Long non-coding RNAs (lncRNAs) are a potential new cell line engineering tool for improvement of yield and stability of CHO cells. In this study, we performed RNA sequencing of mAb producer CHO clones to study the lncRNA and protein coding transcriptome in relation to productivity. First, a robust linear model was used to identify genes correlating to productivity. To unravel specific patterns in expression of these genes, we employed weighted gene coexpression analysis (WGCNA) to find coexpressed modules, looking both for lncRNAs and coding genes. There was little overlap in the genes associated with productivity between the two products studied, possibly due to the difference in absolute range of productivity between the two mAbs. Therefore, we focused on the product with higher productivity and stronger candidate lncRNAs. To evaluate their potential as engineering targets, these candidate lncRNAs were transiently overexpressed or deleted by stable CRISPR Cas9 knock out both in a high and a low productivity subclone. We found that the thus achieved expression level of the identified lncRNAs, as confirmed by qPCR, does correlate well to productivity, so that they represent good markers that may be used for early clone selection. Additionally, we found that the deletion of one tested lncRNA region decreased viable cell density (VCD), prolonged culture time and increased cell size, final titer and specific productivity per cell. These results demonstrate the feasibility and usefulness of engineering lncRNA expression in production cell lines.
Keywords: CHO cells; Gene coexpression network analysis; Productivity; RNA sequencing; lncRNA.
Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.