Blog
About

  • Record: found
  • Abstract: found
  • Article: found
Is Open Access

A Robust, Simple Genotyping-by-Sequencing (GBS) Approach for High Diversity Species

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

      Advances in next generation technologies have driven the costs of DNA sequencing down to the point that genotyping-by-sequencing (GBS) is now feasible for high diversity, large genome species. Here, we report a procedure for constructing GBS libraries based on reducing genome complexity with restriction enzymes (REs). This approach is simple, quick, extremely specific, highly reproducible, and may reach important regions of the genome that are inaccessible to sequence capture approaches. By using methylation-sensitive REs, repetitive regions of genomes can be avoided and lower copy regions targeted with two to three fold higher efficiency. This tremendously simplifies computationally challenging alignment problems in species with high levels of genetic diversity. The GBS procedure is demonstrated with maize (IBM) and barley (Oregon Wolfe Barley) recombinant inbred populations where roughly 200,000 and 25,000 sequence tags were mapped, respectively. An advantage in species like barley that lack a complete genome sequence is that a reference map need only be developed around the restriction sites, and this can be done in the process of sample genotyping. In such cases, the consensus of the read clusters across the sequence tagged sites becomes the reference. Alternatively, for kinship analyses in the absence of a reference genome, the sequence tags can simply be treated as dominant markers. Future application of GBS to breeding, conservation, and global species and population surveys may allow plant breeders to conduct genomic selection on a novel germplasm or species without first having to develop any prior molecular tools, or conservation biologists to determine population structure without prior knowledge of the genome or diversity in the species.

      Related collections

      Most cited references 41

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

      Gapped BLAST and PSI-BLAST: a new generation of protein database search programs.

      The BLAST programs are widely used tools for searching protein and DNA databases for sequence similarities. For protein comparisons, a variety of definitional, algorithmic and statistical refinements described here permits the execution time of the BLAST programs to be decreased substantially while enhancing their sensitivity to weak similarities. A new criterion for triggering the extension of word hits, combined with a new heuristic for generating gapped alignments, yields a gapped BLAST program that runs at approximately three times the speed of the original. In addition, a method is introduced for automatically combining statistically significant alignments produced by BLAST into a position-specific score matrix, and searching the database using this matrix. The resulting Position-Specific Iterated BLAST (PSI-BLAST) program runs at approximately the same speed per iteration as gapped BLAST, but in many cases is much more sensitive to weak but biologically relevant sequence similarities. PSI-BLAST is used to uncover several new and interesting members of the BRCT superfamily.
        Bookmark
        • Record: found
        • Abstract: found
        • Article: found
        Is Open Access

        Fast and accurate short read alignment with Burrows–Wheeler transform

        Motivation: The enormous amount of short reads generated by the new DNA sequencing technologies call for the development of fast and accurate read alignment programs. A first generation of hash table-based methods has been developed, including MAQ, which is accurate, feature rich and fast enough to align short reads from a single individual. However, MAQ does not support gapped alignment for single-end reads, which makes it unsuitable for alignment of longer reads where indels may occur frequently. The speed of MAQ is also a concern when the alignment is scaled up to the resequencing of hundreds of individuals. Results: We implemented Burrows-Wheeler Alignment tool (BWA), a new read alignment package that is based on backward search with Burrows–Wheeler Transform (BWT), to efficiently align short sequencing reads against a large reference sequence such as the human genome, allowing mismatches and gaps. BWA supports both base space reads, e.g. from Illumina sequencing machines, and color space reads from AB SOLiD machines. Evaluations on both simulated and real data suggest that BWA is ∼10–20× faster than MAQ, while achieving similar accuracy. In addition, BWA outputs alignment in the new standard SAM (Sequence Alignment/Map) format. Variant calling and other downstream analyses after the alignment can be achieved with the open source SAMtools software package. Availability: http://maq.sourceforge.net Contact: rd@sanger.ac.uk
          Bookmark
          • Record: found
          • Abstract: found
          • Article: not found

          Sequencing technologies - the next generation.

          Demand has never been greater for revolutionary technologies that deliver fast, inexpensive and accurate genome information. This challenge has catalysed the development of next-generation sequencing (NGS) technologies. The inexpensive production of large volumes of sequence data is the primary advantage over conventional methods. Here, I present a technical review of template preparation, sequencing and imaging, genome alignment and assembly approaches, and recent advances in current and near-term commercially available NGS instruments. I also outline the broad range of applications for NGS technologies, in addition to providing guidelines for platform selection to address biological questions of interest.
            Bookmark

            Author and article information

            Affiliations
            [1 ]Institute for Genomic Diversity, Cornell University, Ithaca, New York, United States of America
            [2 ]Computational Biology Service Unit, Cornell University, Ithaca, New York, United States of America
            [3 ]Hard Winter Wheat Genetics Research Unit, United States Department of Agriculture/Agricultural Research Service, Manhattan, Kansas, United States of America
            [4 ]Plant, Soil and Nutrition Research Unit, United States Department of Agriculture/Agricultural Research Service, Ithaca, New York, United States of America
            Temasek Life Sciences Laboratory, Singapore
            Author notes

            Conceived and designed the experiments: RJE JCG QS JAP KK ESB SEM. Performed the experiments: RJE JCG QS JAP KK. Analyzed the data: RJE JCG QS JAP ESB. Contributed reagents/materials/analysis tools: RJE JCG QS JAP ESB SEM. Wrote the paper: RJE JCG QS JAP ESB SEM.

            Contributors
            Role: Editor
            Journal
            PLoS One
            plos
            plosone
            PLoS ONE
            Public Library of Science (San Francisco, USA )
            1932-6203
            2011
            4 May 2011
            : 6
            : 5
            3087801
            21573248
            PONE-D-10-04702
            10.1371/journal.pone.0019379
            (Editor)
            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.
            Counts
            Pages: 10
            Categories
            Research Article
            Biology
            Genetics
            Heredity
            Genotypes
            Plant Genetics
            Crop Genetics
            Population Genetics
            Genetic Polymorphism
            Genomics
            Genome Complexity
            Genome Sequencing
            Plant Science
            Agronomy
            Plant Breeding
            Plant Genetics
            Plant Genomics

            Uncategorized

            Comments

            Comment on this article