Modeling coding-sequence evolution within the context of residue solvent accessibility.

BACKGROUND: Protein structure mediates site-specific patterns of sequence divergence. In particular, residues in the core of a protein (solvent-inaccessible residues) tend to be more evolutionarily conserved than residues on the surface (solvent-accessible residues). RESULTS: Here, we present a model of sequence evolution that explicitly accounts for the relative solvent accessibility of each residue in a protein. Our model is a variant of the Goldman-Yang 1994 (GY94) model in which all model parameters can be functions of the relative solvent accessibility (RSA) of a residue. We apply this model to a data set comprised of nearly 600 yeast genes, and find that an evolutionary-rate ratio ω that varies linearly with RSA provides a better model fit than an RSA-independent ω or an ω that is estimated separately in individual RSA bins. We further show that the branch length t and the transition-transverion ratio κ also vary with RSA. The RSA-dependent GY94 model performs better than an RSA-dependent Muse-Gaut 1994 (MG94) model in which the synonymous and non-synonymous rates individually are linear functions of RSA. Finally, protein core size affects the slope of the linear relationship between ω and RSA, and gene expression level affects both the intercept and the slope. CONCLUSIONS: Structure-aware models of sequence evolution provide a significantly better fit than traditional models that neglect structure. The linear relationship between ω and RSA implies that genes are better characterized by their ω slope and intercept than by just their mean ω.

The relationship between relative solvent accessibility and evolutionary rate in protein evolution.

Recent work with Saccharomyces cerevisiae shows a linear relationship between the evolutionary rate of sites and the relative solvent accessibility (RSA) of the corresponding residues in the folded protein. Here, we aim to develop a mathematical model that can reproduce this linear relationship. We first demonstrate that two models that both seem reasonable choices (a simple model in which selection strength correlates with RSA and a more complex model based on RSA-dependent amino acid distributions) fail to reproduce the observed relationship. We then develop a model on the basis of observed site-specific amino acid distributions and show that this model behaves appropriately. We conclude that evolutionary rates are directly linked to the distribution of amino acids at individual sites. Because of this link, any future insight into the biophysical mechanisms that determine amino acid distributions will improve our understanding of evolutionary rates.

Very bright green fluorescent proteins from the Pontellid copepod Pontella mimocerami.

BACKGROUND: Fluorescent proteins (FP) homologous to the green fluorescent protein (GFP) from the jellyfish Aequorea victoria have revolutionized biomedical research due to their usefulness as genetically encoded fluorescent labels. Fluorescent proteins from copepods are particularly promising due to their high brightness and rapid fluorescence development. RESULTS: Here we report two novel FPs from Pontella mimocerami (Copepoda, Calanoida, Pontellidae), which were identified via fluorescence screening of a bacterial cDNA expression library prepared from the whole-body total RNA of the animal. The proteins are very similar in sequence and spectroscopic properties. They possess high molar extinction coefficients (79,000 M(-1) cm(-)) and quantum yields (0.92), which make them more than two-fold brighter than the most common FP marker, EGFP. Both proteins form oligomers, which we were able to counteract to some extent by mutagenesis of the N-terminal region; however, this particular modification resulted in substantial drop in brightness. CONCLUSIONS: The spectroscopic characteristics of the two P. mimocerami proteins place them among the brightest green FPs ever described. These proteins may therefore become valuable additions to the in vivo imaging toolkit.