Title: Computational identification of personal genetic variants in an identical twin sisters' family
Authors: Ruoxian Huang; Ruoya Huang; Yongsheng Bai
Addresses: Eastside Catholic High School, 232 228th Ave SE, Sammamish, WA, 98074, USA; School of Health, Georgetown University, 3700 O St NW, Washington DC, 20057, USA ' Eastside Catholic High School, 232 228th Ave SE, Sammamish, WA, 98074, USA; School of Foreign Service, Georgetown University, 3700 O St NW, Washington DC, 20057, USA ' Department of Biology, Eastern Michigan University, 441 Mark Jefferson Hall, Ypsilanti, MI, 48197, USA
Abstract: Nowadays, scientists still have a limited understanding of how much genetic variation exists between identical twins. This study aims to analyse genotypic differences between identical twins and annotate the functional variants. We employed the 23andMe genotyping service to compare the genomes of twin sisters and their family members. With 162,400 SNPs genotyped at the autosomes, we found that there were 64,083 (10.26%) differences between one of the twins and their sibling brothers, while only 2530 differences (0.41%) existed between twin sisters. In total, among the 1974 nonsynonymous variants genotyped, excluding 'no calls,' only 17 shared nonsynonymous pathogenic variants between twin sisters were identified. The 16 pathogenic variants harboured genes are enriched with six significant terms associated with liver function and metabolic pathways. Our research could provide insight for physicians conducting studies related to genetic variations and personalised treatment of genetic disorders of identical twins.
Keywords: genomics; identical twins; mutations; nonsynonymous; 23andMe.
DOI: 10.1504/IJCBDD.2022.126991
International Journal of Computational Biology and Drug Design, 2022 Vol.15 No.2, pp.123 - 138
Received: 28 Dec 2021
Accepted: 20 Apr 2022
Published online: 16 Nov 2022 *