Optimizing urban traffic flow using genetic algorithm with petri net analysis as fitness function

This paper describes a new methodology adopted for urban traffic stream optimization. By using Petri net analysis as fitness function of a Genetic Algorithm, an entire urban road network is controlled in real time. With the advent of new technologies that have been published, particularly focusing on communications among vehicles and roads infrastructures, we consider that vehicles can provide their positions and their destinations to a central server so that it is able to calculate the best route for one of them. Our tests concentrate on comparisons between the proposed approach and other algorithms that are currently used for the same purpose, being possible to conclude that our algorithm optimizes traffic in a relevant manner.

Genetic gain in the selection by multi-effects index in open-pollinated progenies of Eucalyptus grandis Hill ex Maiden

In Brazil, Eucalyptus grandis Hill ex Maiden is widely used for commercial reforestation, especially for production of pulp, paper and energy. Its genetic variability is being explored in tree improvement programs for over 30 years. The objective of this work was to estimate genetic parameters and compare genetic gains by multi-effects index in a breeding population of E. grandis. Progeny tests were established using open-pollinated seeds from ten provenances ranging from 153 to 160 progenies established in a completely randomized block design in four sites of Sao Paulo State (Anhembi, Avere Itarare e Pratania). At 24 months of age the traits diameter at breast height (DBH), height (ALT) and volume (VOL) were measured. The individual site analyses indicated significant genetic differences among progenies, height genetic variability and the mean progeny heritability (> 0.70). For joint analyses of sites, significant differences in genotype x environmental interaction effects were detected, showing differences of performance of the progenies in different sites. The Itarare site gave high genetic gains, effective size and genetic diversity. The genetic diversity and low effective size are unviable factors; considering that the progeny tests studied should retain adequate levels of genetic variability in order to be transformed in future seedling seed orchards.

Genetic variability and demographic history of Heliothis virescens (Lepidoptera: Noctuidae) populations from Brazil inferred by mtDNA sequences

Intra-and inter-population genetic variability and the demographic history of Heliothis virescens (F.) populations were evaluated by using mtDNA markers (coxI, coxII and nad6) with samples from the major cotton-and soybean-producing regions in Brazil in the growing seasons 2007/08, 2008/09 and 2009/10. AMOVA indicated low and non-significant genetic structure, regardless of geographical scale, growing season or crop, with most of genetic variation occurring within populations. Clustering analyzes also indicated low genetic differentiation. The haplotype network obtained with combined datasets resulted in 35 haplotypes, with 28 exclusive occurrences, four of them sampled only from soybean fields. The minimum spanning network showed star-shaped structures typical of populations that underwent a recent demographic expansion. The recent expansion was supported by other demographic analyzes, such as the Bayesian skyline plot, the unimodal distribution of paired differences among mitochondrial sequences, and negative and significant values of neutrality tests for the Tajima's D and Fu's F-S parameters. In addition, high values of haplotype diversity ((H) over cap) and low values of nucleotide diversity (pi), combined with a high number of low frequency haplotypes and values of theta(pi)<theta(W), suggested a recent demographic expansion of H. virescens populations in Brazil. This demographic event could be responsible for the low genetic structure currently found; however, haplotypes present uniquely at the same geographic regions and from one specific host plant suggest an initial differentiation among H. virescens populations within Brazil.

Genetic Control of Mosquitoes: population suppression strategies

Over the last two decades, morbidity and mortality from malaria and dengue fever among other pathogens are an increasing Public Health problem. The increase in the geographic distribution of vectors is accompanied by the emergence of viruses and diseases in new areas. There are insufficient specific therapeutic drugs available and there are no reliable vaccines for malaria or dengue, although some progress has been achieved, there is still a long way between its development and actual field use. Most mosquito control measures have failed to achieve their goals, mostly because of the mosquito's great reproductive capacity and genomic flexibility. Chemical control is increasingly restricted due to potential human toxicity, mortality in no target organisms, insecticide resistance, and other environmental impacts. Other strategies for mosquito control are desperately needed. The Sterile Insect Technique (SIT) is a species-specific and environmentally benign method for insect population suppression, it is based on mass rearing, radiation mediated sterilization, and release of a large number of male insects. Releasing of Insects carrying a dominant lethal gene (RIDL) offers a solution to many of the drawbacks of traditional SIT that have limited its application in mosquitoes while maintaining its environmentally friendly and species-specific utility. The self-limiting nature of sterile mosquitoes tends to make the issues related to field use of these somewhat less challenging than for self-spreading systems characteristic of population replacement strategies. They also are closer to field use, so might be appropriate to consider first. The prospect of genetic control methods against mosquito vectored human diseases is rapidly becoming a reality, many decisions will need to be made on a national, regional and international level regarding the biosafety, social, cultural and ethical aspects of the use and deployment of these vector control methods.

Genetic and morphological variation and differentiation of Raja clavata populations in the European seas: marker development and preliminary data

In this study the population structure and connectivity of the Mediterranean and Atlantic Raja clavata (L., 1758) were investigated by analyzing the genetic variation of six population samples (N = 144) at seven nuclear microsatellite loci. The genetic dataset was generated by selecting population samples available in the tissue databases of the GenoDREAM laboratory (University of Bologna) and of the Department of Life Sciences and Environment (University of Cagliari), all collected during past scientific surveys (MEDITS, GRUND) from different geographical locations in the Mediterranean basin and North-east Atlantic sea, as North Sea, Sardinian coasts, Tuscany coasts and Cyprus Island. This thesis deals with to estimate the genetic diversity and differentiation among 6 geographical samples, in particular, to assess the presence of any barrier (geographic, hydrogeological or biological) to gene flow evaluating both the genetic diversity (nucleotide diversity, observed and expected heterozygosity, Hardy- Weinberg equilibrium analysis) and population differentiation (Fst estimates, population structure analysis). In addition to molecular analysis, quantitative representation and statistical analysis of morphological individuals shape are performed using geometric morphometrics methods and statistical tests. Geometric coordinates call landmarks are fixed in 158 individuals belonging to two population samples of Raja clavata and in population samples of closely related species, Raja straeleni (cryptic sibling) and Raja asterias, to assess significant morphological differences at multiple taxonomic levels. The results obtained from the analysis of the microsatellite dataset suggested a geographic and genetic separation between populations from Central-Western and Eastern Mediterranean basins. Furthermore, the analysis also showed that there was no separation between geographic samples from North Atlantic Ocean and central-Western Mediterranean, grouping them to a panmictic population. The Landmark-based geometric morphometry method results showed significant differences of body shape able to discriminate taxa at tested levels (from species to populations).

A Method for Detecting Population Genetic Structure in Diverse, High Gene-Flow Species

Detecting small amounts of genetic subdivision across geographic space remains a persistent challenge. Often a failure to detect genetic structure is mistaken for evidence of panmixia, when more powerful statistical tests may uncover evidence for subtle geographic differentiation. Such slight subdivision can be demographically and evolutionarily important as well as being critical for management decisions. We introduce here a method, called spatial analysis of shared alleles (SAShA), that detects geographically restricted alleles by comparing the spatial arrangement of allelic co-occurrences with the expectation under panmixia. The approach is allele-based and spatially explicit, eliminating the loss of statistical power that can occur with user-defined populations and statistical averaging within populations. Using simulated data sets generated under a stepping-stone model of gene flow, we show that this method outperforms spatial autocorrelation (SA) and UST under common real-world conditions: at relatively high migration rates when diversity is moderate or high, especially when sampling is poor. We then use this method to show clear differences in the genetic patterns of 2 nearshore Pacific mollusks, Tegula funebralis (5 Chlorostoma funebralis) and Katharina tunicata, whose overall patterns of within-species differentiation are similar according to traditional population genetics analyses. SAShA meaningfully complements UST/FST, SA, and other existing geographic genetic analyses and is especially appropriate for evaluating species with high gene flow and subtle genetic differentiation.

Effect of Mutation and Genetic Background on Drug Resistance in Mycobacterium tuberculosis

Bacterial factors may contribute to the global emergence and spread of drug-resistant tuberculosis (TB). Only a few studies have reported on the interactions between different bacterial factors. We studied drug-resistant Mycobacterium tuberculosis isolates from a nationwide study conducted from 2000 to 2008 in Switzerland. We determined quantitative drug resistance levels of first-line drugs by using Bactec MGIT-960 and drug resistance genotypes by sequencing the hot-spot regions of the relevant genes. We determined recent transmission by molecular methods and collected clinical data. Overall, we analyzed 158 isolates that were resistant to isoniazid, rifampin, or ethambutol, 48 (30.4%) of which were multidrug resistant. Among 154 isoniazid-resistant strains, katG mutations were associated with high-level and inhA promoter mutations with low-level drug resistance. Only katG(S315T) (65.6% of all isoniazid-resistant strains) and inhA promoter -15C/T (22.7%) were found in molecular clusters. M. tuberculosis lineage 2 (includes Beijing genotype) was associated with any drug resistance (adjusted odds ratio [OR], 3.0; 95% confidence interval [CI], 1.7 to 5.6; P < 0.0001). Lineage 1 was associated with inhA promoter -15C/T mutations (OR, 6.4; 95% CI, 2.0 to 20.7; P = 0.002). We found that the genetic strain background influences the level of isoniazid resistance conveyed by particular mutations (interaction tests of drug resistance mutations across all lineages; P < 0.0001). In conclusion, M. tuberculosis drug resistance mutations were associated with various levels of drug resistance and transmission, and M. tuberculosis lineages were associated with particular drug resistance-conferring mutations and phenotypic drug resistance. Our study also supports a role for epistatic interactions between different drug resistance mutations and strain genetic backgrounds in M. tuberculosis drug resistance.

Mapping genetic variants associated with beta-adrenergic responses in inbred mice

β-blockers and β-agonists are primarily used to treat cardiovascular diseases. Inter-individual variability in response to both drug classes is well recognized, yet the identity and relative contribution of the genetic players involved are poorly understood. This work is the first genome-wide association study (GWAS) addressing the values and susceptibility of cardiovascular-related traits to a selective β(1)-blocker, Atenolol (ate), and a β-agonist, Isoproterenol (iso). The phenotypic dataset consisted of 27 highly heritable traits, each measured across 22 inbred mouse strains and four pharmacological conditions. The genotypic panel comprised 79922 informative SNPs of the mouse HapMap resource. Associations were mapped by Efficient Mixed Model Association (EMMA), a method that corrects for the population structure and genetic relatedness of the various strains. A total of 205 separate genome-wide scans were analyzed. The most significant hits include three candidate loci related to cardiac and body weight, three loci for electrocardiographic (ECG) values, two loci for the susceptibility of atrial weight index to iso, four loci for the susceptibility of systolic blood pressure (SBP) to perturbations of the β-adrenergic system, and one locus for the responsiveness of QTc (p<10(-8)). An additional 60 loci were suggestive for one or the other of the 27 traits, while 46 others were suggestive for one or the other drug effects (p<10(-6)). Most hits tagged unexpected regions, yet at least two loci for the susceptibility of SBP to β-adrenergic drugs pointed at members of the hypothalamic-pituitary-thyroid axis. Loci for cardiac-related traits were preferentially enriched in genes expressed in the heart, while 23% of the testable loci were replicated with datasets of the Mouse Phenome Database (MPD). Altogether these data and validation tests indicate that the mapped loci are relevant to the traits and responses studied.

Genetic variations in bile acid homeostasis are not overrepresented in alcoholic cirrhosis compared to patients with heavy alcohol abuse and absent liver disease

Increased serum bile salt levels have been associated to a single-nucleotide polymorphism in the bile salt export pump (BSEP; ABCB11) in several acquired cholestatic liver diseases but there is little evidence in alcoholic liver disease (ALD). Furthermore, a crosstalk between vitamin D and bile acid synthesis has recently been discovered. Whether this crosstalk has an influence on the course of ALD is unclear to date. Our aim was to analyse the role of genetic polymorphisms in BSEP and the vitamin D receptor gene (NR1I1) on the emergence of cirrhosis in patients with ALD. Therefore, 511 alcoholic patients (131 with cirrhosis and 380 without cirrhosis) underwent ABCB11 genotyping (rs2287622). Of these, 321 (131 with cirrhosis and 190 without cirrhosis) were also tested for NR1I1 polymorphisms (bat-haplotype: BsmI rs1544410, ApaI rs7975232 and TaqI rs731236). Frequencies of ABCB11 and NR1I1 genotypes and haplotypes were compared between alcoholic patients with and without cirrhosis and correlated to serum bile salt, bilirubin and aspartate aminotransferase levels in those with cirrhosis. Frequencies of ABCB11 and NR1I1 genotypes and haplotypes did not differ between the two subgroups and no significant association between genotypes/haplotypes and liver function tests could be determined for neither polymorphism. We conclude that ABCB11 and NR1I1 polymorphisms are obviously not associated with development of cirrhosis in patients with ALD.

[A database of available DNA tests in the dog]

For genetic counseling this report presents a database of canine hereditary diseases and coat color characteristics, which have been solved on the molecular level.The database facilitates access to appropriate diagnostic laboratories for specific phenotypes. The recent decoding of the dog genome provides ideal conditions for the molecular genetic analysis of hereditary traits and diseases. Therefore the authors would like to encourage veterinary surgeons in particular to report cases to assist the molecular analysis of further phenotypes in future.

Progression of pulmonary hyperinflation and trapped gas associated with genetic and environmental factors in children with cystic fibrosis

BACKGROUND: Functional deterioration in cystic fibrosis (CF) may be reflected by increasing bronchial obstruction and, as recently shown, by ventilation inhomogeneities. This study investigated which physiological factors (airway obstruction, ventilation inhomogeneities, pulmonary hyperinflation, development of trapped gas) best express the decline in lung function, and what role specific CFTR genotypes and different types of bronchial infection may have upon this process. METHODS: Serial annual lung function tests, performed in 152 children (77 males; 75 females) with CF (age range: 6-18 y) provided data pertaining to functional residual capacity (FRCpleth, FRCMBNW), volume of trapped gas (VTG), effective specific airway resistance (sReff), lung clearance index (LCI), and forced expiratory indices (FVC, FEV1, FEF50). RESULTS: All lung function parameters showed progression with age. Pulmonary hyperinflation (FRCpleth > 2SDS) was already present in 39% of patients at age 6-8 yrs, increasing to 67% at age 18 yrs. The proportion of patients with VTG > 2SDS increased from 15% to 54% during this period. Children with severe pulmonary hyperinflation and trapped gas at age 6-8 yrs showed the most pronounced disease progression over time. Age related tracking of lung function parameters commences early in life, and is significantly influenced by specific CFTR genotypes. The group with chronic P. aeruginosa infection demonstrated most rapid progression in all lung function parameters, whilst those with chronic S. aureus infection had the slowest rate of progression. LCI, measured as an index of ventilation inhomogeneities was the most sensitive discriminator between the 3 types of infection examined (p < 0.0001). CONCLUSION: The relationships between lung function indices, CFTR genotypes and infective organisms observed in this study suggest that measurement of other lung function parameters, in addition to spirometry alone, may provide important information about disease progression in CF.

Power and Robustness of Linkage Tests for Quantitative Traits in General Pedigrees

There are numerous statistical methods for quantitative trait linkage analysis in human studies. An ideal such method would have high power to detect genetic loci contributing to the trait, would be robust to non-normality in the phenotype distribution, would be appropriate for general pedigrees, would allow the incorporation of environmental covariates, and would be appropriate in the presence of selective sampling. We recently described a general framework for quantitative trait linkage analysis, based on generalized estimating equations, for which many current methods are special cases. This procedure is appropriate for general pedigrees and easily accommodates environmental covariates. In this paper, we use computer simulations to investigate the power robustness of a variety of linkage test statistics built upon our general framework. We also propose two novel test statistics that take account of higher moments of the phenotype distribution, in order to accommodate non-normality. These new linkage tests are shown to have high power and to be robust to non-normality. While we have not yet examined the performance of our procedures in the context of selective sampling via computer simulations, the proposed tests satisfy all of the other qualities of an ideal quantitative trait linkage analysis method.

ASSOCIATON TESTS THAT ACCOMMODATE GENOTYPING ERRORS

High-throughput SNP arrays provide estimates of genotypes for up to one million loci, often used in genome-wide association studies. While these estimates are typically very accurate, genotyping errors do occur, which can influence in particular the most extreme test statistics and p-values. Estimates for the genotype uncertainties are also available, although typically ignored. In this manuscript, we develop a framework to incorporate these genotype uncertainties in case-control studies for any genetic model. We verify that using the assumption of a “local alternative” in the score test is very reasonable for effect sizes typically seen in SNP association studies, and show that the power of the score test is simply a function of the correlation of the genotype probabilities with the true genotypes. We demonstrate that the power to detect a true association can be substantially increased for difficult to call genotypes, resulting in improved inference in association studies.

Genetic association studies under the population stratification, family pedigree and application to genome-wide association studies

This dissertation has three separate parts: the first part deals with the general pedigree association testing incorporating continuous covariates; the second part deals with the association tests under population stratification using the conditional likelihood tests; the third part deals with the genome-wide association studies based on the real rheumatoid arthritis (RA) disease data sets from Genetic Analysis Workshop 16 (GAW16) problem 1. Many statistical tests are developed to test the linkage and association using either case-control status or phenotype covariates for family data structure, separately. Those univariate analyses might not use all the information coming from the family members in practical studies. On the other hand, the human complex disease do not have a clear inheritance pattern, there might exist the gene interactions or act independently. In part I, the new proposed approach MPDT is focused on how to use both the case control information as well as the phenotype covariates. This approach can be applied to detect multiple marker effects. Based on the two existing popular statistics in family studies for case-control and quantitative traits respectively, the new approach could be used in the simple family structure data set as well as general pedigree structure. The combined statistics are calculated using the two statistics; A permutation procedure is applied for assessing the p-value with adjustment from the Bonferroni for the multiple markers. We use simulation studies to evaluate the type I error rates and the powers of the proposed approach. Our results show that the combined test using both case-control information and phenotype covariates not only has the correct type I error rates but also is more powerful than the other existing methods. For multiple marker interactions, our proposed method is also very powerful. Selective genotyping is an economical strategy in detecting and mapping quantitative trait loci in the genetic dissection of complex disease. When the samples arise from different ethnic groups or an admixture population, all the existing selective genotyping methods may result in spurious association due to different ancestry distributions. The problem can be more serious when the sample size is large, a general requirement to obtain sufficient power to detect modest genetic effects for most complex traits. In part II, I describe a useful strategy in selective genotyping while population stratification is present. Our procedure used a principal component based approach to eliminate any effect of population stratification. The paper evaluates the performance of our procedure using both simulated data from an early study data sets and also the HapMap data sets in a variety of population admixture models generated from empirical data. There are one binary trait and two continuous traits in the rheumatoid arthritis dataset of Problem 1 in the Genetic Analysis Workshop 16 (GAW16): RA status, AntiCCP and IgM. To allow multiple traits, we suggest a set of SNP-level F statistics by the concept of multiple-correlation to measure the genetic association between multiple trait values and SNP-specific genotypic scores and obtain their null distributions. Hereby, we perform 6 genome-wide association analyses using the novel one- and two-stage approaches which are based on single, double and triple traits. Incorporating all these 6 analyses, we successfully validate the SNPs which have been identified to be responsible for rheumatoid arthritis in the literature and detect more disease susceptibility SNPs for follow-up studies in the future. Except for chromosome 13 and 18, each of the others is found to harbour susceptible genetic regions for rheumatoid arthritis or related diseases, i.e., lupus erythematosus. This topic is discussed in part III.

Spatial isolation and genetic differentiation in naturally fragmented plant populations of the Swiss Alps

Aims The effect Of anthropogenic landscape fragmentation on the genetic diversity and adaptive potential of plant populations is a major issue in conservation biology. However, little is known about the partitioning of genetic diversity in alpine species, which occur in naturally fragmented habitats. Here, we, investigate molecular patterns of three alpine plants (Epilobium fleischeri, Geum reptans and Campanula thyrsoides) across Switzerland and ask whether Spatial isolation has led to high levels of populations differentiation, increasing over distance, and a decrease of within-population variability. We further hypothesize that file contrasting potential for long-distance dispersal (LDD) of Seed in these Species will considerably influence and explain diversity partitioning. Methods For each study species, we Sampled 20-23 individuals from each of 20-32 populations across entire Switzerland. We applied Random Amplified Polymorphic Dimorphism markers to assess genetic diversity within (Nei's expected heterozygosity, H-e; percentage of polymorphic hands, P-P) and among (analysis of molecular variance, Phi(st)) populations and correlated population size and altitude with within-populalion diversity. Spatial patterns of genetic relatedness were investigated using Mantel tests and standardized major axis regression as well as unweighted pair group method with arithmetic mean cluster analyses and Monmonier's algorithm. To avoid known biases, We standardized the numbers of populations, individuals and markers using multiple random reductions. We modelled LDD with a high alpine wind data set using the terminal velocity and height of seed release as key parameters. Additionally, we assessed a number of important life-history traits and factors that potentially influence genetic diversity partitioning (e.g. breeding system, longevity and population size). Important findings For all three species, We found a significant isolation-by-distance relationship but only a moderately high differentiation among populations (Phi(st): 22.7, 48 and 16.8%, for E. fleischeri, G. reptans and C. thyrsoides, respectively). Within-population diversity (H-c: 0.19-0.21, P-p: 62-75%) was not reduced in comparison to known results from lowland species and even small populations with < 50 reproductive individuals contained high levels of genetic diversity. We further found no indication that a high long-distance seed dispersal potential enhances genetic connectivity among populations. Gene flow seems to have a strong stochastic component causing large dissimilarity between population pairs irrespective of the spatial distance. Our results suggest that other life-history traits, especially the breeding System, may play an important role in genetic diversity partitioning. We conclude that spatial isolation in the alpine environment has a strong influence on population relatedness but that a number of factors can considerably influence the strength of this relationship.