142 research outputs found
THE VARIATION OF GENOME SITES ASSOCIATED WITH SEVERE COVID-19 ACROSS POPULATIONS: THE WORLDWIDE AND NATIONAL PATTERNS
No full textSUMMARY Background The knowledge of clinically relevant markers distribution might become a useful tool in COVID-19 therapy using personalized approach in the lack of unified recommendations for COVID-19 patients management during pandemic. We aimed to identify the frequencies and distribution patterns of rs11385942 and rs657152 polymorphic markers, associated with severe COVID-19, among populations of the world, as well at the national level within Russia. The study was also dedicated to reveal whether population frequencies of both polymorphic markers are associated with COVID-19 cases, recovery and death rates. Methods We genotyped 1883 samples from 91 ethnic populations from Russia and neighboring countries by rs11385942 and rs657152 markers. Local populations which were geographically close and genetically similar were pooled into 28 larger groups. In the similar way we compiled a dataset on the other regions of the globe using genotypes extracted or imputed from the available datasets (32 populations worldwide). The differences in alleles frequencies between groups were estimated and the frequency distribution geographic maps have been constructed. We run the correlation analysis of both markers frequencies in various populations with the COVID-19 epidemiological data on the same populations. Findings The cartographic analysis revealed that distribution of rs11385942 follows the West Eurasian pattern: it is frequent in Europeans, West Asians, and particularly in South Asians but rare or absent in all other parts of the globe. Notably, there is no abrupt changes in frequency across Eurasia but the clinal variation instead. The distribution of rs657152 is more homogeneous. Higher population frequencies of both risk alleles correlated positively with the death rate. For the rs11385942 we can state the tendency only (r=0,13, p=0.65), while for rs657152 the correlation was significantly high (r=0,59, p=0,02). These reasonable correlations were obtained on the Russian dataset, but not on the world dataset. Interpretation Using epidemiological statistics on Russia and neighboring countries we revealed the evident correlation of the risk alleles frequencies with the death rate from COVID-19. The lack of such correlations at the world level should be attributed to the differences in the ways epidemiological data have been counted in different countries. So that, we believe that genetic differences between populations make small but real contribution into the heterogeneity of the pandemic worldwide. New studies on the correlations between COVID-19 recovery/mortality rates and population’s gene pool are urgently needed
Recombination gives a new insight in the effective population size and history of the Old World human populations
No full textChristina J. Adler, Alan Cooper, Clio S. I. Der Sarkissian and Wolfgang Haak are members of the Genographic ConsortiumThe information left by recombination in our genomes can be used to make inferences on our recent evolutionary history. Specifically, the number of past recombination events in a population sample is a function of its effective population size (Ne). We have applied a method, Identifying Recombination in Sequences (IRiS), to detect specific past recombination events in 30 Old World populations to infer their Ne. We have found that sub-Saharan African populations have an Ne that is approximately four times greater than those of non-African populations and that outside of Africa, South Asian populations had the largest Ne. We also observe that the patterns of recombinational diversity of these populations correlate with distance out of Africa if that distance is measured along a path crossing South Arabia. No such correlation is found through a Sinai route, suggesting that anatomically modern humans first left Africa through the Bab-el-Mandeb strait rather than through present Egypt.Marta Melé, Asif Javed, Marc Pybus, Pierre Zalloua, Marc Haber, David Comas, Mihai G. Netea, Oleg Balanovsky, Elena Balanovska, Li Jin, Yajun Yang, R. M. Pitchappan, G. Arunkumar, Laxmi Parida, Francesc Calafell, Jaume Bertranpetit, and the Genographic Consortiu
Parallel evolution of genes and languages in the Caucasus region
No full textWe analyzed 40 single nucleotide polymorphism and 19 short tandem repeat Y-chromosomal markers in a large sample of 1,525 indigenous individuals from 14 populations in the Caucasus and 254 additional individuals representing potential source populations. We also employed a lexicostatistical approach to reconstruct the history of the languages of the North Caucasian family spoken by the Caucasus populations. We found a different major haplogroup to be prevalent in each of four sets of populations that occupy distinct geographic regions and belong to different linguistic branches. The haplogroup frequencies correlated with geography and, even more strongly, with language. Within haplogroups, a number of haplotype clusters were shown to be specific to individual populations and languages. The data suggested a direct origin of Caucasus male lineages from the Near East, followed by high levels of isolation, differentiation, and genetic drift in situ. Comparison of genetic and linguistic reconstructions covering the last few millennia showed striking correspondences between the topology and dates of the respective gene and language trees and with documented historical events. Overall, in the Caucasus region, unmatched levels of gene–language coevolution occurred within geographically isolated populations, probably due to its mountainous terrain.Oleg Balanovsky, Khadizhat Dibirova, Anna Dybo, Oleg Mudrak, Svetlana Frolova, Elvira Pocheshkhova, Marc Haber, Daniel Platt, Theodore Schurr, Wolfgang Haak, Marina Kuznetsova, Magomed Radzhabov, Olga Balaganskaya, Alexey Romanov, Tatiana Zakharova, David F. Soria Hernanz, Pierre Zalloua, Sergey Koshel, Merritt Ruhlen, Colin Renfrew, R. Spencer Wells, Chris Tyler-Smith, Elena Balanovska and The Genographic Consortiu
Recombination networks as genetic markers in a human variation study of the Old World
No full textChristina J. Adler, Alan Cooper, Clio S. I. Der Sarkissian and Wolfgang Haak are members of The Genographic ConsortiumWe have analyzed human genetic diversity in 33 Old World populations including 23 populations obtained through Genographic Project studies. A set of 1,536 SNPs in five X chromosome regions were genotyped in 1,288 individuals (mostly males). We use a novel analysis employing subARG network construction with recombining chromosomal segments. Here, a subARG is constructed independently for each of five gene-free regions across the X chromosome, and the results are aggregated across them. For PCA, MDS and ancestry inference with STRUCTURE, the subARG is processed to obtain feature vectors of samples and pairwise distances between samples. The observed population structure, estimated from the five short X chromosomal segments, supports genome-wide frequency-based analyses: African populations show higher genetic diversity, and the general trend of shared variation is seen across the globe from Africa through Middle East, Europe, Central Asia, Southeast Asia, and East Asia in broad patterns. The recombinational analysis was also compared with established methods based on SNPs and haplotypes. For haplotypes, we also employed a fixed-length approach based on information-content optimization. Our recombinational analysis suggested a southern migration route out of Africa, and it also supports a single, rapid human expansion from Africa to East Asia through South Asia.Asif Javed, Marta Melé, Marc Pybus, Pierre Zalloua, Marc Haber, David Comas, Mihai G. Netea, Oleg Balanovsky, Elena Balanovska, Li Jin, Yajun Yang, GaneshPrasad ArunKumar, Ramasamy Pitchappan, Jaume Bertranpetit, Francesc Calafell, Laxmi Parida, The Genographic Consortiu
Ancient DNA reveals prehistoric gene-flow from Siberia in the complex human population history of north east Europe
No full textNorth East Europe harbors a high diversity of cultures and languages, suggesting a complex genetic history. Archaeological, anthropological, and genetic research has revealed a series of influences from Western and Eastern Eurasia in the past. While genetic data from modern-day populations is commonly used to make inferences about their origins and past migrations, ancient DNA provides a powerful test of such hypotheses by giving a snapshot of the past genetic diversity. In order to better understand the dynamics that have shaped the gene pool of North East Europeans, we generated and analyzed 34 mitochondrial genotypes from the skeletal remains of three archaeological sites in northwest Russia. These sites were dated to the Mesolithic and the Early Metal Age (7,500 and 3,500 uncalibrated years Before Present). We applied a suite of population genetic analyses (principal component analysis, genetic distance mapping, haplotype sharing analyses) and compared past demographic models through coalescent simulations using Bayesian Serial SimCoal and Approximate Bayesian Computation. Comparisons of genetic data from ancient and modern-day populations revealed significant changes in the mitochondrial makeup of North East Europeans through time. Mesolithic foragers showed high frequencies and diversity of haplogroups U (U2e, U4, U5a), a pattern observed previously in European hunter-gatherers from Iberia to Scandinavia. In contrast, the presence of mitochondrial DNA haplogroups C, D, and Z in Early Metal Age individuals suggested discontinuity with Mesolithic hunter-gatherers and genetic influx from central/eastern Siberia. We identified remarkable genetic dissimilarities between prehistoric and modern-day North East Europeans/Saami, which suggests an important role of post-Mesolithic migrations from Western Europe and subsequent population replacement/extinctions. This work demonstrates how ancient DNA can improve our understanding of human population movements across Eurasia. It contributes to the description of the spatio-temporal distribution of mitochondrial diversity and will be of significance for future reconstructions of the history of Europeans.Clio Der Sarkissian, Oleg Balanovsky, Guido Brandt, Valery Khartanovich, Alexandra Buzhilova, Sergey Koshel, Valery Zaporozhchenko, Detlef Gronenborn, Vyacheslav Moiseyev, Eugen Kolpakov, Vladimir Shumkin, Kurt W. Alt, Elena Balanovska, Alan Cooper, Wolfgang Haak, the Genographic Consortiu
Ancient DNA from European early Neolithic farmers reveals their near eastern affinities
No full textIn Europe, the Neolithic transition (8,000–4,000 B.C.) from hunting and gathering to agricultural communities was one of the most important demographic events since the initial peopling of Europe by anatomically modern humans in the Upper Paleolithic (40,000 B.C.). However, the nature and speed of this transition is a matter of continuing scientific debate in archaeology, anthropology, and human population genetics. To date, inferences about the genetic make up of past populations have mostly been drawn from studies of modern-day Eurasian populations, but increasingly ancient DNA studies offer a direct view of the genetic past. We genetically characterized a population of the earliest farming culture in Central Europe, the Linear Pottery Culture (LBK; 5,500–4,900 calibrated B.C.) and used comprehensive phylogeographic and population genetic analyses to locate its origins within the broader Eurasian region, and to trace potential dispersal routes into Europe. We cloned and sequenced the mitochondrial hypervariable segment I and designed two powerful SNP multiplex PCR systems to generate new mitochondrial and Y-chromosomal data from 21 individuals from a complete LBK graveyard at Derenburg Meerenstieg II in Germany. These results considerably extend the available genetic dataset for the LBK (n = 42) and permit the first detailed genetic analysis of the earliest Neolithic culture in Central Europe (5,500–4,900 calibrated B.C.). We characterized the Neolithic mitochondrial DNA sequence diversity and geographical affinities of the early farmers using a large database of extant Western Eurasian populations (n = 23,394) and a wide range of population genetic analyses including shared haplotype analyses, principal component analyses, multidimensional scaling, geographic mapping of genetic distances, and Bayesian Serial Simcoal analyses. The results reveal that the LBK population shared an affinity with the modern-day Near East and Anatolia, supporting a major genetic input from this area during the advent of farming in Europe. However, the LBK population also showed unique genetic features including a clearly distinct distribution of mitochondrial haplogroup frequencies, confirming that major demographic events continued to take place in Europe after the early Neolithic.Wolfgang Haak, Oleg Balanovsky, Juan J. Sanchez, Sergey Koshel, Valery Zaporozhchenko, Christina J. Adler, Clio S. I. Der Sarkissian, Guido Brandt, Carolin Schwarz, Nicole Nicklisch, Veit Dresely, Barbara Fritsch, Elena Balanovska, Richard Villems, Harald Meller, Kurt W. Alt, Alan Cooper and the Genographic Consortiu
No Evidence from Genome-Wide Data of a Khazar Origin for the Ashkenazi Jews
No full textThe origin and history of the Ashkenazi Jewish population have long been of great interest, and advances in high-throughput genetic analysis have recently provided a new approach for investigating these topics. We and others have argued on the basis of genome-wide data that the Ashkenazi Jewish population derives its ancestry from a combination of sources tracing to both Europe and the Middle East. It has been claimed, however, through a reanalysis of some of our data, that a large part of the ancestry of the Ashkenazi population originates with the Khazars, a Turkic-speaking group that lived to the north of the Caucasus region ~1,000 years ago. Because the Khazar population has left no obvious modern descendants that could enable a clear test for a contribution to Ashkenazi Jewish ancestry, the Khazar hypothesis has been difficult to examine using genetics. Furthermore, because only limited genetic data have been available from the Caucasus region, and because these data have been concentrated in populations that are genetically close to populations from the Middle East, the attribution of any signal of Ashkenazi-Caucasus genetic similarity to Khazar ancestry rather than shared ancestral Middle Eastern ancestry has been problematic. Here, through integration of genotypes on newly collected samples with data from several of our past studies, we have assembled the largest data set available to date for assessment of Ashkenazi Jewish genetic origins. This data set contains genome-wide single-nucleotide polymorphisms in 1,774 samples from 106 Jewish and non-Jewish populations that span the possible regions of potential Ashkenazi ancestry: Europe, the Middle East, and the region historically associated with the Khazar Khaganate. The data set includes 261 samples from 15 populations from the Caucasus region and the region directly to its north, samples that have not previously been included alongside Ashkenazi Jewish samples in genomic studies. Employing a variety of standard techniques for the analysis of population-genetic structure, we find that Ashkenazi Jews share the greatest genetic ancestry with other Jewish populations, and among non-Jewish populations, with groups from Europe and the Middle East. No particular similarity of Ashkenazi Jews with populations from the Caucasus is evident, particularly with the populations that most closely represent the Khazar region. Thus, analysis of Ashkenazi Jews together with a large sample from the region of the Khazar Khaganate corroborates the earlier results that Ashkenazi Jews derive their ancestry primarily from populations of the Middle East and Europe, that they possess considerable shared ancestry with other Jewish populations, and that there is no indication of a significant genetic contribution either from within or from north of the Caucasus region
Erratum: Geographic population structure analysis of worldwide human populations infers their biogeographical origins (Nature Communications (2014) 5(3513) DOI: 10.1038/ncomms4513)
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