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Workflow for Genome-Wide Determination of Pre-mRNA Splicing Efficiency from Yeast RNA-seq Data
M. Převorovský, M. Hálová, K. Abrhámová, J. Libus, P. Folk,
Language English Country United States
Document type Journal Article
NLK
Free Medical Journals
from 2013
PubMed Central
from 2013
Europe PubMed Central
from 2013
ProQuest Central
from 2013
Open Access Digital Library
from 2001-01-01
Open Access Digital Library
from 2012-12-04
Open Access Digital Library
from 2013-01-01
CINAHL Plus with Full Text (EBSCOhost)
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Medline Complete (EBSCOhost)
from 2013-01-01
Health & Medicine (ProQuest)
from 2013
Wiley-Blackwell Open Access Titles
from 2001
ROAD: Directory of Open Access Scholarly Resources
from 2013
PubMed
28050562
DOI
10.1155/2016/4783841
Knihovny.cz E-resources
- MeSH
- Databases, Nucleic Acid MeSH
- Mutation genetics MeSH
- RNA Precursors genetics MeSH
- Workflow * MeSH
- Saccharomyces cerevisiae genetics MeSH
- Sequence Analysis, RNA methods MeSH
- RNA Splicing genetics MeSH
- Spliceosomes genetics MeSH
- Publication type
- Journal Article MeSH
Pre-mRNA splicing represents an important regulatory layer of eukaryotic gene expression. In the simple budding yeast Saccharomyces cerevisiae, about one-third of all mRNA molecules undergo splicing, and splicing efficiency is tightly regulated, for example, during meiotic differentiation. S. cerevisiae features a streamlined, evolutionarily highly conserved splicing machinery and serves as a favourite model for studies of various aspects of splicing. RNA-seq represents a robust, versatile, and affordable technique for transcriptome interrogation, which can also be used to study splicing efficiency. However, convenient bioinformatics tools for the analysis of splicing efficiency from yeast RNA-seq data are lacking. We present a complete workflow for the calculation of genome-wide splicing efficiency in S. cerevisiae using strand-specific RNA-seq data. Our pipeline takes sequencing reads in the FASTQ format and provides splicing efficiency values for the 5' and 3' splice junctions of each intron. The pipeline is based on up-to-date open-source software tools and requires very limited input from the user. We provide all relevant scripts in a ready-to-use form. We demonstrate the functionality of the workflow using RNA-seq datasets from three spliceosome mutants. The workflow should prove useful for studies of yeast splicing mutants or of regulated splicing, for example, under specific growth conditions.
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