Bayazit Yunusbayev

University of Tartu, Institute of Genomics, Post-Doc

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Bayazit is interested in understanding the evolutionary history of modern human and how this shaped the diversity of phenotypes observed in contemporary populations. His expertise is in population genetics and he uses chip genotyping and next-generation sequencing to characterise human genomic variation. To understand human population history, Bayazit uses coalescent simulations and computational tools that are based on principles of populations genetics. He has studied population history in South Asia, the Middle East and Europe and these works uncovered signals of adaptation in the human genome shared between South Asia and Europe. It was also shown that the genetic diversity in India is second only to that in Africa, suggesting that the diversity resulting from an "out of Africa" migration evolved there, a hypothesis that needs further testing. One of his latest work focused on the population history of temperate Eurasia: a vast region encompassing Eastern Europe, Caucasus, Central Asia and Siberia. It was shown that the admixture of ancestral populations, which were likely separated for over 40 thousand years, has resulted in a complex mosaic of mixed genomes across this vast region. This can be thought of as a natural experiment that combined adaptations to different pathogens, climatic conditions and neutrally accumulated mutations. Bayazit's current focus is to understand how this population history shaped human phenotypes in mixed genomes. Another focus of his current research is to understand how pathogen-driven selection shaped immune-related phenotypes and autoimmune diseases. For this, he uses human cell culturing and immunological experiments.
Supervisors: Richard Villems

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Pedro Cruz

Universidade Estadual de Campinas

Алексей Романчук

Institute of Cultural Heritage

Istanbul Medeniyet University

Guido Alberto Gnecchi Ruscone

ILIA MIKEREZI

Universiteti i Tiranes

Etienne Guichard

Elisabetta Cilli

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Reconstructing recent population history while mapping rare variants using haplotypes

by Ural Yunusbaev and Bayazit Yunusbayev

Reconstructing recent population history while mapping rare variants using haplotypes, 2019

Haplotype-based methods are a cost-effective alternative to characterize unobserved rare variants... more Haplotype-based methods are a cost-effective alternative to characterize unobserved rare variants and map disease-associated alleles. Moreover, they can be used to reconstruct recent population history, which shaped distribution of rare variants and thus can be used to guide gene mapping studies. In this study, we analysed Illumina 650 k genotyped dataset on three underrepresented populations from Eastern Europe, where ancestors of Russians came into contact with two indigenous ethnic groups, Bashkirs and Tatars. Using the IBD mapping approach, we identified two rare IBD haplotypes strongly enriched in asthma patients of distinct ethnic background. We reconstructed recent population history using haplotype-based methods to reconcile this contradictory finding. Our ChromoPainter analysis showed that these haplotypes each descend from a single ancestor coming from one of the ethnic groups studied. Next, we used DoRIS approach and showed that source populations for patients exchanged recent (<60 generations) asymmetric gene flow, which supported the ChromoPainter-based scenario that patients share haplotypes through inter-ethnic admixture. Finally, we show that these IBD haplotypes overlap with asthma-associated genomic regions ascertained in European population. This finding is consistent with the fact that the two donor populations for the rare IBD haplotypes: Russians and Tatars have European ancestry. Low frequency (1% < MAF < 5%) and rare genetic variants (<1%) evolved recently and tend to have more dele-terious effect 1. While such variants may play an important role in the heritability of complex traits 2,3 , their effect remains largely uncharacterized. Accurate detection of rare variants requires extremely large samples (>10000) and costly high-coverage resequencing 4. Therefore, there is a need for cost-effective methods to study rare variants in populations that are underrepresented in large-scale full genome sequencing projects. Chip-genotyped SNP datasets and rare haplotypes (<1%) constructed from them can be used as proxies for rare variants 5,6. For populations that are not present in large-scale re-sequencing projects, use of haplotypes as proxies for rare variants is the only available option currently. Distribution of rare variants has been shaped by more recent demographic events (5000-10000 years ago) in human population history 7. Therefore, when mapping rare variants, knowledge about the recent demographic history for each studies population is essential 7. In this regard, haplotype-based methods offer a rich arsenal of methods designed to reconstruct recent population history 8. In this study, we focus on underrepresented populations (Table 1) from Eastern Europe, the region that borders Central Asia and Siberia (Fig. 1). This region denoted as the Volga-Ural region has been a historical crossroad for human migrations and admixture 9,10. It represents a useful model to understand the effect of recent complex population history on the distribution of rare haplotypes that serve here as a proxy for rare variants. Genome-wide data for our samples were retrieved from a previously published dataset 11 , and here we briefly describe background information relevant for our study. Patients and healthy controls were recruited from the Republic of Bashkortostan (Fig. 1), which geographically represent easternmost European Russia. Three ethnic groups currently represent the majority of the population in this region: Bashkirs, Russians, and Tatars, each amounting roughly 1/3 of the total population (total census size ~4.5 million people). Of these, Bashkirs and

Bayazit Yunusbayev

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