Hostility: A prospective study of the genetic and environmental background and associations with cardiovascular risk

Hostility is a multidimensional construct having wide effects on society. In its different forms, hostility is related to a large array of social and health problems, such as criminality, substance abuse, depression, and cardiovascular risks. Identifying and tackling early-life factors that contribute to hostility may have public health significance. Although the variance in hostility is estimated to be 18-50 percent heritable, there are significant gaps in knowledge regarding the molecular genetics of hostility. It is known that a cold and unsupportive home atmosphere in childhood predicts a child s later hostility. However, the long-term effects of care-giving quality on hostility in adulthood and the role of genes in this association are unclear. The present dissertation is part of the ongoing population-based prospective Young Finns study, which commenced in 1980 with 3596 3-18-year-old boys and girls who were followed for 27 years. The specific aims of the dissertation were first to study the antecedents of hostility by looking at 1) the genetic background, 2) the early environmental predictors, and 3) the gene environment interplay behind hostility. As a second aim, the thesis endeavored to examine 4) the association between hostility and cardiovascular risks, and 5) the moderating effect of demographic factors, such as gender and socioeconomic status, on this association. The study found potential gene polymorphisms from chromosomes 7, 14, 17, and 22 suggestively associated with hostility. Of early environmental influences, breastfeeding and early care-giving were found to predict hostility in adulthood. In addition, a serotonin receptor 2A polymorphism rs6313 moderated the effect of early care-giving on later hostile attitudes. Furthermore, hostility was shown to predict cardiovascular risks, such as metabolic syndrome and inflammation. Finally, parental socioeconomic status was found to moderate the association between anger and early atherosclerosis. The new genetic and early environmental antecedents of hostility identified in this research may help in understanding the development of hostility and its health risks, and in planning appropriate prevention. The significance of early influences on this development is stressed. Although the markers studied are individual- and family-related factors, these may be influenced at the societal level by giving accurate information to all individuals concerned and by improving the societal circumstances.

A Genetic Study of Immunoglobulin E and Atopic Disease Based on Families Ascertained through Asthmatic Children

In order to investigate the modes of inheritance of serum immunoglobulin E (IgE) levels and atopic disease, serum IgE levels and data on allergic disease were obtained from 42 families ascertained through asthmatic children visiting an allergy clinic. Although the mean IgE levels were elevated (mean 637 U/ml), the prevalence of atopic disease in this population was surprisingly low. When the data were analyzed using complex segregation analysis, no major locus could be detected. Moreover, the polygenic heritability was unexpectedly small even though the correlation between serum IgE levels and the liability to atopic disease was around 0.4. Given this unusual set of findings, it is postulated that parasitic infections in this population have (in accordance with well-established results of parasitic disease) caused both elevated levels of serum IgE and a decreased prevalence of allergic disease with the possible masking of the various genetic components of serum IgE levels and atopic disease.

Transposable element-medicated evolution of sex: A population genetic model

For a population made up of individuals capable of sexual as well as asexual modes of reproduction, conditions for the spread of a transposable element are explored using a one-locus, two-haplotype model. The analysis is then extended to include the possibility that the transposable element can modulate the probability of sexual reproduction, thus casting Hickey’s (1982,Genetics 101: 519–531) suggestion in a population genetics framework. The model explicitly includes the cost of sexual reproduction, fitness disadvantage to the transposable element, probability of transposition, and the predisposition for sexual reproduction in the presence and absence of the transposable element. The model predicts several kinds of outcome, including initial frequency dependence and stable polymorphism. More importantly, it is seen that for a wide range of parameter values, the transposable element can go to fixation. Therefore it is able to convert the population from a predominantly asexual to a predominantly sexual mode of reproduction. Viewed in conjunction with recent results implicating short stretches of apparently non-coding DNA in sex determination (McCoubreyet al. 1988,Science 242: 1146–1151), the model hints at the important role this mechanism could have played in the evolution of sexuality.

A near-optimal initial seed value selection in K-means means algorithm using a genetic algorithm

The K-means algorithm for clustering is very much dependent on the initial seed values. We use a genetic algorithm to find a near-optimal partitioning of the given data set by selecting proper initial seed values in the K-means algorithm. Results obtained are very encouraging and in most of the cases, on data sets having well separated clusters, the proposed scheme reached a global minimum.

Dissection of the genetic background of childhood onset progressive myoclonic epilepsies

The progressive myoclonic epilepsies (PMEs) are a clinically and etiologically heterogeneous group of symptomatic epilepsies characterized by myoclonus, tonic-clonic seizures, psychomotor regression and ataxia. Different disorders have been classified as PMEs. Of these, the group of neuronal ceroid lipofuscinoses (NCLs) comprise an entity that has onset in childhood, being the most common cause of neurodegeneration in children. The primary aim of this thesis was to dissect the molecular genetic background of patients with childhood onset PME by studying candidate genes and attempting to identify novel PME-associated genes. Another specific aim was to study the primary protein properties of the most recently identified member of the NCL-causing proteins, MFSD8. To dissect the genetic background of a cohort of Turkish patients with childhood onset PME, a screen of the NCL-associated genes PPT1, TPP1, CLN3, CLN5, CLN6, MFSD8, CLN8 and CTSD was performed. Altogether 49 novel mutations were identified, which together with 56 mutations found by collaborators raised the total number of known NCL mutations to 364. Fourteen of the novel mutations affect the recently identified MFSD8 gene, which had originally been identified in a subset of mainly Turkish patients as the underlying cause of CLN7 disease. To investigate the distribution of MFSD8 defects, a total of 211 patients of different ethnic origins were evaluated for mutations in the gene. Altogether 45 patients from nine different countries were provided with a CLN7 molecular diagnosis, denoting the wide geographical occurrence of MFSD8 defects. The mutations are private with only one having been established by a founder-effect in the Roma population from the former Czechoslovakia. All mutations identified except one are associated with the typical clinical picture of variant late-infantile NCL. To address the trafficking properties of MFSD8, lysosomal targeting of the protein was confirmed in both neuronal and non-neuronal cells. The major determinant for this lysosomal sorting was identified to be an N-terminal dileucine based signal (9-EQEPLL-14), recognized by heterotetrameric AP-1 adaptor proteins, suggesting that MFSD8 takes the direct trafficking pathway en route to the lysosomes. Expression studies revealed the neurons as the primary cell-type and the hippocampus and cerebellar granular cell layer as the predominant regions in which MFSD8 is expressed. To identify novel genes associated with childhood onset PME, a single nucleotide polymorphism (SNP) genomewide scan was performed in three small families and 18 sporadic patients followed by homozygosity mapping to determine the candidate loci. One of the families and a sporadic patient were positive for mutations in PLA2G6, a gene that had previously been shown to cause infantile neuroaxonal dystrophy. Application of next-generation sequencing of candidate regions in the remaining two families led to identification of a homozygous missense mutation in USP19 for the first and TXNDC6 for the second family. Analysis of the 18 sporadic cases mapped the best candidate interval in a 1.5 Mb region on chromosome 7q21. Screening of the positional candidate KCTD7 revealed six mutations in seven unrelated families. All patients with mutations in KCTD7 were reported to have early onset PME, rapid disease progression leading to dementia and no pathologic hallmarks. The identification of KCTD7 mutations in nine patients and the clinical delineation of their phenotype establish KCTD7 as a gene for early onset PME. The findings presented in this thesis denote MFSD8 and KCTD7 as genes commonly associated with childhood onset symptomatic epilepsy. The disease-associated role of TXNDC6 awaits verification through identification of additional mutations in patients with similar phenotypes. Completion of the genetic spectrum underlying childhood onset PMEs and understanding of the gene products functions will comprise important steps towards understanding the underlying pathogenetic mechanisms, and will possibly shed light on the general processes of neurodegeneration and nervous system regulation, facilitating the diagnosis, classification and possibly treatment of the affected cases.

Molecular methods for the epidemiological analysis of methicillin-resistant Staphylococcus aureus (MRSA) and Streptococcus pneumoniae

Methicillin-resistant Staphylococcus aureus (MRSA) and Streptococcus pneumoniae are major health problems worldwide, both found in symptomless carriage but also causing even life-threatening infections. The aim of this thesis was to characterise MRSA and S. pneumoniae in detail by using several molecular typing methods for various epidemiological purposes: clonality analysis, epidemiological surveillance, outbreak investigation, and virulence factor analysis. The characteristics of MRSA isolates from the strain collection of the Finnish National Infectious Disease Register (NIDR) and pneumococcal isolates collected from military recruits and children with acute otitis media (AOM) were analysed using various typing techniques. Antimicrobial susceptibility testing, pulsed-field gel electrophoresis (PFGE), multilocus sequence typing (MLST), spa typing, staphylococcal cassette chromosome mec (SCCmec) typing, and the detection of Panton-Valentine leukocidin (PVL) genes were performed for MRSA isolates. Pneumococcal isolates were analysed using antimicrobial susceptibility testing, serotyping, MLST, and by detecting pilus islet 1 (PI-1) and 2 (PI-2) genes. Several international community- and hospital-associated MRSA clones were recognised in Finland. The genetic diversity among MRSA FIN-4 isolates and among FIN-16 isolates was low. Overall, MRSA blood isolates from 1997 to 2006 were genetically diverse. spa typing was found to be a highly discriminatory, rapid and accurate typing method and it also qualifies as the primary typing method in countries with a long history of PFGE-based MRSA strain nomenclature. However, additional typing by another method, e.g. PFGE, is needed in certain situations to be able to provide adequate discrimination for epidemiological surveillance and outbreak investigation. An outbreak of pneumonia was associated with one pneumococcal strain among military recruits, previously healthy young men living in a crowded setting. The pneumococcal carriage rate after the outbreak was found to be exceptionally high. PI-1 genes were detected at a rather low prevalence among pneumococcal isolates from children with AOM. However, the study demonstrated that PI-1 has existed among pneumococcal isolates prior to pneumococcal conjugate vaccine and the increased antimicrobial resistance era. Moreover, PI-1 was found to associate with the serotype rather than the genotype. This study adds to our understanding of the molecular epidemiology of MRSA strains in Finland and the importance of an appropriate genotyping method to be able to perform high-level laboratory-based surveillance of MRSA. Epidemiological and molecular analyses of S. pneumoniae add to our knowledge of the characteristics of pneumococcal strains in Finland.

Genetic transformation of Brassica nigra by agrobacterium based vector and direct plasmid uptake

Genetic transformation systems have been established for Brassica nigra (cv. IC 257) by using an Agrobacterium binary vector as well as by direct DNA uptake of a plasmid vector. Both the type of vectors carried nptII gene and gus gene. For Agrobacterium mediated transformation, hypocotyl tissue explants were used, and up to 33% of the explants produced calli on selection medium. All of these expressed B-glucuronidase gene on histochemical staining. Protoplasts isolated from hypocotyl tissues of seedlings could be transformed with a plasmid vector by FEG mediated uptake of vector DNA. A number of fertile kanamycin resistant plants were obtained using both the methods, and their transformed nature was confirmed by Southern blot analysis and histochemical staining for GUS. Backcrossed and selfed progenies of these transformed plants showed the presence of npt and gus genes.

Permanent Genetic Resources added to Molecular Ecology Resources Database 1 August 2010-30 September 2010

This article documents the addition of 229 microsatellite marker loci to the Molecular Ecology Resources Database. Loci were developed for the following species: Acacia auriculiformis x Acacia mangium hybrid, Alabama argillacea, Anoplopoma fimbria, Aplochiton zebra, Brevicoryne brassicae, Bruguiera gymnorhiza, Bucorvus leadbeateri, Delphacodes detecta, Tumidagena minuta, Dictyostelium giganteum, Echinogammarus berilloni, Epimedium sagittatum, Fraxinus excelsior, Labeo chrysophekadion, Oncorhynchus clarki lewisi, Paratrechina longicornis, Phaeocystis antarctica, Pinus roxburghii and Potamilus capax. These loci were cross-tested on the following species: Acacia peregrinalis, Acacia crassicarpa, Bruguiera cylindrica, Delphacodes detecta, Tumidagena minuta, Dictyostelium macrocephalum, Dictyostelium discoideum, Dictyostelium purpureum, Dictyostelium mucoroides, Dictyostelium rosarium, Polysphondylium pallidum, Epimedium brevicornum, Epimedium koreanum, Epimedium pubescens, Epimedium wushanese and Fraxinus angustifolia.

Genetic algorithms: a survey

Genetic algorithms provide an alternative to traditional optimization techniques by using directed random searches to locate optimal solutions in complex landscapes. We introduce the art and science of genetic algorithms and survey current issues in GA theory and practice. We do not present a detailed study, instead, we offer a quick guide into the labyrinth of GA research. First, we draw the analogy between genetic algorithms and the search processes in nature. Then we describe the genetic algorithm that Holland introduced in 1975 and the workings of GAs. After a survey of techniques proposed as improvements to Holland's GA and of some radically different approaches, we survey the advances in GA theory related to modeling, dynamics, and deception

Imaging in vivo Neuronal Transport in Genetic Model Organisms Using Microfluidic Devices

Microfluidic devices have been developed for imaging behavior and various cellular processes in Caenorhabditis elegans, but not subcellular processes requiring high spatial resolution. In neurons, essential processes such as axonal, dendritic, intraflagellar and other long-distance transport can be studied by acquiring fast time-lapse images of green fluorescent protein (GFP)-tagged moving cargo. We have achieved two important goals in such in vivo studies namely, imaging several transport processes in unanesthetized intact animals and imaging very early developmental stages. We describe a microfluidic device for immobilizing C. elegans and Drosophila larvae that allows imaging without anesthetics or dissection. We observed that for certain neuronal cargoes in C. elegans, anesthetics have significant and sometimes unexpected effects on the flux. Further, imaging the transport of certain cargo in early developmental stages was possible only in the microfluidic device. Using our device we observed an increase in anterograde synaptic vesicle transport during development corresponding with synaptic growth. We also imaged Q neuroblast divisions and mitochondrial transport during early developmental stages of C. elegans and Drosophila, respectively. Our simple microfluidic device offers a useful means to image high-resolution subcellular processes in C. elegans and Drosophila and can be readily adapted to other transparent or translucent organisms.

Genetic regulation of flower development

Flower development provides a model system to study mechanisms that govern pattern formation in plants. Most flowers consist of four organ types that are present in a specific order from the periphery to the centre of the flower. Reviewed here are studies on flower development in two model species: Arabidopsis thaliana and Antirrhinum majus that focus on the molecular genetic analysis of homeotic mutations affecting pattern formation in the flower. Based on these studies a model was proposed that explains how three classes of regulatory genes can together control the development of the correct pattern of organs in the flower. The universality of the basic tenets of the model is apparent from the analysis of the homologues of the Arabidopsis genes from other plant species

Genetic search: Analysis using fitness moments

Genetic Algorithms are efficient and robust search methods that are being employed in a plethora of applications with extremely large search spaces. The directed search mechanism employed in Genetic Algorithms performs a simultaneous and balanced, exploration of new regions in the search space and exploitation of already discovered regions.This paper introduces the notion of fitness moments for analyzing the working of Genetic Algorithms (GAs). We show that the fitness moments in any generation may be predicted from those of the initial population. Since a knowledge of the fitness moments allows us to estimate the fitness distribution of strings, this approach provides for a method of characterizing the dynamics of GAs. In particular the average fitness and fitness variance of the population in any generation may be predicted. We introduce the technique of fitness-based disruption of solutions for improving the performance of GAs. Using fitness moments, we demonstrate the advantages of using fitness-based disruption. We also present experimental results comparing the performance of a standard GA and GAs (CDGA and AGA) that incorporate the principle of fitness-based disruption. The experimental evidence clearly demonstrates the power of fitness based disruption.

On generating optimal signal probabilities for random tests: A genetic approach

Genetic Algorithms are robust search and optimization techniques. A Genetic Algorithm based approach for determining the optimal input distributions for generating random test vectors is proposed in the paper. A cost function based on the COP testability measure for determining the efficacy of the input distributions is discussed, A brief overview of Genetic Algorithms (GAs) and the specific details of our implementation are described. Experimental results based on ISCAS-85 benchmark circuits are presented. The performance pf our GA-based approach is compared with previous results. While the GA generates more efficient input distributions than the previous methods which are based on gradient descent search, the overheads of the GA in computing the input distributions are larger. To account for the relatively quick convergence of the gradient descent methods, we analyze the landscape of the COP-based cost function. We prove that the cost function is unimodal in the search space. This feature makes the cost function amenable to optimization by gradient-descent techniques as compared to random search methods such as Genetic Algorithms.

Sibling rivalry between seeds within a fruit: Some population genetic models

Competition between seeds within a fruit for parental resources is described using one-locus-two-allele models. While a �normal� allele leads to an equitable distribution of resources between seeds (a situation which also corresponds to the parental optimum), the �selfish� allele is assumed to cause the seed carrying it to usurp a higher proportion of the resources. The outcome of competition between �selfish� alleles is also assumed to lead to an asymmetric distribution of resources, the �winner� being chosen randomly. Conditions for the spread of an initially rare selfish allele and the optimal resource allocation corresponding to the evolutionarily stable strategy, derived for species with n-seeded fruits, are in accordance with expectations based on Hamilton�s inclusive fitness criteria. Competition between seeds is seen to be most intense when there are only two seeds, and decreases with increasing number of seeds, suggesting that two-seeded fruits would be rarer than one-seeded or many-seeded ones. Available data from a large number of plant species are consistent with this prediction of the model.

On an exact populationary model of genetic algorithms

Genetic algorithms (GAs) are search methods that are being employed in a multitude of applications with extremely large search spaces. Recently, there has been considerable interest among GA researchers in understanding and formalizing the working of GAs. In an earlier paper, we have introduced the notion of binomially distributed populations as the central idea behind an exact ''populationary'' model of the large-population dynamics of the GA operators for objective functions called ''functions of unitation.'' In this paper, we extend this populationary model of GA dynamics to a more general class of objective functions called functions of unitation variables. We generalize the notion of a binomially distributed population to a generalized binomially distributed population (GBDP). We show that the effects of selection, crossover, and mutation can be exactly modelled after decomposing the population into GBDPs. Based on this generalized model, we have implemented a GA simulator for functions of two unitation variables-GASIM 2, and the distributions predicted by GASIM 2 match with those obtained from actual GA runs. The generalized populationary model of GA dynamics not only presents a novel and natural way of interpreting the workings of GAs with large populations, but it also provides for an efficient implementation of the model as a GA simulator. (C) Elsevier Science Inc. 1997.