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 | 2014
REPOSITORIES: biostudies-literature
Publications
Gene duplication and phenotypic changes in the evolution of mammalian metabolic networks.
Bekaert Michaël M Conant Gavin C GC
PloS one 20140128 1
Metabolic networks attempt to describe the complete suite of biochemical reactions available to an organism. One notable feature of these networks in mammals is the large number of distinct proteins that catalyze the same reaction. While the existence of these isoenzymes has long been known, their evolutionary significance is still unclear. Using a phylogenetically-aware comparative genomics approach, we infer enzyme orthology networks for sixteen mammals as well as for their common ancestors. W ...[more]
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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.
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Project description:BackgroundResearch on gene duplication is abundant and comes from a wide range of approaches, from high-throughput analyses and experimental evolution to bioinformatics and theoretical models. Notwithstanding, a consensus is still lacking regarding evolutionary mechanisms involved in evolution through gene duplication as well as the conditions that affect them. We argue that a better understanding of evolution through gene duplication requires considering explicitly that genes do not act in isolation. It demands studying how the perturbation that gene duplication implies percolates through the web of gene interactions. Due to evolution's contingent nature, the paths that lead to the final fate of duplicates must depend strongly on the early stages of gene duplication, before gene copies have accumulated distinctive changes.MethodsHere we use a widely-known model of gene regulatory networks to study how gene duplication affects network behavior in early stages. Such networks comprise sets of genes that cross-regulate. They organize gene activity creating the gene expression patterns that give cells their phenotypic properties. We focus on how duplication affects two evolutionarily relevant properties of gene regulatory networks: mitigation of the effect of new mutations and access to new phenotypic variants through mutation.ResultsAmong other observations, we find that those networks that are better at maintaining the original phenotype after duplication are usually also better at buffering the effect of single interaction mutations and that duplication tends to enhance further this ability. Moreover, the effect of mutations after duplication depends on both the kind of mutation and genes involved in it. We also found that those phenotypes that had easier access through mutation before duplication had higher chances of remaining accessible through new mutations after duplication.ConclusionOur results support that gene duplication often mitigates the impact of new mutations and that this effect is not merely due to changes in the number of genes. The work that we put forward helps to identify conditions under which gene duplication may enhance evolvability and robustness to mutations.
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Project description:Even though gene duplication is a key source of new genes and evolutionary innovation, it is unclear how duplicates survive the period immediately following gene duplication, in which both copies are functionally redundant. In the absence of epigenetic silencing, the abundance of the gene product would double after gene duplication, which would often have deleterious effects. However, recent duplicates exhibit low expression levels, which could be at least partially explained by high levels of promoter methylation. What evolutionary paths lead to duplicate hypermethylation, and does it affect both duplicates, or only one? Here, we compare levels of promoter methylation in 10 human and 16 mouse tissues, between singletons and duplicates and among human-mouse orthologs of different kinds (one-to-one, one-to-many, many-to-one, and many-to-many). Our results indicate that: (1) on average, duplicates are more methylated than singletons in mouse, but less methylated than singletons in human, (2) recently duplicated genes tend to exhibit high levels of promoter methylation, (3) genes that undergo duplication tend to be highly methylated before duplication, (4) after gene duplication, one of the copies (the daughter copy, i.e. the one that relocates to a new genomic context) tends to undergo an additional increase in promoter methylation, whereas the other (the parental copy, which remains in the original genomic location) tends to retain pre-duplication methylation levels, and (5) daughter copies tend to be lowly expressed. These observations support a model in which daughter copies are repressed via promoter hypermethylation and can thus survive the filter of purifying selection until both copies diverge functionally.
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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.
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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.
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Project description:BackgroundSequence 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.ResultsEquivalent 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.ConclusionsProtein 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.
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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.
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