title: Inference of distant genetic relations in humans using "1000 genomes".
abstract: Nucleotide sequence differences on the whole-genome scale have been computed for 1,092 people from 14 populations publicly available by the 1000 Genomes Project. Total number of differences in genetic variants between 96,464 human pairs has been calculated. The distributions of these differences for individuals within European, Asian, or African origin were characterized by narrow unimodal peaks with mean values of 3.8, 3.5, and 5.1 million, respectively, and standard deviations of 0.1-0.03 million. The total numbers of genomic differences between pairs of all known relatives were found to be significantly lower than their respective population means and in reverse proportion to the distance of their consanguinity. By counting the total number of genomic differences it is possible to infer familial relations for people that share down to 6% of common loci identical-by-descent. Detection of familial relations can be radically improved when only very rare genetic variants are taken into account. Counting of total number of shared very rare single nucleotide polymorphisms (SNPs) from whole-genome sequences allows establishing distant familial relations for persons with eighth and ninth degrees of relationship. Using this analysis we predicted 271 distant familial pairwise relations among 1,092 individuals that have not been declared by 1000 Genomes Project. Particularly, among 89 British and 97 Chinese individuals we found three British-Chinese pairs with distant genetic relationships. Individuals from these pairs share identical-by-descent DNA fragments that represent 0.001%, 0.004%, and 0.01% of their genomes. With affordable whole-genome sequencing techniques, very rare SNPs should become important genetic markers for familial relationships and population stratification.
authors.affiliation: Program in Bioinformatics and Proteomics/Genomics, University of Toledo.
authors.forename: Ahmed
authors.initials: A
authors.lastname: Al-Khudhair
authors.affiliation: Program in Biomedical Sciences, University of Toledo Department of Medicine, University of Toledo.
authors.forename: Shuhao
authors.initials: S
authors.lastname: Qiu
authors.affiliation: Program in Biomedical Sciences, University of Toledo.
authors.forename: Meghan
authors.initials: M
authors.lastname: Wyse
authors.affiliation: Program in Biomedical Sciences, University of Toledo.
authors.forename: Shilpi
authors.initials: S
authors.lastname: Chowdhury
authors.affiliation: Program in Biomedical Sciences, University of Toledo.
authors.forename: Xi
authors.initials: X
authors.lastname: Cheng
authors.affiliation: Program in Biomedical Sciences, University of Toledo.
authors.forename: Dulat
authors.initials: D
authors.lastname: Bekbolsynov
authors.affiliation: Program in Bioinformatics and Proteomics/Genomics, University of Toledo.
authors.forename: Arnab
authors.initials: A
authors.lastname: Saha-Mandal
authors.affiliation: Program in Biomedical Sciences, University of Toledo Department of Medicine, University of Toledo.
authors.forename: Rajib
authors.initials: R
authors.lastname: Dutta
authors.affiliation: GEMA-Biomics, Ottawa Hills, Ohio.
authors.forename: Larisa
authors.initials: L
authors.lastname: Fedorova
authors.affiliation: Program in Bioinformatics and Proteomics/Genomics, University of Toledo Department of Medicine, University of Toledo alexei.fedorov@utoledo.edu.
authors.forename: Alexei
authors.initials: A
authors.lastname: Fedorov
mesh_terms: D002877:Chromosomes, Human / Q000235:genetics; D014644:Genetic Variation; D005828:Genetics, Population; D015894:Genome, Human; D006801:Humans; D010802:Phylogeny
keywords: bioinformatics; haplotype; population genetics; vrGV