Defining functional DNA elements in the human genome
Name
Kellis-2014-Defining functional.pdf
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864.34 KB
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Checksum (MD5)
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Author(s)
Kellis, Manolis
Wold, Barbara
Snyder, Michael P.
Bernstein, Bradley E.
Kundaje, Anshul
Marinov, Georgi K.
Ward, Lucas D.
Birney, Ewan
Crawford, Gregory E.
Dekker, Job
Date Issued
April 2014
Journal
Proceedings of the National Academy of Sciences
Publisher
National Academy of Sciences (U.S.)
Citation
Kellis, M., B. Wold, M. P. Snyder, B. E. Bernstein, A. Kundaje, G. K. Marinov, L. D. Ward, et al. “Defining Functional DNA Elements in the Human Genome.” Proceedings of the National Academy of Sciences 111, no. 17 (April 21, 2014): 6131–6138.
Version
Final published version
Abstract
With the completion of the human genome sequence, attention turned to identifying and annotating its functional DNA elements. As a complement to genetic and comparative genomics approaches, the Encyclopedia of DNA Elements Project was launched to contribute maps of RNA transcripts, transcriptional regulator binding sites, and chromatin states in many cell types. The resulting genome-wide data reveal sites of biochemical activity with high positional resolution and cell type specificity that facilitate studies of gene regulation and interpretation of noncoding variants associated with human disease. However, the biochemically active regions cover a much larger fraction of the genome than do evolutionarily conserved regions, raising the question of whether nonconserved but biochemically active regions are truly functional. Here, we review the strengths and limitations of biochemical, evolutionary, and genetic approaches for defining functional DNA segments, potential sources for the observed differences in estimated genomic coverage, and the biological implications of these discrepancies. We also analyze the relationship between signal intensity, genomic coverage, and evolutionary conservation. Our results reinforce the principle that each approach provides complementary information and that we need to use combinations of all three to elucidate genome function in human biology and disease.
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
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DOI of Published Version
https://doi.org/10.1073/pnas.1318948111
