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

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

PROVIDER: PRJNA706029 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	SRR13833774.fastq.gz	Fastqsanger.gz
	SRR13833775.fastq.gz	Fastqsanger.gz
	SRR13833776.fastq.gz	Fastqsanger.gz
	SRR13833777.fastq.gz	Fastqsanger.gz
	SRR13833778.fastq.gz	Fastqsanger.gz

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

Project description: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

2024-03-02 | GSE168110 | GEO

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

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

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

Project description:Purpose: Next-generation sequencing (NGS) has revolutionized systems-based analysis of cellular pathways. The goals of this study are to compare NGS-derived retinal transcriptome profiling (RNA-seq) to microarray and quantitative reverse transcription polymerase chain reaction (qRT–PCR) methods and to evaluate protocols for optimal high-throughput data analysis

2022-09-20 | GSE166816 | GEO

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.

2022-06-10 | GSE183830 | GEO

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

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

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Next Generation Sequencing Facilitates Quantitative Analysis of FLox and SMYD2 KO Aortic Smooth Muscle Cell Transcriptomes

Project description:Next Generation Sequencing Facilitates Quantitative Analysis of FLox and SMYD2 KO Aortic Smooth Muscle Cell Transcriptomes

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Next Generation Sequencing Facilitates Quantitative Analysis of FLox and SMYD2 KO Aortic Smooth Muscle Cell Transcriptomes

Project description:Purpose: Methyltransferase SMYD2 has been implicated in cancer cell growth and cardiomyocytes development. However, its role in vascular smooth muscle cell(VSMC) is still unknown. This study aims to investigate differentially expressed genes in Flox and SMYD2 knockout VSMC. Methods:RNA profiles of Aortic Smooth Muscle Cell isolated from Flox and SMYD2 knockout (SMYD2−/−) mice were generated by deep sequencing, in triplicate, using BGISEQ-500 platform. Firstly, we filter the low quality reads (More than 20% of the bases qualities are lower than 10),reads with adaptors and reads with unknown bases (N bases more than 5%)to get the clean reads. Then we map those clean reads onto reference genome, followed with novel gene prediction, SNP &INDEL calling and gene splicing detection. Finally, we identify DEGs (differentially expressed genes) between samples and do clustering analysis and functional annotations. Results: In our project, we sequenced 6 samples on BGISEQ-500 Platform in total and generated about 4.69 Gb per sample. The average genome mapping rate is 96.62% and the average gene mapping rate is 80.92%. 18,112 genes were identified in which 16,992 of them are known genes and 1,351 of them are novel genes. 13,680 novel transcipts were identified in which 11,251 of them are previously unknown splicing event for known genes, 1,351 of them are novel coding transcripts without any known features, and the remaining 1,078 are long noncoding RNA. Conclusions: Our study represents the first detailed analysis of SMYD2 KO VSMC transcriptomes, with biologic replicates, generated by RNA-seq technology.

2023-05-12 | GSE161004 | GEO

Next Generation Sequencing Facilitates Quantitative Analysis of Normal Human Kidney Transcriptomes

Project description:Next-generation sequencing (NGS) has revolutionized systems-based analysis of cellular pathways. The goals of this study are to compare NGS-derived normal human kidney transcriptome profiling (RNA-seq) to microarray and quantitative reverse transcription polymerase chain reaction (qRT–PCR) methods and to evaluate protocols for optimal high-throughput data analysis The kidney tissue was immediately placed and stored in RNAlater® (Ambion), according to the manufacturer’s instruction. The tissue was manually microdissected under microscope in RNAlater® pool for glomerular and tubular compartment. Dissected tissue was homogenized and RNA was prepared using RNAeasy mini columns (Qiagen, Valencia, CA, US), according to the manufacturer’s instructions. RNA quality and quantity were determined using the Laboratory-on-Chip Total RNA PicoKit Agilent BioAnalyzer. Only samples without evidence of degradation were further used (RNA Integrity Number >6).

2014-08-06 | E-GEOD-60119 | biostudies-arrayexpress

Next Generation Sequencing Facilitates Quantitative Analysis of Solanum lycopersicum bud and flower Transcriptomes

Project description:Next Generation Sequencing Facilitates Quantitative Analysis of Solanum lycopersicum bud and flower Transcriptomes

2021-02-27 | GSE164382 | GEO

Next Generation Sequencing Facilitates Quantitative Analysis of IBP Transcriptomes

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