4.5 Article

Genomic sequence is highly predictive of local nucleosome depletion

Journal

PLOS COMPUTATIONAL BIOLOGY
Volume 4, Issue 1, Pages -

Publisher

PUBLIC LIBRARY SCIENCE
DOI: 10.1371/journal.pcbi.0040013

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Funding

  1. NHGRI NIH HHS [R01 HG005085] Funding Source: Medline
  2. NIGMS NIH HHS [R01 GM078990, R01-GM078990] Funding Source: Medline
  3. NATIONAL HUMAN GENOME RESEARCH INSTITUTE [R01HG005085] Funding Source: NIH RePORTER
  4. NATIONAL INSTITUTE OF GENERAL MEDICAL SCIENCES [R01GM078990] Funding Source: NIH RePORTER

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The regulation of DNA accessibility through nucleosome positioning is important for transcription control. Computational models have been developed to predict genome-wide nucleosome positions from DNA sequences, but these models consider only nucleosome sequences, which may have limited their power. We developed a statistical multi-resolution approach to identify a sequence signature, called the N-score, that distinguishes nucleosome binding DNA from non-nucleosome DNA. This new approach has significantly improved the prediction accuracy. The sequence information is highly predictive for local nucleosome enrichment or depletion, whereas predictions of the exact positions are only modestly more accurate than a null model, suggesting the importance of other regulatory factors in fine-tuning the nucleosome positions. The N-score in promoter regions is negatively correlated with gene expression levels. Regulatory elements are enriched in low N-score regions. While our model is derived from yeast data, the N-score pattern computed from this model agrees well with recent high-resolution protein-binding data in human.

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