An Ancient Evolutionary Origin of Genes Associated with Human Genetic Diseases

Several thousand genes in the human genome have been linked to a heritable genetic disease. The majority of these appear to be nonessential genes (i.e., are not embryonically lethal when inactivated), and one could therefore speculate that they are late additions in the evolutionary lineage toward humans. Contrary to this expectation, we find that they are in fact significantly overrepresented among the genes that have emerged during the early evolution of the metazoa. Using a phylostratigraphic approach, we have studied the evolutionary emergence of such genes at 19 phylogenetic levels. The majority of disease genes was already present in the eukaryotic ancestor, and the second largest number has arisen around the time of evolution of multicellularity. Conversely, genes specific to the mammalian lineage are highly underrepresented. Hence, genes involved in genetic diseases are not simply a random subset of all genes in the genome but are biased toward ancient genes

ProteinHistorian: Tools for the Comparative Analysis of Eukaryote Protein Origin

The evolutionary history of a protein reflects the functional history of its ancestors. Recent phylogenetic studies identified distinct evolutionary signatures that characterize proteins involved in cancer, Mendelian disease, and different ontogenic stages. Despite the potential to yield insight into the cellular functions and interactions of proteins, such comparative phylogenetic analyses are rarely performed, because they require custom algorithms. We developed ProteinHistorian to make tools for performing analyses of protein origins widely available. Given a list of proteins of interest, ProteinHistorian estimates the phylogenetic age of each protein, quantifies enrichment for proteins of specific ages, and compares variation in protein age with other protein attributes. ProteinHistorian allows flexibility in the definition of protein age by including several algorithms for estimating ages from different databases of evolutionary relationships. We illustrate the use of ProteinHistorian with three example analyses. First, we demonstrate that proteins with high expression in human, compared to chimpanzee and rhesus macaque, are significantly younger than those with human-specific low expression. Next, we show that human proteins with annotated regulatory functions are significantly younger than proteins with catalytic functions. Finally, we compare protein length and age in many eukaryotic species and, as expected from previous studies, find a positive, though often weak, correlation between protein age and length. ProteinHistorian is available through a web server with an intuitive interface and as a set of command line tools; this allows biologists and bioinformaticians alike to integrate these approaches into their analysis pipelines. ProteinHistorian's modular, extensible design facilitates the integration of new datasets and algorithms. The ProteinHistorian web server, source code, and pre-computed ages for 32 eukaryotic genomes are freely available under the GNU public license at http://lighthouse.ucsf.edu/ProteinHistorian/

Animals in a Bacterial World, A New Imperative for the Life Sciences

In the last two decades, the widespread application of genetic and genomic approaches has revealed a bacterial world astonishing in its ubiquity and diversity. This review examines how a growing knowledge of the vast range of animal–bacterial interactions, whether in shared ecosystems or intimate symbioses, is fundamentally altering our understanding of animal biology. Specifically, we highlight recent technological and intellectual advances that have changed our thinking about five questions: how have bacteria facilitated the origin and evolution of animals; how do animals and bacteria affect each other’s genomes; how does normal animal development depend on bacterial partners; how is homeostasis maintained between animals and their symbionts; and how can ecological approaches deepen our understanding of the multiple levels of animal–bacterial interaction. As answers to these fundamental questions emerge, all biologists will be challenged to broaden their appreciation of these interactions and to include investigations of the relationships between and among bacteria and their animal partners as we seek a better understanding of the natural world.Earth and Planetary SciencesOrganismic and Evolutionary Biolog

Ortho2ExpressMatrix—a web server that interprets cross-species gene expression data by gene family information

<p>Abstract</p> <p>Background</p> <p>The study of gene families is pivotal for the understanding of gene evolution across different organisms and such phylogenetic background is often used to infer biochemical functions of genes. Modern high-throughput experiments offer the possibility to analyze the entire transcriptome of an organism; however, it is often difficult to deduct functional information from that data.</p> <p>Results</p> <p>To improve functional interpretation of gene expression we introduce Ortho2ExpressMatrix, a novel tool that integrates complex gene family information, computed from sequence similarity, with comparative gene expression profiles of two pre-selected biological objects: gene families are displayed with two-dimensional matrices. Parameters of the tool are object type (two organisms, two individuals, two tissues, etc.), type of computational gene family inference, experimental meta-data, microarray platform, gene annotation level and genome build. Family information in Ortho2ExpressMatrix bases on computationally different protein family approaches such as EnsemblCompara, InParanoid, SYSTERS and Ensembl Family. Currently, respective all-against-all associations are available for five species: human, mouse, worm, fruit fly and yeast. Additionally, microRNA expression can be examined with respect to miRBase or TargetScan families. The visualization, which is typical for Ortho2ExpressMatrix, is performed as matrix view that displays functional traits of genes (differential expression) as well as sequence similarity of protein family members (BLAST e-values) in colour codes. Such translations are intended to facilitate the user's perception of the research object.</p> <p>Conclusions</p> <p>Ortho2ExpressMatrix integrates gene family information with genome-wide expression data in order to enhance functional interpretation of high-throughput analyses on diseases, environmental factors, or genetic modification or compound treatment experiments. The tool explores differential gene expression in the light of orthology, paralogy and structure of gene families up to the point of ambiguity analyses. Results can be used for filtering and prioritization in functional genomic, biomedical and systems biology applications. The web server is freely accessible at <url>http://bioinf-data.charite.de/o2em/cgi-bin/o2em.pl</url>.</p

Structural View of a Non Pfam Singleton and Crystal Packing Analysis

Comparative genomic analysis has revealed that in each genome a large number of open reading frames have no homologues in other species. Such singleton genes have attracted the attention of biochemists and structural biologists as a potential untapped source of new folds. Cthe_2751 is a 15.8 kDa singleton from an anaerobic, hyperthermophile Clostridium thermocellum. To gain insights into the architecture of the protein and obtain clues about its function, we decided to solve the structure of Cthe_2751.The protein crystallized in 4 different space groups that diffracted X-rays to 2.37 Å (P3(1)21), 2.17 Å (P2(1)2(1)2(1)), 3.01 Å (P4(1)22), and 2.03 Å (C222(1)) resolution, respectively. Crystal packing analysis revealed that the 3-D packing of Cthe_2751 dimers in P4(1)22 and C222(1) is similar with only a rotational difference of 2.69° around the C axes. A new method developed to quantify the differences in packing of dimers in crystals from different space groups corroborated the findings of crystal packing analysis. Cthe_2751 is an all α-helical protein with a central hydrophobic core providing thermal stability via π:cation and π: π interactions. A ProFunc analysis retrieved a very low match with a splicing endonuclease, suggesting a role for the protein in the processing of nucleic acids.Non-Pfam singleton Cthe_2751 folds into a known all α-helical fold. The structure has increased sequence coverage of non-Pfam proteins such that more protein sequences can be amenable to modelling. Our work on crystal packing analysis provides a new method to analyze dimers of the protein crystallized in different space groups. The utility of such an analysis can be expanded to oligomeric structures of other proteins, especially receptors and signaling molecules, many of which are known to function as oligomers

Protein coalitions in a core mammalian biochemical network linked by rapidly evolving proteins

<p>Abstract</p> <p>Background</p> <p>Cellular ATP levels are generated by glucose-stimulated mitochondrial metabolism and determine metabolic responses, such as glucose-stimulated insulin secretion (GSIS) from the β-cells of pancreatic islets. We describe an analysis of the evolutionary processes affecting the core enzymes involved in glucose-stimulated insulin secretion in mammals. The proteins involved in this system belong to ancient enzymatic pathways: glycolysis, the TCA cycle and oxidative phosphorylation.</p> <p>Results</p> <p>We identify two sets of proteins, or protein coalitions, in this group of 77 enzymes with distinct evolutionary patterns. Members of the glycolysis, TCA cycle, metabolite transport, pyruvate and NADH shuttles have low rates of protein sequence evolution, as inferred from a human-mouse comparison, and relatively high rates of evolutionary gene duplication. Respiratory chain and glutathione pathway proteins evolve faster, exhibiting lower rates of gene duplication. A small number of proteins in the system evolve significantly faster than co-pathway members and may serve as rapidly evolving adapters, linking groups of co-evolving genes.</p> <p>Conclusions</p> <p>Our results provide insights into the evolution of the involved proteins. We find evidence for two coalitions of proteins and the role of co-adaptation in protein evolution is identified and could be used in future research within a functional context.</p

Sponge non-metastatic Group I Nme gene/protein - structure and function is conserved from sponges to humans

<p>Abstract</p> <p>Background</p> <p>Nucleoside diphosphate kinases NDPK are evolutionarily conserved enzymes present in Bacteria, Archaea and Eukarya, with human Nme1 the most studied representative of the family and the first identified metastasis suppressor. Sponges (Porifera) are simple metazoans without tissues, closest to the common ancestor of all animals. They changed little during evolution and probably provide the best insight into the metazoan ancestor's genomic features. Recent studies show that sponges have a wide repertoire of genes many of which are involved in diseases in more complex metazoans. The original function of those genes and the way it has evolved in the animal lineage is largely unknown. Here we report new results on the metastasis suppressor gene/protein homolog from the marine sponge <it>Suberites domuncula</it>, NmeGp1Sd. The purpose of this study was to investigate the properties of the sponge Group I Nme gene and protein, and compare it to its human homolog in order to elucidate the evolution of the structure and function of Nme.</p> <p>Results</p> <p>We found that sponge genes coding for Group I Nme protein are intron-rich. Furthermore, we discovered that the sponge NmeGp1Sd protein has a similar level of kinase activity as its human homolog Nme1, does not cleave negatively supercoiled DNA and shows nonspecific DNA-binding activity. The sponge NmeGp1Sd forms a hexamer, like human Nme1, and all other eukaryotic Nme proteins. NmeGp1Sd interacts with human Nme1 in human cells and exhibits the same subcellular localization. Stable clones expressing sponge NmeGp1Sd inhibited the migratory potential of CAL 27 cells, as already reported for human Nme1, which suggests that Nme's function in migratory processes was engaged long before the composition of true tissues.</p> <p>Conclusions</p> <p>This study suggests that the ancestor of all animals possessed a NmeGp1 protein with properties and functions similar to evolutionarily recent versions of the protein, even before the appearance of true tissues and the origin of tumors and metastasis.</p

Structure and Age Jointly Influence Rates of Protein Evolution

What factors determine a protein's rate of evolution are actively debated. Especially unclear is the relative role of intrinsic factors of present-day proteins versus historical factors such as protein age. Here we study the interplay of structural properties and evolutionary age, as determinants of protein evolutionary rate. We use a large set of one-to-one orthologs between human and mouse proteins, with mapped PDB structures. We report that previously observed structural correlations also hold within each age group – including relationships between solvent accessibility, designabililty, and evolutionary rates. However, age also plays a crucial role: age modulates the relationship between solvent accessibility and rate. Additionally, younger proteins, despite being less designable, tend to evolve faster than older proteins. We show that previously reported relationships between age and rate cannot be explained by structural biases among age groups. Finally, we introduce a knowledge-based potential function to study the stability of proteins through large-scale computation. We find that older proteins are more stable for their native structure, and more robust to mutations, than younger ones. Our results underscore that several determinants, both intrinsic and historical, can interact to determine rates of protein evolution

The map-1 Gene Family in Root-Knot Nematodes, Meloidogyne spp.: A Set of Taxonomically Restricted Genes Specific to Clonal Species

Taxonomically restricted genes (TRGs), i.e., genes that are restricted to a limited subset of phylogenetically related organisms, may be important in adaptation. In parasitic organisms, TRG-encoded proteins are possible determinants of the specificity of host-parasite interactions. In the root-knot nematode (RKN) Meloidogyne incognita, the map-1 gene family encodes expansin-like proteins that are secreted into plant tissues during parasitism, thought to act as effectors to promote successful root infection. MAP-1 proteins exhibit a modular architecture, with variable number and arrangement of 58 and 13-aa domains in their central part. Here, we address the evolutionary origins of this gene family using a combination of bioinformatics and molecular biology approaches. Map-1 genes were solely identified in one single member of the phylum Nematoda, i.e., the genus Meloidogyne, and not detected in any other nematode, thus indicating that the map-1 gene family is indeed a TRG family. A phylogenetic analysis of the distribution of map-1 genes in RKNs further showed that these genes are specifically present in species that reproduce by mitotic parthenogenesis, with the exception of M. floridensis, and could not be detected in RKNs reproducing by either meiotic parthenogenesis or amphimixis. These results highlight the divergence between mitotic and meiotic RKN species as a critical transition in the evolutionary history of these parasites. Analysis of the sequence conservation and organization of repeated domains in map-1 genes suggests that gene duplication(s) together with domain loss/duplication have contributed to the evolution of the map-1 family, and that some strong selection mechanism may be acting upon these genes to maintain their functional role(s) in the specificity of the plant-RKN interactions

Towards an Evolutionary Model of Transcription Networks

DNA evolution models made invaluable contributions to comparative genomics, although it seemed formidable to include non-genomic features into these models. In order to build an evolutionary model of transcription networks (TNs), we had to forfeit the substitution model used in DNA evolution and to start from modeling the evolution of the regulatory relationships. We present a quantitative evolutionary model of TNs, subjecting the phylogenetic distance and the evolutionary changes of cis-regulatory sequence, gene expression and network structure to one probabilistic framework. Using the genome sequences and gene expression data from multiple species, this model can predict regulatory relationships between a transcription factor (TF) and its target genes in all species, and thus identify TN re-wiring events. Applying this model to analyze the pre-implantation development of three mammalian species, we identified the conserved and re-wired components of the TNs downstream to a set of TFs including Oct4, Gata3/4/6, cMyc and nMyc. Evolutionary events on the DNA sequence that led to turnover of TF binding sites were identified, including a birth of an Oct4 binding site by a 2nt deletion. In contrast to recent reports of large interspecies differences of TF binding sites and gene expression patterns, the interspecies difference in TF-target relationship is much smaller. The data showed increasing conservation levels from genomic sequences to TF-DNA interaction, gene expression, TN, and finally to morphology, suggesting that evolutionary changes are larger at molecular levels and smaller at functional levels. The data also showed that evolutionarily older TFs are more likely to have conserved target genes, whereas younger TFs tend to have larger re-wiring rates