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Next-generation Sequencing contributes to Quantitative Analysis of Transcriptomes in circBNC2-KO L-02 cells

ABSTRACT: Next-generation Sequencing contributes to Quantitative Analysis of Transcriptomes in circBNC2-KO L-02 cells

PROVIDER: PRJNA744392 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	SRR15058316_1.fastq.gz	Fastqsanger.gz
	SRR15058316_2.fastq.gz	Fastqsanger.gz
	SRR15058317_1.fastq.gz	Fastqsanger.gz
	SRR15058317_2.fastq.gz	Fastqsanger.gz

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Next-generation Sequencing contributes to Quantitative Analysis of Transcriptomes in circBNC2-KO L-02 cells

Project description:Purpose: We idenficied a circRNA, circBNC2, that was downregulated during hepatocytes injury. To study the function of circBNC2, we performed CRISPR-Cas9 to knock out circBNC2 in L-02 (a well recognized human hepatocytes) cells. Next-generation Sequencing was used to identified the differentially expressed mRNA between circBNC2-KO L-02 cells and wild-type L-02 cells.

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Next-generation Sequencing contributes to Quantitative Analysis of Transcriptomes in circBNC2-KO HK2 cells

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Project description:Purpose: We idenficied a circRNA, circBNC2, that was downregulated during tubular epithelial cell (TEC) injury. To study the function of circBNC2, we performed CRISPR-Cas9 to knock out circBNC2 in HK2 (a well recognized TEC) cells. Next-generation Sequencing was used to identified the differentially expressed mRNA between circBNC2-KO HK2 cells and wild-type HK2 cells.

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Project description:Purpose: Next-generation sequencing (NGS) has revolutionized systems-based analysis of cellular pathways. The goals of this study are to compare TP53-WT and TP53-KO HCT116 cells transcriptome profiling (RNA-seq) under 5-FU treatment condition and to evaluate the correlation between transcriptome profileing and chromatin accessibility under 5-FU treatment. Methods: HCT116 cell profiles of TP53-WT and TP53- KO were generated by deep sequencing, in duplicates, using Illumina GAIIx. The sequence reads that passed quality filters were analyzed at the transcript isoform levels: Burrows–Wheeler Aligner (BWA) followed by ANOVA (ANOVA). Conclusions: Our study represents the detailed analysis of TP53-WT and TP53-KO HCT116 cell transcriptomes under 5-FU treatment with different timepoint, 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 RNA-seq offers a comprehensive and more accurate quantitative and qualitative evaluation of mRNA content within a TP53-WT and TP53-KO cells with and without 5-FU treatment in different timepoint. We conclude that NGS based transcriptome characterization would expedite genetic network analyses and permit the dissection of complex biologic functions.

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