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Novel Bioinformatics Method for Identification of Genome-Wide Non-Canonical Spliced Regions Using RNA-Seq Data

SETTING: During endoplasmic reticulum (ER) stress, the endoribonuclease (RNase) Ire1α initiates removal of a 26 nt region from the mRNA encoding the transcription factor Xbp1 via an unconventional mechanism (atypically within the cytosol). This causes an open reading frame-shift that leads to altere...

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Autores principales: Bai, Yongsheng, Hassler, Justin, Ziyar, Ahdad, Li, Philip, Wright, Zachary, Menon, Rajasree, Omenn, Gilbert S., Cavalcoli, James D., Kaufman, Randal J., Sartor, Maureen A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4084626/
https://www.ncbi.nlm.nih.gov/pubmed/24991935
http://dx.doi.org/10.1371/journal.pone.0100864
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author Bai, Yongsheng
Hassler, Justin
Ziyar, Ahdad
Li, Philip
Wright, Zachary
Menon, Rajasree
Omenn, Gilbert S.
Cavalcoli, James D.
Kaufman, Randal J.
Sartor, Maureen A.
author_facet Bai, Yongsheng
Hassler, Justin
Ziyar, Ahdad
Li, Philip
Wright, Zachary
Menon, Rajasree
Omenn, Gilbert S.
Cavalcoli, James D.
Kaufman, Randal J.
Sartor, Maureen A.
author_sort Bai, Yongsheng
collection PubMed
description SETTING: During endoplasmic reticulum (ER) stress, the endoribonuclease (RNase) Ire1α initiates removal of a 26 nt region from the mRNA encoding the transcription factor Xbp1 via an unconventional mechanism (atypically within the cytosol). This causes an open reading frame-shift that leads to altered transcriptional regulation of numerous downstream genes in response to ER stress as part of the unfolded protein response (UPR). Strikingly, other examples of targeted, unconventional splicing of short mRNA regions have yet to be reported. OBJECTIVE: Our goal was to develop an approach to identify non-canonical, possibly very short, splicing regions using RNA-Seq data and apply it to ER stress-induced Ire1α heterozygous and knockout mouse embryonic fibroblast (MEF) cell lines to identify additional Ire1α targets. RESULTS: We developed a bioinformatics approach called the Read-Split-Walk (RSW) pipeline, and evaluated it using two Ire1α heterozygous and two Ire1α-null samples. The 26 nt non-canonical splice site in Xbp1 was detected as the top hit by our RSW pipeline in heterozygous samples but not in the negative control Ire1α knockout samples. We compared the Xbp1 results from our approach with results using the alignment program BWA, Bowtie2, STAR, Exonerate and the Unix “grep” command. We then applied our RSW pipeline to RNA-Seq data from the SKBR3 human breast cancer cell line. RSW reported a large number of non-canonical spliced regions for 108 genes in chromosome 17, which were identified by an independent study. CONCLUSIONS: We conclude that our RSW pipeline is a practical approach for identifying non-canonical splice junction sites on a genome-wide level. We demonstrate that our pipeline can detect novel splice sites in RNA-Seq data generated under similar conditions for multiple species, in our case mouse and human.
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spelling pubmed-40846262014-07-10 Novel Bioinformatics Method for Identification of Genome-Wide Non-Canonical Spliced Regions Using RNA-Seq Data Bai, Yongsheng Hassler, Justin Ziyar, Ahdad Li, Philip Wright, Zachary Menon, Rajasree Omenn, Gilbert S. Cavalcoli, James D. Kaufman, Randal J. Sartor, Maureen A. PLoS One Research Article SETTING: During endoplasmic reticulum (ER) stress, the endoribonuclease (RNase) Ire1α initiates removal of a 26 nt region from the mRNA encoding the transcription factor Xbp1 via an unconventional mechanism (atypically within the cytosol). This causes an open reading frame-shift that leads to altered transcriptional regulation of numerous downstream genes in response to ER stress as part of the unfolded protein response (UPR). Strikingly, other examples of targeted, unconventional splicing of short mRNA regions have yet to be reported. OBJECTIVE: Our goal was to develop an approach to identify non-canonical, possibly very short, splicing regions using RNA-Seq data and apply it to ER stress-induced Ire1α heterozygous and knockout mouse embryonic fibroblast (MEF) cell lines to identify additional Ire1α targets. RESULTS: We developed a bioinformatics approach called the Read-Split-Walk (RSW) pipeline, and evaluated it using two Ire1α heterozygous and two Ire1α-null samples. The 26 nt non-canonical splice site in Xbp1 was detected as the top hit by our RSW pipeline in heterozygous samples but not in the negative control Ire1α knockout samples. We compared the Xbp1 results from our approach with results using the alignment program BWA, Bowtie2, STAR, Exonerate and the Unix “grep” command. We then applied our RSW pipeline to RNA-Seq data from the SKBR3 human breast cancer cell line. RSW reported a large number of non-canonical spliced regions for 108 genes in chromosome 17, which were identified by an independent study. CONCLUSIONS: We conclude that our RSW pipeline is a practical approach for identifying non-canonical splice junction sites on a genome-wide level. We demonstrate that our pipeline can detect novel splice sites in RNA-Seq data generated under similar conditions for multiple species, in our case mouse and human. Public Library of Science 2014-07-03 /pmc/articles/PMC4084626/ /pubmed/24991935 http://dx.doi.org/10.1371/journal.pone.0100864 Text en © 2014 Bai et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Bai, Yongsheng
Hassler, Justin
Ziyar, Ahdad
Li, Philip
Wright, Zachary
Menon, Rajasree
Omenn, Gilbert S.
Cavalcoli, James D.
Kaufman, Randal J.
Sartor, Maureen A.
Novel Bioinformatics Method for Identification of Genome-Wide Non-Canonical Spliced Regions Using RNA-Seq Data
title Novel Bioinformatics Method for Identification of Genome-Wide Non-Canonical Spliced Regions Using RNA-Seq Data
title_full Novel Bioinformatics Method for Identification of Genome-Wide Non-Canonical Spliced Regions Using RNA-Seq Data
title_fullStr Novel Bioinformatics Method for Identification of Genome-Wide Non-Canonical Spliced Regions Using RNA-Seq Data
title_full_unstemmed Novel Bioinformatics Method for Identification of Genome-Wide Non-Canonical Spliced Regions Using RNA-Seq Data
title_short Novel Bioinformatics Method for Identification of Genome-Wide Non-Canonical Spliced Regions Using RNA-Seq Data
title_sort novel bioinformatics method for identification of genome-wide non-canonical spliced regions using rna-seq data
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4084626/
https://www.ncbi.nlm.nih.gov/pubmed/24991935
http://dx.doi.org/10.1371/journal.pone.0100864
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