Loading...
Genome-wide prediction of DNase I hypersensitivity using gene expression
Zhou, Weiqiang Sherwood, Ben Ji, Zhicheng Xue, Yingchao Du, Fang Bai, Jiawei Ying, Mingyao Ji, Hongkai
Zhou, Weiqiang
Sherwood, Ben
Ji, Zhicheng
Xue, Yingchao
Du, Fang
Bai, Jiawei
Ying, Mingyao
Ji, Hongkai
Citations
Altmetric:
Abstract
We evaluate the feasibility of using a biological sample’s transcriptome to predict its genome-wide regulatory element activities measured by DNase I hypersensitivity (DH). We develop BIRD, Big Data Regression for predicting DH, to handle this high-dimensional problem. Applying BIRD to the Encyclopedia of DNA Elements (ENCODE) data, we found that to a large extent gene expression predicts DH, and information useful for prediction is contained in the whole transcriptome rather than limited to a regulatory element’s neighboring genes. We show applications of BIRD-predicted DH in predicting transcription factor-binding sites (TFBSs), turning publicly available gene expression samples in Gene Expression Omnibus (GEO) into a regulome database, predicting differential regulatory element activities, and facilitating regulome data analyses by serving as pseudo-replicates. Besides improving our understanding of the regulome–transcriptome relationship, this study suggests that transcriptome-based prediction can provide a useful new approach for regulome mapping.
Description
Date
2017-10-19
Journal Title
Journal ISSN
Volume Title
Publisher
Nature Research
Collections
Research Projects
Organizational Units
Journal Issue
Keywords
Citation
Zhou, W., Sherwood, B., Ji, Z., Xue, Y., Du, F., Bai, J., ... & Ji, H. (2017). Genome-wide prediction of DNase I hypersensitivity using gene expression. Nature communications, 8(1), 1038.