Translational selection and yeast proteome evolution
Amino acid altering mutations could
affect an organisms fitness through physiological effects that are independent
of their effects on protein function. Although individual amino acid mutations
are likely to have small effects on overall cell physiology, global evolutionary
forces could underlie proteome-wide patterns of amino acid composition as well
as variation in rates of protein evolution. In this project, the Saccharomyces
cerevisiae genome sequence, DNA microarray expression data, tRNA gene numbers,
and functional categorizations of proteins were employed to determine whether
the amino acid composition of peptides reflects natural selection to optimize
the speed and accuracy of translation.
Among microbes, as well as multicellular eukaryotes,
synonymous codon usage is co-adapted with tRNA pools to enhance the efficiency
of protein synthesis (reviewed in Akashi 2001). Differences in cellular concentrations
or codon-anticodon stability could lead to translation selection both within
and among synonymous families. Usage of several amino acids show associations
with gene expression (Figure 1), and changes in amino acid composition result
in stronger correlations between amino acid usage and tRNA abundances in highly
expressed genes than in less expressed loci (figure 2, 3). Similar relationships
within protein functional categories support that the primary structures of
proteins reflect natural selection to enhance the rate and accuracy of their
synthesis. Selection for efficient biosynthesis may also constrain protein size;
among proteins in the same broad functional category, proteins encoded by highly
expressed genes are consistently smaller than those encoded by less expressed
loci.
| Figure 1. Transcript abundance and amino acid usage. |
| Data are graphed for expression categories (bin sizes é5x104 codons). Abundances are among all codons. |
| Figure 2. Correlations between amino acid usage and tRNA gene copy numbers. |
| tRNA gene copy numbers from Percudani et al. (1997). The numbers are pooled among genes encoding isoacceptors for each amino acid. |
| Figure 3. Correlation between amino acid usage and tRNA gene copy numbers among expression classes. |
|  Data are graphed for expression categories (bin sizes é5x104 codons). Pearson product moment correlation coefficients between tRNA gene copy numbers and amino acid usage are plotted on the y-axis. |
References
Akashi, H., 2001 Gene expression and molecular evolution. Curr.
Op. Genet. Dev. 11: 660-666.
Akashi, H. 2003 Translational selection and yeast proteome evolution. Genetics
164: 1291-1303.
Percudani,
R., A. Pavesi and S. Ottonello, 1997 Transfer RNA gene redundancy and translational
selection in Saccharomyces cerevisiae. J Mol Biol 268: 322-330.