Mathematical models in population genomics and their applications

Population genomics is an interdisciplinary science at the intersection of genetics, mathematics and computer science, studying the structure of populations and the history of their development based on genetic data. Events such as population size changes, separation and mixing of populations leave imprints in genomes. By reducing the cost of DNA sequencing and the speed of data processing, we have obtained an unprecedented variety of genomic data.
In the first part of the report, we will discuss the basic mathematical population models used in genomics. We will also discuss the main methods of population analysis of genetic data based on them. Then we will look at examples of practical application of population models to experimental data. In particular, the report will present the results of the study of the SARS-CoV-2 coronavirus pandemic in Russia, when viral sequences become available for analysis in almost real time. This allowed us to estimate the number of virus shipments to Russia, as well as the sources of these shipments. We also studied the nosocomial outbreak of Covid-19 at the Institute of Traumatology. It was damaged and showed that the virus was introduced there independently 2-3 times.