Population structure at different minor allele frequency levels

Cruz, Omar De la; Raska, Paola

doi:10.1186/1753-6561-8-s1-s55

Cited by 28 publications

(26 citation statements)

References 9 publications

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“…After SNPs were successfully identified, one SNP genotype per locus was exported from Stacks using the populations tool, retaining only SNPs with a minimum genotyping rate of 75% (−r 0.75) and a minimum minor allele frequency (MAF) of 3.3% (−min_maf 0.033), the lowest detectable MAF in at least one population of each species, following Massatti and Knowles (). Minimum MAF is an important parameter to consider because it can impact inference of genetic structure (De la Cruz & Raska, ). We therefore explored preliminary principal component (PC) analyses (see below) with minimum MAF = 1% and 5%, but found that using the higher minimum MAF (5%) made little qualitative difference in preliminary results.…”

Section: Methodsmentioning

confidence: 99%

Genomic evidence of a widespread southern distribution during the Last Glacial Maximum for two eastern North American hickory species

Bemmels

Dick

2018

Journal of Biogeography

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Aim Phylogeographical studies of temperate forest taxa often infer complex histories involving population subdivision into distinct refugia during the Last Glacial Maximum (LGM). However, some temperate deciduous trees may have been broadly distributed in southeastern North America during the LGM. We investigate genome‐wide genetic structure in two widespread eastern North American tree species to determine if range expansion from genetically isolated refugia or from a broader, less genetically subdivided region better explains their post‐glacial history. Location Eastern North America (ENA). Taxa Bitternut hickory (Carya cordiformis [Wangenh.] K.Koch) and shagbark hickory (Carya ovata [Mill.] K.Koch). Methods Genetic diversity and differentiation indices were calculated from >1,000 nuclear SNP loci genotyped in ca. 180 individuals per species sampled across ENA. Genetic structure was investigated using principle component analysis and genetic clustering algorithms. As an additional tool for inference, areas of suitable habitat during the LGM were predicted using species distribution models (SDMs). Results Populations across all latitudes showed similar levels of genetic diversity. Most genetic variation was weakly differentiated across ENA, with the exception of an outlier population of Carya ovata in Texas. Genetic structure in each species exhibited an isolation‐by‐distance pattern. SDMs predicted high LGM habitat suitability over much of the southeastern United States. Main conclusions Both hickory species likely survived the LGM in low‐density populations that were broadly distributed across southeastern North America and not highly genetically differentiated, except that the range‐edge Texas population of Carya ovata may represent a separate glacial refugium. Over most of ENA, genetic structure in both species is best explained by simple latitudinal range shifts and high gene flow among populations, rather than expansions from multiple, genetically isolated refugia as is characteristic of taxa from other Northern Hemisphere temperate regions of the world.

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Section: Methodsmentioning

confidence: 99%

Genomic evidence of a widespread southern distribution during the Last Glacial Maximum for two eastern North American hickory species

Bemmels

Dick

2018

Journal of Biogeography

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“…Indeed, it has been shown that nonsynonymous SNPs are more likely to have a MAF less than 0.05 (Cargill et al, 1999) and alleles associated with environment can be significantly rarer than the average allele (Fournier-Level et al, 2011). In addition, studies including minor alleles with very However, SNPs with a low MAF may contribute to inconstant population structure estimates (De la Cruz & Raska, 2014;Mathieson & McVean, 2012). This can be overcome by removing minor alleles below the 0.05 threshold when estimating population structure.…”

Section: Variation In Sequencing Approaches and Genome Samplingmentioning

confidence: 99%

The search for loci under selection: trends, biases and progress

et al. 2018

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Detecting genetic variants under selection using F outlier analysis (OA) and environmental association analyses (EAAs) are popular approaches that provide insight into the genetic basis of local adaptation. Despite the frequent use of OA and EAA approaches and their increasing attractiveness for detecting signatures of selection, their application to field-based empirical data have not been synthesized. Here, we review 66 empirical studies that use Single Nucleotide Polymorphisms (SNPs) in OA and EAA. We report trends and biases across biological systems, sequencing methods, approaches, parameters, environmental variables and their influence on detecting signatures of selection. We found striking variability in both the use and reporting of environmental data and statistical parameters. For example, linkage disequilibrium among SNPs and numbers of unique SNP associations identified with EAA were rarely reported. The proportion of putatively adaptive SNPs detected varied widely among studies, and decreased with the number of SNPs analysed. We found that genomic sampling effort had a greater impact than biological sampling effort on the proportion of identified SNPs under selection. OA identified a higher proportion of outliers when more individuals were sampled, but this was not the case for EAA. To facilitate repeatability, interpretation and synthesis of studies detecting selection, we recommend that future studies consistently report geographical coordinates, environmental data, model parameters, linkage disequilibrium, and measures of genetic structure. Identifying standards for how OA and EAA studies are designed and reported will aid future transparency and comparability of SNP-based selection studies and help to progress landscape and evolutionary genomics.

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“…present in less than one per thousand people). These rare variants tend to be geographically restricted 29,30 or even private to an individual or family (Box 2). Rare variants also tend to be younger than common variants 31 .…”

Section: Rare Variants Deleterious Variantsmentioning

confidence: 99%

Estimating the mutation load in human genomes

et al. 2015

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Next-generation sequencing technology has facilitated the discovery of millions of variants in human genomes. A sizeable fraction of these alleles are thought to be deleterious. We review the pattern of deleterious alleles as ascertained in genomic data and ask whether human populations differ in their predicted burden of deleterious alleles, a phenomenon known as “mutation load.” We discuss three demographic models that are predicted to affect mutation load and relate these models to the evidence (or the lack thereof) for variation in the efficacy of purifying selection in diverse human genomes. We also discuss why accurate estimation of mutation load depends on assumptions regarding the distribution of dominance and selection coefficients, quantities that are poorly characterized for current genomic datasets.

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Population structure at different minor allele frequency levels

Cited by 28 publications

References 9 publications

Genomic evidence of a widespread southern distribution during the Last Glacial Maximum for two eastern North American hickory species

Genomic evidence of a widespread southern distribution during the Last Glacial Maximum for two eastern North American hickory species

The search for loci under selection: trends, biases and progress

Estimating the mutation load in human genomes

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