Transcriptomics is increasingly being used on Chinese hamster ovary (CHO) cells to unveil physiological insights related to their performance during production processes. The rich transcriptome data can be exploited to provide impetus for systems investigation such as modeling the central carbon metabolism or glycosylation pathways, or even building genome-scale models.
To harness the power of transcriptome assays, researchers from the University of Minnesota assembled and annotated a set of RNA-seq data from multiple CHO cell lines and Chinese hamster tissues, and constructed a DNA microarray. The identity of genes involved in major functional pathways and their transcript levels generated in this study will serve as a reference for future studies employing kinetic models. In particular, the data on glycolysis and glycosylation pathways indicate that the variability of gene expression level among different cell lines and tissues may contribute to their differences in metabolism and glycosylation patterns. Thereby, these insights can potentially lead to opportunities for cell engineering. This repertoire of transcriptome data also enables the identification of potential sequence variants in cell lines and allows tracing of cell lineages. Overall the study is an illustration of the potential benefit of RNA-seq that is yet to be exploited.