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

ZSF1 大鼠 RNA 测序数据中可变剪接的计算识别和验证,这是 2 型糖尿病肾病的临床前模型

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作者:Chi Zhang, Ken Dower, Baohong Zhang, Robert V Martinez, Lih-Ling Lin, Shanrong Zhao

Abstract

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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