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PubMed2003

Patterns of human genetic diversity: implications for human evolutionary history and disease.

Since the completion of the human genome sequencing project, the discovery and characterization of human genetic variation is a principal focus for future research. Comparative studies across ethnically diverse human populations and across human and nonhuman primate species is important for reconstructing human evolutionary history and for understanding the genetic basis of human disease. In this review, we summarize data on patterns of human genetic diversity and the evolutionary forces (mutation, genetic drift, migration, and selection) that have shaped these patterns of variation across both human populations and the genome. African population samples typically have higher levels of genetic diversity, a complex population substructure, and low levels of linkage disequilibrium (LD) relative to non-African populations. We discuss these differences and their implications for mapping disease genes and for understanding how population and genomic diversity have been important in the evolution, differentiation, and adaptation of humans.

Biological Evolution↗
PubMed1999

Heat-shock proteins, molecular chaperones, and the stress response: evolutionary and ecological physiology.

Molecular chaperones, including the heat-shock proteins (Hsps), are a ubiquitous feature of cells in which these proteins cope with stress-induced denaturation of other proteins. Hsps have received the most attention in model organisms undergoing experimental stress in the laboratory, and the function of Hsps at the molecular and cellular level is becoming well understood in this context. A complementary focus is now emerging on the Hsps of both model and nonmodel organisms undergoing stress in nature, on the roles of Hsps in the stress physiology of whole multicellular eukaryotes and the tissues and organs they comprise, and on the ecological and evolutionary correlates of variation in Hsps and the genes that encode them. This focus discloses that (a) expression of Hsps can occur in nature, (b) all species have hsp genes but they vary in the patterns of their expression, (c) Hsp expression can be correlated with resistance to stress, and (d) species' thresholds for Hsp expression are correlated with levels of stress that they naturally undergo. These conclusions are now well established and may require little additional confirmation; many significant questions remain unanswered concerning both the mechanisms of Hsp-mediated stress tolerance at the organismal level and the evolutionary mechanisms that have diversified the hsp genes.

Animals↗
PubMed2003

An evolutionary approach for identifying potential transcription factor binding sites: the renin gene as an example.

Evolutionary pressure has resulted in the conservation of certain nucleotide sequences. These conserved regions are potentially important for certain functions. Here we give an example of a comparison between noncoding sequences combined with other independent database information to shed light onto the regulation of the renin gene, a gene that has great importance for cardiovascular and renal homeostasis. To combine the information regarding conservation and weight matrices of transcription factor (TF) binding sites, an algorithm was developed (TFprofile). Notably, a local peak in the resulting binding profile coincides with a previously experimentally identified regulatory region for the renin gene. The existence of further peaks in the binding profile in the conserved 3.9-kb-long hRENc DNA block upstream of the renin gene suggests additional regions of potential importance for gene regulation. The algorithm TFprofile may be used to integrate information on cross-species evolutionary conservation and aspects of TF binding characteristics to provide putative regulatory DNA regions for experimental verification.

Animals↗
PubMed2004

An evolutionary perspective on single-nucleotide polymorphism screening in molecular cancer epidemiology.

Given that there are millions of single-nucleotide polymorphisms (SNPs) in the entire human genome, a major difficulty faced by scientists in planning costly population-based genotyping is to choose target SNPs that are most likely to affect phenotypic functions and ultimately contribute to disease development. Although it is widely accepted that sequences with important functionality tend to be less variable across species because of selective pressure, to what extent evolutionary conservation is mirrored by epidemiological outcome has never been demonstrated. In this study, we surveyed odds ratios detected for 46 SNPs in 39 different cancer-related genes from 166 molecular epidemiological studies. The conservation levels of amino acid that these SNPs affected were calculated as a tolerance index by comparing sequences from different species. Our results provide evidence of a significant relationship between the detected odds ratios associated with cancer risk and the conservation levels of the SNP-affected amino acids (P = 0.002; R(2) = 0.06). Tolerance indices were further calculated for 355 nonsynonymous SNPs identified in 90 human DNA repair genes, of which 103 caused amino acid changes in very conserved positions. Our findings support the concept that SNPs altering the conserved amino acids are more likely to be associated with cancer susceptibility. Using such a molecular evolutionary approach may hold great promise for prioritizing SNPs to be genotyped in future molecular epidemiological studies.

Alleles↗
PubMed1999

Evolutionary disruptions of human syntenic groups 3, 12, 14, and 15 in Ateles paniscus chamek (Platyrrhini, primates).

Comparative gene assignments of 18 markers, based on analyses of somatic cell hybrids and previous data in the literature, indicated that human (HSA) syntenic groups 3, 12, 14, and 15 are dissociated in the spider monkey species Ateles paniscus chamek (APC). Markers present in HSA 3p were allocated to APC 3 and APC 9. The HSA 12 cluster was split into two syntenic groups, one mainly including HSA 12p markers in APC 16 and the other, including HSA 12q markers, in APC 2p. The HSA 14q cluster split into three syntenic groups, corresponding to APC 2q, APC 6, and APC 12. Finally, the HSA 15 cluster split into two syntenic groups, APC 2q and APC 3. Comparisons with previous gene assignments and human SROs led to the tentative postulation of rearrangements having occurred during the evolutionary divergence of man and A. paniscus chamek. Chromosome painting data in the congeneric species A. geoffroyi, other New World and Old World primates, and several representative non-primate animals were compared in an attempt to delineate the ancestral and derived conditions underlying the evolutionary rearrangement of syntenic groups in mammals.

Animals↗
PubMed1998

Evolutionary history of lorisiform primates.

We integrate information from the fossil record, morphology, behavior and molecular studies to provide a current overview of lorisoid evolution. Several Eocene prosimians of the northern continents, including both omomyids and adapoids, have been suggested as possible lorisoid ancestors, but these cannot be substantiated as true strepsirhines. A small-bodied primate, Anchomomys, of the middle Eocene of Europe may be the best candidate among putative adapoids for status as a true strepsirhine. Recent finds of Eocene primates in Africa have revealed new prosimian taxa that are also viable contenders for strepsirhine status. Plesiopithecus teras is a Nycticebussized, nocturnal prosimian from the late Eocene, Fayum, Egypt, that shares cranial specializations with lorisoids, but it also retains primitive features (e.g. four premolars) and has unique specializations of the anterior teeth excluding it from direct lorisiform ancestry. Another unnamed Fayum primate resembles modern cheirogaleids in dental structure and body size. Two genera from Oman, Omanodon and Shizarodon, also reveal a mix of similarities to both cheirogaleids and anchomomyin adapoids. Resolving the phylogenetic position of these Africa primates of the early Tertiary will surely require more and better fossils. By the early to middle Miocene, lorisoids were well established in East Africa, and the debate about whether these represent lorisines or galagines is reviewed. Neontological data are used to address the controversial branching sequences among extent lorisid clades. Data from the skin and scent glands, when integrated with other lines of evidence, suggest that Asian and African lorisines share a common lorisine ancestry. The hypothesis of an African clade containing both pottos and galagos to the exclusion of Asian lorisines is less tenable. True galagines are found in the fossil record of Namibia, while true lorisines are known from the Miocene of Asia. The hypothetical branching sequences can be integrated with behavioral and morphological features to develop an adaptive model of lorisoid divergence. By specializing on two different foraging modes early in their radiation, lorisines and galagines subsequently underwent a chain of integrated evolutionary changes eventually having an impact on many components of locomotor behavior, anatomy, physiology, reproduction, life history, and social behavior. Ongoing evolutionary studies of extant galagines are illuminating population phenomena and processes of speciation in an ecological context.

Africa↗
PubMed2004

The evolutionary conservation of the human chitotriosidase gene in rodents and primates.

Chitinases have been identified in a variety of organisms ranging from prokaryotes to eukaryotes, known to specifically degrade chitin, an abundant polymer of N-acetylglucosamine. Recently a human chitinolytic enzyme called CHIT1 was discovered. CHIT1 is expressed by activated macrophages and hydrolyzes artificial chitotrioside substrates, but its specific function in humans is unknown, since it is generally believed that man completely lacks endogenous chitin and endogenous substrates for chitinases. An intriguing question is whether the chitotriosidase activity is just an evolutionary remnant or it has a physiological function in man. To test these hypotheses we utilized a "phylogenomic" approach performing accurate sequence analyses of this gene, coding for CHIT1, in rodents and primates. Inspecting the sequences available in public databases, we determined that this gene is conserved in rodents (mouse and rat) and primates (chimpanzee, gorilla, orangutan, gibbon, baboon, a common marmoset and black macaque). Moreover we found that a 24-base pair duplication that determines an enzymatically inactive human protein is not present in primates, suggesting that this polymorphism was created during human evolution. These results indicate that chitotriosidase is conserved across the evolutionary scale. Such conservation of the CHIT1 gene argues in favour of an important biological role.

Amino Acid Sequence↗
PubMed2005

Inactivity of recombinant ELA2B provides a new example of evolutionary elastase silencing in humans.

BACKGROUND: The archetypal mammalian elastase (ELA1) is not expressed in the human pancreas, because evolutionary mutations suppressed transcription of the ELA1 gene. AIMS: In this study, we tested the theory that the unique duplication of the ELA2 gene in humans might compensate for the loss of ELA1. METHODS: Recombinant ELA2A and ELA2B were expressed in Escherichia coli, and their activity was tested on Glt-Ala-Ala-Pro-Leu-p-nitroanilide, DQ elastin and bovine milk protein. RESULTS: Surprisingly, recombinant ELA2B was completely devoid of proteolytic activity, while ELA2A readily hydrolyzed all three test substrates. Furthermore, ELA2A formed an SDS-resistant complex with alpha1-antitrypsin, whereas ELA2B did not bind covalently to the inhibitor. Finally, chimeras and point mutations engineered between ELA2A and ELA2B revealed that multiple evolutionary mutations inactivated ELA2B. CONCLUSIONS: The results indicate that ELA2B is not an elastase enzyme and confirm that ELA2A is the major elastase in the human pancreas.

Biological Evolution↗
PubMed1990

Evolutionary innovation in behavior and speciation: opportunities for behavioral neuroethology.

Populations of animals differentiate by speciation. How speciation takes place, for long a puzzle for evolutionary biologists, should be regarded as a research opportunity for neuroethologists and comparative behaviorists. It is now clear that behavior may play an important part in the process of speciation. The existence of sexually dimorphic anatomy and behavior in many animals has provided a rich subject for investigation by comparative neurobiologists and behaviorists, who emphasize analysis of proximate mechanisms that generate dimorphism in phenotype. However, sexual dimorphisms also figure prominently in the theory of sexual selection. Sexual selection is viewed as a primary behavioral mechanism in the process of speciation. Some examples of 'explosive' speciation are presented, and the putative role that sexual selection plays in these cases is reviewed. A consideration of any evolutionary selective process must include genetics, and I will briefly summarize studies that indicate that even complex behavioral systems such as sexual selection, which sociobiologists refer to as a 'strategy', can have a relatively simple genetic basis.

Animals↗
PubMed1996

Chicken CP49: significant or paltry? An evolutionary perspective.

The lens-specific intermediate filament (IF) proteins CP49 and filensin have been identified in a large number of evolutionary divergent species. In the chick lens both CP49 and filensin have been identified. Recently a unique variant of CP49, CP49ins has been identified. CP49ins contains an insertion of 49 amino acids in helix 1b giving it characteristics similar to the lamin-like cytoplasmic IF of invertebrates. The presence of this variant form in the chick lens poses some important questions about the co-assembly of the two CP49 forms and also the evolutionary relationship with invertebrate IF proteins.

Animals↗
PubMed1991

Matching between ventricle and arterial load. An evolutionary process.

The hemodynamic properties of the ventricle are related to those of the arterial load. However, the precise nature of this relation is not known. At least three different matching criteria have been described in the literature: optimization of heart rate, of power output, and of external efficiency. Although these suggestions are based on experimental findings, there is little understanding of the underlying principles. We now suggest that the balance between the ventricle and its load is a result of the evolutionary process. To support our view, three simple assumptions are proposed regarding the evolutionary determinants underlying the relation between ventricle and arterial load: 1) Arterial pressure and flow to be generated by the ventricular pump under normal (control) conditions are set by the demands of the body. 2) Mechanical properties of contractile machinery and arterial wall material are given. 3) The heart and arterial system should have minimum size. On the basis thereof, we argue that heart rate is related to maintenance of diastolic pressure and show that the ventricle operates close to optimum power and efficiency to attain minimum size.

Animals↗
PubMed2003

Speeding up backpropagation using multiobjective evolutionary algorithms.

The use of backpropagation for training artificial neural networks (ANNs) is usually associated with a long training process. The user needs to experiment with a number of network architectures; with larger networks, more computational cost in terms of training time is required. The objective of this letter is to present an optimization algorithm, comprising a multiobjective evolutionary algorithm and a gradient-based local search. In the rest of the letter, this is referred to as the memetic Pareto artificial neural network algorithm for training ANNs. The evolutionary approach is used to train the network and simultaneously optimize its architecture. The result is a set of networks, with each network in the set attempting to optimize both the training error and the architecture. We also present a self-adaptive version with lower computational cost. We show empirically that the proposed method is capable of reducing the training time compared to gradient-based techniques.

Algorithms↗
PubMed2001

A convergence analysis of unconstrained and bound constrained evolutionary pattern search.

We present and analyze a class of evolutionary algorithms for unconstrained and bound constrained optimization on R(n): evolutionary pattern search algorithms (EPSAs). EPSAs adaptively modify the step size of the mutation operator in response to the success of previous optimization steps. The design of EPSAs is inspired by recent analyses of pattern search methods. We show that EPSAs can be cast as stochastic pattern search methods, and we use this observation to prove that EPSAs have a probabilistic, weak stationary point convergence theory. This convergence theory is distinguished by the fact that the analysis does not approximate the stochastic process of EPSAs, and hence it exactly characterizes their convergence properties.

Algorithms↗
PubMed2001

Gene expression and fast construction of distributed evolutionary representation.

The gene expression process in nature produces different proteins in different cells from different portions of the DNA. Since proteins control almost every important activity in a living organism, at an abstract level, gene expression can be viewed as a process that evaluates the merit or "fitness" of the DNA. This distributed evaluation of the DNA would not be possible without a decomposed representation of the fitness function defined over the DNAs. This paper argues that, unless the living body was provided with such a representation, we have every reason to believe that it must have an efficient mechanism to construct this distributed representation. This paper demonstrates polynomial-time computability of such a representation by proposing a class of efficient algorithms. The main contribution of this paper is two-fold. On the algorithmic side, it offers a way to scale up evolutionary search by detecting the underlying structure of the search space. On the biological side, it proves that the distributed representation of the evolutionary fitness function in gene expression can be computed in polynomial-time. It advances our understanding about the representation construction in gene expression from the perspective of computing. It also presents experimental results supporting the theoretical performance of the proposed algorithms.

Algorithms↗
PubMed2001

Optical coating designs using the family competition evolutionary algorithm.

A robust evolutionary approach, called the Family Competition Evolutionary Algorithm (FCEA), is described for the synthesis of optical thin-film designs. Based on family competition and adaptive rules, the proposed approach consists of global and local strategies by integrating decreasing mutations and self-adaptive mutations. The method is applied to three different optical coating designs with complex spectral quantities. Numerical results indicate that the proposed approach performs very robustly and is very competitive with other approaches.

Algorithms↗
PubMed2001

Theoretical analysis of mutation-adaptive evolutionary algorithms.

Adaptive evolutionary algorithms require a more sophisticated modeling than their static-parameter counterparts. Taking into account the current population is not enough when implementing parameter-adaptation rules based on success rates (evolution strategies) or on premature convergence (genetic algorithms). Instead of Markov chains, we use random systems with complete connections - accounting for a complete, rather than recent, history of the algorithm's evolution. Under the new paradigm, we analyze the convergence of several mutation-adaptive algorithms: a binary genetic algorithm, the 1/5 success rule evolution strategy, a continuous, respectively a dynamic (1+1) evolutionary algorithm.

Algorithms↗
PubMed2002

A computationally efficient evolutionary algorithm for real-parameter optimization.

Due to increasing interest in solving real-world optimization problems using evolutionary algorithms (EAs), researchers have recently developed a number of real-parameter genetic algorithms (GAs). In these studies, the main research effort is spent on developing an efficient recombination operator. Such recombination operators use probability distributions around the parent solutions to create an offspring. Some operators emphasize solutions at the center of mass of parents and some around the parents. In this paper, we propose a generic parent-centric recombination operator (PCX) and a steady-state, elite-preserving, scalable, and computationally fast population-alteration model (we call the G3 model). The performance of the G3 model with the PCX operator is investigated on three commonly used test problems and is compared with a number of evolutionary and classical optimization algorithms including other real-parameter GAs with the unimodal normal distribution crossover (UNDX) and the simplex crossover (SPX) operators, the correlated self-adaptive evolution strategy, the covariance matrix adaptation evolution strategy (CMA-ES), the differential evolution technique, and the quasi-Newton method. The proposed approach is found to consistently and reliably perform better than all other methods used in the study. A scale-up study with problem sizes up to 500 variables shows a polynomial computational complexity of the proposed approach. This extensive study clearly demonstrates the power of the proposed technique in tackling real-parameter optimization problems.

Algorithms↗
PubMed2003

Redundant representations in evolutionary computation.

This paper discusses how the use of redundant representations influences the performance of genetic and evolutionary algorithms. Representations are redundant if the number of genotypes exceeds the number of phenotypes. A distinction is made between synonymously and non-synonymously redundant representations. Representations are synonymously redundant if the genotypes that represent the same phenotype are very similar to each other. Non-synonymously redundant representations do not allow genetic operators to work properly and result in a lower performance of evolutionary search. When using synonymously redundant representations, the performance of selectorecombinative genetic algorithms (GAs) depends on the modification of the initial supply. We have developed theoretical models for synonymously redundant representations that show the necessary population size to solve a problem and the number of generations goes with O(2(kr)/r), where kr is the order of redundancy and r is the number of genotypic building blocks (BB) that represent the optimal phenotypic BB. As a result, uniformly redundant representations do not change the behavior of GAs. Only by increasing r, which means overrepresenting the optimal solution, does GA performance increase. Therefore, non-uniformly redundant representations can only be used advantageously if a-priori information exists regarding the optimal solution. The validity of the proposed theoretical concepts is illustrated for the binary trivial voting mapping and the real-valued link-biased encoding. Our empirical investigations show that the developed population sizing and time to convergence models allow an accurate prediction of the empirical results.

Algorithms↗