A bioinformatics pipeline for the identification of CHO cell differential gene expression from RNA-Seq data

TL;DR

This paper presents a computational pipeline for analyzing CHO cell RNA-Seq data to identify differentially expressed genes, aiding biopharmaceutical research with accessible tools and workflows.

Contribution

It introduces a new bioinformatics pipeline specifically designed for CHO cell RNA-Seq data analysis, including an example workflow and publicly available resources.

Findings

Pipeline successfully identifies differentially expressed genes in CHO cells

Workflow is freely accessible and reproducible

Enhances understanding of CHO cell transcriptome

Abstract

In recent years the publication of genome sequences for the Chinese hamster and Chinese hamster ovary (CHO) cell lines have facilitated study of these biopharmaceutical cell factories with unprecedented resolution. Our understanding of the CHO cell transcriptome, in particular, has rapidly advanced through the application of next-generation sequencing (NGS) technology to characterise RNA expression (RNA-Seq). In this chapter we present a computational pipeline for the analysis of CHO cell RNA-Seq data from the Illumina platform to identify differentially expressed genes. The example data and bioinformatics workflow required to run this analysis are freely available at www.cgcdb.org/rnaseq_analysis_protocol.html.