Relatedness in the post-genomic era: is it still useful?
Abstract
Relatedness is a fundamental concept in genetics but is surprisingly hard to define in a rigorous yet useful way. Traditional relatedness coefficients specify expected genome sharing between individuals in pedigrees, but actual genome sharing can differ considerably from these expected values, which in any case vary according to the pedigree that happens to be available. Nowadays, we can measure genome sharing directly from genome-wide single-nucleotide polymorphism (SNP) data; however, there are many such measures in current use, and we lack good criteria for choosing among them. Here, we review SNP-based measures of relatedness and criteria for comparing them. We discuss how useful pedigree-based concepts remain today and highlight opportunities for further advances in quantitative genetics, with a focus on heritability estimation and phenotype prediction.
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The correlation of normalized and centered genotype counts is well suited as a measure of genetic relatedness when considering differences across genetically diverse populations.
“This relatedness measure is widely used to control for population structure in cohorts drawn from multiple mating populations (e.g., genetic principal components analysis or as the covariance structure of random effects in linear-mixed models of genetic association tests) and, thus, is well suited as a measure of genetic relatedness when considering differences across genetically diverse”
From Population structure of human gut bacteria in a diverse cohort from rural Tanzania and Botswana (2019) · cites this paper as [48]
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- Authors
- Speed, D., & Balding, D. J.
- Affiliations
- University College London (GB)
- The University of Melbourne (AU)
- Corresponding author
- Balding, David J.
- Venue
- Nature Reviews Genetics
- Published
- 2014-11-18
- Volume
- 16
- Issue
- 1
- Pages
- 33-44
- ISSN
- 1471-0056 (ISSN-L)
- 1471-0064
- OpenAlex
- W2031781568
- Cited by
- 316
- References
- 98
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- 3.09
- Type
- journal article
- Language
- en
- Open access
- closed
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- www.springer.com/tdm (tdm)
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- Funders
- Wellcome Trust
- Medical Research Council (MR/L012561/1)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic and phenotypic traits in livestock
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Mapping and Diversity in Plants and Animals
- Keywords
- relatedness, genome similarity, single nucleotide polymorphisms, heritability estimation, phenotype prediction, quantitative genetics, post-genomic era
- MeSH terms
- Computer Simulation, Genetics, Population, Humans, Models, Genetic, Pedigree, Phenotype, Genetic Variation, Polymorphism, Single Nucleotide
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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