Molecular evolution and network-level analysis of the N-glycosylation metabolic pathway across primates

Human-specific features and developmental dynamics of the brain N-glycome

Comparative "omics" studies have revealed unique aspects of human neurobiology, yet an evolutionary perspective of the brain N-glycome is lacking. We performed multiregional characterization of rat, macaque, chimpanzee, and human brain N-glycomes using chromatography and mass spectrometry and then integrated these data with complementary glycotranscriptomic data. We found that, in primates, the brain N-glycome has diverged more rapidly than the underlying transcriptomic framework, providing a means for rapidly generating additional interspecies diversity. Our data suggest that brain N-glycome evolution in hominids has been characterized by an overall increase in complexity coupled with a shift toward increased usage of α(2-6)-linked N-acetylneuraminic acid. Moreover, interspecies differences in the cell type expression pattern of key glycogenes were identified, including some human-specific differences, which may underpin this evolutionary divergence. Last, by comparing the prenatal and adult human brain N-glycomes, we uncovered region-specific neurodevelopmental pathways that lead to distinct spatial N-glycosylation profiles in the mature brain.

Molecular characterization of MyD88 as a potential biomarker for pesticide-induced stress in Bombyx mori

The widespread use of pesticides hampers the immune system of non-target organisms, however, there is a lack of common biomarkers to detect such effects. Myeloid differentiation primary response factor 88 (MyD88) is a crucial junction protein in the Toll-like receptor signaling pathway, which plays an important role in the inflammatory response. In this study, we investigated MyD88 as a potential biomarker for pesticide-induced stress. Phylogenetic analysis revealed that MyD88 was a conserved protein in the evolution of vertebrates and invertebrates. MyD88s usually have death domain (DD) and Toll/interleukin-1 receptor (TIR) domain. Bombyx mori (B. mori) is an important economic insect that is sensitive to toxic substances. We found microbial pesticides enhanced the expression level of MyD88 in B. mori. Transcriptome analysis demonstrated that MyD88 expression level was increased in the fatbody after dinotefuran exposure, a third-generation neonicotinoid pesticide. Moreover, the expression of MyD88 was upregulated in fatbody and midgut by imidacloprid, a first-generation neonicotinoid pesticide. Additionally, insect growth regulator (IGR) pesticides, such as methoprene and fenoxycarb, could induce MyD88 expression in the fatbody of B. mori. These results indicated that MyD88 is a potential biomarker for pesticide-induced stress in B. mori. This study provides novel insights into screening common biomarkers for multiple pesticide stresses and important implications for the development of more sustainable pest management strategies.

Molecular evolution of GDP-L-galactose phosphorylase, a key regulatory gene in plant ascorbate biosynthesis

Ascorbic acid (AsA) is a widespread antioxidant in living organisms, and plays essential roles in the growth and development of animals and plants as well as in the response to abiotic stress tolerance. The GDP-L-galactose phosphorylase (GGP) is a key regulatory gene in plant AsA biosynthesis that can regulate the concentration of AsA at the transcriptional and translational levels. The function and regulation mechanisms of GGP have been well understood; however, the molecular evolutionary patterns of the gene remain unclear. In this study, a total of 149 homologous sequences of GGP were sampled from 71 plant species covering the major groups of Viridiplantae, and the phylogenetic relationships, gene duplication and molecular evolution analyses of the genes were systematically investigated. Results showed that GGP genes are present throughout the plant kingdom and five shared whole-genome duplications and several lineage-specific whole-genome duplications were found, which led to the rapid expansion of GGPs in seed plants, especially in angiosperms. The structure of GGP genes was more conserved in land plants, but varied greatly in green algae, indicating that GGP may have undergone great differentiation in the early stages of plant evolution. Most GGP proteins had a conserved motif arrangement and composition, suggesting that plant GGPs have similar catalytic functions. Molecular evolutionary analyses showed that GGP genes were predominated by purifying selection, indicating that the gene is functionally conserved due to its vital importance in AsA biosynthesis. Most of the branches under positive selection identified by the branch-site model were mainly in the chlorophytes lineage, indicating episodic diversifying selection may contribute to the evolution of GGPs, especially in the chlorophyte lineage. The conserved function of GGP and its rapid expansion in angiosperms maybe one of the reasons for the increase of AsA content in angiosperms, enabling angiosperms to adapt to changing environments.

Gene expression predictions and networks in natural populations supports the omnigenic theory

Background

Recent literature on the differential role of genes within networks distinguishes core from peripheral genes. If previous works have shown contrasting features between them, whether such categorization matters for phenotype prediction remains to be studied.

Results

We measured 17 phenotypic traits for 241 cloned genotypes from a Populus nigra collection, covering growth, phenology, chemical and physical properties. We also sequenced RNA for each genotype and built co-expression networks to define core and peripheral genes. We found that cores were more differentiated between populations than peripherals while being less variable, suggesting that they have been constrained through potentially divergent selection. We also showed that while cores were overrepresented in a subset of genes statistically selected for their capacity to predict the phenotypes (by Boruta algorithm), they did not systematically predict better than peripherals or even random genes.

Conclusion

Our work is the first attempt to assess the importance of co-expression network connectivity in phenotype prediction. While highly connected core genes appear to be important, they do not bear enough information to systematically predict better quantitative traits than other gene sets.

Influence of pathway topology and functional class on the molecular evolution of human metabolic genes

Metabolic networks comprise thousands of enzymatic reactions functioning in a controlled manner and have been shaped by natural selection. Thanks to the genome data, the footprints of adaptive (positive) selection are detectable, and the strength of purifying selection can be measured. This has made possible to know where, in the metabolic network, adaptive selection has acted and where purifying selection is more or less strong and efficient. We have carried out a comprehensive molecular evolutionary study of all the genes involved in the human metabolism. We investigated the type and strength of the selective pressures that acted on the enzyme-coding genes belonging to metabolic pathways during the divergence of primates and rodents. Then, we related those selective pressures to the functional and topological characteristics of the pathways. We have used DNA sequences of all enzymes (956) of the metabolic pathways comprised in the HumanCyc database, using genome data for humans and five other mammalian species. We have found that the evolution of metabolic genes is primarily constrained by the layer of the metabolism in which the genes participate: while genes encoding enzymes of the inner core of metabolism are much conserved, those encoding enzymes participating in the outer layer, mediating the interaction with the environment, are evolutionarily less constrained and more plastic, having experienced faster functional evolution. Genes that have been targeted by adaptive selection are endowed by higher out-degree centralities than non-adaptive genes, while genes with high in-degree centralities are under stronger purifying selection. When the position along the pathway is considered, a funnel-like distribution of the strength of the purifying selection is found. Genes at bottom positions are highly preserved by purifying selection, whereas genes at top positions, catalyzing the first steps, are open to evolutionary changes. These results show how functional and topological characteristics of metabolic pathways contribute to shape the patterns of evolutionary pressures driven by natural selection and how pathway network structure matters in the evolutionary process that shapes the evolution of the system.

Metabolic Determinants of Enzyme Evolution in a Genome-Scale Bacterial Metabolic Network

Different genes and proteins evolve at very different rates. To identify the factors that explain these differences is an important aspect of research in molecular evolution. One such factor is the role a protein plays in a large molecular network. Here, we analyze the evolutionary rates of enzyme-coding genes in the genome-scale metabolic network of Escherichia coli to find the evolutionary constraints imposed by the structure and function of this complex metabolic system. Central and highly connected enzymes appear to evolve more slowly than less connected enzymes, but we find that they do so as a by-product of their high abundance, and not because of their position in the metabolic network. In contrast, enzymes catalyzing reactions with high metabolic flux-high substrate to product conversion rates-evolve slowly even after we account for their abundance. Moreover, enzymes catalyzing reactions that are difficult to by-pass through alternative pathways, such that they are essential in many different genetic backgrounds, also evolve more slowly. Our analyses show that an enzyme's role in the function of a metabolic network affects its evolution more than its place in the network's structure. They highlight the value of a system-level perspective for studies of molecular evolution.

Stronger selective constraint on downstream genes in the oxidative phosphorylation pathway of cetaceans

The oxidative phosphorylation (OXPHOS) pathway is an efficient way to produce energy via adenosine triphosphate (ATP), which is critical for sustaining an energy supply for cetaceans in a hypoxic environment. Several studies have shown that natural selection may shape the evolution of the genes involved in OXPHOS. However, how network architecture drives OXPHOS protein sequence evolution remains poorly explored. Here, we investigated the evolutionary patterns of genes in the OXPHOS pathway across six cetacean genomes within the framework of a functional network. Our results show a negative correlation between the strength of purifying selection and pathway position. This result indicates that downstream genes were subjected to stronger evolutionary constraints than upstream genes, which may be due to the dual function of ATP synthase in the OXPHOS pathway. Additionally, there was a positive correlation between codon usage bias and omega (ω = dN/dS) and a negative correlation with synonymous substitution rate (dS), indicating that the stronger selective constraint on genes (with less biased codon usage) along the OXPHOS pathway is attributable to an increase in the rate of synonymous substitution. Surprisingly, there was no significant correlation between protein-protein interactions and the evolutionary estimates, implying that highly connected enzymes may not always show greater evolutionary constraints. Compared with that observed for terrestrial mammals, we found that the signature of positive selection detected in five genes (ATP5J, LHPP, PPA1, UQCRC1 and UQCRQ) was cetacean-specific, reflecting the importance of OXPHOS for survival in hypoxic, aquatic environments.

Dynamic sensitivity and nonlinear interactions influence the system-level evolutionary patterns of phototransduction proteins

Determining the influence of complex, molecular-system dynamics on the evolution of proteins is hindered by the significant challenge of quantifying the control exerted by the proteins on system output. We have employed a combination of systems biology and molecular evolution analyses in a first attempt to unravel this relationship. We employed a comprehensive mathematical model of mammalian phototransduction to predict the degree of influence that each protein in the system exerts on the high-level dynamic behaviour. We found that the genes encoding the most dynamically sensitive proteins exhibit relatively relaxed evolutionary constraint. We also investigated the evolutionary and epistatic influences of the many nonlinear interactions between proteins in the system and found several pairs to have coevolved, including those whose interactions are purely dynamical with respect to system output. This evidence points to a key role played by nonlinear system dynamics in influencing patterns of molecular evolution.

Functional role of positively selected amino acid substitutions in mammalian rhodopsin evolution

Visual rhodopsins are membrane proteins that function as light photoreceptors in the vertebrate retina. Specific amino acids have been positively selected in visual pigments during mammal evolution, which, as products of adaptive selection, would be at the base of important functional innovations. We have analyzed the top candidates for positive selection at the specific amino acids and the corresponding reverse changes (F13M, Q225R and A346S) in order to unravel the structural and functional consequences of these important sites in rhodopsin evolution. We have constructed, expressed and immunopurified the corresponding mutated pigments and analyzed their molecular phenotypes. We find that position 13 is very important for the folding of the receptor and also for proper protein glycosylation. Position 225 appears to be important for the function of the protein affecting the G-protein activation process, and position 346 would also regulate functionality of the receptor by enhancing G-protein activation and presumably affecting protein phosphorylation by rhodopsin kinase. Our results represent a link between the evolutionary analysis, which pinpoints the specific amino acid positions in the adaptive process, and the structural and functional analysis, closer to the phenotype, making biochemical sense of specific selected genetic sequences in rhodopsin evolution.

Evolutionary patterns of Toll-like receptor signaling pathway genes in the Suidae

BACKGROUND

The Toll-like receptor (TLR) signaling pathway constitutes an essential component of the innate immune system. Highly conserved proteins, indicative of their critical roles in host survival, characterize this pathway. Selective constraints could vary depending on the gene's position within the pathway as TLR signaling is a sequential process and that genes downstream of the TLRs may be more selectively constrained to ensure efficient immune responses given the important role of downstream genes in the signaling process. Thus, we investigated whether gene position influenced protein evolution in the TLR signaling pathway of the Suidae. The members of the Suidae examined included the European Sus scrofa (wild boar), Asian Sus scrofa (wild boar), Sus verrucosus, Sus celebensis, Sus scebifrons, Sus barbatus, Babyrousa babyrussa, Potamochoerus larvatus, Potamochoerus porcus and Phacochoerus africanus.

RESULTS

A total of 33 TLR signaling pathway genes in the Suidae were retrieved from resequencing data. The evolutionary parameter ω (dn/ds) had an overall mean of 0.1668 across genes, indicating high functional conservation within the TLR signaling pathway. A significant relationship was inferred for the network parameters gene position, number of protein-protein interactions, protein length and the evolutionary parameter dn (nonsynonymous substitutions) such that downstream genes had lower nonsynonymous substitution rates, more interactors and shorter protein length than upstream genes. Gene position was significantly correlated with the number of protein-protein interactions and protein length. Thus, the polarity in the selective constraint along the TLR signaling pathway was due to the number of molecules a protein interacted with and the protein's length.

CONCLUSION

Results indicate that the level of selective constraints on genes within the TLR signaling pathway of the Suidae is dependent on the gene's position and network parameters. In particular, downstream genes evolve more slowly as a result of being highly connected and having shorter protein lengths. These findings highlight the critical role of gene network parameters in gene evolution.

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.

Patterns of variation during adaptation in functionally linked loci

An understanding of the distribution of natural patterns of genetic variation is relevant to such fundamental biological fields as evolution and development. One recent approach to understanding such patterns has been to focus on the constraints that may arise as a function of the network or pathway context in which genes are embedded. Despite theoretical expectations of higher evolutionary constraint for genes encoding upstream versus downstream enzymes in metabolic pathways, empirical results have varied. Here we combine two complementary models from population genetics and enzyme kinetics to explore genetic variation as a function of pathway position when selection acts on whole-pathway flux. We are able to qualitatively reproduce empirically observed patterns of polymorphism and divergence and suggest that expectations should vary depending on the evolutionary trajectory of a population. Upstream genes are initially more polymorphic and diverge faster after an environmental change, while we see the opposite trend as the population approaches its fitness optimum.

Insights into miRNA regulation of the human glycome

Glycosylation is an intricate process requiring the coordinated action of multiple proteins, including glycosyltransferases, glycosidases, sugar nucleotide transporters and trafficking proteins. Work by several groups points to a role for microRNA (miRNA) in controlling the levels of specific glycosyltransferases involved in cancer, neural migration and osteoblast formation. Recent work in our laboratory suggests that miRNA are a principal regulator of the glycome, translating genomic information into the glycocode through tuning of enzyme levels. Herein we overlay predicted miRNA regulation of glycosylation related genes (glycogenes) onto maps of the common N-linked and O-linked glycan biosynthetic pathways to identify key regulatory nodes of the glycome. Our analysis provides insights into glycan regulation and suggests that at the regulatory level, glycogenes are non-redundant.

Molecular evolution of multiple-level control of heme biosynthesis pathway in animal kingdom

Adaptation of enzymes in a metabolic pathway can occur not only through changes in amino acid sequences but also through variations in transcriptional activation, mRNA splicing and mRNA translation. The heme biosynthesis pathway, a linear pathway comprised of eight consecutive enzymes in animals, provides researchers with ample information for multiple types of evolutionary analyses performed with respect to the position of each enzyme in the pathway. Through bioinformatics analysis, we found that the protein-coding sequences of all enzymes in this pathway are under strong purifying selection, from cnidarians to mammals. However, loose evolutionary constraints are observed for enzymes in which self-catalysis occurs. Through comparative genomics, we found that in animals, the first intron of the enzyme-encoding genes has been co-opted for transcriptional activation of the genes in this pathway. Organisms sense the cellular content of iron, and through iron-responsive elements in the 5′ untranslated regions of mRNAs and the intron-exon boundary regions of pathway genes, translational inhibition and exon choice in enzymes may be enabled, respectively. Pathway product (heme)-mediated negative feedback control can affect the transport of pathway enzymes into the mitochondria as well as the ubiquitin-mediated stability of enzymes. Remarkably, the positions of these controls on pathway activity are not ubiquitous but are biased towards the enzymes in the upstream portion of the pathway. We revealed that multiple-level controls on the activity of the heme biosynthesis pathway depend on the linear depth of the enzymes in the pathway, indicating a new strategy for discovering the molecular constraints that shape the evolution of a metabolic pathway.

Molecular evolution constraints in the floral organ specification gene regulatory network module across 18 angiosperm genomes

The gene regulatory network of floral organ cell fate specification of Arabidopsis thaliana is a robust developmental regulatory module. Although such finding was proposed to explain the overall conservation of floral organ types and organization among angiosperms, it has not been confirmed that the network components are conserved at the molecular level among flowering plants. Using the genomic data that have accumulated, we address the conservation of the genes involved in this network and the forces that have shaped its evolution during the divergence of angiosperms. We recovered the network gene homologs for 18 species of flowering plants spanning nine families. We found that all the genes are highly conserved with no evidence of positive selection. We studied the sequence conservation features of the genes in the context of their known biological function and the strength of the purifying selection acting upon them in relation to their placement within the network. Our results suggest an association between protein length and sequence conservation, evolutionary rates, and functional category. On the other hand, we found no significant correlation between the strength of purifying selection and gene placement. Our results confirm that the studied robust developmental regulatory module has been subjected to strong functional constraints. However, unlike previous studies, our results do not support the notion that network topology plays a major role in constraining evolutionary rates. We speculate that the dynamical functional role of genes within the network and not just its connectivity could play an important role in constraining evolution.

Evolutionary rate patterns of genes involved in the Drosophila Toll and Imd signaling pathway

BACKGROUND

To survive in a hostile environment, insects have evolved an innate immune system to defend against infection. Studies have shown that natural selection may drive the evolution of immune system-related proteins. Yet, how network architecture influences protein sequence evolution remains unclear. Here, we analyzed the molecular evolutionary patterns of genes in the Toll and Imd innate immune signaling pathways across six Drosophila genomes within the context of a functional network.

RESULTS

Based on published literature, we identified 50 genes that are directly involved in the Drosophila Toll and Imd signaling pathways. Of those genes, only two (Sphinx1 and Dnr1) exhibited signals of positive selection. There existed a negative correlation between the strength of purifying selection and gene position within the pathway; the downstream genes were more conserved, indicating that they were subjected to stronger evolutionary constraints. Interestingly, there was also a significantly negative correlation between the rate of protein evolution and the number of regulatory microRNAs, implying that genes regulated by more miRNAs experience stronger functional constraints and therefore evolve more slowly.

CONCLUSION

Taken together, our results suggested that both network architecture and miRNA regulation affect protein sequence evolution. These findings improve our understanding of the evolutionary patterns of genes involved in Drosophila innate immune pathways.

Metabolic flux is a determinant of the evolutionary rates of enzyme-encoding genes

Relationships between evolutionary rates and gene properties on a genomic, functional, pathway, or system level are being explored to unravel the principles of the evolutionary process. In particular, functional network properties have been analyzed to recognize the constraints they may impose on the evolutionary fate of genes. Here we took as a case study the core metabolic network in human erythrocytes and we analyzed the relationship between the evolutionary rates of its genes and the metabolic flux distribution throughout it. We found that metabolic flux correlates with the ratio of nonsynonymous to synonymous substitution rates. Genes encoding enzymes that carry high fluxes have been more constrained in their evolution, while purifying selection is more relaxed in genes encoding enzymes carrying low metabolic fluxes. These results demonstrate the importance of considering the dynamical functioning of gene networks when assessing the action of selection on system-level properties.

Interpretation of genomic variants using a unified biological network approach

The decreasing cost of sequencing is leading to a growing repertoire of personal genomes. However, we are lagging behind in understanding the functional consequences of the millions of variants obtained from sequencing. Global system-wide effects of variants in coding genes are particularly poorly understood. It is known that while variants in some genes can lead to diseases, complete disruption of other genes, called ‘loss-of-function tolerant’, is possible with no obvious effect. Here, we build a systems-based classifier to quantitatively estimate the global perturbation caused by deleterious mutations in each gene. We first survey the degree to which gene centrality in various individual networks and a unified ‘Multinet’ correlates with the tolerance to loss-of-function mutations and evolutionary conservation. We find that functionally significant and highly conserved genes tend to be more central in physical protein-protein and regulatory networks. However, this is not the case for metabolic pathways, where the highly central genes have more duplicated copies and are more tolerant to loss-of-function mutations. Integration of three-dimensional protein structures reveals that the correlation with centrality in the protein-protein interaction network is also seen in terms of the number of interaction interfaces used. Finally, combining all the network and evolutionary properties allows us to build a classifier distinguishing functionally essential and loss-of-function tolerant genes with higher accuracy (AUC = 0.91) than any individual property. Application of the classifier to the whole genome shows its strong potential for interpretation of variants involved in Mendelian diseases and in complex disorders probed by genome-wide association studies.

The number of personal genomes sequenced has grown rapidly over the last few years and is likely to grow further. In order to use the DNA sequence variants amongst individuals for personalized medicine, we need to understand the functional impact of these variants. Deleterious variants in genes can have a wide spectrum of global effects, ranging from fatal for essential genes to no obvious damaging effect for loss-of-function tolerant genes. The global effect of a gene mutation is largely governed by the diverse biological networks in which the gene participates. Since genes participate in many networks, no singular network captures the global picture of gene interactions. Here we integrate the diverse modes of gene interactions (regulatory, genetic, phosphorylation, signaling, metabolic and physical protein-protein interactions) to create a unified biological network. We then exploit the unique properties of loss-of-function tolerant and essential genes in this unified network to build a computational model that can predict global perturbation caused by deleterious mutations in all genes. Our model can distinguish between these two gene sets with high accuracy and we further show that it can be used for interpretation of variants involved in Mendelian diseases and in complex disorders probed by genome-wide association studies.

A system-level, molecular evolutionary analysis of mammalian phototransduction

Background

Visual perception is initiated in the photoreceptor cells of the retina via the phototransduction system. This system has shown marked evolution during mammalian divergence in such complex attributes as activation time and recovery time. We have performed a molecular evolutionary analysis of proteins involved in mammalian phototransduction in order to unravel how the action of natural selection has been distributed throughout the system to evolve such traits.

Results

We found selective pressures to be non-randomly distributed according to both a simple protein classification scheme and a protein-interaction network representation of the signaling pathway. Proteins which are topologically central in the signaling pathway, such as the G proteins, as well as retinoid cycle chaperones and proteins involved in photoreceptor cell-type determination, were found to be more constrained in their evolution. Proteins peripheral to the pathway, such as ion channels and exchangers, as well as the retinoid cycle enzymes, have experienced a relaxation of selective pressures. Furthermore, signals of positive selection were detected in two genes: the short-wave (blue) opsin (OPN1SW) in hominids and the rod-specific Na⁺/ Ca²⁺, K⁺ ion exchanger (SLC24A1) in rodents.

Conclusions

The functions of the proteins involved in phototransduction and the topology of the interactions between them have imposed non-random constraints on their evolution. Thus, in shaping or conserving system-level phototransduction traits, natural selection has targeted the underlying proteins in a concerted manner.

The evolution and origin of animal Toll-like receptor signaling pathway revealed by network-level molecular evolutionary analyses

Genes carry out their biological functions through pathways in complex networks consisting of many interacting molecules. Studies on the effect of network architecture on the evolution of individual proteins will provide valuable information for understanding the origin and evolution as well as functional conservation of signaling pathways. However, the relationship between the network architecture and the individual protein sequence evolution is yet little known. In current study, we carried out network-level molecular evolution analysis on TLR (Toll-like receptor ) signaling pathway, which plays an important role in innate immunity in insects and mammals, and we found that: 1) The selection constraint of genes was negatively correlated with its position along TLR signaling pathway; 2) all genes in TLR signaling pathway were highly conserved and underwent strong purifying selection; 3) the distribution of selective pressure along the pathway was driven by differential nonsynonymous substitution levels; 4) The TLR signaling pathway might present in a common ancestor of sponges and eumetazoa, and evolve via the TLR, IKK, IκB and NF-κB genes underwent duplication events as well as adaptor molecular enlargement, and gene structure and conservation motif of NF-κB genes shifted in their evolutionary history. Our results will improve our understanding on the evolutionary history of animal TLR signaling pathway as well as the relationship between the network architecture and the sequences evolution of individual protein.

Distribution of events of positive selection and population differentiation in a metabolic pathway: the case of asparagine N-glycosylation

Background

Asparagine N-Glycosylation is one of the most important forms of protein post-translational modification in eukaryotes. This metabolic pathway can be subdivided into two parts: an upstream sub-pathway required for achieving proper folding for most of the proteins synthesized in the secretory pathway, and a downstream sub-pathway required to give variability to trans-membrane proteins, and involved in adaptation to the environment and innate immunity. Here we analyze the nucleotide variability of the genes of this pathway in human populations, identifying which genes show greater population differentiation and which genes show signatures of recent positive selection. We also compare how these signals are distributed between the upstream and the downstream parts of the pathway, with the aim of exploring how forces of population differentiation and positive selection vary among genes involved in the same metabolic pathway but subject to different functional constraints.

Results

Our results show that genes in the downstream part of the pathway are more likely to show a signature of population differentiation, while events of positive selection are equally distributed among the two parts of the pathway. Moreover, events of positive selection are frequent on genes that are known to be at bifurcation points, and that are identified as being in key position by a network-level analysis such as MGAT3 and GCS1.

Conclusions

These findings indicate that the upstream part of the Asparagine N-Glycosylation pathway has lower diversity among populations, while the downstream part is freer to tolerate diversity among populations. Moreover, the distribution of signatures of population differentiation and positive selection can change between parts of a pathway, especially between parts that are exposed to different functional constraints. Our results support the hypothesis that genes involved in constitutive processes can be expected to show lower population differentiation, while genes involved in traits related to the environment should show higher variability. Taken together, this work broadens our knowledge on how events of population differentiation and of positive selection are distributed among different parts of a metabolic pathway.

Evolutionary conservation and network structure characterize genes of phenotypic relevance for mitosis in human

The impact of gene silencing on cellular phenotypes is difficult to establish due to the complexity of interactions in the associated biological processes and pathways. A recent genome-wide RNA knock-down study both identified and phenotypically characterized a set of important genes for the cell cycle in HeLa cells. Here, we combine a molecular interaction network analysis, based on physical and functional protein interactions, in conjunction with evolutionary information, to elucidate the common biological and topological properties of these key genes. Our results show that these genes tend to be conserved with their corresponding protein interactions across several species and are key constituents of the evolutionary conserved molecular interaction network. Moreover, a group of bistable network motifs is found to be conserved within this network, which are likely to influence the network stability and therefore the robustness of cellular functioning. They form a cluster, which displays functional homogeneity and is significantly enriched in genes phenotypically relevant for mitosis. Additional results reveal a relationship between specific cellular processes and the phenotypic outcomes induced by gene silencing. This study introduces new ideas regarding the relationship between genotype and phenotype in the context of the cell cycle. We show that the analysis of molecular interaction networks can result in the identification of genes relevant to cellular processes, which is a promising avenue for future research.

Genome-wide evolutionary conservation of N-glycosylation sites

Although posttranslational protein modifications are generally thought to perform important cellular functions, recent studies showed that a large fraction of phosphorylation sites are not evolutionarily conserved. Whether the same is true for other protein modifications, such as N-glycosylation is an open question. N-glycosylation is a form of cotranslational and posttranslational modification that occurs by enzymatic addition of a polysaccharide, or glycan, to an asparagine (N) residue of a protein. Examining a large set of experimentally determined mouse N-glycosylation sites, we find that the evolutionary rate of glycosylated asparagines is significantly lower than that of nonglycosylated asparagines of the same proteins. We further confirm that the conservation of glycosylated asparagines is accompanied by the conservation of the canonical motif sequence for glycosylation, suggesting that the above substitution rate difference is related to glycosylation. Interestingly, when solvent accessibility is considered, the substitution rate disparity between glycosylated and nonglycosylated asparagines is highly significant at solvent accessible sites but not at solvent inaccessible sites. Thus, although the solvent inaccessible glycosylation sites were experimentally identified, they are unlikely to be genuine or physiologically important. For solvent accessible asparagines, our analysis reveals a widespread and strong functional constraint on glycosylation, unlike what has been observed for phosphorylation sites in most studies, including our own analysis. Because the majority of N-glycosylation occurs at solvent accessible sites, our results show an overall functional importance for N-glycosylation.