The long non-coding RNA transcriptome landscape in CHO cells

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.

Vito D, Smales CM. (2018) The Long Non-Coding RNA Transcriptome Landscape in CHO Cells Under Batch and Fed-Batch Conditions. Biotechnol J [Epub ahead of print]. [abstract]

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