Into the unknown: expression profiling without genome sequence information in CHO by next generation sequencing

Abstract

The arrival of next-generation sequencing (NGS) technologies has led to novel opportunities for expression profiling and genome analysis by utilizing vast amounts of short read sequence data. Here, we demonstrate that expression profiling in organisms lacking any genome or transcriptome sequence information is feasible by combining Illumina’s mRNA-seq technology with a novel bioinformatics pipeline that integrates assembled and annotated Chinese hamster ovary (CHO) sequences with information derived from related organisms. We applied this pipeline to the analysis of CHO cells which were chosen as a model system owing to its relevance in the production of therapeutic proteins. Specifically, we analysed CHO cells undergoing butyrate treatment which is known to affect cell cycle regulation and to increase the specific productivity of recombinant proteins. By this means, we identified sequences for >13 000 CHO genes which added sequence information of ∼5000 novel genes to the CHO model. More than 6000 transcript sequences are predicted to be complete, as they covered >95% of the corresponding mouse orthologs. Detailed analysis of selected biological functions such as DNA replication and cell cycle control, demonstrated the potential of NGS expression profiling in organisms without extended genome sequence to improve both data quantity and quality.

De novo assembly and characterization of skin transcriptome using RNAseq in sheep (Ovis aries)

“…Currently, the development of new-generation sequencing and RNA sequencing (RNASeq) provides new approaches that may elucidate the molecular regulation mechanism of hair follicle development (Jager et al, 2011;Okano et al, 2012;Geng et al, 2013). New-generation sequence technologies have opened the door to genome-scale experiments in organisms that lack comprehensive genome or transcriptome information, thus making it possible to assemble novel transcripts and identify differential regulation in a single experiment (Birzele et al, 2010;Sun et al, 2010;Abyzov et al, 2012).…”

Supplementation of serum free media with HT is not sufficient to restore growth properties of DHFR−/− cells in fed-batch processes – Implications for designing novel CHO-based expression platforms

“…These platforms include optimized vector systems, selection and amplification protocols, sophisticated and partly automated screening procedures as well as media and process platforms tailor-made for the individual needs of the CHO host cell clone. Moreover, transcriptomics (Nissom et al, 2006;Birzele et al, 2010;Kantardjieff et al, 2010), proteomics (Meleady, 2007;Pascoe et al, 2007) and metabolomics approaches (Nolan and Lee, 2011;Chong et al, 2010) have been used to elucidate the regulatory mechanisms within this host cell and genetic modifications might have been introduced to enhance viability, cellular productivity or other beneficial properties (for review, see also Kuystermans et al, 2007;Mohan et al, 2008). Thus, high titers achieved through effec- tive gene amplification as well as the know-how built around them made DHFR-deficient CHO cells very successful production host cells for the biopharmaceutical industry.…”

Genomic landscapes of Chinese hamster ovary cell lines as revealed by the Cricetulus griseus draft genome

“…Meanwhile, efforts to engineer mouse cells have greatly benefited from numerous genomic tools and technologies, owing in large part to the availability of the Mus musculus reference genome sequence. Genomic resources are also becoming available for CHO cells, such as the CHO-K1 genome 5 , expressed sequence tag 6,7 and bacterial artificial chromosome (BAC) libraries 8 , and compendia of proteomic [9][10][11] and transcriptomic data 7,[12][13][14][15][16] . However, much like how murine cell line data are routinely studied in the context of the Mus musculus reference genome, there is a need for a standard reference for all CHO cell lines to contextualize all of these valuable genomic resources.…”