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Correlation Between DNase I Hypersensitive Site Distribution and Gene Expression in HeLa S3 Cells

Overview of attention for article published in PLOS ONE, August 2012
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Title
Correlation Between DNase I Hypersensitive Site Distribution and Gene Expression in HeLa S3 Cells
Published in
PLOS ONE, August 2012
DOI 10.1371/journal.pone.0042414
Pubmed ID
Authors

Ya-Mei Wang, Ping Zhou, Li-Yong Wang, Zhen-Hua Li, Yao-Nan Zhang, Yu-Xiang Zhang

Abstract

Mapping DNase I hypersensitive sites (DHSs) within nuclear chromatin is a traditional and powerful method of identifying genetic regulatory elements. DHSs have been mapped by capturing the ends of long DNase I-cut fragments (>100,000 bp), or 100-1200 bp DNase I-double cleavage fragments (also called double-hit fragments). But next generation sequencing requires a DNA library containing DNA fragments of 100-500 bp. Therefore, we used short DNA fragments released by DNase I digestion to generate DNA libraries for next generation sequencing. The short segments are 100-300 bp and can be directly cloned and used for high-throughput sequencing. We identified 83,897 DHSs in 2,343,479 tags across the human genome. Our results indicate that the DHSs identified by this DHS assay are consistent with those identified by longer fragments in previous studies. We also found: (1) the distribution of DHSs in promoter and other gene regions of similarly expressed genes differs among different chromosomes; (2) silenced genes had a more open chromatin structure than previously thought; (3) DHSs in 3'untranslated regions (3'UTRs) are negatively correlated with level of gene expression.

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Geographical breakdown

Country Count As %
United States 3 3%
Italy 2 2%
Germany 2 2%
Turkey 1 <1%
Unknown 101 93%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 29 27%
Student > Master 23 21%
Researcher 16 15%
Student > Bachelor 15 14%
Student > Postgraduate 6 6%
Other 7 6%
Unknown 13 12%
Readers by discipline Count As %
Agricultural and Biological Sciences 51 47%
Biochemistry, Genetics and Molecular Biology 22 20%
Engineering 5 5%
Medicine and Dentistry 4 4%
Computer Science 2 2%
Other 9 8%
Unknown 16 15%