Unknown,Transcriptomics,Genomics,Proteomics

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Global identification of target recognition and cleavage by the Microprocessor in human ESCs.

ABSTRACT: The Microprocessor plays an essential role in canonical miRNA biogenesis by facilitating cleavage of stem-loop structures in primary transcripts to yield pre-miRNAs. Although miRNA biogenesis has been extensively studied through biochemical and molecular genetic approaches, it has yet to be addressed to what extent the current miRNA biogenesis models hold true in intact cells. To address the issues of in vivo recognition and cleavage by the Microprocessor, we investigate RNAs that are associated with DGCR8 and Drosha by using immunoprecipitation coupled with next-generation sequencing. Here, we present global protein-RNA interactions with unprecedented sensitivity and specificity. Our data indicate that precursors of canonical miRNAs and miRNA-like hairpins are the major substrates of the Microprocessor. As a result of specific enrichment of nascent cleavage products, we are able to pinpoint the Microprocessor-mediated cleavage sites per se at single-nucleotide resolution. Unexpectedly, a 2-nt 3M-bM-^@M-^Y overhang invariably exists at the ends of cleaved bases instead of nascent pre-miRNAs. Besides canonical miRNA precursors, we find that two novel miRNA-like structures embedded in mRNAs are cleaved to yield pre-miRNA-like hairpins, uncoupled from miRNA maturation. Our data provide a framework for in vivo Microprocessor-mediated cleavage and a foundation for experimental and computational studies on miRNA biogenesis in living cells. CLIP-seq for DGCR8 and Drosha, RIP-seq for DGCR8, sequencing of AGO2-assocated miRNA

ORGANISM(S): Homo sapiens

SUBMITTER: Young-Soo Kwon

PROVIDER: E-GEOD-61979 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Project description:To accelerate previous RNA structure probing approaches, which focus on analyzing one RNA sequence at a time, we have developed FragSeq, a high-throughput RNA structure probing method that uses high-throughput RNA sequencing to identify single-stranded RNA (ssRNA) regions from fragments generated by nuclease P1, which is specific for single-stranded nucleic acids. In the accompanying study, we show that we can accurately and simultaneously map ssRNA regions in multiple non-coding RNAs with known structure in experiments probing the entire mouse nuclear transcriptome. We carried out probing in two cell types to assess reproducibility. We also identified and experimentally validated structured regions in ncRNAs never previously probed. We examined mouse nuclear RNA from two cell types: undifferentiated embryonic stem cells (UNDIFF) and cells differentiated into neural precursors (D5NP). For each cell type, nuclear RNA was purified and deproteinized, denatured, and refolded in vitro, from which we prepared three barcoded samples: "nuclease" (RNA partially digested with P1 ssRNA-specific nuclease, yielding 5'-PO4/3'-OH end chemistry at each cleavage site), "control" (control for "nuclease" sample to idenfity endogenous 5'-PO4/3'-OH), and "PNK" (same as "control" but followed by a polynucleotide kinase treatment to convert 5'-OH/3'-cyclic-phosphate ends to clonable 5'-PO4/3'-OH ends). Resulting RNA fragments were cloned using the SOLiD Small RNA Expression Kit (SREK) protocol, which ligates linkers only to 5'-PO4/3'-OH containing RNA, enriching for clones of products resulting from P1 cleavage in "nuclease" sample and selecting against random degradation. Two cell types, three treatments each, thus resulted in six barcoded samples total (barcodes 01, 02, 04, 05, 07, 08). Four other barcoded samples were prepared for separate experiments not used in our study (barcodes 03, 06, 09, 10), so their preparation is not described here. The total run of ten barcodes was done on the ABI SOLiD3 platform and a custom algorithm (FragSeq v0.0.1) was used to compute "cutting scores" (as described in our paper) that show ssRNA regions in hundreds of ncRNAs.

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Global identification of target recognition and cleavage by the Microprocessor in human ESCs.

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