Ab initio reconstruction of cell type–specific transcriptomes in mouse reveals the conserved multi-exonic structure of lincRNAs View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2010-05

AUTHORS

Mitchell Guttman, Manuel Garber, Joshua Z Levin, Julie Donaghey, James Robinson, Xian Adiconis, Lin Fan, Magdalena J Koziol, Andreas Gnirke, Chad Nusbaum, John L Rinn, Eric S Lander, Aviv Regev

ABSTRACT

Massively parallel cDNA sequencing (RNA-Seq) provides an unbiased way to study a transcriptome, including both coding and noncoding genes. Until now, most RNA-Seq studies have depended crucially on existing annotations and thus focused on expression levels and variation in known transcripts. Here, we present Scripture, a method to reconstruct the transcriptome of a mammalian cell using only RNA-Seq reads and the genome sequence. We applied it to mouse embryonic stem cells, neuronal precursor cells and lung fibroblasts to accurately reconstruct the full-length gene structures for most known expressed genes. We identified substantial variation in protein coding genes, including thousands of novel 5' start sites, 3' ends and internal coding exons. We then determined the gene structures of more than a thousand large intergenic noncoding RNA (lincRNA) and antisense loci. Our results open the way to direct experimental manipulation of thousands of noncoding RNAs and demonstrate the power of ab initio reconstruction to render a comprehensive picture of mammalian transcriptomes. More... »

PAGES

503

Identifiers

URI

http://scigraph.springernature.com/pub.10.1038/nbt.1633

DOI

http://dx.doi.org/10.1038/nbt.1633

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1025339324

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/20436462


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": "Animals", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Cell Line", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Computational Biology", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "DNA, Intergenic", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Embryonic Stem Cells", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Gene Expression Profiling", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Gene Library", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Mice", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Models, Genetic", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "RNA, Messenger", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Sequence Analysis, RNA", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Transcription, Genetic", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Massachusetts Institute of Technology", 
          "id": "https://www.grid.ac/institutes/grid.116068.8", 
          "name": [
            "Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA.", 
            "Department of Biology, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA."
          ], 
          "type": "Organization"
        }, 
        "familyName": "Guttman", 
        "givenName": "Mitchell", 
        "id": "sg:person.013620551417.54", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013620551417.54"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Broad Institute", 
          "id": "https://www.grid.ac/institutes/grid.66859.34", 
          "name": [
            "Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA."
          ], 
          "type": "Organization"
        }, 
        "familyName": "Garber", 
        "givenName": "Manuel", 
        "id": "sg:person.01213005106.80", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01213005106.80"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Broad Institute", 
          "id": "https://www.grid.ac/institutes/grid.66859.34", 
          "name": [
            "Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA."
          ], 
          "type": "Organization"
        }, 
        "familyName": "Levin", 
        "givenName": "Joshua Z", 
        "id": "sg:person.01222432021.01", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01222432021.01"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Broad Institute", 
          "id": "https://www.grid.ac/institutes/grid.66859.34", 
          "name": [
            "Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA."
          ], 
          "type": "Organization"
        }, 
        "familyName": "Donaghey", 
        "givenName": "Julie", 
        "id": "sg:person.01333761720.00", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01333761720.00"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Broad Institute", 
          "id": "https://www.grid.ac/institutes/grid.66859.34", 
          "name": [
            "Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA."
          ], 
          "type": "Organization"
        }, 
        "familyName": "Robinson", 
        "givenName": "James", 
        "id": "sg:person.01277446770.81", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01277446770.81"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Broad Institute", 
          "id": "https://www.grid.ac/institutes/grid.66859.34", 
          "name": [
            "Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA."
          ], 
          "type": "Organization"
        }, 
        "familyName": "Adiconis", 
        "givenName": "Xian", 
        "id": "sg:person.01000014215.36", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01000014215.36"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Broad Institute", 
          "id": "https://www.grid.ac/institutes/grid.66859.34", 
          "name": [
            "Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA."
          ], 
          "type": "Organization"
        }, 
        "familyName": "Fan", 
        "givenName": "Lin", 
        "id": "sg:person.0650451313.47", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0650451313.47"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Beth Israel Deaconess Medical Center", 
          "id": "https://www.grid.ac/institutes/grid.239395.7", 
          "name": [
            "Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA.", 
            "Department of Pathology, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA."
          ], 
          "type": "Organization"
        }, 
        "familyName": "Koziol", 
        "givenName": "Magdalena J", 
        "id": "sg:person.0640342011.25", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0640342011.25"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Broad Institute", 
          "id": "https://www.grid.ac/institutes/grid.66859.34", 
          "name": [
            "Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA."
          ], 
          "type": "Organization"
        }, 
        "familyName": "Gnirke", 
        "givenName": "Andreas", 
        "id": "sg:person.0645200471.91", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0645200471.91"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Broad Institute", 
          "id": "https://www.grid.ac/institutes/grid.66859.34", 
          "name": [
            "Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA."
          ], 
          "type": "Organization"
        }, 
        "familyName": "Nusbaum", 
        "givenName": "Chad", 
        "id": "sg:person.01170225154.35", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01170225154.35"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Beth Israel Deaconess Medical Center", 
          "id": "https://www.grid.ac/institutes/grid.239395.7", 
          "name": [
            "Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA.", 
            "Department of Pathology, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA."
          ], 
          "type": "Organization"
        }, 
        "familyName": "Rinn", 
        "givenName": "John L", 
        "id": "sg:person.015653074047.50", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015653074047.50"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Harvard University", 
          "id": "https://www.grid.ac/institutes/grid.38142.3c", 
          "name": [
            "Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA.", 
            "Department of Biology, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.", 
            "Department of Systems Biology, Harvard Medical School, Boston, Massachusetts, USA."
          ], 
          "type": "Organization"
        }, 
        "familyName": "Lander", 
        "givenName": "Eric S", 
        "id": "sg:person.01260666165.62", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01260666165.62"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Massachusetts Institute of Technology", 
          "id": "https://www.grid.ac/institutes/grid.116068.8", 
          "name": [
            "Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA.", 
            "Department of Biology, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.", 
            "Howard Hughes Medical Institute, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA."
          ], 
          "type": "Organization"
        }, 
        "familyName": "Regev", 
        "givenName": "Aviv", 
        "id": "sg:person.01311753732.26", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01311753732.26"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "https://doi.org/10.1126/science.1138341", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1002326113"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1371/journal.pcbi.1000598", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1005301630"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/nar/gkl842", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1008035809"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nature07638", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1009442631", 
          "https://doi.org/10.1038/nature07638"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/bioinformatics/btp120", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1012425816"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/bioinformatics/btp367", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1015468380"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/gb-2008-9-12-r175", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1016469219", 
          "https://doi.org/10.1186/gb-2008-9-12-r175"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.cell.2008.03.029", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1020929996"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1073/pnas.0904715106", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1022579887"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1126/science.1115901", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1024645561"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nature07509", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1029002744", 
          "https://doi.org/10.1038/nature07509"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1073/pnas.0914114107", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1033167226"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nature06008", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1036216819", 
          "https://doi.org/10.1038/nature06008"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1126/science.1163045", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1038655698"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/bioinformatics/btp190", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1041785738"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1126/science.1103388", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1042123507"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1101/gr.6679507", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1043091736"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1371/journal.pbio.0030283", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1045076866"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1371/journal.pbio.0030283", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1045076866"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1073/pnas.0812841106", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1045146500"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nmeth.1226", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1045381177", 
          "https://doi.org/10.1038/nmeth.1226"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1371/journal.pcbi.1000067", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1047797581"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1126/science.1112009", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1048209390"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nmeth.1223", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1048586936", 
          "https://doi.org/10.1038/nmeth.1223"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1101/gr.103697.109", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1049494483"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/gb-2009-10-3-r25", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1049583368", 
          "https://doi.org/10.1186/gb-2009-10-3-r25"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/ng.259", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1050283464", 
          "https://doi.org/10.1038/ng.259"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nature07672", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1051133532", 
          "https://doi.org/10.1038/nature07672"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.cell.2007.05.022", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1051644950"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1126/science.1112014", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1052847323"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/349038a0", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1053275082", 
          "https://doi.org/10.1038/349038a0"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2010-05", 
    "datePublishedReg": "2010-05-01", 
    "description": "Massively parallel cDNA sequencing (RNA-Seq) provides an unbiased way to study a transcriptome, including both coding and noncoding genes. Until now, most RNA-Seq studies have depended crucially on existing annotations and thus focused on expression levels and variation in known transcripts. Here, we present Scripture, a method to reconstruct the transcriptome of a mammalian cell using only RNA-Seq reads and the genome sequence. We applied it to mouse embryonic stem cells, neuronal precursor cells and lung fibroblasts to accurately reconstruct the full-length gene structures for most known expressed genes. We identified substantial variation in protein coding genes, including thousands of novel 5' start sites, 3' ends and internal coding exons. We then determined the gene structures of more than a thousand large intergenic noncoding RNA (lincRNA) and antisense loci. Our results open the way to direct experimental manipulation of thousands of noncoding RNAs and demonstrate the power of ab initio reconstruction to render a comprehensive picture of mammalian transcriptomes.", 
    "genre": "research_article", 
    "id": "sg:pub.10.1038/nbt.1633", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": true, 
    "isFundedItemOf": [
      {
        "id": "sg:grant.2529375", 
        "type": "MonetaryGrant"
      }, 
      {
        "id": "sg:grant.2355082", 
        "type": "MonetaryGrant"
      }, 
      {
        "id": "sg:grant.2699326", 
        "type": "MonetaryGrant"
      }
    ], 
    "isPartOf": [
      {
        "id": "sg:journal.1115214", 
        "issn": [
          "1087-0156", 
          "1546-1696"
        ], 
        "name": "Nature Biotechnology", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "5", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "28"
      }
    ], 
    "name": "Ab initio reconstruction of cell type\u2013specific transcriptomes in mouse reveals the conserved multi-exonic structure of lincRNAs", 
    "pagination": "503", 
    "productId": [
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "78b7b20b215e850fe1b7177b984a3f9d73346005191658830267ed449e881706"
        ]
      }, 
      {
        "name": "pubmed_id", 
        "type": "PropertyValue", 
        "value": [
          "20436462"
        ]
      }, 
      {
        "name": "nlm_unique_id", 
        "type": "PropertyValue", 
        "value": [
          "9604648"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1038/nbt.1633"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1025339324"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1038/nbt.1633", 
      "https://app.dimensions.ai/details/publication/pub.1025339324"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-11T00:56", 
    "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_8697_00000435.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "https://www.nature.com/articles/nbt.1633"
  }
]
 

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.10.1038/nbt.1633'

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

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1038/nbt.1633'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1038/nbt.1633'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1038/nbt.1633'


 

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

321 TRIPLES      21 PREDICATES      71 URIs      33 LITERALS      21 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1038/nbt.1633 schema:about N16cb61857d7845049c61b2d58cfcab62
2 N1d70a81a03404c35bb9e13579e001088
3 N3f0f29f1b46a404f8a49a7190c63bb39
4 N4b9aeaefa8b343de8b6bb905c857b65b
5 N749162c1cbc747c28924d607e9c3775a
6 N760360fc8c2d456e9460ff2a1c8707e3
7 N795a004ac02c48779eb653189ebd9268
8 N9494c22dfc474e4782b47b21375d032e
9 Nca8725b2e585440faaf2c64846abc981
10 Ncc40410f39ac4dfab0823192817c427f
11 Nd61c59579f9847388f22643ce636c4ba
12 Ne229a27af7ce4314a6aea54c8a768158
13 anzsrc-for:06
14 anzsrc-for:0604
15 schema:author Nc8216bbc8fb34b669685575f81106774
16 schema:citation sg:pub.10.1038/349038a0
17 sg:pub.10.1038/nature06008
18 sg:pub.10.1038/nature07509
19 sg:pub.10.1038/nature07638
20 sg:pub.10.1038/nature07672
21 sg:pub.10.1038/ng.259
22 sg:pub.10.1038/nmeth.1223
23 sg:pub.10.1038/nmeth.1226
24 sg:pub.10.1186/gb-2008-9-12-r175
25 sg:pub.10.1186/gb-2009-10-3-r25
26 https://doi.org/10.1016/j.cell.2007.05.022
27 https://doi.org/10.1016/j.cell.2008.03.029
28 https://doi.org/10.1073/pnas.0812841106
29 https://doi.org/10.1073/pnas.0904715106
30 https://doi.org/10.1073/pnas.0914114107
31 https://doi.org/10.1093/bioinformatics/btp120
32 https://doi.org/10.1093/bioinformatics/btp190
33 https://doi.org/10.1093/bioinformatics/btp367
34 https://doi.org/10.1093/nar/gkl842
35 https://doi.org/10.1101/gr.103697.109
36 https://doi.org/10.1101/gr.6679507
37 https://doi.org/10.1126/science.1103388
38 https://doi.org/10.1126/science.1112009
39 https://doi.org/10.1126/science.1112014
40 https://doi.org/10.1126/science.1115901
41 https://doi.org/10.1126/science.1138341
42 https://doi.org/10.1126/science.1163045
43 https://doi.org/10.1371/journal.pbio.0030283
44 https://doi.org/10.1371/journal.pcbi.1000067
45 https://doi.org/10.1371/journal.pcbi.1000598
46 schema:datePublished 2010-05
47 schema:datePublishedReg 2010-05-01
48 schema:description Massively parallel cDNA sequencing (RNA-Seq) provides an unbiased way to study a transcriptome, including both coding and noncoding genes. Until now, most RNA-Seq studies have depended crucially on existing annotations and thus focused on expression levels and variation in known transcripts. Here, we present Scripture, a method to reconstruct the transcriptome of a mammalian cell using only RNA-Seq reads and the genome sequence. We applied it to mouse embryonic stem cells, neuronal precursor cells and lung fibroblasts to accurately reconstruct the full-length gene structures for most known expressed genes. We identified substantial variation in protein coding genes, including thousands of novel 5' start sites, 3' ends and internal coding exons. We then determined the gene structures of more than a thousand large intergenic noncoding RNA (lincRNA) and antisense loci. Our results open the way to direct experimental manipulation of thousands of noncoding RNAs and demonstrate the power of ab initio reconstruction to render a comprehensive picture of mammalian transcriptomes.
49 schema:genre research_article
50 schema:inLanguage en
51 schema:isAccessibleForFree true
52 schema:isPartOf N17095edee9ec4b4f8d24a8a4f8bca86e
53 N5a8cfa00bd234a5f854fda7e4efa0881
54 sg:journal.1115214
55 schema:name Ab initio reconstruction of cell type–specific transcriptomes in mouse reveals the conserved multi-exonic structure of lincRNAs
56 schema:pagination 503
57 schema:productId N1ae82e19e66e468080657a99a9d772d4
58 N871621c73eaf424d9a12e2747d4ca623
59 N8af5a72f69a14d528e3cb97651ffc8e8
60 Neb3f3dd4fbec42fe9b8e82c768db03ec
61 Nfa6e4e784cb0451e8036045041930861
62 schema:sameAs https://app.dimensions.ai/details/publication/pub.1025339324
63 https://doi.org/10.1038/nbt.1633
64 schema:sdDatePublished 2019-04-11T00:56
65 schema:sdLicense https://scigraph.springernature.com/explorer/license/
66 schema:sdPublisher N9c411bc6d0d74a069de2a07f0883f573
67 schema:url https://www.nature.com/articles/nbt.1633
68 sgo:license sg:explorer/license/
69 sgo:sdDataset articles
70 rdf:type schema:ScholarlyArticle
71 N16cb61857d7845049c61b2d58cfcab62 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
72 schema:name Transcription, Genetic
73 rdf:type schema:DefinedTerm
74 N17095edee9ec4b4f8d24a8a4f8bca86e schema:issueNumber 5
75 rdf:type schema:PublicationIssue
76 N1ae82e19e66e468080657a99a9d772d4 schema:name doi
77 schema:value 10.1038/nbt.1633
78 rdf:type schema:PropertyValue
79 N1d70a81a03404c35bb9e13579e001088 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
80 schema:name DNA, Intergenic
81 rdf:type schema:DefinedTerm
82 N233b75c4aff84bd49ebb1403f4556f60 rdf:first sg:person.0645200471.91
83 rdf:rest Nc75d66649c0346c5a10fd3b51405f0b2
84 N26df0129a4e145efa678fd5ae6f4de29 rdf:first sg:person.01000014215.36
85 rdf:rest N8336e6f91ef94eb59a9812859e204519
86 N3f0f29f1b46a404f8a49a7190c63bb39 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
87 schema:name RNA, Messenger
88 rdf:type schema:DefinedTerm
89 N4b9aeaefa8b343de8b6bb905c857b65b schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
90 schema:name Sequence Analysis, RNA
91 rdf:type schema:DefinedTerm
92 N5a8cfa00bd234a5f854fda7e4efa0881 schema:volumeNumber 28
93 rdf:type schema:PublicationVolume
94 N749162c1cbc747c28924d607e9c3775a schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
95 schema:name Embryonic Stem Cells
96 rdf:type schema:DefinedTerm
97 N760360fc8c2d456e9460ff2a1c8707e3 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
98 schema:name Computational Biology
99 rdf:type schema:DefinedTerm
100 N795a004ac02c48779eb653189ebd9268 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
101 schema:name Animals
102 rdf:type schema:DefinedTerm
103 N8336e6f91ef94eb59a9812859e204519 rdf:first sg:person.0650451313.47
104 rdf:rest Nfff064e0990246049865efa3a2cb7d35
105 N86496a31a31946228351830804ff911c rdf:first sg:person.01213005106.80
106 rdf:rest Nb25f16bcd22948f3b8cc2941e009db6f
107 N871621c73eaf424d9a12e2747d4ca623 schema:name pubmed_id
108 schema:value 20436462
109 rdf:type schema:PropertyValue
110 N8af5a72f69a14d528e3cb97651ffc8e8 schema:name nlm_unique_id
111 schema:value 9604648
112 rdf:type schema:PropertyValue
113 N9494c22dfc474e4782b47b21375d032e schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
114 schema:name Gene Library
115 rdf:type schema:DefinedTerm
116 N951948dca8c0423d803dbea9ad61d4f1 rdf:first sg:person.01333761720.00
117 rdf:rest Ne06b51d9353b4f19b1912508a7f0f968
118 N9c411bc6d0d74a069de2a07f0883f573 schema:name Springer Nature - SN SciGraph project
119 rdf:type schema:Organization
120 Nb25f16bcd22948f3b8cc2941e009db6f rdf:first sg:person.01222432021.01
121 rdf:rest N951948dca8c0423d803dbea9ad61d4f1
122 Nc75d66649c0346c5a10fd3b51405f0b2 rdf:first sg:person.01170225154.35
123 rdf:rest Ncf9b1a1e8e514821b111e367862bc38b
124 Nc8216bbc8fb34b669685575f81106774 rdf:first sg:person.013620551417.54
125 rdf:rest N86496a31a31946228351830804ff911c
126 Nca8725b2e585440faaf2c64846abc981 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
127 schema:name Mice
128 rdf:type schema:DefinedTerm
129 Ncc40410f39ac4dfab0823192817c427f schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
130 schema:name Models, Genetic
131 rdf:type schema:DefinedTerm
132 Ncf9b1a1e8e514821b111e367862bc38b rdf:first sg:person.015653074047.50
133 rdf:rest Nfcd460190b0d447db6777c851c048f44
134 Nd61c59579f9847388f22643ce636c4ba schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
135 schema:name Cell Line
136 rdf:type schema:DefinedTerm
137 Ne06b51d9353b4f19b1912508a7f0f968 rdf:first sg:person.01277446770.81
138 rdf:rest N26df0129a4e145efa678fd5ae6f4de29
139 Ne229a27af7ce4314a6aea54c8a768158 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
140 schema:name Gene Expression Profiling
141 rdf:type schema:DefinedTerm
142 Neb3f3dd4fbec42fe9b8e82c768db03ec schema:name dimensions_id
143 schema:value pub.1025339324
144 rdf:type schema:PropertyValue
145 Nf57986fed1a14f938bcd02c3f080e876 rdf:first sg:person.01311753732.26
146 rdf:rest rdf:nil
147 Nfa6e4e784cb0451e8036045041930861 schema:name readcube_id
148 schema:value 78b7b20b215e850fe1b7177b984a3f9d73346005191658830267ed449e881706
149 rdf:type schema:PropertyValue
150 Nfcd460190b0d447db6777c851c048f44 rdf:first sg:person.01260666165.62
151 rdf:rest Nf57986fed1a14f938bcd02c3f080e876
152 Nfff064e0990246049865efa3a2cb7d35 rdf:first sg:person.0640342011.25
153 rdf:rest N233b75c4aff84bd49ebb1403f4556f60
154 anzsrc-for:06 schema:inDefinedTermSet anzsrc-for:
155 schema:name Biological Sciences
156 rdf:type schema:DefinedTerm
157 anzsrc-for:0604 schema:inDefinedTermSet anzsrc-for:
158 schema:name Genetics
159 rdf:type schema:DefinedTerm
160 sg:grant.2355082 http://pending.schema.org/fundedItem sg:pub.10.1038/nbt.1633
161 rdf:type schema:MonetaryGrant
162 sg:grant.2529375 http://pending.schema.org/fundedItem sg:pub.10.1038/nbt.1633
163 rdf:type schema:MonetaryGrant
164 sg:grant.2699326 http://pending.schema.org/fundedItem sg:pub.10.1038/nbt.1633
165 rdf:type schema:MonetaryGrant
166 sg:journal.1115214 schema:issn 1087-0156
167 1546-1696
168 schema:name Nature Biotechnology
169 rdf:type schema:Periodical
170 sg:person.01000014215.36 schema:affiliation https://www.grid.ac/institutes/grid.66859.34
171 schema:familyName Adiconis
172 schema:givenName Xian
173 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01000014215.36
174 rdf:type schema:Person
175 sg:person.01170225154.35 schema:affiliation https://www.grid.ac/institutes/grid.66859.34
176 schema:familyName Nusbaum
177 schema:givenName Chad
178 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01170225154.35
179 rdf:type schema:Person
180 sg:person.01213005106.80 schema:affiliation https://www.grid.ac/institutes/grid.66859.34
181 schema:familyName Garber
182 schema:givenName Manuel
183 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01213005106.80
184 rdf:type schema:Person
185 sg:person.01222432021.01 schema:affiliation https://www.grid.ac/institutes/grid.66859.34
186 schema:familyName Levin
187 schema:givenName Joshua Z
188 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01222432021.01
189 rdf:type schema:Person
190 sg:person.01260666165.62 schema:affiliation https://www.grid.ac/institutes/grid.38142.3c
191 schema:familyName Lander
192 schema:givenName Eric S
193 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01260666165.62
194 rdf:type schema:Person
195 sg:person.01277446770.81 schema:affiliation https://www.grid.ac/institutes/grid.66859.34
196 schema:familyName Robinson
197 schema:givenName James
198 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01277446770.81
199 rdf:type schema:Person
200 sg:person.01311753732.26 schema:affiliation https://www.grid.ac/institutes/grid.116068.8
201 schema:familyName Regev
202 schema:givenName Aviv
203 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01311753732.26
204 rdf:type schema:Person
205 sg:person.01333761720.00 schema:affiliation https://www.grid.ac/institutes/grid.66859.34
206 schema:familyName Donaghey
207 schema:givenName Julie
208 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01333761720.00
209 rdf:type schema:Person
210 sg:person.013620551417.54 schema:affiliation https://www.grid.ac/institutes/grid.116068.8
211 schema:familyName Guttman
212 schema:givenName Mitchell
213 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013620551417.54
214 rdf:type schema:Person
215 sg:person.015653074047.50 schema:affiliation https://www.grid.ac/institutes/grid.239395.7
216 schema:familyName Rinn
217 schema:givenName John L
218 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015653074047.50
219 rdf:type schema:Person
220 sg:person.0640342011.25 schema:affiliation https://www.grid.ac/institutes/grid.239395.7
221 schema:familyName Koziol
222 schema:givenName Magdalena J
223 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0640342011.25
224 rdf:type schema:Person
225 sg:person.0645200471.91 schema:affiliation https://www.grid.ac/institutes/grid.66859.34
226 schema:familyName Gnirke
227 schema:givenName Andreas
228 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0645200471.91
229 rdf:type schema:Person
230 sg:person.0650451313.47 schema:affiliation https://www.grid.ac/institutes/grid.66859.34
231 schema:familyName Fan
232 schema:givenName Lin
233 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0650451313.47
234 rdf:type schema:Person
235 sg:pub.10.1038/349038a0 schema:sameAs https://app.dimensions.ai/details/publication/pub.1053275082
236 https://doi.org/10.1038/349038a0
237 rdf:type schema:CreativeWork
238 sg:pub.10.1038/nature06008 schema:sameAs https://app.dimensions.ai/details/publication/pub.1036216819
239 https://doi.org/10.1038/nature06008
240 rdf:type schema:CreativeWork
241 sg:pub.10.1038/nature07509 schema:sameAs https://app.dimensions.ai/details/publication/pub.1029002744
242 https://doi.org/10.1038/nature07509
243 rdf:type schema:CreativeWork
244 sg:pub.10.1038/nature07638 schema:sameAs https://app.dimensions.ai/details/publication/pub.1009442631
245 https://doi.org/10.1038/nature07638
246 rdf:type schema:CreativeWork
247 sg:pub.10.1038/nature07672 schema:sameAs https://app.dimensions.ai/details/publication/pub.1051133532
248 https://doi.org/10.1038/nature07672
249 rdf:type schema:CreativeWork
250 sg:pub.10.1038/ng.259 schema:sameAs https://app.dimensions.ai/details/publication/pub.1050283464
251 https://doi.org/10.1038/ng.259
252 rdf:type schema:CreativeWork
253 sg:pub.10.1038/nmeth.1223 schema:sameAs https://app.dimensions.ai/details/publication/pub.1048586936
254 https://doi.org/10.1038/nmeth.1223
255 rdf:type schema:CreativeWork
256 sg:pub.10.1038/nmeth.1226 schema:sameAs https://app.dimensions.ai/details/publication/pub.1045381177
257 https://doi.org/10.1038/nmeth.1226
258 rdf:type schema:CreativeWork
259 sg:pub.10.1186/gb-2008-9-12-r175 schema:sameAs https://app.dimensions.ai/details/publication/pub.1016469219
260 https://doi.org/10.1186/gb-2008-9-12-r175
261 rdf:type schema:CreativeWork
262 sg:pub.10.1186/gb-2009-10-3-r25 schema:sameAs https://app.dimensions.ai/details/publication/pub.1049583368
263 https://doi.org/10.1186/gb-2009-10-3-r25
264 rdf:type schema:CreativeWork
265 https://doi.org/10.1016/j.cell.2007.05.022 schema:sameAs https://app.dimensions.ai/details/publication/pub.1051644950
266 rdf:type schema:CreativeWork
267 https://doi.org/10.1016/j.cell.2008.03.029 schema:sameAs https://app.dimensions.ai/details/publication/pub.1020929996
268 rdf:type schema:CreativeWork
269 https://doi.org/10.1073/pnas.0812841106 schema:sameAs https://app.dimensions.ai/details/publication/pub.1045146500
270 rdf:type schema:CreativeWork
271 https://doi.org/10.1073/pnas.0904715106 schema:sameAs https://app.dimensions.ai/details/publication/pub.1022579887
272 rdf:type schema:CreativeWork
273 https://doi.org/10.1073/pnas.0914114107 schema:sameAs https://app.dimensions.ai/details/publication/pub.1033167226
274 rdf:type schema:CreativeWork
275 https://doi.org/10.1093/bioinformatics/btp120 schema:sameAs https://app.dimensions.ai/details/publication/pub.1012425816
276 rdf:type schema:CreativeWork
277 https://doi.org/10.1093/bioinformatics/btp190 schema:sameAs https://app.dimensions.ai/details/publication/pub.1041785738
278 rdf:type schema:CreativeWork
279 https://doi.org/10.1093/bioinformatics/btp367 schema:sameAs https://app.dimensions.ai/details/publication/pub.1015468380
280 rdf:type schema:CreativeWork
281 https://doi.org/10.1093/nar/gkl842 schema:sameAs https://app.dimensions.ai/details/publication/pub.1008035809
282 rdf:type schema:CreativeWork
283 https://doi.org/10.1101/gr.103697.109 schema:sameAs https://app.dimensions.ai/details/publication/pub.1049494483
284 rdf:type schema:CreativeWork
285 https://doi.org/10.1101/gr.6679507 schema:sameAs https://app.dimensions.ai/details/publication/pub.1043091736
286 rdf:type schema:CreativeWork
287 https://doi.org/10.1126/science.1103388 schema:sameAs https://app.dimensions.ai/details/publication/pub.1042123507
288 rdf:type schema:CreativeWork
289 https://doi.org/10.1126/science.1112009 schema:sameAs https://app.dimensions.ai/details/publication/pub.1048209390
290 rdf:type schema:CreativeWork
291 https://doi.org/10.1126/science.1112014 schema:sameAs https://app.dimensions.ai/details/publication/pub.1052847323
292 rdf:type schema:CreativeWork
293 https://doi.org/10.1126/science.1115901 schema:sameAs https://app.dimensions.ai/details/publication/pub.1024645561
294 rdf:type schema:CreativeWork
295 https://doi.org/10.1126/science.1138341 schema:sameAs https://app.dimensions.ai/details/publication/pub.1002326113
296 rdf:type schema:CreativeWork
297 https://doi.org/10.1126/science.1163045 schema:sameAs https://app.dimensions.ai/details/publication/pub.1038655698
298 rdf:type schema:CreativeWork
299 https://doi.org/10.1371/journal.pbio.0030283 schema:sameAs https://app.dimensions.ai/details/publication/pub.1045076866
300 rdf:type schema:CreativeWork
301 https://doi.org/10.1371/journal.pcbi.1000067 schema:sameAs https://app.dimensions.ai/details/publication/pub.1047797581
302 rdf:type schema:CreativeWork
303 https://doi.org/10.1371/journal.pcbi.1000598 schema:sameAs https://app.dimensions.ai/details/publication/pub.1005301630
304 rdf:type schema:CreativeWork
305 https://www.grid.ac/institutes/grid.116068.8 schema:alternateName Massachusetts Institute of Technology
306 schema:name Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA.
307 Department of Biology, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.
308 Howard Hughes Medical Institute, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.
309 rdf:type schema:Organization
310 https://www.grid.ac/institutes/grid.239395.7 schema:alternateName Beth Israel Deaconess Medical Center
311 schema:name Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA.
312 Department of Pathology, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA.
313 rdf:type schema:Organization
314 https://www.grid.ac/institutes/grid.38142.3c schema:alternateName Harvard University
315 schema:name Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA.
316 Department of Biology, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.
317 Department of Systems Biology, Harvard Medical School, Boston, Massachusetts, USA.
318 rdf:type schema:Organization
319 https://www.grid.ac/institutes/grid.66859.34 schema:alternateName Broad Institute
320 schema:name Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA.
321 rdf:type schema:Organization
 




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


...