Genetic differentiation across the social transition in a socially polymorphic sweat bee, Halictus rubicundus

Eusociality is widely considered a major evolutionary transition. The socially polymorphic sweat bee Halictus rubicundus, solitary in cooler regions of its holarctic range and eusocial in warmer parts, is an excellent model organism to address this transition, and specifically the question of whether sociality is associated with a strong barrier to gene flow between phenotypically divergent populations. Mitochondrial DNA (COI) from specimens collected across the British Isles, where both solitary and social phenotypes are represented, displayed limited variation, but placed all specimens in the same European lineage; haplotype network analysis failed to differentiate solitary and social lineages. Microsatellite genetic variability was high and enabled us to quantify genetic differentiation among populations and social phenotypes across Great Britain and Ireland. Results from conceptually different analyses consistently showed greater genetic differentiation between geographically distant populations, independently of their social phenotype, suggesting that the two social forms are not reproductively isolated. A landscape genetic approach revealed significant isolation by distance (Mantel test r = 0.622, p

Convergent evolutionary processes driven by foraging opportunity in two sympatric morph pairs of Arctic charr with contrasting post-glacial origins

The expression of two or more discrete phenotypes amongst individuals within a species (morphs) provides multiple modes upon which selection can act semi-independently, and thus may be an important stage in speciation. In the present study, we compared two sympatric morph systems aiming to address hypotheses related to their evolutionary origin. Arctic charr in sympatry in Loch Tay, Scotland, exhibit one of two discrete, alternative body size phenotypes at maturity (large or small body size). Arctic charr in Loch Awe segregate into two temporally segregated spawning groups (breeding in either spring or autumn). Mitochondrial DNA restriction fragment length polymorphism analysis showed that the morph pairs in both lakes comprise separate gene pools, although segregation of the Loch Awe morphs is more subtle than that of Loch Tay. We conclude that the Loch Awe morphs diverged in situ (within the lake), whereas Loch Tay morphs most likely arose through multiple invasions by different ancestral groups that segregated before post-glacial invasion (i.e. in allopatry). Both morph pairs showed clear trophic segregation between planktonic and benthic resources (measured by stable isotope analysis) but this was significantly less distinct in Loch Tay than in Loch Awe. By contrast, both inter-morph morphological and life-history differences were more subtle in Loch Awe than in Loch Tay. The strong ecological but relatively weak morphological and life-history divergence of the in situ derived morphs compared to morphs with allopatric origins indicates a strong link between early ecological and subsequent genetic divergence of sympatric origin emerging species pairs. The emergence of parallel specialisms despite distinct genetic origins of these morph pairs suggests that the effect of available foraging opportunities may be at least as important as genetic origin in structuring sympatric divergence in post-glacial fishes with high levels of phenotypic plasticity. (c) 2012 The Linnean Society of London, Biological Journal of the Linnean Society, 2012, , .

Parallel and nonparallel ecological, morphological and genetic divergence in lake-stream stickleback from a single catchment

Parallel phenotypic evolution in similar environments has been well studied in evolutionary biology; however, comparatively little is known about the influence of determinism and historical contingency on the nature, extent and generality of this divergence. Taking advantage of a novel system containing multiple lake-stream stickleback populations, we examined the extent of ecological, morphological and genetic divergence between three-spined stickleback present in parapatric environments. Consistent with other lake-stream studies, we found a shift towards a deeper body and shorter gill rakers in stream fish. Morphological shifts were concurrent with changes in diet, indicated by both stable isotope and stomach contents analysis. Performing a multivariate test for shared and unique components of evolutionary response to the distance gradient from the lake, we found a strong signature of parallel adaptation. Nonparallel divergence was also present, attributable mainly to differences between river locations. We additionally found evidence of genetic substructuring across five lake-stream transitions, indicating that some level of reproductive isolation occurs between populations in these habitats. Strong correlations between pairwise measures of morphological, ecological and genetic distance between lake and stream populations supports the hypothesis that divergent natural selection between habitats drives adaptive divergence and reproductive isolation. Lake-stream stickleback divergence in Lough Neagh provides evidence for the deterministic role of selection and supports the hypothesis that parallel selection in similar environments may initiate parallel speciation.

Parallel patterns + Macro Data Flow for multi-core programming

Data flow techniques have been around since the early '70s when they were used in compilers for sequential languages. Shortly after their introduction they were also consideredas a possible model for parallel computing, although the impact here was limited. Recently, however, data flow has been identified as a candidate for efficient implementation of various programming models on multi-core architectures. In most cases, however, the burden of determining data flow "macro" instructions is left to the programmer, while the compiler/run time system manages only the efficient scheduling of these instructions. We discuss a structured parallel programming approach supporting automatic compilation of programs to macro data flow and we show experimental results demonstrating the feasibility of the approach and the efficiency of the resulting "object" code on different classes of state-of-the-art multi-core architectures. The experimental results use different base mechanisms to implement the macro data flow run time support, from plain pthreads with condition variables to more modern and effective lock- and fence-free parallel frameworks. Experimental results comparing efficiency of the proposed approach with those achieved using other, more classical, parallel frameworks are also presented. © 2012 IEEE.

Restrospective genetic monitoring of the threatened Yellow marsh saxifrage (Saxifraga hirculus) reveals genetic erosion but provides valuable information for conservation strategies

Aim: Retrospective genetic monitoring, comparing genetic diversity of extant populations with historical samples, can provide valuable and often unique insights into evolutionary processes informing conservation strategies. The Yellow marsh saxifrage (Saxifraga hirculus) is listed as ‘critically endangered’ in Ireland with only two extant populations. We quantified genetic changes over time and identified genotypes in extant populations that could be used as founders for reintroductions to sites where the species is extinct.

Location: Ireland.

Methods: Samples were obtained from both locations where the species is currently found, including the most threatened site at the Garron Plateau, Co. Antrim, which held only 13 individuals during 2011. Herbarium samples covering the period from 1886 to 1957 were obtained including plants from the same area as the most threatened population, as well as three extinct populations. In total, 422 individuals (319 present-day and 103 historical) were genotyped at six microsatellite loci. Species distribution modelling was used to identify areas of potentially suitable habitat for reintroductions.

Results: Level of phenotypic diversity within the most threatened population was significantly lower in the present-day compared with historical samples but levels of observed heterozygosity and number of alleles, whilst reduced, did not differ significantly. However, Bayesian clustering analysis suggested gradual lineage replacement over time. All three measures of genetic diversity were generally lower at the most threatened population compared with the more substantial extant populations in Co. Mayo. Species distribution modelling suggested that habitat at one site where the species is extinct may be suitable for reintroduction.

Main conclusions: The dominant genetic lineage in the most threatened population is rare elsewhere; thus, care needs to be taken when formulating any potential reintroduction programme. Our findings highlight both the need for genetic monitoring of threatened populations, but also for its swift implementation before levels of diversity become critically low.

Hybrid address spaces: A methodology for implementing scalable high-level programming models on non-coherent many-core architectures

This paper introduces hybrid address spaces as a fundamental design methodology for implementing scalable runtime systems on many-core architectures without hardware support for cache coherence. We use hybrid address spaces for an implementation of MapReduce, a programming model for large-scale data processing, and the implementation of a remote memory access (RMA) model. Both implementations are available on the Intel SCC and are portable to similar architectures. We present the design and implementation of HyMR, a MapReduce runtime system whereby different stages and the synchronization operations between them alternate between a distributed memory address space and a shared memory address space, to improve performance and scalability. We compare HyMR to a reference implementation and we find that HyMR improves performance by a factor of 1.71× over a set of representative MapReduce benchmarks. We also compare HyMR with Phoenix++, a state-of-art implementation for systems with hardware-managed cache coherence in terms of scalability and sustained to peak data processing bandwidth, where HyMR demon- strates improvements of a factor of 3.1× and 3.2× respectively. We further evaluate our hybrid remote memory access (HyRMA) programming model and assess its performance to be superior of that of message passing.

Enhancing Linear Programming with Motion Modeling for Multi-target Tracking

In this paper we extend the minimum-cost network flow approach to multi-target tracking, by incorporating a motion model, allowing the tracker to better cope with longterm occlusions and missed detections. In our new method, the tracking problem is solved iteratively: Firstly, an initial tracking solution is found without the help of motion information. Given this initial set of tracklets, the motion at each detection is estimated, and used to refine the tracking solution.
Finally, special edges are added to the tracking graph, allowing a further revised tracking solution to be found, where distant tracklets may be linked based on motion similarity. Our system has been tested on the PETS S2.L1 and Oxford town-center sequences, outperforming the baseline system, and achieving results comparable with the current state of the art.

Pool Evolution: A Parallel Pattern for Evolutionary and Symbolic Computing

We introduce a new parallel pattern derived from a specific application domain and show how it turns out to have application beyond its domain of origin. The pool evolution pattern models the parallel evolution of a population subject to mutations and evolving in such a way that a given fitness function is optimized. The pattern has been demonstrated to be suitable for capturing and modeling the parallel patterns underpinning various evolutionary algorithms, as well as other parallel patterns typical of symbolic computation. In this paper we introduce the pattern, we discuss its implementation on modern multi/many core architectures and finally present experimental results obtained with FastFlow and Erlang implementations to assess its feasibility and scalability.

Computational scheduling methods for integrating plug-in electric vehicles with power systems: a review

Traditional internal combustion engine vehicles are a major contributor to global greenhouse gas emissions and other air pollutants, such as particulate matter and nitrogen oxides. If the tail pipe point emissions could be managed centrally without reducing the commercial and personal user functionalities, then one of the most attractive solutions for achieving a significant reduction of emissions in the transport sector would be the mass deployment of electric vehicles. Though electric vehicle sales are still hindered by battery performance, cost and a few other technological bottlenecks, focused commercialisation and support from government policies are encouraging large scale electric vehicle adoptions. The mass proliferation of plug-in electric vehicles is likely to bring a significant additional electric load onto the grid creating a highly complex operational problem for power system operators. Electric vehicle batteries also have the ability to act as energy storage points on the distribution system. This double charge and storage impact of many uncontrollable small kW loads, as consumers will want maximum flexibility, on a distribution system which was originally not designed for such operations has the potential to be detrimental to grid balancing. Intelligent scheduling methods if established correctly could smoothly integrate electric vehicles onto the grid. Intelligent scheduling methods will help to avoid cycling of large combustion plants, using expensive fossil fuel peaking plant, match renewable generation to electric vehicle charging and not overload the distribution system causing a reduction in power quality. In this paper, a state-of-the-art review of scheduling methods to integrate plug-in electric vehicles are reviewed, examined and categorised based on their computational techniques. Thus, in addition to various existing approaches covering analytical scheduling, conventional optimisation methods (e.g. linear, non-linear mixed integer programming and dynamic programming), and game theory, meta-heuristic algorithms including genetic algorithm and particle swarm optimisation, are all comprehensively surveyed, offering a systematic reference for grid scheduling considering intelligent electric vehicle integration.

Molecular pedigree reconstruction and estimation of evolutionary parameters in a wild Atlantic salmon river system with incomplete sampling: a power analysis

Background: Pedigree reconstruction using genetic analysis provides a useful means to estimate fundamental population biology parameters relating to population demography, trait heritability and individual fitness when combined with other sources of data. However, there remain limitations to pedigree reconstruction in wild populations, particularly in systems where parent-offspring relationships cannot be directly observed, there is incomplete sampling of individuals, or molecular parentage inference relies on low quality DNA from archived material. While much can still be inferred from incomplete or sparse pedigrees, it is crucial to evaluate the quality and power of available genetic information a priori to testing specific biological hypotheses. Here, we used microsatellite markers to reconstruct a multi-generation pedigree of wild Atlantic salmon (Salmo salar L.) using archived scale samples collected with a total trapping system within a river over a 10 year period. Using a simulation-based approach, we determined the optimal microsatellite marker number for accurate parentage assignment, and evaluated the power of the resulting partial pedigree to investigate important evolutionary and quantitative genetic characteristics of salmon in the system.

Results: We show that at least 20 microsatellites (ave. 12 alleles/locus) are required to maximise parentage assignment and to improve the power to estimate reproductive success and heritability in this study system. We also show that 1.5 fold differences can be detected between groups simulated to have differing reproductive success, and that it is possible to detect moderate heritability values for continuous traits (h(2) similar to 0.40) with more than 80% power when using 28 moderately to highly polymorphic markers.

Conclusion: The methodologies and work flow described provide a robust approach for evaluating archived samples for pedigree-based research, even where only a proportion of the total population is sampled. The results demonstrate the feasibility of pedigree-based studies to address challenging ecological and evolutionary questions in free-living populations, where genealogies can be traced only using molecular tools, and that significant increases in pedigree assignment power can be achieved by using higher numbers of markers.

Optimal design of cold-formed steel portal frames for stressed-skin action using genetic algorithm

This paper describes a stressed-skin diaphragm approach to the optimal design of the internal frame of a cold-formed steel portal framing system, in conjunction with the effect of semi-rigid joints. Both ultimate and serviceability limit states are considered. Wind load combinations are included. The designs are optimized using a real-coded niching genetic algorithm, in which both discrete and continuous decision variables are processed. For a building with two internal frames, it is shown that the material cost of the internal frame can be reduced by as much as 53%, compared with a design that ignores stressed-skin action.

Outlier SNP markers reveal fine-scale genetic structuring across European hake populations (Merluccius merluccius)

Shallow population structure is generally reported for most marine fish and explained as a consequence of high dispersal, connectivity and large population size. Targeted gene analyses and more recently genome-wide studies have challenged such view, suggesting that adaptive divergence might occur even when neutral markers provide genetic homogeneity across populations. Here, 381 SNPs located in transcribed regions were used to assess large- and fine-scale population structure in the European hake (Merluccius merluccius), a widely distributed demersal species of high priority for the European fishery. Analysis of 850 individuals from 19 locations across the entire distribution range showed evidence for several outlier loci, with significantly higher resolving power. While 299 putatively neutral SNPs confirmed the genetic break between basins (F(CT) = 0.016) and weak differentiation within basins, outlier loci revealed a dramatic divergence between Atlantic and Mediterranean populations (F(CT) range 0.275-0.705) and fine-scale significant population structure. Outlier loci separated North Sea and Northern Portugal populations from all other Atlantic samples and revealed a strong differentiation among Western, Central and Eastern Mediterranean geographical samples. Significant correlation of allele frequencies at outlier loci with seawater surface temperature and salinity supported the hypothesis that populations might be adapted to local conditions. Such evidence highlights the importance of integrating information from neutral and adaptive evolutionary patterns towards a better assessment of genetic diversity. Accordingly, the generated outlier SNP data could be used for tackling illegal practices in hake fishing and commercialization as well as to develop explicit spatial models for defining management units and stock boundaries.

Inbreeding uncovers fundamental differences in the genetic load affecting male and female fertility in a butterfly

Inbreeding depression is most pronounced for traits closely associated with fitness. The traditional explanation is that natural selection eliminates deleterious mutations with additive or dominant effects more effectively than recessive mutations, leading to directional dominance for traits subject to strong directional selection. Here we report the unexpected finding that, in the butterfly Bicyclus anynana, male sterility contributes disproportionately to inbreeding depression for fitness (complete sterility in about half the sons from brother-sister matings), while female fertility is insensitive to inbreeding. The contrast between the sexes for functionally equivalent traits is inconsistent with standard selection arguments, and suggests that trait-specific developmental properties and cryptic selection play crucial roles in shaping genetic architecture. There is evidence that spermatogenesis is less developmentally stable than oogenesis, though the unusually high male fertility load in B. anynana additionally suggests the operation of complex selection maintaining male sterility recessives. Analysis of the precise causes of inbreeding depression will be needed to generate a model that reliably explains variation in directional dominance and reconciles the gap between observed and expected genetic loads carried by populations. This challenging evolutionary puzzle should stimulate work on the occurrence and causes of sex differences in fertility load.

Directional genetic differentiation and relative migration

Understanding the population structure and patterns of gene flow within species is of fundamental importance to the study of evolution. In the fields of population and evolutionary genetics, measures of genetic differentiation are commonly used to gather this information. One potential caveat is that these measures assume gene flow to be symmetric. However, asymmetric gene flow is common in nature, especially in systems driven by physical processes such as wind or water currents. As information about levels of asymmetric gene flow among populations is essential for the correct interpretation of the distribution of contemporary genetic diversity within species, this should not be overlooked. To obtain information on asymmetric migration patterns from genetic data, complex models based on maximum-likelihood or Bayesian approaches generally need to be employed, often at great computational cost. Here, a new simpler and more efficient approach for understanding gene flow patterns is presented. This approach allows the estimation of directional components of genetic divergence between pairs of populations at low computational effort, using any of the classical or modern measures of genetic differentiation. These directional measures of genetic differentiation can further be used to calculate directional relative migration and to detect asymmetries in gene flow patterns. This can be done in a user-friendly web application called divMigrate-online introduced in this study. Using simulated data sets with known gene flow regimes, we demonstrate that the method is capable of resolving complex migration patterns under a range of study designs.