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使用 dREG 从新生转录本中识别调控元件。

Identification of regulatory elements from nascent transcription using dREG.

机构信息

Baker Institute for Animal Health, College of Veterinary Medicine, Cornell University, Ithaca, New York 14853, USA.

Graduate Field of Computational Biology, Cornell University, Ithaca, New York 14853, USA.

出版信息

Genome Res. 2019 Feb;29(2):293-303. doi: 10.1101/gr.238279.118. Epub 2018 Dec 20.

Abstract

Our genomes encode a wealth of transcription initiation regions (TIRs) that can be identified by their distinctive patterns of actively elongating RNA polymerase. We previously introduced dREG to identify TIRs using PRO-seq data. Here, we introduce an efficient new implementation of dREG that uses PRO-seq data to identify both uni- and bidirectionally transcribed TIRs with 70% improvement in accuracy, three- to fourfold higher resolution, and >100-fold increases in computational efficiency. Using a novel strategy to identify TIRs based on their statistical confidence reveals extensive overlap with orthogonal assays, yet also reveals thousands of additional weakly transcribed TIRs that were not identified by H3K27ac ChIP-seq or DNase-seq. Novel TIRs discovered by dREG were often associated with RNA polymerase III initiation, bound by pioneer transcription factors, or located in broad domains marked by repressive chromatin modifications. Our results suggest that transcription initiation can be a powerful tool for expanding the catalog of functional elements.

摘要

我们的基因组编码了丰富的转录起始区域(TIRs),这些区域可以通过其独特的活跃延伸 RNA 聚合酶模式来识别。我们之前介绍了 dREG 来使用 PRO-seq 数据识别单方向和双向转录的 TIRs。在这里,我们引入了一种高效的新 dREG 实现方法,该方法使用 PRO-seq 数据来识别 TIRs,其准确性提高了 70%,分辨率提高了三到四倍,计算效率提高了 100 多倍。使用一种基于统计置信度的新策略来识别 TIRs,与正交测定法有广泛的重叠,但也揭示了数千个额外的弱转录 TIRs,这些 TIRs不能通过 H3K27ac ChIP-seq 或 DNase-seq 来识别。dREG 发现的新 TIRs 通常与 RNA 聚合酶 III 起始有关,由先驱转录因子结合,或位于由抑制性染色质修饰标记的广泛结构域中。我们的结果表明,转录起始可以成为扩展功能元件目录的有力工具。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/15c8/6360809/6f22cd4df6b3/293f01.jpg

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