Effective estimation of the minimum number of amino acid residues required for functional divergence between duplicate genes

Anciently duplicated genes continuously recruited to heart expression in vertebrate evolution are associated with heart chamber increase

Although gene/genome duplications in the early stage of vertebrates have been thought to provide major resources of raw genetic materials for evolutionary innovations, it is unclear whether they continuously contribute to the evolution of morphological complexity during the course of vertebrate evolution, such as the evolution from two heart chambers (fishes) to four heart chambers (mammals and birds). We addressed this issue by our heart RNA-Seq experiments combined with published data, using 13 vertebrates and one invertebrate (sea squirt, as an outgroup). Our evolutionary transcriptome analysis showed that number of ancient paralogous genes expressed in heart tends to increase with the increase of heart chamber number along the vertebrate phylogeny, in spite that most of them were duplicated at the time near to the origin of vertebrates or even more ancient. Moreover, those paralogs expressed in heart exert considerably different functions from heart-expressed singletons: the former are functionally enriched in cardiac muscle and muscle contraction-related categories, whereas the latter play more basic functions of energy generation like aerobic respiration. These findings together support the notion that recruiting anciently paralogous genes that are expressed in heart is associated with the increase of chamber number in vertebrate evolution.

Binding of single-mutant epidermal growth factor (EGF) ligands alters the stability of the EGF receptor dimer and promotes growth signaling

The epidermal growth factor receptor (EGFR) is a membrane-anchored tyrosine kinase that is able to selectively respond to multiple extracellular stimuli. Previous studies have indicated that the modularity of this system may be caused by ligand-induced differences in the stability of the receptor dimer. However, this hypothesis has not been explored using single-mutant ligands thus far. Herein, we developed a new approach to identify residues responsible for functional divergence by selecting residues in the epidermal growth factor (EGF) ligand that are conserved among orthologs yet divergent between paralogs. Then, we mutated these residues and assessed the mutants' effects on the receptor using a combination of molecular dynamics (MD) and biochemical techniques. Although the EGF mutants had binding affinities for the EGFR comparable with the WT ligand, the EGF mutants showed differential patterns of receptor phosphorylation and cell growth in multiple cell lines. The MD simulations of the EGF mutants indicated that mutations had long-range effects on the receptor dimer interface. This study shows for the first time that a single mutation in the EGF is sufficient to alter the activation of the EGFR signaling pathway at the cellular level. These results also support that biased ligand-receptor signaling in the tyrosine kinase receptor system can lead to differential downstream outcomes and demonstrate a promising new method to study ligand-receptor interactions.

Recurrent sequence evolution after independent gene duplication

Background

Convergent and parallel evolution provide unique insights into the mechanisms of natural selection. Some of the most striking convergent and parallel (collectively recurrent) amino acid substitutions in proteins are adaptive, but there are also many that are selectively neutral. Accordingly, genome-wide assessment has shown that recurrent sequence evolution in orthologs is chiefly explained by nearly neutral evolution. For paralogs, more frequent functional change is expected because additional copies are generally not retained if they do not acquire their own niche. Yet, it is unknown to what extent recurrent sequence differentiation is discernible after independent gene duplications in different eukaryotic taxa.

Results

We develop a framework that detects patterns of recurrent sequence evolution in duplicated genes. This is used to analyze the genomes of 90 diverse eukaryotes. We find a remarkable number of families with a potentially predictable functional differentiation following gene duplication. In some protein families, more than ten independent duplications show a similar sequence-level differentiation between paralogs. Based on further analysis, the sequence divergence is found to be generally asymmetric. Moreover, about 6% of the recurrent sequence evolution between paralog pairs can be attributed to recurrent differentiation of subcellular localization. Finally, we reveal the specific recurrent patterns for the gene families Hint1/Hint2, Sco1/Sco2 and vma11/vma3.

Conclusions

The presented methodology provides a means to study the biochemical underpinning of functional differentiation between paralogs. For instance, two abundantly repeated substitutions are identified between independently derived Sco1 and Sco2 paralogs. Such identified substitutions allow direct experimental testing of the biological role of these residues for the repeated functional differentiation. We also uncover a diverse set of families with recurrent sequence evolution and reveal trends in the functional and evolutionary trajectories of this hitherto understudied phenomenon.

Genomic Survey of Tyrosine Kinases Repertoire in Electrophorus electricus With an Emphasis on Evolutionary Conservation and Diversification

Tyrosine kinases (TKs) play key roles in the regulation of multicellularity in organisms and involved primarily in cell growth, differentiation, and cell-to-cell communication. Genome-wide characterization of TKs has been conducted in many metazoans; however, systematic information regarding this superfamily in Electrophorus electricus (electric eel) is still lacking. In this study, we identified 114 TK genes in the E electricus genome and investigated their evolution, molecular features, and domain architecture using phylogenetic profiling to gain a better understanding of their similarities and specificity. Our results suggested that the electric eel TK (EeTK) repertoire was shaped by whole-genome duplications (WGDs) and tandem duplication events. Compared with other vertebrate TKs, gene members in Jak, Src, and EGFR subfamily duplicated specifically, but with members lost in Eph, Axl, and Ack subfamily in electric eel. We also conducted an exhaustive survey of TK genes in genomic databases, identifying 1674 TK proteins in 31 representative species covering all the main metazoan lineages. Extensive evolutionary analysis indicated that TK repertoire in vertebrates tended to be remarkably conserved, but the gene members in each subfamily were very variable. Comparative expression profile analysis showed that electric organ tissues and muscle shared a similar pattern with specific highly expressed TKs (ie, epha7, musk, jak1, and pdgfra), suggesting that regulation of TKs might play an important role in specifying an electric organ identity from its muscle precursor. We further identified TK genes exhibiting tissue-specific expression patterns, indicating that members in TKs participated in subfunctionalization representing an evolutionary divergence required for the performance of different tissues. This work generates valuable information for further gene function analysis and identifying candidate TK genes reflecting their unique tissue-function specializations in electric eel.

Prediction of Protein-Ligand Interaction Based on the Positional Similarity Scores Derived from Amino Acid Sequences

The affinity of different drug-like ligands to multiple protein targets reflects general chemical–biological interactions. Computational methods estimating such interactions analyze the available information about the structure of the targets, ligands, or both. Prediction of protein–ligand interactions based on pairwise sequence alignment provides reasonable accuracy if the ligands’ specificity well coincides with the phylogenic taxonomy of the proteins. Methods using multiple alignment require an accurate match of functionally significant residues. Such conditions may not be met in the case of diverged protein families. To overcome these limitations, we propose an approach based on the analysis of local sequence similarity within the set of analyzed proteins. The positional scores, calculated by sequence fragment comparisons, are used as input data for the Bayesian classifier. Our approach provides a prediction accuracy comparable or exceeding those of other methods. It was demonstrated on the popular Gold Standard test sets, presenting different sequence heterogeneity and varying from the group, including different protein families to the more specific groups. A reasonable prediction accuracy was also found for protein kinases, displaying weak relationships between sequence phylogeny and inhibitor specificity. Thus, our method can be applied to the broad area of protein–ligand interactions.