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Comprehensive RNA-Chromatin Interactome Reveals Global and Specific Regulatory Functions by Long Non-Coding RNAs

ABSTRACT: Long non-coding RNAs (lncRNAs) are an emerging class of regulatory molecules with a potentially broad-range of epigenomic regulatory functions. These functions are likely mediated by lncRNA-chromatin interactions either directly or indirectly through protein intermediates. Thus, comprehensive genomic mapping of all lncRNA targets describing the ‘RNA-chromatin interactome’ are critical for inferring lncRNA functions. Current methodologies for investigating lncRNA-chromatin interaction are one-RNA-at-a-time, and most inferred lncRNA functions were based on indirect “guilt-by-association”. To address these limitations, we devised an unbiased genome-wide strategy to identify all RNA interactions with chromatin by paired-end-tag sequencing (RICh-PET). We comprehensively characterized a human RNA-chromatin interactome and uncovered complex RNA-chromatin networks with many showing long-distance interactions predominantly at gene promoters. Further analysis revealed both global and specific transcriptional regulation by lncRNAs to genes involved in cancer biology, demonstrating the capacity of RICh-PET to concomitantly identify thousands of lncRNAs and chromatin targets in the human genome, thus significantly advancing the understanding of lncRNA functions.

ORGANISM(S): Homo sapiens

PROVIDER: GSE53052 | GEO | 2023/04/30

REPOSITORIES: GEO

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Project description:Higher-order chromosomal organization for transcription regulation is poorly understood in eukaryotes. Using genome-wide Chromatin Interaction Analysis with Paired-End-Tag sequencing (ChIA-PET), we mapped long-range chromatin interactions associated with RNA polymerase II in human cells and uncovered widespread promoter-centered intragenic, extragenic, and intergenic interactions. These interactions further aggregated into higher-order clusters, wherein proximal and distal genes were engaged through promoter-promoter interactions. Most genes with promoter-promoter interactions were active and transcribed cooperatively, and some interacting promoters could influence each other implying combinatorial complexity of transcriptional controls. Comparative analyses of different cell lines showed that cell-specific chromatin interactions could provide structural frameworks for cell-specific transcription, and suggested significant enrichment of enhancer-promoter interactions for cell-specific functions. Furthermore, genetically-identified disease-associated noncoding elements were found to be spatially engaged with corresponding genes through long-range interactions. Overall, our study provides insights into transcription regulation by three-dimensional chromatin interactions for both housekeeping and cell-specific genes in human cells. RNA polymerase II (RNAPII) bound chromatin interactions were extracted with Chromatin Interaction Analysis with Paired-End Tag (ChIA-PET) sequencing, in order to study the transcription regulations with RNAPII-associated long-range chromatin interactions. Five cell lines, namely MCF7 (ATCC# HTB-22), K562 (ATCC# CCL-243), HCT116 (ATCC# CCL-247), HeLa (ATCC# CCL-2.2), and NB4 (Roussel and Lanotte, 2001) (provided by Dr. Sherman Weissman, Yale University), were grown under standard culture conditions and harvested at log phase. Harvested cells were cross-linked using 1% formaldehyde followed by neutralization with 0.2M glycine. Chromatin was isolated and subjected to ChIA-PET protocol as described in Fullwood et al (Fullwood et al: An oestrogen-receptor-alpha-bound human chromatin interactome. Nature 2009, 462(7269):58-64). The ChIA-PET sequence reads were processed and analyzed using ChIA-PET Tool (Li et al: ChIA-PET tool for comprehensive chromatin interaction analysis with paired-end tag sequencing. Genome Biol 2010, 11(2):R22).

Project description:We aimed at systematically inferring the regulatory functions of host lncRNAs in response to influenza A virus (IAV) and severe acute respiratory syndrome coronavirus (SARS-CoV) in the mouse model, using a ‘guilt-by-association’ approach which relies on finding which lncRNAs have similar expression profiles to protein-coding genes of known function. To build a large panel of diverse host responses to viral infection, we took advantage of the genetic diversity present in the 8 founder strains of the Collaborative Cross (CC) mouse resource. Extensive pulmonary host-response profiling was performed on mock and viral-infected lungs at 2 and 4 days post-infection using total RNA-Seq. Overall lncRNAs accounted for about 40% of total genes differentially expressed upon infections (5,329 DE lncRNAs). To predict the functions of these lncRNAs, we constructed a co-expression network using the weighted correlation network analysis (WGCNA) and identified modules of co-expressed genes. Several lncRNAs were identified as belonging to gene modules associated with viral replication or weight loss, and enriched in various infection-related biological processes such as immune response. In addition, each lncRNA was individually annotated using ranked list of DE genes based on signed correlation with each LncRNA. We predicted that a few lncRNAs may be implicated in more than 50 biological processes or pathways. Finally, we identified the lncRNAs that were positively or negatively correlated with all their neighbors and may have cis enhancer or inhibitor effects. We validated our prediction by examining additional RNASeq dataset of mice treated with IFN-alpha. Altogether, these results provide a broad categorization of lncRNA functions and identify subsets of lncRNAs with potential key roles for respiratory virus pathogenesis. These data are fully accessible through The MOuse NOn-Code Lung database (MONOCLdb) http://monocldb.viromics.washington.edu/ At 2 or 4 days post infection, Collaborative Cross founders mice (n=2-3 for infected conditions, n=2 for mocks) were euthanized and lungs were used for total RNA-Seq.

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Comprehensive RNA-Chromatin Interactome Reveals Global and Specific Regulatory Functions by Long Non-Coding RNAs

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