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Next-generation sequencing facilitates quantitative analysis of CON and PMB treatment HepG2 cells transcriptomes

ABSTRACT: Next-generation sequencing facilitates quantitative analysis of CON and PMB treatment HepG2 cells transcriptomes

PROVIDER: PRJNA856662 | ENA |

REPOSITORIES: ENA

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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.

2023-08-11 | GSE185840 | GEO

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

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

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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 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.

2023-08-11 | GSE207670 | GEO

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

Project description: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

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Murine host body reactions to implanted scaffolds: non-coat polystyrene scaffold vs. collagen- or PMB-coated scaffold

Project description:This study investigated early host reactions to implanted materials to predict successful tissue regeneration with implant. Three kinds of scaffold, i.e., non-coat, collagen-coated, and PMB-coated porous polystylene scaffolds were implanted subcutaneously in mice dorsal area. Those scaffolds were used as bio-incomopatible materials, appropriate materials for tissue regeneration (bio active), and inappropriate to regenration (bio-inert) scaffolds. Seven days after implantation, scaffolds were explanted and total RNA was isolated from infiltrated host cells into scaffold by laser microdissection. Gene expressions of cells in collagen- and PMB-coated scaffold were normalized using results of non coat scaffold. Genes with more than 2-fold difference between collagen and PMB were picked up and narrowed to related keywords; inflammation, angiogenesis, wound healing, and mcrophage polarization. Among those genes, interluekin (IL)-1beta which promote both inflammation and wound healing was up-regulated in collagen-coated scaffold. On the other hand, IL-10 which suppress both inflammation and wound healing was up-regulated in PMB-coated scaffold. Angiogenesis-promoting genes were up-regulated and angiogenesis suppressve genes were suppressed in collagen. Up-regulation of IL-1b and the angiogenesis-relating genes inside the porous scaffolds are the possibly important factors for controlling tissue regeneration. Three-condition experiment, host cells infiltrated in non coat (reference), collagen-coated, and PMB-coated scaffolds. Two-microarray condition experiments, collagen vs. non coat and PMB coat vs. non coat. Hybridization: 2 replicates. Scanning: 3 replicates. Biological experiments: once.

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2012-03-30 | E-GEOD-30137 | biostudies-arrayexpress

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Project description:Purpose: Using RNA-seq to analyze the different expressions induced by IFNα among the SETD2-KO HepG2 cells, STAT1-KO HepG2 cells and STAT1-K525A-Re HepG2 cells and HepG2 control cells Methods: mRNA profiles of HepG2 control cells and SETD2-KO cells, STAT1-KO cells, STAT1-K525A-Re cells were generated by deep sequencing, using BGISEQ-500RS. The sequence reads that passed quality filters were analyzed at the transcriptional level with RSEM (RNA-seq by Expectation Maximization).

2019-03-12 | GSE98372 | GEO

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Project description:Geothrix sp. PMB-07 Genome sequencing

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