Sociocultural behavior, sex-biased admixture, and effective population sizes in Central African Pygmies and non-Pygmies.

Sociocultural phenomena, such as exogamy or phylopatry, can largely determine human sex-specific demography. In Central Africa, diverging patterns of sex-specific genetic variation have been observed between mobile hunter-gatherer Pygmies and sedentary agricultural non-Pygmies. However, their sex-specific demography remains largely unknown. Using population genetics and approximate Bayesian computation approaches, we inferred male and female effective population sizes, sex-specific migration, and admixture rates in 23 Central African Pygmy and non-Pygmy populations, genotyped for autosomal, X-linked, Y-linked, and mitochondrial markers. We found much larger effective population sizes and migration rates among non-Pygmy populations than among Pygmies, in agreement with the recent expansions and migrations of non-Pygmies and, conversely, the isolation and stationary demography of Pygmy groups. We found larger effective sizes and migration rates for males than for females for Pygmies, and vice versa for non-Pygmies. Thus, although most Pygmy populations have patrilocal customs, their sex-specific genetic patterns resemble those of matrilocal populations. In fact, our results are consistent with a lower prevalence of polygyny and patrilocality in Pygmies compared with non-Pygmies and a potential female transmission of reproductive success in Pygmies. Finally, Pygmy populations showed variable admixture levels with the non-Pygmies, with often much larger introgression from male than from female lineages. Social discrimination against Pygmies triggering complex movements of spouses in intermarriages can explain these male-biased admixture patterns in a patrilocal context. We show how gender-related sociocultural phenomena can determine highly variable sex-specific demography among populations, and how population genetic approaches contrasting chromosomal types allow inferring detailed human sex-specific demographic history.

The role of GHR and IGF1 genes in the genetic determination of African pygmies' short stature.

African pygmies are at the lower extreme of human variation in adult stature and many evolutionary hypotheses have been proposed to explain this phenotype. We showed in a recent study that the difference in average stature of about 10 cm observed between contemporary pygmies and neighboring non-pygmies has a genetic component. Nevertheless, the genetic basis of African pygmies' short stature remains unknown. Using a candidate-gene approach, we show that intronic polymorphisms in GH receptor (GHR) and insulin-like growth factor 1 (IGF1) genes present outlying values of the genetic distance between Baka pygmies and their non-pygmy Nzimé neighbors. We further show that GHR and IGF1 genes have experienced divergent natural selection pressures between pygmies and non-pygmies throughout evolution. In addition, these SNPs are associated with stature in a sample composed of 60 pygmies and 30 non-pygmies and this association remains significant when correcting for population structure for the GHR locus. We conclude that the GHR and IGF1 genes may have a role in African pygmies' short stature. The use of phenotypically contrasted populations is a promising strategy to identify new variants associated with complex traits in humans.

Indirect evidence for the genetic determination of short stature in African Pygmies.

Central African Pygmy populations are known to be the shortest human populations worldwide. Many evolutionary hypotheses have been proposed to explain this short stature: adaptation to food limitations, climate, forest density, or high mortality rates. However, such hypotheses are difficult to test given the lack of long-term surveys and demographic data. Whether the short stature observed nowadays in African Pygmy populations as compared to their Non-Pygmy neighbors is determined by genetic factors remains widely unknown. Here, we study a uniquely large new anthropometrical dataset comprising more than 1,000 individuals from 10 Central African Pygmy and neighboring Non-Pygmy populations, categorized as such based on cultural criteria rather than height. We show that climate, or forest density may not play a major role in the difference in adult stature between existing Pygmies and Non-Pygmies, without ruling out the hypothesis that such factors played an important evolutionary role in the past. Furthermore, we analyzed the relationship between stature and neutral genetic variation in a subset of 213 individuals and found that the Pygmy individuals' stature was significantly positively correlated with levels of genetic similarity with the Non-Pygmy gene-pool for both men and women. Overall, we show that a Pygmy individual exhibiting a high level of genetic admixture with the neighboring Non-Pygmies is likely to be taller. These results show for the first time that the major morphological difference in stature found between Central African Pygmy and Non-Pygmy populations is likely determined by genetic factors.

Can life history trade-offs explain the evolution of short stature in human pygmies? A response to Migliano et al. (2007).

Walker et al. ["Growth rates and life histories in twenty-two small-scale societies," Am. J. Hum. Biol. 18:295-311 (2006)] used life history theory to develop an innovative explanation for human diversity in stature. Short stature could have been selected for in some human populations as a result of the advantage of an earlier growth cessation and earlier reproduction in a context of high mortality. Migliano et al. ["Life history trade-offs explain the evolution of human pygmies," Proc. Natl. Acad. Sci. USA 104:20,216-20,219 (2007)] recently published an important article that tested this hypothesis to explain short stature in human pygmy populations. However innovative this work may be, we believe that some of the data and results presented are controversial if not questionable. As problematic points we note (1) the use of an arbitrary threshold of height (155 cm) to categorize populations into pygmies and nonpygmies; (2) the use of demographic data from Philippine pygmy groups that have experienced dramatic cultural and environmental changes in the last 20 years, and (3) the use of demographic data concerning African pygmy groups because good systematic data on these groups are not available. Finally, we report here mathematical errors and loopholes in the optimization model developed by Migliano and colleagues. In this paper we suggest alternative trade-offs that can be used to explain Migliano's results on more reliable bases.