30 resultados para Genetic Algorithms, Adaptation, Internet Computing


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Background The European trout (Salmo trutta species complex) occurs across a very wide altitudinal range from lowland rivers to alpine streams. Historically, the major European river systems contained different, evolutionarily distinct trout lineages, and some of this genetic diversity has persisted in spite of extensive human-mediated translocations. We used AFLP-based genome scans to investigate the extent of potentially adaptive divergence among major drainages and along altitudinal gradients replicated in several rivers. Results The proportion of loci showing evidence of divergent selection was larger between drainages than along altitudinal transects within drainages. This suggests divergent selection is stronger between drainages, or adaptive divergence is constrained by gene flow among populations within drainages, although the latter could not be confirmed at a more local scale. Still, altitudinal divergence occurred and, at approximately 2% of the markers, parallel changes of the AFLP band frequencies with altitude were observed suggesting that altitude may well be an important source of divergent selection within rivers. Conclusions Our results indicate that adaptive genetic divergence is common both between major European river systems and along altitudinal gradients within drainages. Alpine trout appear to be a promising model system to investigate the relative roles of divergent selection and gene flow in promoting or preventing adaptation to climate gradients.

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Background: Transgressive segregation describes the occurrence of novel phenotypes in hybrids with extreme trait values not observed in either parental species. A previously experimentally untested prediction is that the amount of transgression increases with the genetic distance between hybridizing species. This follows from QTL studies suggesting that transgression is most commonly due to complementary gene action or epistasis, which become more frequent at larger genetic distances. This is because the number of QTLs fixed for alleles with opposing signs in different species should increase with time since speciation provided that speciation is not driven by disruptive selection. We measured the amount of transgression occurring in hybrids of cichlid fish bred from species pairs with gradually increasing genetic distances and varying phenotypic similarity. Transgression in multi-trait shape phenotypes was quantified using landmark-based geometric morphometric methods. Results: We found that genetic distance explained 52% and 78% of the variation in transgression frequency in F1 and F2 hybrids, respectively. Confirming theoretical predictions, transgression when measured in F2 hybrids, increased linearly with genetic distance between hybridizing species. Phenotypic similarity of species on the other hand was not related to the amount of transgression. Conclusion: The commonness and ease with which novel phenotypes are produced in cichlid hybrids between unrelated species has important implications for the interaction of hybridization with adaptation and speciation. Hybridization may generate new genotypes with adaptive potential that did not reside as standing genetic variation in either parental population, potentially enhancing a population's responsiveness to selection. Our results make it conceivable that hybridization contributed to the rapid rates of phenotypic evolution in the large and rapid adaptive radiations of haplochromine cichlids.

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The genetic determinants and phenotypic traits which make a Staphylococcus aureus strain a successful colonizer are largely unknown. The genetic diversity and population structure of 133 S. aureus isolates from healthy, generally risk-free adult carriers were investigated using four different typing methods: multilocus sequence typing (MLST), amplified fragment length polymorphism analysis (AFLP), double-locus sequence typing (DLST), and spa typing were compared. Carriage isolates displayed great genetic diversity which could only be revealed fully by DLST. Results of AFLP and MLST were highly concordant in the delineation of genotypic clusters of closely related isolates, roughly equivalent to clonal complexes. spa typing and DLST provided considerably less phylogenetic information. The resolution of spa typing was similar to that of AFLP and inferior to that of DLST. AFLP proved to be the most universal method, combining a phylogeny-building capacity similar to that of MLST with a much higher resolution. However, it had a lower reproducibility than sequencing-based MLST, DLST, and spa typing. We found two cases of methicillin-resistant S. aureus colonization, both of which were most likely associated with employment at a health service. Of 21 genotypic clusters detected, 2 were most prevalent: cluster 45 and cluster 30 each colonized 24% of the carrier population. The number of bacteria found in nasal samples varied significantly among the clusters, but the most prevalent clusters were not particularly numerous in the nasal samples. We did not find much evidence that genotypic clusters were associated with different carrier characteristics, such as age, sex, medical conditions, or antibiotic use. This may provide empirical support for the idea that genetic clusters in bacteria are maintained in the absence of adaptation to different niches. Alternatively, carrier characteristics other than those evaluated here or factors other than human hosts may exert selective pressure maintaining genotypic clusters.

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Altitudinal gradients offer valuable study systems to investigate how adap- tive genetic diversity is distributed within and between natural populations and which factors promote or prevent adaptive differentiation. The environ- mental clines along altitudinal gradients tend to be steep relative to the dispersal distance of many organisms, providing an opportunity to study the joint effects of divergent natural selection and gene flow. Temperature is one variable showing consistent altitudinal changes, and altitudinal gradi- ents can therefore provide spatial surrogates for some of the changes antici- pated under climate change. Here, we investigate the extent and patterns of adaptive divergence in animal populations along altitudinal gradients by sur- veying the literature for (i) studies on phenotypic variation assessed under common garden or reciprocal transplant designs and (ii) studies looking for signatures of divergent selection at the molecular level. Phenotypic data show that significant between-population differences are common and taxo- nomically widespread, involving traits such as mass, wing size, tolerance to thermal extremes and melanization. Several lines of evidence suggest that some of the observed differences are adaptively relevant, but rigorous tests of local adaptation or the link between specific phenotypes and fitness are sorely lacking. Evidence for a role of altitudinal adaptation also exists for a number of candidate genes, most prominently haemoglobin, and for anony- mous molecular markers. Novel genomic approaches may provide valuable tools for studying adaptive diversity, also in species that are not amenable to experimentation.

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Chondrostoma nasus is a cyprinid fish with highly specialized, ecologically and geographically distinct, ontogenetic trophic niches. Nase population numbers across their Swiss range have shown massive declines and many localized extinctions. Here we integrate data from different genetic markers with phenotypic and demographic data to survey patterns of neutral and adaptive genetic diversity in all extant (and one extinct) Swiss nase populations, with the aim to delineate intraspecific conservation units (CUs) and to inform future population management strategies. We discovered two major genetically and geographically distinct population groupings. The first population grouping comprises nase inhabiting rivers flowing into Lake Constance; the second comprises nase populations from Rhine drainages below Lake Constance. Within these clusters there is generally limited genetic differentiation among populations. Genomic outlier scans based on 256–377 polymorphic AFLP loci revealed little evidence of local adaptation both within and among population clusters, with the exception of one candidate locus identified in scans involving the inbred Schanzengraben population. However, significant phenotypic differentiation in body shape between certain populations suggests a need for more intensive future studies of local adaptation. Our data strongly suggests that the two major population groups should be treated as distinct CUs, with any supplemental stocking and reintroductions sourced only from within the range of the CU concerned.

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Prevalence and genetic relatedness were determined for third-generation cephalosporin-resistant Escherichia coli (3GC-R-Ec) detected in Swiss beef, veal, pork, and poultry retail meat. Samples from meat-packing plants (MPPs) processing 70% of the slaughtered animals in Switzerland were purchased at different intervals between April and June 2013 and analyzed. Sixty-nine 3GC-R-Ec isolates were obtained and characterized by microarray, PCR/DNA sequencing, Multi Locus Sequence Typing (MLST), and plasmid replicon typing. Plasmids of selected strains were transformed by electroporation into E. coli TOP10 cells and analyzed by plasmid MLST. The prevalence of 3GC-R-Ec was 73.3% in chicken and 2% in beef meat. No 3GC-R-Ec were found in pork and veal. Overall, the blaCTX-M-1 (79.4%), blaCMY-2 (17.6%), blaCMY-4 (1.5%), and blaSHV-12 (1.5%) β-lactamase genes were detected, as well as other genes conferring resistance to chloramphenicol (cmlA1-like), sulfonamides (sul), tetracycline (tet), and trimethoprim (dfrA). The 3GC-R-Ec from chicken meat often harbored virulence genes associated with avian pathogens. Plasmid incompatibility (Inc) groups IncI1, IncFIB, IncFII, and IncB/O were the most frequent. A high rate of clonality (e.g., ST1304, ST38, and ST93) among isolates from the same MPPs suggests that strains persist at the plant and spread to meat at the carcass-processing stage. Additionally, the presence of the blaCTX-M-1 gene on an IncI1 plasmid sequence type 3 (IncI1/pST3) in genetically diverse strains indicates interstrain spread of an epidemic plasmid. The blaCMY-2 and blaCMY-4 genes were located on IncB/O plasmids. This study represents the first comprehensive assessment of 3GC-R-Ec in meat in Switzerland. It demonstrates the need for monitoring contaminants and for the adaptation of the Hazard Analysis and Critical Control Point concept to avoid the spread of multidrug-resistant bacteria through the food chain.

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Cloud Computing has evolved to become an enabler for delivering access to large scale distributed applications running on managed network-connected computing systems. This makes possible hosting Distributed Enterprise Information Systems (dEISs) in cloud environments, while enforcing strict performance and quality of service requirements, defined using Service Level Agreements (SLAs). {SLAs} define the performance boundaries of distributed applications, and are enforced by a cloud management system (CMS) dynamically allocating the available computing resources to the cloud services. We present two novel VM-scaling algorithms focused on dEIS systems, which optimally detect most appropriate scaling conditions using performance-models of distributed applications derived from constant-workload benchmarks, together with SLA-specified performance constraints. We simulate the VM-scaling algorithms in a cloud simulator and compare against trace-based performance models of dEISs. We compare a total of three SLA-based VM-scaling algorithms (one using prediction mechanisms) based on a real-world application scenario involving a large variable number of users. Our results show that it is beneficial to use autoregressive predictive SLA-driven scaling algorithms in cloud management systems for guaranteeing performance invariants of distributed cloud applications, as opposed to using only reactive SLA-based VM-scaling algorithms.

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Cloud Computing enables provisioning and distribution of highly scalable services in a reliable, on-demand and sustainable manner. However, objectives of managing enterprise distributed applications in cloud environments under Service Level Agreement (SLA) constraints lead to challenges for maintaining optimal resource control. Furthermore, conflicting objectives in management of cloud infrastructure and distributed applications might lead to violations of SLAs and inefficient use of hardware and software resources. This dissertation focusses on how SLAs can be used as an input to the cloud management system, increasing the efficiency of allocating resources, as well as that of infrastructure scaling. First, we present an extended SLA semantic model for modelling complex service-dependencies in distributed applications, and for enabling automated cloud infrastructure management operations. Second, we describe a multi-objective VM allocation algorithm for optimised resource allocation in infrastructure clouds. Third, we describe a method of discovering relations between the performance indicators of services belonging to distributed applications and then using these relations for building scaling rules that a CMS can use for automated management of VMs. Fourth, we introduce two novel VM-scaling algorithms, which optimally scale systems composed of VMs, based on given SLA performance constraints. All presented research works were implemented and tested using enterprise distributed applications.

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In this paper we present BitWorker, a platform for community distributed computing based on BitTorrent. Any splittable task can be easily specified by a user in a meta-information task file, such that it can be downloaded and performed by other volunteers. Peers find each other using Distributed Hash Tables, download existing results, and compute missing ones. Unlike existing distributed computing schemes relying on centralized coordination point(s), our scheme is totally distributed, therefore, highly robust. We evaluate the performance of BitWorker using mathematical models and real tests, showing processing and robustness gains. BitWorker is available for download and use by the community.

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Living at high altitude is one of the most difficult challenges that humans had to cope with during their evolution. Whereas several genomic studies have revealed some of the genetic bases of adaptations in Tibetan, Andean, and Ethiopian populations, relatively little evidence of convergent evolution to altitude in different continents has accumulated. This lack of evidence can be due to truly different evolutionary responses, but it can also be due to the low power of former studies that have mainly focused on populations from a single geographical region or performed separate analyses on multiple pairs of populations to avoid problems linked to shared histories between some populations. We introduce here a hierarchical Bayesian method to detect local adaptation that can deal with complex demographic histories. Our method can identify selection occurring at different scales, as well as convergent adaptation in different regions. We apply our approach to the analysis of a large SNP data set from low- and high-altitude human populations from America and Asia. The simultaneous analysis of these two geographic areas allows us to identify several candidate genome regions for altitudinal selection, and we show that convergent evolution among continents has been quite common. In addition to identifying several genes and biological processes involved in high-altitude adaptation, we identify two specific biological pathways that could have evolved in both continents to counter toxic effects induced by hypoxia.

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Recently telecommunication industry benefits from infrastructure sharing, one of the most fundamental enablers of cloud computing, leading to emergence of the Mobile Virtual Network Operator (MVNO) concept. The most momentous intents by this approach are the support of on-demand provisioning and elasticity of virtualized mobile network components, based on data traffic load. To realize it, during operation and management procedures, the virtualized services need be triggered in order to scale-up/down or scale-out/in an instance. In this paper we propose an architecture called MOBaaS (Mobility and Bandwidth Availability Prediction as a Service), comprising two algorithms in order to predict user(s) mobility and network link bandwidth availability, that can be implemented in cloud based mobile network structure and can be used as a support service by any other virtualized mobile network services. MOBaaS can provide prediction information in order to generate required triggers for on-demand deploying, provisioning, disposing of virtualized network components. This information can be used for self-adaptation procedures and optimal network function configuration during run-time operation, as well. Through the preliminary experiments with the prototype implementation on the OpenStack platform, we evaluated and confirmed the feasibility and the effectiveness of the prediction algorithms and the proposed architecture.

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Currently several thousands of objects are being tracked in the MEO and GEO regions through optical means. The problem faced in this framework is that of Multiple Target Tracking (MTT). In this context both the correct associations among the observations, and the orbits of the objects have to be determined. The complexity of the MTT problem is defined by its dimension S. Where S stands for the number of ’fences’ used in the problem, each fence consists of a set of observations that all originate from dierent targets. For a dimension of S ˃ the MTT problem becomes NP-hard. As of now no algorithm exists that can solve an NP-hard problem in an optimal manner within a reasonable (polynomial) computation time. However, there are algorithms that can approximate the solution with a realistic computational e ort. To this end an Elitist Genetic Algorithm is implemented to approximately solve the S ˃ MTT problem in an e cient manner. Its complexity is studied and it is found that an approximate solution can be obtained in a polynomial time. With the advent of improved sensors and a heightened interest in the problem of space debris, it is expected that the number of tracked objects will grow by an order of magnitude in the near future. This research aims to provide a method that can treat the correlation and orbit determination problems simultaneously, and is able to e ciently process large data sets with minimal manual intervention.

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Tropical forests are believed to be very harsh environments for human life. It is unclear whether human beings would have ever subsisted in those environments without external resources. It is therefore possible that humans have developed recent biological adaptations in response to specific selective pressures to cope with this challenge. To understand such biological adaptations we analyzed genome-wide SNP data under a Bayesian statistics framework, looking for outlier markers with an overly large extent of differentiation between populations living in a tropical forest, as compared to genetically related populations living outside the forest in Africa and the Americas. The most significant positive selection signals were found in genes related to lipid metabolism, the immune system, body development, and RNA Polymerase III transcription initiation. The results are discussed in the light of putative tropical forest selective pressures, namely food scarcity, high prevalence of pathogens, difficulty to move, and inefficient thermoregulation. Agreement between our results and previous studies on the pygmy phenotype, a putative prototype of forest adaptation, were found, suggesting that a few genetic regions previously described as associated with short stature may be evolving under similar positive selection in Africa and the Americas. In general, convergent evolution was less pervasive than local adaptation in one single continent, suggesting that Africans and Amerindians may have followed different routes to adapt to similar environmental selective pressures.

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Schmallenberg virus (SBV), an arthropod-borne orthobunyavirus was first detected in 2011 in cattle suffering from diarrhea and fever. The most severe impact of an SBV infection is the induction of malformations in newborns and abortions. Between 2011 and 2013 SBV spread throughout Europe in an unprecedented epidemic wave. SBV contains a tripartite genome consisting of the three negative-sense RNA segments L, M, and S. The virus is usually isolated from clinical samples by inoculation of KC (insect) or BHK-21 (mammalian) cells. Several virus passages are required to allow adaptation of SBV to cells in vitro. In the present study, the porcine SK-6 cell line was used for isolation and passaging of SBV. SK-6 cells proved to be more sensitive to SBV infection and allowed to produce higher titers more rapidly as in BHK-21 cells after just one passage. No adaptation was required. In order to determine the in vivo genetic stability of SBV during an epidemic spread of the virus the nucleotide sequence of the genome from seven SBV field isolates collected in summer 2012 in Switzerland was determined and compared to other SBV sequences available in GenBank. A total of 101 mutations, mostly transitions randomly dispersed along the L and M segment were found when the Swiss isolates were compared to the first SBV isolated late 2011 in Germany. However, when these mutations were studied in detail, a previously described hypervariable region in the M segment was identified. The S segment was completely conserved among all sequenced SBV isolates. To assess the in vitro genetic stability of SBV, three isolates were passage 10 times in SK-6 cells and sequenced before and after passaging. Between two and five nt exchanges per genome were found. This low in vitro mutation rate further demonstrates the suitability of SK-6 cells for SBV propagation.

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Gene flow is usually thought to reduce genetic divergence and impede local adaptation by homogenising gene pools between populations. However, evidence for local adaptation and phenotypic differentiation in highly mobile species, experiencing high levels of gene flow, is emerging. Assessing population genetic structure at different spatial scales is thus a crucial step towards understanding mechanisms underlying intraspecific differentiation and diversification. Here, we studied the population genetic structure of a highly mobile species – the great tit Parus major – at different spatial scales. We analysed 884 individuals from 30 sites across Europe including 10 close-by sites (< 50 km), using 22 microsatellite markers. Overall we found a low but significant genetic differentiation among sites (FST = 0.008). Genetic differentiation was higher, and genetic diversity lower, in south-western Europe. These regional differences were statistically best explained by winter temperature. Overall, our results suggest that great tits form a single patchy metapopulation across Europe, in which genetic differentiation is independent of geographical distance and gene flow may be regulated by environmental factors via movements related to winter severity. This might have important implications for the evolutionary trajectories of sub-populations, especially in the context of climate change, and calls for future investigations of local differences in costs and benefits of philopatry at large scales.