The role of non-coding RNAs in determining growth, productivity, and recombinant product quality attributes in Chinese hamster ovary (CHO) cells has received much attention in recent years, exemplified by studies into microRNAs in particular. However, other classes of non-coding RNAs have received less attention. One such class are the non-coding RNAs known collectively as long non-coding RNAs (lncRNAs).
Researchers at the University of Kent have undertaken the first landscape analysis of the lncRNA transcriptome in CHO using a mouse based microarray that also provided for the surveillance of the coding transcriptome. They report on those lncRNAs present in a model host CHO cell line under batch and fed-batch conditions on two different days and relate the expression of different lncRNAs to each other. The researchers demonstrate that the mouse microarray is suitable for the detection and analysis of thousands of CHO lncRNAs and validated a number of these by qRT-PCR. They then further analyzed the data to identify those lncRNAs whose expression changed the most between growth and stationary phases of culture or between batch and fed-batch culture to identify potential lncRNA targets for further functional studies with regard to their role in controlling growth of CHO cells. The researchers discuss the implications for the publication of this rich dataset and how this may be used by the community.
Summary of the experimental workflow
Growth and culture viability of a CHO-S cell line in Batch and Fed-batch cultures were measured for 10 days and samples for RNA extraction taken at Day 4 and at Day 7. The samples were analysed on a mouse array containing all the coding and non-coding transcripts stored in the main public databases. The measured intensities were log -normalized and differentially expressed transcripts/genes were filtered for a fold change (FC) ≥ 2 and an FDR ≤ 0.10. A selected group of genes was validated through RT-qPCR (Supplementary Material). Due to the poor annotation of lncRNAs in CHO, the identification of potential targets with a described biological role required the comparison of human and mouse literature and databases, followed by alignment against the Chinese hamster genome, leading to predicted lncRNAs transcripts and previously un-annotated genomic regions (Table 1). At the same time, GO and pathway enrichment was implemented on mRNAs.