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Computational identification and validation of alternative splicing in ZSF1 rat RNA-seq data, a preclinical model for type 2 diabetic nephropathy

Obese ZSF1 rats exhibit spontaneous time-dependent diabetic nephropathy and are considered to be a highly relevant animal model of progressive human diabetic kidney disease. We previously identified gene expression changes between disease and control animals across six time points from 12 to 41 week...

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Autores principales: Zhang, Chi, Dower, Ken, Zhang, Baohong, Martinez, Robert V., Lin, Lih-Ling, Zhao, Shanrong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5955895/
https://www.ncbi.nlm.nih.gov/pubmed/29769602
http://dx.doi.org/10.1038/s41598-018-26035-x
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author Zhang, Chi
Dower, Ken
Zhang, Baohong
Martinez, Robert V.
Lin, Lih-Ling
Zhao, Shanrong
author_facet Zhang, Chi
Dower, Ken
Zhang, Baohong
Martinez, Robert V.
Lin, Lih-Ling
Zhao, Shanrong
author_sort Zhang, Chi
collection PubMed
description Obese ZSF1 rats exhibit spontaneous time-dependent diabetic nephropathy and are considered to be a highly relevant animal model of progressive human diabetic kidney disease. We previously identified gene expression changes between disease and control animals across six time points from 12 to 41 weeks. In this study, the same data were analysed at the isoform and exon levels to reveal additional disease mechanisms that may be governed by alternative splicing. Our analyses identified alternative splicing patterns in genes that may be implicated in disease pathogenesis (such as Shc1, Serpinc1, Epb4.1l5, and Il-33), which would have been overlooked in standard gene-level analysis. The alternatively spliced genes were enriched in pathways related to cell adhesion, cell–cell interactions/junctions, and cytoskeleton signalling, whereas the differentially expressed genes were enriched in pathways related to immune response, G protein-coupled receptor, and cAMP signalling. Our findings indicate that additional mechanistic insights can be gained from exon- and isoform-level data analyses over standard gene-level analysis. Considering alternative splicing is poorly conserved between rodents and humans, it is noted that this work is not translational, but the point holds true that additional insights can be gained from alternative splicing analysis of RNA-seq data.
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spelling pubmed-59558952018-05-21 Computational identification and validation of alternative splicing in ZSF1 rat RNA-seq data, a preclinical model for type 2 diabetic nephropathy Zhang, Chi Dower, Ken Zhang, Baohong Martinez, Robert V. Lin, Lih-Ling Zhao, Shanrong Sci Rep Article Obese ZSF1 rats exhibit spontaneous time-dependent diabetic nephropathy and are considered to be a highly relevant animal model of progressive human diabetic kidney disease. We previously identified gene expression changes between disease and control animals across six time points from 12 to 41 weeks. In this study, the same data were analysed at the isoform and exon levels to reveal additional disease mechanisms that may be governed by alternative splicing. Our analyses identified alternative splicing patterns in genes that may be implicated in disease pathogenesis (such as Shc1, Serpinc1, Epb4.1l5, and Il-33), which would have been overlooked in standard gene-level analysis. The alternatively spliced genes were enriched in pathways related to cell adhesion, cell–cell interactions/junctions, and cytoskeleton signalling, whereas the differentially expressed genes were enriched in pathways related to immune response, G protein-coupled receptor, and cAMP signalling. Our findings indicate that additional mechanistic insights can be gained from exon- and isoform-level data analyses over standard gene-level analysis. Considering alternative splicing is poorly conserved between rodents and humans, it is noted that this work is not translational, but the point holds true that additional insights can be gained from alternative splicing analysis of RNA-seq data. Nature Publishing Group UK 2018-05-16 /pmc/articles/PMC5955895/ /pubmed/29769602 http://dx.doi.org/10.1038/s41598-018-26035-x Text en © The Author(s) 2018 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Zhang, Chi
Dower, Ken
Zhang, Baohong
Martinez, Robert V.
Lin, Lih-Ling
Zhao, Shanrong
Computational identification and validation of alternative splicing in ZSF1 rat RNA-seq data, a preclinical model for type 2 diabetic nephropathy
title Computational identification and validation of alternative splicing in ZSF1 rat RNA-seq data, a preclinical model for type 2 diabetic nephropathy
title_full Computational identification and validation of alternative splicing in ZSF1 rat RNA-seq data, a preclinical model for type 2 diabetic nephropathy
title_fullStr Computational identification and validation of alternative splicing in ZSF1 rat RNA-seq data, a preclinical model for type 2 diabetic nephropathy
title_full_unstemmed Computational identification and validation of alternative splicing in ZSF1 rat RNA-seq data, a preclinical model for type 2 diabetic nephropathy
title_short Computational identification and validation of alternative splicing in ZSF1 rat RNA-seq data, a preclinical model for type 2 diabetic nephropathy
title_sort computational identification and validation of alternative splicing in zsf1 rat rna-seq data, a preclinical model for type 2 diabetic nephropathy
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5955895/
https://www.ncbi.nlm.nih.gov/pubmed/29769602
http://dx.doi.org/10.1038/s41598-018-26035-x
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