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

Roberto Olivares Hernandez (Institutionen för kemi- och bioteknik, Systembiologi) ; R. Usaite ; Jens B. Nielsen (Institutionen för kemi- och bioteknik, Systembiologi)
Biotechnology and Bioengineering (0006-3592). Vol. 107 (2010), 5, p. 865-875.
[Artikel, refereegranskad vetenskaplig]

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.

Nyckelord: Saccharomyces cerevisiae, proteome, transcriptome, correlation, messenger-rna translation, saccharomyces-cerevisiae, mass-spectrometry, codon usage, metabolic network, genomic scale, expression, abundance, specificity, selection

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Denna post skapades 2010-12-15. Senast ändrad 2014-10-27.
CPL Pubid: 130890


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Institutioner (Chalmers)

Institutionen för kemi- och bioteknik, Systembiologi (2008-2014)


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Chalmers infrastruktur

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Systems Biology in Saccharomyces cerevisiae. Statistical data analysis and mathematical methods