A Quantitative Approach in Identifying Natural Selection Signals on Biallelic Single Nucleotide Polymorphisms of BRCA1 Gene in Diverse Populations
Population-specific studies reveal that cancer-related mechanisms of BRCA1 gene mutations may vary by ethnicity. The wealth of public genomic data may provide insight into the functional roles of BRCA1 in diverse populations. In this study, we performed population differentiation analysis on biallelic SNPs located in the BRCA1 region using variant-calling data from the 1000 Human Genome Project. First, we conducted an Analysis of Molecular Variance (AMOVA) in global populations to infer a differentiation of BRCA1 gene in three hierarchical levels: “superpopulation”, “population”, and “individual”. An evaluation of the F_ST value was also conducted for each defined locus in the gene. Moreover, the signals of the natural selection in BRCA1 gene were computed using integrated Haplotype Score (iHS) per locus implemented via package rehh in R. The AMOVA and F_ST demonstrated that BRCA1 gene differentiation can be attributed to the continental difference, for example, the genetic difference between Asian and African superpopulations accounts for 25% of the total variance. Imposing the p-value-based approach on iHS computation, we found that only BRCA1 was found in two East Asian populations that underwent a positive selection, in which only benign variants were observed. Our study is expected to ignite research interest in cancer-related genes for underrepresented populations.
Authors:
Alam Ahmad Hidayat, Rudi Nirwantono, Joko Pebrianto Trinugroho, and Bens Pardamean
The 8th International Conference on Biological Sciences (ICBS) 2023