The evolutionary relationships among arboviruses and the evolutionary relationships of their vectors provides a method for understanding vector-host interactions.
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Animals↗
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[The problem of evolutionary epidemiology. I. Prerequisites for a theory of evolutionary epidemiology].
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Biological Evolution↗
Evolutionary trends and evolutionary origins: relevance to theory in comparative psychology.
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Animals↗
[Evolutionary and conformational analysis of a family of globins. The evolutionary role of deletions and insertions].
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Amino Acid Sequence↗
[Evolutionary sequence of biological oxygen toxicity protection, respiration and oxygen evolving photosynthesis in prokaryotes--a question of evolutionary trees presented by Schwartz and Dayhoff (author's transl)].
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Biological Evolution↗
A Bayesian evolutionary distance for parametrically aligned sequences.
There is an inherent relationship between the process of pairwise sequence alignment and the estimation of evolutionary distance. This relationship is explored and made explicit. Assuming an evolutionary model and given a specific pattern of observed base mismatches, the relative probabilities of evolution at each evolutionary distance are computed using a Bayesian framework. The mean or the median of this probability distribution provides a robust estimate of the central value. The evolutionary distance has traditionally been computed as zero for an observed homology of 20 bases with no mismatches; we prove that it is highly probable that the distance is greater than 0.01. The mean of the distribution is 0.047, which is a better estimate of the evolutionary distance. Bayesian estimates of the evolutionary distance incorporate arbitrary prior information about variable mutation rates both over time and along sequence position, thus requiring only a weak form of the molecular-clock hypothesis. The endpoints of the similarity between genomic DNA sequences are often ambiguous. The probability of evolution at each evolutionary distance can be estimated over the entire set of alignments by choosing the best alignment at each distance and the corresponding probability of duplication at that evolutionary distance. A central value of this distribution provides a robust evolutionary distance estimate. We provide an efficient algorithm for computing the parametric alignment, considering evolutionary distance as the only parameter. These techniques and estimates are used to infer the duplication history of the genomic sequence in C. elegans and in S. cerevisiae. Our results indicate that repeats discovered using a single scoring matrix show a considerable bias in subsequent evolutionary distance estimates.
Animals↗
Aminoacyl-tRNA synthetases, the genetic code, and the evolutionary process.
The aminoacyl-tRNA synthetases (AARSs) and their relationship to the genetic code are examined from the evolutionary perspective. Despite a loose correlation between codon assignments and AARS evolutionary relationships, the code is far too highly structured to have been ordered merely through the evolutionary wanderings of these enzymes. Nevertheless, the AARSs are very informative about the evolutionary process. Examination of the phylogenetic trees for each of the AARSs reveals the following. (i) Their evolutionary relationships mostly conform to established organismal phylogeny: a strong distinction exists between bacterial- and archaeal-type AARSs. (ii) Although the evolutionary profiles of the individual AARSs might be expected to be similar in general respects, they are not. It is argued that these differences in profiles reflect the stages in the evolutionary process when the taxonomic distributions of the individual AARSs became fixed, not the nature of the individual enzymes. (iii) Horizontal transfer of AARS genes between Bacteria and Archaea is asymmetric: transfer of archaeal AARSs to the Bacteria is more prevalent than the reverse, which is seen only for the "gemini group. " (iv) The most far-ranging transfers of AARS genes have tended to occur in the distant evolutionary past, before or during formation of the primary organismal domains. These findings are also used to refine the theory that at the evolutionary stage represented by the root of the universal phylogenetic tree, cells were far more primitive than their modern counterparts and thus exchanged genetic material in far less restricted ways, in effect evolving in a communal sense.
Amino Acids↗
The relationship between evolutionary theory and phylogenetic analysis.
The relationship between phylogenetic reconstruction and evolutionary theory is reassessed. It is argued here that phylogenies, and evolutionary principles, should be analysed initially as independently from each other as possible. Only then can they be used to test one another. If the phylogenies and evolutionary principles are totally consistent with one another, this consilience of independent lines of evidence increases confidence in both. If, however, there is a conflict, then one should assess the relative support for each hypothesis, and tentatively accept the more strongly supported one. We review examples where the phylogenetic hypothesis is preferred over the evolutionary principle, and vice versa, and instances where the conflict cannot be readily resolved. Because the analyses of pattern and process must initially be kept separate, the temporal order in which they are performed is unimportant. Therefore, the widespread methodology of always proceeding from cladogram to evolutionary 'scenario' cannot be justified philosophically. Such an approach means that cladograms cannot be properly tested against evolutionary principles, and that evolutionary 'scenarios' have no independent standing. Instead, we propose the 'consilience' approach where phylogenetic and evolutionary hypotheses are formulated independently from each other and then examined for agreement.
Animals↗
Ecological aspects of the evolutionary processes.
Darwin in his On the Origin of species made it clear that evolutionary change depends on the combined action of two different causes, the first being the origin of genetically based phenotypic variation in the individual organisms comprising the population and the second being the action of selective agents of the external environment placing demands on the individual organisms. For over a century following Darwin, most evolutionists focused on the origin of inherited variation and its transmission; many workers continue to regard genetics to be the core of evolutionary theory. Far less attention has been given to the exact nature of the selective agents with most evolutionists still treating this cause imprecisely to the detriment of our understanding of both nomological and historical evolutionary theory. Darwin was vague in the meaning of his new concept of "Natural Selection," using it interchangeably as one of the causes for evolutionary change and as the final outcome (= evolutionary change). In 1930, natural selection was defined clearly as "non-random, differential reproduction of genes" by R. Fisher and J.B.S. Haldane which is a statement of the outcome of evolutionary process and which omits mention of the causes bringing about this change. Evolutionists quickly accepted this outcome definition of natural selection, and have used interchangeably selection both as a cause and as the result of evolutionary change, causing great confusion. Herein, the details will be discussed of how the external environment (i.e., the environment-phenotype interaction) serves as selective agents and exerts demands on the phenotypic organisms. Included are the concepts of fitness and of the components of fitness (= adaptations) which are respectively (a) survival, (b) direct reproductive and (c) indirect reproductive features. Finally, it will be argued that historical-narrative analyses of organisms, including classification and phylogenetic history, are possible only with a full understanding of nomological evolutionary theory and with functional/adaptive studies of the employed taxonomic features in addition to the standard comparative investigations.
Adaptation, Physiological↗
Inference for phylogenies under a hybrid parsimony method: evolutionary-symmetric transversion parsimony.
A new method is proposed for inferring topology for evolutionary trees. Existing methods have complementary strengths and weaknesses. Maximum and transversion parsimony are powerful methods, but they lack statistical consistency, that is, they do not always infer the correct tree as the sequence length becomes very large. Evolutionary parsimony overcomes this deficiency, but it may lack sufficient power when sequence length is small (less than 1000 aligned nucleotides; Sinsheimer, Lake, and Little, 1996, Biometrics 52, 193-210). Our proposed method, evolutionary-symmetric transversion parsimony, is a hybrid that retains the consistency of evolutionary parsimony, while increasing power by incorporating a modified form of transversion parsimony within a statistical model. The method requires choice of a parameter gamma that represents the prior probability that symmetric transversion parsimony yields consistent results. Properties of the method are assessed for a variety of choices of gamma in a large simulation study. In general, inference under the evolutionary-symmetric transversion parsimony has more discriminating power than inference under evolutionary parsimony and is better calibrated than inference under symmetric transversion parsimony. The results are quite robust to the choice of gamma, indicating a value of 0.90 as a reasonable overall choice when the true value of gamma ranges between 0.85 to 1.00. Our method is, like evolutionary parsimony and maximum parsimony, computationally straightforward. The same statistical approach can be applied to combine evolutionary parsimony with other inconsistent methods, such as maximum parsimony, but at the expense of more difficult computations.
Animals↗
Evolutionary algorithms and a fractal inverse problem.
Over the past 30 years, algorithms that model natural evolution have generated robust search methods. These so-called evolutionary algorithms have been successfully applied to a wide range of problems. This paper discusses two types of evolutionary algorithms and their application to a problem in shape representation. Genetic algorithms and evolutionary programming, although both based on evolutionary principles, each place different emphasis on what drives the evolutionary process. While genetic algorithms rely on mimicking specific genotypic transformations, evolutionary programming emphasizes phenotypic adaptation. Results presented show the success of evolutionary programming in solving an example of a fractal inverse problem, but indicate that a genetic algorithm is not as successful. Reasons for this disparity are discussed.
Algorithms↗
Gene competition and the possible evolutionary role of tumours.
The evolutionary role of tumours might consist of providing the conditions for the expression of evolutionary new genes and thus in providing the material for the origin of new cell types. To approach this concept the principle of gene competition is essential. With an increase in gene number in the genomes of the evolving multicellular organisms the enforcement of gene competition should take place. Therefore, the pre-existing cell types possess limited possibilities for the expression of evolutionary new genes. Like evolutionary new genes originated from extra copies (duplicates) of old genes, evolutionary new cell types had to originate from extra cells which were not functionally necessary to the organism. Tumours could have supplied the evolving multicellular organisms with extra cells for the expression of originating evolutionary new genes. Of course, on the basis of this proposal only tumours at the earlier stages of progression are considered to be meaningful, or some kind of tumour-like processes, but not malignant tumours at late stages of progression. The evolutionary new genes originate in the DNA of germ line cells but not in DNA of tumour cells. Until the moment of their expression in the tumour cells these genes could stay silent. After the expression of these genes tumour cells should acquire the function in the organism, differentiate and lose their previous autonomy. The organisms with a new cell type should then be selected against their fitness and competitive abilities.
Animals↗
The concept of developmental reprogramming and the quest for an inclusive theory of evolutionary mechanisms.
Evolutionary developmental biology has already made a major contribution to our understanding of evolutionary patterns, notably homology. However, while it has the potential to make an equally important contribution to our understanding of evolutionary mechanisms, and indeed to the integration of mechanism and pattern, it has not yet done so. This paper explores how this potential may be realized. In particular, I focus on the limitations of present-day neo-Darwinian theory, and indicate how a combination of the neo-Darwinian and "evo-devo" approaches provides a more inclusive view of evolutionary mechanisms with greater explanatory power. There is a particular focus on developmental reprogramming, which lies logically between mutation and selection, yet has been neglected in mainstream evolutionary theory. The inclusion of developmental reprogramming in the list of evolutionary mechanisms leads to a view that the direction of evolutionary change is determined by a combination of internal and external factors, rather than being controlled entirely by the environment.
Biological Evolution↗
Understanding developmental psychopathology: how useful are evolutionary accounts?
OBJECTIVE: To consider the power of principles derived from evolutionary biology to explain the causes and determinants of some forms of child and adolescent mental disorders. METHOD: The authors reviewed the scientific literature for evolutionary mechanisms proposed to contribute to the pathogenesis of early-onset disorders. RESULTS: A diverse set of evolutionary mechanisms has been proposed. With the exception of certain genetically determined conditions, many of the proposed mechanisms have little empirical data to support them. One mechanism focuses on the vulnerabilities associated with conserved behavior patterns, such as separation anxiety and other alarm responses. These behavioral patterns are adaptive if they appear in some situations, but not in others. Other attractive theories include a co-optation of underlying neurobiology systems (substance abuse), environmental shifts (transformation of present day environments away from primeval environments), and evolutionary arms races as may occur in putative autoimmune disorders with neuropsychiatric sequelae. CONCLUSIONS: Evolutionary biology provides a potentially powerful framework for understanding disease pathogenesis in child psychiatry and should permit the integration of new knowledge from a broad range of scientific disciplines. Evolutionary explanations are typically population-based and fail to account for why a particular individual is disciplines. Evolutionary explanations are typically population-based and fail to account for why a particular individual is affected. Consequently, any adequate account of disease pathogenesis requires that environmental events that impinge on CNS development be considered. Finally, the empirical testing of specific theories may prove to be difficult if not impossible.
Adolescent↗
Comparative analysis of evolutionary mechanisms of the hemagglutinin and three internal protein genes of influenza B virus: multiple cocirculating lineages and frequent reassortment of the NP, M, and NS genes.
Phylogenetic profiles of the genes coding for the hemagglutinin (HA) protein, nucleoprotein (NP), matrix (M) protein, and nonstructural (NS) proteins of influenza B viruses isolated from 1940 to 1998 were analyzed in a parallel manner in order to understand the evolutionary mechanisms of these viruses. Unlike human influenza A (H3N2) viruses, the evolutionary pathways of all four genes of recent influenza B viruses revealed similar patterns of genetic divergence into two major lineages. Although evolutionary rates of the HA, NP, M, and NS genes of influenza B viruses were estimated to be generally lower than those of human influenza A viruses, genes of influenza B viruses demonstrated complex phylogenetic patterns, indicating alternative mechanisms for generation of virus variability. Topologies of the evolutionary trees of each gene were determined to be quite distinct from one another, showing that these genes were evolving in an independent manner. Furthermore, variable topologies were apparently the result of frequent genetic exchange among cocirculating epidemic viruses. Evolutionary analysis done in the present study provided further evidence for cocirculation of multiple lineages as well as sequestering and reemergence of phylogenetic lineages of the internal genes. In addition, comparison of deduced amino acid sequences revealed a novel amino acid deletion in the HA1 domain of the HA protein of recent isolates from 1998 belonging to the B/Yamagata/16/88-like lineage. It thus became apparent that, despite lower evolutionary rates, influenza B viruses were able to generate genetic diversity among circulating viruses through a combination of evolutionary mechanisms involving cocirculating lineages and genetic reassortment by which new variants with distinct gene constellations emerged.
Base Sequence↗
Towards a unified evolutionary genetics of microorganisms.
I propose here that evolutionary genetics, apart from improving our basic knowledge of the taxonomy and evolution of microbes (either eukaryotes or prokaryotes), can also greatly contribute to applied research in microbiology. Evolutionary genetics provides convenient guidelines for better interpreting genetic and molecular data dealing with microorganisms. The three main potential applications of evolutionary genetics in microbiology are (a) epidemiological follow-up (with the necessity of evaluating the stability of microbial genotypes over space and time); (b) taxonomy in the broad sense (better definition and sharper delimitation of presently described taxa, research of hidden genetic subdivisions); and (c) evaluation of the impact of the genetic diversity of microbes on their relevant properties (pathogenicity, resistance to drugs, etc). At present, two main kinds of population structure can be distinguished in natural microbial populations: (a) species that are not subdivided into discrete phylogenetic lineages (panmictic species or basically sexual species with occasional bouts of short-term clonality fall into this category); (b) species that are strongly subdivided by either cryptic speciation or clonal evolution. Improvements in available statistical methods are required to refine these distinctions and to better quantify the actual impact of gene exchange in natural microbial populations. Moreover, a codified selection of markers with appropriate molecular clocks (in other words: adapted levels of resolution) is sorely needed to answer distinct questions that address different scales of time and space: experimental, epidemic, and evolutionary. The problems raised by natural genetic diversity are very similar for all microbial species, in terms of both basic and applied science. Despite this fact, a regrettable compartmentalization among specialists has hampered progress in this field. I propose a synthetic approach, relying on the statistical improvements and technical standardizations called for above, to settle a unified evolutionary genetics of microorganisms, valid whatever the species studied, whether eukaryotic (parasitic protozoa and fungi) or prokaryotic (bacteria). Apart from benefits for basic evolutionary research, the anticipated payoff from this synthetic approach is to render routine and common-place the use of microbial evolutionary genetics in the fields of epidemiology, medicine, and agronomy.
Animals↗
Behavioral genetics and evolutionary psychology: unified perspective on personality research.
Behavioral geneticists and evolutionary psychologists have generally pursued human behavioral analyses with little theoretical or methodological exchange. However, significant benefits might accrue from increased communication between these disciplines. The primary goals of this article are (1) to identify meaningful junctures between behavioral genetics and evolutionary psychology, (2) to describe behavioral genetic research designs and their applications to evolutionary analyses, and (3) to reassess current personality research in light of behavioral genetic and evolutionary concepts and techniques. The five-factor model of personality is conceptualized as subsuming variation in normative species-typical systems with adaptive functions in the human environment of evolutionary adaptation. Considered as universal evolved mechanisms, personality systems are often seen in dynamic conflict within individuals and as highly compartmentalized in their functioning between settings. However, genetically influenced individual differences in personality may also be understood within an evolutionary framework. Studies of the heritability of personality traits indicate broad-sense heritabilities in the 0.40-0.50 range with evidence of substantial nonadditive genetic variation and nonshared environmental influences. Evidence indicates that evolutionary theory (e.g., inclusive fitness theory) predicts patterns of social interaction (e.g., cooperation and bereavement) in relatives. Furthermore, variation in personality may constitute a range of viable strategies matching the opportunities available in the complex niche environment of human societies. Within this wide range of viable strategies, personality variation functions as a resource environment for individuals in the sense that personality variation is evaluated according to the interests of the evaluator (e.g., friendships, coalitions, or mate choice).
Biological Evolution↗
Cladistic approaches to identifying determinants of variability in multifactorial phenotypes and the evolutionary significance of variation in the human genome.
Genetic surveys based on detailed restriction site mapping or DNA sequencing allow one to identify many different classes of mutational change at the molecular level and to estimate the evolutionary history of the genetic variation (a haplotype tree). These two sources of information can be combined in a powerful fashion to test hypotheses about the evolutionary significance of genetic variation and to identify mutations that are associated with diseases. Hypotheses about selection on various classes of genetic variation can be tested by examining the distribution patterns of different mutational classes upon the haplotype tree. The power of this procedure can be enhanced if it is coupled with comparative data from other, closely related species. With respect to disease associations, all mutations that affect phenotypic variation in a population occurred at some point in the evolutionary history of the region of the gene containing the mutations. Even if this evolutionary history is estimated from mutations other than those causing phenotypic effects, the phenotypically important mutations are imbedded in this same evolutionary history. Hence, whole branches (clades) of the haplotype tree should display homogeneous phenotypic effects and this fact is utilized to search for phenotypic associations of haplotypes by using nested clades in a haplotype tree. This procedure has more power than alternatives that do not use evolutionary history, and it avoids several statistical and interpretative problems associated with single-marker analyses. All of these methods could be used more extensively if more human genetic surveys concentrated on greater genetic resolution in small DNA regions and included non-human apes.
Animals↗