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Preclinical efficacy and safety study of encapsulated human proliferating hepatocyte organoids in the treatment of liver failure

ABSTRACT: Preclinical efficacy and safety study of encapsulated human proliferating hepatocyte organoids in the treatment of liver failure

PROVIDER: PRJNA812769 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	SRR18218671_1.fastq.gz	Fastqsanger.gz
	SRR18218671_2.fastq.gz	Fastqsanger.gz
	SRR18218672_1.fastq.gz	Fastqsanger.gz
	SRR18218672_2.fastq.gz	Fastqsanger.gz
	SRR18218673_1.fastq.gz	Fastqsanger.gz

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Preclinical efficacy and safety study of encapsulated human proliferating hepatocyte organoids in the treatment of liver failure

Project description:Purpose: The goals of this study are to analyze the NGS-derived transcriptome profiling (RNA-seq) between the normal, control and experimental group after extended hepatectomy. Results: All sequencing reads from RNA-seq were mapped to the mouse reference genome (GRCm38.84) using hisat2-2.10 (Kim et al., 2015). FPKM (fragments per kilobase of exon per million fragments mapped) values were calculated by Cufflinks v.2.2.1 (Trapnell et al., 2012) using default parameters for gene expression levels. We used htseq-count (Anders et al., 2015) to count reads on genes. Differential expression analysis was performed using DESeq2 (R package, (Love et al., 2014)). Genes were considered differentially expressed if FPKM >=1 in at least one sample and |fold change| >= 2, adjusted p-value < 0.05. The gene ontology analyses was performed using Metascape v3.5 (http://metascape.org/gp/index.html, (Zhou et al., 2019)). Principal component analysis was performed with whole genes using the R package (function: prcomp()). Conclusions: Our study represents the first detailed analysis of liver transcriptomes after extended hepatectomy, 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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