48
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Prospects and limits of marker imputation in quantitative genetic studies in European elite wheat ( Triticum aestivum L.)

      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

          The main goal of our study was to investigate the implementation, prospects, and limits of marker imputation for quantitative genetic studies contrasting map-independent and map-dependent algorithms. We used a diversity panel consisting of 372 European elite wheat ( Triticum aestivum L.) varieties, which had been genotyped with SNP arrays, and performed intensive simulation studies.

          Results

          Our results clearly showed that imputation accuracy was substantially higher for map-dependent compared to map-independent methods. The accuracy of marker imputation depended strongly on the linkage disequilibrium between the markers in the reference panel and the markers to be imputed. For the decay of linkage disequilibrium present in European wheat, we concluded that around 45,000 markers are needed for low cost, low-density marker profiling. This will facilitate high imputation accuracy, also for rare alleles. Genomic selection and diversity studies profited only marginally from imputing missing values. In contrast, the power of association mapping increased substantially when missing values were imputed.

          Conclusions

          Imputing missing values is especially of interest for an economic implementation of association mapping in breeding populations.

          Electronic supplementary material

          The online version of this article (doi:10.1186/s12864-015-1366-y) contains supplementary material, which is available to authorized users.

          Related collections

          Most cited references37

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

          Structure of linkage disequilibrium and phenotypic associations in the maize genome.

          Association studies based on linkage disequilibrium (LD) can provide high resolution for identifying genes that may contribute to phenotypic variation. We report patterns of local and genome-wide LD in 102 maize inbred lines representing much of the worldwide genetic diversity used in maize breeding, and address its implications for association studies in maize. In a survey of six genes, we found that intragenic LD generally declined rapidly with distance (r(2) < 0.1 within 1500 bp), but rates of decline were highly variable among genes. This rapid decline probably reflects large effective population sizes in maize during its evolution and high levels of recombination within genes. A set of 47 simple sequence repeat (SSR) loci showed stronger evidence of genome-wide LD than did single-nucleotide polymorphisms (SNPs) in candidate genes. LD was greatly reduced but not eliminated by grouping lines into three empirically determined subpopulations. SSR data also supplied evidence that divergent artificial selection on flowering time may have played a role in generating population structure. Provided the effects of population structure are effectively controlled, this research suggests that association studies show great promise for identifying the genetic basis of important traits in maize with very high resolution.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Genotype imputation.

            Genotype imputation is now an essential tool in the analysis of genome-wide association scans. This technique allows geneticists to accurately evaluate the evidence for association at genetic markers that are not directly genotyped. Genotype imputation is particularly useful for combining results across studies that rely on different genotyping platforms but also increases the power of individual scans. Here, we review the history and theoretical underpinnings of the technique. To illustrate performance of the approach, we summarize results from several gene mapping studies. Finally, we preview the role of genotype imputation in an era when whole genome resequencing is becoming increasingly common.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Genome-wide genetic changes during modern breeding of maize.

              The success of modern maize breeding has been demonstrated by remarkable increases in productivity over the last four decades. However, the underlying genetic changes correlated with these gains remain largely unknown. We report here the sequencing of 278 temperate maize inbred lines from different stages of breeding history, including deep resequencing of 4 lines with known pedigree information. The results show that modern breeding has introduced highly dynamic genetic changes into the maize genome. Artificial selection has affected thousands of targets, including genes and non-genic regions, leading to a reduction in nucleotide diversity and an increase in the proportion of rare alleles. Genetic changes during breeding happen rapidly, with extensive variation (SNPs, indels and copy-number variants (CNVs)) occurring, even within identity-by-descent regions. Our genome-wide assessment of genetic changes during modern maize breeding provides new strategies as well as practical targets for future crop breeding and biotechnology.
                Bookmark

                Author and article information

                Contributors
                sang@ipk-gatersleben.de
                zhao@ipk-gatersleben.de
                mette@ipk-gatersleben.de
                Reiner.Bothe@kws.com
                ebmeyer@kws-lochow.de
                sharbel@ipk-gatersleben.de
                reif@ipk-gatersleben.de
                jiang@ipk-gatersleben.de
                Journal
                BMC Genomics
                BMC Genomics
                BMC Genomics
                BioMed Central (London )
                1471-2164
                11 March 2015
                11 March 2015
                2015
                : 16
                : 1
                : 168
                Affiliations
                [ ]Department of Breeding Research, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, D-06466 Stadt Seeland, Germany
                [ ]KWS LOCHOW GMBH, D-29296 Bergen, Germany
                Article
                1366
                10.1186/s12864-015-1366-y
                4364688
                25886991
                f472bc67-855b-4552-a2c1-8242814fc997
                © He et al.; licensee BioMed Central. 2015

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. 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
                : 5 November 2014
                : 20 February 2015
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2015

                Genetics
                elite wheat,map-dependent imputation,map-independent imputation,intensive simulation,genomic selection,association mapping

                Comments

                Comment on this article