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Effective number of breeders from sibship reconstruction: empirical evaluations using hatchery steelhead.

ABSTRACT: Effective population size (N_e ) is among the most important metrics in evolutionary biology. In natural populations, it is often difficult to collect adequate demographic data to calculate N_e directly. Consequently, genetic methods to estimate N_e have been developed. Two N_e estimators based on sibship reconstruction using multilocus genotype data have been developed in recent years: sibship assignment and parentage analysis without parents. In this study, we evaluated the accuracy of sibship reconstruction using a large empirical dataset from five hatchery steelhead populations with known pedigrees and using 95 single nucleotide polymorphism (SNP) markers. We challenged the software COLONY with 2,599,961 known relationships and demonstrated that reconstruction of full-sib and unrelated pairs was greater than 95% and 99% accurate, respectively. However, reconstruction of half-sib pairs was poor (<5% accurate). Despite poor half-sib reconstruction, both estimators provided accurate estimates of the effective number of breeders (N_b ) when sample sizes were near or greater than the true N_b and when assuming a monogamous mating system. We further demonstrated that both methods provide roughly equivalent estimates of N_b . Our results indicate that sibship reconstruction and current SNP panels provide promise for estimating N_b in steelhead populations in the region.

SUBMITTER: Ackerman MW

PROVIDER: S-EPMC5253425 | biostudies-literature | 2017 Feb

REPOSITORIES: biostudies-literature

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Effective number of breeders from sibship reconstruction: empirical evaluations using hatchery steelhead.

Ackerman Michael W MW Hand Brian K BK Waples Ryan K RK Luikart Gordon G Waples Robin S RS Steele Craig A CA Garner Brittany A BA McCane Jesse J Campbell Matthew R MR

Evolutionary applications 20161018 2

Effective population size (Ne ) is among the most important metrics in evolutionary biology. In natural populations, it is often difficult to collect adequate demographic data to calculate Ne directly. Consequently, genetic methods to estimate Ne have been developed. Two Ne estimators based on sibship reconstruction using multilocus genotype data have been developed in recent years: sibship assign ...[more]

PMID: 28127391

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Project description:Detecting trends in population size fluctuations is a major focus in ecology, evolution, and conservation biology. Populations of colonial waterbirds have been monitored using demographic approaches to determine annual census size (Na). We propose the addition of genetic estimates of the effective number of breeders (Nb) as indirect measures of the risk of loss of genetic diversity to improve the evaluation of demographics and increase the accuracy of trend estimates in breeding colonies. Here, we investigated which methods of the estimation of Nb are more precise under conditions of moderate genetic diversity, limited sample sizes and few microsatellite loci, as often occurs with natural populations. We used the wood stork as a model species and we offered a workflow that researchers can follow for monitoring bird breeding colonies. Our approach started with simulations using five estimators of Nb and the theoretical results were validated with empirical data collected from breeding colonies settled in the Brazilian Pantanal wetland. In parallel, we estimated census size using a corrected method based on counting active nests. Both in simulations and in natural populations, the approximate Bayesian computation (ABC) and sibship assignment (SA) methods yielded more precise estimates than the linkage disequilibrium, heterozygosity excess, and molecular coancestry methods. In particular, the ABC method performed best with few loci and small sample sizes, while the other estimators required larger sample sizes and at least 13 loci to not underestimate Nb. Moreover, according to our Nb/Na estimates (values were often ≤0.1), the wood stork colonies evaluated could be facing the loss of genetic diversity. We demonstrate that the combination of genetic and census estimates is a useful approach for monitoring natural breeding bird populations. This methodology has been recommended for populations of rare species or with a known history of population decline to support conservation efforts.

Project description:BackgroundNumerous immune-mediated diseases have been associated with the class I and II HLA genes located within the major histocompatibility complex (MHC) consisting of highly polymorphic alleles encoded by the HLA-A, -B, -C, -DRB1, -DQB1 and -DPB1 loci. Genotyping for HLA alleles is complex and relatively expensive. Recent studies have demonstrated the feasibility of predicting HLA alleles, using MHC SNPs inside and outside of HLA that are typically included in SNP arrays and are commonly available in genome-wide association studies (GWAS). We have recently described a novel method that is complementary to the previous methods, for accurately predicting HLA alleles using unphased flanking SNPs genotypes. In this manuscript, we address several practical issues relevant to the application of this methodology.ResultsApplying this new methodology to three large independent study cohorts, we have evaluated the performance of the predictive models in ethnically diverse populations. Specifically, we have found that utilizing imputed in addition to genotyped SNPs generally yields comparable if not better performance in prediction accuracies. Our evaluation also supports the idea that predictive models trained on one population are transferable to other populations of the same ethnicity. Further, when the training set includes multi-ethnic populations, the resulting models are reliable and perform well for the same subpopulations across all HLA genes. In contrast, the predictive models built from single ethnic populations have superior performance within the same ethnic population, but are not likely to perform well in other ethnic populations.ConclusionsThe empirical explorations reported here provide further evidence in support of the application of this approach for predicting HLA alleles with GWAS-derived SNP data. Utilizing all available samples, we have built "state of the art" predictive models for HLA-A, -B, -C, -DRB1, -DQB1 and -DPB1. The HLA allele predictive models, along with the program used to carry out the prediction, are available on our website.

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Effective number of breeders from sibship reconstruction: empirical evaluations using hatchery steelhead.

Publications

Effective number of breeders from sibship reconstruction: empirical evaluations using hatchery steelhead.

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