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Theis, F.J. ; Latif, N.* ; Wong, P. ; Frishman, D.

Complex principal component and correlation structure of 16 yeast genomic variables.

Mol. Biol. Evol. 28, 2501-2512 (2011)
Verlagsversion DOI PMC
Open Access Gold
A quickly growing number of characteristics reflecting various aspects of gene function and evolution can be either measured experimentally or computed from DNA and protein sequences. The study of pairwise correlations between such quantitative genomic variables as well as collective analysis of their interrelations by multidimensional methods have delivered crucial insights into the processes of molecular evolution. Here, we present a principal component analysis (PCA) of 16 genomic variables from Saccharomyces cerevisiae, the largest data set analyzed so far. Because many missing values and potential outliers hinder the direct calculation of principal components, we introduce the application of Bayesian PCA. We confirm some of the previously established correlations, such as evolutionary rate versus protein expression, and reveal new correlations such as those between translational efficiency, phosphorylation density, and protein age. Although the first principal component primarily contrasts genomic change and protein expression, the second component separates variables related to gene existence and expressed protein functions. Enrichment analysis on genes affecting variable correlations unveils classes of influential genes. For example, although ribosomal and nuclear transport genes make important contributions to the correlation between protein isoelectric point and molecular weight, protein synthesis and amino acid metabolism genes help cause the lack of significant correlation between propensity for gene loss and protein age. We present the novel Quagmire database (Quantitative Genomics Resource) which allows exploring relationships between more genomic variables in three model organisms-Escherichia coli, S. cerevisiae, and Homo sapiens.
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Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Schlagwörter molecular evolution; genome analysis; proteomics; principal component; analysis; PROTEIN-PROTEIN INTERACTIONS; SACCHAROMYCES-CEREVISIAE; INTERACTION NETWORK; EVOLUTIONARY RATE; GENE DISPENSABILITY; INTEGRATED VIEW; HUB PROTEINS; DATABASE; EXPRESSION; DISORDER
Sprache englisch
Veröffentlichungsjahr 2011
HGF-Berichtsjahr 2011
ISSN (print) / ISBN 0737-4038
e-ISSN 1537-1719
Zeitschrift Molecular Biology and Evolution
Quellenangaben Band: 28, Heft: 9, Seiten: 2501-2512 Artikelnummer: , Supplement: ,
Verlag Oxford University Press
Verlagsort Oxford
Begutachtungsstatus Peer reviewed
Institut(e) Institute of Bioinformatics and Systems Biology (IBIS)
POF Topic(s) 30505 - New Technologies for Biomedical Discoveries
Forschungsfeld(er) Enabling and Novel Technologies
PSP-Element(e) G-503700-004
G-503700-001
DOI 10.1093/molbev/msr077
Scopus ID 80052137984
PubMed ID 21444651
Erfassungsdatum 2011-11-21
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