Transcriptomics

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Next Generation Sequencing Facilitates Transcriptomes Quantitative Analysis of siRNA mediated ASGR1 knockdown


ABSTRACT: Purpose: The goal of this study is to demonstrate the gene profiles of ASGR1 knock down mediated by siRNA compared with siControl in Huh7 cells. Methods: The Huh7 cells were transfected with small interference RNA (siRNA) targeting scramble (WT) or ASGR1 (AS2) for 8 hours, then cells were refreshed with Dulbecco's Modified Eagle Medium (DMEM) supplemented with 100 units ml-1 penicillin, 100 μg ml-1 streptomycin sulfate, and 10% fetal bovine serum (FBS). After 72 hours, the cells were harvested for RNA isolation and followed by high-throughput sequencing, in triplicate, using Illumina GAIIx. The sequence reads that passed quality filters were analyzed at the transcriptome with Hisat2(v2.0.1). qRT–PCR validation was performed using SYBR Green assays. Results: Using an optimized data analysis workflow, we mapped about 45 million sequence reads per sample to the human genome in the WT and AS2 cell lines Hisat2 (v2.0.1). RNA-seq data confirmed stable expression of the known housekeeping genes, and these genes were validated with qRT–PCR. RNA-seq data had a linear relationship with qRT–PCR for more than a goodness of fit (R2) of 0.9. Approximately 4.2% of the transcripts showed significantly differential expression between the WT and AS2 cell lines, with a log2 fold change ≥1.0 and p value <0.05. Altered expression of 5 genes was confirmed with qRT–PCR, demonstrating the high degree of sensitivity of the RNA-seq method. Conclusions: Our study represents the first detailed transcriptomes analysis of ASGR1 knock down in Huh7 cells, 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 the WT and AS2 cell. We conclude that RNA-seq based transcriptome characterization would expedite genetic network analyses and permit the dissection of complex biologic functions.

ORGANISM(S): Homo sapiens

PROVIDER: GSE183013 | GEO | 2022/05/19

REPOSITORIES: GEO

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