The Russian Federation is a large country uniting many nationalities and populations. However, their genetic diversity is still understudied: existing researchs consider either a specific population or a part of the genome. At the same time, a comparison of whole genome data from different populations can help to learn more about the spread of diseases and resistance to them. Therefore, St. Petersburg State University initiated the "Russian Genomes" project, in terms of which scientists from various organizations create a database of genetic data of Russian population.
Recently, this work has brought new results: for the first time, researchers managed to compare the whole genome data of several populations. Scientists analyzed 204 genome datasets of different populations from other papers and added to this 60 new genomes from Pskov, Novgorod and Yakutia. All in all, 264 representatives of 55 ethnic groups were examined during the study.
The researchers used a special program written by ITMO University to predict demographic history for three of these populations.This demographic history describes the populations development: how and when they were one ancestral population, how the population size changed, what were the rates of their migration.
"We developed a program to search for the optimal demographic history according to the genomes of samples of the populations. This required calculation and analysis of different alleles occurrence frequency. The program then built many demographic histories to find out which of them is more appropriate for this data," says Ekaterina Noskova from the Laboratory of Computer Technologies at ITMO University.
It turned out, for example, that in the past the current inhabitants of Pskov, Novgorod and Yakutia were one population of about 2000 people. But 7000 years ago the Yakuts separated from it, and about 1,200 years ago representatives of Pskov and Novgorod divided. Since then, all three populations began to grow sharply in numbers.
According to scientists, comparing the genome of different populations, as well as their development histories, helps to understand, which gene variants cause diseases and which, on the contrary, protect from them. Therefore, for the next step of this study the researchers plan to carefully analyze the data and look for correlations with diseases.
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