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Next generation sequencing facilliates quantitative analysis of Wild type and KitW/Wv Smooth muscle cells transcriptomes

ABSTRACT: We extracted RNA from primary smooth muscle cells from five KitW/WV mice and five Wild type mice and used next generation RNA sequenceing to compare the difference in gene expression profiles

ORGANISM(S): Mus musculus

PROVIDER: GSE168110 | GEO | 2024/03/02

REPOSITORIES: GEO

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Next generation sequencing facilliates quantitative analysis of Wild type and KitW/Wv Smooth muscle cells transcriptomes

Project description:Next generation sequencing facilliates quantitative analysis of Wild type and KitW/Wv Smooth muscle cells transcriptomes

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RNA Sequencing Analysis of Wild-type, Efferent Duct-Ligated, and W/Wv Caput Epididymal Transcriptomes

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Expression analysis of Wv/Wv fetal gonads

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Next Generation Sequencing Facilitates Quantitative Analysis of Wild Type and miR-21-/- Smooth Muscle Cell Transcriptomes

Project description:Purpose: Next-generation sequencing (NGS) has revolutionized systems-based analysis of cellular pathways. The goals of this study are to investigate the effect of miR-21 knockout in aortic smooth muscle cell transcriptome profiling (RNA-seq) to understand how miR-21 regulates SMC function at basal level. Methods: Aortic smooth muscle cell (SMC) mRNA profiles of 12-week-old wild-type (WT) and SMC specific miR-21 knockout (miR-21fl/flmTmG/Myh11ERT2) mice were generated by deep sequencing, in triplicate. The sequence reads that passed quality filters were analyzed at the transcript isoform level . qRT–PCR validation was performed using TaqMan and SYBR Green assays to confirm miR-21 knockout. Results: Using an optimized data analysis workflow, we mapped about 30 million sequence reads per sample to the mouse genome (build mm9) and identified 16,014 transcripts in the SMCs of WT and miR-21fl/flmTmG/Myh11ERT2 mice. RNA-seq data revealed >400 genes differentially expressed in miR-21 knockout SMCs. Hierarchical clustering of differentially expressed genes uncovered several as yet uncharacterized pathways that may contribute to SMC function. Conclusions: Our study represents the first detailed analysis of SMC lacking of miR-21 transcriptomes, with biologic replicates, generated by RNA-seq technology. The optimized data analysis workflows reported here should provide a framework for comparative investigations of expression profiles. Our results show that NGS offers a comprehensive and more accurate quantitative and qualitative evaluation of mRNA content within a cell or tissue. We conclude that RNA-seq based transcriptome characterization would expedite genetic network analyses and permit the dissection of complex biologic functions.

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Next Generation Sequencing Facilitates Quantitative Analysis of control smooth muscle cells and Tet3-inactivation smooth muscle cells transcriptomes

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Smooth muscle cell reprogramming in aortic aneurysms [scRNA-Seq]

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