A comparative analysis of transcription factor binding models learned from PBM, HT-SELEX and ChIP data
Identifieur interne : 001145 ( Pmc/Checkpoint ); précédent : 001144; suivant : 001146A comparative analysis of transcription factor binding models learned from PBM, HT-SELEX and ChIP data
Auteurs : Yaron Orenstein ; Ron ShamirSource :
- Nucleic Acids Research [ 0305-1048 ] ; 2014.
Abstract
Understanding gene regulation is a key challenge in today's biology. The new technologies of protein-binding microarrays (PBMs) and high-throughput SELEX (HT-SELEX) allow measurement of the binding intensities of one transcription factor (TF) to numerous synthetic double-stranded DNA sequences in a single experiment. Recently, Jolma
Url:
DOI: 10.1093/nar/gku117
PubMed: 24500199
PubMed Central: 4005680
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<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">A comparative analysis of transcription factor binding models learned from PBM, HT-SELEX and ChIP data</title><author><name sortKey="Orenstein, Yaron" sort="Orenstein, Yaron" uniqKey="Orenstein Y" first="Yaron" last="Orenstein">Yaron Orenstein</name></author><author><name sortKey="Shamir, Ron" sort="Shamir, Ron" uniqKey="Shamir R" first="Ron" last="Shamir">Ron Shamir</name></author></titleStmt><publicationStmt><idno type="wicri:source">PMC</idno><idno type="pmid">24500199</idno><idno type="pmc">4005680</idno><idno type="url">http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4005680</idno><idno type="RBID">PMC:4005680</idno><idno type="doi">10.1093/nar/gku117</idno><date when="2014">2014</date><idno type="wicri:Area/Pmc/Corpus">000F54</idno><idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Corpus" wicri:corpus="PMC">000F54</idno><idno type="wicri:Area/Pmc/Curation">000F54</idno><idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Curation">000F54</idno><idno type="wicri:Area/Pmc/Checkpoint">001145</idno><idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Checkpoint">001145</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en" level="a" type="main">A comparative analysis of transcription factor binding models learned from PBM, HT-SELEX and ChIP data</title><author><name sortKey="Orenstein, Yaron" sort="Orenstein, Yaron" uniqKey="Orenstein Y" first="Yaron" last="Orenstein">Yaron Orenstein</name></author><author><name sortKey="Shamir, Ron" sort="Shamir, Ron" uniqKey="Shamir R" first="Ron" last="Shamir">Ron Shamir</name></author></analytic><series><title level="j">Nucleic Acids Research</title><idno type="ISSN">0305-1048</idno><idno type="eISSN">1362-4962</idno><imprint><date when="2014">2014</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><p>Understanding gene regulation is a key challenge in today's biology. The new technologies of protein-binding microarrays (PBMs) and high-throughput SELEX (HT-SELEX) allow measurement of the binding intensities of one transcription factor (TF) to numerous synthetic double-stranded DNA sequences in a single experiment. Recently, Jolma <italic>et al.</italic> reported the results of 547 HT-SELEX experiments covering human and mouse TFs. Because 162 of these TFs were also covered by PBM technology, for the first time, a large-scale comparison between implementations of these two <italic>in vitro</italic> technologies is possible. Here we assessed the similarities and differences between binding models, represented as position weight matrices, inferred from PBM and HT-SELEX, and also measured how well these models predict <italic>in vivo</italic> binding. Our results show that HT-SELEX- and PBM-derived models agree for most TFs. For some TFs, the HT-SELEX-derived models are longer versions of the PBM-derived models, whereas for other TFs, the HT-SELEX models match the secondary PBM-derived models. Remarkably, PBM-based 8-mer ranking is more accurate than that of HT-SELEX, but models derived from HT-SELEX predict <italic>in vivo</italic> binding better. In addition, we reveal several biases in HT-SELEX data including nucleotide frequency bias, enrichment of C-rich k-mers and oligos and underrepresentation of palindromes.</p></div></front><back><div1 type="bibliography"><listBibl><biblStruct><analytic><author><name sortKey="Aparicio, O" uniqKey="Aparicio O">O Aparicio</name></author><author><name sortKey="Geisberg, Jv" uniqKey="Geisberg J">JV Geisberg</name></author><author><name sortKey="Struhl, K" uniqKey="Struhl K">K Struhl</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Johnson, Ds" uniqKey="Johnson D">DS Johnson</name></author><author><name sortKey="Mortazavi, A" uniqKey="Mortazavi A">A Mortazavi</name></author><author><name sortKey="Myers, Rm" uniqKey="Myers R">RM Myers</name></author><author><name sortKey="Wold, B" uniqKey="Wold B">B Wold</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Rhee, Hs" uniqKey="Rhee H">HS Rhee</name></author><author><name 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<front><journal-meta><journal-id journal-id-type="nlm-ta">Nucleic Acids Res</journal-id><journal-id journal-id-type="iso-abbrev">Nucleic Acids Res</journal-id><journal-id journal-id-type="publisher-id">nar</journal-id><journal-id journal-id-type="hwp">nar</journal-id><journal-title-group><journal-title>Nucleic Acids Research</journal-title></journal-title-group><issn pub-type="ppub">0305-1048</issn><issn pub-type="epub">1362-4962</issn><publisher><publisher-name>Oxford University Press</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="pmid">24500199</article-id><article-id pub-id-type="pmc">4005680</article-id><article-id pub-id-type="doi">10.1093/nar/gku117</article-id><article-id pub-id-type="publisher-id">gku117</article-id><article-categories><subj-group subj-group-type="heading"><subject>Methods Online</subject></subj-group></article-categories><title-group><article-title>A comparative analysis of transcription factor binding models learned from PBM, HT-SELEX and ChIP data</article-title></title-group><contrib-group><contrib contrib-type="author"><name><surname>Orenstein</surname><given-names>Yaron</given-names></name></contrib><contrib contrib-type="author"><name><surname>Shamir</surname><given-names>Ron</given-names></name><xref ref-type="corresp" rid="gku117-COR1">*</xref></contrib><aff>Blavatnik School of Computer Science, Tel-Aviv University, Tel Aviv 69978, Israel</aff></contrib-group><author-notes><corresp id="gku117-COR1">*To whom correspondence should be addressed. Tel: <phone>+972 3 6405383</phone>; Fax: <fax>+972 3 640 5384</fax>; Email: <email>rshamir@tau.ac.il</email></corresp><fn><p>Present address: Ron Shamir, School of Computer Science, Tel-Aviv University, P.O.B. 39040, Tel-Aviv 69978, Israel.</p></fn></author-notes><pub-date pub-type="ppub"><month>4</month><year>2014</year></pub-date><pub-date pub-type="epub"><day>5</day><month>2</month><year>2014</year></pub-date><pub-date pub-type="pmc-release"><day>5</day><month>2</month><year>2014</year></pub-date><pmc-comment> PMC Release delay is 0 months and 0 days and was based on the
<volume>42</volume><issue>8</issue><fpage>e63</fpage><lpage>e63</lpage><history><date date-type="received"><day>11</day><month>11</month><year>2013</year></date><date date-type="rev-recd"><day>22</day><month>12</month><year>2013</year></date><date date-type="accepted"><day>16</day><month>1</month><year>2014</year></date></history><permissions><copyright-statement>© The Author(s) 2014. Published by Oxford University Press.</copyright-statement><copyright-year>2014</copyright-year><license license-type="creative-commons" xlink:href="http://creativecommons.org/licenses/by/3.0/"><license-p><pmc-comment>CREATIVE COMMONS</pmc-comment>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type="uri" xlink:href="http://creativecommons.org/licenses/by/3.0/">http://creativecommons.org/licenses/by/3.0/</ext-link>), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.</license-p></license></permissions><abstract><p>Understanding gene regulation is a key challenge in today's biology. The new technologies of protein-binding microarrays (PBMs) and high-throughput SELEX (HT-SELEX) allow measurement of the binding intensities of one transcription factor (TF) to numerous synthetic double-stranded DNA sequences in a single experiment. Recently, Jolma <italic>et al.</italic> reported the results of 547 HT-SELEX experiments covering human and mouse TFs. Because 162 of these TFs were also covered by PBM technology, for the first time, a large-scale comparison between implementations of these two <italic>in vitro</italic> technologies is possible. Here we assessed the similarities and differences between binding models, represented as position weight matrices, inferred from PBM and HT-SELEX, and also measured how well these models predict <italic>in vivo</italic> binding. Our results show that HT-SELEX- and PBM-derived models agree for most TFs. For some TFs, the HT-SELEX-derived models are longer versions of the PBM-derived models, whereas for other TFs, the HT-SELEX models match the secondary PBM-derived models. Remarkably, PBM-based 8-mer ranking is more accurate than that of HT-SELEX, but models derived from HT-SELEX predict <italic>in vivo</italic> binding better. In addition, we reveal several biases in HT-SELEX data including nucleotide frequency bias, enrichment of C-rich k-mers and oligos and underrepresentation of palindromes.</p></abstract><counts><page-count count="10"></page-count></counts></article-meta></front></pmc><affiliations><list></list><tree><noCountry><name sortKey="Orenstein, Yaron" sort="Orenstein, Yaron" uniqKey="Orenstein Y" first="Yaron" last="Orenstein">Yaron Orenstein</name><name sortKey="Shamir, Ron" sort="Shamir, Ron" uniqKey="Shamir R" first="Ron" last="Shamir">Ron Shamir</name></noCountry></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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| HfdSelect -Kh $EXPLOR_AREA/Data/Pmc/Checkpoint/biblio.hfd \
| NlmPubMed2Wicri -a MersV1
| This area was generated with Dilib version V0.6.33. |  |