Low Levels of Genetic Divergence across Geographically and Linguistically Diverse Populations from India

Rosenberg, Noah A.; Mahajan, Saurabh; González-Quevedo, Catalina; Blum, Michaël G. B.; Nino-Rosales, Laura; Ninis, Vasiliki; Das, Parimal; Hegde, Madhuri; Molinari, Laura; Zapata, Gladys; Weber, James L.; Belmont, John W.; Patel, Pragna I.

doi:10.1371/journal.pgen.0020215

Cited by 85 publications

(123 citation statements)

References 48 publications

(52 reference statements)

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“…The extreme underestimation of African genetic diversity and the high differentiation between African and Eurasian populations do not make them suitable for inferences on past human demography at a large geographic scale. This set of markers has not been widely used so far and then only in conjunction with STRs Rosenberg et al, 2006;Friedlaender et al, 2008). Because of their far lower information content compared to STRs (information content is proportional to polymorphism in most population genetics analyses), they probably only contributed marginally in the conclusions reached.…”

Section: Strong Bias On Indelsmentioning

confidence: 99%

How accurate is the current picture of human genetic variation?

et al. 2008

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Our understanding of the distribution of worldwide human genomic diversity has greatly increased over recent years thanks to the availability of large data sets derived from short tandem repeats (STRs), insertion deletion polymorphisms (indels) and single nucleotide polymorphisms (SNPs). A concern, however, is that the current picture of worldwide human genomic diversity may be inaccurate because of biases in the selection process of genetic markers (so-called 'ascertainment bias'). To evaluate this problem, we first compared the distribution of genomic diversity between these three types of genetic markers in the populations from the HGDP-CEPH panel for evidence of bias or incongruities. In a second step, using a very relaxed set of criteria to prevent the intrusion of bias, we developed a new set of unbiased STR markers and compared the results against those from available panels. Contrarily to recent claims, our results show that the STR markers suffer from no discernible bias, and can thus be used as a baseline reference for human genetic diversity and population differentiation. The bias on SNPs is moderate compared to that on the set of indels analysed, which we recommend should be avoided for work describing the distribution of human genetic diversity or making inference on human settlement history.

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Section: Strong Bias On Indelsmentioning

confidence: 99%

How accurate is the current picture of human genetic variation?

et al. 2008

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“…A later analysis of genetic polymorphisms and language boundaries suggested a causal role for language in restricting gene flow in Europe (5). More recently, populationlevel genetic data have been compared with patterns expected from language family classifications (2,(6)(7)(8)(9)(10)(11)(12). Other studies addressed whether the serial founder effect model from genetics-human expansion from an origin in Africa, followed by serial contractions in effective population size during the peopling of the world (13,14)-explains various linguistic patterns (15)(16)(17)(18)(19).…”

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confidence: 99%

A comparison of worldwide phonemic and genetic variation in human populations

Creanza¹,

Ruhlen

Pemberton

et al. 2015

Proc. Natl. Acad. Sci. U.S.A.

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Worldwide patterns of genetic variation are driven by human demographic history. Here, we test whether this demographic history has left similar signatures on phonemes-sound units that distinguish meaning between words in languages-to those it has left on genes. We analyze, jointly and in parallel, phoneme inventories from 2,082 worldwide languages and microsatellite polymorphisms from 246 worldwide populations. On a global scale, both genetic distance and phonemic distance between populations are significantly correlated with geographic distance. Geographically close language pairs share significantly more phonemes than distant language pairs, whether or not the languages are closely related. The regional geographic axes of greatest phonemic differentiation correspond to axes of genetic differentiation, suggesting that there is a relationship between human dispersal and linguistic variation. However, the geographic distribution of phoneme inventory sizes does not follow the predictions of a serial founder effect during human expansion out of Africa. Furthermore, although geographically isolated populations lose genetic diversity via genetic drift, phonemes are not subject to drift in the same way: within a given geographic radius, languages that are relatively isolated exhibit more variance in number of phonemes than languages with many neighbors. This finding suggests that relatively isolated languages are more susceptible to phonemic change than languages with many neighbors. Within a language family, phoneme evolution along genetic, geographic, or cognate-based linguistic trees predicts similar ancestral phoneme states to those predicted from ancient sources. More genetic sampling could further elucidate the relative roles of vertical and horizontal transmission in phoneme evolution. cultural evolution | human migration | languages | population genetics

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“…A study by Rosenberg, et al 40 stated that false-positives due to genetic heterogeneity in diverse Indian population could be smaller than expected. Still, we made considerable efforts to avoid population stratification by recruiting subjects in both the phases with great caution with regards to their ethnicity and geographical regions, forming a homogenous cluster as reported by the Indian Genome Variation Consortium.…”

Section: Resultsmentioning

confidence: 92%