Prospects for inferring pairwise relationships with single nucleotide polymorphisms

Glaubitz, Jeffrey C.; Rhodes, O. Eugene; Dewoody, J. Andrew

doi:10.1046/j.1365-294x.2003.01790.x

Cited by 136Genetic diversity and population structureForensic and Genetic ResearchGenetic Mapping and Diversity in Plants and Animals

Prospects for inferring pairwise relationships with single nucleotide polymorphisms

Glaubitz, Jeffrey C., Rhodes, O. Eugene, Dewoody, J. Andrew·2003·Molecular Ecology

DOI 10.1046/j.1365-294x.2003.01790.x

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Abstract

An extraordinarily large number of single nucleotide polymorphisms (SNPs) are now available in humans as well as in other model organisms. Technological advancements may soon make it feasible to assay hundreds of SNPs in virtually any organism of interest. One potential application of SNPs is the determination of pairwise genetic relationships in populations without known pedigrees. Although microsatellites are currently the marker of choice for this purpose, the number of independently segregating microsatellite markers that can be feasibly assayed is limited. Thus, it can be difficult to distinguish reliably some classes of relationship (e.g. full‐sibs from half‐sibs) with microsatellite data alone. We assess, via Monte Carlo computer simulation, the potential for using a large panel of independently segregating SNPs to infer genetic relationships, following the analytical approach of Blouin et al. (1996). We have explored a ‘best case scenario’ in which 100 independently segregating SNPs are available. For discrimination among single‐generation relationships or for the identification of parent–offspring pairs, it appears that such a panel of moderately polymorphic SNPs (minor allele frequency of 0.20) will provide discrimination power equivalent to only 16–20 independently segregating microsatellites. Although newly available analytical methods that can account for tight genetic linkage between markers will, in theory, allow improved estimation of relationships using thousands of SNPs in highly dense genomic scans, in practice such studies will only be feasible in a handful of model organisms. Given the comparable amount of effort required for the development of both types of markers, it seems that microsatellites will remain the marker of choice for relationship estimation in nonmodel organisms, at least for the foreseeable future.

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Authors: Glaubitz, J. C., Rhodes, O. E., & Dewoody, J. A.
Affiliations: Purdue University West Lafayette (US)
Corresponding author: Glaubitz, Jeffrey C.
ORCID: Rhodes, O. Eugene
Dewoody, J. Andrew
Venue: Molecular Ecology
Publisher: Wiley
Published: 2003-03-28
Volume: 12
Issue: 4
Pages: 1039-1047
ISSN: 0962-1083 (ISSN-L)
1365-294X
DOI: 10.1046/j.1365-294x.2003.01790.x
OpenAlex: W2150374976
Cited by: 136
References: 49
Citations by year: 2026: 1 · 2025: 2 · 2024: 4 · 2023: 4 · 2021: 4 · 2020: 3 · 2019: 3 · 2018: 12 · 2017: 6 · 2016: 7 · 2015: 4 · 2014: 7 · 2013: 9 · 2012: 3
FWCI: 3.89
Type: journal article
Language: en
Open access: closed
Licence: onlinelibrary.wiley.com/termsAndConditions#vor (vor)
Locations: Molecular Ecology (publishedVersion, public-domain)
PubMed (publishedVersion)
Topics: Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic diversity and population structure
Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Forensic and Genetic Research
Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Mapping and Diversity in Plants and Animals
Keywords: single nucleotide polymorphisms, microsatellite markers, relationship inference, minor allele frequency, genetic linkage, non-model organisms, population genetics
MeSH terms: Computer Simulation, Pedigree, Polymorphism, Single Nucleotide

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Prospects for inferring pairwise relationships with single nucleotide polymorphisms

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