SNeP: a tool to estimate trends in recent effective population size trajectories using genome-wide SNP data

Barbato, Mario; Orozco‐terWengel, Pablo; Tapio, Miika; Bruford, Michael William

doi:10.3389/fgene.2015.00109

Cited by 378 publications

(328 citation statements)

References 35 publications

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“…For data quality control, the effective population size was investigated using the SNeP tool described by Barbato et al (2015). The method examines the relationship between the variance in linkage disequilibrium and effective population size in the presence of mutation.…”

Section: Resultsmentioning

confidence: 99%

Inference of population structure of purebred dairy and beef cattle using high-density genotype data

Kelleher

Berry

Kearney³

et al. 2017

Animal

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Information on the genetic diversity and population structure of cattle breeds is useful when deciding the most optimal, for example, crossbreeding strategies to improve phenotypic performance by exploiting heterosis. The present study investigated the genetic diversity and population structure of the most prominent dairy and beef breeds used in Ireland. Illumina high-density genotypes (777 962 single nucleotide polymorphisms; SNPs) were available on 4623 purebred bulls from nine breeds; Angus (n = 430), Belgian Blue (n = 298), Charolais (n = 893), Hereford (n = 327), Holstein-Friesian (n = 1261), Jersey (n = 75), Limousin (n = 943), Montbéliarde (n = 33) and Simmental (n = 363). Principal component analysis revealed that Angus, Hereford, and Jersey formed non-overlapping clusters, representing distinct populations. In contrast, overlapping clusters suggested geographical proximity of origin and genetic similarity between Limousin, Simmental and Montbéliarde and to a lesser extent between Holstein, Friesian and Belgian Blue. The observed SNP heterozygosity averaged across all loci was 0.379. The Belgian Blue had the greatest mean observed heterozygosity (H O = 0.389) among individuals within breed while the Holstein-Friesian and Jersey populations had the lowest mean heterozygosity (H O = 0.370 and 0.376, respectively). The correlation between the genomic-based and pedigree-based inbreeding coefficients was weak (r = 0.171; P < 0.001). Mean genomic inbreeding estimates were greatest for Jersey (0.173) and least for Hereford (0.051). The pair-wise breed fixation index ( F st ) ranged from 0.049 (Limousin and Charolais) to 0.165 (Hereford and Jersey). In conclusion, substantial genetic variation exists among breeds commercially used in Ireland. Thus custom-mating strategies would be successful in maximising the exploitation of heterosis in crossbreeding strategies.Keywords: genetic diversity, population structure, fixation index, phylogenetic ImplicationsThe strong use of artificial selection to increase the frequency of favourable alleles at the loci affecting phenotypic performance (e.g. milk production), coupled with intense selection that featured heavily in some breeds, has resulted in reduced genetic diversity within breed and has affected the extent of genomic homozygosity. In this study high-density genotypic data on a large number of individuals of different breeds was available to make inferences of population structure for the different breeds used in temperate cattle production systems. IntroductionDomestic cattle (Bos taurus and Bos indicus) originated from populations of the wild extinct aurochs~10 000 years ago (Diamond, 2002). The complex origins that led to the domestication of the modern cow have led to numerous different cattle breeds specialised for different traits, such as milk and meat products, disease and pest resistance, drafting ability and religious beliefs. The differentiation among breeds is a result of natural selection, geographical variability due to drift, and more recently, stron...

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Section: Resultsmentioning

confidence: 99%

Inference of population structure of purebred dairy and beef cattle using high-density genotype data

Kelleher

Berry

Kearney³

et al. 2017

Animal

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“…92), which takes genome-wide polymorphism data from several individuals in a population as input. The European Diversity Panel filtered VCF file with the reduced SNP set of 38 trees (the same as used in PCA and STRUCTURE analysis) was converted into Map and Ped files.…”

Section: Methodsmentioning

confidence: 99%

Genome sequence and genetic diversity of European ash trees

Sollars

Harper

Kelly

et al. 2016

Nature

178

227

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Ash trees (genus. Here we sequence the genome of a low-heterozygosity Fraxinus excelsior tree from Gloucestershire, UK, annotating 38,852 protein-coding genes of which 25% appear ash specific when compared with the genomes of ten other plant species. Analyses of paralogous genes suggest a whole-genome duplication shared with olive (Olea europaea, Oleaceae). We also re-sequence 37 F. excelsior trees from Europe, finding evidence for apparent long-term decline in effective population size. Using our reference sequence, we reanalyse association transcriptomic data 3 , yielding improved markers for reduced susceptibility to ash dieback. Surveys of these markers in British populations suggest that reduced susceptibility to ash dieback may be more widespread in Great Britain than in Denmark. We also present evidence that susceptibility of trees to H. fraxineus is associated with their iridoid glycoside levels. This rapid, integrated, multidisciplinary research response to an emerging health threat in a non-model organism opens the way for mitigation of the epidemic.

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“…LD of markers of different recombination rates sheds light on the effective size of the population in different time periods in the past (Wang, 2005). Quite a few methods (Hayes et al, 2003;Barbato et al, 2015;Mezzavilla and Ghirotto, 2015;Saura et al, 2015) have been developed to exploit the LD information from many densely spaced markers on a chromosome segment in inferring the N e at different time points in the past.…”

Section: Linkage Disequilibriummentioning

confidence: 99%

Prediction and estimation of effective population size

2016

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Effective population size (N e ) is a key parameter in population genetics. It has important applications in evolutionary biology, conservation genetics and plant and animal breeding, because it measures the rates of genetic drift and inbreeding and affects the efficacy of systematic evolutionary forces, such as mutation, selection and migration. We review the developments in predictive equations and estimation methodologies of effective size. In the prediction part, we focus on the equations for populations with different modes of reproduction, for populations under selection for unlinked or linked loci and for the specific applications to conservation genetics. In the estimation part, we focus on methods developed for estimating the current or recent effective size from molecular marker or sequence data. We discuss some underdeveloped areas in predicting and estimating N e for future research.Heredity ( INTRODUCTIONThe concept of effective population size, introduced by Sewall Wright (1931, 1933), is central to plant and animal breeding (Falconer and Mackay, 1996), conservation genetics (Frankham et al., 2010;Allendorf et al., 2013) and molecular variation and evolution (Charlesworth and Charlesworth, 2010), as it quantifies the magnitude of genetic drift and inbreeding in real-world populations. A substantial number of extensions to the basic theory and predictions were made since the seminal work of Wright, with main early developments by James Crow and Motoo Kimura (Kimura and Crow, 1963a;Crow and Kimura, 1970) and later by a list of contributors. Several review papers (Crow and Denniston, 1988;Caballero, 1994;Wang and Caballero, 1999;Nomura, 2005a) and population genetic books (Fisher, 1965;Wright, 1969;Ewens, 1979;Nagylaki, 1992) have summarised the existing theory in predicting the effective size of a population at different spatial and timescales under various inheritance modes and demographies. Comparatively, methodological developments (reviewed by Schwartz et al., 1999;Beaumont, 2003a;Wang, 2005;Palstra and Ruzzante, 2008;Luikart et al., 2010;Gilbert and Whitlock, 2015) in estimating the effective size of natural populations from genetic data lag behind but are accelerating in the past decade, thanks to the rapid developments of molecular biology.The classical developments of effective population size theory are based on the rate of change in gene frequency variance (genetic drift) or the rate of inbreeding. The effective population size is defined in reference to the Wright-Fisher idealised population, that is, a hypothetical population with very simplifying characteristics where genetic drift is the only factor in operation, and the dynamics of allelic and genotypic frequencies across generations merely depend on the population census (N) size. The effective size of a real population is then defined as the size of an idealised population, which would give rise to the rate of inbreeding and the rate of change in variance of gene frequencies actually observed in the population under consideration,

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SNeP: a tool to estimate trends in recent effective population size trajectories using genome-wide SNP data

Cited by 378 publications

References 35 publications

Inference of population structure of purebred dairy and beef cattle using high-density genotype data

Inference of population structure of purebred dairy and beef cattle using high-density genotype data

Genome sequence and genetic diversity of European ash trees

Prediction and estimation of effective population size

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