Tag: denisovan

Demographic history and genetic adaptation in the Himalayan region

Open access Demographic history and genetic adaptation in the Himalayan region inferred from genome-wide SNP genotypes of 49 populations, by Arciero et al. Mol. Biol. Evol (2018), accepted manuscript (msy094).

Abstract (emphasis mine):

We genotyped 738 individuals belonging to 49 populations from Nepal, Bhutan, North India or Tibet at over 500,000 SNPs, and analysed the genotypes in the context of available worldwide population data in order to investigate the demographic history of the region and the genetic adaptations to the harsh environment. The Himalayan populations resembled other South and East Asians, but in addition displayed their own specific

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Two sources of archaic Denisovan ancestry in East Asia, one possibly after the isolation of Native Americans

east-asian-ancestry

Open access paper Analysis of Human Sequence Data Reveals Two Pulses of Archaic Denisovan Admixture, by Sharon L. Browning, Brian L. Browning, Zhou, Tucci, & Akey, Cell (2018).

Summary:

Anatomically modern humans interbred with Neanderthals and with a related archaic population known as Denisovans. Genomes of several Neanderthals and one Denisovan have been sequenced, and these reference genomes have been used to detect introgressed genetic material in present-day human genomes. Segments of introgression also can be detected without use of reference genomes, and doing so can be advantageous for finding introgressed segments that are less closely related to the

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Optimal Migration Routes of Initial Upper Palaeolithic Populations to Eurasia

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Ecological Niche and Least-Cost Path Analyses to Estimate Optimal Migration Routes of Initial Upper Palaeolithic Populations to Eurasia, by Kondo et al. (2018), from The Middle and Upper Paleolithic Archeology of the Levant and Beyond, Replacement of Neanderthals by Modern Humans Series. Chapter downloadable at Academia.edu.

Abstract:

This paper presents a computer-based method to estimate optimal migration routes of early human population groups by a combination of ecological niche analysis and least-cost path analysis. In the proposed method, niche probability is predicted by MaxEnt, an ecological niche model based on the maximum entropy theory. Location of known

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