PLoS Computational BiologyGenomicsPeer-reviewed journal article
Chromatin-enriched RNAs mark active and repressive cis-regulation: an analysis of nuclear RNA-seq
Xiangying Sun, Zhezhen WangiD, Johnathon M. HalliD, Carlos Perez-CervantesiD, Alexander J. RuthenburgiD, Ivan P. G. MoskowitziD, Michael GribskoviD, Xinan Holly YangiD
Abstract
Long noncoding RNAs (lncRNAs) localize in the cell nucleus and influence gene expression through a variety of molecular mechanisms. RNA sequencing of two biochemical fractions of nuclei reveals a unique class of lncRNAs, termed chromatin-enriched nuclear RNAs (cheRNAs) that are tightly bound to chromatin and putatively function to cis-activate gene expression. Until now, a rigorous analytic pipeline for nuclear RNA-seq has been lacking. In this study, we survey four computational strategies for nuclear RNA-seq data analysis and show that a new pipeline, Tuxedo, outperforms other approaches. Tuxedo not only assembles a more complete transcriptome, but also identifies cheRNA with higher accuracy. We have used Tuxedo to analyze gold-standard K562 cell datasets and further characterize the genomic features of intergenic cheRNA (icheRNA) and their similarity to those of enhancer RNA (eRNA). Moreover, we quantify the transcriptional correlation of icheRNA and adjacent genes, and suggest that icheRNA may be the cis-acting transcriptional regulator that is more positively associated with neighboring gene expression than eRNA predicted by state-of-art method or CAGE signal. We also explore two novel genomic associations, suggesting cheRNA may have diverse functions. A possible new role of H3K9me3 modification coincident with icheRNA may be associated with active enhancer derived from ancient mobile elements, while a potential cis-repressive function of antisense cheRNA (as-cheRNA) is likely to be involved in transiently modulating cell type-specific cis-regulation.\n\nAuthor SummaryChromatin-enriched nuclear RNA (cheRNA) is a class of gene regulatory non-coding RNAs. CheRNA provides a powerful way to profile the nuclear transcriptional landscape, especially to profile the noncoding transcriptome. The computational framework presented here provides a reliable approach to identifying cheRNA, and for studying cell-type specific gene regulation. We found that intergenic cheRNA, including intergenic cheRNA with high levels of H3K9me3 (a mark associated with closed/repressed chromatin), may act as a transcriptional activator. In contrast, antisense cheRNA, which originates from the complementary strand of the protein-coding gene, may interact with diverse chromatin modulators to repress local transcription. With our new pipeline, one future challenge will be refining the functional mechanisms of these noncoding RNA classes through exploring their regulatory roles, which are involved in diverse molecular and cellular processes in human and other organisms.
- organism: human
- assay: bulk RNA-seq
- research focus: cell type annotation
- research focus: differential expression
- research focus: gene regulatory network inference
- research focus: database / resource
- approach: statistical model
- Citations
- 6
- FWCI
- 0.26
- Field percentile
- 39th percentile
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