153
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      A Large Maize (Zea mays L.) SNP Genotyping Array: Development and Germplasm Genotyping, and Genetic Mapping to Compare with the B73 Reference Genome

      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

          SNP genotyping arrays have been useful for many applications that require a large number of molecular markers such as high-density genetic mapping, genome-wide association studies (GWAS), and genomic selection. We report the establishment of a large maize SNP array and its use for diversity analysis and high density linkage mapping. The markers, taken from more than 800,000 SNPs, were selected to be preferentially located in genes and evenly distributed across the genome. The array was tested with a set of maize germplasm including North American and European inbred lines, parent/F1 combinations, and distantly related teosinte material. A total of 49,585 markers, including 33,417 within 17,520 different genes and 16,168 outside genes, were of good quality for genotyping, with an average failure rate of 4% and rates up to 8% in specific germplasm. To demonstrate this array's use in genetic mapping and for the independent validation of the B73 sequence assembly, two intermated maize recombinant inbred line populations – IBM (B73×Mo17) and LHRF (F2×F252) – were genotyped to establish two high density linkage maps with 20,913 and 14,524 markers respectively. 172 mapped markers were absent in the current B73 assembly and their placement can be used for future improvements of the B73 reference sequence. Colinearity of the genetic and physical maps was mostly conserved with some exceptions that suggest errors in the B73 assembly. Five major regions containing non-colinearities were identified on chromosomes 2, 3, 6, 7 and 9, and are supported by both independent genetic maps. Four additional non-colinear regions were found on the LHRF map only; they may be due to a lower density of IBM markers in those regions or to true structural rearrangements between lines. Given the array's high quality, it will be a valuable resource for maize genetics and many aspects of maize breeding.

          Related collections

          Most cited references34

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

          Genome-wide association studies for complex traits: consensus, uncertainty and challenges.

          The past year has witnessed substantial advances in understanding the genetic basis of many common phenotypes of biomedical importance. These advances have been the result of systematic, well-powered, genome-wide surveys exploring the relationships between common sequence variation and disease predisposition. This approach has revealed over 50 disease-susceptibility loci and has provided insights into the allelic architecture of multifactorial traits. At the same time, much has been learned about the successful prosecution of association studies on such a scale. This Review highlights the knowledge gained, defines areas of emerging consensus, and describes the challenges that remain as researchers seek to obtain more complete descriptions of the susceptibility architecture of biomedical traits of interest and to translate the information gathered into improvements in clinical management.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Development and Characterization of a High Density SNP Genotyping Assay for Cattle

            The success of genome-wide association (GWA) studies for the detection of sequence variation affecting complex traits in human has spurred interest in the use of large-scale high-density single nucleotide polymorphism (SNP) genotyping for the identification of quantitative trait loci (QTL) and for marker-assisted selection in model and agricultural species. A cost-effective and efficient approach for the development of a custom genotyping assay interrogating 54,001 SNP loci to support GWA applications in cattle is described. A novel algorithm for achieving a compressed inter-marker interval distribution proved remarkably successful, with median interval of 37 kb and maximum predicted gap of <350 kb. The assay was tested on a panel of 576 animals from 21 cattle breeds and six outgroup species and revealed that from 39,765 to 46,492 SNP are polymorphic within individual breeds (average minor allele frequency (MAF) ranging from 0.24 to 0.27). The assay also identified 79 putative copy number variants in cattle. Utility for GWA was demonstrated by localizing known variation for coat color and the presence/absence of horns to their correct genomic locations. The combination of SNP selection and the novel spacing algorithm allows an efficient approach for the development of high-density genotyping platforms in species having full or even moderate quality draft sequence. Aspects of the approach can be exploited in species which lack an available genome sequence. The BovineSNP50 assay described here is commercially available from Illumina and provides a robust platform for mapping disease genes and QTL in cattle.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: found
              Is Open Access

              Design of a High Density SNP Genotyping Assay in the Pig Using SNPs Identified and Characterized by Next Generation Sequencing Technology

              Background The dissection of complex traits of economic importance to the pig industry requires the availability of a significant number of genetic markers, such as single nucleotide polymorphisms (SNPs). This study was conducted to discover several hundreds of thousands of porcine SNPs using next generation sequencing technologies and use these SNPs, as well as others from different public sources, to design a high-density SNP genotyping assay. Methodology/Principal Findings A total of 19 reduced representation libraries derived from four swine breeds (Duroc, Landrace, Large White, Pietrain) and a Wild Boar population and three restriction enzymes (AluI, HaeIII and MspI) were sequenced using Illumina's Genome Analyzer (GA). The SNP discovery effort resulted in the de novo identification of over 372K SNPs. More than 549K SNPs were used to design the Illumina Porcine 60K+SNP iSelect Beadchip, now commercially available as the PorcineSNP60. A total of 64,232 SNPs were included on the Beadchip. Results from genotyping the 158 individuals used for sequencing showed a high overall SNP call rate (97.5%). Of the 62,621 loci that could be reliably scored, 58,994 were polymorphic yielding a SNP conversion success rate of 94%. The average minor allele frequency (MAF) for all scorable SNPs was 0.274. Conclusions/Significance Overall, the results of this study indicate the utility of using next generation sequencing technologies to identify large numbers of reliable SNPs. In addition, the validation of the PorcineSNP60 Beadchip demonstrated that the assay is an excellent tool that will likely be used in a variety of future studies in pigs.
                Bookmark

                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                1932-6203
                2011
                8 December 2011
                : 6
                : 12
                : e28334
                Affiliations
                [1 ]TraitGenetics GmbH, Gatersleben, Germany
                [2 ]Etude du Polymorphisme des Génomes Végétaux, INRA – CEA – Institut de Génomique – Centre National de Génotypage, Evry, France
                [3 ]Cornell University, Ithaca, New York, United States of America
                [4 ]UMR de Génétique Végétale, INRA – Université Paris-Sud – CNRS – AgroParisTech, Gif-sur-Yvette, France
                [5 ]Syngenta Biotechnology Inc., Research Triangle Park, North Carolina, United States of America
                [6 ]Illumina Inc., San Diego, California, United States of America
                [7 ]Plant Genetics Research Unit, USDA-Agricultural Research Service, Columbia, Missouri, United States of America
                [8 ]Department of Plant Breeding, Technische Universität München, Freising, Germany
                University of Guelph, Canada
                Author notes

                Conceived and designed the experiments: MWG GD ESB AC JDC MH MDM C-CS MF. Performed the experiments: GD AB M-CLP MDM. Analyzed the data: MWG GD AP JDC E-MG MH MDM MR C-CS QS HW OCM MF. Contributed reagents/materials/analysis tools: GD AB M-CLP ESB AP AC JDC E-MG JJ MDM PM MR C-CS OCM MF. Wrote the paper: MWG OCM MF.

                Article
                PONE-D-11-18026
                10.1371/journal.pone.0028334
                3234264
                22174790
                8429d8bd-ded0-44f7-a1b6-c981c928475e
                This is an open-access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.
                History
                : 14 September 2011
                : 5 November 2011
                Page count
                Pages: 15
                Categories
                Research Article
                Agriculture
                Agricultural Biotechnology
                Marker-Assisted Selection
                Crops
                Cereals
                Maize
                Biology
                Biotechnology
                Plant Biotechnology
                Marker-Assisted Selection
                Computational Biology
                Genomics
                Genome Analysis Tools
                Genetic Maps
                Genome-Wide Association Studies
                Linkage Maps
                Structural Genomics
                Population Genetics
                Genetic Polymorphism
                Genetics
                Heredity
                Complex Traits
                Linkage (Genetics)
                Quantitative Traits
                Trait Locus
                Plant Genetics
                Crop Genetics
                Population Genetics
                Genetic Polymorphism
                Genome-Wide Association Studies
                Genomics
                Genome Analysis Tools
                Genome-Wide Association Studies
                Linkage Maps
                Plant Science
                Agronomy
                Plant Breeding
                Plant Biotechnology
                Plant Genomics
                Plant Genetics
                Plant Genomics
                Population Biology
                Population Genetics
                Genetic Polymorphism

                Uncategorized
                Uncategorized

                Comments

                Comment on this article