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PubMed2003

The emergence of communication in evolutionary robots.

Evolutionary robotics is a biologically inspired approach to robotics that is advantageous to studying the evolution of communication. A new model for the emergence of communication is developed and tested through various simulation experiments. In the first simulation, the emergence of simple signalling behaviour is studied. This is used to investigate the inter-relationships between communication abilities, namely linguistic production and comprehension, and other behavioural skills. The model supports the hypothesis that the ability to form categories from direct interaction with an environment constitutes the grounds for subsequent evolution of communication and language. In the second simulation, evolutionary robots are used to study the emergence of simple syntactic categories, e.g. action names (verbs). Comparisons between the two simulations indicate that the signalling lexicon emerged in the first simulation follows the evolutionary pattern of nouns, as observed in related models on the evolution of syntactic categories. Results also support the language-origin hypothesis on the fact that nouns precede verbs in both phylogenesis and ontogenesis. Further extensions of this new evolutionary robotic model for testing hypotheses on language origins are also discussed.

Adaptation, Physiological↗
PubMed2006

Longevity and ageing: appraising the evolutionary consequences of growing old.

Senescence or ageing is an increase in mortality and/or decline in fertility with increasing age. Evolutionary theories predict that ageing or longevity evolves in response to patterns of extrinsic mortality or intrinsic damage. If ageing is viewed as the outcome of the processes of behaviour, growth and reproduction then it should be possible to predict mortality rate. Recent developments have shown that it is now possible to integrate these ecological and physiological processes and predict the shape of mortality trajectories. By drawing on the key exciting developments in the cellular, physiological and ecological process of longevity the evolutionary consequences of ageing are reviewed. In presenting these ideas an evolutionary demographic framework is used to argue how trade-offs in life-history strategies are important in the maintenance of variation in longevity within and between species. Evolutionary processes associated with longevity have an important role in explaining levels of biological diversity and speciation. In particular, the effects of life-history trait trade-offs in maintaining and promoting species diversity are explored. Such trade-offs can alleviate the effects of intense competition between species and promote species coexistence and diversification. These results have important implications for understanding a number of core ecological processes such as how species are divided among niches, how closely related species co-occur and the rules by which species assemble into food-webs. Theoretical work reveals that the proximate physiological processes are as important as the ecological factors in explaining the variation in the evolution of longevity. Possible future research challenges integrating work on the evolution and mechanisms of growing old are briefly discussed.

Aging↗
PubMed2025

Integrative genomics elucidates the evolutionary, temporal, and developmental origins of a hydrocephalus risk gene.

INTRODUCTION: A prior integrative, multi-omics human genetics and functional genomics study identified maelstrom (MAEL), a gene involved in regulation of DNA transposon activity and genome structure, as a transcriptome-wide predictor of hydrocephalus (HC) in the brain cortex. Here we expand on this discovery and further characterize the evolutionary origin and expression of MAEL across developmental timescales and cell-lineages in the neonatal human brain towards a mechanistic understanding how variation in MAEL expression may cause HC. OBJECTIVE: To characterize the evolutionary, temporal, developmental, and lineages of MAEL expression in HC and the developing human brain. METHODS: Ensembl was used to delineate the evolution and taxonomy of MAEL across species. Analysis of single-cell RNA sequencing (scRNA-seq) of 49 brain regions across pre- and post-natal timescales from the Developing Human Brain Atlas (Allen Institute) identified temporal and spatial MAEL expression patterns. We quantified MAEL expression in primary cortical brain tissue obtained during the surgical treatment of HC. RESULTS: We performed taxonomic gene-mapping to define the evolutionary origin of MAEL to assess suitability for mechanistic characterization in vitro and in vivo across species. We find that MAEL is among the top 0.01% human-specific genes and < 50% sequence homology among commonly used model organisms with highly divergent functions, necessitating mechanistic validation in human tissue. scRNA-seq of the non-disease prenatal human brain identified MAEL expression enriched in cortical excitatory neurons, which was recapitulated in primary HC brain tissue obtained during surgery. Finally, using scRNA-seq of primary HC brain tissue, we functionally validated reduced MAEL expression, consistent with a prior human TWAS analysis. CONCLUSIONS: We identify the evolutionary, temporal, and developmental expression pattern of MAEL in the neonatal human brain. We also provide direct evidence for reduced MAEL expression in human HC brain tissue. These data, at least in part, implicate reduced MAEL expression underlying human HC across etiologies.

Journal Article↗
PubMed2001

Molecular replacement by evolutionary search.

Stochastic search algorithms can be used to perform rapid six-dimensional molecular-replacement searches. A molecular-replacement procedure has been developed that uses an evolutionary algorithm to simultaneously optimize the orientation and position of a search model in a unit cell. Here, the performance of this algorithm and its dependence on search model quality and choice of target function are examined. Although the evolutionary search procedure is capable of finding solutions with search models that represent only a small fraction of the total scattering matter of the target molecule, the efficiency of the search procedure is highly dependent on the quality of the search model. Polyalanine models frequently provide better search efficiency than all-atom models, even in cases where the side-chain positions are known with high accuracy. Although the success of the search procedure is not highly dependent on the statistic used as the target function, the correlation coefficient between observed and calculated structure-factor amplitudes generally results in better search efficiency than does the R factor. An alternative stochastic search procedure, simulated annealing, provides similar overall performance to evolutionary search. Methods of extending the evolutionary search algorithm to include internal optimization, selection and construction of the search model are now beginning to be investigated.

Algorithms↗
PubMed2002

Adaptive elastic segmentation of brain MRI via shape-model-guided evolutionary programming.

This paper presents a fully automated segmentation method for medical images. The goal is to localize and parameterize a variety of types of structure in these images for subsequent quantitative analysis. We propose a new hybrid strategy that combines a general elastic template matching approach and an evolutionary heuristic. The evolutionary algorithm uses prior statistical information about the shape of the target structure to control the behavior of a number of deformable templates. Each template, modeled in the form of a B-spline, is warped in a potential field which is itself dynamically adapted. Such a hybrid scheme proves to be promising: by maintaining a population of templates, we cover a large domain of the solution space under the global guidance of the evolutionary heuristic, and thoroughly explore interesting areas. We address key issues of automated image segmentation systems. The potential fields are initially designed based on the spatial features of the edges in the input image, and are subjected to spatially adaptive diffusion to guarantee the deformation of the template. This also improves its global consistency and convergence speed. The deformation algorithm can modify the internal structure of the templates to allow a better match. We investigate in detail the preprocessing phase that the images undergo before they can be used more effectively in the iterative elastic matching procedure: a texture classifier, trained via linear discriminant analysis of a learning set, is used to enhance the contrast of the target structure with respect to surrounding tissues. We show how these techniques interact within a statistically driven evolutionary scheme to achieve a better tradeoff between template flexibility and sensitivity to noise and outliers. We focus on understanding the features of template matching that are most beneficial in terms of the achieved match. Examples from simulated and real image data are discussed, with considerations of algorithmic efficiency.

Algorithms↗
PubMed2005

Learning deterministic finite automata with a smart state labeling evolutionary algorithm.

Learning a Deterministic Finite Automaton (DFA) from a training set of labeled strings is a hard task that has been much studied within the machine learning community. It is equivalent to learning a regular language by example and has applications in language modeling. In this paper, we describe a novel evolutionary method for learning DFA that evolves only the transition matrix and uses a simple deterministic procedure to optimally assign state labels. We compare its performance with the Evidence Driven State Merging (EDSM) algorithm, one of the most powerful known DFA learning algorithms. We present results on random DFA induction problems of varying target size and training set density. We also studythe effects of noisy training data on the evolutionary approach and on EDSM. On noise-free data, we find that our evolutionary method outperforms EDSM on small sparse data sets. In the case of noisy training data, we find that our evolutionary method consistently outperforms EDSM, as well as other significant methods submitted to two recent competitions.

Algorithms↗
PubMed2000

Evolutionary developmental biology and the problem of variation.

One of the oldest problems in evolutionary biology remains largely unsolved. Which mutations generate evolutionarily relevant phenotypic variation? What kinds of molecular changes do they entail? What are the phenotypic magnitudes, frequencies of origin, and pleiotropic effects of such mutations? How is the genome constructed to allow the observed abundance of phenotypic diversity? Historically, the neo-Darwinian synthesizers stressed the predominance of micromutations in evolution, whereas others noted the similarities between some dramatic mutations and evolutionary transitions to argue for macromutationism. Arguments on both sides have been biased by misconceptions of the developmental effects of mutations. For example, the traditional view that mutations of important developmental genes always have large pleiotropic effects can now be seen to be a conclusion drawn from observations of a small class of mutations with dramatic effects. It is possible that some mutations, for example, those in cis-regulatory DNA, have few or no pleiotropic effects and may be the predominant source of morphological evolution. In contrast, mutations causing dramatic phenotypic effects, although superficially similar to hypothesized evolutionary transitions, are unlikely to fairly represent the true path of evolution. Recent developmental studies of gene function provide a new way of conceptualizing and studying variation that contrasts with the traditional genetic view that was incorporated into neo-Darwinian theory and population genetics. This new approach in developmental biology is as important for microevolutionary studies as the actual results from recent evolutionary developmental studies. In particular, this approach will assist in the task of identifying the specific mutations generating phenotypic variation and elucidating how they alter gene function. These data will provide the current missing link between molecular and phenotypic variation in natural populations.

Animals↗
PubMed2001

The evolutionary history of brown trout (Salmo trutta L.) inferred from phylogeographic, nested clade, and mismatch analyses of mitochondrial DNA variation.

Phylogeographic, nested clade, and mismatch analyses of mitochondrial DNA (mtDNA) variation were used to infer the temporal dynamics of distributional and demographic history of brown trout (Salmo trutta). Both new and previously published data were analyzed for 1,794 trout from 174 populations. This combined analysis improved our knowledge of the complex evolutionary history of brown trout throughout its native Eurasian and North African range of distribution in many ways. It confirmed the existence of five major evolutionary lineages that evolved in geographic isolation during the Pleistocene and have remained largely allopatric since then. These should be recognized as the basic evolutionarily significant units within brown trout. Finer phylogeographic structuring was also resolved within major lineages. Contrasting temporal juxtaposition of different evolutionary factors and timing of major demographic expansions were observed among lineages. These unique evolutionary histories have been shaped both by the differential latitudinal impact of glaciations on habitat loss and potential for dispersal, as well as climatic impacts and landscape heterogeneity that translated in a longitudinal pattern of genetic diversity and population structuring at more southern latitudes. This study also provided evidence for the role of biological factors in addition to that of physical isolation in limiting introgressive hybridization among major trout lineages.

Animals↗
PubMed2004

On the evolutionary costs of self-incompatibility: incomplete reproductive compensation due to pollen limitation.

Pollen limitation affects plants with diverse reproductive systems and ecologies. In self-incompatible (SI) species, pollen limitation may preclude full reproductive compensation for prezygotic rejection of pollen. We present a model designed to explore the effects of incomplete reproductive compensation on evolutionary changes at a modifier locus that regulates the level of SI expression. Our results indicate that incomplete reproductive compensation greatly increases the evolutionary costs of SI, particularly in populations with low S-allele diversity. The evolutionary fate of modifiers of SI expression depends on the rate at which they are transmitted to future generations as well as the effects of SI on offspring number and quality. Partial SI expression can represent a stable condition rather than an evolutionarily transient state between full expression and full suppression. This unanticipated result provides the first theoretical support for the evolutionary stability of such mixed mating systems, the existence of which has recently been documented.

Evolution, Molecular↗
PubMed2006

RNA world - the dark matter of evolutionary genomics.

For a long time, molecular evolutionary biologists have been focused on DNA and proteins, whereas RNA has lived in the shadow of its famous chemical cousins as a mere intermediary. Although this perspective has begun to change since genome-wide transcriptional profiling was successfully extended to evolutionary biology, it still echoes in evolutionary literature. In this mini-review, new developments of RNA biochemistry and transcriptomics are brought to the attention of evolutionary biologists. In particular, the unexpected abundance and functional significance of noncoding RNAs is briefly reviewed. Noncoding RNAs control a remarkable range of biological pathways and processes, all with obvious fitness consequences, such as initiation of translation, mRNA abundance, transposon jumping, chromosome architecture, stem cell maintenance, development of brain and muscles, insulin secretion, cancerogenesis and plant resistance to viral infections.

Animals↗
PubMed1997

Genetics of reproduction and its evolutionary significance.

PROBLEM: To provide an evolutionary perspective on reproductive problems. METHOD OF STUDY: A broad range of evolutionary and reproductive data in the literature were analyzed. RESULTS: Evolutionary considerations provide some insight into two aspects of human reproduction. First, the inefficiency of the reproductive process (20-35% of fertilized ova yield successful pregnancies) may reflect the stress placed on the reproductive process by the relatively short evolutionary time between the hunter--gatherer and settled agricultural patterns of human life. Second, the immaturity of the immune response of the human newborn is most likely a consequence of its delivery while still in the embryonic/fetal stage of development. Delivery at this time is necessitated by the rapid development of the human brain in utero. CONCLUSIONS: The attempts to develop reproductive technologies should take into account the fundamental limits on the human reproductive process. A variety of in utero preventive and therapeutic techniques should be developed to provide the newborn with enhanced resistance to infectious diseases or to correct congenital defects. All new procedures should be thoroughly investigated and proved before being put into clinical practice.

Animals↗
PubMed2000

On the evolution of misunderstandings about evolutionary psychology.

Some of the controversy surrounding evolutionary explanations of human behavior may be due to cognitive information-processing patterns that are themselves the result of evolutionary processes. Two such patterns are (1) the tendency to oversimplify information so as to reduce demand on cognitive resources and (2) our strong desire to generate predictability and stability from perceptions of the external world. For example, research on social stereotyping has found that people tend to focus automatically on simplified social-categorical information, to use such information when deciding how to behave, and to rely on such information even in the face of contradictory evidence. Similarly, an undying debate over nature vs. nurture is shaped by various data-reduction strategies that frequently oversimplify, and thus distort, the intent of the supporting arguments. This debate is also often marked by an assumption that either the nature or the nurture domain may be justifiably excluded at an explanatory level because one domain appears to operate in a sufficiently stable and predictable way for a particular argument. As a result, critiques in-veighed against evolutionary explanations of behavior often incorporate simplified--and erroneous--assumptions about either the mechanics of how evolution operates or the inevitable implications of evolution for understanding human behavior. The influences of these tendencies are applied to a discussion of the heritability of behavioral characteristics. It is suggested that the common view that Mendelian genetics can explain the heritability of complex behaviors, with a one-gene-one-trait process, is misguided. Complex behaviors are undoubtedly a product of a more complex interaction between genes and environment, ensuring that both nature and nurture must be accommodated in a yet-to-be-developed post-Mendelian model of genetic influence. As a result, current public perceptions of evolutionary explanations of behavior are handicapped by the lack of clear articulation of the relationship between inherited genes and manifest behavior.

Biological Evolution↗
PubMed2001

Is music an evolutionary adaptation?

In contemplating the function and origin of music, a number of scholars have considered whether music might be an evolutionary adaptation. This article reviews the basic arguments related to evolutionary claims for music. Although evolutionary theories about music remain wholly speculative, musical behaviors satisfy a number of basic conditions, which suggests that there is indeed merit in pursuing possible evolutionary accounts.

Adaptation, Physiological↗
PubMed1998

Evolutionary epidemiology and manic depression.

The reformulation of epidemiological prevalence rates as evolutionary frequency rates puts medical genetics within an explicit framework of Darwinian theory. Yet an enduring and still current assumption of genomic medicine is that genes associated with disease are necessarily maladapted. Indeed, it seems it could hardly be otherwise. However, evolutionary epidemiology has begun to uncover important and surprising counter-exemplary case-studies. Thus, the present aim is to first outline this emerging sub-discipline of 'evolutionary epidemiology'. Then, a major psychopathological syndrome--manic-depression--is examined in some detail within the purview of evolutionary epidemiology. Its medical genetics are those of an adaptive polymorphism in the human genome. Hence, genes associated with what is now a major public health problem accrued as they conferred selective advantage in phylogeny. Why should manic-depressive etiogenes have been selected? A preliminary anatomic-functional model, assembled from facts of human paleoneuropsychiatry, more adequately contextualises manic-depressive genomics and phenotypy. In this model, manic-depression finds its heuristic origins in a hierarchy of behavioural strategies stabilised in phylogeny and embedded at serial levels in the brain (Hawk-Dove ESS). A proportion of the population has variant genotypy which appears to have been favoured in social competition phylogenetically but express more pathogenic phenotypy in the current environment. The paper closes with a brief consideration of clinical practices and ethical issues as alternative considerations emerge with the syndrome recast in a more positive Darwinian light.

Adaptation, Physiological↗
PubMed1998

Prevalence differences in depression among males and females: are there evolutionary explanations?

Differences in male-female prevalence rates of depression are interpreted in evolutionary perspective. Three evolutionary hypotheses are evaluated: (a) depression represents an evolved strategy to deal with adverse social interactions, particularly among partners, (b) depression has self-preservative and manipulative features, and (c) depression is a consequence of failing to achieve biological goals. While these hypotheses are not necessarily mutually exclusive, evolutionary explanations often suffer from not specifying which hypothesis is primary and which are secondary. We argue that failing to achieve biological goals is primary and that evolved strategies and self-preservative and manipulative behaviour are secondary. Findings pointing to depression-contributing features of male-female differences, asymmetries in male-female relationships and male-female differences associated with reproduction are discussed to support our view that evolutionary explanations can adequately account for a significant percentage of the reported prevalence differences.

Adaptation, Psychological↗
PubMed1971

Fitting discrete probability distributions to evolutionary events.

The assumptions underlying the use of the Poisson distribution are essentially that the probability of an event is small but nearly identical for all occurrences and that the occurrence of an event does not alter the probability of recurrence of such events. These assumptions do not seem to be met for evolutionary events since (i) the probability of fixing nucleotide codon substitutions is not equal for all substitutions at a codon, and probably varies for the same substitution in different lineages; (ii) the probability of fixing codon substitutions varies among positions of a cistron; and (iii) the fixation of a nucleotide codon substitution at one position in a cistron modifies, and may even promote, the fixation of a codon substitution elsewhere along the cistron. Natural selection presumably is the causative factor that acts to modify the probability of a nucleotide codon substitution's being fixed in a population. The use of the negative binomial distribution is consistent with the evidence that selective pressure on amino acid or nucleotide codon positions varies both among codon positions of a cistron and at a particular position during evolutionary time. If the number of fixations of nucleotide codon substitutions per position of cistrons encoding cytochromes c are phyletically inferred (phylogeny based on a paleontological record) rather than phenetically inferred (based on paired comparisons of extant species' differences in the absence of a phylogeny) the distribution of these fixation data cannot be described adequately by a single Poisson distribution. The fit of these same data to a negative binomial distribution is very satisfactory. It has been argued that the fit of phenetically inferred fixation data, which do not take account of parallel or reverse fixations, to the Poisson distribution was supportive evidence for the hypothesis that protein evolution results from the fixation of selectively neutral codon substitutions. This argument now appears to be undercut by the evidence that data on nucleotide codon fixation are more probably distributed according to the negative binomial distribution. The fact that fixation data can be described by a particular discrete probability distribution does not of itself provide insight into the mechanisms of the evolutionary process. However, the facts-(i) that the assumptions underlying the use of the negative binomial distribution adequately deal with the varying probability of fixing amino acid or nucleotide codon substitutions at and among the positions of a cistron and (ii) that the negative binomial distribution provides an excellent fit for the phyletically inferred fixation data-suggest that the negative binomial is a very appropriate discrete probability distribution for describing evolutionary events. Amino acids or their nucleotide codon substitutions may be fixed at a position of a cistron as though selectively neutral relative to the codon being replaced, even though the codon position will not be selectively neutral, since many amino acids cannot function there. The negative binomial distribution treats this situation well whereas a single Poisson distribution could only be satisfactory if all codon positions that could vary were selectively neutral.

Amino Acid Sequence↗
PubMed2000

Accommodating phylogenetic uncertainty in evolutionary studies.

Many evolutionary studies use comparisons across species to detect evidence of natural selection and to examine the rate of character evolution. Statistical analyses in these studies are usually performed by means of a species phylogeny to accommodate the effects of shared evolutionary history. The phylogeny is usually treated as known without error; this assumption is problematic because inferred phylogenies are subject to both stochastic and systematic errors. We describe methods for accommodating phylogenetic uncertainty in evolutionary studies by means of Bayesian inference. The methods are computationally intensive but general enough to be applied in most comparative evolutionary studies.

Animals↗
PubMed1998

IS6110 transposition and evolutionary scenario of the direct repeat locus in a group of closely related Mycobacterium tuberculosis strains.

In recent years, various polymorphic loci and multicopy insertion elements have been discovered in the Mycobacterium tuberculosis genome, such as the direct repeat (DR) locus, the major polymorphic tandem repeats, the polymorphic GC-rich repetitive sequence, IS6110, and IS1081. These, especially IS6110 and the DR locus, have been widely used as genetic markers to differentiate M. tuberculosis isolates and will continue to be so used, due to the conserved nature of the genome of M. tuberculosis. However, little is known about the processes involved in generating these or of their relative rates of change. Without an understanding of the biological characteristics of these genetic markers, it is difficult to use them to their full extent for understanding the population genetics and epidemiology of M. tuberculosis. To address these points, we identified a cluster of 7 isolates in a collection of 101 clinical isolates and investigated them with various polymorphic genetic markers, which indicated that they were highly related to each other. This cluster provided a model system for the study of IS6110 transposition, evolution at the DR locus, and the effects of these on the determination of evolutionary relationships among M. tuberculosis strains. Our results suggest that IS6110 restriction fragment length polymorphism patterns are useful in grouping closely related isolates together; however, they can be misleading if used for making inferences about the evolutionary relationships between closely related isolates. DNA sequence analysis of the DR loci of these isolates revealed an evolutionary scenario, which, complemented with the information from IS6110, allowed a reconstruction of the evolutionary steps and relationships among these closely related isolates. Loss of the IS6110 copy in the DR locus was noted, and the mechanisms of this loss are discussed.

Base Sequence↗