Gene duplication and phenotypic changes in the evolution of mammalian metabolic networks.
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ABSTRACT:
SUBMITTER: Bekaert M
PROVIDER: S-EPMC3904969 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Gene duplication has been widely recognized as a major driver of evolutionary change and organismal complexity through the generation of multi-gene families. Therefore, understanding the forces that govern the evolution of gene families through the retention or loss of duplicated genes is fundamentally important in our efforts to study genome evolution. Previous work from our lab has shown that ribosomal protein (RP) genes constitute one of the largest classes of conserved duplicated genes in mammals. This result was surprising due to the fact that ribosomal protein genes evolve slowly and transcript levels are very tightly regulated. In our present study, we identified and characterized all RP duplicates in eight mammalian genomes in order to investigate the tempo and mode of ribosomal protein family evolution. We show that a sizable number of duplicates are transcriptionally active and are very highly conserved. Furthermore, we conclude that existing gene duplication models do not readily account for the preservation of a very large number of intact retroduplicated ribosomal protein (RT-RP) genes observed in mammalian genomes. We suggest that selection against dominant-negative mutations may underlie the unexpected retention and conservation of duplicated RP genes, and may shape the fate of newly duplicated genes, regardless of duplication mechanism.
| S-EPMC4219774 | biostudies-literature
Project description:The majority of homeobox genes are highly conserved across animals, but the eutherian-specific ETCHbox genes, embryonically expressed and highly divergent duplicates of CRX, are a notable exception. Here we compare the ETCHbox genes of 34 mammalian species, uncovering dynamic patterns of gene loss and tandem duplication, including the presence of a large tandem array of LEUTX loci in the genome of the European rabbit (Oryctolagus cuniculus). Despite extensive gene gain and loss, all sampled species possess at least two ETCHbox genes, suggesting their collective role is indispensable. We find evidence for positive selection and show that TPRX1 and TPRX2 have been the subject of repeated gene conversion across the Boreoeutheria, homogenising their sequences and preventing divergence, especially in the homeobox region. Together, these results are consistent with a model where mammalian ETCHbox genes are dynamic in evolution due to functional overlap, yet have collective indispensable roles.
| S-EPMC8208926 | biostudies-literature
Project description:Human cytomegalovirus (HCMV) is a widespread pathogen that is particularly skillful at evading immune detection and defense mechanisms, largely due to extensive co-evolution with its host. One aspect of this co-evolution involves the acquisition of virally encoded G protein-coupled receptors (GPCRs) with homology to the chemokine receptor family. GPCRs are the largest family of cell surface proteins, found in organisms from yeast to humans, and they regulate a variety of cellular processes including development, sensory perception, and immune cell trafficking. The US27 and US28 genes are encoded by human and primate CMVs, but homologs are not found in the genomes of viruses infecting rodents or other species. Phylogenetic analysis was used to investigate the US27 and US28 genes, which are adjacent in the unique short (US) region of the HCMV genome, and their relationship to one another and to human chemokine receptor genes. The results indicate that both US27 and US28 share the same common ancestor with human chemokine receptor CX3CR1, suggesting that a single host gene was captured and a subsequent viral gene duplication event occurred. The US28 gene product (pUS28) has maintained the function of the ancestral gene and has the ability to bind and signal in response to CX3CL1/fractalkine, the natural ligand for CX3CR1. In contrast, pUS27 does not bind to any known chemokine ligand, and the sequence has diverged significantly, highlighted by the fact that pUS27 currently exhibits greater sequence similarity to human CCR1. While the evolutionary advantage of the gene duplication and neofunctionalization event remains unclear, the US27 and US28 genes are highly conserved among different HCMV strains and retained even in laboratory strains that have lost many virulence genes, suggesting that US27 and US28 have each evolved distinct, important functions during virus infection.
| S-EPMC5438267 | biostudies-literature
Project description:BACKGROUND: Sequence related families of genes and proteins are common in bacterial genomes. In Escherichia coli they constitute over half of the genome. The presence of families and superfamilies of proteins suggest a history of gene duplication and divergence during evolution. Genome encoded protein families, their size and functional composition, reflect metabolic potentials of the organisms they are found in. Comparing protein families of different organisms give insight into functional differences and similarities. RESULTS: Equivalent enzyme families with metabolic functions were selected from the genomes of four experimentally characterized bacteria belonging to separate genera. Both similarities and differences were detected in the protein family memberships, with more similarities being detected among the more closely related organisms. Protein family memberships reflected known metabolic characteristics of the organisms. Differences in divergence of functionally characterized enzyme family members accounted for characteristics of taxa known to differ in those biochemical properties and capabilities. While some members of the gene families will have been acquired by lateral exchange and other former family members will have been lost over time, duplication and divergence of genes and functions appear to have been a significant contributor to the functional diversity of today's microbes. CONCLUSIONS: Protein families seem likely to have arisen during evolution by gene duplication and divergence where the gene copies that have been retained are the variants that have led to distinct bacterial physiologies and taxa. Thus divergence of the duplicate enzymes has been a major process in the generation of different kinds of bacteria.
| S-EPMC2787491 | biostudies-literature
Project description:BackgroundConvergent 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.ResultsWe 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.ConclusionsThe 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.
| S-EPMC7414715 | biostudies-literature
Project description:Genomic duplication-divergence processes are the primary source of new protein functions and thereby contribute to the evolutionary expansion of functional molecular networks. Yet, it is still unclear to what extent such duplication-divergence processes also restrict by construction the emerging properties of molecular networks, regardless of any specific cellular functions. We address this question, here, focusing on the evolution of protein-protein interaction (PPI) networks. We solve a general duplication-divergence model, based on the statistically necessary deletions of protein-protein interactions arising from stochastic duplications at various genomic scales, from single-gene to whole-genome duplications. Major evolutionary scenarios are shown to depend on two global parameters only: (i) a protein conservation index (M), which controls the evolutionary history of PPI networks, and (ii) a distinct topology index (M') controlling their resulting structure. We then demonstrate that conserved, nondense networks, which are of prime biological relevance, are also necessarily scale-free by construction, irrespective of any evolutionary variations or fluctuations of the model parameters. It is shown to result from a fundamental linkage between individual protein conservation and network topology under general duplication-divergence evolution. By contrast, we find that conservation of network motifs with two or more proteins cannot be indefinitely preserved under general duplication-divergence evolution (independently from any network rewiring dynamics), in broad agreement with empirical evidence between phylogenetically distant species. All in all, these evolutionary constraints, inherent to duplication-divergence processes, appear to have largely controlled the overall topology and scale-dependent conservation of PPI networks, regardless of any specific biological function.
| S-EPMC2481380 | biostudies-literature
Project description:BackgroundThe architecture of biological networks has been reported to exhibit high level of modularity, and to some extent, topological modules of networks overlap with known functional modules. However, how the modular topology of the molecular network affects the evolution of its member proteins remains unclear.ResultsIn this work, the functional and evolutionary modularity of Homo sapiens (H. sapiens) metabolic network were investigated from a topological point of view. Network decomposition shows that the metabolic network is organized in a highly modular core-periphery way, in which the core modules are tightly linked together and perform basic metabolism functions, whereas the periphery modules only interact with few modules and accomplish relatively independent and specialized functions. Moreover, over half of the modules exhibit co-evolutionary feature and belong to specific evolutionary ages. Peripheral modules tend to evolve more cohesively and faster than core modules do.ConclusionThe correlation between functional, evolutionary and topological modularity suggests that the evolutionary history and functional requirements of metabolic systems have been imprinted in the architecture of metabolic networks. Such systems level analysis could demonstrate how the evolution of genes may be placed in a genome-scale network context, giving a novel perspective on molecular evolution.
| S-EPMC2001200 | biostudies-literature
Project description:Noise in gene expression can lead to reversible phenotypic switching. Several experimental studies have shown that the abundance distributions of proteins in a population of isogenic cells may display multiple distinct maxima. Each of these maxima may be associated with a subpopulation of a particular phenotype, the quantification of which is important for understanding cellular decision-making. Here, we devise a methodology which allows us to quantify multimodal gene expression distributions and single-cell power spectra in gene regulatory networks. Extending the commonly used linear noise approximation, we rigorously show that, in the limit of slow promoter dynamics, these distributions can be systematically approximated as a mixture of Gaussian components in a wide class of networks. The resulting closed-form approximation provides a practical tool for studying complex nonlinear gene regulatory networks that have thus far been amenable only to stochastic simulation. We demonstrate the applicability of our approach in a number of genetic networks, uncovering previously unidentified dynamical characteristics associated with phenotypic switching. Specifically, we elucidate how the interplay of transcriptional and translational regulation can be exploited to control the multimodality of gene expression distributions in two-promoter networks. We demonstrate how phenotypic switching leads to birhythmical expression in a genetic oscillator, and to hysteresis in phenotypic induction, thus highlighting the ability of regulatory networks to retain memory.
| S-EPMC4024914 | biostudies-literature
Project description:Phenotypic plasticity represents a capacity by which the organism changes its phenotypes in response to environmental stimuli. Despite its pivotal role in adaptive evolution, how phenotypic plasticity is genetically controlled remains elusive. Here, we develop a unified framework for coalescing all single nucleotide polymorphisms (SNPs) from a genome-wide association study (GWAS) into a quantitative graph. This framework integrates functional genetic mapping, evolutionary game theory, and predator-prey theory to decompose the net genetic effect of each SNP into its independent and dependent components. The independent effect arises from the intrinsic capacity of a SNP, only expressed when it is in isolation, whereas the dependent effect results from the extrinsic influence of other SNPs. The dependent effect is conceptually beyond the traditional definition of epistasis by not only characterizing the strength of epistasis but also capturing the bi-causality of epistasis and the sign of the causality. We implement functional clustering and variable selection to infer multilayer, sparse, and multiplex interactome networks from any dimension of genetic data. We design and conduct two GWAS experiments using Staphylococcus aureus, aimed to test the genetic mechanisms underlying the phenotypic plasticity of this species to vancomycin exposure and Escherichia coli coexistence. We reconstruct the two most comprehensive genetic networks for abiotic and biotic phenotypic plasticity. Pathway analysis shows that SNP-SNP epistasis for phenotypic plasticity can be annotated to protein-protein interactions through coding genes. Our model can unveil the regulatory mechanisms of significant loci and excavate missing heritability from some insignificant loci. Our multilayer genetic networks provide a systems tool for dissecting environment-induced evolution.
| S-EPMC8421358 | biostudies-literature
Project description:Recombination is an important source of metabolic innovation, especially in prokaryotes, which have evolved the ability to survive on many different sources of chemical elements and energy. Metabolic systems have a well-understood genotype-phenotype relationship, which permits a quantitative and biochemically principled understanding of how recombination creates novel phenotypes. Here, we investigate the power of recombination to create genome-scale metabolic reaction networks that enable an organism to survive in new chemical environments. To this end, we use flux balance analysis, an experimentally validated computational method that can predict metabolic phenotypes from metabolic genotypes. We show that recombination is much more likely to create novel metabolic abilities than random changes in chemical reactions of a metabolic network. We also find that phenotypic innovation is more likely when recombination occurs between parents that are genetically closely related, phenotypically highly diverse, and viable on few rather than many carbon sources. Survival on a new carbon source preferentially involves reactions that are superessential, that is, essential in many metabolic networks. We validate our observations with data from 61 reconstructed prokaryotic metabolic networks. Our systematic and quantitative analysis of metabolic systems helps understand how recombination creates innovation.
| S-EPMC5046906 | biostudies-literature