Integrative Analysis Using Proteome and Transcriptome Data From Yeast to Unravel Regulatory Patterns at Post-Transcriptional Level
Journal article, 2010

Exist several studies on the correlation between proteome and transcriptome and these studies have shown that generally there is only a weak positive correlation between the,e two omes, which means that post-transcriptional events play an important role in determining the protein levels in the cell In this stud) we combined proteome and transcriptome data from six different published dataset to identify patterns that can provide new insight into the reasons for these deviations By using a categorization method and integrating genome-scale information we found that the relation between protein and mRNA is related to the gene function We could further identify that for genes belonging to amino acid biosynthetic pathways there is no translational regulation, meaning that there is generally a good correlation between mRNA and protein levels We also found that there is generally translational control for large proteins and there also evidence for a role of conserved motifs m the 3' untranslated regions in the mRNA-protein correlation, probably by controlling the level of mRNA.

correlation

mass-spectrometry

codon usage

selection

expression

transcriptome

abundance

proteome

Saccharomyces cerevisiae

metabolic network

specificity

genomic scale

saccharomyces-cerevisiae

messenger-rna translation

Author

Roberto Olivares Hernandez

Chalmers, Chemical and Biological Engineering, Life Sciences

R. Usaite

Technical University of Denmark (DTU)

Jens B Nielsen

Chalmers, Chemical and Biological Engineering, Life Sciences

Biotechnology and Bioengineering

0006-3592 (ISSN) 1097-0290 (eISSN)

Vol. 107 5 865-875

Subject Categories

Industrial Biotechnology

Areas of Advance

Life Science Engineering (2010-2018)

DOI

10.1002/bit.22868

More information

Latest update

2/28/2018