Population Genetic Polymorphism of Skeletal Muscle Strength Related Genes in Five Ethnic Minorities in North China

Abstract

Musculoskeletal performance is a complex trait influenced by environmental and genetic factors, and it has different manifestations in different populations. Heilongjiang province, located in northern China, is a multi-ethnic region with human cultures dating back to the Paleolithic Age. The Daur, Hezhen, Ewenki, Mongolian and Manchu ethnic groups in Heilongjiang province may have strong physical fitness to a certain extent. Based on the genetic characteristics of significant correlation between some important genes and skeletal muscle function, this study selected 23 SNPs of skeletal muscle strength-related genes and analyzed the distribution of these loci and genetic diversity in the five ethnic groups. Use Haploview (version 4.1) software to calculate the chi-square and the Hardy-Weinberg equilibrium to assess the difference between the two ethnic groups. Use R (version 4.0.2) software to perform principal component analysis of different ethnic groups. Use MEGA (version 7.0) software to construct the phylogenetic tree of different ethnic groups. Use POPGENE (version 1.32) software to calculate the heterozygosity and the FST values of 23 SNPs. Use Arlequin (version 3.5.2.2) software to analyze molecular variance (AMOVA) among 31 populations. The results showed that there was haplotype diversity of VDR, angiotensin-converting enzyme, ACTN3, EPO and IGF1 genes in the five ethnic groups, and there were genetic differences in the distribution of these genes in the five ethnic groups. Among them, the average gene heterozygosity (AVE_HET) of the 23 SNPs in the five populations was 0.398. The FST values of the 23 SNPs among the five ethnic groups varied from 0.0011 to 0.0137. According to the principal component analysis, the genetic distance of Daur, Mongolian and Ewenki is relatively close. According to the phylogenetic tree, the five ethnic groups are clustered together with the Asian population. These data will enrich existing genetic information of ethnic minorities.