Armenian Genome Project

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The Armenian Genome Project aims at unraveling our genetic background and bringing personalized and precision medicine to Armenia

Web page: http://armeniangenome.am/

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Arsen Arakelyan

Projects: Sex-specific differences in long-term gamma and simGCRsim-associated alterations in deferential gene expression in the heart tissue, Functional Genomics of Vine, Molecular Profiling of Cancer Metastases, Omics-Based Insights into Human Long-Term Exposure to Environmental Metals, Biological pathway activity analysis, ML approaches for omic data analysis, Tools for Telomere Biology, Mental disorders and aging brain, Armenian Wine Genome Program, Study of the molecular mechanisms of familial Mediterranean fever using genetic engineering and functional genomics, Molecular characterization of cancers with long-read RNA sequencing, Low dose radiation risks: present research and future perspectives

Institutions: Institute of Molecular Biology NAS RA, Armenian Bioinformatics Institute

https://orcid.org/0000-0002-6851-1056

Lana Karapetyan

Projects: Study of the molecular mechanisms of familial Mediterranean fever using genetic engineering and functional genomics, Development of induced pluripotent stem cell bank of patients with Familial Mediterranean Fever, Molecular Profiling of Cancer Metastases, Sex-specific differences in long-term gamma and simGCRsim-associated alterations in deferential gene expression in the heart tissue, Molecular characterization of cancers with long-read RNA sequencing, ML approaches for omic data analysis, Mental disorders and aging brain, Armenian Wine Genome Program, Functional Genomics of Vine, COVID-19, Genetic History of Armenians, Molecular epidemiology of multi-drug resistance, Multi-Omics Molecular Diversity of Cancers

Institutions: Russian-Armenian University, Institute of Molecular Biology NAS RA

https://orcid.org/0009-0009-7992-1366

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Genetic History of Armenians

No description specified

Programme: Armenian Genome Project

Public web page: Not specified

Organisms: Human

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Institute of Molecular Biology NAS RA

Country: Armenia

City: Yerevan

Web page: https://molbiol.sci.am

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Demographic history and genetic variation of the Armenian population

Genetic History of Armenians

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 …

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

DOI: 10.1016/j.ajhg.2024.10.022

Citation: The American Journal of Human Genetics,112(1):11-27

Created: 22nd Aug 2025 at 08:00

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

Genetic History of Armenians

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, …

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

DOI: 10.1007/s00438-019-01596-2

Citation: Molecular Genetics and Genomics,294(6):1547-1559

Created: 22nd Aug 2025 at 08:32

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

Genetic History of Armenians

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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

DOI: 10.3389/fgene.2019.00394

Citation: Frontiers in Genetics,10

Created: 22nd Aug 2025 at 08:29

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