title: Atlas of Cryptic Genetic Relatedness Among 1000 Human Genomes.
abstract: A novel computational method for detecting identical-by-descent (IBD) chromosomal segments between sequenced genomes is presented. It utilizes the distribution patterns of very rare genetic variants (vrGVs), which have minor allele frequencies <0.2%. Contrary to the existing probabilistic approaches our method is rather deterministic, because it considers a group of very rare events which cannot happen together only by chance. This method has been applied for exhaustive computational search of shared IBD segments among 1,092 sequenced individuals from 14 populations. It demonstrated that clusters of vrGVs are unique and powerful markers of genetic relatedness, that uncover IBD chromosomal segments between and within populations, irrespective of whether divergence was recent or occurred hundreds-to-thousands of years ago. We found that several IBD segments are shared by practically any possible pair of individuals belonging to the same population. Moreover, shared short IBD segments (median size 183 kb) were found in 10% of inter-continental human pairs, each comprising of a person from sub-Saharan Africa and a person from Southern Europe. The shortest shared IBD segments (median size 54 kb) were found in 0.42% of inter-continental pairs composed of individuals from Chinese/Japanese populations and Africans from Kenya and Nigeria. Knowledge of inheritance of IBD segments is important in clinical case-control and cohort studies, since unknown distant familial relationships could compromise interpretation of collected data. Clusters of vrGVs should be useful markers for familial relationship and common multifactorial disorders.
authors.affiliation: GEMA-Biomics, Ottawa Hills, OH, lvfedorova3@gmail.com Alexei.fedorov@utoledo.edu.
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.
authors.forename: Shuhao
authors.initials: S
authors.lastname: Qiu
authors.affiliation: Program in Biomedical Sciences, University of Toledo.
authors.forename: Rajib
authors.initials: R
authors.lastname: Dutta
authors.affiliation: Program in Bioinformatics and Proteomics/Genomics, University of Toledo Department of Medicine, University of Toledo lvfedorova3@gmail.com Alexei.fedorov@utoledo.edu.
authors.forename: Alexei
authors.initials: A
authors.lastname: Fedorov
mesh_terms: D044466:Asian People / Q000235:genetics; D044383:Black People / Q000235:genetics; D002875:Chromosomes / Q000235:genetics; D005787:Gene Frequency / Q000235:genetics*; D014644:Genetic Variation; D005828:Genetics, Population; D015894:Genome, Human; D059014:High-Throughput Nucleotide Sequencing; D006801:Humans
keywords: DNA; bioinformatics; biomarker; evolution; genealogy; inheritance