A new, fast algorithm for detecting protein coevolution using maximum compatible cliques

Characterizing human genomic coevolution in locus-gene regulatory interactions

Background

Coevolution has been used to identify and predict interactions and functional relationships between proteins of many different organisms including humans. Current efforts in annotating the human genome increasingly show that non-coding DNA sequence has important functional and regulatory interactions. Furthermore, regulatory elements do not necessarily reside in close proximity of the coding region for their target genes.

Results

We characterize coevolution as it appears in locus-gene interactions in the human genome, focusing on expression Quantitative Trait - Locus (eQTL) interactions. Our results show that in these interactions the conservation status of the loci is predictive of the conservation status of their target genes. Furthermore, comparing the phylogenetic histories of intra-chromosomal pairs of loci and transcription start sites, we find that pairs that appear coevolved are enriched for cis-eQTL interactions. Exploring this property we found that coevolution might be useful in prioritizing association tests in cis-eQTL detection.

Conclusions

The relationship between the conservation status of pairs of loci and protein coding transcription start sites reveal correlations with regulatory interactions. Pairs that appear coevolved are enriched for intra-chromosomal regulatory interactions, thus our results suggest that measures of coevolution can be useful for prediction and detection of new interactions. Measures of coevolution are genome-wide and could potentially be used to prioritize the detection of distant or inter-chromosomal interactions such as trans-eQTL interactions in the human genome.

PrePhyloPro: phylogenetic profile-based prediction of whole proteome linkages

Direct and indirect functional links between proteins as well as their interactions as part of larger protein complexes or common signaling pathways may be predicted by analyzing the correlation of their evolutionary patterns. Based on phylogenetic profiling, here we present a highly scalable and time-efficient computational framework for predicting linkages within the whole human proteome. We have validated this method through analysis of 3,697 human pathways and molecular complexes and a comparison of our results with the prediction outcomes of previously published co-occurrency model-based and normalization methods. Here we also introduce PrePhyloPro, a web-based software that uses our method for accurately predicting proteome-wide linkages. We present data on interactions of human mitochondrial proteins, verifying the performance of this software. PrePhyloPro is freely available at http://prephylopro.org/phyloprofile/.

Protein sites with more coevolutionary connections tend to evolve slower, while more variable protein families acquire higher coevolutionary connections

Background: Amino acid exchanges within proteins sometimes compensate for one another and could therefore be co-evolved. It is essential to investigate the intricate relationship between the extent of coevolution and the evolutionary variability exerted at individual protein sites, as well as the whole protein. Methods: In this study, we have used a reliable set of coevolutionary connections (sites within 10Å spatial distance) and investigated their correlation with the evolutionary diversity within the respective protein sites. Results: Based on our observations, we propose an interesting hypothesis that higher numbers of coevolutionary connections are associated with lesser evolutionary variable protein sites, while higher numbers of the coevolutionary connections can be observed for a protein family that has higher evolutionary variability. Our findings also indicate that highly coevolved sites located in a solvent accessible state tend to be less evolutionary variable. This relationship reverts at the whole protein level where cytoplasmic and extracellular proteins show moderately higher anti-correlation between the number of coevolutionary connections and the average evolutionary conservation of the whole protein. Conclusions: Observations and hypothesis presented in this study provide intriguing insights towards understanding the critical relationship between coevolutionary and evolutionary changes observed within proteins. Our observations encourage further investigation to find out the reasons behind subtle variations in the relationship between coevolutionary connectivity and evolutionary diversity for proteins located at various cellular localizations and/or involved in different molecular-biological functions.

Rapid molecular evolution across amniotes of the IIS/TOR network

The insulin/insulin-like signaling and target of rapamycin (IIS/TOR) network regulates lifespan and reproduction, as well as metabolic diseases, cancer, and aging. Despite its vital role in health, comparative analyses of IIS/TOR have been limited to invertebrates and mammals. We conducted an extensive evolutionary analysis of the IIS/TOR network across 66 amniotes with 18 newly generated transcriptomes from nonavian reptiles and additional available genomes/transcriptomes. We uncovered rapid and extensive molecular evolution between reptiles (including birds) and mammals: (i) the IIS/TOR network, including the critical nodes insulin receptor substrate (IRS) and phosphatidylinositol 3-kinase (PI3K), exhibit divergent evolutionary rates between reptiles and mammals; (ii) compared with a proxy for the rest of the genome, genes of the IIS/TOR extracellular network exhibit exceptionally fast evolutionary rates; and (iii) signatures of positive selection and coevolution of the extracellular network suggest reptile- and mammal-specific interactions between members of the network. In reptiles, positively selected sites cluster on the binding surfaces of insulin-like growth factor 1 (IGF1), IGF1 receptor (IGF1R), and insulin receptor (INSR); whereas in mammals, positively selected sites clustered on the IGF2 binding surface, suggesting that these hormone-receptor binding affinities are targets of positive selection. Further, contrary to reports that IGF2R binds IGF2 only in marsupial and placental mammals, we found positively selected sites clustered on the hormone binding surface of reptile IGF2R that suggest that IGF2R binds to IGF hormones in diverse taxa and may have evolved in reptiles. These data suggest that key IIS/TOR paralogs have sub- or neofunctionalized between mammals and reptiles and that this network may underlie fundamental life history and physiological differences between these amniote sister clades.

Practical aspects of protein co-evolution

Co-evolution is a fundamental aspect of Evolutionary Theory. At the molecular level, co-evolutionary linkages between protein families have been used as indicators of protein interactions and functional relationships from long ago. Due to the complexity of the problem and the amount of genomic data required for these approaches to achieve good performances, it took a relatively long time from the appearance of the first ideas and concepts to the quotidian application of these approaches and their incorporation to the standard toolboxes of bioinformaticians and molecular biologists. Today, these methodologies are mature (both in terms of performance and usability/implementation), and the genomic information that feeds them large enough to allow their general application. This review tries to summarize the current landscape of co-evolution-based methodologies, with a strong emphasis on describing interesting cases where their application to important biological systems, alone or in combination with other computational and experimental approaches, allowed getting new insight into these.

Slow co-evolution of the MAGO and Y14 protein families is required for the maintenance of their obligate heterodimerization mode

The exon junction complex (EJC) plays important roles in RNA metabolisms and the development of eukaryotic organisms. MAGO (short form of MAGO NASHI) and Y14 (also Tsunagi or RBM8) are the EJC core components. Their biological roles have been well investigated in various species, but the evolutionary patterns of the two gene families and their protein-protein interactions are poorly known. Genome-wide survey suggested that the MAGO and Y14 two gene families originated in eukaryotic organisms with the maintenance of a low copy. We found that the two protein families evolved slowly; however, the MAGO family under stringent purifying selection evolved more slowly than the Y14 family that was under relative relaxed purifying selection. MAGO and Y14 were obliged to form heterodimer in a eukaryotic organism, and this obligate mode was plesiomorphic. Lack of binding of MAGO to Y14 as functional barrier was observed only among distantly species, suggesting that a slow co-evolution of the two protein families. Inter-protein co-evolutionary signal was further quantified in analyses of the Tol-MirroTree and co-evolution analysis using protein sequences. About 20% of the 41 significantly correlated mutation groups (involving 97 residues) predicted between the two families was clade-specific. Moreover, around half of the predicted co-evolved groups and nearly all clade-specific residues fell into the minimal interaction domains of the two protein families. The mutagenesis effects of the clade-specific residues strengthened that the co-evolution is required for obligate MAGO-Y14 heterodimerization mode. In turn, the obliged heterodimerization in an organism serves as a strong functional constraint for the co-evolution of the MAGO and Y14 families. Such a co-evolution allows maintaining the interaction between the proteins through large evolutionary time scales. Our work shed a light on functional evolution of the EJC genes in eukaryotes, and facilitates to understand the co-evolutionary processes among protein families.

Evolution of gene neighborhoods within reconciled phylogenies

Motivation: Most models of genome evolution integrating gene duplications, losses and chromosomal rearrangements are computationally intract able, even when comparing only two genomes. This prevents large-scale studies that consider different types of genome structural variations.

Results: We define an ‘adjacency phylogenetic tree’ that describes the evolution of an adjacency, a neighborhood relation between two genes, by speciation, duplication or loss of one or both genes, and rearrangement. We describe an algorithm that, given a species tree and a set of gene trees where the leaves are connected by adjacencies, computes an adjacency forest that minimizes the number of gains and breakages of adjacencies (caused by rearrangements) and runs in polynomial time. We use this algorithm to reconstruct contiguous regions of mammalian and plant ancestral genomes in a few minutes for a dozen species and several thousand genes. We show that this method yields reduced conflict between ancestral adjacencies. We detect duplications involving several genes and compare the different modes of evolution between phyla and among lineages.

Availability: C++ implementation using BIO++ package, available upon request to Sèverine Bérard.

Contact:Severine.Berard@cirad.fr or Eric.Tannier@inria.fr

Supplementary information:Supplementary material is available at Bioinformatics online.

Citrus tristeza virus: Evolution of Complex and Varied Genotypic Groups

Amongst the Closteroviridae, Citrus tristeza virus (CTV) is almost unique in possessing a number of distinct and characterized strains, isolates of which produce a wide range of phenotype combinations among its different hosts. There is little understanding to connect genotypes to phenotypes, and to complicate matters more, these genotypes are found throughout the world as members of mixed populations within a single host plant. There is essentially no understanding of how combinations of genotypes affect symptom expression and disease severity. We know little about the evolution of the genotypes that have been characterized to date, little about the biological role of their diversity and particularly, about the effects of recombination. Additionally, genotype grouping has not been standardized. In this study we utilized an extensive array of CTV genomic information to classify the major genotypes, and to determine the major evolutionary processes that led to their formation and subsequent retention. Our analyses suggest that three major processes act on these genotypes: (1) ancestral diversification of the major CTV lineages, followed by (2) conservation and co-evolution of the major functional domains within, though not between CTV genotypes, and (3) extensive recombination between lineages that have given rise to new genotypes that have subsequently been retained within the global population. The effects of genotype diversity and host-interaction are discussed, as is a proposal for standardizing the classification of existing and novel CTV genotypes.

Correlated evolution of gonadotropin-releasing hormone and gonadotropin-inhibitory hormone and their receptors in mammals

BACKGROUND

Evolutionary rate variation in genes (proteins) is manifested both within the species (genome) and between the species (genomes). However, the interdependent components of a biological system in form of a gene or a protein are expected to evolve in a correlated manner under a common functional constraint.

METHODS

The phylogenetic analysis and correlation analysis of gonadotropin-releasing hormone (GnRH) and gonadotropin-inhibitory hormone (GnIH) and their receptors (GnRHR and GnIHR) was conducted along with other control neuropeptides.

RESULTS

Both neuropeptides and their receptors regulating the reproductive neuroendocrine axis in vertebrates exhibited a correlated evolution under a common physiological constraint to regulate the release of gonadotropin. This result supports a coordinated substitution of amino acids in the GnRH and the GnIH neuropeptides along with their receptors in terms of similar evolutionary rates and distances with similar nucleotide composition of genes.

CONCLUSION

This is the first demonstration of the correlated evolution of two components of an endocrine system regulating the release of gonadotropin which are acting in concert for successful reproduction.

Coevolution reveals a network of human proteins originating with multicellularity

Protein interaction networks play central roles in biological systems, from simple metabolic pathways through complex programs permitting the development of organisms. Multicellularity could only have arisen from a careful orchestration of cellular and molecular roles and responsibilities, all properly controlled and regulated. Disease reflects a breakdown of this organismal homeostasis. To better understand the evolution of interactions whose dysfunction may be contributing factors to disease, we derived the human protein coevolution network using our MatrixMatchMaker algorithm and using the Orthologous MAtrix project (OMA) database as a source for protein orthologs from 103 eukaryotic genomes. We annotated the coevolution network using protein–protein interaction data, many functional data sources, and we explored the evolutionary rates and dates of emergence of the proteins in our data set. Strikingly, clustering based only on the topology of the coevolution network partitions it into two subnetworks, one generally representing ancient eukaryotic functions and the other functions more recently acquired during animal evolution. That latter subnetwork is enriched for proteins with roles in cell–cell communication, the control of cell division, and related multicellular functions. Further annotation using data from genetic disease databases and cancer genome sequences strongly implicates these proteins in both ciliopathies and cancer. The enrichment for such disease markers in the animal network suggests a functional link between these coevolving proteins. Genetic validation corroborates the recruitment of ancient cilia in the evolution of multicellularity.

Protein sequence alignment analysis by local covariation: coevolution statistics detect benchmark alignment errors

The use of sequence alignments to understand protein families is ubiquitous in molecular biology. High quality alignments are difficult to build and protein alignment remains one of the largest open problems in computational biology. Misalignments can lead to inferential errors about protein structure, folding, function, phylogeny, and residue importance. Identifying alignment errors is difficult because alignments are built and validated on the same primary criteria: sequence conservation. Local covariation identifies systematic misalignments and is independent of conservation. We demonstrate an alignment curation tool, LoCo, that integrates local covariation scores with the Jalview alignment editor. Using LoCo, we illustrate how local covariation is capable of identifying alignment errors due to the reduction of positional independence in the region of misalignment. We highlight three alignments from the benchmark database, BAliBASE 3, that contain regions of high local covariation, and investigate the causes to illustrate these types of scenarios. Two alignments contain sequential and structural shifts that cause elevated local covariation. Realignment of these misaligned segments reduces local covariation; these alternative alignments are supported with structural evidence. We also show that local covariation identifies active site residues in a validated alignment of paralogous structures. Loco is available at https://sourceforge.net/projects/locoprotein/files/

Accelerated evolution and coevolution drove the evolutionary history of AGPase sub-units during angiosperm radiation

BACKGROUND AND AIMS

ADP-glucose pyrophosphorylase (AGPase) is a key enzyme of starch biosynthesis. In the green plant lineage, it is composed of two large (LSU) and two small (SSU) sub-units encoded by paralogous genes, as a consequence of several rounds of duplication. First, our aim was to detect specific patterns of molecular evolution following duplication events and the divergence between monocotyledons and dicotyledons. Secondly, we investigated coevolution between amino acids both within and between sub-units.

METHODS

A phylogeny of each AGPase sub-unit was built using all gymnosperm and angiosperm sequences available in databases. Accelerated evolution along specific branches was tested using the ratio of the non-synonymous to the synonymous substitution rate. Coevolution between amino acids was investigated taking into account compensatory changes between co-substitutions.

KEY RESULTS

We showed that SSU paralogues evolved under high functional constraints during angiosperm radiation, with a significant level of coevolution between amino acids that participate in SSU major functions. In contrast, in the LSU paralogues, we identified residues under positive selection (1) following the first LSU duplication that gave rise to two paralogues mainly expressed in angiosperm source and sink tissues, respectively; and (2) following the emergence of grass-specific paralogues expressed in the endosperm. Finally, we found coevolution between residues that belong to the interaction domains of both sub-units.

CONCLUSIONS

Our results support the view that coevolution among amino acid residues, especially those lying in the interaction domain of each sub-unit, played an important role in AGPase evolution. First, within SSU, coevolution allowed compensating mutations in a highly constrained context. Secondly, the LSU paralogues probably acquired tissue-specific expression and regulatory properties via the coevolution between sub-unit interacting domains. Finally, the pattern we observed during LSU evolution is consistent with repeated sub-functionalization under 'Escape from Adaptive Conflict', a model rarely illustrated in the literature.