Flexible and scalable genotyping-by-sequencing strategies for population studies View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2014-12

AUTHORS

Christopher Heffelfinger, Christopher A Fragoso, Maria A Moreno, John D Overton, John P Mottinger, Hongyu Zhao, Joe Tohme, Stephen L Dellaporta

ABSTRACT

BACKGROUND: Many areas critical to agricultural production and research, such as the breeding and trait mapping in plants and livestock, require robust and scalable genotyping platforms. Genotyping-by-sequencing (GBS) is a one such method highly suited to non-human organisms. In the GBS protocol, genomic DNA is fractionated via restriction digest, then reduced representation is achieved through size selection. Since many restriction sites are conserved across a species, the sequenced portion of the genome is highly consistent within a population. This makes the GBS protocol highly suited for experiments that require surveying large numbers of markers within a population, such as those involving genetic mapping, breeding, and population genomics. We have modified the GBS technology in a number of ways. Custom, enzyme specific adaptors have been replaced with standard Illumina adaptors compatible with blunt-end restriction enzymes. Multiplexing is achieved through a dual barcoding system, and bead-based library preparation protocols allows for in-solution size selection and eliminates the need for columns and gels. RESULTS: A panel of eight restriction enzymes was selected for testing on B73 maize and Nipponbare rice genomic DNA. Quality of the data was demonstrated by identifying that the vast majority of reads from each enzyme aligned to restriction sites predicted in silico. The link between enzyme parameters and experimental outcome was demonstrated by showing that the sequenced portion of the genome was adaptable by selecting enzymes based on motif length, complexity, and methylation sensitivity. The utility of the new GBS protocol was demonstrated by correctly mapping several in a maize F2 population resulting from a B73×Country Gentleman test cross. CONCLUSIONS: This technology is readily adaptable to different genomes, highly amenable to multiplexing and compatible with over forty commercially available restriction enzymes. These advancements represent a major improvement in genotyping technology by providing a highly flexible and scalable GBS that is readily implemented for studies on genome-wide variation. More... »

PAGES

979

References to SciGraph publications

  • 2010-01. Sequencing technologies — the next generation in NATURE REVIEWS GENETICS
  • 2012-07. Maize HapMap2 identifies extant variation from a genome in flux in NATURE GENETICS
  • 2013-06. Comprehensive genotyping of the USA national maize inbred seed bank in GENOME BIOLOGY
  • 1994. The Maize Handbook in NONE
  • 2014-12. An evaluation of genotyping by sequencing (GBS) to map the Breviaristatum-e (ari-e) locus in cultivated barley in BMC GENOMICS
  • 2009-09-10. Targeted capture and massively parallel sequencing of 12 human exomes in NATURE
  • 2010-12. SNP discovery by high-throughput sequencing in soybean in BMC GENOMICS
  • 2011-11. Exome sequencing as a tool for Mendelian disease gene discovery in NATURE REVIEWS GENETICS
  • 2012-08. 2b-RAD: a simple and flexible method for genome-wide genotyping in NATURE METHODS
  • 2013-12. Improved workflows for high throughput library preparation using the transposome-based nextera system in BMC BIOTECHNOLOGY
  • 2010-07. Genotype imputation for genome-wide association studies in NATURE REVIEWS GENETICS
  • 2012-04. Fast gapped-read alignment with Bowtie 2 in NATURE METHODS
  • 2013-06. Understanding the origin of species with genome-scale data: modelling gene flow in NATURE REVIEWS GENETICS
  • 2014-12. Generation of SNP datasets for orangutan population genomics using improved reduced-representation sequencing and direct comparisons of SNP calling algorithms in BMC GENOMICS
  • 2010-10-28. A map of human genome variation from population-scale sequencing in NATURE
  • 2012-09. Next-generation sequencing data interpretation: enhancing reproducibility and accessibility in NATURE REVIEWS GENETICS
  • 2013-12. Improvement of the Oryza sativa Nipponbare reference genome using next generation sequence and optical map data in RICE
  • 2011-01. A scalable, fully automated process for construction of sequence-ready human exome targeted capture libraries in GENOME BIOLOGY
  • 2012-05. Performance comparison of benchtop high-throughput sequencing platforms in NATURE BIOTECHNOLOGY
  • 2012-11. An integrated map of genetic variation from 1,092 human genomes in NATURE
  • 2011-06. Genotype and SNP calling from next-generation sequencing data in NATURE REVIEWS GENETICS
  • 2008-03. SNP discovery and allele frequency estimation by deep sequencing of reduced representation libraries in NATURE METHODS
  • 2012-01. Performance comparison of whole-genome sequencing platforms in NATURE BIOTECHNOLOGY
  • 2013-11. Bridging the genotyping gap: using genotyping by sequencing (GBS) to add high-density SNP markers and new value to traditional bi-parental mapping and breeding populations in THEORETICAL AND APPLIED GENETICS
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1186/1471-2164-15-979

    DOI

    http://dx.doi.org/10.1186/1471-2164-15-979

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1021732223

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/25406744


    Indexing Status Check whether this publication has been indexed by Scopus and Web Of Science using the SN Indexing Status Tool
    Incoming Citations Browse incoming citations for this publication using opencitations.net

    JSON-LD is the canonical representation for SciGraph data.

    TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT

    [
      {
        "@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json", 
        "about": [
          {
            "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0604", 
            "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
            "name": "Genetics", 
            "type": "DefinedTerm"
          }, 
          {
            "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/06", 
            "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
            "name": "Biological Sciences", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Base Composition", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Base Pairing", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Computer Simulation", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Crosses, Genetic", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Databases, Genetic", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Genetics, Population", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Genomics", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Genotyping Techniques", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "High-Throughput Nucleotide Sequencing", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Methylation", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Oryza", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Quantitative Trait, Heritable", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Reproducibility of Results", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Restriction Mapping", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Zea mays", 
            "type": "DefinedTerm"
          }
        ], 
        "author": [
          {
            "affiliation": {
              "alternateName": "Yale University", 
              "id": "https://www.grid.ac/institutes/grid.47100.32", 
              "name": [
                "Department of Molecular, Cellular, and Developmental Biology, Yale University, 06511, New Haven, CT, USA"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Heffelfinger", 
            "givenName": "Christopher", 
            "id": "sg:person.01200102234.05", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01200102234.05"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Yale University", 
              "id": "https://www.grid.ac/institutes/grid.47100.32", 
              "name": [
                "Department of Molecular, Cellular, and Developmental Biology, Yale University, 06511, New Haven, CT, USA", 
                "Department of Computational Biology and Bioinformatics, Yale University, 06520-8034, New Haven, CT, USA"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Fragoso", 
            "givenName": "Christopher A", 
            "id": "sg:person.01241246636.91", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01241246636.91"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Yale University", 
              "id": "https://www.grid.ac/institutes/grid.47100.32", 
              "name": [
                "Department of Molecular, Cellular, and Developmental Biology, Yale University, 06511, New Haven, CT, USA"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Moreno", 
            "givenName": "Maria A", 
            "id": "sg:person.01334452105.38", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01334452105.38"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Regeneron (United States)", 
              "id": "https://www.grid.ac/institutes/grid.418961.3", 
              "name": [
                "Yale Center for Genome Analysis, Yale University, 06516, New Haven, CT, USA", 
                "Regeneron Genetics Center, Regeneron, 10591, Tarrytown, NY, USA"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Overton", 
            "givenName": "John D", 
            "id": "sg:person.0646660007.32", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0646660007.32"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "University of Rhode Island", 
              "id": "https://www.grid.ac/institutes/grid.20431.34", 
              "name": [
                "Department of Cell and Molecular Biology, University of Rhode Island, 02881, Kingston, RI, USA"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Mottinger", 
            "givenName": "John P", 
            "id": "sg:person.074311623.91", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.074311623.91"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Yale University", 
              "id": "https://www.grid.ac/institutes/grid.47100.32", 
              "name": [
                "Department of Computational Biology and Bioinformatics, Yale University, 06520-8034, New Haven, CT, USA"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Zhao", 
            "givenName": "Hongyu", 
            "id": "sg:person.01220125371.89", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01220125371.89"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Centro Internacional de Agricultura Tropical", 
              "id": "https://www.grid.ac/institutes/grid.418348.2", 
              "name": [
                "Agrobiodiversity Research Area, Centro Internacional de Agricultura Tropical (CIAT), A.A. 6713, Cali, Colombia"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Tohme", 
            "givenName": "Joe", 
            "id": "sg:person.01221150240.30", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01221150240.30"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Yale University", 
              "id": "https://www.grid.ac/institutes/grid.47100.32", 
              "name": [
                "Department of Molecular, Cellular, and Developmental Biology, Yale University, 06511, New Haven, CT, USA"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Dellaporta", 
            "givenName": "Stephen L", 
            "id": "sg:person.0654762257.09", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0654762257.09"
            ], 
            "type": "Person"
          }
        ], 
        "citation": [
          {
            "id": "https://doi.org/10.1101/gr.115402.110", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1000102598"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nature11632", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1000661742", 
              "https://doi.org/10.1038/nature11632"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1073/pnas.151244298", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1001425614"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1002/bies.201300014", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1002532349"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/bioinformatics/btr597", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1005259061"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1371/journal.pone.0019379", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1005754650"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/ng.2313", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1005827701", 
              "https://doi.org/10.1038/ng.2313"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nmeth.1923", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1006541515", 
              "https://doi.org/10.1038/nmeth.1923"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nrg2796", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1009739594", 
              "https://doi.org/10.1038/nrg2796"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nrg2796", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1009739594", 
              "https://doi.org/10.1038/nrg2796"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nature09534", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1010608717", 
              "https://doi.org/10.1038/nature09534"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nature09534", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1010608717", 
              "https://doi.org/10.1038/nature09534"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/bioinformatics/btr477", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1010875176"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/gb-2013-14-6-r55", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1013393822", 
              "https://doi.org/10.1186/gb-2013-14-6-r55"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nbt.2065", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1015669612", 
              "https://doi.org/10.1038/nbt.2065"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nrg2986", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1016983398", 
              "https://doi.org/10.1038/nrg2986"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1146/annurev-genom-082908-150112", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1017422233"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/1471-2164-11-469", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1018455529", 
              "https://doi.org/10.1186/1471-2164-11-469"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1146/annurev.genom.9.081307.164242", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1018499775"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/bib/bbq015", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1019203929"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/bib/bbq015", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1019203929"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1126/science.1068275", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1020691036"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1371/journal.pone.0090346", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1021321243"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1101/gr.5681207", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1021863999"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/bioinformatics/btp352", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1023014918"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nrg2626", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1023911485", 
              "https://doi.org/10.1038/nrg2626"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nrg2626", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1023911485", 
              "https://doi.org/10.1038/nrg2626"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1086/321275", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1026846351"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1534/g3.112.005363", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1027862745"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1534/g3.112.005363", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1027862745"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1371/journal.pone.0074612", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1029438548"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-1-4612-2694-9", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1030382453", 
              "https://doi.org/10.1007/978-1-4612-2694-9"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-1-4612-2694-9", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1030382453", 
              "https://doi.org/10.1007/978-1-4612-2694-9"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nmeth.2023", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1030462219", 
              "https://doi.org/10.1038/nmeth.2023"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nrg3446", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1032702350", 
              "https://doi.org/10.1038/nrg3446"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nmeth.1185", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1034942023", 
              "https://doi.org/10.1038/nmeth.1185"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1371/journal.pgen.1003215", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1035247728"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1534/genetics.113.158014", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1035312886"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1534/genetics.113.158014", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1035312886"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/gbe/evr008", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1036716842"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1534/g3.113.007807", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1038540664"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1534/g3.113.007807", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1038540664"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nature08250", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1038593056", 
              "https://doi.org/10.1038/nature08250"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nature08250", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1038593056", 
              "https://doi.org/10.1038/nature08250"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1534/genetics.112.147710", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1039966655"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1534/genetics.112.147710", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1039966655"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nrg3305", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1040199034", 
              "https://doi.org/10.1038/nrg3305"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1371/journal.pone.0032253", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1041572486"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1534/g3.113.008227", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1041889342"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1534/g3.113.008227", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1041889342"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/nar/29.18.3705", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1042378558"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/1939-8433-6-4", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1043618498", 
              "https://doi.org/10.1186/1939-8433-6-4"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nbt.2198", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1043867750", 
              "https://doi.org/10.1038/nbt.2198"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00122-013-2166-x", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1043948216", 
              "https://doi.org/10.1007/s00122-013-2166-x"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1111/mec.12350", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1044019287"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/1471-2164-15-16", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1044329294", 
              "https://doi.org/10.1186/1471-2164-15-16"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1371/journal.pone.0016607", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1044987561"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/gb-2011-12-1-r1", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1045286538", 
              "https://doi.org/10.1186/gb-2011-12-1-r1"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.virusres.2013.12.028", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1045776172"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nrg3031", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1047038706", 
              "https://doi.org/10.1038/nrg3031"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1101/gr.078212.108", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1047542880"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/nar/22.21.4543", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1047873787"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1371/journal.pone.0054603", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1048447797"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1371/journal.pone.0037135", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1049371751"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/1471-2164-15-104", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1049667117", 
              "https://doi.org/10.1186/1471-2164-15-104"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/1472-6750-13-104", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1053040079", 
              "https://doi.org/10.1186/1472-6750-13-104"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1101/gr.117259.110", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1053247679"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1086/379378", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1058672120"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1086/379378", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1058672120"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1086/502802", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1058783626"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1126/science.1178534", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1062460510"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.3835/plantgenome2012.05.0005", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1071447816"
            ], 
            "type": "CreativeWork"
          }
        ], 
        "datePublished": "2014-12", 
        "datePublishedReg": "2014-12-01", 
        "description": "BACKGROUND: Many areas critical to agricultural production and research, such as the breeding and trait mapping in plants and livestock, require robust and scalable genotyping platforms. Genotyping-by-sequencing (GBS) is a one such method highly suited to non-human organisms. In the GBS protocol, genomic DNA is fractionated via restriction digest, then reduced representation is achieved through size selection. Since many restriction sites are conserved across a species, the sequenced portion of the genome is highly consistent within a population. This makes the GBS protocol highly suited for experiments that require surveying large numbers of markers within a population, such as those involving genetic mapping, breeding, and population genomics. We have modified the GBS technology in a number of ways. Custom, enzyme specific adaptors have been replaced with standard Illumina adaptors compatible with blunt-end restriction enzymes. Multiplexing is achieved through a dual barcoding system, and bead-based library preparation protocols allows for in-solution size selection and eliminates the need for columns and gels.\nRESULTS: A panel of eight restriction enzymes was selected for testing on B73 maize and Nipponbare rice genomic DNA. Quality of the data was demonstrated by identifying that the vast majority of reads from each enzyme aligned to restriction sites predicted in silico. The link between enzyme parameters and experimental outcome was demonstrated by showing that the sequenced portion of the genome was adaptable by selecting enzymes based on motif length, complexity, and methylation sensitivity. The utility of the new GBS protocol was demonstrated by correctly mapping several in a maize F2 population resulting from a B73\u00d7Country Gentleman test cross.\nCONCLUSIONS: This technology is readily adaptable to different genomes, highly amenable to multiplexing and compatible with over forty commercially available restriction enzymes. These advancements represent a major improvement in genotyping technology by providing a highly flexible and scalable GBS that is readily implemented for studies on genome-wide variation.", 
        "genre": "research_article", 
        "id": "sg:pub.10.1186/1471-2164-15-979", 
        "inLanguage": [
          "en"
        ], 
        "isAccessibleForFree": true, 
        "isFundedItemOf": [
          {
            "id": "sg:grant.2674130", 
            "type": "MonetaryGrant"
          }, 
          {
            "id": "sg:grant.2681175", 
            "type": "MonetaryGrant"
          }, 
          {
            "id": "sg:grant.2516183", 
            "type": "MonetaryGrant"
          }, 
          {
            "id": "sg:grant.2675478", 
            "type": "MonetaryGrant"
          }, 
          {
            "id": "sg:grant.2705220", 
            "type": "MonetaryGrant"
          }, 
          {
            "id": "sg:grant.3111343", 
            "type": "MonetaryGrant"
          }
        ], 
        "isPartOf": [
          {
            "id": "sg:journal.1023790", 
            "issn": [
              "1471-2164"
            ], 
            "name": "BMC Genomics", 
            "type": "Periodical"
          }, 
          {
            "issueNumber": "1", 
            "type": "PublicationIssue"
          }, 
          {
            "type": "PublicationVolume", 
            "volumeNumber": "15"
          }
        ], 
        "name": "Flexible and scalable genotyping-by-sequencing strategies for population studies", 
        "pagination": "979", 
        "productId": [
          {
            "name": "readcube_id", 
            "type": "PropertyValue", 
            "value": [
              "678ab1e636bd669da106721770a2e0df39955d7689ec6bf1b9164e671bd0d071"
            ]
          }, 
          {
            "name": "pubmed_id", 
            "type": "PropertyValue", 
            "value": [
              "25406744"
            ]
          }, 
          {
            "name": "nlm_unique_id", 
            "type": "PropertyValue", 
            "value": [
              "100965258"
            ]
          }, 
          {
            "name": "doi", 
            "type": "PropertyValue", 
            "value": [
              "10.1186/1471-2164-15-979"
            ]
          }, 
          {
            "name": "dimensions_id", 
            "type": "PropertyValue", 
            "value": [
              "pub.1021732223"
            ]
          }
        ], 
        "sameAs": [
          "https://doi.org/10.1186/1471-2164-15-979", 
          "https://app.dimensions.ai/details/publication/pub.1021732223"
        ], 
        "sdDataset": "articles", 
        "sdDatePublished": "2019-04-10T22:30", 
        "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
        "sdPublisher": {
          "name": "Springer Nature - SN SciGraph project", 
          "type": "Organization"
        }, 
        "sdSource": "s3://com-uberresearch-data-dimensions-target-20181106-alternative/cleanup/v134/2549eaecd7973599484d7c17b260dba0a4ecb94b/merge/v9/a6c9fde33151104705d4d7ff012ea9563521a3ce/jats-lookup/v90/0000000001_0000000264/records_8690_00000505.jsonl", 
        "type": "ScholarlyArticle", 
        "url": "http://link.springer.com/10.1186%2F1471-2164-15-979"
      }
    ]
     

    Download the RDF metadata as:  json-ld nt turtle xml License info

    HOW TO GET THIS DATA PROGRAMMATICALLY:

    JSON-LD is a popular format for linked data which is fully compatible with JSON.

    curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1186/1471-2164-15-979'

    N-Triples is a line-based linked data format ideal for batch operations.

    curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1186/1471-2164-15-979'

    Turtle is a human-readable linked data format.

    curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1186/1471-2164-15-979'

    RDF/XML is a standard XML format for linked data.

    curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1186/1471-2164-15-979'


     

    This table displays all metadata directly associated to this object as RDF triples.

    404 TRIPLES      21 PREDICATES      104 URIs      36 LITERALS      24 BLANK NODES

    Subject Predicate Object
    1 sg:pub.10.1186/1471-2164-15-979 schema:about N06dc7a21f0b64e4393965c26a71e0586
    2 N0738587f67ed4852994f92afd312fd2e
    3 N0e819a2e5b2c48ccb9b4012d558cc437
    4 N35bbb82d0e704329b5083ab64f5c3b60
    5 N64f9c6185ccd4c7d960fb3d935f26cfa
    6 N7a5b117f9fa946a99194ff38f6d6b2ea
    7 N7d776e101f9a4e9296613f918df574d3
    8 N828afa827ecb474d94abdbe67c22f24a
    9 N8c4d98c388694ebfa54ab484373cf254
    10 Na70db34cad6f4c01affc8c5f77f7fa84
    11 Nb008f008f72548de8ea8ac0f80462c20
    12 Nba839f92c50b4d48ba82ebe5eea2fe1a
    13 Nf7a36b5930dc44f0945288dd7559af68
    14 Nfdd2dce99b6145ff8b550cdb1c246bd1
    15 Nff649c9eda484c6daeb619b599890524
    16 anzsrc-for:06
    17 anzsrc-for:0604
    18 schema:author N1145d52d028246a980f01a403f63c339
    19 schema:citation sg:pub.10.1007/978-1-4612-2694-9
    20 sg:pub.10.1007/s00122-013-2166-x
    21 sg:pub.10.1038/nature08250
    22 sg:pub.10.1038/nature09534
    23 sg:pub.10.1038/nature11632
    24 sg:pub.10.1038/nbt.2065
    25 sg:pub.10.1038/nbt.2198
    26 sg:pub.10.1038/ng.2313
    27 sg:pub.10.1038/nmeth.1185
    28 sg:pub.10.1038/nmeth.1923
    29 sg:pub.10.1038/nmeth.2023
    30 sg:pub.10.1038/nrg2626
    31 sg:pub.10.1038/nrg2796
    32 sg:pub.10.1038/nrg2986
    33 sg:pub.10.1038/nrg3031
    34 sg:pub.10.1038/nrg3305
    35 sg:pub.10.1038/nrg3446
    36 sg:pub.10.1186/1471-2164-11-469
    37 sg:pub.10.1186/1471-2164-15-104
    38 sg:pub.10.1186/1471-2164-15-16
    39 sg:pub.10.1186/1472-6750-13-104
    40 sg:pub.10.1186/1939-8433-6-4
    41 sg:pub.10.1186/gb-2011-12-1-r1
    42 sg:pub.10.1186/gb-2013-14-6-r55
    43 https://doi.org/10.1002/bies.201300014
    44 https://doi.org/10.1016/j.virusres.2013.12.028
    45 https://doi.org/10.1073/pnas.151244298
    46 https://doi.org/10.1086/321275
    47 https://doi.org/10.1086/379378
    48 https://doi.org/10.1086/502802
    49 https://doi.org/10.1093/bib/bbq015
    50 https://doi.org/10.1093/bioinformatics/btp352
    51 https://doi.org/10.1093/bioinformatics/btr477
    52 https://doi.org/10.1093/bioinformatics/btr597
    53 https://doi.org/10.1093/gbe/evr008
    54 https://doi.org/10.1093/nar/22.21.4543
    55 https://doi.org/10.1093/nar/29.18.3705
    56 https://doi.org/10.1101/gr.078212.108
    57 https://doi.org/10.1101/gr.115402.110
    58 https://doi.org/10.1101/gr.117259.110
    59 https://doi.org/10.1101/gr.5681207
    60 https://doi.org/10.1111/mec.12350
    61 https://doi.org/10.1126/science.1068275
    62 https://doi.org/10.1126/science.1178534
    63 https://doi.org/10.1146/annurev-genom-082908-150112
    64 https://doi.org/10.1146/annurev.genom.9.081307.164242
    65 https://doi.org/10.1371/journal.pgen.1003215
    66 https://doi.org/10.1371/journal.pone.0016607
    67 https://doi.org/10.1371/journal.pone.0019379
    68 https://doi.org/10.1371/journal.pone.0032253
    69 https://doi.org/10.1371/journal.pone.0037135
    70 https://doi.org/10.1371/journal.pone.0054603
    71 https://doi.org/10.1371/journal.pone.0074612
    72 https://doi.org/10.1371/journal.pone.0090346
    73 https://doi.org/10.1534/g3.112.005363
    74 https://doi.org/10.1534/g3.113.007807
    75 https://doi.org/10.1534/g3.113.008227
    76 https://doi.org/10.1534/genetics.112.147710
    77 https://doi.org/10.1534/genetics.113.158014
    78 https://doi.org/10.3835/plantgenome2012.05.0005
    79 schema:datePublished 2014-12
    80 schema:datePublishedReg 2014-12-01
    81 schema:description BACKGROUND: Many areas critical to agricultural production and research, such as the breeding and trait mapping in plants and livestock, require robust and scalable genotyping platforms. Genotyping-by-sequencing (GBS) is a one such method highly suited to non-human organisms. In the GBS protocol, genomic DNA is fractionated via restriction digest, then reduced representation is achieved through size selection. Since many restriction sites are conserved across a species, the sequenced portion of the genome is highly consistent within a population. This makes the GBS protocol highly suited for experiments that require surveying large numbers of markers within a population, such as those involving genetic mapping, breeding, and population genomics. We have modified the GBS technology in a number of ways. Custom, enzyme specific adaptors have been replaced with standard Illumina adaptors compatible with blunt-end restriction enzymes. Multiplexing is achieved through a dual barcoding system, and bead-based library preparation protocols allows for in-solution size selection and eliminates the need for columns and gels. RESULTS: A panel of eight restriction enzymes was selected for testing on B73 maize and Nipponbare rice genomic DNA. Quality of the data was demonstrated by identifying that the vast majority of reads from each enzyme aligned to restriction sites predicted in silico. The link between enzyme parameters and experimental outcome was demonstrated by showing that the sequenced portion of the genome was adaptable by selecting enzymes based on motif length, complexity, and methylation sensitivity. The utility of the new GBS protocol was demonstrated by correctly mapping several in a maize F2 population resulting from a B73×Country Gentleman test cross. CONCLUSIONS: This technology is readily adaptable to different genomes, highly amenable to multiplexing and compatible with over forty commercially available restriction enzymes. These advancements represent a major improvement in genotyping technology by providing a highly flexible and scalable GBS that is readily implemented for studies on genome-wide variation.
    82 schema:genre research_article
    83 schema:inLanguage en
    84 schema:isAccessibleForFree true
    85 schema:isPartOf N0b3cf6982bbb4932b81cd7becbc3f1dd
    86 Nf51f1bb3ab0b493592538bdfeab5fbe5
    87 sg:journal.1023790
    88 schema:name Flexible and scalable genotyping-by-sequencing strategies for population studies
    89 schema:pagination 979
    90 schema:productId N235bc4d7e9d349738010023c1a60a539
    91 N578738c8e1d04104b25511fbb25cebca
    92 N66f56c8abe8e4e5788387de780dad3f1
    93 N7205f98a5dc44b8a9f96db14a225444d
    94 Nc1e2b36de47e4069b16dfdbf1934cbed
    95 schema:sameAs https://app.dimensions.ai/details/publication/pub.1021732223
    96 https://doi.org/10.1186/1471-2164-15-979
    97 schema:sdDatePublished 2019-04-10T22:30
    98 schema:sdLicense https://scigraph.springernature.com/explorer/license/
    99 schema:sdPublisher N5b841e0cf75e4166813542aa96c66023
    100 schema:url http://link.springer.com/10.1186%2F1471-2164-15-979
    101 sgo:license sg:explorer/license/
    102 sgo:sdDataset articles
    103 rdf:type schema:ScholarlyArticle
    104 N06dc7a21f0b64e4393965c26a71e0586 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    105 schema:name Methylation
    106 rdf:type schema:DefinedTerm
    107 N0738587f67ed4852994f92afd312fd2e schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    108 schema:name Zea mays
    109 rdf:type schema:DefinedTerm
    110 N0b3cf6982bbb4932b81cd7becbc3f1dd schema:volumeNumber 15
    111 rdf:type schema:PublicationVolume
    112 N0e819a2e5b2c48ccb9b4012d558cc437 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    113 schema:name Databases, Genetic
    114 rdf:type schema:DefinedTerm
    115 N1145d52d028246a980f01a403f63c339 rdf:first sg:person.01200102234.05
    116 rdf:rest N68159a87f6824c7eb74abdf288ae1da0
    117 N235bc4d7e9d349738010023c1a60a539 schema:name readcube_id
    118 schema:value 678ab1e636bd669da106721770a2e0df39955d7689ec6bf1b9164e671bd0d071
    119 rdf:type schema:PropertyValue
    120 N2381fa7b55a54f27b9b4d6c6588ebd60 rdf:first sg:person.0646660007.32
    121 rdf:rest N7034b765d28349038908458180d6966a
    122 N2874c61d9ab740fd858d03c0cc32f854 rdf:first sg:person.0654762257.09
    123 rdf:rest rdf:nil
    124 N2d58b389238047ac8b89c593bbf0967b rdf:first sg:person.01334452105.38
    125 rdf:rest N2381fa7b55a54f27b9b4d6c6588ebd60
    126 N35bbb82d0e704329b5083ab64f5c3b60 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    127 schema:name Computer Simulation
    128 rdf:type schema:DefinedTerm
    129 N4b3dd454b20a4a2faaad1f789de9ba1d rdf:first sg:person.01220125371.89
    130 rdf:rest N787ab7d7cb244893995980ce20225d39
    131 N578738c8e1d04104b25511fbb25cebca schema:name nlm_unique_id
    132 schema:value 100965258
    133 rdf:type schema:PropertyValue
    134 N5b841e0cf75e4166813542aa96c66023 schema:name Springer Nature - SN SciGraph project
    135 rdf:type schema:Organization
    136 N64f9c6185ccd4c7d960fb3d935f26cfa schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    137 schema:name Restriction Mapping
    138 rdf:type schema:DefinedTerm
    139 N66f56c8abe8e4e5788387de780dad3f1 schema:name pubmed_id
    140 schema:value 25406744
    141 rdf:type schema:PropertyValue
    142 N68159a87f6824c7eb74abdf288ae1da0 rdf:first sg:person.01241246636.91
    143 rdf:rest N2d58b389238047ac8b89c593bbf0967b
    144 N7034b765d28349038908458180d6966a rdf:first sg:person.074311623.91
    145 rdf:rest N4b3dd454b20a4a2faaad1f789de9ba1d
    146 N7205f98a5dc44b8a9f96db14a225444d schema:name dimensions_id
    147 schema:value pub.1021732223
    148 rdf:type schema:PropertyValue
    149 N787ab7d7cb244893995980ce20225d39 rdf:first sg:person.01221150240.30
    150 rdf:rest N2874c61d9ab740fd858d03c0cc32f854
    151 N7a5b117f9fa946a99194ff38f6d6b2ea schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    152 schema:name Genetics, Population
    153 rdf:type schema:DefinedTerm
    154 N7d776e101f9a4e9296613f918df574d3 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    155 schema:name Crosses, Genetic
    156 rdf:type schema:DefinedTerm
    157 N828afa827ecb474d94abdbe67c22f24a schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    158 schema:name Base Pairing
    159 rdf:type schema:DefinedTerm
    160 N8c4d98c388694ebfa54ab484373cf254 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    161 schema:name Base Composition
    162 rdf:type schema:DefinedTerm
    163 Na70db34cad6f4c01affc8c5f77f7fa84 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    164 schema:name Quantitative Trait, Heritable
    165 rdf:type schema:DefinedTerm
    166 Nb008f008f72548de8ea8ac0f80462c20 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    167 schema:name Reproducibility of Results
    168 rdf:type schema:DefinedTerm
    169 Nba839f92c50b4d48ba82ebe5eea2fe1a schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    170 schema:name High-Throughput Nucleotide Sequencing
    171 rdf:type schema:DefinedTerm
    172 Nc1e2b36de47e4069b16dfdbf1934cbed schema:name doi
    173 schema:value 10.1186/1471-2164-15-979
    174 rdf:type schema:PropertyValue
    175 Nf51f1bb3ab0b493592538bdfeab5fbe5 schema:issueNumber 1
    176 rdf:type schema:PublicationIssue
    177 Nf7a36b5930dc44f0945288dd7559af68 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    178 schema:name Genotyping Techniques
    179 rdf:type schema:DefinedTerm
    180 Nfdd2dce99b6145ff8b550cdb1c246bd1 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    181 schema:name Oryza
    182 rdf:type schema:DefinedTerm
    183 Nff649c9eda484c6daeb619b599890524 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    184 schema:name Genomics
    185 rdf:type schema:DefinedTerm
    186 anzsrc-for:06 schema:inDefinedTermSet anzsrc-for:
    187 schema:name Biological Sciences
    188 rdf:type schema:DefinedTerm
    189 anzsrc-for:0604 schema:inDefinedTermSet anzsrc-for:
    190 schema:name Genetics
    191 rdf:type schema:DefinedTerm
    192 sg:grant.2516183 http://pending.schema.org/fundedItem sg:pub.10.1186/1471-2164-15-979
    193 rdf:type schema:MonetaryGrant
    194 sg:grant.2674130 http://pending.schema.org/fundedItem sg:pub.10.1186/1471-2164-15-979
    195 rdf:type schema:MonetaryGrant
    196 sg:grant.2675478 http://pending.schema.org/fundedItem sg:pub.10.1186/1471-2164-15-979
    197 rdf:type schema:MonetaryGrant
    198 sg:grant.2681175 http://pending.schema.org/fundedItem sg:pub.10.1186/1471-2164-15-979
    199 rdf:type schema:MonetaryGrant
    200 sg:grant.2705220 http://pending.schema.org/fundedItem sg:pub.10.1186/1471-2164-15-979
    201 rdf:type schema:MonetaryGrant
    202 sg:grant.3111343 http://pending.schema.org/fundedItem sg:pub.10.1186/1471-2164-15-979
    203 rdf:type schema:MonetaryGrant
    204 sg:journal.1023790 schema:issn 1471-2164
    205 schema:name BMC Genomics
    206 rdf:type schema:Periodical
    207 sg:person.01200102234.05 schema:affiliation https://www.grid.ac/institutes/grid.47100.32
    208 schema:familyName Heffelfinger
    209 schema:givenName Christopher
    210 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01200102234.05
    211 rdf:type schema:Person
    212 sg:person.01220125371.89 schema:affiliation https://www.grid.ac/institutes/grid.47100.32
    213 schema:familyName Zhao
    214 schema:givenName Hongyu
    215 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01220125371.89
    216 rdf:type schema:Person
    217 sg:person.01221150240.30 schema:affiliation https://www.grid.ac/institutes/grid.418348.2
    218 schema:familyName Tohme
    219 schema:givenName Joe
    220 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01221150240.30
    221 rdf:type schema:Person
    222 sg:person.01241246636.91 schema:affiliation https://www.grid.ac/institutes/grid.47100.32
    223 schema:familyName Fragoso
    224 schema:givenName Christopher A
    225 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01241246636.91
    226 rdf:type schema:Person
    227 sg:person.01334452105.38 schema:affiliation https://www.grid.ac/institutes/grid.47100.32
    228 schema:familyName Moreno
    229 schema:givenName Maria A
    230 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01334452105.38
    231 rdf:type schema:Person
    232 sg:person.0646660007.32 schema:affiliation https://www.grid.ac/institutes/grid.418961.3
    233 schema:familyName Overton
    234 schema:givenName John D
    235 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0646660007.32
    236 rdf:type schema:Person
    237 sg:person.0654762257.09 schema:affiliation https://www.grid.ac/institutes/grid.47100.32
    238 schema:familyName Dellaporta
    239 schema:givenName Stephen L
    240 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0654762257.09
    241 rdf:type schema:Person
    242 sg:person.074311623.91 schema:affiliation https://www.grid.ac/institutes/grid.20431.34
    243 schema:familyName Mottinger
    244 schema:givenName John P
    245 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.074311623.91
    246 rdf:type schema:Person
    247 sg:pub.10.1007/978-1-4612-2694-9 schema:sameAs https://app.dimensions.ai/details/publication/pub.1030382453
    248 https://doi.org/10.1007/978-1-4612-2694-9
    249 rdf:type schema:CreativeWork
    250 sg:pub.10.1007/s00122-013-2166-x schema:sameAs https://app.dimensions.ai/details/publication/pub.1043948216
    251 https://doi.org/10.1007/s00122-013-2166-x
    252 rdf:type schema:CreativeWork
    253 sg:pub.10.1038/nature08250 schema:sameAs https://app.dimensions.ai/details/publication/pub.1038593056
    254 https://doi.org/10.1038/nature08250
    255 rdf:type schema:CreativeWork
    256 sg:pub.10.1038/nature09534 schema:sameAs https://app.dimensions.ai/details/publication/pub.1010608717
    257 https://doi.org/10.1038/nature09534
    258 rdf:type schema:CreativeWork
    259 sg:pub.10.1038/nature11632 schema:sameAs https://app.dimensions.ai/details/publication/pub.1000661742
    260 https://doi.org/10.1038/nature11632
    261 rdf:type schema:CreativeWork
    262 sg:pub.10.1038/nbt.2065 schema:sameAs https://app.dimensions.ai/details/publication/pub.1015669612
    263 https://doi.org/10.1038/nbt.2065
    264 rdf:type schema:CreativeWork
    265 sg:pub.10.1038/nbt.2198 schema:sameAs https://app.dimensions.ai/details/publication/pub.1043867750
    266 https://doi.org/10.1038/nbt.2198
    267 rdf:type schema:CreativeWork
    268 sg:pub.10.1038/ng.2313 schema:sameAs https://app.dimensions.ai/details/publication/pub.1005827701
    269 https://doi.org/10.1038/ng.2313
    270 rdf:type schema:CreativeWork
    271 sg:pub.10.1038/nmeth.1185 schema:sameAs https://app.dimensions.ai/details/publication/pub.1034942023
    272 https://doi.org/10.1038/nmeth.1185
    273 rdf:type schema:CreativeWork
    274 sg:pub.10.1038/nmeth.1923 schema:sameAs https://app.dimensions.ai/details/publication/pub.1006541515
    275 https://doi.org/10.1038/nmeth.1923
    276 rdf:type schema:CreativeWork
    277 sg:pub.10.1038/nmeth.2023 schema:sameAs https://app.dimensions.ai/details/publication/pub.1030462219
    278 https://doi.org/10.1038/nmeth.2023
    279 rdf:type schema:CreativeWork
    280 sg:pub.10.1038/nrg2626 schema:sameAs https://app.dimensions.ai/details/publication/pub.1023911485
    281 https://doi.org/10.1038/nrg2626
    282 rdf:type schema:CreativeWork
    283 sg:pub.10.1038/nrg2796 schema:sameAs https://app.dimensions.ai/details/publication/pub.1009739594
    284 https://doi.org/10.1038/nrg2796
    285 rdf:type schema:CreativeWork
    286 sg:pub.10.1038/nrg2986 schema:sameAs https://app.dimensions.ai/details/publication/pub.1016983398
    287 https://doi.org/10.1038/nrg2986
    288 rdf:type schema:CreativeWork
    289 sg:pub.10.1038/nrg3031 schema:sameAs https://app.dimensions.ai/details/publication/pub.1047038706
    290 https://doi.org/10.1038/nrg3031
    291 rdf:type schema:CreativeWork
    292 sg:pub.10.1038/nrg3305 schema:sameAs https://app.dimensions.ai/details/publication/pub.1040199034
    293 https://doi.org/10.1038/nrg3305
    294 rdf:type schema:CreativeWork
    295 sg:pub.10.1038/nrg3446 schema:sameAs https://app.dimensions.ai/details/publication/pub.1032702350
    296 https://doi.org/10.1038/nrg3446
    297 rdf:type schema:CreativeWork
    298 sg:pub.10.1186/1471-2164-11-469 schema:sameAs https://app.dimensions.ai/details/publication/pub.1018455529
    299 https://doi.org/10.1186/1471-2164-11-469
    300 rdf:type schema:CreativeWork
    301 sg:pub.10.1186/1471-2164-15-104 schema:sameAs https://app.dimensions.ai/details/publication/pub.1049667117
    302 https://doi.org/10.1186/1471-2164-15-104
    303 rdf:type schema:CreativeWork
    304 sg:pub.10.1186/1471-2164-15-16 schema:sameAs https://app.dimensions.ai/details/publication/pub.1044329294
    305 https://doi.org/10.1186/1471-2164-15-16
    306 rdf:type schema:CreativeWork
    307 sg:pub.10.1186/1472-6750-13-104 schema:sameAs https://app.dimensions.ai/details/publication/pub.1053040079
    308 https://doi.org/10.1186/1472-6750-13-104
    309 rdf:type schema:CreativeWork
    310 sg:pub.10.1186/1939-8433-6-4 schema:sameAs https://app.dimensions.ai/details/publication/pub.1043618498
    311 https://doi.org/10.1186/1939-8433-6-4
    312 rdf:type schema:CreativeWork
    313 sg:pub.10.1186/gb-2011-12-1-r1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1045286538
    314 https://doi.org/10.1186/gb-2011-12-1-r1
    315 rdf:type schema:CreativeWork
    316 sg:pub.10.1186/gb-2013-14-6-r55 schema:sameAs https://app.dimensions.ai/details/publication/pub.1013393822
    317 https://doi.org/10.1186/gb-2013-14-6-r55
    318 rdf:type schema:CreativeWork
    319 https://doi.org/10.1002/bies.201300014 schema:sameAs https://app.dimensions.ai/details/publication/pub.1002532349
    320 rdf:type schema:CreativeWork
    321 https://doi.org/10.1016/j.virusres.2013.12.028 schema:sameAs https://app.dimensions.ai/details/publication/pub.1045776172
    322 rdf:type schema:CreativeWork
    323 https://doi.org/10.1073/pnas.151244298 schema:sameAs https://app.dimensions.ai/details/publication/pub.1001425614
    324 rdf:type schema:CreativeWork
    325 https://doi.org/10.1086/321275 schema:sameAs https://app.dimensions.ai/details/publication/pub.1026846351
    326 rdf:type schema:CreativeWork
    327 https://doi.org/10.1086/379378 schema:sameAs https://app.dimensions.ai/details/publication/pub.1058672120
    328 rdf:type schema:CreativeWork
    329 https://doi.org/10.1086/502802 schema:sameAs https://app.dimensions.ai/details/publication/pub.1058783626
    330 rdf:type schema:CreativeWork
    331 https://doi.org/10.1093/bib/bbq015 schema:sameAs https://app.dimensions.ai/details/publication/pub.1019203929
    332 rdf:type schema:CreativeWork
    333 https://doi.org/10.1093/bioinformatics/btp352 schema:sameAs https://app.dimensions.ai/details/publication/pub.1023014918
    334 rdf:type schema:CreativeWork
    335 https://doi.org/10.1093/bioinformatics/btr477 schema:sameAs https://app.dimensions.ai/details/publication/pub.1010875176
    336 rdf:type schema:CreativeWork
    337 https://doi.org/10.1093/bioinformatics/btr597 schema:sameAs https://app.dimensions.ai/details/publication/pub.1005259061
    338 rdf:type schema:CreativeWork
    339 https://doi.org/10.1093/gbe/evr008 schema:sameAs https://app.dimensions.ai/details/publication/pub.1036716842
    340 rdf:type schema:CreativeWork
    341 https://doi.org/10.1093/nar/22.21.4543 schema:sameAs https://app.dimensions.ai/details/publication/pub.1047873787
    342 rdf:type schema:CreativeWork
    343 https://doi.org/10.1093/nar/29.18.3705 schema:sameAs https://app.dimensions.ai/details/publication/pub.1042378558
    344 rdf:type schema:CreativeWork
    345 https://doi.org/10.1101/gr.078212.108 schema:sameAs https://app.dimensions.ai/details/publication/pub.1047542880
    346 rdf:type schema:CreativeWork
    347 https://doi.org/10.1101/gr.115402.110 schema:sameAs https://app.dimensions.ai/details/publication/pub.1000102598
    348 rdf:type schema:CreativeWork
    349 https://doi.org/10.1101/gr.117259.110 schema:sameAs https://app.dimensions.ai/details/publication/pub.1053247679
    350 rdf:type schema:CreativeWork
    351 https://doi.org/10.1101/gr.5681207 schema:sameAs https://app.dimensions.ai/details/publication/pub.1021863999
    352 rdf:type schema:CreativeWork
    353 https://doi.org/10.1111/mec.12350 schema:sameAs https://app.dimensions.ai/details/publication/pub.1044019287
    354 rdf:type schema:CreativeWork
    355 https://doi.org/10.1126/science.1068275 schema:sameAs https://app.dimensions.ai/details/publication/pub.1020691036
    356 rdf:type schema:CreativeWork
    357 https://doi.org/10.1126/science.1178534 schema:sameAs https://app.dimensions.ai/details/publication/pub.1062460510
    358 rdf:type schema:CreativeWork
    359 https://doi.org/10.1146/annurev-genom-082908-150112 schema:sameAs https://app.dimensions.ai/details/publication/pub.1017422233
    360 rdf:type schema:CreativeWork
    361 https://doi.org/10.1146/annurev.genom.9.081307.164242 schema:sameAs https://app.dimensions.ai/details/publication/pub.1018499775
    362 rdf:type schema:CreativeWork
    363 https://doi.org/10.1371/journal.pgen.1003215 schema:sameAs https://app.dimensions.ai/details/publication/pub.1035247728
    364 rdf:type schema:CreativeWork
    365 https://doi.org/10.1371/journal.pone.0016607 schema:sameAs https://app.dimensions.ai/details/publication/pub.1044987561
    366 rdf:type schema:CreativeWork
    367 https://doi.org/10.1371/journal.pone.0019379 schema:sameAs https://app.dimensions.ai/details/publication/pub.1005754650
    368 rdf:type schema:CreativeWork
    369 https://doi.org/10.1371/journal.pone.0032253 schema:sameAs https://app.dimensions.ai/details/publication/pub.1041572486
    370 rdf:type schema:CreativeWork
    371 https://doi.org/10.1371/journal.pone.0037135 schema:sameAs https://app.dimensions.ai/details/publication/pub.1049371751
    372 rdf:type schema:CreativeWork
    373 https://doi.org/10.1371/journal.pone.0054603 schema:sameAs https://app.dimensions.ai/details/publication/pub.1048447797
    374 rdf:type schema:CreativeWork
    375 https://doi.org/10.1371/journal.pone.0074612 schema:sameAs https://app.dimensions.ai/details/publication/pub.1029438548
    376 rdf:type schema:CreativeWork
    377 https://doi.org/10.1371/journal.pone.0090346 schema:sameAs https://app.dimensions.ai/details/publication/pub.1021321243
    378 rdf:type schema:CreativeWork
    379 https://doi.org/10.1534/g3.112.005363 schema:sameAs https://app.dimensions.ai/details/publication/pub.1027862745
    380 rdf:type schema:CreativeWork
    381 https://doi.org/10.1534/g3.113.007807 schema:sameAs https://app.dimensions.ai/details/publication/pub.1038540664
    382 rdf:type schema:CreativeWork
    383 https://doi.org/10.1534/g3.113.008227 schema:sameAs https://app.dimensions.ai/details/publication/pub.1041889342
    384 rdf:type schema:CreativeWork
    385 https://doi.org/10.1534/genetics.112.147710 schema:sameAs https://app.dimensions.ai/details/publication/pub.1039966655
    386 rdf:type schema:CreativeWork
    387 https://doi.org/10.1534/genetics.113.158014 schema:sameAs https://app.dimensions.ai/details/publication/pub.1035312886
    388 rdf:type schema:CreativeWork
    389 https://doi.org/10.3835/plantgenome2012.05.0005 schema:sameAs https://app.dimensions.ai/details/publication/pub.1071447816
    390 rdf:type schema:CreativeWork
    391 https://www.grid.ac/institutes/grid.20431.34 schema:alternateName University of Rhode Island
    392 schema:name Department of Cell and Molecular Biology, University of Rhode Island, 02881, Kingston, RI, USA
    393 rdf:type schema:Organization
    394 https://www.grid.ac/institutes/grid.418348.2 schema:alternateName Centro Internacional de Agricultura Tropical
    395 schema:name Agrobiodiversity Research Area, Centro Internacional de Agricultura Tropical (CIAT), A.A. 6713, Cali, Colombia
    396 rdf:type schema:Organization
    397 https://www.grid.ac/institutes/grid.418961.3 schema:alternateName Regeneron (United States)
    398 schema:name Regeneron Genetics Center, Regeneron, 10591, Tarrytown, NY, USA
    399 Yale Center for Genome Analysis, Yale University, 06516, New Haven, CT, USA
    400 rdf:type schema:Organization
    401 https://www.grid.ac/institutes/grid.47100.32 schema:alternateName Yale University
    402 schema:name Department of Computational Biology and Bioinformatics, Yale University, 06520-8034, New Haven, CT, USA
    403 Department of Molecular, Cellular, and Developmental Biology, Yale University, 06511, New Haven, CT, USA
    404 rdf:type schema:Organization
     




    Preview window. Press ESC to close (or click here)


    ...