Genomic Boundaries between Human Populations

Abstract

Different authors disagree on whether human genome variation should be described as continuous or discontinuous; in the latter case, by attributing an individual’s genotype to one genetic cluster, one would also obtain information on the individual’s genome in general. An analysis of 377 microsatellites of the CEPH human diversity panel was interpreted as evidence that most genotypes cluster into one of five distinct groups, approximately corresponding to continents, which were pro- posed by some authors as the major biological subdivisions of humankind. Here we analyse the same dataset by a specific numerical method, designed to detect genomic boundaries, i.e. zones of increased change in maps of genomic variation. We show that statistically significant boundaries can be described between groups of populations, but different clusters are identified, depending on the assumptions of the model. In addition, these clusters do not correspond to the clusters inferred from previous analyses of the same or of other polymorphisms. We conclude that it is indeed possible to cluster genotypes according to geography, but no study so far identified unambiguously anything that can be regarded as a major genetic subdivision of humankind, and hence discontinuous models of human diversity are unsupported by data.

Community-Based Dialogue: Engaging Communities of Color in the United States' Genetics Policy Conversation

“…Researchers have reported using genetic markers to classify individuals into four to six racial or ethnic groups (Barbujani and Belle 2006; Tang et al 2005). Recent research has reported different distributions of gene variants or polymorphisms related to risk for myocardial infarction (Helgadottir et al 2006), prostate cancer (Freedman et al 2006), and pre-term birth (Wang et al 2006) by populations linked to racial and ethnic groups.…”

A test of the influence of continental axes of orientation on patterns of human gene flow

“…For the most extensively studied case, the Neolithic transition in Europe, it has been argued that observed archaeological and genetic data are compatible with a pattern of demic diffusion (Childe, 1925; Clark, 1965; Ammerman and Cavalli-Sforza, 1971; Renfrew, 1973; Ammerman and Cavalli-Sforza, 1984; Dupanloup et al, 2004; Pinhasi et al, 2005). Even for this well-studied example, however, the debate about the relative importance of demic diffusion and cultural diffusion remains unresolved (Fix, 1996; Richards et al, 2000; Barbujani and Bertorelle, 2001; Haak et al, 2005; Barbujani and Chikhi, 2006). Rather than evaluating the evidence for demic diffusion as a general phenomenon, our interest is in testing whether continental axes of orientation affected the rates of gene flow among human populations — and by extension, the spread of technologies — conditional on the assumption that ancient technology spread largely by demic diffusion (Fig.…”

Human Genetic Diversity and its History

“…Using a Bayesian MCMC approach, Corander et al (2003) found that more than six groups are needed to represent global human genetic diversity, with evidence for subdivision in South America). Barbujani and Belle (2006) used a method for recognising genetic boundaries in maps of genomic variation (Manni et al, 2004), finding evidence for several distinct clusters in the Americas, and for three clusters separated by zones of rapid genomic change in Africa, a result consistent with extensive diversity known to exist in that continent (Kaessmann et al, 1999;Yu et al, 2003;Watkins et al, 2003). Evidence for substructuring in Africa had also been detected by STRUCTURE in one analysis where the inferred clusters were four .…”

“…The exceptions, namely zones of rapid genetic change or genetic boundaries, point to migrational or reproductive barriers. In the few studies so far attempting to map them at the DNA level, genetic boundaries have been shown to occur mostly between small genetic isolates, sometimes separated by just a few kilometres, such as the Suruì and Karitiana populations of Brazil (Barbujani and Belle, 2006). This suggests that, at the small geographical scale, chance and possibly adaptation to local conditions may lead to even sharp population differentiation, thus causing local departures from the general clinal pattern.…”