Inference of relationships in population data using identity-by-descent and identity-by-state

Eric L. Stevens, Greg Heckenberg, Elisha D O Roberson, Joseph D. Baugher, Thomas J. Downey, Jonathan A. Pevsner

Research output: Contribution to journalArticle

Abstract

It is an assumption of large, population-based datasets that samples are annotated accurately whether they correspond to known relationships or unrelated individuals. These annotations are key for a broad range of genetics applications. While many methods are available to assess relatedness that involve estimates of identity-by-descent (IBD) and/or identity-by-state (IBS) allele-sharing proportions, we developed a novel approach that estimates IBD0, 1, and 2 based on observed IBS within windows. When combined with genome-wide IBS information, it provides an intuitive and practical graphical approach with the capacity to analyze datasets with thousands of samples without prior information about relatedness between individuals or haplotypes. We applied the method to a commonly used Human Variation Panel consisting of 400 nominally unrelated individuals. Surprisingly, we identified identical, parent-child, and full-sibling relationships and reconstructed pedigrees. In two instances non-sibling pairs of individuals in these pedigrees had unexpected IBD2 levels, as well as multiple regions of homozygosity, implying inbreeding. This combined method allowed us to distinguish related individuals from those having atypical heterozygosity rates and determine which individuals were outliers with respect to their designated population. Additionally, it becomes increasingly difficult to identify distant relatedness using genome-wide IBS methods alone. However, our IBD method further identified distant relatedness between individuals within populations, supported by the presence of megabase-scale regions lacking IBS0 across individual chromosomes. We benchmarked our approach against the hidden Markov model of a leading software package (PLINK), showing improved calling of distantly related individuals, and we validated it using a known pedigree from a clinical study. The application of this approach could improve genome-wide association, linkage, heterozygosity, and other population genomics studies that rely on SNP genotype data.

Original languageEnglish (US)
Article numbere1002287
JournalPLoS Genetics
Volume7
Issue number9
DOIs
StatePublished - Sep 2011

Fingerprint

relatedness
Pedigree
pedigree
genome
Population
Genome
heterozygosity
Metagenomics
methodology
Inbreeding
inbreeding
homozygosity
outlier
Haplotypes
Single Nucleotide Polymorphism
linkage (genetics)
Siblings
chromosome
clinical trials
genomics

ASJC Scopus subject areas

  • Genetics
  • Molecular Biology
  • Ecology, Evolution, Behavior and Systematics
  • Cancer Research
  • Genetics(clinical)

Cite this

Stevens, E. L., Heckenberg, G., Roberson, E. D. O., Baugher, J. D., Downey, T. J., & Pevsner, J. A. (2011). Inference of relationships in population data using identity-by-descent and identity-by-state. PLoS Genetics, 7(9), [e1002287]. https://doi.org/10.1371/journal.pgen.1002287

Inference of relationships in population data using identity-by-descent and identity-by-state. / Stevens, Eric L.; Heckenberg, Greg; Roberson, Elisha D O; Baugher, Joseph D.; Downey, Thomas J.; Pevsner, Jonathan A.

In: PLoS Genetics, Vol. 7, No. 9, e1002287, 09.2011.

Research output: Contribution to journalArticle

Stevens, Eric L. ; Heckenberg, Greg ; Roberson, Elisha D O ; Baugher, Joseph D. ; Downey, Thomas J. ; Pevsner, Jonathan A. / Inference of relationships in population data using identity-by-descent and identity-by-state. In: PLoS Genetics. 2011 ; Vol. 7, No. 9.
@article{5e1d3a9d0bec4e059c42e68474087fc8,
title = "Inference of relationships in population data using identity-by-descent and identity-by-state",
abstract = "It is an assumption of large, population-based datasets that samples are annotated accurately whether they correspond to known relationships or unrelated individuals. These annotations are key for a broad range of genetics applications. While many methods are available to assess relatedness that involve estimates of identity-by-descent (IBD) and/or identity-by-state (IBS) allele-sharing proportions, we developed a novel approach that estimates IBD0, 1, and 2 based on observed IBS within windows. When combined with genome-wide IBS information, it provides an intuitive and practical graphical approach with the capacity to analyze datasets with thousands of samples without prior information about relatedness between individuals or haplotypes. We applied the method to a commonly used Human Variation Panel consisting of 400 nominally unrelated individuals. Surprisingly, we identified identical, parent-child, and full-sibling relationships and reconstructed pedigrees. In two instances non-sibling pairs of individuals in these pedigrees had unexpected IBD2 levels, as well as multiple regions of homozygosity, implying inbreeding. This combined method allowed us to distinguish related individuals from those having atypical heterozygosity rates and determine which individuals were outliers with respect to their designated population. Additionally, it becomes increasingly difficult to identify distant relatedness using genome-wide IBS methods alone. However, our IBD method further identified distant relatedness between individuals within populations, supported by the presence of megabase-scale regions lacking IBS0 across individual chromosomes. We benchmarked our approach against the hidden Markov model of a leading software package (PLINK), showing improved calling of distantly related individuals, and we validated it using a known pedigree from a clinical study. The application of this approach could improve genome-wide association, linkage, heterozygosity, and other population genomics studies that rely on SNP genotype data.",
author = "Stevens, {Eric L.} and Greg Heckenberg and Roberson, {Elisha D O} and Baugher, {Joseph D.} and Downey, {Thomas J.} and Pevsner, {Jonathan A.}",
year = "2011",
month = "9",
doi = "10.1371/journal.pgen.1002287",
language = "English (US)",
volume = "7",
journal = "PLoS Genetics",
issn = "1553-7390",
publisher = "Public Library of Science",
number = "9",

}

TY - JOUR

T1 - Inference of relationships in population data using identity-by-descent and identity-by-state

AU - Stevens, Eric L.

AU - Heckenberg, Greg

AU - Roberson, Elisha D O

AU - Baugher, Joseph D.

AU - Downey, Thomas J.

AU - Pevsner, Jonathan A.

PY - 2011/9

Y1 - 2011/9

N2 - It is an assumption of large, population-based datasets that samples are annotated accurately whether they correspond to known relationships or unrelated individuals. These annotations are key for a broad range of genetics applications. While many methods are available to assess relatedness that involve estimates of identity-by-descent (IBD) and/or identity-by-state (IBS) allele-sharing proportions, we developed a novel approach that estimates IBD0, 1, and 2 based on observed IBS within windows. When combined with genome-wide IBS information, it provides an intuitive and practical graphical approach with the capacity to analyze datasets with thousands of samples without prior information about relatedness between individuals or haplotypes. We applied the method to a commonly used Human Variation Panel consisting of 400 nominally unrelated individuals. Surprisingly, we identified identical, parent-child, and full-sibling relationships and reconstructed pedigrees. In two instances non-sibling pairs of individuals in these pedigrees had unexpected IBD2 levels, as well as multiple regions of homozygosity, implying inbreeding. This combined method allowed us to distinguish related individuals from those having atypical heterozygosity rates and determine which individuals were outliers with respect to their designated population. Additionally, it becomes increasingly difficult to identify distant relatedness using genome-wide IBS methods alone. However, our IBD method further identified distant relatedness between individuals within populations, supported by the presence of megabase-scale regions lacking IBS0 across individual chromosomes. We benchmarked our approach against the hidden Markov model of a leading software package (PLINK), showing improved calling of distantly related individuals, and we validated it using a known pedigree from a clinical study. The application of this approach could improve genome-wide association, linkage, heterozygosity, and other population genomics studies that rely on SNP genotype data.

AB - It is an assumption of large, population-based datasets that samples are annotated accurately whether they correspond to known relationships or unrelated individuals. These annotations are key for a broad range of genetics applications. While many methods are available to assess relatedness that involve estimates of identity-by-descent (IBD) and/or identity-by-state (IBS) allele-sharing proportions, we developed a novel approach that estimates IBD0, 1, and 2 based on observed IBS within windows. When combined with genome-wide IBS information, it provides an intuitive and practical graphical approach with the capacity to analyze datasets with thousands of samples without prior information about relatedness between individuals or haplotypes. We applied the method to a commonly used Human Variation Panel consisting of 400 nominally unrelated individuals. Surprisingly, we identified identical, parent-child, and full-sibling relationships and reconstructed pedigrees. In two instances non-sibling pairs of individuals in these pedigrees had unexpected IBD2 levels, as well as multiple regions of homozygosity, implying inbreeding. This combined method allowed us to distinguish related individuals from those having atypical heterozygosity rates and determine which individuals were outliers with respect to their designated population. Additionally, it becomes increasingly difficult to identify distant relatedness using genome-wide IBS methods alone. However, our IBD method further identified distant relatedness between individuals within populations, supported by the presence of megabase-scale regions lacking IBS0 across individual chromosomes. We benchmarked our approach against the hidden Markov model of a leading software package (PLINK), showing improved calling of distantly related individuals, and we validated it using a known pedigree from a clinical study. The application of this approach could improve genome-wide association, linkage, heterozygosity, and other population genomics studies that rely on SNP genotype data.

UR - http://www.scopus.com/inward/record.url?scp=80053460553&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=80053460553&partnerID=8YFLogxK

U2 - 10.1371/journal.pgen.1002287

DO - 10.1371/journal.pgen.1002287

M3 - Article

C2 - 21966277

AN - SCOPUS:80053460553

VL - 7

JO - PLoS Genetics

JF - PLoS Genetics

SN - 1553-7390

IS - 9

M1 - e1002287

ER -