Aim. Formation of polymorphic variants panel of the proteasome genes 20S, potentially significant for the study as balance modifier factors of p105/p50 NFKB1.Materials and methods. Determination of genes that encode proteins of the multisubunit proteasome complex prospective for research purposes, was carried out on the basis of information retrieved from eLIBRARY and PubMed. The source of information for the formation of polymorphic variants panel of genes (SNP, single nucleotide polymorphism) was the Ensembl genomic browser, http://www.ensembl.org. The structure of genes is described by the NCBI (databases Gene, http:// www.ncbi.nlm.nih.gov/gene). The panel was filled with the minor allelic frequency in the population (MAF), the localization of SNP in the gene structure and the availability of data on the relationship with multifactorial diseases and other effects in mind. To calculate the genetic distances between populations, we used the methord of comparing the populations by frequencies of polymorphic marker alleles proposed by Ney, the obtained matrices are illustrated by the method of multidimensional scaling in space using Statistica v.8.0.Results. Discussion of the algorithm and results of analytical screening of polymorphic variants of 14 genes (PSMA1-PSMA7, PSMB1–PSMB7) encoding proteasome subunits 20S. The characteristics of the SNP panel are given, compiled with the selection criteria taken into account. According to the data on the frequencies of polymorphic gene variants, the features of global and European population gene pools (283 SNP), as well as samples from Russian populations (20 SNP) are analyzed. Based on the results of the analysis of information on the associations of selected SNPs with various diseases, a panel (42 SNPs) of 20S proteasome genes was formed, potentially significant for the study as factors modifying the p105/p50 NFKB1 balance.Conclusion. Annotation of the formed panel of SNP genes of the 20S proteasome with MAF>0.1 indicates the potential role of polymorphism in the pathogenesis of diseases of various profiles. This may be of research interest to the formed panel in context of implementation of traditional approaches – the search for candidate genes based on the analysis of associations with diseases, as well as the analysis of the influence of SNP on the level of genetic expression, synthesis of gene products, NFKB1 processing and p105/p50 balance in silico and on model objects.
