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Demographic history and genetic variation of the Armenian population

Abstract (Expand)

We introduce a sizable (n = 34) whole-genome dataset on Armenians, a population inhabiting the region in West Asia known as the Armenian highlands. Equipped with this genetic data, we conducted a … whole-genome study of Armenians and deciphered their fine-scale population structure and complex demographic history. We demonstrated that the Armenian populations from western, central, and eastern parts of the highlands are relatively homogeneous. The Sasun, a population in the south that had been argued to have received a major genetic contribution from Assyrians, was instead shown to have derived its slightly divergent genetic profile from a bottleneck that occurred in the recent past. We also investigated the debated question on the genetic origin of Armenians and failed to find any significant support for historical suggestions by Herodotus of their Balkan-related ancestry. We checked the degree of continuity of modern Armenians with ancient inhabitants of the eastern Armenian highlands and detected a genetic input into the region from a source linked to Neolithic Levantine Farmers at some point after the Early Bronze Age. Additionally, we cataloged an abundance of new mutations unique to the population, including a missense mutation predicted to cause familial Mediterranean fever, an autoinflammatory disorder highly prevalent in Armenians. Thus, we highlight the importance of further genetic and medical studies of this population.

Authors: Anahit Hovhannisyan, Pierpaolo Maisano Delser, Anna Hakobyan, Eppie R. Jones, Joshua G. Schraiber, Mariya Antonosyan, Ashot Margaryan, Zhe Xue, Sungwon Jeon, Jong Bhak, Peter Hrechdakian, Hovhannes Sahakyan, Lehti Saag, Zaruhi Khachatryan, Levon Yepiskoposyan, Andrea Manica

Date Published: 25th Nov 2024

Publication Type: Journal

Insights into matrilineal genetic structure, differentiation and ancestry of Armenians based on complete mitogenome data

Abstract (Expand)

Distinctive peculiarities of Armenians such as their millennia-long genetic isolation and strong national identity attract a keen interest while studying the demographic history of the West Asia. Here, … to examine their fine-scale matrilineal genetic structure, ancestry and relationships with neighboring populations, we analyzed 536 complete mitogenomes (141 of which are novel) from 8 geographically different Armenian populations, covering the whole stretch of historical Armenia. The observed patterns highlight a remarkable degree of matrilineal genetic heterogeneity and weak population structuring of Armenians. Moreover, our phylogeographic analysis reveals common ancestries for some mtDNA lineages shared by West Asians, Transcaucasians, Europeans, Central Asians and Armenians. About third of the mtDNA subhaplogroups found in Armenian gene pool might be considered as Armenian-specific, as these are virtually absent elsewhere in Europe, West Asia and Transcaucasia. Coalescence ages of most of these lineages do not exceed 3.1 kya and coincide well with the population size growth started around 1.8-2.8 kya detectable only in the Bayesian Skyline Plots based on the Armenian-specific mtDNA haplotypes.

Authors: Miroslava Derenko, Galina Denisova, Boris Malyarchuk, Anahit Hovhannisyan, Zaruhi Khachatryan, Peter Hrechdakian, Andrey Litvinov, Levon Yepiskoposyan

Date Published: 1st Aug 2019

Publication Type: Journal

Population Levels Assessment of the Distribution of Disease-Associated Variants With Emphasis on Armenians – A Machine Learning Approach

Abstract (Expand)

Background: During the last decades a number of genome-wide association studies (GWASs) has identified numerous single nucleotide polymorphisms (SNPs) associated with different complex diseases. However, … associations reported in one population are often conflicting and did not replicate when studied in other populations. One of the reasons could be that most GWAS employ a case-control design in one or a limited number of populations, but little attention was paid to the global distribution of disease-associated alleles across different populations. Moreover, the majority of GWAS have been performed on selected European, African, and Chinese populations and the considerable number of populations remains understudied. Aim: We have investigated the global distribution of so far discovered disease-associated SNPs across worldwide populations of different ancestry and geographical regions with a special focus on the understudied population of Armenians. Data and Methods: We have used genotyping data from the Human Genome Diversity Project and of Armenian population and combined them with disease-associated SNP data taken from public repositories leading to a final dataset of 44,234 markers. Their frequency distribution across 1039 individuals from 53 populations was analyzed using self-organizing maps (SOM) machine learning. Our SOM portrayal approach reduces data dimensionality, clusters SNPs with similar frequency profiles and provides two-dimensional data images which enable visual evaluation of disease-associated SNPs landscapes among human populations. Results: We find that populations from Africa, Oceania, and America show specific patterns of minor allele frequencies of disease-associated SNPs, while populations from Europe, Middle East, Central South Asia, and Armenia mostly share similar patterns. Importantly, different sets of SNPs associated with common polygenic diseases, such as cancer, diabetes, neurodegeneration in populations from different geographic regions. Armenians are characterized by a set of SNPs that are distinct from other populations from the neighboring geographical regions. Conclusion: Genetic associations of diseases considerably vary across populations which necessitates health-related genotyping efforts especially for so far understudied populations. SOM portrayal represents novel promising methods in population genetic research with special strength in visualization-based comparison of SNP data.

Authors: Maria Nikoghosyan, Siras Hakobyan, Anahit Hovhannisyan, Henry Loeffler-Wirth, Hans Binder, Arsen Arakelyan

Date Published: 26th Apr 2019

Publication Type: Journal

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