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At least 919 records · Page 51Linked to original sources
PubMed2001

Modeling genetic networks and their evolution: a complex dynamical systems perspective.

After finishing the sequence of the human genome, a functional understanding of genome dynamics is the next major step on the agenda of the biosciences. New approaches, such as microarray techniques, and new methods of bioinformatics provide powerful tools aiming in this direction. In the last few years, important parts of genome organization and dynamics in a number of model organisms have been determined. However, an integrated view of gene regulation on a genomic scale is still lacking. Here, genome function is discussed from a complex dynamical systems perspective: which dynamical properties can a large genomic system exhibit in principle, given the local mechanisms governing the small subsystems that we know today? Models of artificial genetic networks are used to explore dynamical principles and possible emergent dynamical phenomena in networks of genetic switches. One observes evolution of robustness and dynamical self-organization in large networks of artificial regulators that are based on the dynamic mechanism of transcriptional regulators as observed in biological gene regulation. Possible biological observables and ways of experimental testing of global phenomena in genome function and dynamics are discussed. Models of artificial genetic networks provide a tool to address questions in genome dynamics and their evolution and allow simulation studies in evolutionary genomics.

Biological Evolution↗
PubMed1986

Trophic molecules and evolution of the nervous system.

Although recent work has reemphasized the general importance of ontogeny in evolution, underlying developmental molecular mechanisms are largely undefined. What heritable ontogenetic mechanisms result in the evolution of new morphologies and functions? Such questions are particularly difficult in the nervous system, in which each of 10(11) neurons forms approximately equal to 10(4) specific interconnections. I propose that specific heritable, trophic interactions during development, which determine cell survival and pathway size, form a substrate for neural evolution. This model is based on the observation that neurons are vastly overproduced during ontogeny; neurons, their pathways and connections are dependent on target-derived trophic factors for developmental survival; and co-innervating, functionally and anatomically distinct neural populations compete for common trophic factors for survival. Focusing on sympathetic and sensory neurons, which require the target-derived, trophic protein nerve growth factor at different times for developmental survival, and which innervate common targets, different classes of ontogenetic evolutionary mechanisms may be characterized. Evolution may occur from heritable changes in the structure of trophic gene products or altered timing of expression. Molecular mechanisms underlying heterochrony are thereby described. The model is directly applicable to evolution of the brain and is testable in a variety of situations.

Biological Evolution↗
PubMed2004

Model selection in ecology and evolution.

Recently, researchers in several areas of ecology and evolution have begun to change the way in which they analyze data and make biological inferences. Rather than the traditional null hypothesis testing approach, they have adopted an approach called model selection, in which several competing hypotheses are simultaneously confronted with data. Model selection can be used to identify a single best model, thus lending support to one particular hypothesis, or it can be used to make inferences based on weighted support from a complete set of competing models. Model selection is widely accepted and well developed in certain fields, most notably in molecular systematics and mark-recapture analysis. However, it is now gaining support in several other areas, from molecular evolution to landscape ecology. Here, we outline the steps of model selection and highlight several ways that it is now being implemented. By adopting this approach, researchers in ecology and evolution will find a valuable alternative to traditional null hypothesis testing, especially when more than one hypothesis is plausible.

Journal Article↗
PubMed2005

Advances in phylogeny reconstruction from gene order and content data.

Genomes can be viewed in terms of their gene content and the order in which the genes appear along each chromosome. Evolutionary events that affect the gene order or content are "rare genomic events" (rarer than events that affect the composition of the nucleotide sequences) and have been advocated by systematists for inferring deep evolutionary histories. This chapter surveys recent developments in the reconstruction of phylogenies from gene order and content, focusing on their performance under various stochastic models of evolution. Because such methods are quite restricted in the type of data they can analyze, we also present research aimed at handling the full range of whole-genome data.

Algorithms↗
PubMed2004

Molecular systematics and biogeography of the southern South american freshwater "crabs" Aegla (decapoda: Anomura: Aeglidae) using multiple heuristic tree search approaches.

Recently new heuristic genetic algorithms such as Treefinder and MetaGA have been developed to search for optimal trees in a maximum likelihood (ML) framework. In this study we combined these methods with other standard heuristic approaches such as ML and maximum parsimony hill-climbing searches and Bayesian inference coupled with Markov chain Monte Carlo techniques under homogeneous and mixed models of evolution to conduct an extensive phylogenetic analysis of the most abundant and widely distributed southern South American freshwater"crab,"the Aegla(Anomura: Aeglidae). A total of 167 samples representing 64 Aegla species and subspecies were sequenced for one nuclear (28S rDNA) and four mitochondrial (12S and 16S rDNA, COI, and COII) genes (5352 bp total). Additionally, six other anomuran species from the genera Munida,Pachycheles, and Uroptychus(Galatheoidea), Lithodes(Paguroidea), and Lomis(Lomisoidea) and the nuclear 18S rDNA gene (1964 bp) were included in preliminary analyses for rooting the Aegla tree. Nonsignificantly different phylogenetic hypotheses resulted from all the different heuristic methods used here, although the best scored topologies found under the ML hill-climbing, Bayesian, and MetaGA approaches showed considerably better likelihood scores (Delta> 54) than those found under the MP and Treefinder approaches. Our trees provided strong support for most of the recognized Aegla species except for A. cholchol,A. jarai,A. parana,A. marginata, A. platensis, and A. franciscana, which may actually represent multiple species. Geographically, the Aegla group was divided into a basal western clade (21 species and subspecies) composed of two subclades with overlapping distributions, and a more recent central-eastern clade (43 species) composed of three subclades with fairly well-recognized distributions. This result supports the Pacific-Origin Hypothesis postulated for the group; alternative hypotheses of Atlantic or multiple origins were significantly rejected by our analyses. Finally, we combined our phylogenetic results with previous hypotheses of South American paleodrainages since the Jurassic to propose a biogeographical framework of the Aegla radiation.

Animals↗
PubMed2006

Model use in phylogenetics: nine key questions.

Models of character evolution underpin all phylogeny estimations, thus model adequacy remains a crucial issue for phylogenetics and its many applications. Although progress has been made in selecting appropriate models for phylogeny estimation, there is still concern about their purpose and proper use. How do we interpret models in a phylogenetic context? What are their effects on phylogeny estimation? How can we improve confidence in the models that we choose? That the phylogenetics community is asking such questions denotes an important stage in the use of explicit models. Here, we examine these and other common questions and draw conclusions about how the community is using and choosing models, and where this process will take us next.

Animals↗
PubMed2026

Episode clustering in phylogenetic networks.

MOTIVATION: The classical duplication episode clustering (EC) model introduced by Guigó et al. in the 1990s provides a foundational approach for inferring genomic duplication events crucial to understanding genome evolution. This model clusters single gene duplications from a collection of gene trees at locations in the species tree to minimize the total number of such locations, called duplication episodes. However, it does not capture reticulate evolutionary histories. RESULTS: Here, we introduce NetEC, a novel extension of this problem to phylogenetic networks. To solve NetEC, we first develop a polynomial-time dynamic programming (DP) algorithm for testing whether a given set of network nodes can serve as episode locations. We then propose a main inference algorithm that utilizes this DP component to optimize the episode count; while the feasibility test runs in polynomial time, the full optimization has exponential worst-case complexity, and an optional heuristic mode is provided for larger instances. We also propose an extended episode analysis procedure that identifies additional genomic duplication candidates below reticulation nodes, complementing the main algorithm by resolving potential upward clustering of duplications induced by reticulation. We evaluate our method on simulated data and on an empirical Pandanales dataset comprising over 29 000 gene trees, demonstrating exact and accurate inference of genomic duplication events even in the presence of multiple reticulations. AVAILABILITY AND IMPLEMENTATION: All experiments were conducted using the NetEC tool (https://github.com/ppgorecki/netec), with all input data, scripts, and parameter settings for reproduction available in the same repository.

Phylogeny↗
PubMed2006

Model based on a quantum algorithm to study the evolution of an epidemics.

A model based on a quantum algorithm is used to study the spread of HIV virus and to predict infection rates on individuals who are not aware of their particular condition. The model makes an analogy between quantum systems and individuals who are infected by the disease. Individuals are represented by two-level quantum systems (quantum "bit"), and the interactions among individuals who cause the infection are represented by unitary transformations. The population is divided into categories according to their behaviour, and the interactions among those individuals in the same category and those in different categories are simulated. The objective is to obtain statistical data on the number of infected individuals depending on the time for every category and for the entire population. Besides, we analyse the impact of the evolution of the disease on individuals who have not knowledge of their specific sanitary condition.

Algorithms↗
PubMed1994

Developmental quantitative genetic models of evolutionary change.

Discussions about evolutionary change in developmental processes or morphological structures are predicated on specific quantitative genetic models whose parameters predict whether evolutionary change can occur, its relative rate and direction, and if correlated change will occur in other related and unrelated structures. The appropriate genetic model should reflect the relevant genetical and developmental biology of the organisms, yet be simple enough in its parameters so that deductions can be made and hypotheses tested. As a consequence, the choice of the most appropriate genetic model for polygenically controlled traits is a complex tissue and the eventual choice of model is often a compromise between completeness of the model and computational expediency. Herein, we discuss several developmental quantitative genetic models for the evolution of development and morphology. The models range from the classical direct effects model to complex epigenetic models. Further, we demonstrate the algebraic equivalency of the Cowley and Atchley epigenetic model and Wagner's developmental mapping model. Finally, we propose a new multivariate model for continuous growth trajectories. The relative efficacy of these various models for understanding evolutionary change in developmental and morphological traits is discussed.

Animals↗
PubMed2000

The evolution of haplodiploidy under inbreeding.

Although haplodiploid organisms tend to be inbred, previous models of the evolution of haplodiploidy have assumed outbred populations. Here a model for the evolution of haplodiploidy is developed which incorporates sib mating, deleterious mutations generated by mutation, and fitness differences between haploids and diploids. Simulations of the model allow an assessment of the effect of inbreeding on the deleterious mutation and maternal transmission theories for the evolution of haplodiploidy. As expected from intuitive arguments, inbreeding favours haplodiploidy under the deleterious mutation hypothesis but disfavours haplodiploidy under the maternal transmission hypothesis. It appears that the effect of inbreeding is greater on the maternal transmission theory, and thus inbreeding may restrict the evolution of haplodiploidy.

Animals↗
PubMed1993

Natural selection on multivariate traits in age-structured populations.

The theory of selection on multivariate traits in age-structured populations has important implications for empirical and theoretical studies of life-history evolution. A model of natural selection on a set of correlated quantitative traits with age structure is derived here, using an extension of previous work on selection at a single locus. This formulation provides an equation for the change of the mean of a vector of traits that is accurate is selection is weak, and does not require the population always to be in demographic equilibrium as selection proceeds. The treatment is extended to density-dependent populations, and to equilibrium populations under frequency-dependent selection. In addition, further approximations are derived that produce evolutionary equilibria equivalent to those predicted by optimization and evolutionarily stable strategy (ESS) theory. It is shown that the conditions for equilibrium are valid even if selection is strong.

Aging↗
PubMed2004

Testing alternative models for sexual isolation in natural populations of Littorina saxatilis: indirect support for by-product ecological speciation?

Two ecotypes of the rough periwinkle Littorina saxatilis occur at different shore levels, showing assortative mating for size and partial reproductive isolation when they meet at the mid-shore. This system represents a putative case of incomplete speciation in sympatry. Two processes contribute to the assortative mating: morph-specific microhabitat aggregation and mate choice. The estimation of mate choice coefficients in nature and a simulation of the aggregation effects on sexual isolation were used to disentangle these processes as well as to test alternative mechanisms of mate choice. Mate choice significantly increased the frequency of within-morph pairs and significantly decreased the frequency of between-morph pairs, whereas those pairs including at least one hybrid morph mated randomly. These results allow us to reject a discriminant mate choice and support a model of evolution of sexual isolation as a side-effect of size-assortative mating in a context of divergent natural selection for size in the population. This mechanism is more compatible with a model of incomplete by-product ecological speciation, as suggested by previous evidence.

Animals↗
PubMed2000

Comparative analyses for adaptive radiations.

Biologists generally agree that most morphological variation between closely related species is adaptive. The most common method of comparative analysis to test for co-evolved character variation is based on a Brownian-motion model of character evolution. If we are to test for the evolution of character-covariation, and we believe that characters have evolved adaptively to fill niches during an adaptive radiation, then it is appropriate to employ appropriate models for character evolution. We show here that under several models of adaptive character evolution and coevolution during an adaptive radiation, which result in closely related species being more similar to each other than to more distantly related species, cross-species analyses are statistically more appropriate than contrast analyses. If the evolution of some traits fits the Brownian-motion model, while others evolve to fill niches during an adaptive radiation, it might be necessary to identify the number of relevant niche dimensions and the modes of character evolution before deciding on appropriate statistical procedures. Alternatively, maximum-likelihood procedures might be used to determine appropriate transformations of phylogenetic branch lengths that accord with particular models of character evolution.

Adaptation, Physiological↗
PubMed2005

Analysis of vertebrate genomes suggests a new model for clade B serpin evolution.

BACKGROUND: The human genome contains 13 clade B serpin genes at two loci, 6p25 and 18q21. The three genes at 6p25 all conform to a 7-exon gene structure with conserved intron positioning and phasing, however, at 18q21 there are two 7-exon genes and eight genes with an additional exon yielding an 8-exon structure. Currently, it is not known how these two loci evolved, nor which gene structure arose first--did the 8-exon genes gain an exon, or did the 7-exon genes lose one? Here we use the genomes of diverse vertebrate species to plot the emergence of clade B serpin genes and to identify the point at which the two genomic structures arose. RESULTS: Analysis of the chicken genome indicated the presence of a single clade B serpin gene locus, containing orthologues of both human loci and both genomic structures. The frog genome and the genomes of three fish species presented progressively simpler loci, although only the 7-exon structure could be identified. The Serpinb12 gene contains seven exons in the frog genome, but eight exons in chickens and humans, indicating that the additional exon evolved in this gene. CONCLUSION: We propose a new model for clade B serpin evolution from a single 7-exon gene (either Serpinb1 or Serpinb6). An additional exon was gained in the Serpinb12 gene between the tetrapoda and amniota radiations to produce the 8-exon structure. Both structures were then duplicated at a single locus until a chromosomal breakage occurred at some point along the mammalian lineage resulting in the two modern loci.

Animals↗
PubMed1992

Cranial capacity evolution in Homo erectus and early Homo sapiens.

This paper investigates patterns of cranial capacity evolution in Homo erectus, early Homo sapiens, and in regional subsamples of H. erectus. Specifically, models explaining evolution of cranial capacity in these taxa are evaluated with statistical techniques developed for the analysis of time series data. Regression estimates of rates of evolution in cranial capacity are also obtained. A non-parametric test for trend suggests that cranial capacity in both H. erectus and early H. sapiens may increase significantly through time. Cranial capacity in an Asian subsample of H. erectus (comprised of Chinese and Indonesian specimens) increases significantly through time. Other subsamples of H. erectus (African, Chinese, and Indonesian) do not appear to increase significantly through time. Regression results generally corroborate results of the test for trend. Spatial and temporal variation may characterize evolution of cranial capacity in H. erectus. Different patterns of cranial capacity evolution may distinguish H. erectus from early H. sapiens.

Africa↗
PubMed1997

Effect of time delay and evolutionarily stable strategy.

In this paper, a simple two-phenotype model with time delay is investigated. The main results are that: (i) the stability of the interior equilibrium point of the pure strategy model not only depends on the property of the payoff matrix but also the effect of time delay; (ii) the conditions of the evolutionarily stable strategy in the two-phenotype model with time delay are completely identical with the conditions in the two-phenotype model with no time delay; and (iii) a mixed evolutionarily stable strategy can be an unstable equilibrium state of the population in the two-phenotype model with time delay.

Animals↗