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PubMed2005

Evolutionary sequence analysis of complete eukaryote genomes.

BACKGROUND: Gene duplication and gene loss during the evolution of eukaryotes have hindered attempts to estimate phylogenies and divergence times of species. Although current methods that identify clusters of orthologous genes in complete genomes have helped to investigate gene function and gene content, they have not been optimized for evolutionary sequence analyses requiring strict orthology and complete gene matrices. Here we adopt a relatively simple and fast genome comparison approach designed to assemble orthologs for evolutionary analysis. Our approach identifies single-copy genes representing only species divergences (panorthologs) in order to minimize potential errors caused by gene duplication. We apply this approach to complete sets of proteins from published eukaryote genomes specifically for phylogeny and time estimation. RESULTS: Despite the conservative criterion used, 753 panorthologs (proteins) were identified for evolutionary analysis with four genomes, resulting in a single alignment of 287,000 amino acids. With this data set, we estimate that the divergence between deuterostomes and arthropods took place in the Precambrian, approximately 400 million years before the first appearance of animals in the fossil record. Additional analyses were performed with seven, 12, and 15 eukaryote genomes resulting in similar divergence time estimates and phylogenies. CONCLUSION: Our results with available eukaryote genomes agree with previous results using conventional methods of sequence data assembly from genomes. They show that large sequence data sets can be generated relatively quickly and efficiently for evolutionary analyses of complete genomes.

Animals↗
PubMed2006

Protein protein interactions, evolutionary rate, abundance and age.

BACKGROUND: Does a relationship exist between a protein's evolutionary rate and its number of interactions? This relationship has been put forward many times, based on a biological premise that a highly interacting protein will be more restricted in its sequence changes. However, to date several studies have voiced conflicting views on the presence or absence of such a relationship. RESULTS: Here we perform a large scale study over multiple data sets in order to demonstrate that the major reason for conflict between previous studies is the use of different but overlapping datasets. We show that lack of correlation, between evolutionary rate and number of interactions in a data set is related to the error rate. We also demonstrate that the correlation is not an artifact of the underlying distributions of evolutionary distance and interactions and is therefore likely to be biologically relevant. Further to this, we consider the claim that the dependence is due to gene expression levels and find some supporting evidence. A strong and positive correlation between the number of interactions and the age of a protein is also observed and we show this relationship is independent of expression levels. CONCLUSION: A correlation between number of interactions and evolutionary rate is observed but is dependent on the accuracy of the dataset being used. However it appears that the number of interactions a protein participates in depends more on the age of the protein than the rate at which it changes.

Aging↗
PubMed2006

MultiSeq: unifying sequence and structure data for evolutionary analysis.

BACKGROUND: Since the publication of the first draft of the human genome in 2000, bioinformatic data have been accumulating at an overwhelming pace. Currently, more than 3 million sequences and 35 thousand structures of proteins and nucleic acids are available in public databases. Finding correlations in and between these data to answer critical research questions is extremely challenging. This problem needs to be approached from several directions: information science to organize and search the data; information visualization to assist in recognizing correlations; mathematics to formulate statistical inferences; and biology to analyze chemical and physical properties in terms of sequence and structure changes. RESULTS: Here we present MultiSeq, a unified bioinformatics analysis environment that allows one to organize, display, align and analyze both sequence and structure data for proteins and nucleic acids. While special emphasis is placed on analyzing the data within the framework of evolutionary biology, the environment is also flexible enough to accommodate other usage patterns. The evolutionary approach is supported by the use of predefined metadata, adherence to standard ontological mappings, and the ability for the user to adjust these classifications using an electronic notebook. MultiSeq contains a new algorithm to generate complete evolutionary profiles that represent the topology of the molecular phylogenetic tree of a homologous group of distantly related proteins. The method, based on the multidimensional QR factorization of multiple sequence and structure alignments, removes redundancy from the alignments and orders the protein sequences by increasing linear dependence, resulting in the identification of a minimal basis set of sequences that spans the evolutionary space of the homologous group of proteins. CONCLUSION: MultiSeq is a major extension of the Multiple Alignment tool that is provided as part of VMD, a structural visualization program for analyzing molecular dynamics simulations. Both are freely distributed by the NIH Resource for Macromolecular Modeling and Bioinformatics and MultiSeq is included with VMD starting with version 1.8.5. The MultiSeq website has details on how to download and use the software: http://www.scs.uiuc.edu/~schulten/multiseq/

Algorithms↗
PubMed2006

EGenBio: a data management system for evolutionary genomics and biodiversity.

BACKGROUND: Evolutionary genomics requires management and filtering of large numbers of diverse genomic sequences for accurate analysis and inference on evolutionary processes of genomic and functional change. We developed Evolutionary Genomics and Biodiversity (EGenBio; http://egenbio.lsu.edu) to begin to address this. DESCRIPTION: EGenBio is a system for manipulation and filtering of large numbers of sequences, integrating curated sequence alignments and phylogenetic trees, managing evolutionary analyses, and visualizing their output. EGenBio is organized into three conceptual divisions, Evolution, Genomics, and Biodiversity. The Genomics division includes tools for selecting pre-aligned sequences from different genes and species, and for modifying and filtering these alignments for further analysis. Species searches are handled through queries that can be modified based on a tree-based navigation system and saved. The Biodiversity division contains tools for analyzing individual sequences or sequence alignments, whereas the Evolution division contains tools involving phylogenetic trees. Alignments are annotated with analytical results and modification history using our PRAED format. A miscellaneous Tools section and Help framework are also available. EGenBio was developed around our comparative genomic research and a prototype database of mtDNA genomes. It utilizes MySQL-relational databases and dynamic page generation, and calls numerous custom programs. CONCLUSION: EGenBio was designed to serve as a platform for tools and resources to ease combined analysis in evolution, genomics, and biodiversity.

Animals↗
PubMed2006

Tracking the connection between evolutionary and functional shifts using the fungal lipase/feruloyl esterase A family.

BACKGROUND: There have been many claims of adaptive molecular evolution, but what role does positive selection play in functional divergence? The aim of this study was to test the relationship between evolutionary and functional shifts with special emphasis on the role of the environment. For this purpose, we studied the fungal lipase/feruloyl esterase A family, whose functional diversification makes it a very promising candidate. RESULTS: The results suggested functional shift following a duplication event where neofunctionalisation of feruloyl esterase A had occurred with conservation of the ancestral lipase function. Evolutionary shift was detected using the branch-site model for testing positive selection on individual codons along specific lineages. Positively selected amino acids were detected. Furthermore, biological data obtained from site-directed mutagenesis experiments clearly demonstrated that certain amino acids under positive selection were involved in the functional shift. We reassessed evolutionary history in terms of environmental response, and hypothesized that environmental changes such as colonisation by terrestrial plants might have driven adaptation by functional diversification in Euascomycetes (Aspergilli), thus conferring a selective advantage on this group. CONCLUSION: The results reported here illustrate a rare example of connection between fundamental events in molecular evolution. We demonstrated an unequivocal connection between evolutionary and functional shifts, which led us to conclude that these events were probably linked to environmental change.

Amino Acids↗
PubMed2006

Differential evolutionary conservation of motif modes in the yeast protein interaction network.

BACKGROUND: The importance of a network motif (a recurring interconnected pattern of special topology which is over-represented in a biological network) lies in its position in the hierarchy between the protein molecule and the module in a protein-protein interaction network. Until now, however, the methods available have greatly restricted the scope of research. While they have focused on the analysis in the resolution of a motif topology, they have not been able to distinguish particular motifs of the same topology in a protein-protein interaction network. RESULTS: We have been able to assign the molecular function annotations of Gene Ontology to each protein in the protein-protein interactions of Saccharomyces cerevisiae. For various motif topologies, we have developed an algorithm, enabling us to unveil one million "motif modes", each of which features a unique topological combination of molecular functions. To our surprise, the conservation ratio, i.e., the extent of the evolutionary constraints upon the motif modes of the same motif topology, varies significantly, clearly indicative of distinct differences in the evolutionary constraints upon motifs of the same motif topology. Equally important, for all motif modes, we have found a power-law distribution of the motif counts on each motif mode. We postulate that motif modes may very well represent the evolutionary-conserved topological units of a protein interaction network. CONCLUSION: For the first time, the motifs of a protein interaction network have been investigated beyond the scope of motif topology. The motif modes determined in this study have not only enabled us to differentiate among different evolutionary constraints on motifs of the same topology but have also opened up new avenues through which protein interaction networks can be analyzed.

Algorithms↗
PubMed2002

JEvTrace: refinement and variations of the evolutionary trace in JAVA.

BACKGROUND: Details of functional speciation within gene families can be difficult to identify using standard multiple sequence alignment (MSA) methods. The evolutionary trace (ET) was developed as a visualization tool to combine MSA, phylogenetic and structural data for identification of functional sites in proteins. The method has been successful in extracting evolutionary details of functional surfaces in a number of biological systems and modifications of the method are useful in creating hypotheses about the function of previously unannotated genes. We wish to facilitate the graphical interpretation of disparate data types through the creation of flexible software implementations. RESULTS: We have implemented the ET method in a JAVA graphical interface, JEvTrace. Users can analyze and visualize ET input and output with respect to protein phylogeny, sequence and structure. Function discovery with JEvTrace is demonstrated on two proteins with recently determined crystal structures: YlxR from Streptococcus pneumoniae with a predicted RNA-binding function, and a Haemophilus influenzae protein of unknown function, YbaK. To facilitate analysis and storage of results we propose a MSA coloring data structure. The sequence coloring format readily captures evolutionary, biological, functional and structural features of MSAs. CONCLUSIONS: Protein families and phylogeny represent complex data with statistical outliers and special cases. The JEvTrace implementation of the ET method allows detailed mining and graphical visualization of evolutionary sequence relationships.

Amino Acid Sequence↗
PubMed2005

An evolutionary and functional assessment of regulatory network motifs.

BACKGROUND: Cellular functions are regulated by complex webs of interactions that might be schematically represented as networks. Two major examples are transcriptional regulatory networks, describing the interactions among transcription factors and their targets, and protein-protein interaction networks. Some patterns, dubbed motifs, have been found to be statistically over-represented when biological networks are compared to randomized versions thereof. Their function in vitro has been analyzed both experimentally and theoretically, but their functional role in vivo, that is, within the full network, and the resulting evolutionary pressures remain largely to be examined. RESULTS: We investigated an integrated network of the yeast Saccharomyces cerevisiae comprising transcriptional and protein-protein interaction data. A comparative analysis was performed with respect to Candida glabrata, Kluyveromyces lactis, Debaryomyces hansenii and Yarrowia lipolytica, which belong to the same class of hemiascomycetes as S. cerevisiae but span a broad evolutionary range. Phylogenetic profiles of genes within different forms of the motifs show that they are not subject to any particular evolutionary pressure to preserve the corresponding interaction patterns. The functional role in vivo of the motifs was examined for those instances where enough biological information is available. In each case, the regulatory processes for the biological function under consideration were found to hinge on post-transcriptional regulatory mechanisms, rather than on the transcriptional regulation by network motifs. CONCLUSION: The overabundance of the network motifs does not have any immediate functional or evolutionary counterpart. A likely reason is that motifs within the networks are not isolated, that is, they strongly aggregate and have important edge and/or node sharing with the rest of the network.

Drug Resistance, Fungal↗
PubMed2006

Evolutionary origins of leadership and followership.

Drawing upon evolutionary logic, leadership is reconceptualized in terms of the outcome of strategic interactions among individuals who are following different, yet complementary, decision rules to solve recurrent coordination problems. This article uses the vast psychological literature on leadership as a database to test several evolutionary hypotheses about the origins of leadership and followership in humans. As expected, leadership correlates with initiative taking, trait measures of intelligence, specific task competencies, and several indicators of generosity. The review finds no link between leadership and dominance. The evolutionary analysis accounts for reliable age, health, and sex differences in leadership emergence. In general, evolutionary theory provides a useful, integrative framework for studying leader-follower relationships and generates various novel research hypotheses.

Biological Evolution↗
PubMed2004

Evolutionary diversification of pigment pattern in Danio fishes: differential fms dependence and stripe loss in D. albolineatus.

The developmental bases for species differences in adult phenotypes remain largely unknown. An emerging system for studying such variation is the adult pigment pattern expressed by Danio fishes. These patterns result from several classes of pigment cells including black melanophores and yellow xanthophores, which differentiate during metamorphosis from latent stem cells of presumptive neural crest origin. In the zebrafish D. rerio, alternating light and dark horizontal stripes develop, in part, owing to interactions between melanophores and cells of the xanthophore lineage that depend on the fms receptor tyrosine kinase; zebrafish fms mutants lack xanthophores and have disrupted melanophore stripes. By contrast, the closely related species D. albolineatus exhibits a uniform pattern of melanophores, and previous interspecific complementation tests identified fms as a potential contributor to this difference between species. Here, we survey additional species and demonstrate marked variation in the fms-dependence of hybrid pigment patterns, suggesting interspecific variation in the fms pathway or fms requirements during pigment pattern formation. We next examine the cellular bases for the evolutionary loss of stripes in D. albolineatus and test the simplest model to explain this transformation, a loss of fms activity in D. albolineatus relative to D. rerio. Within D. albolineatus, we demonstrate increased rates of melanophore death and decreased melanophore migration, different from wild-type D. rerio but similar to fms mutant D. rerio. Yet, we also find persistent fms expression in D. albolineatus and enhanced xanthophore development compared with wild-type D. rerio, and in stark contrast to fms mutant D. rerio. These findings exclude the simplest model in which stripe loss in D. albolineatus results from a loss of fms-dependent xanthophores and their interactions with melanophores. Rather, our results suggest an alternative model in which evolutionary changes in pigment cell interactions themselves have contributed to stripe loss, and we test this model by manipulating melanophore numbers in interspecific hybrids. Together, these data suggest evolutionary changes in the fms pathway or fms requirements, and identify changes in cellular interactions as a likely mechanism of evolutionary change in Danio pigment patterns.

Alleles↗
PubMed2002

Toward an integration of interpersonal and biological processes: evolutionary psychiatry as an empirically testable framework for psychiatric research.

Phenomenological, biological, and interpersonal aspects of psychiatric disorders lack an integrative empirical framework. In this paper evolutionary psychiatry is proposed as a meta-theory to integrate biological and interpersonal aspects of psychopathology. Pathological cognition, emotions, and behaviors may be examined according to specific biosocial goals originally pursued to increase the individual's inclusive fitness, similar to the ways that "normal" processes have been analyzed by evolutionary psychology. Sex-specific differences in prevalence rates and symptomatology of psychiatric disorders may also be better understood if divergent problems of adaptation for men and women in human evolutionary history are taken into account. Instead of mistaking the evolutionary approach for being deterministic and empirically untestable, it may rather be appropriate to provide a functional classification which adds to the contemporary psychiatric nosology through analysis according to specific conflicts of adaptation (at the ultimate level), the pursuit of biosocial goals, and proximate specifiers such as genetic, developmental, and interpersonal causes of disorders.

Adaptation, Psychological↗
PubMed2005

A stability pattern of protein hydrophobic mutations that reflects evolutionary structural optimization.

We have determined the effect of mutations involving isoleucine and valine (i.e., mutations I-->V and V-->I) on the stability of Escherichia coli thioredoxin. Despite the similarity in chemical structure (V and I differ only in a methyl group), we find that many environments are optimized to a significant extent for either V or I. We find, furthermore, that a plot of effect of hydrophobic mutations on stability versus packing density shows a strikingly simple pattern that clearly reflects evolutionary structural optimization. The existence of such patterns suggests the possibility of rationalizing (and perhaps even predicting) mutation effects on protein stability on the basis of evolutionary models. By "evolutionary model" we specifically refer in this context to a model for mutation effects on stability in which certain physical features of the mutated residue environments are evaluated from an assumption regarding how such environments have been selected during protein evolution (as opposed to a purely "physical model" in which those features would be derived from some kind of energetics analysis of the protein structural characteristics). To illustrate this novel approach and provide general guidelines for its application, we develop here a simple evolutionary model that successfully explains the effect of the I<-->V mutations on thioredoxin stability.

Algorithms↗
PubMed2002

Evolutionary speed of species invasions.

Successful invasion may depend of the capacity of a species to adjust genetically to a spatially varying environment. This research modeled a species invasion by examining the interaction between a quantitative genetic trait and population density. It assumed: (I) a quantitative genetic trait describes the adaptation of an individual to its local ecological conditions; (2) populations far from the local optimum grow more slowly than those near the optimum; and (3) the evolution of a trait depends on local population density, because differences in local population densities cause asymmetrical gene flow. This genetics-density interaction determined the propagation speed of populations. Numerical simulations showed that populations spread by advancing as two synchronic traveling waves, one for population density and one for trait adaptation. The form of the density wave was a step front that advances homogenizing populations at their carrying capacity; the adaptation wave was a curve with finite slope that homogenizes populations at full adaptation. The largest speed of population expansion, for a dimensionless analysis, corresponded to an almost homogeneous spatial environment when this model approached an ecological description such as the Fisher-Skellam's model. A large genetic response also favored faster speeds. Evolutionary speeds, in a natural scale, showed a wide range of rates that were also slower compared to models that only consider demographics. This evolutionary speed increased with high heritability, strong stabilizing selection, and high intrinsic growth rate. It decreased for steeper environmental gradients. Also indicated was an optimal dispersal rate over which evolutionary speed declined. This is expected because dispersal moves individuals further, but homogenizes populations genetically, making them maladapted. The evolutionary speed was compared to observed data. Furthermore, a moderate increase in the speed of expansion was predicted for ecological changes related to global warming.

Adaptation, Biological↗
PubMed2001

Evolution and development: some insights from evolutionary theory.

Developmental biology and evolutionary biology are both mature integrative disciplines which started in the 19th century and then followed parallel and independent scientific pathways. Recently, a genetical component has stepped into both disciplines (developmental genetics and evolutionary genetics) pointing out the need for future convergent maturation. Indeed, the Evo-Devo approach is becoming popular among developmental biologists, based on the facts that distant groups share a common ancestry, that precise phylogenies can be worked out and that homologous genes often play similar roles during the development of very different organisms. In this essay, I try to show that the real future of Evo-Devo thinking is still broader. The evolutionary theory is a set of diverse concepts which can and should be used in any biological field. Evolutionary thinking trains to ask << why >> questions and to provide logical and plausible answers. It can shed some light on a diversity of general problems such as how to distinguish homologies from analogies, the costs and benefits of multicellularity, the origin of novel structures (e.g. the head), or the evolution of sexual reproduction. In the next decade, we may expect a progressive convergence between developmental genetics and quantitative genetics.

Animals↗
PubMed2005

[Evolutionary medicine: an emergent basic science].

Evolutionary Medicine is an emergent basic science that offers new and varied perspectives to the comprehension of human health. The application of classic evolutionary theories (descent with modification, and natural selection) to the human organism, to its pathogens, and their mutual co-evolution, provides new explanations about why we get sick, how we can prevent this, and how we can heal. Medicine has focused mainly on the proximate or immediate causes of diseases and the treatment of symptoms, and very little on its evolutionary or mediate causes. For instance, the present human genome and phenotypes are essentially paleolithic ones: they are not adapted to modern life style, thus favoring the so-called diseases of civilization (ie: ateroesclerosis, senescence, myopia, phobias, panic attacks, stress, reproductive cancers). With the evolutionary approach, post-modern medicine is detecting better the vulnerabilities, restrictions, biases, adaptations and maladaptations of human body, its actual diseases, and its preventions.

Biological Evolution↗
PubMed1998

The cement of medical thought. Evolutionary emergence and downward causation.

The aetio-pathogenetic sequences and the physio-pathological patterns of diabetes, emphysema, cholera, circulatory shock and thrombosis have been analysed with respect to an evolutionary interpretation. The diseases, although reflecting alterations of processes that can always be described in physico-chemical language, occur only at the level of biological systems which reflects the decodification of genomic project: the teleonomic projects that have been developed during evolution. The concepts of evolutionary emergence and of downward causation have been used to discuss the relationship between the molecular events responsible for the initiation of the disease, and the subsequent events responsible for the aetio-pathogenesis, for the systemic disarrangement and for the additional alterations of tissues and cells independent of the initial molecular events. In diabetes the systemic disarrangement, glycosuria and hyperglycemia, reflect the evolutionary emergence of the processes regulating carbohydrate metabolism, whereas the cardiovascular and neurological alterations are effects of the systemic disarrangement by a mechanism of downward causation. The complexity of the aetio-pathogenesis and of the physio-pathological patterns of diseases is due to the generation of information during the evolution of multi-hierarchical entities. The evolutionary epistemology approach is useful to explain the behaviour of complex systems.

Biological Evolution↗
PubMed2001

Evolutionary fallacies of Nazi psychiatry. Implications for current research.

Evolutionary theory has had a major impact on psychiatry since the middle of the 19th century. During the Nazi regime psychiatry supported compulsory sterilization and euthanasia of physically and mentally ill and subsequently the killing of "inferior" races by borrowing scientifically invalid conclusions from evolutionary biology. The present paper deals with some of the flaws and shortcomings of the scientific paradigms of evolutionary theory adopted by psychiatry during the Nazi regime and discusses possible implications for modern research in evolutionary psychology and psychiatry.

Biological Evolution↗
PubMed1997

[Predicibility of scientific medicine. 1. The role of chaotic and evolutionary processes].

The deterministic processes, whether mechanicistic or statistic but not chaotic, have a high degree of predicibility in contrast with evolutionary processes. Following the methodological principle of C. Bernard of diseases as alterations of biochemical and physiological processes, medicine has been assigned to the area of the functional biological, i.e. to the area of the deterministic processes. However in many cases the evolution of pathological processes is hardly predictable due to many reasons. The first is the exponential evolution of many physiological processes, a reason for which the evolution tends to become chaotic. The second is that, although deterministic, frequency and distribution of diseases require a statistical approach. The third and most important reason is that a large number of pathological processes are of evolutionary nature and are therefore accompanied by the continuous generation of new information. Some examples of evolutionary processes, such the tumor trasformations and the autoimmune diseases are discussed but it is suggested that the field of evolutionary medicine will rapidly expand.

Biological Evolution↗