A comparison of worldwide phonemic and genetic variation in human populations

Creanza, Nicole; Ruhlen, Merritt; Pemberton, Trevor J.; Rosenberg, Noah A.; Feldman, Marcus W.; Ramachandran, Sohini

doi:10.1073/pnas.1424033112

Cited by 118 publications

(157 citation statements)

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“…This result was not significant (r = 0.06, P = 0.30). Although an association between F st and geographic distance within Africa has been documented (Ramachandran et al 2005;Tishkoff et al 2009;Creanza et al 2015), a Mantel test for the relationship between F st and pairwise geographic distance in our data set was also null (r = 0.021, P = 0.38), reflecting the nonlinear aspect of shared ancestry in southern Africa as seen in Figure 1 and Figure 2.…”

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confidence: 66%

“…Weir and Cockerham genetic distances (F st ) were calculated from allele frequencies estimated with vcftools (Danecek et al 2011). A Jaccard phonemic distance matrix was used as formulated in Creanza et al (2015). Populations included in the analysis were the Nama, 6 ¼Khomani, East Taa, West Taa, Naro, G|ui, G||ana, Shua, Kua, !Xuun, and Khwe.…”

Section: Estimating Effective Migration Surfaces (Eems) Analysismentioning

confidence: 99%

“…The genetic data were compared to a phonemic distance matrix (Jaccard 1908) as well as geographic distances between each population (Table S3). In order to test whether genetic distance (F st ) was associated with geography or language, we performed a partial Mantel test for the relationship between F st and language (Creanza et al 2015) accounting for geographic distance among 11 KhoeSan populations. This result was not significant (r = 0.06, P = 0.30).…”

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confidence: 99%

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Fine-Scale Human Population Structure in Southern Africa Reflects Ecogeographic Boundaries

et al. 2016

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Recent genetic studies have established that the KhoeSan populations of southern Africa are distinct from all other African populations and have remained largely isolated during human prehistory until 2000 years ago. Dozens of different KhoeSan groups exist, belonging to three different language families, but very little is known about their population history. We examine new genomewide polymorphism data and whole mitochondrial genomes for .100 South Africans from the 6 ¼Khomani San and Nama populations of the Northern Cape, analyzed in conjunction with 19 additional southern African populations. Our analyses reveal fine-scale population structure in and around the Kalahari Desert. Surprisingly, this structure does not always correspond to linguistic or subsistence categories as previously suggested, but rather reflects the role of geographic barriers and the ecology of the greater Kalahari Basin. Regardless of subsistence strategy, the indigenous Khoe-speaking Nama pastoralists and the N|u-speaking 6 ¼Khomani (formerly hunter-gatherers) share ancestry with other Khoe-speaking forager populations that form a rim around the Kalahari Desert. We reconstruct earlier migration patterns and estimate that the southern Kalahari populations were among the last to experience gene flow from Bantu speakers, 14 generations ago. We conclude that local adoption of pastoralism, at least by the Nama, appears to have been primarily a cultural process with limited genetic impact from eastern Africa.

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confidence: 66%

Section: Estimating Effective Migration Surfaces (Eems) Analysismentioning

confidence: 99%

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confidence: 99%

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Fine-Scale Human Population Structure in Southern Africa Reflects Ecogeographic Boundaries

et al. 2016

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“…Syntactic parameters are also the only type of data that allows to approach the same task for languages belonging to different language families; indeed, by definition, languages from different families do not share lexical features (common etymologies) and the comparison of phonological features has so far been unable to suggest plausible phylogenies for their apparent lack of sufficient time depth, and for being subject to important secondary contact effects (Longobardi & Guardiano, 2009;Creanza et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

Learning implicational models of universal grammar parameters

Kazakov¹,

Cordoni²,

Algahtani³

et al. 2018

Proceedings of the 12th International Conference on the Evolution of Language (Evolang12)

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The use of parameters in the description of natural language syntax has to balance between the need to discriminate among (sometimes subtly different) languages, which can be seen as a cross-linguistic version of Chomsky's descriptive adequacy (Chomsky, 1964), and the complexity of the acquisition task that a large number of parameters would imply, which is a problem for explanatory adequacy. Here we first present a novel approach in which machine learning is used to detect hidden dependencies in a table of parameters. The result is a dependency graph in which some of the parameters can be fully predicted from others. These findings can be then subjected to linguistic analysis, which may either refute them by providing typological counterexamples of languages not included in the original dataset, dismiss them on theoretical grounds, or uphold them as tentative empirical laws worth of further study. Machine learning is also used to explore the full sets of parameters that are sufficient to distinguish one historically established language family from others. These results provide a new type of empirical evidence about the historical adequacy of parameter theories.

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“…For this reason, as Sapir (2) so eloquently put it, "the history of each is apt to follow a distinctive course." In PNAS, Creanza et al (3) weigh in on this debate and provide a conceptual and methodological framework for future studies of population genetic and linguistic coevolution.…”

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confidence: 99%

Reassessment of global gene–language coevolution

Hunley

2015

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

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A comparison of worldwide phonemic and genetic variation in human populations

Cited by 118 publications

References 57 publications

Fine-Scale Human Population Structure in Southern Africa Reflects Ecogeographic Boundaries

Fine-Scale Human Population Structure in Southern Africa Reflects Ecogeographic Boundaries

Learning implicational models of universal grammar parameters

Reassessment of global gene–language coevolution

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