Fractional dynamics of genetic algorithms using hexagonal space tessellation

The paper formulates a genetic algorithm that evolves two types of objects in a plane. The fitness function promotes a relationship between the objects that is optimal when some kind of interface between them occurs. Furthermore, the algorithm adopts an hexagonal tessellation of the two-dimensional space for promoting an efficient method of the neighbour modelling. The genetic algorithm produces special patterns with resemblances to those revealed in percolation phenomena or in the symbiosis found in lichens. Besides the analysis of the spacial layout, a modelling of the time evolution is performed by adopting a distance measure and the modelling in the Fourier domain in the perspective of fractional calculus. The results reveal a consistent, and easy to interpret, set of model parameters for distinct operating conditions.

Optimal location of supports in beam structures using genetic algorithms

Real structures can be thought as an assembly of components, as for instances plates, shells and beams. This later type of component is very commonly found in structures like frames which can involve a significant degree of complexity or as a reinforcement element of plates or shells. To obtain the desired mechanical behavior of these components or to improve their operating conditions when rehabilitating structures, one of the eventual parameters to consider for that purpose, when possible, is the location of the supports. In the present work, a beam-type structure is considered, and for a set of cases concerning different number and types of supports, as well as different load cases, the authors optimize the location of the supports in order to obtain minimum values of the maximum transverse deflection. The optimization processes are carried out using genetic algorithms. The results obtained, clearly show a good performance of the approach proposed. © 2014 IEEE.

Crossing genetic and swarm intelligence algorithms to generate logic circuits

Genetic Algorithms (GAs) are adaptive heuristic search algorithm based on the evolutionary ideas of natural selection and genetic. The basic concept of GAs is designed to simulate processes in natural system necessary for evolution, specifically those that follow the principles first laid down by Charles Darwin of survival of the fittest. On the other hand, Particle swarm optimization (PSO) is a population based stochastic optimization technique inspired by social behavior of bird flocking or fish schooling. PSO shares many similarities with evolutionary computation techniques such as GAs. The system is initialized with a population of random solutions and searches for optima by updating generations. However, unlike GA, PSO has no evolution operators such as crossover and mutation. In PSO, the potential solutions, called particles, fly through the problem space by following the current optimum particles. PSO is attractive because there are few parameters to adjust. This paper presents hybridization between a GA algorithm and a PSO algorithm (crossing the two algorithms). The resulting algorithm is applied to the synthesis of combinational logic circuits. With this combination is possible to take advantage of the best features of each particular algorithm.

Optimal fuzzy PID control tuned with genetic algorithms

Fuzzy logic controllers (FLC) are intelligent systems, based on heuristic knowledge, that have been largely applied in numerous areas of everyday life. They can be used to describe a linear or nonlinear system and are suitable when a real system is not known or too difficult to find their model. FLC provide a formal methodology for representing, manipulating and implementing a human heuristic knowledge on how to control a system. These controllers can be seen as artificial decision makers that operate in a closed-loop system, in real time. The main aim of this work was to develop a single optimal fuzzy controller, easily adaptable to a wide range of systems – simple to complex, linear to nonlinear – and able to control all these systems. Due to their efficiency in searching and finding optimal solution for high complexity problems, GAs were used to perform the FLC tuning by finding the best parameters to obtain the best responses. The work was performed using the MATLAB/SIMULINK software. This is a very useful tool that provides an easy way to test and analyse the FLC, the PID and the GAs in the same environment. Therefore, it was proposed a Fuzzy PID controller (FL-PID) type namely, the Fuzzy PD+I. For that, the controller was compared with the classical PID controller tuned with, the heuristic Ziegler-Nichols tuning method, the optimal Zhuang-Atherton tuning method and the GA method itself. The IAE, ISE, ITAE and ITSE criteria, used as the GA fitness functions, were applied to compare the controllers performance used in this work. Overall, and for most systems, the FL-PID results tuned with GAs were very satisfactory. Moreover, in some cases the results were substantially better than for the other PID controllers. The best system responses were obtained with the IAE and ITAE criteria used to tune the FL-PID and PID controllers.

Cerebral vasculopathy in children with sickle cell disease A study of genetic modulators of the disease

Sickle cell disease (SCD) is a genetic disorder with recessive transmission, caused by the mutation HBB:c.20A>T. It originates hemoglobin S that forms polymers inside the erythrocyte, upon deoxygenation, deforming it and ultimately leading to premature hemolysis. The disease presents with high heterogeneity of clinical manifestations, the most devastating of which, ischemic stroke, occurs in 11% of patients until 20 years of age. In this study, we tried to identify genetic modifiers of risk and episodes of stroke by studying 66 children with SCD, grouped according to the degree of cerebral vasculopathy (Stroke, Risk and Control). Association studies were performed between the three phenotypic groups and hematological and biochemical parameters of patients, as well as with 23 polymorphic regions in genes related to vascular cell adhesion (VCAM-1, THBS-1 and CD36), vascular tonus (NOS3 and ET-1) and inflammation (TNF-α and HMOX-1). Relevant data was collected from patient’s medical records. Known genetic modulators of SCD (beta-globin cluster haplotype and HBA and BCL11A genotypes) and putative genetic modifiers of cerebral vasculopathy were characterized. Differences in their distribution among groups were assessed. VCAM-1 rs1409419 allele C and NOS3 rs207044 allele C were associated to stroke events, while VCAM-1 rs1409419 allele T was found to be protective. Alleles 4a and 4b of NOS3 27 bp VNTR appeared to be respectively associated to stroke risk and protection. HMOX-1 longer STRs seemed to predispose to stroke. Higher hemoglobin F levels were found in Control group, as a result of Senegal haplotype or of BCL11A rs11886868 allele T, and higher lactate dehydrogenase levels, marker of hemolysis, were found in Risk group. Molecular mechanisms underlying the modifier functions of the relevant genetic variants are discussed.

Population genetic structure of brown crab (Cancer pagurus) in Irish waters

The brown crab (Cancer pagurus) fishery in Ireland is one of the most important financially and socio-economically, with the species worth approximately €15m per year in the first half of the decade. Only mackerel (Scomber scombrus) and Dublin Bay prawn (Nephrops norvegicus) are of greater value. Despite this, very little research has been conducted to describe the stock structure of brown crab on a national scale. In this study a country-wide assessment of genetic population structure was carried out. Sampling was conducted from commercial fishing boats from 11/06 to 04/08 at seven sample sites representing the central Irish brown crab fisheries, with one sample site from the UK also included in the study. Six microsatellite markers, specifically developed for brown crab, were used to assess genetic diversity and estimate population differentiation parameters. Significant genetic structuring was found using F-statistics (Fst = 0.007) and exact tests, but not with Bayesian methods. Samples from the UK and Wexford were found to be genetically distinct from all other populations. Three northern populations from Malm Head and Stanton Bank were genetically similar with Fst estimates suggesting connectivity between them. Also, Stanton Bank, again on the basis of Fst estimates, appeared to be connected to populations down the west coast of Ireland, as far south as Kerry. Two Galway samples, one inside and one outside of Galway Bay, were genetically differentiated despite their close geographic proximity. It is hypothesised that a persistent northerly summer current could transport pelagic larvae from populations along the southwest and west coasts of Ireland towards Stanton Bank in the North, resulting in the apparent connectivity observed in this study.

Restriction site-associated DNA sequencing, genotyping error estimation and de novo assembly optimization for population genetic inference.

Restriction site-associated DNA sequencing (RADseq) provides researchers with the ability to record genetic polymorphism across thousands of loci for nonmodel organisms, potentially revolutionizing the field of molecular ecology. However, as with other genotyping methods, RADseq is prone to a number of sources of error that may have consequential effects for population genetic inferences, and these have received only limited attention in terms of the estimation and reporting of genotyping error rates. Here we use individual sample replicates, under the expectation of identical genotypes, to quantify genotyping error in the absence of a reference genome. We then use sample replicates to (i) optimize de novo assembly parameters within the program Stacks, by minimizing error and maximizing the retrieval of informative loci; and (ii) quantify error rates for loci, alleles and single-nucleotide polymorphisms. As an empirical example, we use a double-digest RAD data set of a nonmodel plant species, Berberis alpina, collected from high-altitude mountains in Mexico.

Cadmium hyperaccumulation and genetic differentiation of Thlaspi caerulescens populations

Although the knowledge on heavy metal hyperaccumulation mechanisms is increasing, the genetic basis of cadmium (Cd) hyperaccurnulation remains to be elucidated. Thlaspi caerulescens is an attractive model since Cd accumulation polymorphism observed in this species suggests genetic differences between populations with low versus high Cd hyperaccumulation capacities. In our study, a methodology is proposed to analyse at a regional scale the genetic differentiation of T. caerulescens natural populations in relation to Cd hyperaccumulation capacity while controlling for different environmental, soil, plant parameters and geographic origins of populations. Twenty-two populations were characterised with AFLP markers and cpDNA polymorphism. Over all loci, a partial Mantel test showed no significant genetic structure with regard to the Cd hyperaccumulation capacity. Nevertheless, when comparing the marker variation to a neutral model, seven AFLP fragments (9% of markers) were identified as presenting particularly high genetic differentiation between populations with low and high Cd hyperaccurnulation capacity. Using simulations, the number of outlier loci was showed to be significantly higher than expected at random. These loci presented a genetic structure linked to Cd hyperaccumulation capacity independently of the geography, environment, soil parameters and Zn, Pb, Fe and Cu concentrations in plants. Using a canonical correspondence analysis, we identified three of them as particularly related to the Cd hyperaccumutation capacity. This study demonstrates that populations with low and high hyperaccurnulation capacities can be significantly distinguished based on molecular data. Further investigations with candidate genes and mapped markers may allow identification and characterization of genomic regions linked to factors involved in Cd hyperaccumulation.

On the transition of genetic differentiation from isolation to panmixia: What we can learn from GST and D.

Population genetic differentiation characterizes the repartition of alleles among populations. It is commonly thought that genetic differentiation measures, such as GST and D, should be near zero when allele frequencies are close to their expected value in panmictic populations, and close to one when they are close to their expected value in isolated populations. To analyse those properties, we first derive analytically a reference function f of known parameters that describes how important features of genetic differentiation (e.g. gene diversity, proportion of private alleles, frequency of the most common allele) are close to their expected panmictic and isolation value. We find that the behaviour of function f differs according to three distinct mutation regimes defined by the scaled mutation rate and the number of populations. Then, we compare GST and D to f, and demonstrate that their signal of differentiation strongly depends on the mutation regime. In particular, we show that D captures well the variations of genetic diversity when mutation is weak, otherwise it overestimates it when panmixia is not met. GST detects population differentiation when mutation is intermediate but has a low sensitivity to the variations of genetic diversity when mutation is weak. When mutation is strong the domain of sensitivity of both measures are altered. Finally, we also point out the importance of the number of populations on genetic differentiation measures, and provide recommendations for the use of GST and D.

Restriction site-associated DNA sequencing, genotyping error estimation and de novo assembly optimization for population genetic inference.

Restriction site-associated DNA sequencing (RADseq) provides researchers with the ability to record genetic polymorphism across thousands of loci for nonmodel organisms, potentially revolutionizing the field of molecular ecology. However, as with other genotyping methods, RADseq is prone to a number of sources of error that may have consequential effects for population genetic inferences, and these have received only limited attention in terms of the estimation and reporting of genotyping error rates. Here we use individual sample replicates, under the expectation of identical genotypes, to quantify genotyping error in the absence of a reference genome. We then use sample replicates to (i) optimize de novo assembly parameters within the program Stacks, by minimizing error and maximizing the retrieval of informative loci; and (ii) quantify error rates for loci, alleles and single-nucleotide polymorphisms. As an empirical example, we use a double-digest RAD data set of a nonmodel plant species, Berberis alpina, collected from high-altitude mountains in Mexico.

Population genetic structure and demography analysis in palinurus elephas populations from atlantic and mediterranean waters

Report for the scientific sojourn at the University of Reading, United Kingdom, from January until May 2008. The main objectives have been firstly to infer population structure and parameters in demographic models using a total of 13 microsatellite loci for genotyping approximately 30 individuals per population in 10 Palinurus elephas populations both from Mediterranean and Atlantic waters. Secondly, developing statistical methods to identify discrepant loci, possibly under selection and implement those methods using the R software environment. It is important to consider that the calculation of the probability distribution of the demographic and mutational parameters for a full genetic data set is numerically difficult for complex demographic history (Stephens 2003). The Approximate Bayesian Computation (ABC), based on summary statistics to infer posterior distributions of variable parameters without explicit likelihood calculations, can surmount this difficulty. This would allow to gather information on different demographic prior values (i.e. effective population sizes, migration rate, microsatellite mutation rate, mutational processes) and assay the sensitivity of inferences to demographic priors by assuming different priors.

Genetic variability among populations of Lutzomyia (Psathyromyia) shannoni (Dyar 1929) (Diptera: Psychodidae: Phlebotominae) in Colombia

Polyacrylamide gel electrophoresis was used to elucidate genetic variation at 13 isozyme loci among forest populations of Lutzomyia shannoni from three widely separated locations in Colombia: Palambí (Nariño Department), Cimitarra (Santander Department) and Chinácota (Norte de Santander Department). These samples were compared with a laboratory colony originating from the Magdalena Valley in Central Colombia. The mean heterozygosity ranged from 16 to 22%, with 2.1 to 2.6 alleles detected per locus. Nei's genetic distances among populations were low, ranging from 0.011 to 0.049. The estimated number of migrants (Nm=3.8) based on Wright's F-Statistic, F ST, indicated low levels of gene flow among Lu. shannoni forest populations. This low level of migration indicates that the spread of stomatitis virus occurs via infected host, not by infected insect. In the colony sample of 79 individuals, the Gpi locus was homozygotic (0.62/0.62) in all females and heterozygotic (0.62/0.72) in all males. Although this phenomenon is probably a consequence of colonization, it indicates that Gpi is linked to a sex determining locus.

Genetic and environmental components of phenotypic variation in immune response and body size of a colonial bird, Delichon urbica (the house martin).

Directional selection for parasite resistance is often intense in highly social host species. Using a partial cross-fostering experiment we studied environmental and genetic variation in immune response and morphology in a highly colonial bird species, the house martin (Delichon urbica). We manipulated intensity of infestation of house martin nests by the haematophagous parasitic house martin bug Oeciacus hirundinis either by spraying nests with a weak pesticide or by inoculating them with 50 bugs. Parasitism significantly affected tarsus length, T cell response, immunoglobulin and leucocyte concentrations. We found evidence of strong environmental effects on nestling body mass, body condition, wing length and tarsus length, and evidence of significant additive genetic variance for wing length and haematocrit. We found significant environmental variance, but no significant additive genetic variance in immune response parameters such as T cell response to the antigenic phytohemagglutinin, immunoglobulins, and relative and absolute numbers of leucocytes. Environmental variances were generally greater than additive genetic variances, and the low heritabilities of phenotypic traits were mainly a consequence of large environmental variances and small additive genetic variances. Hence, highly social bird species such as the house martin, which are subject to intense selection by parasites, have a limited scope for immediate microevolutionary response to selection because of low heritabilities, but also a limited scope for long-term response to selection because evolvability as indicated by small additive genetic coefficients of variation is weak.

Trypanosoma cruzi: genetic group with peculiar biochemical and biological behavior

Thirty-two Trypanosoma cruzi strains, isolated from chronic chagasic patients in the northwest of the state of Paraná (Brazil), were analyzed using molecular, biochemical and biological characteristics. Genotypic analysis using randomly amplified polymorphic DNA and simple sequence repeat-anchored polymerase chain reaction amplified profiles showed a large, genetically well-correlated group that contained the majority of the strains and a divergent group that included the PR-150 strain. For glycoconjugate composition, the PR-150 strain was different from the other strains considering the absence or presence of specific bands in aqueous or detergent phases. This strain was also totally different from the others in one out of the six parameters related to in vitro and in vivo biological behavior. We highlight the fact that the PR-150 was totally resistant to benznidazole. For the other biological parameters this strain was not totally distinct from the others, but it showed a peculiar behavior.

European collaborative study of early-onset bipolar disorder: Evidence for genetic heterogeneity on 2q14 according to age at onset.

Bipolar disorder has a genetic component, but the mode of inheritance remains unclear. A previous genome scan conducted in 70 European families led to detect eight regions linked to bipolar disease. Here, we present an investigation of whether the phenotypic heterogeneity of the disorder corresponds to genetic heterogeneity in these regions using additional markers and an extended sample of families. The MLS statistic was used for linkage analyses. The predivided sample test and the maximum likelihood binomial methods were used to test genetic homogeneity between early-onset bipolar type I (cut-off of 22 years) and other types of the disorder (later onset of bipolar type I and early-onset bipolar type II), using a total of 138 independent bipolar-affected sib-pairs. Analysis of the extended sample of families supports linkage in four regions (2q14, 3p14, 16p23, and 20p12) of the eight regions of linkage suggested by our previous genome scan. Heterogeneity testing revealed genetic heterogeneity between early and late-onset bipolar type I in the 2q14 region (P = 0.0001). Only the early form of the bipolar disorder but not the late form appeared to be linked to this region. This region may therefore include a genetic factor either specifically involved in the early-onset bipolar type I or only influencing the age at onset (AAO). Our findings illustrate that stratification according to AAO may be valuable for the identification of genetic vulnerability polymorphisms.