NDLI: A computational exploration of gene regulation by nucleosome position

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A computational exploration of gene regulation by nucleosome position

Content Provider	ACM Digital Library
Author	Dennis, Jonathan H. Fincher, Justin A. Tyson, Gary
Abstract	More than two meters of DNA is organized inside a five micrometer nucleus of every human cell. This is accomplished by the wrapping of DNA around protein "spools" (histones) to form nucleosomes. Some DNA sequences are more likely to be organized into nucleosomes than others. Because nucleosomes, not bare DNA, are the substrate for DNA-templated reactions, the position and density of nucleosomes play an important role in these processes (e.g., affecting gene regulation). We used a machine learning tool trained to distinguish nucleosome forming from nucleosome inhibitory DNA sequences. This Support Vector Machine (SVM) was used to evaluate DNA sequence and generate nucleosome occupancy predictions for the entire human genome. We used the resulting scores to characterize DNA-encoded nucleosome positioning signals at specific genomic regions. Scores around protein coding regions, specifically intron-exon boundaries, showed a characteristic nucleosome positioning pattern. Previously these boundaries had been identified using a DNA consensus sequence, and we were able to identify a subset of protein genes based on sequence features recognized by the SVM that are not readily identifiable by traditional sequence evaluation techniques. We anticipate that this type of analysis will allow us to refine our understanding of DNA regulatory processes.
Starting Page	469
Ending Page	471
Page Count	3
File Format	PDF
ISBN	9781450304382
DOI	10.1145/1854776.1854860
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2010-08-02
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Chromatin Nucleosome Machine learning Support vector machine Dna sequence
Content Type	Text
Resource Type	Article

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