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Strategies for determining kinship in wild populations using genetic data

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ABSTRACT

Knowledge of kin relationships between members of wild animal populations has broad application in ecology and evolution research by allowing the investigation of dispersal dynamics, mating systems, inbreeding avoidance, kin recognition, and kin selection as well as aiding the management of endangered populations. However, the assessment of kinship among members of wild animal populations is difficult in the absence of detailed multigenerational pedigrees. Here, we first review the distinction between genetic relatedness and kinship derived from pedigrees and how this makes the identification of kin using genetic data inherently challenging. We then describe useful approaches to kinship classification, such as parentage analysis and sibship reconstruction, and explain how the combined use of marker systems with biparental and uniparental inheritance, demographic information, likelihood analyses, relatedness coefficients, and estimation of misclassification rates can yield reliable classifications of kinship in groups with complex kin structures. We outline alternative approaches for cases in which explicit knowledge of dyadic kinship is not necessary, but indirect inferences about kinship on a group‐ or population‐wide scale suffice, such as whether more highly related dyads are in closer spatial proximity. Although analysis of highly variable microsatellite loci is still the dominant approach for studies on wild populations, we describe how the long‐awaited use of large‐scale single‐nucleotide polymorphism and sequencing data derived from noninvasive low‐quality samples may eventually lead to highly accurate assessments of varying degrees of kinship in wild populations.

No MeSH data available.


ISI Web of Knowledge cumulative search results per year Search words: “wild population” and “microsatellite” (STR) or “SNP” (single‐nucleotide polymorphism) or “next‐generation sequencing” (NGS), excluding “plant.”
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ece32346-fig-0005: ISI Web of Knowledge cumulative search results per year Search words: “wild population” and “microsatellite” (STR) or “SNP” (single‐nucleotide polymorphism) or “next‐generation sequencing” (NGS), excluding “plant.”

Mentions: Studies of wild animals typically rely upon noninvasive samples such as hair (Morin & Woodruff 1992), blow (Frère et al. 2010), food wadges (Hashimoto et al. 1996), feathers and egg membranes (Pearce et al. 1997), shed skin (Villarreal et al. 1996), urine (Hayakawa & Takenaka 1999), or fecal samples (Höss et al. 1992). Although the DNA extracted from these samples is usually degraded and contains low proportions of endogenous DNA, accurate microsatellite genotypes can be obtained if extensive replication is performed (Taberlet & Luikart 1999). First described in the 1980s, microsatellites (STRs) are tandem repeats of short sequences and have long been the most common markers used in studies of wild populations (Fig. B1) with single‐nucleotide polymorphisms (SNPs), single base‐pair differences between the genomes of two individuals of a species, and next‐generation sequencing being less commonly used. The advantages and disadvantages of microsatellites and SNPs for population genetic applications in general have been extensively reviewed (Morin et al. 2004; Guichoux et al. 2011).


Strategies for determining kinship in wild populations using genetic data
ISI Web of Knowledge cumulative search results per year Search words: “wild population” and “microsatellite” (STR) or “SNP” (single‐nucleotide polymorphism) or “next‐generation sequencing” (NGS), excluding “plant.”
© Copyright Policy - creativeCommonsBy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC5016635&req=5

ece32346-fig-0005: ISI Web of Knowledge cumulative search results per year Search words: “wild population” and “microsatellite” (STR) or “SNP” (single‐nucleotide polymorphism) or “next‐generation sequencing” (NGS), excluding “plant.”
Mentions: Studies of wild animals typically rely upon noninvasive samples such as hair (Morin & Woodruff 1992), blow (Frère et al. 2010), food wadges (Hashimoto et al. 1996), feathers and egg membranes (Pearce et al. 1997), shed skin (Villarreal et al. 1996), urine (Hayakawa & Takenaka 1999), or fecal samples (Höss et al. 1992). Although the DNA extracted from these samples is usually degraded and contains low proportions of endogenous DNA, accurate microsatellite genotypes can be obtained if extensive replication is performed (Taberlet & Luikart 1999). First described in the 1980s, microsatellites (STRs) are tandem repeats of short sequences and have long been the most common markers used in studies of wild populations (Fig. B1) with single‐nucleotide polymorphisms (SNPs), single base‐pair differences between the genomes of two individuals of a species, and next‐generation sequencing being less commonly used. The advantages and disadvantages of microsatellites and SNPs for population genetic applications in general have been extensively reviewed (Morin et al. 2004; Guichoux et al. 2011).

View Article: PubMed Central - PubMed

ABSTRACT

Knowledge of kin relationships between members of wild animal populations has broad application in ecology and evolution research by allowing the investigation of dispersal dynamics, mating systems, inbreeding avoidance, kin recognition, and kin selection as well as aiding the management of endangered populations. However, the assessment of kinship among members of wild animal populations is difficult in the absence of detailed multigenerational pedigrees. Here, we first review the distinction between genetic relatedness and kinship derived from pedigrees and how this makes the identification of kin using genetic data inherently challenging. We then describe useful approaches to kinship classification, such as parentage analysis and sibship reconstruction, and explain how the combined use of marker systems with biparental and uniparental inheritance, demographic information, likelihood analyses, relatedness coefficients, and estimation of misclassification rates can yield reliable classifications of kinship in groups with complex kin structures. We outline alternative approaches for cases in which explicit knowledge of dyadic kinship is not necessary, but indirect inferences about kinship on a group‐ or population‐wide scale suffice, such as whether more highly related dyads are in closer spatial proximity. Although analysis of highly variable microsatellite loci is still the dominant approach for studies on wild populations, we describe how the long‐awaited use of large‐scale single‐nucleotide polymorphism and sequencing data derived from noninvasive low‐quality samples may eventually lead to highly accurate assessments of varying degrees of kinship in wild populations.

No MeSH data available.