associated with height in previous genetic studies. This suggests that the genetic basis of their small stature is likely due to the combined effect of multiple genes rather than a single gene with a large effect. Furthermore, we could also identify some new candidate genes potentially involved in this combined effect. Finally, our reconstruction of the population history of Pygmies from the genetic data confirms a previously suggested model of genetic isolation combined with very recent gene flow from non-Pygmy populations starting around 20 generations ago.

Research institution(s)
  • University of Stanford - 100%

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