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NanoPARE: Parallel analysis of RNA 5' ends from low input RNA

ABSTRACT: nanoPARE: Parallel analysis of RNA 5' ends from low input RNA

PROVIDER: PRJNA449355 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	SRR6967080.fastq.gz	Fastqsanger.gz
	SRR6967090.fastq.gz	Fastqsanger.gz
	SRR6967100.fastq.gz	Fastqsanger.gz
	SRR6967081.fastq.gz	Fastqsanger.gz
	SRR6967091.fastq.gz	Fastqsanger.gz

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nanoPARE: Parallel analysis of RNA 5' ends from low input RNA

Project description:A diversity of RNA molecule 5' ends are generated during transcriptional and post-transcriptional processes. Different RNA ends can confer or represent different functional activities and thus the identification of RNA end usage dynamics contributes to the functional characterization of RNA molecules. Here we present a method that enables the accurate identification of RNA 5' ends from samples with low amounts of total RNAs, and thus allow characterization of RNA regulatory mechanisms in specific cell-types.

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Project description:Diverse RNA 5' ends are generated through both transcriptional and post-transcriptional processes. These important modes of gene regulation often vary across cell types and can contribute to the diversification of transcriptomes and thus cellular differentiation. Therefore, the identification of primary and processed 5' ends of RNAs is important for their functional characterization. Methods have been developed to profile either RNA 5' ends from primary transcripts or the products of RNA degradation genome-wide. However, these approaches either require high amounts of starting RNA or are performed in the absence of paired gene-body mRNA-seq data. This limits current efforts in RNA 5' end annotation to whole tissues and can prevent accurate RNA 5' end classification due to biases in the data sets. To enable the accurate identification and precise classification of RNA 5' ends from standard and low-input RNA, we developed a next-generation sequencing-based method called nanoPARE and associated software. By integrating RNA 5' end information from nanoPARE with gene-body mRNA-seq data from the same RNA sample, our method enables the identification of transcription start sites at single-nucleotide resolution from single-cell levels of total RNA, as well as small RNA-mediated cleavage events from at least 10,000-fold less total RNA compared to conventional approaches. NanoPARE can therefore be used to accurately profile transcription start sites, noncapped RNA 5' ends, and small RNA targeting events from individual tissue types. As a proof-of-principle, we utilized nanoPARE to improve Arabidopsis thaliana RNA 5' end annotations and quantify microRNA-mediated cleavage events across five different flower tissues.

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