CiteULike: Tag genetic

From Genotype to Phenotype: Systems Biology Meets Natural Variation

Philip Benfey — 2008-04-24T22:05:03-00:00

Science, Vol. 320, No. 5875. (25 April 2008), pp. 495-497.

The promise that came with genome sequencing was that we would soon know what genes do, particularly genes involved in human diseases and those of importance to agriculture. We now have the full genomic sequence of human, chimpanzee, mouse, chicken, dog, worm, fly, rice, and cress, as well as those for a wide variety of other species, and yet we still have a lot of trouble figuring out what genes do. Mapping genes to their function is called the "genotype-to-phenotype problem," where phenotype is whatever is changed in the organism when a gene's function is altered. 10.1126/science.1153716

Integrating physical and genetic maps: from genomes to interaction networks

Andreas Beyer — 2007-08-18T01:43:38-00:00

Nature Reviews Genetics, Vol. 8, No. 9., pp. 699-710.

Buffering Mechanisms in Aging: A Systems Approach Toward Uncovering the Genetic Component of Aging

Aviv Bergman — 2007-09-03T00:51:56-00:00

PLoS Computational Biology, Vol. 3, No. 8. (1 August 2007), e170.

An unrealized potential to understand the genetic basis of aging in humans, is to consider the immense survival advantage of the rare individuals who live 100 years or more. The Longevity Gene Study was initiated in 1998 at the Albert Einstein College of Medicine to investigate longevity genes in a selected population: the “oldest old” Ashkenazi Jews, 95 years of age and older, and their children. The study proved the principle that some of these subjects are endowed with longevity-promoting genotypes. Here we reason that some of the favorable genotypes act as mechanisms that buffer the deleterious effect of age-related disease genes. As a result, the frequency of deleterious genotypes may increase among individuals with extreme lifespan because their protective genotype allows disease-related genes to accumulate. Thus, studies of genotypic frequencies among different age groups can elucidate the genetic determinants and pathways responsible for longevity. Borrowing from evolutionary theory, we present arguments regarding the differential survival via buffering mechanisms and their target age-related disease genes in searching for aging and longevity genes. Using more than 1,200 subjects between the sixth and eleventh decades of life (at least 140 subjects in each group), we corroborate our hypotheses experimentally. We study 66 common allelic site polymorphism in 36 candidate genes on the basis of their phenotype. Among them we have identified a candidate-buffering mechanism and its candidate age-related disease gene target. Previously, the beneficial effect of an advantageous cholesteryl ester transfer protein (CETP-VV) genotype on lipoprotein particle size in association with decreased metabolic and cardiovascular diseases, as well as with better cognitive function, have been demonstrated. We report an additional advantageous effect of the CETP-VV (favorable) genotype in neutralizing the deleterious effects of the lipoprotein(a) (LPA) gene. Finally, using literature-based interaction discovery methods, we use the set of longevity genes, buffering genes, and their age-related target disease genes to construct the underlying subnetwork of interacting genes that is expected to be responsible for longevity. Genome wide, high-throughput hypothesis-free analyses are currently being utilized to elucidate unknown genetic pathways in many model organisms, linking observed phenotypes to their underlying genetic mechanisms. The longevity phenotype and its genetic mechanisms, such as our buffering hypothesis, are similar; thus, the experimental corroboration of our hypothesis provides a proof of concept for the utility of high-throughput methods for elucidating such mechanisms. It also provides a framework for developing strategies to prevent some age-related diseases by intervention at the appropriate level.

Genetic Association Mapping via Evolution-Based Clustering of Haplotypes

Ioanna Tachmazidou — 2007-08-02T15:30:41-00:00

PLoS Genetics, Vol. 3, No. 7. (1 July 2007), e111.

Multilocus analysis of single nucleotide polymorphism haplotypes is a promising approach to dissecting the genetic basis of complex diseases. We propose a coalescent-based model for association mapping that potentially increases the power to detect disease-susceptibility variants in genetic association studies. The approach uses Bayesian partition modelling to cluster haplotypes with similar disease risks by exploiting evolutionary information. We focus on candidate gene regions with densely spaced markers and model chromosomal segments in high linkage disequilibrium therein assuming a perfect phylogeny. To make this assumption more realistic, we split the chromosomal region of interest into sub-regions or windows of high linkage disequilibrium. The haplotype space is then partitioned into disjoint clusters, within which the phenotype–haplotype association is assumed to be the same. For example, in case-control studies, we expect chromosomal segments bearing the causal variant on a common ancestral background to be more frequent among cases than controls, giving rise to two separate haplotype clusters. The novelty of our approach arises from the fact that the distance used for clustering haplotypes has an evolutionary interpretation, as haplotypes are clustered according to the time to their most recent common ancestor. Our approach is fully Bayesian and we develop a Markov Chain Monte Carlo algorithm to sample efficiently over the space of possible partitions. We compare the proposed approach to both single-marker analyses and recently proposed multi-marker methods and show that the Bayesian partition modelling performs similarly in localizing the causal allele while yielding lower false-positive rates. Also, the method is computationally quicker than other multi-marker approaches. We present an application to real genotype data from the CYP2D6 gene region, which has a confirmed role in drug metabolism, where we succeed in mapping the location of the susceptibility variant within a small error.

Exploring genetic interactions and networks with yeast

Charles Boone — 2007-05-19T03:15:41-00:00

Nature Reviews Genetics, Vol. 8, No. 6., pp. 437-449.

The evolution of genetic networks by non-adaptive processes

Michael Lynch — 2007-09-19T03:51:54-00:00

Nature Reviews Genetics, Vol. 8, No. 10., pp. 803-813.

From E-MAPs to module maps: dissecting quantitative genetic interactions using physical interactions

Igor Ulitsky — 2008-07-22T05:55:26-00:00

Mol Syst Biol, Vol. 4 (15 July 2008)

Genetic reconstruction of a functional transcriptional regulatory network.

Zhanzhi Hu — 2007-04-11T06:25:05-00:00

Nat Genet (8 April 2007)

Although global analyses of transcription factor binding provide one view of potential transcriptional regulatory networks, regulation also occurs at levels distinct from transcription factor binding. Here, we use a genetic approach to identify targets of transcription factors in yeast and reconstruct a functional regulatory network. First, we profiled transcriptional responses in S. cerevisiae strains with individual deletions of 263 transcription factors. Then we used directed-weighted graph modeling and regulatory epistasis analysis to identify indirect regulatory relationships between these transcription factors, and from this we reconstructed a functional transcriptional regulatory network. The enrichment of promoter motifs and Gene Ontology annotations provide insight into the biological functions of the transcription factors.

New models of collaboration in genome-wide association studies: the Genetic Association Information Network

2007-09-05T00:52:38-00:00

Nat Genet, Vol. 39, No. 9. (2007), pp. 1045-1051.

High-throughput genetic interaction mapping in the fission yeast Schizosaccharomyces pombe

Assen Roguev — 2007-09-29T16:55:21-00:00

Nature Methods, Vol. 4, No. 10. (23 September 2007), pp. 861-866.

Functional dissection of protein complexes involved in yeast chromosome biology using a genetic interaction map

Sean Collins — 2007-02-22T10:11:12-00:00

Nature (21 February 2007)

The genetic basis of a plant insect coevolutionary key innovation

Christopher Wheat — 2007-12-12T07:49:23-00:00

Proceedings of the National Academy of Sciences (11 December 2007), 0706229104.

Ehrlich and Raven formally introduced the concept of stepwise coevolution using butterfly and angiosperm interactions in an attempt to account for the impressive biological diversity of these groups. However, many biologists currently envision butterflies evolving 50 to 30 million years (Myr) after the major angiosperm radiation and thus reject coevolutionary origins of butterfly biodiversity. The unresolved central tenet of Ehrlich and Raven's theory is that evolution of plant chemical defenses is followed closely by biochemical adaptation in insect herbivores, and that newly evolved detoxification mechanisms result in adaptive radiation of herbivore lineages. Using one of their original butterfly-host plant systems, the Pieridae, we identify a pierid glucosinolate detoxification mechanism, nitrile-specifier protein (NSP), as a key innovation. Larval NSP activity matches the distribution of glucosinolate in their host plants. Moreover, by using five different temporal estimates, NSP seems to have evolved shortly after the evolution of the host plant group (Brassicales) (approx10 Myr). An adaptive radiation of these glucosinolate-feeding Pierinae followed, resulting in significantly elevated species numbers compared with related clades. Mechanistic understanding in its proper historical context documents more ancient and dynamic plantinsect interactions than previously envisioned. Moreover, these mechanistic insights provide the tools for detailed molecular studies of coevolution from both the plant and insect perspectives. 10.1073/pnas.0706229104

Preferential protection of protein interaction network hubs in yeast: Evolved functionality of genetic redundancy

Ran Kafri — 2008-01-24T08:26:01-00:00

Proceedings of the National Academy of Sciences (23 January 2008), 0711043105.

The widely observed dispensability of duplicate genes is typically interpreted to suggest that a proportion of the duplicate pairs are at least partially redundant in their functions, thus allowing for compensatory affects. However, because redundancy is expected to be evolutionarily short lived, there is currently debate on both the proportion of redundant duplicates and their functional importance. Here, we examined these compensatory interactions by relying on a genome wide data analysis, followed by experiments and literature mining in yeast. Our data, thus, strongly suggest that compensated duplicates are not randomly distributed within the protein interaction network but are rather strategically allocated to the most highly connected proteins. This design is appealing because it suggests that many of the potentially vulnerable nodes that would otherwise be highly sensitive to mutations are often protected by redundancy. Furthermore, divergence analyses show that this association between redundancy and protein connectivity becomes even more significant among the ancient duplicates, suggesting that these functional overlaps have undergone purifying selection. Our results suggest an intriguing conclusion although redundancy is typically transient on evolutionary time scales, it tends to be preserved among some of the central proteins in the cellular interaction network. 10.1073/pnas.0711043105

Which evolutionary processes influence natural genetic variation for phenotypic traits?

Thomas Mitchell-Olds — 2007-10-18T12:55:35-00:00

Nat Rev Genet, Vol. 8, No. 11. (November 2007), pp. 845-856.

Conformation selectivity in the binding of diazepam and analogues to alpha1-acid glycoprotein.

I Fitos — 2008-03-01T00:36:07-00:00

Bioorg Med Chem, Vol. 15, No. 14. (15 July 2007), pp. 4857-4862.

Diazepam, a 1,4-benzodiazepine lacking chiral centre, exists in an equimolar mixture of two chiral conformers. Induced circular dichroism spectra for the binding of diazepam and its 3,3-dimethyl substituted analogues to alpha1-acid glycoprotein (AGP) revealed that opposite to human serum albumin, AGP preferably binds the P-conformers. Accordingly, slightly favoured binding of (R)-enantiomers of 3-alkyl derivatives having P-conformation was found. In case of 3-acyloxy derivatives, however, AGP preferably binds the (S)-enantiomers. Studies with the separated genetic variants of AGP proved similar binding affinities, but markedly different conformation selectivities. For diazepam bound by the F1-S variant, a P/M selectivity of about 2 could be estimated.

Assessment of the genetic diversity and phylogenetic relationships of a temperate bamboo collection by using transferred EST-SSR markers

NA Barkley — 2005-08-11T20:51:20-00:00

Genome, Vol. 48, No. 4. (1 August 2005), pp. 731-737.

Composite Module Analyst: identification of transcription factor binding site combinations using genetic algorithm.

T Waleev — 2008-04-29T07:09:53-00:00

Nucleic acids research, Vol. 34, No. Web Server issue. (1 July 2006)

Composite Module Analyst (CMA) is a novel software tool aiming to identify promoter-enhancer models based on the composition of transcription factor (TF) binding sites and their pairs. CMA is closely interconnected with the TRANSFAC database. In particular, CMA uses the positional weight matrix (PWM) library collected in TRANSFAC and therefore provides the possibility to search for a large variety of different TF binding sites. We model the structure of the long gene regulatory regions by a Boolean function that joins several local modules, each consisting of co-localized TF binding sites. Having as an input a set of co-regulated genes, CMA builds the promoter model and optimizes the parameters of the model automatically by applying a genetic-regression algorithm. We use a multicomponent fitness function of the algorithm which includes several statistical criteria in a weighted linear function. We show examples of successful application of CMA to a microarray data on transcription profiling of TNF-alpha stimulated primary human endothelial cells. The CMA web server is freely accessible at http://www.gene-regulation.com/pub/programs/cma/CMA.html. An advanced version of CMA is also a part of the commercial system ExPlaintrade mark (www.biobase.de) designed for causal analysis of gene expression data.

Composite Module Analyst: a fitness-based tool for identification of transcription factor binding site combinations

A Kel — 2006-05-09T02:31:25-00:00

Bioinformatics, Vol. 22, No. 10. (15 May 2006), pp. 1190-1197.

GAME: detecting cis-regulatory elements using a genetic algorithm

Wei — 2006-07-02T09:51:29-00:00

Bioinformatics, Vol. 22, No. 13. (1 July 2006), pp. 1577-1584.

Motif discovery in upstream sequences of coordinately expressed genes

M Stine — 2008-01-15T03:28:52-00:00

Evolutionary Computation, 2003. CEC '03. The 2003 Congress on, Vol. 3 (2003), pp. 1596-1603 Vol.3.

The paper presents a genetic mining approach to discover highly conserved motifs amongst upstream sequences of co-regulated genes. These motifs represent putative cis-regulatory elements that could play an important role in the co-ordinated expression of these genes. A structured genetic algorithm (St-GA) was used to evolve candidate motifs of variable length. Fitness values were assigned as a function of high scoring alignments performed with NCBI BLAST. The St-GA performed favorable with respect to existing methods on simple (l,k) insertion problems, but was unable to overcome the (l,4) insertion problem that has proved elusive to other methods. Deterministic crowding was added to the St-GA to help cope with the multimodal nature of real-world genomic data. The genetic search was performed on a set of genes selected based on their expression values as highly predictive of a subtype of pediatric ALL. Four high scoring motifs were obtained that successfully matched subsequences of cis-elements found in the TRANSFAC database. Results demonstrated that the St-GA approach to motif finding has the potential to be a competitive method for this type of problem.

Identification of weak motifs in multiple biological sequences using genetic algorithm

Topon Paul — 2008-01-15T03:25:44-00:00

(2006), pp. 271-278.

FMGA: finding motifs by genetic algorithm

FFM Liu — 2008-01-15T03:23:54-00:00

Bioinformatics and Bioengineering, 2004. BIBE 2004. Proceedings. Fourth IEEE Symposium on (2004), pp. 459-466.

In the era of post-genomics, almost all the genes have been sequenced and enormous amounts of data have been generated. Hence, to mine useful information from these data is a very important topic. In this paper we propose a new approach for finding potential motifs in the regions located from the -2000 bp upstream to +1000 bp downstream of transcription start site (TSS). This new approach is developed based on the genetic algorithm (GA). The mutation in the GA is performed by using position weight matrices to reserve the completely conserved positions. The crossover is implemented with special-designed gap penalties to produce the optimal child pattern. We also present a rearrangement method based on position weight matrices to avoid the presence of a very stable local minimum, which may make it quite difficult for the other operators to generate the optimal pattern. Our approach shows superior results by comparing with multiple em for motif elicitation (MEME) and Gibbs sampler, which are two popular algorithms for finding motifs.

Discovery, validation, and genetic dissection of transcription factor binding sites by comparative and functional genomics

Jason Gertz — 2007-10-29T05:27:56-00:00

Genome Res., Vol. 15, No. 8. (1 August 2005), pp. 1145-1152.

Completing the annotation of a genome sequence requires identifying the regulatory sequences that control gene expression. To identify these sequences, we developed an algorithm that searches for short, conserved sequence motifs in the genomes of related species. The method is effective in finding motifs de novo and for refining known regulatory motifs in Saccharomyces cerevisiae. We tested one novel motif prediction of the algorithm and found it to be the binding site of Stp2; it is significantly different from the previously predicted Stp2 binding site. We show that Stp2 physically interacts with this sequence motif, and that stp2 mutations affect the expression of genes associated with the motif. We demonstrate that the Stp2 binding site also interacts genetically with Stp1, a regulator of amino acid permease genes and, with Sfp1, a key regulator of cell growth. These results illuminate an important transcriptional circuit that regulates cell growth through external nutrient uptake. 10.1101/gr.3859605

A GA Approach to the Definition of Regulatory Signals in Genomic Sequences

Giancarlo Mauri — 2008-04-29T03:28:50-00:00

Genetic and Evolutionary Computation – GECCO 2004 (2004), pp. 380-391.

One of the main challenges in modern biology and genome research is to understand the complex mechanisms that regulate gene expression. Being able to tell when, why, and how one or more genes are activated could provide information of inestimable value for the understanding of the mechanisms of life. The wealth of genomic data now available opens new opportunities to researchers. We present how a method based on genetic algorithms has been applied to the characterization of two regulatory signals in DNA sequences, that help the cellular apparatus to locate the beginning of a gene along the genome, and to start its transcription. The signals have been derived from the analysis of a large number of genomic sequences. Comparisons with related work show that our method presents different improvements, both from the computational viewpoint, and in the biological relevance of the results obtained.

MDGA: motif discovery using a genetic algorithm

Dongsheng Che — 2008-01-15T03:19:29-00:00

(2005), pp. 447-452.

TFBS identification by position- and consensus-led genetic algorithm with local filtering

Tak-Ming Chan — 2008-01-15T02:58:51-00:00

(2007), pp. 377-384.

A Clustering Method for Improving the Global Search Capability of Genetic Algorithms

Leizer Schnitman — 2008-04-22T01:00:01-00:00

(2000)

Fitness sharing and niching methods revisited

B Sareni — 2008-04-21T23:40:50-00:00

Evolutionary Computation, IEEE Transactions on, Vol. 2, No. 3. (1998), pp. 97-106.

Interest in multimodal optimization function is expanding rapidly since real-world optimization problems often require the location of multiple optima in the search space. In this context, fitness sharing has been used widely to maintain population diversity and permit the investigation of manly peaks in the feasible domain. This paper reviews various strategies of sharing and proposes new recombination schemes to improve its efficiency. Some empirical results are presented for high and a limited number of fitness function evaluations. Finally, the study compares the sharing method with other niching techniques

A self-adaptive mate selection model for genetic programming

R Fry — 2008-04-21T23:40:05-00:00

Evolutionary Computation, 2005. The 2005 IEEE Congress on, Vol. 3 (2005), pp. 2707-2714 Vol. 3.

This paper documents new extensions to the selection model in genetic programming, designed to be analogous to the more complex behaviour of selection in natural evolution. Specifically, a negative assortative mating scheme is presented in conjunction with a model of psychological evolution, allowing the mating strategy to change throughout the evolutionary process. Results show that self-adaptive mate selection accelerates evolution for several well known test problems.

Effective transcription factor binding site prediction using a combination of optimization, a genetic algorithm and discriminant analysis to capture distant interactions

Victor Levitsky — 2007-12-20T03:31:35-00:00

BMC Bioinformatics, Vol. 8, No. 1. (2007)

BACKGROUND:Reliable transcription factor binding site (TFBS) prediction methods are essential for computer annotation of large amount of genome sequence data. However, current methods to predict TFBSs are hampered by the high false-positive rates that occur when only sequence conservation at the core binding-sites is considered. RESULTS:To improve this situation, we have quantified the performance of several Position Weight Matrix (PWM) algorithms, using exhaustive approaches to find their optimal length and position. We applied these approaches to bio-medically important TFBSs involved in the regulation of cell growth and proliferation as well as in inflammatory, immune, and antiviral responses (NF-kB, ISGF3, IRF1, STAT1), obesity and lipid metabolism (PPAR, SREBP, HNF4), regulation of the steroidogenic (SF-1) and cell cycle (E2F) genes expression. We have also gained extra specificity using a method, entitled SiteGA, which takes into account structural interactions within TFBS core and flanking regions, using a genetic algorithm (GA) with a discriminant function of locally positioned dinucleotide (LPD) frequencies. To ensure a higher confidence in our approach, we applied resampling-jackknife and bootstrap tests for the comparison, it appears that, optimized PWM and SiteGA have shown similar recognition performances. Then we applied SiteGA and optimized PWMs (both separately and together) to sequences in the Eukaryotic Promoter Database (EPD). The resulting SiteGA recognition models can now be used to search sequences for BSs using the web tool, SiteGA. Analysis of dependencies between close and distant LPDs revealed by SiteGA models has shown that the most significant correlations are between close LPDs, and are generally located in the core (footprint) region. A greater number of less significant correlations are mainly between distant LPDs, which spanned both core and flanking regions. When SiteGA and optimized PWM models were applied together, this substantially reduced false positives at least at higher stringencies. CONCLUSIONS:Based on this analysis, SiteGA adds substantial specificity even to optimized PWMs and may be considered for large-scale genome analysis. It adds to the range of techniques available for TFBS prediction, and EPD analysis has led to a list of genes which appear to be regulated by the above TFs.

A genetic algorithm for the detection of new cis-regulatory modules in sets of coregulated genes.

S Aerts — 2004-12-13T16:57:04-00:00

Bioinformatics, Vol. 20, No. 12. (12 August 2004), pp. 1974-1976.

SUMMARY: The implementation of a genetic algorithm is described that provides a fast method of searching for the optimal combination of transcription factor binding sites in a set of regulatory sequences. AVAILABILITY: The algorithm can be used transparently as a web service from within the Toucan software. Toucan can be accessed at http://www.esat.kuleuven.ac.be/~saerts/software/toucan.php. A standalone version of the software is available upon request.

TFBS Identification Based on Genetic Algorithm with Combined Representations and Adaptive Post-processing.

Tak-Ming Chan — 2007-12-11T23:52:52-00:00

Bioinformatics (6 December 2007)

MOTIVATION: Identification of transcription factor binding sites (TFBSs) plays an important role in deciphering the mechanisms of gene regulation. Recently, GAME (Wei and Jensen, 2006), a Genetic Algorithm (GA) based approach with iterative post-processing, has shown superior performance in TFBS identification. However, the basic GA in GAME is not elaborately designed, and may be trapped in local optima in real problems. The feature operators are only applied in the post-processing, but the final performance heavily depends on the GA output. Hence, both effectiveness and efficiency of the overall algorithm can be improved by introducing more advanced representations and novel operators in the GA, as well as designing the post-processing in an adaptive way. RESULTS: We propose a novel framework GALF-P, consisting of Genetic Algorithm with Local Filtering (GALF) and adaptive postprocessing techniques (-P), to achieve both effectiveness and efficiency for TFBS identification. GALF combines the position-led and consensus-led representations used separately in current GAs and employs a novel local filtering operator to get rid of false positives within an individual efficiently during the evolutionary process in the GA. Pre-selection is used to maintain diversity and avoid local optima. Post-processing with adaptive adding and removing is developed to handle general cases with arbitrary numbers of instances per sequence. GALF-P shows superior performance to GAME, MEME, BioProspector and BioOptimizer on synthetic datasets with difficult scenarios and real test datasets. GALF-P is also more robust and reliable when further compared with GAME, the current state-of-thearts approach. AVAILABILITY: http://www.cse.cuhk.edu.hk/~tmchan/GALFP/ CONTACT: tmchan@cse.cuhk.edu.hk Supplementary Material: Available at Bioinformatics online.

Advances in mechanisms of genetic instability related to hereditary neurological diseases.

RD Wells — 2006-02-16T19:48:47-00:00

Nucleic Acids Res, Vol. 33, No. 12. (2005), pp. 3785-3798.

Substantial progress has been realized in the past several years in our understanding of the molecular mechanisms responsible for the expansions and deletions (genetic instabilities) of repeating tri-, tetra- and pentanucleotide repeating sequences associated with a number of hereditary neurological diseases. These instabilities occur by replication, recombination and repair processes, probably acting in concert, due to slippage of the DNA complementary strands relative to each other. The biophysical properties of the folded-back repeating sequence strands play a critical role in these instabilities. Non-B DNA structural elements (hairpins and slipped structures, DNA unwinding elements, tetraplexes, triplexes and sticky DNA) are described. The replication mechanisms are influenced by pausing of the replication fork, orientation of the repeat strands, location of the repeat sequences relative to replication origins and the flap endonuclease. Methyl-directed mismatch repair, nucleotide excision repair, and repair of damage caused by mutagens are discussed. Genetic recombination and double-strand break repair advances in Escherichia coli, yeast and mammalian models are reviewed. Furthermore, the newly discovered capacities of certain triplet repeat sequences to cause gross chromosomal rearrangements are discussed.

Genetic Algorithms for Real Parameter Optimization

Alden Wright — 2007-07-06T14:05:29-00:00

(1991), pp. 205-218.

This paper is concerned with the application of genetic algorithms to optimization problems over several real parameters. It is shown that k-point crossover (for k small relative to the number of parameters) can be viewed as a crossover operation on the vector of parameters plus perturbations of some of the parameters. Mutation can also be considered as a perturbation of some of the parameters. This suggests a genetic algorithm that uses real parameter vectors as chromosomes, real parameters as ...

Clonal and spatial genetic structures of aspen (Populus tremuloides Michx.)

Marie-Claire Namroud — 2005-08-13T02:27:05-00:00

Molecular Ecology, Vol. 14, No. 10. (September 2005), pp. 2969-2980.

Clonal structure and genet-level sex ratios suggest different roles of vegetative and sexual reproduction in the clonal moss Hylocomium splendens

Nils Cronberg — 2006-02-10T01:31:03-00:00

Ecography, Vol. 29, No. 1. (2006), pp. 95-103.

The allozyme haplotype was determined for 157 ramets of the unisexual, perennial, clonal moss Hylocomium splendens within five 10x10 cm plots, which had been the subject of demographic studies over a 5-yr period. In addition, 25 shoots were analyzed from outside the plots and from four neighbouring patches. Only four haplotypes were encountered within the plots; one female type occurred in all plots and one male type in four plots, whereas two male haplotypes occurred in only one plot. Genets grew intermingled in all but one plot. The sex ratio within the five plots was female-biased at the ramet level (male:female=1:2.6), but male-biased at the genet level (3:1). Sporophytes were produced abundantly during the study period, but no signs of recruitment from spores were observed in the plots. Nine additional genets were encountered in neighbouring patches but from only one patch each. Four (44%) of these could potentially have been derived from spores generated within the plots. Our results suggest that each patch of H. splendens is colonized by a small number of genets, whereas different patches have different sets of genets, i.e. clonal diversity is determined by vegetative reproduction at within-patch scales and structured by sexual processes at among-patch scales.

Local genetic structure in a clonal dioecious angiosperm

MV Ruggiero — 2005-03-18T04:59:54-00:00

Molecular Ecology, Vol. 14, No. 4. (April 2005), pp. 957-967.

Psychological and Behavioural Impact of Genetic Testing Smokers for Lung Cancer Risk: A Phase II Exploratory Trial

Saskia Sanderson — 2008-04-17T15:49:33-00:00

J Health Psychol, Vol. 13, No. 4. (1 May 2008), pp. 481-494.

The behavioural and psychological impact of genetic testing for lung cancer susceptibility was examined among smokers (N = 61) who were randomly allocated to a GSTM1 genetic testing group (with GSTM1-missing or GSTM1-present result) or no-test control group. The GSTM1-missing (higher risk) group reported greater motivation to quit smoking, and both genetic testing groups reported lower depression than the control group at one-week follow-up (p < .05 for all). Differences were not significant at two months follow-up. This study indicates the feasibility of much-needed research into the risks and benefits for individuals of emerging lifestyle-related genetic susceptibility tests. 10.1177/1359105308088519

Less is More - Genetic Optimisation of Nearest Neighbour Classifiers

V Ramos — 2005-11-24T18:18:48-00:00

(1998)

The present paper deals with optimisation of Nearest Neighbour rule Classifiers via Genetic Algorithms. The methodology consists on implement a Genetic Algorithm capable of search the input feature space used by the NNR classifier. Results show that is adequate to perform feature reduction and simultaneous improve the Recognition Rate. Some practical examples prove that is possible to Recognise Portuguese Granites in 100%, with only 3 morphological features (from an original set of 117...

Biology of Wolbachia

John Werren — 2008-03-13T13:27:47-00:00

Annual Review of Entomology, Vol. 42, No. 1. (1997), pp. 587-609.

Abstract Wolbachia are a common and widespread group of bacteria found in reproductive tissues of arthropods. These bacteria are transmitted through the cytoplasm of eggs and have evolved various mechanisms for manipulating reproduction of their hosts, including induction of reproductive incompatibility, pathenogenesis, and feminization. Wolbachia are also transmitted horizontally between arthropod species. Significant recent advances have been made in the study of these interesting microorganisms. In this paper, Wolbachia biology is reviewed, including their phylogeny and distribution, mechanisms of action, population biology and evolution, and biological control implications. Potential directions for future research are also discussed.

Phylogeny of the arthropod endosymbiont Wolbachia based on the wsp gene

MMM van Meer — 2008-03-13T13:23:12-00:00

Insect Molecular Biology, Vol. 8, No. 3. (1999), pp. 399-408.

Bacteria of the genus Wolbachia (Rickettsiae) are widespread in arthropods and can induce cytoplasmic incompatibility (CI), thelytoky (T) or feminization (F) in their host. Recent research on the wsp gene of mainly CI inducing Wolbachia has shown that this gene evolves at a much faster rate than previously sequenced genes such as 16S or ftsZ. As a result this gene appears to be very useful in subdividing the Wolbachia and twelve groups have been distinguished to date. Here we extend the Wolbachia wsp data set with fifteen T-Wolbachia, one F-Wolbachia and three other CI-Wolbachia strains. The results showed: (i) the addition of seven groups; (ii) no relation between host phenotype and Wolbachia phylogenetic position; and (iii) possible horizontal Wolbachia transfer between the moth Ephestia kuehniella and its parasitoid Trichogramma spp.

Microorganisms associated with chromosome destruction and reproductive isolation between two insect species

Johannes Breeuwer — 2008-03-13T13:20:55-00:00

Nature, Vol. 346, No. 6284. (1990), pp. 558-560.

Cloning and Characterization of a Gene Encoding the Major Surface Protein of the Bacterial Endosymbiont Wolbachia pipientis

Henk Braig — 2007-08-23T00:34:12-00:00

J. Bacteriol., Vol. 180, No. 9. (1 May 1998), pp. 2373-2378.

The maternally inherited intracellular symbiont Wolbachia pipientis is well known for inducing a variety of reproductive abnormalities in the diverse arthropod hosts it infects. It has been implicated in causing cytoplasmic incompatibility, parthenogenesis, and the feminization of genetic males in different hosts. The molecular mechanisms by which this fastidious intracellular bacterium causes these reproductive and developmental abnormalities have not yet been determined. In this paper, we report on (i) the purification of one of the most abundantly expressed Wolbachia proteins from infected Drosophila eggs and (ii) the subsequent cloning and characterization of the gene (wsp) that encodes it. The functionality of the wsp promoter region was also successfully tested in Escherichia coli. Comparison of sequences of this gene from different strains of Wolbachia revealed a high level of variability. This sequence variation correlated with the ability of certain Wolbachia strains to induce or rescue the cytoplasmic incompatibility phenotype in infected insects. As such, this gene will be a very useful tool for Wolbachia strain typing and phylogenetic analysis, as well as understanding the molecular basis of the interaction of Wolbachia with its host.

Evaluation of Genetic Diversity in Rice Subspecies Using Microsatellite Markers

Junjian Ni — 2008-03-29T11:30:14-00:00

Crop Sci, Vol. 42, No. 2. (1 March 2002), pp. 601-607.

Molecular markers are useful tools for evaluating genetic diversity and determining cultivar identity. The purpose of this study was to evaluate the genetic diversity within a diverse collection of rice (Oryza sativa L.) accessions, and to determine differences in the patterns of diversity within the two rice subspecies indica and japonica. Thirty-eight rice cultivars of particular interest to U.S. breeding programs and two wild species accessions (O. rufipogon Griffithand O. nivara Sharma et Shastry) were evaluated by means of 111 microsatellite markers distributed over the whole rice genome. A total of 753 alleles were detected, and the number of alleles per marker ranged from 1 to 17, with an average of 6.8. A positive correlation was found between the number of alleles per locus and the maximum number of repeats within a microsatellite marker. Compared to indica cultivars, the japonica group showed significantly higher genetic diversity on chromosomes 6 and 7, and considerably lower diversity on chromosome 2. All rice cultivars and lines could be uniquely distinguished, and the resulting groups corresponded exactly to the indica and japonica subspecies, with japonica divided into temperate and tropical types. With stepwise discrimination, two subsets of approximately 30 markers were identified that produced genetic distance matrices and dendrograms that were the same as those produced by means of all 111 markers. The results suggested that a relatively small number of microsatellite markers could be used for the estimation of genetic diversity and the identification of rice cultivars.

A genetic algorithm tutorial

Darrell Whitley — 2007-07-11T14:44:39-00:00

Statistics and Computing, Vol. 4, No. 2. (1 June 1994), pp. 65-85.

This tutorial covers the canonical genetic algorithm as well as more experimental forms of genetic algorithms, including parallel island models and parallel cellular genetic algorithms. The tutorial also illustrates genetic search by hyperplane sampling. The theoretical foundations of genetic algorithms are reviewed, include the schema theorem as well as recently developed exact models of the canonical genetic algorithm.

In silico protein recombination: enhancing template and sequence alignment selection for comparative protein modelling.

B Contreras-Moreira — 2005-05-21T14:00:57-00:00

J Mol Biol, Vol. 328, No. 3. (2 May 2003), pp. 593-608.

Comparative modelling of proteins is a predictive technique to build an atomic model for a given amino acid sequence, on the basis of the structures of other proteins (templates) that have been determined experimentally. Critical problems arise in this procedure: selecting the correct templates, aligning the query sequence with them and building the non-conserved surface loops. In this work, we apply a genetic algorithm, with crossover and mutation, as a new tool to overcome the first two. In silico protein recombination proves to be an effective way to exploit the variability of templates and sequence alignments to produce populations of optimized models by artificial selection. Despite some limitations, the procedure is shown to be robust to alignment errors, while simplifying the task of selecting templates, making it a good candidate for automatic building of reliable protein models.

Novel use of a genetic algorithm for protein structure prediction: searching template and sequence alignment space.

B Contreras-Moreira — 2005-05-21T13:59:43-00:00

Proteins, Vol. 53 Suppl 6 (2003), pp. 424-429.

A novel genetic algorithm was applied to all CASP5 targets. The algorithm simultaneously searches template and alignment space. Results show that the current implementation of the method is perhaps most useful in recognizing and refining remote homology targets. This new method is briefly described and results are analyzed. Strengths and weaknesses of the current implementation of the algorithm are discussed.

Genetic Programming: On the Programming of Computers by Means of Natural Selection (Complex Adaptive Systems)

John Koza — 2005-04-23T08:52:02-00:00

(11 December 1992)

Predicting non-coding RNA genes in Escherichia coli with boosted genetic programming.

P Saetrom — 2005-06-25T12:03:29-00:00

Nucleic Acids Res, Vol. 33, No. 10. (2005), pp. 3263-3270.

Several methods exist for predicting non-coding RNA (ncRNA) genes in Escherichia coli (E.coli). In addition to about sixty known ncRNA genes excluding tRNAs and rRNAs, various methods have predicted more than thousand ncRNA genes, but only 95 of these candidates were confirmed by more than one study. Here, we introduce a new method that uses automatic discovery of sequence patterns to predict ncRNA genes. The method predicts 135 novel candidates. In addition, the method predicts 152 genes that overlap with predictions in the literature. We test sixteen predictions experimentally, and show that twelve of these are actual ncRNA transcripts. Six of the twelve verified candidates were novel predictions. The relatively high confirmation rate indicates that many of the untested novel predictions are also ncRNAs, and we therefore speculate that E.coli contains more ncRNA genes than previously estimated.

Molecular Epidemiology of Recent North American H5 and H7 Avian Influenza Viruses

M García — 2008-07-09T21:49:46-00:00

Avian Diseases, Vol. 47 (2003), pp. 95-104.

The phylogenetic relationship of the hemagglutinin (HA) and non-structural (NS) genes from avian influenza (AI) H5 subtype viruses of North American origin is presented. Analysis of the HA sequences of several uncharacterized isolates from migratory waterfowl and turkeys, provided clear evidence of significant sequence variation and existence of multiple virus clades or sublineages, maintained in migratory waterfowl. Phylogenetic analysis of the NS gene sequences further demonstrated multiple sublineages and reassortment of two NS genes in wild duck populations. Based on the HA1 gene sequences, at least four clades exist with waterfowl isolates included in three of the four groups. The fastest evolving su-blineage of the North America viruses is composed of recent isolates from the outbreak of AI in Central Mexico. This group of viruses which replicated unabated in chickens for at least 16 months exhibited the highest mutation rate of the four H5 sublineages. The phylogenetic relationship of the hemagglutinin (HA) genes of fourteen H7 isolates from Europe, Australia, South Africa, Hong Kong, and twelve United State (US) isolates were examined. Analysis of these twelve US isolates allowed the identification of a new clade of H7 viruses that further diverge from the prototype Turkey/Oregon/71 virus.