Systematic mapping of RNA-chromatin interactions in vivo
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA357269 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR5278100_1.fastq.gz | Fastqsanger.gz | |||
| SRR5278100_2.fastq.gz | Fastqsanger.gz | |||
| SRR5278101_1.fastq.gz | Fastqsanger.gz | |||
| SRR5278101_2.fastq.gz | Fastqsanger.gz | |||
| SRR5278102_1.fastq.gz | Fastqsanger.gz |
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Project description:RNA molecules can attach to chromatin and thus provide a type of epigenomic information. It remains difficult to know what RNAs are associated with chromatin and where are the genomic target loci of these RNAs. Here, we present MARGI (Mapping RNA-genome interactions), a technology to massively reveal native RNA-chromatin interactions from unperturbed cells. The gist of this technology is to ligate chromatin-associated RNA (caRNA) with their target genomic sequence by proximity ligation, forming RNA-DNA chimeric sequences, which are converted to sequencing library for paired-end sequencing. Using MARGI, we produced RNA-genome interaction maps for human embryonic stem (ES) cells and HEK cells. MARGI revealed hundreds of chromatin-associated RNAs (caRNA), including previously known XIST, SNHG1, NEAT1, and MALAT1, as well as each caRNA's genomic interaction loci. Using a cross-species experiment, we estimated that approximately 2.2% of MARGI identified interactions are false positives. MARGI data suggested that 80-95% of interactions are proximal, where a caRNA is connected to its nearby genomic regions, 1-2% are distal, and 5-15% are inter-chromosomal. The majority of TSSs are associated with distal or inter-chromosomal caRNAs. ChIP-seq reported H3K27ac and H3K4me3 levels are positively correlated while H3K9me is negatively correlated with MARGI reported RNA attachment levels. The MARGI technology should facilitate revealing novel RNA functions and epigenomic events.
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Project description:RNA molecules can attach to chromatin. It remains difficult to know what RNAs are associated with chromatin and where the genomic target loci of these RNAs are. Here, we present MARGI (mapping RNA-genome interactions), a technology to massively reveal native RNA-chromatin interactions from unperturbed cells. The gist of this technology is to ligate chromatin-associated RNAs (caRNAs) with their target genomic sequences by proximity ligation, forming RNA-DNA chimeric sequences, which are converted to a sequencing library for paired-end sequencing. Using MARGI, we produced RNA-genome interaction maps for human embryonic stem cells (ESCs) and human embryonic kidney (HEK) cells. MARGI revealed hundreds of caRNAs, including previously known XIST, SNHG1, NEAT1, and MALAT1, as well as each caRNA's genomic interaction loci. Using a cross-species experiment, we estimated that approximately 2.2% of MARGI-identified interactions were false positives. In ESCs and HEK cells, the RNA ends of more than 5% of MARGI read pairs were mapped to distal or inter-chromosomal locations as compared to the locations of their corresponding DNA ends. The majority of transcription start sites are associated with distal or inter-chromosomal caRNAs. Chromatin-immunoprecipitation-sequencing (ChIP-seq)-reported H3K27ac and H3K4me3 levels are positively correlated, while H3K9me3 is negatively correlated, with MARGI-reported RNA attachment levels. The MARGI technology should facilitate revealing novel RNA functions and their genomic target regions.
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Project description:Systematic mapping of 3D enhancer interactions reveals lineage specific regulatory networks during early mouse developmental decisions
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Project description:In vivo protein-DNA interactions connect each transcription factor with its direct targets to form a gene network scaffold. To map these protein-DNA interactions comprehensively across entire mammalian genomes, we developed a large-scale chromatin immunoprecipitation assay (ChIPSeq) based on direct ultrahigh-throughput DNA sequencing. This sequence census method was then used to map in vivo binding of the neuron-restrictive silencer factor (NRSF; also known as REST, for repressor element–1 silencing transcription factor) to 1946 locations in the human genome. The data display sharp resolution of binding position [±50 base pairs (bp)], which facilitated our finding motifs and allowed us to identify noncanonical NRSF-binding motifs. These ChIPSeq data also have high sensitivity and specificity [ROC (receiver operator characteristic) area ≥ 0.96] and statistical confidence (P < 10−4), properties that were important for inferring new candidate interactions. These include key transcription factors in the gene network that regulates pancreatic islet cell development. Experiment Overall Design: Exam NRSF binding in Jurkat T cell line
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