Inferring patterns of folktale diffusion using genomic data - PubMed (original) (raw)

. 2017 Aug 22;114(34):9140-9145.

doi: 10.1073/pnas.1614395114. Epub 2017 Aug 7.

Eugenio Bortolini 1 2 3, Enrico R Crema 6, Stefania Sarno 3, Chiara Barbieri 7, Alessio Boattini 3, Marco Sazzini 3, Sara Graça da Silva 8, Gessica Martini 9, Mait Metspalu 4, Davide Pettener 3, Donata Luiselli 3, Jamshid J Tehrani 10

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Inferring patterns of folktale diffusion using genomic data

Eugenio Bortolini et al. Proc Natl Acad Sci U S A. 2017.

Abstract

Observable patterns of cultural variation are consistently intertwined with demic movements, cultural diffusion, and adaptation to different ecological contexts [Cavalli-Sforza and Feldman (1981) Cultural Transmission and Evolution: A Quantitative Approach; Boyd and Richerson (1985) _Culture and the Evolutionary Process_]. The quantitative study of gene-culture coevolution has focused in particular on the mechanisms responsible for change in frequency and attributes of cultural traits, the spread of cultural information through demic and cultural diffusion, and detecting relationships between genetic and cultural lineages. Here, we make use of worldwide whole-genome sequences [Pagani et al. (2016) Nature 538:238-242] to assess the impact of processes involving population movement and replacement on cultural diversity, focusing on the variability observed in folktale traditions (n = 596) [Uther (2004) _The Types of International Folktales: A Classification and Bibliography. Based on the System of Antti Aarne and Stith Thompson_] in Eurasia. We find that a model of cultural diffusion predicted by isolation-by-distance alone is not sufficient to explain the observed patterns, especially at small spatial scales (up to [Formula: see text]4,000 km). We also provide an empirical approach to infer presence and impact of ethnolinguistic barriers preventing the unbiased transmission of both genetic and cultural information. After correcting for the effect of ethnolinguistic boundaries, we show that, of the alternative models that we propose, the one entailing cultural diffusion biased by linguistic differences is the most plausible. Additionally, we identify 15 tales that are more likely to be predominantly transmitted through population movement and replacement and locate putative focal areas for a set of tales that are spread worldwide.

Keywords: Eurasia; cultural diffusion; demic diffusion; folktales; whole-genome sequences.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Fig. 1.

Fig. 1.

(A) Plot of product–moment correlation values between pairwise genetic distance (both whole genome and biased for linguistic barriers) and pairwise geographic distance over cumulative geographic distance. (B) Map showing the spatial distribution of 33 populations in dataset MAIN. Surface colors represent interpolated richness values (i.e., the number of folktales exhibited by each population). Purple indicates higher values, whereas yellow indicates lower numbers. (C) Example of a map with SpaceMix results for genetic and folktale distance both projected on standard geographic coordinates. It is evident how, overall, folktale distribution (F) tends to cluster closer to geographic coordinates (dots), whereas the inferred source and direction of possible genetic admixture (G) are mismatched. For example, Burmese and Yakut exhibit quite segregated folktale assemblages, whereas their putative source of genetic admixture is closer in space. The case of Hungarian is emblematic for its folkloric assemblage rooted in Europe, whereas its putative genetic (and linguistic) source of admixture is located in the Ural region.

Fig. 2.

Fig. 2.

Comparison of the null model of cultural diffusion dictated by IBD (folktale ∼ geographic; light blue) against all alternative models: demic diffusion (folktale ∼ genetic; red), language-biased cultural diffusion (folktaleL ∼ geographic; purple), and language-biased demic diffusion (folktaleL ∼ geneticL; yellow) over cumulative geographic distance. Product–moment correlation coefficients are calculated at each geographic bin (size = 2,000 km), with original distance matrices up to 12,000 km.

Fig. 3.

Fig. 3.

Possible focal area and dispersion pattern for tale ATU313 “The Magic Flight,” one the most popular folktales in this dataset, which may have been additionally spread through population movement and replacement. It is interesting to note how this tale reached locations that are far from its putative origin (such as Japan and southeastern Africa), whereas it was not retained by many populations located in between (gray dots).

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References

    1. Currie TE, Greenhill SJ, Gray RD, Hasegawa T, Mace R. Rise and fall of political complexity in island South-East Asia and the Pacific. Nature. 2010;467:801–804. - PubMed
    1. Mathew S, Perreault C. Behavioural variation in 172 small-scale societies indicates that social learning is the main mode of human adaptation. Proc Biol Sci. 2015;282:20150061. - PMC - PubMed
    1. da Silva S, Tehrani J. Comparative phylogenetic analyses uncover the ancient roots of Indo-European folktales. R Soc Open Sci. 2016;3:150645. - PMC - PubMed
    1. Cavalli-Sforza LL, Feldman MW. Cultural Transmission and Evolution: A Quantitative Approach. Princeton Univ Press; Princeton: 1981. - PubMed
    1. Boyd R, Richerson PJ. Culture and the Evolutionary Process. Univ of Chicago Press; Chicago: 1985.

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