71
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Estimating genomic diversity and population differentiation – an empirical comparison of microsatellite and SNP variation in Arabidopsis halleri

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Background

          Microsatellite markers are widely used for estimating genetic diversity within and differentiation among populations. However, it has rarely been tested whether such estimates are useful proxies for genome-wide patterns of variation and differentiation. Here, we compared microsatellite variation with genome-wide single nucleotide polymorphisms (SNPs) to assess and quantify potential marker-specific biases and derive recommendations for future studies. Overall, we genotyped 180 Arabidopsis halleri individuals from nine populations using 20 microsatellite markers. Twelve of these markers were originally developed for Arabidopsis thaliana (cross-species markers) and eight for A. halleri (species-specific markers). We further characterized 2 million SNPs across the genome with a pooled whole-genome re-sequencing approach (Pool-Seq).

          Results

          Our analyses revealed that estimates of genetic diversity and differentiation derived from cross-species and species-specific microsatellites differed substantially and that expected microsatellite heterozygosity (SSR- H e) was not significantly correlated with genome-wide SNP diversity estimates (SNP- H e and θ Watterson) in A. halleri. Instead, microsatellite allelic richness ( A r) was a better proxy for genome-wide SNP diversity. Estimates of genetic differentiation among populations ( F ST) based on both marker types were correlated, but microsatellite-based estimates were significantly larger than those from SNPs. Possible causes include the limited number of microsatellite markers used, marker ascertainment bias, as well as the high variance in microsatellite-derived estimates. In contrast, genome-wide SNP data provided unbiased estimates of genetic diversity independent of whether genome- or only exome-wide SNPs were used. Further, we inferred that a few thousand random SNPs are sufficient to reliably estimate genome-wide diversity and to distinguish among populations differing in genetic variation.

          Conclusions

          We recommend that future analyses of genetic diversity within and differentiation among populations use randomly selected high-throughput sequencing-based SNP data to draw conclusions on genome-wide diversity patterns. In species comparable to A. halleri, a few thousand SNPs are sufficient to achieve this goal.

          Electronic supplementary material

          The online version of this article (doi:10.1186/s12864-016-3459-7) contains supplementary material, which is available to authorized users.

          Related collections

          Most cited references54

          • Record: found
          • Abstract: not found
          • Book: not found

          R: A Language and Environment for Statistical Computing.

            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            The rate and molecular spectrum of spontaneous mutations in Arabidopsis thaliana.

            To take complete advantage of information on within-species polymorphism and divergence from close relatives, one needs to know the rate and the molecular spectrum of spontaneous mutations. To this end, we have searched for de novo spontaneous mutations in the complete nuclear genomes of five Arabidopsis thaliana mutation accumulation lines that had been maintained by single-seed descent for 30 generations. We identified and validated 99 base substitutions and 17 small and large insertions and deletions. Our results imply a spontaneous mutation rate of 7 x 10(-9) base substitutions per site per generation, the majority of which are G:C-->A:T transitions. We explain this very biased spectrum of base substitution mutations as a result of two main processes: deamination of methylated cytosines and ultraviolet light-induced mutagenesis.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              The estimation of population differentiation with microsatellite markers.

              Microsatellite markers are routinely used to investigate the genetic structuring of natural populations. The knowledge of how genetic variation is partitioned among populations may have important implications not only in evolutionary biology and ecology, but also in conservation biology. Hence, reliable estimates of population differentiation are crucial to understand the connectivity among populations and represent important tools to develop conservation strategies. The estimation of differentiation is c from Wright's FST and/or Slatkin's RST, an FST -analogue assuming a stepwise mutation model. Both these statistics have their drawbacks. Furthermore, there is no clear consensus over their relative accuracy. In this review, we first discuss the consequences of different temporal and spatial sampling strategies on differentiation estimation. Then, we move to statistical problems directly associated with the estimation of population structuring itself, with particular emphasis on the effects of high mutation rates and mutation patterns of microsatellite loci. Finally, we discuss the biological interpretation of population structuring estimates.
                Bookmark

                Author and article information

                Contributors
                +41 44 633 93 19 , martin.fischer@env.ethz.ch
                christian.rellstab@wsl.ch
                marieleu@bluewin.ch
                marie.roumet@env.ethz.ch
                felix.gugerli@wsl.ch
                kentaro.shimizu@ieu.uzh.ch
                rolf.holderegger@wsl.ch
                alex.widmer@env.ethz.ch
                Journal
                BMC Genomics
                BMC Genomics
                BMC Genomics
                BioMed Central (London )
                1471-2164
                11 January 2017
                11 January 2017
                2017
                : 18
                : 69
                Affiliations
                [1 ]ETH Zürich, Institute of Integrative Biology, Universitätstrasse 16, 8092 Zürich, Switzerland
                [2 ]WSL Swiss Federal Research Institute, Zürcherstrasse 111, 8903 Birmensdorf, Switzerland
                [3 ]Institute of Evolutionary Biology and Environmental Studies and Institute of Plant Biology, University of Zurich, Winterthurerstrasse 190, 8057 Zürich, Switzerland
                Article
                3459
                10.1186/s12864-016-3459-7
                5225627
                28077077
                7f62e953-b9ed-4fc7-b313-5e8650b74d3d
                © The Author(s). 2017

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 1 April 2016
                : 22 December 2016
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100001711, Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung;
                Award ID: CRSI33_127155
                Award Recipient :
                Funded by: Adaptation to a Changing Environment (ACE) Fellowship, ETH Zurich
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2017

                Genetics
                microsatellites,ssr,arabidopsis halleri,genetic diversity,expected heterozygosity,snps,population genomics,whole-genome re-sequencing,pool-seq,conservation units

                Comments

                Comment on this article