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Cryptic Distant Relatives Are Common in Both Isolated and Cosmopolitan Genetic Samples

Overview of attention for article published in PLOS ONE, April 2012
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Title
Cryptic Distant Relatives Are Common in Both Isolated and Cosmopolitan Genetic Samples
Published in
PLOS ONE, April 2012
DOI 10.1371/journal.pone.0034267
Pubmed ID
Authors

Brenna M. Henn, Lawrence Hon, J. Michael Macpherson, Nick Eriksson, Serge Saxonov, Itsik Pe'er, Joanna L. Mountain

Abstract

Although a few hundred single nucleotide polymorphisms (SNPs) suffice to infer close familial relationships, high density genome-wide SNP data make possible the inference of more distant relationships such as 2(nd) to 9(th) cousinships. In order to characterize the relationship between genetic similarity and degree of kinship given a timeframe of 100-300 years, we analyzed the sharing of DNA inferred to be identical by descent (IBD) in a subset of individuals from the 23andMe customer database (n = 22,757) and from the Human Genome Diversity Panel (HGDP-CEPH, n = 952). With data from 121 populations, we show that the average amount of DNA shared IBD in most ethnolinguistically-defined populations, for example Native American groups, Finns and Ashkenazi Jews, differs from continentally-defined populations by several orders of magnitude. Via extensive pedigree-based simulations, we determined bounds for predicted degrees of relationship given the amount of genomic IBD sharing in both endogamous and 'unrelated' population samples. Using these bounds as a guide, we detected tens of thousands of 2(nd) to 9(th) degree cousin pairs within a heterogenous set of 5,000 Europeans. The ubiquity of distant relatives, detected via IBD segments, in both ethnolinguistic populations and in large 'unrelated' populations samples has important implications for genetic genealogy, forensics and genotype/phenotype mapping studies.

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Geographical breakdown

Country Count As %
United States 4 2%
Portugal 1 <1%
Ireland 1 <1%
Canada 1 <1%
United Kingdom 1 <1%
Japan 1 <1%
Russia 1 <1%
Unknown 169 94%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 43 24%
Researcher 36 20%
Professor 13 7%
Student > Bachelor 12 7%
Student > Master 11 6%
Other 35 20%
Unknown 29 16%
Readers by discipline Count As %
Agricultural and Biological Sciences 69 39%
Biochemistry, Genetics and Molecular Biology 34 19%
Medicine and Dentistry 12 7%
Computer Science 5 3%
Social Sciences 5 3%
Other 15 8%
Unknown 39 22%