Abstract:
:It is well-established that non-random patterns in coding DNA sequence (CDS) features can be partially explained by translational selection. Recent extensions of microarray and proteomic expression data have stimulated many genome-wide investigations of the relationships between gene expression and various CDS features. However, only modest correlations have been found. Here we introduced the one-way ANOVA, a more powerful extension of previous grouping methods, to re-examine these relationships at the whole genome scale for Saccharomyces cerevisiae, where genome-wide protein abundance has been recently quantified. Our results clarify that coding sequence features are inappropriate for use as genome-wide estimators for protein expression levels. This analysis also demonstrates that one-way ANOVA is a powerful and simple method to explore the influence of gene expression on CDS features.
journal_name
Biochem Biophys Res Communjournal_title
Biochemical and biophysical research communicationsauthors
Wu G,Nie L,Freeland SJdoi
10.1016/j.bbrc.2007.05.043subject
Has Abstractpub_date
2007-07-13 00:00:00pages
1108-13issue
4eissn
0006-291Xissn
1090-2104pii
S0006-291X(07)01014-5journal_volume
358pub_type
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