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An efficient method for genome-wide polyadenylation site mapping and RNA quantification.

ABSTRACT: The use of alternative poly(A) sites is common and affects the post-transcriptional fate of mRNA, including its stability, subcellular localization and translation. Here, we present a method to identify poly(A) sites in a genome-wide and strand-specific manner. This method, termed 3'T-fill, initially fills in the poly(A) stretch with unlabeled dTTPs, allowing sequencing to start directly after the poly(A) tail into the 3'-untranslated regions (UTR). Our comparative analysis demonstrates that it outperforms existing protocols in quality and throughput and accurately quantifies RNA levels as only one read is produced from each transcript. We use this method to characterize the diversity of polyadenylation in Saccharomyces cerevisiae, showing that alternative RNA molecules are present even in a genetically identical cell population. Finally, we observe that overlap of convergent 3'-UTRs is frequent but sharply limited by coding regions, suggesting factors that restrict compression of the yeast genome.

SUBMITTER: Wilkening S

PROVIDER: S-EPMC3597643 | biostudies-literature | 2013 Mar

REPOSITORIES: biostudies-literature

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An efficient method for genome-wide polyadenylation site mapping and RNA quantification.

Wilkening Stefan S Pelechano Vicent V Järvelin Aino I AI Tekkedil Manu M MM Anders Simon S Benes Vladimir V Steinmetz Lars M LM

Nucleic acids research 20130107 5

The use of alternative poly(A) sites is common and affects the post-transcriptional fate of mRNA, including its stability, subcellular localization and translation. Here, we present a method to identify poly(A) sites in a genome-wide and strand-specific manner. This method, termed 3'T-fill, initially fills in the poly(A) stretch with unlabeled dTTPs, allowing sequencing to start directly after the poly(A) tail into the 3'-untranslated regions (UTR). Our comparative analysis demonstrates that it ...[more]

PMID: 23295673

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Project description:MOTIVATION:RNAs fold into complex structures that are integral to the diverse mechanisms underlying RNA regulation of gene expression. Recent development of transcriptome-wide RNA structure profiling through the application of structure-probing enzymes or chemicals combined with high-throughput sequencing has opened a new field that greatly expands the amount of in vitro and in vivo RNA structural information available. The resultant datasets provide the opportunity to investigate RNA structural information on a global scale. However, the analysis of high-throughput RNA structure profiling data requires considerable computational effort and expertise. RESULTS:We present a new platform, StructureFold, that provides an integrated computational solution designed specifically for large-scale RNA structure mapping and reconstruction across any transcriptome. StructureFold automates the processing and analysis of raw high-throughput RNA structure profiling data, allowing the seamless incorporation of wet-bench structural information from chemical probes and/or ribonucleases to restrain RNA secondary structure prediction via the RNAstructure and ViennaRNA package algorithms. StructureFold performs reads mapping and alignment, normalization and reactivity derivation, and RNA structure prediction in a single user-friendly web interface or via local installation. The variation in transcript abundance and length that prevails in living cells and consequently causes variation in the counts of structure-probing events between transcripts is accounted for. Accordingly, StructureFold is applicable to RNA structural profiling data obtained in vivo as well as to in vitro or in silico datasets. StructureFold is deployed via the Galaxy platform. AVAILABILITY AND IMPLEMENTATION:StructureFold is freely available as a component of Galaxy available at: https://usegalaxy.org/. CONTACT:yxt148@psu.edu or sma3@psu.edu SUPPLEMENTARY INFORMATION:Supplementary data are available at Bioinformatics online.

Dataset Information

An efficient method for genome-wide polyadenylation site mapping and RNA quantification.

Publications

An efficient method for genome-wide polyadenylation site mapping and RNA quantification.

Similar Datasets

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