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Next-generation sequencing facilitates quantitative analysis of CON and PMB treated HepG2 cells and CreAlbMYC and CreAlbScarb2F/FMYC mice liver transcriptomes, and CUT&Tag analysis genome-wide maps of chromatin state in CTRLcas9 and SCARB2cas9 HepG2 cells

ABSTRACT: Next-generation sequencing facilitates quantitative analysis of CON and PMB treated HepG2 cells and CreAlbMYC and CreAlbScarb2F/FMYC mice liver transcriptomes, and CUT&Tag analysis genome-wide maps of chromatin state in CTRLcas9 and SCARB2cas9 HepG2 cells

PROVIDER: PRJNA856657 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	SRR20020531_1.fastq.gz	Fastqsanger.gz
	SRR20020531_2.fastq.gz	Fastqsanger.gz
	SRR20020532_1.fastq.gz	Fastqsanger.gz
	SRR20020532_2.fastq.gz	Fastqsanger.gz
	SRR20020533_1.fastq.gz	Fastqsanger.gz

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Next Generation Sequencing Facilitates Quantitative Analysis of CON and PMB treatment HepG2 cells Transcriptomes

Project description:Purpose: Next-generation sequencing (NGS) has revolutionized systems-based analysis of cellular pathways. The goals of this study are to analysis the differiational genes and pathways in CON and PMB treatment cells by using RNA-seq Methods: CON and PMB treatment cells mRNA profiles were generated by deep sequencing, using Illumina Novaseq. The sequence reads that passed quality filters were analyzed at the transcript isoform level with following methods: Alignment by using HISAT2 , IGV was used to to view the mapping result by the Heatmap, histogram, scatter plot or other stytle, FPKM was then calculated to estimate the expression level of genes in each sample, EdgeR software was used for differential gene expression analysis and Function Enrichment Analysis including GO enrichment analysis and KEGG . Conclusions: Our study represents detailed analysis of CON and PMB cells 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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Project description:Purpose: Next-generation sequencing (NGS) has revolutionized systems-based analysis of cellular pathways. The goals of this study are to analyse the differential genes and pathways in CTRL and PMB treatment cells by using RNA-seq. Methods: CTRL and PMB treatment cells mRNA profiles were generated by deep sequencing, using Illumina Novaseq. The sequence reads that passed quality filters were analyzed at the transcript isoform level with following methods: Alignment by using HISAT2, IGV was used to view the mapping result by the Heatmap, histogram, scatter plot or other style, FPKM was then calculated to estimate the expression level of genes in each sample, EdgeR software was used for differential gene expression analysis and Function Enrichment Analysis including GO enrichment analysis and KEGG. Conclusions: Our study represents detailed analysis of CTRL and PMB cells 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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