Construction of a public CHO cell line transcript database using versatile bioinformatics analysis pipelines

Oliver Rupp1, Jennifer Becker2, Karina Brinkrolf3

  • 1Center for Biotechnology, Bielefeld University, Bielefeld, Germany ; Cell Culture Technology, Bielefeld University, Bielefeld, Germany ; Bioinformatics and Systems Biology, Justus-Liebig-University, Giessen, Germany.

Plos One
|January 16, 2014
PubMed

Insights

Researchers developed new methods to assemble Chinese hamster ovary (CHO) cell transcripts, significantly expanding the available data for this key mammalian expression system used in biopharmaceutical production.

Area of Science:

  • Biotechnology
  • Genomics
  • Molecular Biology

Background:

  • Chinese hamster ovary (CHO) cells are the primary mammalian expression system for therapeutic protein production.
  • Limited public data on CHO cell transcriptomes hinders biotechnological process optimization.
  • Existing annotation systems (GenDBE, SAMS) are foundational but require expanded transcript data.

Purpose of the Study:

  • To develop a high-quality CHO cell transcript set from extensive sequencing data.
  • To establish robust pipelines for assembling and improving CHO cell transcripts.
  • To create a publicly accessible platform for CHO cell genome/transcriptome analysis.

Main Methods:

  • Constructed cDNA libraries from diverse CHO cell lines and culture conditions.
  • Employed Roche/454 and Illumina sequencing technologies.
  • Utilized de novo assembly (Trinity, Oases, CAP3) and reference-based assembly (TopHat/Cufflinks, GMAP, cuffmerge) pipelines.

Main Results:

  • Assembled 28,874 transcripts from 16,492 gene loci using a combined approach.
  • Identified a total of 65,561 transcripts for CHO cell lines.
  • Clustered transcripts into 17,598 distinct gene clusters based on sequence identity.

Conclusions:

  • The developed strategy significantly enhances the available CHO cell transcript data.
  • This expanded dataset is crucial for advancing research and optimizing biopharmaceutical production using CHO cells.
  • The established pipelines and data contribute to a more comprehensive CHO cell analysis platform.