A Quantitative Approach in Identifying Natural Selection Signals on Biallelic Single Nucleotide Polymorphisms of BRCA1 Gene in Diverse Populations

¹ Mathematics Department, School of Computer Science, Bina Nusantara University, 11480 Jakarta, Indonesia
² Bioinformatics and Data Science Research Center, Bina Nusantara University, 11480 Jakarta, Indonesia
³ Biotechnology Department, Faculty of Engineering, Bina Nusantara University, 11480 Jakarta, Indonesia
⁴ BINUS Graduate Program‑Master of Computer Science Program, Bina Nusantara University 11480, Jakarta, Indonesia

^* Corresponding author: alam.ahmad@binus.ac.id

Abstract

Population-specific studies reveal that cancer-related mechanisms of BRCA1 gene mutations may vary by ethnicity. The wealth of public genomic data provides 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 population-related hierarchical levels. An F_ST-based approach 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. The results 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 iHS computation, we found that only two East Asian populations that underwent a positive selection, in which only benign variants were observed. In addition, those putative variants are only found in the non-coding regions: intron and 3’ UTR. Our study is expected to ignite research interest in cancer-related genes for underrepresented populations.