Transcription-factor occupancy at HOT regions quantitatively predicts RNA polymerase recruitment in five human cell lines.
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ArticleAuthors
Foley, Joseph WSidow, Arend
Date
2013-10-20Online Publication Date
2013-10-20Print Publication Date
2013Permanent link to this record
http://hdl.handle.net/10754/596828
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BACKGROUND: High-occupancy target (HOT) regions are compact genome loci occupied by many different transcription factors (TFs). HOT regions were initially defined in invertebrate model organisms, and we here show that they are a ubiquitous feature of the human gene-regulation landscape. RESULTS: We identified HOT regions by a comprehensive analysis of ChIP-seq data from 96 DNA-associated proteins in 5 human cell lines. Most HOT regions co-localize with RNA polymerase II binding sites, but many are not near the promoters of annotated genes. At HOT promoters, TF occupancy is strongly predictive of transcription preinitiation complex recruitment and moderately predictive of initiating Pol II recruitment, but only weakly predictive of elongating Pol II and RNA transcript abundance. TF occupancy varies quantitatively within human HOT regions; we used this variation to discover novel associations between TFs. The sequence motif associated with any given TF's direct DNA binding is somewhat predictive of its empirical occupancy, but a great deal of occupancy occurs at sites without the TF's motif, implying indirect recruitment by another TF whose motif is present. CONCLUSIONS: Mammalian HOT regions are regulatory hubs that integrate the signals from diverse regulatory pathways to quantitatively tune the promoter for RNA polymerase II recruitment.Citation
Foley JW, Sidow A (2013) Transcription-factor occupancy at HOT regions quantitatively predicts RNA polymerase recruitment in five human cell lines. BMC Genomics 14: 720. Available: http://dx.doi.org/10.1186/1471-2164-14-720.Sponsors
We thank Cheryl Smith, Ed Grow, Noah Spies, and Erik Lehnert for critical reading of this manuscript. We are also grateful to Anshul Kundaje and Phil Lacroute for invaluable technical advice. This work was supported by the Stanford Genome Training Program (NIH/NHGRI T32 HG000044), a subcontract to ENCODE grant HG004695, and a KAUST AEA grant.Publisher
Springer NatureJournal
BMC GenomicsPubMed ID
24138567PubMed Central ID
PMC3826616ae974a485f413a2113503eed53cd6c53
10.1186/1471-2164-14-720
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Publications Acknowledging KAUST Support
Except where otherwise noted, this item's license is described as This is an Open Access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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