The effect of close relatives on unsupervised Bayesian clustering algorithms in population genetic structure analysis

Rodríguez‐Ramilo, Silvia Teresa; Wang, Jinliang

doi:10.1111/j.1755-0998.2012.03156.x

Cited by 144 publications

(117 citation statements)

References 23 publications

(90 reference statements)

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“…The social system of lion tamarins consists of family groups with cooperative breeding and a typically monogamous mating system [Baker et al, 1993[Baker et al, , 2002. Furthermore, the clustering analyses performed by STRUCTURE can be influenced by the presence of highly related individuals in the samples [Rodríguez-Ramilo and Wang, 2012]. Our samples were obtained from social groups, which might bias our results.…”

Section: Data Analysesmentioning

confidence: 79%

Population Genetic Structure of an Endangered Endemic Primate (Leontopithecus chrysomelas) in a Highly Fragmented Atlantic Coastal Rain Forest

Moraes

Grativol

Vleeschouwer

et al. 2018

IJFP

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This study evaluated the genetic structure of wild populations of the endangered primate, Leontopithecus chrysomelas. We tested the assumption that populations of L. chrysomelas, given their larger population size and a higher degree of habitat continuity, would have higher genetic diversity and less genetic structuring than other lion tamarins. We used 11 microsatellites and 122 hair samples from different locations to assess their genetic diversity and genetic structure, and to make inferences about the isolation by distance. The overall expected heterozygosity (0.51 ± 0.03) and the average number of alleles (3.6 ± 0.2) were relatively low, as is the case in other endangered lion tamarins. Genetic clustering analyses indicated two main clusters, whereas the statistical analyses based on genotype similarities and F_st suggested further substructure. A Mantel test showed that only 34% of this genetic differentiation was explained by the linear distance. In addition to linear distance, structural differences in the landscape, physical barriers and behavioural factors may be causing significant genetic structuring. Overall, this study suggests that these populations have a relatively low genetic diversity and a relatively high population genetic structure, putting in question whether the presence of agroforest systems (known locally as cabruca) is enough to fully re-establish functional landscape connectivity.

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Section: Data Analysesmentioning

confidence: 79%

Population Genetic Structure of an Endangered Endemic Primate (Leontopithecus chrysomelas) in a Highly Fragmented Atlantic Coastal Rain Forest

Moraes

Grativol

Vleeschouwer

et al. 2018

IJFP

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“…A confounding of family-level with population-level structure might explain the observed decreasing STRUCTURE accuracy with increasing number of loci under the most difficult-to-detect simulated conditions. This problem has been generally recognized (Anderson and Dunham 2008;Rodriguez-Ramilo and Wang 2012). Reduced STRUCTURE accuracy with more loci seems counterintuitive until this confounding effect is considered.…”

Section: Structure -Simulationsmentioning

confidence: 95%

Simulation and empirical analysis of novel sibship-based genetic determination of fish passage

Whiteley

Coombs

Letcher

et al. 2014

Can. J. Fish. Aquat. Sci.

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We develop and test a new analytic approach, termed "sib-split", to detect fish passage through road crossings. This new approach is based on the genetic analysis of full-siblings on opposite sides of potential barriers. We used simulations and data from two empirical case studies involving brook trout (Salvelinus fontinalis) movement with respect to barriers that varied in strength of effect on fish passage. Simulations revealed that both sib-split and the population assignment-based method (STRUCTURE) were highly accurate (mean accuracy > 99%) under easy-to-detect conditions (moderate to strong genetic differentiation and no movement). However, under difficult-to-detect simulated conditions (no genetic differentiation, 10% movement each generation), sib-split had higher accuracy (mean accuracy = 98%) than STRUCTURE (mean accuracy = 84%). Sib-split also outperformed STRUCTURE (mean accuracy 98% versus 89%) under a more difficult-to-detect simulated management scenario (simulated construction of a new complete barrier to movement). Sib-split provided more reliable and easily interpretable movement detection in both easy-and difficult-to-detect empirical case studies. With the empirical case studies, sensitivity to the prior on migration rate precluded use of STRUCTURE by itself, but a two-step approach where sib-split results were used to provide an informed migration prior for STRUCTURE provided additional information for both case studies.Résumé : Nous avons mis au point et validé une nouvelle approche analytique désignée « sib-split » pour déceler le passage de poissons par des franchissements de route. Cette approche repose sur l'analyse génétique de groupes de fratrie de part et d'autre de barrières potentielles. Nous avons utilisé des simulations et les données de deux études empiriques de cas portant sur les déplacements des ombles de fontaine (Salvelinus fontinalis) par rapport à des barrières présentant différentes intensités d'effet sur le passage des poissons. Les simulations ont démontré que tant l'approche sib-split que la méthode d'affectation à des populations (STRUCTURE) étaient très exactes (exactitude moyenne > 99 %) pour des conditions de détection facile (différentiation génétique modérée à forte et aucun déplacement). Cependant, dans des conditions simulées de détection difficile (pas de différentiation génétique, 10 % de déplacements pour chaque génération), l'approche sib-split était plus exacte (exactitude moyenne = 98 %) que STRUCTURE (exactitude moyenne = 84 %). La méthode sib-split a également donné de meilleurs résultats que STRUCTURE (exactitude moyenne de 98 % contre 89 %) pour un scénario de gestion simulé avec détection plus difficile (construction simulée d'une nouvelle barrière complètement étanche aux déplacements). L'approche sib-split permettait une détection des déplacements plus fiable et facile à interpréter pour les études de cas empiriques de détection facile et difficile. En ce qui concerne les études de cas empiriques, la sensibilité aux informations a priori sur le tau...

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“…These results also show that any captive individual is most likely to share the same genetic cluster as its ancestor (χ 2 = 9, p = 0.0111), which would be expected, as these Bayesian clustering algorithms are known to group more closely related individuals (Pritchard et al 2000;Rodriguez-Ramilo and Wang 2012). …”

Section: Genetic Structurementioning

confidence: 53%

Genetic structure of captive and free-ranging okapi (Okapia johnstoni) with implications for management

et al. 2015

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Breeding programs for endangered species increasingly use molecular genetics to inform their management strategies. Molecular approaches can be useful for investigating relatedness, resolving pedigree uncertainties, and for estimating genetic diversity in captive and wild populations. Genetic data can also be used to evaluate the representation of wild population genomes within captive population gene-pools. Maintaining a captive population that is genetically representative of its wild counterpart offers a means of conserving the original evolutionary potential of a species. Okapi, an even-toed ungulate, endemic to the Democratic Republic of Congo, have recently been reclassified as Endangered by the IUCN. We carried out a genetic assessment of the ex-situ okapi (Okapia johnstoni) population, alongside an investigation into the genetic structure of wild populations across their geographic range. We found that while levels of nuclear (12 microsatellite loci) genetic variation in the wild, founder and captive okapi populations were similar, mitochondrial (833 bp of Cyt b, CR, tRNA-Thr and tRNA-Pro) variation within captive okapi was considerably reduced compared to the wild, with 16 % lower haplotype diversity. Further, both nuclear and mitochondrial alleles present in captivity provided only partial representation of those present in the wild. Thirty mitochondrial haplotypes found in the wild were not found in captivity, and two haplotypes found in captivity were not found in the wild, and the patterns of genetic variation at microsatellite loci in our captive samples were considerably different to those of the wild samples. Our study highlights the importance of genetic characterisation of captive populations, even for well-managed ex-situ breeding programs with detailed studbooks. We recommend that the captive US population should be further genetically characterised to guide management of translocations between European and US captive populations.

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The effect of close relatives on unsupervised Bayesian clustering algorithms in population genetic structure analysis

Cited by 144 publications

References 23 publications

Population Genetic Structure of an Endangered Endemic Primate (Leontopithecus chrysomelas) in a Highly Fragmented Atlantic Coastal Rain Forest

Population Genetic Structure of an Endangered Endemic Primate (Leontopithecus chrysomelas) in a Highly Fragmented Atlantic Coastal Rain Forest

Simulation and empirical analysis of novel sibship-based genetic determination of fish passage

Genetic structure of captive and free-ranging okapi (Okapia johnstoni) with implications for management

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