Evolutionary placement of continuously operating reference stations of network Real-Time Kinematic

Network RTK (Real-Time Kinematic) is a technology that is based on GPS (Global Positioning System) or more generally on GNSS (Global Navigation Satellite System) observations to achieve centimeter-level accuracy positioning in real time. It is enabled by a network of Continuously Operating Reference Stations (CORS). CORS placement is an important problem in the design of network RTK as it directly affects not only the installation and running costs of the network RTK, but also the Quality of Service (QoS) provided by the network RTK. In our preliminary research on the CORS placement, we proposed a polynomial heuristic algorithm for a so-called location-based CORS placement problem. From a computational point of view, the location-based CORS placement is a largescale combinatorial optimization problem. Thus, although the heuristic algorithm is efficient in computation time it may not be able to find an optimal or near optimal solution. Aiming at improving the quality of solutions, this paper proposes a repairing genetic algorithm (RGA) for the location-based CORS placement problem. The RGA has been implemented and compared to the heuristic algorithm by experiments. Experimental results have shown that the RGA produces better quality of solutions than the heuristic algorithm.

A parallel cooperative co-evolutionary genetic algorithm for the composite SaaS placement problem in Cloud computing

A composite SaaS (Software as a Service) is a software that is comprised of several software components and data components. The composite SaaS placement problem is to determine where each of the components should be deployed in a cloud computing environment such that the performance of the composite SaaS is optimal. From the computational point of view, the composite SaaS placement problem is a large-scale combinatorial optimization problem. Thus, an Iterative Cooperative Co-evolutionary Genetic Algorithm (ICCGA) was proposed. The ICCGA can find reasonable quality of solutions. However, its computation time is noticeably slow. Aiming at improving the computation time, we propose an unsynchronized Parallel Cooperative Co-evolutionary Genetic Algorithm (PCCGA) in this paper. Experimental results have shown that the PCCGA not only has quicker computation time, but also generates better quality of solutions than the ICCGA.

Mitochondrial genome deletions and minicircles are common in lice (Insecta: Phthiraptera)

Background The gene composition, gene order and structure of the mitochondrial genome are remarkably stable across bilaterian animals. Lice (Insecta: Phthiraptera) are a major exception to this genomic stability in that the canonical single chromosome with 37 genes found in almost all other bilaterians has been lost in multiple lineages in favour of multiple, minicircular chromosomes with less than 37 genes on each chromosome. Results Minicircular mt genomes are found in six of the ten louse species examined to date and three types of minicircles were identified: heteroplasmic minicircles which coexist with full sized mt genomes (type 1); multigene chromosomes with short, simple control regions, we infer that the genome consists of several such chromosomes (type 2); and multiple, single to three gene chromosomes with large, complex control regions (type 3). Mapping minicircle types onto a phylogenetic tree of lice fails to show a pattern of their occurrence consistent with an evolutionary series of minicircle types. Analysis of the nuclear-encoded, mitochondrially-targetted genes inferred from the body louse, Pediculus, suggests that the loss of mitochondrial single-stranded binding protein (mtSSB) may be responsible for the presence of minicircles in at least species with the most derived type 3 minicircles (Pediculus, Damalinia). Conclusions Minicircular mt genomes are common in lice and appear to have arisen multiple times within the group. Life history adaptive explanations which attribute minicircular mt genomes in lice to the adoption of blood-feeding in the Anoplura are not supported by this expanded data set as minicircles are found in multiple non-blood feeding louse groups but are not found in the blood-feeding genus Heterodoxus. In contrast, a mechanist explanation based on the loss of mtSSB suggests that minicircles may be selectively favoured due to the incapacity of the mt replisome to synthesize long replicative products without mtSSB and thus the loss of this gene lead to the formation of minicircles in lice.

A mitochondrial genome phylogeny of termites (Blattodea: Termitoidae) : robust support for interfamilial relationships and molecular synapomorphies define major clades

Despite their ecological significance as decomposers and their evolutionary significance as the most speciose eusocial insect group outside the Hymenoptera, termite (Blattodea: Termitoidae or Isoptera) evolutionary relationships have yet to be well resolved. Previous morphological and molecular analyses strongly conflict at the family level and are marked by poor support for backbone nodes. A mitochondrial (mt) genome phylogeny of termites was produced to test relationships between the recognised termite families, improve nodal support and test the phylogenetic utility of rare genomic changes found in the termite mt genome. Complete mt genomes were sequenced for 7 of the 9 extant termite families with additional representatives of each of the two most speciose families Rhinotermitidae (3 of 7 subfamilies) and Termitidae (3 of 8 subfamilies). The mt genome of the well supported sister group of termites, the subsocial cockroach Cryptocercus, was also sequenced. A highly supported tree of termite relationships was produced by all analytical methods and data treatment approaches, however the relationship of the termites + Cryptocercus clade to other cockroach lineages was highly affected by the strong nucleotide compositional bias found in termites relative to other dictyopterans. The phylogeny supports previously proposed suprafamilial termite lineages, the Euisoptera and Neoisoptera, a later derived Kalotermitidae as sister group of the Neoisoptera and a monophyletic clade of dampwood (Stolotermitidae, Archotermopsidae) and harvester termites (Hodotermitidae). In contrast to previous termite phylogenetic studies, nodal supports were very high for family-level relationships within termites. Two rare genomic changes in the mt genome control region were found to be molecular synapomorphies for major clades. An elongated stem-loop structure defined the clade Polyphagidae + (Cryptocercus + termites), and a further series of compensatory base changes in this stem loop is synapomorphic for the Neoisoptera. The complicated repeat structures first identified in Reticulitermes, composed of short (A-type) and long (B-type repeats) defines the clade Heterotermitinae + Termitidae, while the secondary loss of A-type repeats is synapomorphic for the non-macrotermitine Termitidae.

A human-simulated immune evolutionary computation approach

Premature convergence to local optimal solutions is one of the main difficulties when using evolutionary algorithms in real-world optimization problems. To prevent premature convergence and degeneration phenomenon, this paper proposes a new optimization computation approach, human-simulated immune evolutionary algorithm (HSIEA). Considering that the premature convergence problem is due to the lack of diversity in the population, the HSIEA employs the clonal selection principle of artificial immune system theory to preserve the diversity of solutions for the search process. Mathematical descriptions and procedures of the HSIEA are given, and four new evolutionary operators are formulated which are clone, variation, recombination, and selection. Two benchmark optimization functions are investigated to demonstrate the effectiveness of the proposed HSIEA.

An expressed sequence tag (EST) library for Drosophila serrata, a model system for sexual selection and climatic adaptation studies

The native Australian fly Drosophila serrata belongs to the highly speciose montium subgroup of the melanogaster species group. It has recently emerged as an excellent model system with which to address a number of important questions, including the evolution of traits under sexual selection and traits involved in climatic adaptation along latitudinal gradients. Understanding the molecular genetic basis of such traits has been limited by a lack of genomic resources for this species. Here, we present the first expressed sequence tag (EST) collection for D. serrata that will enable the identification of genes underlying sexually-selected phenotypes and physiological responses to environmental change and may help resolve controversial phylogenetic relationships within the montium subgroup.

Gene duplication is an evolutionary mechanism for expanding spectral diversity in the long-wavelength photopigments of butterflies

Butterfly long-wavelength (L) photopigments are interesting for comparative studies of adaptive evolution because of the tremendous phenotypic variation that exists in their wavelength of peak absorbance (lambda(max) value). Here we present a comprehensive survey of L photopigment variation by measuring lambda(max) in 12 nymphalid and 1 riodinid species using epi-microspectrophotometry. Together with previous data, we find that L photopigment lambda(max) varies from 510-565 nm in 22 nymphalids, with an even broader 505- to 600-nm range in riodinids. We then surveyed the L opsin genes for which lambda(max) values are available as well as from related taxa and found 2 instances of L opsin gene duplication within nymphalids, in Hermeuptychia hermes and Amathusia phidippus, and 1 instance within riodinids, in the metalmark butterfly Apodemia mormo. Using maximum parsimony and maximum likelihood ancestral state reconstructions to map the evolution of spectral shifts within the L photopigments of nymphalids, we estimate the ancestral pigment had a lambda(max) = 540 nm +/- 10 nm standard error and that blueshifts in wavelength have occurred at least 4 times within the family. We used ancestral state reconstructions to investigate the importance of several amino acid substitutions (Ile17Met, Ala64Ser, Asn70Ser, and Ser137Ala) previously shown to have evolved under positive selection that are correlated with blue spectral shifts. These reconstructions suggest that the Ala64Ser substitution has indeed occurred along the newly identified blueshifted L photopigment lineages. Substitutions at the other 3 sites may also be involved in the functional diversification of L photopigments. Our data strongly suggest that there are limits to the evolution of L photopigment spectral shifts among species with only one L opsin gene and that opsin gene duplication broadens the potential range of lambda(max) values.

Beyond barcoding : a mitochondrial genomics approach to molecular phylogenetics and diagnostics of blowflies (Diptera: Calliphoridae)

Members of the Calliphoridae (blowflies) are significant for medical and veterinary management, due to the ability of some species to consume living flesh as larvae, and for forensic investigations due to the ability of others to develop in corpses. Due to the difficulty of accurately identifying larval blowflies to species there is a need for DNA-based diagnostics for this family, however the widely used DNA-barcoding marker, cox1, has been shown to fail for several groups within this family. Additionally, many phylogenetic relationships within the Calliphoridae are still unresolved, particularly deeper level relationships. Sequencing whole mt genomes has been demonstrated both as an effective method for identifying the most informative diagnostic markers and for resolving phylogenetic relationships. Twenty-seven complete, or nearly so, mt genomes were sequenced representing 13 species, seven genera and four calliphorid subfamilies and a member of the related family Tachinidae. PCR and sequencing primers developed for sequencing one calliphorid species could be reused to sequence related species within the same superfamily with success rates ranging from 61% to 100%, demonstrating the speed and efficiency with which an mt genome dataset can be assembled. Comparison of molecular divergences for each of the 13 protein-coding genes and 2 ribosomal RNA genes, at a range of taxonomic scales identified novel targets for developing as diagnostic markers which were 117–200% more variable than the markers which have been used previously in calliphorids. Phylogenetic analysis of whole mt genome sequences resulted in much stronger support for family and subfamily-level relationships. The Calliphoridae are polyphyletic, with the Polleninae more closely related to the Tachinidae, and the Sarcophagidae are the sister group of the remaining calliphorids. Within the Calliphoridae, there was strong support for the monophyly of the Chrysomyinae and Luciliinae and for the sister-grouping of Luciliinae with Calliphorinae. Relationships within Chrysomya were not well resolved. Whole mt genome data, supported the previously demonstrated paraphyly of Lucilia cuprina with respect to L. sericata and allowed us to conclude that it is due to hybrid introgression prior to the last common ancestor of modern sericata populations, rather than due to recent hybridisation, nuclear pseudogenes or incomplete lineage sorting.

The evolutionary value of recombination is constrained by genome modularity

Genetic recombination is a fundamental evolutionary mechanism promoting biological adaptation. Using engineered recombinants of the small single-stranded DNA plant virus, Maize streak virus (MSV), we experimentally demonstrate that fragments of genetic material only function optimally if they reside within genomes similar to those in which they evolved. The degree of similarity necessary for optimal functionality is correlated with the complexity of intragenomic interaction networks within which genome fragments must function. There is a striking correlation between our experimental results and the types of MSV recombinants that are detectable in nature, indicating that obligatory maintenance of intragenome interaction networks strongly constrains the evolutionary value of recombination for this virus and probably for genomes in general.

A highly divergent South African geminivirus species illuminates the ancient evolutionary history of this family

Background. We have characterised a new highly divergent geminivirus species, Eragrostis curvula streak virus (ECSV), found infecting a hardy perennial South African wild grass. ECSV represents a new genus-level geminivirus lineage, and has a mixture of features normally associated with other specific geminivirus genera. Results. Whereas the ECSV genome is predicted to express a replication associated protein (Rep) from an unspliced complementary strand transcript that is most similar to those of begomoviruses, curtoviruses and topocuviruses, its Rep also contains what is apparently a canonical retinoblastoma related protein interaction motif such as that found in mastreviruses. Similarly, while ECSV has the same unusual TAAGATTCC virion strand replication origin nonanucleotide found in another recently described divergent geminivirus, Beet curly top Iran virus (BCTIV), the rest of the transcription and replication origin is structurally more similar to those found in begomoviruses and curtoviruses than it is to those found in BCTIV and mastreviruses. ECSV also has what might be a homologue of the begomovirus transcription activator protein gene found in begomoviruses, a mastrevirus-like coat protein gene and two intergenic regions. Conclusion. Although it superficially resembles a chimaera of geminiviruses from different genera, the ECSV genome is not obviously recombinant, implying that the features it shares with other geminiviruses are those that were probably present within the last common ancestor of these viruses. In addition to inferring how the ancestral geminivirus genome may have looked, we use the discovery of ECSV to refine various hypotheses regarding the recombinant origins of the major geminivirus lineages. © 2009 Varsani et al; licensee BioMed Central Ltd.

Prediction of transcriptional regulatory interactions in bacteria : a comparative genomics approach

Exponential growth of genomic data in the last two decades has made manual analyses impractical for all but trial studies. As genomic analyses have become more sophisticated, and move toward comparisons across large datasets, computational approaches have become essential. One of the most important biological questions is to understand the mechanisms underlying gene regulation. Genetic regulation is commonly investigated and modelled through the use of transcriptional regulatory network (TRN) structures. These model the regulatory interactions between two key components: transcription factors (TFs) and the target genes (TGs) they regulate. Transcriptional regulatory networks have proven to be invaluable scientific tools in Bioinformatics. When used in conjunction with comparative genomics, they have provided substantial insights into the evolution of regulatory interactions. Current approaches to regulatory network inference, however, omit two additional key entities: promoters and transcription factor binding sites (TFBSs). In this study, we attempted to explore the relationships among these regulatory components in bacteria. Our primary goal was to identify relationships that can assist in reducing the high false positive rates associated with transcription factor binding site predictions and thereupon enhance the reliability of the inferred transcription regulatory networks. In our preliminary exploration of relationships between the key regulatory components in Escherichia coli transcription, we discovered a number of potentially useful features. The combination of location score and sequence dissimilarity scores increased de novo binding site prediction accuracy by 13.6%. Another important observation made was with regards to the relationship between transcription factors grouped by their regulatory role and corresponding promoter strength. Our study of E.coli ��70 promoters, found support at the 0.1 significance level for our hypothesis | that weak promoters are preferentially associated with activator binding sites to enhance gene expression, whilst strong promoters have more repressor binding sites to repress or inhibit gene transcription. Although the observations were specific to �70, they nevertheless strongly encourage additional investigations when more experimentally confirmed data are available. In our preliminary exploration of relationships between the key regulatory components in E.coli transcription, we discovered a number of potentially useful features { some of which proved successful in reducing the number of false positives when applied to re-evaluate binding site predictions. Of chief interest was the relationship observed between promoter strength and TFs with respect to their regulatory role. Based on the common assumption, where promoter homology positively correlates with transcription rate, we hypothesised that weak promoters would have more transcription factors that enhance gene expression, whilst strong promoters would have more repressor binding sites. The t-tests assessed for E.coli �70 promoters returned a p-value of 0.072, which at 0.1 significance level suggested support for our (alternative) hypothesis; albeit this trend may only be present for promoters where corresponding TFBSs are either all repressors or all activators. Nevertheless, such suggestive results strongly encourage additional investigations when more experimentally confirmed data will become available. Much of the remainder of the thesis concerns a machine learning study of binding site prediction, using the SVM and kernel methods, principally the spectrum kernel. Spectrum kernels have been successfully applied in previous studies of protein classification [91, 92], as well as the related problem of promoter predictions [59], and we have here successfully applied the technique to refining TFBS predictions. The advantages provided by the SVM classifier were best seen in `moderately'-conserved transcription factor binding sites as represented by our E.coli CRP case study. Inclusion of additional position feature attributes further increased accuracy by 9.1% but more notable was the considerable decrease in false positive rate from 0.8 to 0.5 while retaining 0.9 sensitivity. Improved prediction of transcription factor binding sites is in turn extremely valuable in improving inference of regulatory relationships, a problem notoriously prone to false positive predictions. Here, the number of false regulatory interactions inferred using the conventional two-component model was substantially reduced when we integrated de novo transcription factor binding site predictions as an additional criterion for acceptance in a case study of inference in the Fur regulon. This initial work was extended to a comparative study of the iron regulatory system across 20 Yersinia strains. This work revealed interesting, strain-specific difierences, especially between pathogenic and non-pathogenic strains. Such difierences were made clear through interactive visualisations using the TRNDifi software developed as part of this work, and would have remained undetected using conventional methods. This approach led to the nomination of the Yfe iron-uptake system as a candidate for further wet-lab experimentation due to its potential active functionality in non-pathogens and its known participation in full virulence of the bubonic plague strain. Building on this work, we introduced novel structures we have labelled as `regulatory trees', inspired by the phylogenetic tree concept. Instead of using gene or protein sequence similarity, the regulatory trees were constructed based on the number of similar regulatory interactions. While the common phylogentic trees convey information regarding changes in gene repertoire, which we might regard being analogous to `hardware', the regulatory tree informs us of the changes in regulatory circuitry, in some respects analogous to `software'. In this context, we explored the `pan-regulatory network' for the Fur system, the entire set of regulatory interactions found for the Fur transcription factor across a group of genomes. In the pan-regulatory network, emphasis is placed on how the regulatory network for each target genome is inferred from multiple sources instead of a single source, as is the common approach. The benefit of using multiple reference networks, is a more comprehensive survey of the relationships, and increased confidence in the regulatory interactions predicted. In the present study, we distinguish between relationships found across the full set of genomes as the `core-regulatory-set', and interactions found only in a subset of genomes explored as the `sub-regulatory-set'. We found nine Fur target gene clusters present across the four genomes studied, this core set potentially identifying basic regulatory processes essential for survival. Species level difierences are seen at the sub-regulatory-set level; for example the known virulence factors, YbtA and PchR were found in Y.pestis and P.aerguinosa respectively, but were not present in both E.coli and B.subtilis. Such factors and the iron-uptake systems they regulate, are ideal candidates for wet-lab investigation to determine whether or not they are pathogenic specific. In this study, we employed a broad range of approaches to address our goals and assessed these methods using the Fur regulon as our initial case study. We identified a set of promising feature attributes; demonstrated their success in increasing transcription factor binding site prediction specificity while retaining sensitivity, and showed the importance of binding site predictions in enhancing the reliability of regulatory interaction inferences. Most importantly, these outcomes led to the introduction of a range of visualisations and techniques, which are applicable across the entire bacterial spectrum and can be utilised in studies beyond the understanding of transcriptional regulatory networks.

Hybrid game evolutionary algorithm for mission path planning of aerial survey tasks

The aim of this paper is to implement a Game-Theory based offline mission path planner for aerial inspection tasks of large linear infrastructures. Like most real-world optimisation problems, mission path planning involves a number of objectives which ideally should be minimised simultaneously. The goal of this work is then to develop a Multi-Objective (MO) optimisation tool able to provide a set of optimal solutions for the inspection task, given the environment data, the mission requirements and the definition of the objectives to minimise. Results indicate the robustness and capability of the method to find the trade-off between the Pareto-optimal solutions.

An evolutionary computation approach to three-dimensional path planning for unmanned aerial vehicles with tactical and kinematic constraints

This paper presents a novel evolutionary computation approach to three-dimensional path planning for unmanned aerial vehicles (UAVs) with tactical and kinematic constraints. A genetic algorithm (GA) is modified and extended for path planning. Two GAs are seeded at the initial and final positions with a common objective to minimise their distance apart under given UAV constraints. This is accomplished by the synchronous optimisation of subsequent control vectors. The proposed evolutionary computation approach is called synchronous genetic algorithm (SGA). The sequence of control vectors generated by the SGA constitutes to a near-optimal path plan. The resulting path plan exhibits no discontinuity when transitioning from curve to straight trajectories. Experiments and results show that the paths generated by the SGA are within 2% of the optimal solution. Such a path planner when implemented on a hardware accelerator, such as field programmable gate array chips, can be used in the UAV as on-board replanner, as well as in ground station systems for assisting in high precision planning and modelling of mission scenarios.

A strong quantitative trait locus for wing length on chromosome 2 in a wild population of great reed warblers

Wing length is a key character for essential behaviours related to bird flight such as migration and foraging. In the present study, we initiate the search for the genes underlying wing length in birds by studying a long-distance migrant, the great reed warbler (Acrocephalus arundinaceus). In this species wing length is an evolutionary interesting trait with pronounced latitudinal gradient and sex-specific selection regimes in local populations. We performed a quantitative trait locus (QTL) scan for wing length in great reed warblers using phenotypic, genotypic, pedigree and linkage map data from our long-term study population in Sweden. We applied the linkage analysis mapping method implemented in GRIDQTL (a new web-based software) and detected a genome-wide significant QTL for wing length on chromosome 2, to our knowledge, the first detected QTL in wild birds. The QTL extended over 25 cM and accounted for a substantial part (37%) of the phenotypic variance of the trait. A genome scan for tarsus length (a bodysize-related trait) did not show any signal, implying that the wing-length QTL on chromosome 2 was not associated with body size. Our results provide a first important step into understanding the genetic architecture of avian wing length, and give opportunities to study the evolutionary dynamics of wing length at the locus level. This journal is© 2010 The Royal Society.