-
Je něco špatně v tomto záznamu ?
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,
Jazyk angličtina Země Spojené státy americké
Typ dokumentu časopisecké články
NLK
Free Medical Journals
od 2013
PubMed Central
od 2013
Europe PubMed Central
od 2013
ProQuest Central
od 2013
Open Access Digital Library
od 2001-01-01
Open Access Digital Library
od 2012-12-04
Open Access Digital Library
od 2013-01-01
CINAHL Plus with Full Text (EBSCOhost)
od 2013-01-01
Medline Complete (EBSCOhost)
od 2013-01-01
Health & Medicine (ProQuest)
od 2013
Wiley-Blackwell Open Access Titles
od 2001
ROAD: Directory of Open Access Scholarly Resources
od 2013
PubMed
28050562
DOI
10.1155/2016/4783841
Knihovny.cz E-zdroje
- MeSH
- databáze nukleových kyselin MeSH
- mutace genetika MeSH
- prekurzory RNA genetika MeSH
- průběh práce * MeSH
- Saccharomyces cerevisiae genetika MeSH
- sekvenční analýza RNA metody MeSH
- sestřih RNA genetika MeSH
- spliceozomy genetika MeSH
- Publikační typ
- časopisecké články 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.
Citace poskytuje Crossref.org
- 000
- 00000naa a2200000 a 4500
- 001
- bmc17013319
- 003
- CZ-PrNML
- 005
- 20170418103327.0
- 007
- ta
- 008
- 170413s2016 xxu f 000 0|eng||
- 009
- AR
- 024 7_
- $a 10.1155/2016/4783841 $2 doi
- 035 __
- $a (PubMed)28050562
- 040 __
- $a ABA008 $b cze $d ABA008 $e AACR2
- 041 0_
- $a eng
- 044 __
- $a xxu
- 100 1_
- $a Převorovský, Martin $u Department of Cell Biology, Faculty of Science, Charles University, Viničná 7, 128 43 Prague 2, Czech Republic.
- 245 10
- $a Workflow for Genome-Wide Determination of Pre-mRNA Splicing Efficiency from Yeast RNA-seq Data / $c M. Převorovský, M. Hálová, K. Abrhámová, J. Libus, P. Folk,
- 520 9_
- $a 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.
- 650 _2
- $a databáze nukleových kyselin $7 D030561
- 650 _2
- $a mutace $x genetika $7 D009154
- 650 _2
- $a prekurzory RNA $x genetika $7 D012322
- 650 _2
- $a sestřih RNA $x genetika $7 D012326
- 650 _2
- $a Saccharomyces cerevisiae $x genetika $7 D012441
- 650 _2
- $a sekvenční analýza RNA $x metody $7 D017423
- 650 _2
- $a spliceozomy $x genetika $7 D017381
- 650 12
- $a průběh práce $7 D057188
- 655 _2
- $a časopisecké články $7 D016428
- 700 1_
- $a Hálová, Martina $u Department of Cell Biology, Faculty of Science, Charles University, Viničná 7, 128 43 Prague 2, Czech Republic.
- 700 1_
- $a Abrhámová, Kateřina $u Department of Cell Biology, Faculty of Science, Charles University, Viničná 7, 128 43 Prague 2, Czech Republic. $7 gn_A_00000825
- 700 1_
- $a Libus, Jiří $u Department of Cell Biology, Faculty of Science, Charles University, Viničná 7, 128 43 Prague 2, Czech Republic.
- 700 1_
- $a Folk, Petr $u Department of Cell Biology, Faculty of Science, Charles University, Viničná 7, 128 43 Prague 2, Czech Republic.
- 773 0_
- $w MED00182164 $t BioMed research international $x 2314-6141 $g Roč. 2016, č. - (2016), s. 4783841
- 856 41
- $u https://pubmed.ncbi.nlm.nih.gov/28050562 $y Pubmed
- 910 __
- $a ABA008 $b sig $c sign $y a $z 0
- 990 __
- $a 20170413 $b ABA008
- 991 __
- $a 20170418103635 $b ABA008
- 999 __
- $a ok $b bmc $g 1199784 $s 974097
- BAS __
- $a 3
- BAS __
- $a PreBMC
- BMC __
- $a 2016 $b 2016 $c - $d 4783841 $e 20161206 $i 2314-6141 $m BioMed research international $n Biomed Res Int $x MED00182164
- LZP __
- $a Pubmed-20170413