Large-scale analysis of orthologs and paralogs under covarion-like and constant-but-different models of amino acid evolution

A Phylogenetic Rate Parameter Indicates Different Sequence Divergence Patterns in Orthologs and Paralogs

Heterotachy-the change in sequence evolutionary rate over time-is a common feature of protein molecular evolution. Decades of studies have shed light on the conditions under which heterotachy occurs, and there is evidence that site-specific evolutionary rate shifts are correlated with changes in protein function. Here, we present a large-scale, computational analysis using thousands of protein sequence alignments from animal and plant proteomes, representing genes related either by orthology (speciation events) or paralogy (gene duplication), to compare sequence divergence patterns in orthologous vs. paralogous sequence alignments. We use sequence-based phylogenetic analyses to infer overall sequence divergence (tree length/number of sequences) and to fit site-specific rates to a discrete gamma distribution with a shape parameter α. This inference method is applied to real protein sequence alignments, as well as alignments simulated under various models of protein sequence evolution. Our simulations indicate that sequence divergence and the α parameter are positively correlated when sequences evolve with heterotachy, meaning that inferred site rate distributions appear more uniform as sequences diverge. Divergence and α are also positively correlated in both orthologous and paralogous genes, but the average increase in α (as a function of divergence) is significantly higher in paralogous protein alignments than in orthologous alignments. This result is consistent with the widely held view that recently duplicated proteins initially evolve under relaxed selective pressure, promoting functional divergence by accumulation of amino acid replacements, and hence experience more evolutionary rate fluctuations than orthologous proteins. We discuss these findings in the context of the ortholog conjecture, a long-standing assumption in molecular evolution, which posits that protein sequences related by orthology tend to be more functionally conserved than paralogous proteins.

Expansion of fish CCL20_like chemokines by genome and local gene duplication: Characterisation and expression analysis of 10 CCL20_like chemokines in rainbow trout (Oncorhynchus mykiss)

Mammalian CCL20, or macrophage inflammatory protein-3α, can function as a homeostatic and inflammatory chemokine. In relation to the latter, it is responsible for the chemoattraction of lymphocytes and dendritic cells to mucosal immune sites under inflammatory and pathological conditions. CK1, CK8A and CK8B are rainbow trout (Oncorhynchus mykiss) CC chemokines that were reported previously to be phylogenetically related to mammalian CCL20. In the current study, an additional seven CCL20_L paralogues in rainbow trout are reported, that are divided into three subgroups and have been designated here as: CCL20_L1a (also referred to as CK1), CCL20_L1b1-2, CCL20_L2a (CK8A), CCL20_L2b (CK8B), CCL20_L3a, and CCL20_L3b1-4. Multiple CCL20_L genes were also identified in other salmonids that arose from both whole genome duplication and local gene duplication. Phylogenetic tree, homology and synteny analysis support that CCL20_L1-3 found in salmonids are also present in most teleosts arose from the 3 R whole genome duplication and in some species, local gene duplication. Like mammalian CCL20, rainbow trout CCL20_L molecules possess a high positive net charge with a pI of 9.34-10.16, that is reported to be important for antimicrobial activity. Rainbow trout CCL20_L paralogues are differentially expressed and in general highly expressed in mucosal tissues, such as gills, thymus and intestine. The expression levels of rainbow trout CCL20_L paralogues are increased during development and following PAMP/cytokine stimulation. For example, in RTS-11 cells CCL20_L3b1 and CCL20_L3b2 are highly up-regulated by LPS, Poly I:C, recombinant(r) IFNa and rIL-1β. Trout CCL20_L paralogues are also increased after Yersinia ruckeri infection or Poly I:C stimulation in vivo, with CCL20_L3b1 and CCL20_L3b2 again highly up-regulated. Overall, this is the first report of the complete CCL20 chemokine subfamily in rainbow trout, and the analysis of their expression and modulation in vitro and in vivo. These results suggest that teleosts possess divergent CCL20_L molecules that may have important roles in anti-viral/anti-bacterial defence and in mucosal immunity.

Further Simulations and Analyses Demonstrate Open Problems of Phylostratigraphy

Phylostratigraphy, originally designed for gene age estimation by BLAST-based protein homology searches of sequenced genomes, has been widely used for studying patterns and inferring mechanisms of gene origination and evolution. We previously showed by computer simulation that phylostratigraphy underestimates gene age for a nonnegligible fraction of genes and that the underestimation is severer for genes with certain properties such as fast evolution and short protein sequences. Consequently, many previously reported age distributions of gene properties may have been methodological artifacts rather than biological realities. Domazet-Lošo and colleagues recently argued that our simulations were flawed and that phylostratigraphic bias does not impact inferences about gene emergence and evolution. Here we discuss conceptual difficulties of phylostratigraphy, identify numerous problems in Domazet-Lošo et al.’s argument, reconfirm phylostratigraphic error using simulations suggested by Domazet-Lošo and colleagues, and demonstrate that a phylostratigraphic trend claimed to be robust to error disappears when genes likely to be error-resistant are analyzed. We conclude that extreme caution is needed in interpreting phylostratigraphic results because of the inherent biases of the method and that reanalysis using genes exhibiting no error in realistic simulations may help reduce spurious findings.

Evolutionary rate heterogeneity between multi- and single-interface hubs across human housekeeping and tissue-specific protein interaction network: Insights from proteins' and its partners' properties

Integrating gene expression into protein-protein interaction network (PPIN) leads to the construction of tissue-specific (TS) and housekeeping (HK) sub-networks, with distinctive TS- and HK-hubs. All such hub proteins are divided into multi-interface (MI) hubs and single-interface (SI) hubs, where MI hubs evolve slower than SI hubs. Here we explored the evolutionary rate difference between MI and SI proteins within TS- and HK-PPIN and observed that this difference is present only in TS, but not in HK-class. Next, we explored whether proteins' own properties or its partners' properties are more influential in such evolutionary discrepancy. Statistical analyses revealed that this evolutionary rate correlates negatively with protein's own properties like expression level, miRNA count, conformational diversity and functional properties and with its partners' properties like protein disorder and tissue expression similarity. Moreover, partial correlation and regression analysis revealed that both proteins' and its partners' properties have independent effects on protein evolutionary rate.

Tissue-Specificity of Gene Expression Diverges Slowly between Orthologs, and Rapidly between Paralogs

The ortholog conjecture implies that functional similarity between orthologous genes is higher than between paralogs. It has been supported using levels of expression and Gene Ontology term analysis, although the evidence was rather weak and there were also conflicting reports. In this study on 12 species we provide strong evidence of high conservation in tissue-specificity between orthologs, in contrast to low conservation between within-species paralogs. This allows us to shed a new light on the evolution of gene expression patterns. While there have been several studies of the correlation of expression between species, little is known about the evolution of tissue-specificity itself. Ortholog tissue-specificity is strongly conserved between all tetrapod species, with the lowest Pearson correlation between mouse and frog at r = 0.66. Tissue-specificity correlation decreases strongly with divergence time. Paralogs in human show much lower conservation, even for recent Primate-specific paralogs. When both paralogs from ancient whole genome duplication tissue-specific paralogs are tissue-specific, it is often to different tissues, while other tissue-specific paralogs are mostly specific to the same tissue. The same patterns are observed using human or mouse as focal species, and are robust to choices of datasets and of thresholds. Our results support the following model of evolution: in the absence of duplication, tissue-specificity evolves slowly, and tissue-specific genes do not change their main tissue of expression; after small-scale duplication the less expressed paralog loses the ancestral specificity, leading to an immediate difference between paralogs; over time, both paralogs become more broadly expressed, but remain poorly correlated. Finally, there is a small number of paralog pairs which stay tissue-specific with the same main tissue of expression, for at least 300 million years.

Coevolution of URAT1 and Uricase during Primate Evolution: Implications for Serum Urate Homeostasis and Gout

Uric acid is the highly insoluble end-product of purine metabolism in humans. Serum levels exceeding the solubility threshold can trigger formation of urate crystals resulting in gouty arthritis. Uric acid is primarily excreted through the kidneys with 90% reabsorbed back into the bloodstream through the uric acid transporter URAT1. This reabsorption process is essential for the high serum uric acid levels found in humans. We discovered that URAT1 proteins from humans and baboons have higher affinity for uric acid compared with transporters from rats and mice. This difference in transport kinetics of URAT1 orthologs, along with inability of modern apes to oxidize uric acid due to loss of the uricase enzyme, prompted us to ask whether these events occurred concomitantly during primate evolution. Ancestral URAT1 sequences were computationally inferred and ancient transporters were resurrected and assayed, revealing that affinity for uric acid was increased during the evolution of primates. This molecular fine-tuning occurred between the origins of simians and their diversification into New- and Old-World monkey and ape lineages. Remarkably, it was driven in large-part by only a few amino acid replacements within the transporter. This alteration in primate URAT1 coincided with changes in uricase that greatly diminished the enzymatic activity and took place 27–77 Ma. These results suggest that the modifications to URAT1 transporters were potentially adaptive and that maintaining more constant, high levels of serum uric acid may have provided an advantage to our primate ancestors.

Understanding the functional difference between growth arrest-specific protein 6 and protein S: an evolutionary approach

Although protein S (PROS1) and growth arrest-specific protein 6 (GAS6) proteins are homologous with a high degree of structural similarity, they are functionally different. The objectives of this study were to identify the evolutionary origins from which these functional differences arose. Bioinformatics methods were used to estimate the evolutionary divergence time and to detect the amino acid residues under functional divergence between GAS6 and PROS1. The properties of these residues were analysed in the light of their three-dimensional structures, such as their stability effects, the identification of electrostatic patches and the identification potential protein-protein interaction. The divergence between GAS6 and PROS1 probably occurred during the whole-genome duplications in vertebrates. A total of 78 amino acid sites were identified to be under functional divergence. One of these sites, Asn463, is involved in N-glycosylation in GAS6, but is mutated in PROS1, preventing this post-translational modification. Sites experiencing functional divergence tend to express a greater diversity of stabilizing/destabilizing effects than sites that do not experience such functional divergence. Three electrostatic patches in the LG1/LG2 domains were found to differ between GAS6 and PROS1. Finally, a surface responsible for protein-protein interactions was identified. These results may help researchers to analyse disease-causing mutations in the light of evolutionary and structural constraints, and link genetic pathology to clinical phenotypes.

Sequence-structure based phylogeny of GPCR Class A Rhodopsin receptors

Current methods of G protein coupled receptors (GPCRs) phylogenetic classification are sequence based and therefore inappropriate for highly divergent sequences, sharing low sequence identity. In this study, sequence structure profile based alignment generated by PROMALS3D was used to understand the GPCR Class A Rhodopsin superfamily evolution using the MEGA 5 software. Phylogenetic analysis included a combination of Neighbor-Joining method and Maximum Likelihood method, with 1000 bootstrap replicates. Our study was able to identify potential ligand association for Class A Orphans and putative/unclassified Class A receptors with no cognate ligand information: GPR21 and GPR52 with fatty acids; GPR75 with Neuropeptide Y; GPR82, GPR18, GPR141 with N-arachidonylglycine; GPR176 with Free fatty acids, GPR10 with Tachykinin & Neuropeptide Y; GPR85 with ATP, ADP & UDP glucose; GPR151 with Galanin; GPR153 and GPR162 with Adrenalin, Noradrenalin; GPR146, GPR139, GPR142 with Neuromedin, Ghrelin, Neuromedin U-25 & Thyrotropin-releasing hormone; GPR171 with ATP, ADP & UDP Glucose; GPR88, GPR135, GPR161, GPR101with 11-cis-retinal; GPR83 with Tackykinin; GPR148 with Prostanoids, GPR109b, GPR81, GPR31with ATP & UTP and GPR150 with GnRH I & GnRHII. Furthermore, we suggest that this study would prove useful in re-classification of receptors, selecting templates for homology modeling and identifying ligands which may show cross reactivity with other GPCRs as signaling via multiple ligands play a significant role in disease modulation.

Interchanging functionality among homologous elongation factors using signatures of heterotachy

Numerous models of molecular evolution have been formulated to describe the forces that shape sequence divergence among homologous proteins. These models have greatly enhanced our understanding of evolutionary processes. Rarely are such models empirically tested in the laboratory, and even more rare, are such models exploited to generate novel molecules useful for synthetic biology. Here, we experimentally demonstrate that the heterotachy model of evolution captures signatures of functional divergence among homologous elongation factors (EFs) between bacterial EF-Tu and eukaryotic eEF1A. These EFs are GTPases that participate in protein translation by presenting aminoacylated-tRNAs to the ribosome. Upon release from the ribosome, the EFs are recharged by nucleotide exchange factors EF-Ts in bacteria or eEF1B in eukaryotes. The two nucleotide exchange factors perform analogous functions despite not being homologous proteins. The heterotachy model was used to identify a set of sites in eEF1A/EF-Tu associated with eEF1B binding in eukaryotes and another reciprocal set associated with EF-Ts binding in bacteria. Introduction of bacterial EF-Tu residues at these sites into eEF1A protein efficiently disrupted binding of cognate eEF1B as well as endowed eEF1A with the novel ability to bind bacterial EF-Ts. We further demonstrate that eEF1A variants, unlike yeast wild-type, can function in a reconstituted in vitro bacterial translation system.

Residue mutations and their impact on protein structure and function: detecting beneficial and pathogenic changes

The present review focuses on the evolution of proteins and the impact of amino acid mutations on function from a structural perspective. Proteins evolve under the law of natural selection and undergo alternating periods of conservative evolution and of relatively rapid change. The likelihood of mutations being fixed in the genome depends on various factors, such as the fitness of the phenotype or the position of the residues in the three-dimensional structure. For example, co-evolution of residues located close together in three-dimensional space can occur to preserve global stability. Whereas point mutations can fine-tune the protein function, residue insertions and deletions (‘decorations’ at the structural level) can sometimes modify functional sites and protein interactions more dramatically. We discuss recent developments and tools to identify such episodic mutations, and examine their applications in medical research. Such tools have been tested on simulated data and applied to real data such as viruses or animal sequences. Traditionally, there has been little if any cross-talk between the fields of protein biophysics, protein structure–function and molecular evolution. However, the last several years have seen some exciting developments in combining these approaches to obtain an in-depth understanding of how proteins evolve. For example, a better understanding of how structural constraints affect protein evolution will greatly help us to optimize our models of sequence evolution. The present review explores this new synthesis of perspectives.

Complex patterns of divergence among green-sensitive (RH2a) African cichlid opsins revealed by Clade model analyses

BACKGROUND

Gene duplications play an important role in the evolution of functional protein diversity. Some models of duplicate gene evolution predict complex forms of paralog divergence; orthologous proteins may diverge as well, further complicating patterns of divergence among and within gene families. Consequently, studying the link between protein sequence evolution and duplication requires the use of flexible substitution models that can accommodate multiple shifts in selection across a phylogeny. Here, we employed a variety of codon substitution models, primarily Clade models, to explore how selective constraint evolved following the duplication of a green-sensitive (RH2a) visual pigment protein (opsin) in African cichlids. Past studies have linked opsin divergence to ecological and sexual divergence within the African cichlid adaptive radiation. Furthermore, biochemical and regulatory differences between the RH2aα and RH2aβ paralogs have been documented. It thus seems likely that selection varies in complex ways throughout this gene family.

RESULTS

Clade model analysis of African cichlid RH2a opsins revealed a large increase in the nonsynonymous-to-synonymous substitution rate ratio (ω) following the duplication, as well as an even larger increase, one consistent with positive selection, for Lake Tanganyikan cichlid RH2aβ opsins. Analysis using the popular Branch-site models, by contrast, revealed no such alteration of constraint. Several amino acid sites known to influence spectral and non-spectral aspects of opsin biochemistry were found to be evolving divergently, suggesting that orthologous RH2a opsins may vary in terms of spectral sensitivity and response kinetics. Divergence appears to be occurring despite intronic gene conversion among the tandemly-arranged duplicates.

CONCLUSIONS

Our findings indicate that variation in selective constraint is associated with both gene duplication and divergence among orthologs in African cichlid RH2a opsins. At least some of this variation may reflect an adaptive response to differences in light environment. Interestingly, these patterns only became apparent through the use of Clade models, not through the use of the more widely employed Branch-site models; we suggest that this difference stems from the increased flexibility associated with Clade models. Our results thus bear both on studies of cichlid visual system evolution and on studies of gene family evolution in general.

The evolution of novelty in conserved gene families

One of the major aims of contemporary evolutionary biology is the understanding of the current pattern of biological diversity. This involves, first, the description of character distribution at various nodes of the phylogenetic tree of life and, second, the functional explanation of such changes. The analysis of character distribution is a powerful tool at both the morphological and molecular levels. Recent high-throughput sequencing approaches provide new opportunities to study the genetic architecture of organisms at the genome-wide level. In eukaryotes, one overarching finding is the absence of simple correlations of gene count and biological complexity. Instead, the domain architecture of proteins is becoming a central focus for large-scale evolutionary innovations. Here, we review examples of the evolution of novelty in conserved gene families in insects and nematodes. We highlight how in the absence of whole-genome duplications molecular novelty can arise, how members of gene families have diversified at distinct mechanistic levels, and how gene expression can be maintained in the context of multiple innovations in regulatory mechanisms.

Multidimensional scaling reveals the main evolutionary pathways of class A G-protein-coupled receptors

Class A G-protein-coupled receptors (GPCRs) constitute the largest family of transmembrane receptors in the human genome. Understanding the mechanisms which drove the evolution of such a large family would help understand the specificity of each GPCR sub-family with applications to drug design. To gain evolutionary information on class A GPCRs, we explored their sequence space by metric multidimensional scaling analysis (MDS). Three-dimensional mapping of human sequences shows a non-uniform distribution of GPCRs, organized in clusters that lay along four privileged directions. To interpret these directions, we projected supplementary sequences from different species onto the human space used as a reference. With this technique, we can easily monitor the evolutionary drift of several GPCR sub-families from cnidarians to humans. Results support a model of radiative evolution of class A GPCRs from a central node formed by peptide receptors. The privileged directions obtained from the MDS analysis are interpretable in terms of three main evolutionary pathways related to specific sequence determinants. The first pathway was initiated by a deletion in transmembrane helix 2 (TM2) and led to three sub-families by divergent evolution. The second pathway corresponds to the differentiation of the amine receptors. The third pathway corresponds to parallel evolution of several sub-families in relation with a covarion process involving proline residues in TM2 and TM5. As exemplified with GPCRs, the MDS projection technique is an important tool to compare orthologous sequence sets and to help decipher the mutational events that drove the evolution of protein families.

Fast statistical tests for detecting heterotachy in protein evolution

The w statistic introduced by Lockhart et al. (1998. A covariotide model explains apparent phylogenetic structure of oxygenic photosynthetic lineages. Mol Biol Evol. 15:1183-1188) is a simple and easily calculated statistic intended to detect heterotachy by comparing amino acid substitution patterns between two monophyletic groups of protein sequences. It is defined as the difference between the fraction of varied sites in both groups and the fraction of varied sites in each group. The w test has been used to distinguish a covarion process from equal rates and rates variation across sites processes. Using simulation we show that the w test is effective for small data sets and for data sets that have low substitution rates in the groups but can have difficulties when these conditions are not met. Using site entropy as a measure of variability of a sequence site, we modify the w statistic to a w' statistic by assigning as varied in one group those sites that are actually varied in both groups but have a large entropy difference. We show that the w' test has more power to detect two kinds of heterotachy processes (covarion and bivariate rate shifts) in large and variable data. We also show that a test of Pearson's correlation of the site entropies between two monophyletic groups can be used to detect heterotachy and has more power than the w' test. Furthermore, we demonstrate that there are settings where the correlation test as well as w and w' tests do not detect heterotachy signals in data simulated under a branch length mixture model. In such cases, it is sometimes possible to detect heterotachy through subselection of appropriate taxa. Finally, we discuss the abilities of the three statistical tests to detect a fourth mode of heterotachy: lineage-specific changes in proportion of variable sites.