Branching genes are conserved across species. Genes controlling a novel signal in pea are coregulated by other long-distance signals

Physiological and genetic studies with the ramosus (rms) mutants in garden pea (Pisum sativum) and more axillary shoots (max) mutants in Arabidopsis (Arabidopsis thaliana) have shown that shoot branching is regulated by a network of long-distance signals. Orthologous genes RMS1 and MAX4 control the synthesis of a novel graft-transmissible branching signal that may be a carotenoid derivative and acts as a branching inhibitor. In this study, we demonstrate further conservation of the branching control system by showing that MAX2 and MAX3 are orthologous to RMS4 and RMS5, respectively. This is consistent with the longstanding hypothesis that branching in pea is regulated by a novel long-distance signal produced by RMS1 and RMS5 and that RMS4 is implicated in the response to this signal. We examine RMS5 expression and show that it is more highly expressed relative to RMS1, but under similar transcriptional regulation as RMS1. Further expression studies support the hypothesis that RMS4 functions in shoot and rootstock and participates in the feedback regulation of RMS1 and RMS5 expression. This feedback involves a second novel long-distance signal that is lacking in rms2 mutants. RMS1 and RMS5 are also independently regulated by indole-3-acetic acid. RMS1, rather than RMS5, appears to be a key regulator of the branching inhibitor. This study presents new interactions between RMS genes and provides further evidence toward the ongoing elucidation of a model of axillary bud outgrowth in pea.

Modelling the dynamics of genetic algorithms using statistical mechanics

A formalism for modelling the dynamics of Genetic Algorithms (GAs) using methods from statistical mechanics, originally due to Prugel-Bennett and Shapiro, is reviewed, generalized and improved upon. This formalism can be used to predict the averaged trajectory of macroscopic statistics describing the GA's population. These macroscopics are chosen to average well between runs, so that fluctuations from mean behaviour can often be neglected. Where necessary, non-trivial terms are determined by assuming maximum entropy with constraints on known macroscopics. Problems of realistic size are described in compact form and finite population effects are included, often proving to be of fundamental importance. The macroscopics used here are cumulants of an appropriate quantity within the population and the mean correlation (Hamming distance) within the population. Including the correlation as an explicit macroscopic provides a significant improvement over the original formulation. The formalism is applied to a number of simple optimization problems in order to determine its predictive power and to gain insight into GA dynamics. Problems which are most amenable to analysis come from the class where alleles within the genotype contribute additively to the phenotype. This class can be treated with some generality, including problems with inhomogeneous contributions from each site, non-linear or noisy fitness measures, simple diploid representations and temporally varying fitness. The results can also be applied to a simple learning problem, generalization in a binary perceptron, and a limit is identified for which the optimal training batch size can be determined for this problem. The theory is compared to averaged results from a real GA in each case, showing excellent agreement if the maximum entropy principle holds. Some situations where this approximation brakes down are identified. In order to fully test the formalism, an attempt is made on the strong sc np-hard problem of storing random patterns in a binary perceptron. Here, the relationship between the genotype and phenotype (training error) is strongly non-linear. Mutation is modelled under the assumption that perceptron configurations are typical of perceptrons with a given training error. Unfortunately, this assumption does not provide a good approximation in general. It is conjectured that perceptron configurations would have to be constrained by other statistics in order to accurately model mutation for this problem. Issues arising from this study are discussed in conclusion and some possible areas of further research are outlined.

A genetic algorithm to optimise the component placement process in the PCB assembly

In printed circuit board (PCB) assembly, the efficiency of the component placement process is dependent on two interrelated issues: the sequence of component placement, that is, the component sequencing problem, and the assignment of component types to feeders of the placement machine, that is, the feeder arrangement problem. In cases where some components with the same type are assigned to more than one feeder, the component retrieval problem should also be considered. Due to their inseparable relationship, a hybrid genetic algorithm is adopted to solve these three problems simultaneously for a type of PCB placement machines called the sequential pick-and-place (PAP) machine in this paper. The objective is to minimise the total distance travelled by the placement head for assembling all components on a PCB. Besides, the algorithm is compared with the methods proposed by other researchers in order to examine its effectiveness and efficiency.

A hybrid genetic algorithm for sequencing PCB component placement

A chip shooter machine for electronic components assembly has a movable feeder carrier holding components, a movable X-Y table carrying a printed circuit board (PCB), and a rotary turret having multiple assembly heads. This paper presents a hybrid genetic algorithm to optimize the sequence of component placements for a chip shooter machine. The objective of the problem is to minimize the total traveling distance of the X-Y table or the board. The genetic algorithm developed in the paper hybridizes the nearest neighbor heuristic, and an iterated swap procedure, which is a new improved heuristic. We have compared the performance of the hybrid genetic algorithm with that of the approach proposed by other researchers and have demonstrated our algorithm is superior in terms of the distance traveled by the X-Y table or the board.

A hybrid genetic algorithm for component sequencing and feeder arrangement

This paper presents a hybrid genetic algorithm to optimize the sequence of component placements on a printed circuit board and the arrangement of component types to feeders simultaneously for a pick-and-place machine with multiple stationary feeders, a fixed board table and a movable placement head. The objective of the problem is to minimize the total travelling distance, or the travelling time, of the placement head. The genetic algorithm developed in the paper hybrisizes different search heuristics including the nearest neighbor heuristic, the 2-opt heuristic, and an iterated swap procedure, which is a new improving heuristic. Compared with the results obtained by other researchers, the performance of the hybrid genetic algorithm is superior to others in terms of the distance travelled by the placement head.

Implementation of Genetic Algorithms for Transit Points Arrangement

The problem of transit points arrangement is presented in the paper. This issue is connected with accuracy of tariff distance calculation and it is the urgent problem at present. Was showed that standard method of tariff distance discovering is not optimal. The Genetic Algorithms are used in optimization problem resolution. The UML application class diagram and class content are showed. In the end the example of transit points arrangement is represented.

Lost at sea: Genetic, oceanographic and meteorological evidence for storm-forced dispersal

[EN] For many species, there is broad-scale dispersal of juvenile stages and/or long-distance migration of individuals and hence the processes that drive these various wide-ranging move- ments have important life-history consequences. Sea turtles are one of these paradigmatic long-distance travellers, with hatchlings thought to be dispersed by ocean currents and adults often shuttling between distant breeding and foraging grounds. Here, we use multi- disciplinary oceanographic, atmospheric and genetic mixed stock analyses to show that juvenile turtles are encountered ‘downstream’ at sites predicted by currents. However, in some cases, unusual occurrences of juveniles are more readily explained by storm events and we show that juvenile turtles may be displaced thousands of kilometres from their expected dispersal based on prevailing ocean currents.

Lost at sea: Genetic, oceanographic and meteorological evidence for storm-forced dispersal

[EN] For many species, there is broad-scale dispersal of juvenile stages and/or long-distance migration of individuals and hence the processes that drive these various wide-ranging move- ments have important life-history consequences. Sea turtles are one of these paradigmatic long-distance travellers, with hatchlings thought to be dispersed by ocean currents and adults often shuttling between distant breeding and foraging grounds. Here, we use multi- disciplinary oceanographic, atmospheric and genetic mixed stock analyses to show that juvenile turtles are encountered ‘downstream’ at sites predicted by currents. However, in some cases, unusual occurrences of juveniles are more readily explained by storm events and we show that juvenile turtles may be displaced thousands of kilometres from their expected dispersal based on prevailing ocean currents.

Genetic variation of temperature-regulated curd induction in cauliflower: elucidation of floral transition by genome-wide association mapping and gene expression analysis

Cauliflower (Brassica oleracea var. botrytis) is a vernalization-responsive crop. High ambient temperatures delay harvest time. The elucidation of the genetic regulation of floral transition is highly interesting for a precise harvest scheduling and to ensure stable market supply. This study aims at genetic dissection of temperature-dependent curd induction in cauliflower by genome-wide association studies and gene expression analysis. To assess temperature dependent curd induction, two greenhouse trials under distinct temperature regimes were conducted on a diversity panel consisting of 111 cauliflower commercial parent lines, genotyped with 14,385 SNPs. Broad phenotypic variation and high heritability (0.93) were observed for temperature-related curd induction within the cauliflower population. GWA mapping identified a total of 18 QTL localized on chromosomes O1, O2, O3, O4, O6, O8, and O9 for curding time under two distinct temperature regimes. Among those, several QTL are localized within regions of promising candidate flowering genes. Inferring population structure and genetic relatedness among the diversity set assigned three main genetic clusters. Linkage disequilibrium (LD) patterns estimated global LD extent of r(2) = 0.06 and a maximum physical distance of 400 kb for genetic linkage. Transcriptional profiling of flowering genes FLOWERING LOCUS C (BoFLC) and VERNALIZATION 2 (BoVRN2) was performed, showing increased expression levels of BoVRN2 in genotypes with faster curding. However, functional relevance of BoVRN2 and BoFLC2 could not consistently be supported, which probably suggests to act facultative and/or might evidence for BoVRN2/BoFLC-independent mechanisms in temperature regulated floral transition in cauliflower. Genetic insights in temperature-regulated curd induction can underpin genetically informed phenology models and benefit molecular breeding strategies toward the development of thermo-tolerant cultivars.

Absence of consistent genetic differentiation among several morphs of Actinia (Actiniaria: Actiniidae) occurring in the portuguese coast

Actinia equina, the beadlet sea anemone, is a very labile species, displaying variable colour patterns, broad habitat choice and diverse modes of reproduction. Historically, studies using genetic markers such as allozymes and differences in habitat choice lead several authors to propose that different colour morphs could represent different species. One of the species defined was A. fragacea. In this paper, the relationships between brown, red and green colour morphs of A. equina and A. fragacea were studied, using two DNA fragments (one mitochondrial and one nuclear). Individuals were sampled from three different areas in Portugal separated by a maximum distance of 500 km. This is the first study applying direct sequencing of selected gene fragments to approach the validity of Actinia morphs as different genetic entities. The results show that, at least in the Portuguese coast, these colour morphs do not correspond to the two valid species recognized in the literature. The existence of cryptic species is discussed.

Spatial patterns of genetic diversity in Mediterranean eagle owl Bubo bubo populations

Little information is available on the patterns of genetic connectivity in owls. We studied the genetic structure of the eagle owl Bubo bubo (Linnaeus, 1758) in southeastern Spain at two different spatial scales. Seven microsatellites previously described for this species were used, although only six loci amplified correctly. The observed low genetic variation could be explained by the short dispersal distance, high mortality rate and high degree of monogamy shown by this large nocturnal predator. As expected, the highest genetic isolation was detected in the geographically most isolated population. Significant genetic differentiation was found among study units separated by less than 50 km. The territorial analysis showed interesting connectivity patterns related with the gene flow and turnover rate of the breeding individuals. The lowest genetic diversity was found in the region with the largest population, which could imply incipient inbreeding.

Connectivity patterns inferred from the genetic structure of white seabream (Diplodus sargus L.)

Themarine environment seems, at first sight, to be a homogeneousmediumlacking barriers to species dispersal. Nevertheless, populations of marine species show varying levels of gene flow and population differentiation, so barriers to gene flow can often be detected. Weaimto elucidate the role of oceanographical factors ingenerating connectivity among populations shaping the phylogeographical patterns in the marine realm, which is not only a topic of considerable interest for understanding the evolution ofmarine biodiversity but also formanagement and conservation of marine life. For this proposal,we investigate the genetic structure and connectivity between continental and insular populations ofwhite seabreamin North East Atlantic (NEA) and Mediterranean Sea (MS) aswell as the influence of historical and contemporary factors in this scenario using mitochondrial (cytochrome b) and nuclear (a set of 9 microsatellite) molecular markers. Azores population appeared genetically differentiated in a single cluster using Structure analysis. This result was corroborated by Principal Component Analysis (PCA) and Monmonier algorithm which suggested a boundary to gene flow, isolating this locality. Azorean population also shows the highest significant values of FST and genetic distances for both molecular markers (microsatellites and mtDNA). We suggest that the breakdown of effective genetic exchange between Azores and the others' samples could be explained simultaneously by hydrographic (deep water) and hydrodynamic (isolating current regimes) factors acting as barriers to the free dispersal of white seabream(adults and larvae) and by historical factors which could be favoured for the survival of Azorean white seabream population at the last glaciation. Mediterranean islands show similar genetic diversity to the neighbouring continental samples and nonsignificant genetic differences. Proximity to continental coasts and the current system could promote an optimal larval dispersion among Mediterranean islands (Mallorca and Castellamare) and coasts with high gene flow.

High interannual variability in connectivity and genetic pool of a temperate clingfish matches oceanographic transport predictions

Adults of most marine benthic and demersal fish are site-attached, with the dispersal of their larval stages ensuring connectivity among populations. In this study we aimed to infer spatial and temporal variation in population connectivity and dispersal of a marine fish species, using genetic tools and comparing these with oceanographic transport. We focused on an intertidal rocky reef fish species, the shore clingfish Lepadogaster lepadogaster, along the southwest Iberian Peninsula, in 2011 and 2012. We predicted high levels of self-recruitment and distinct populations, due to short pelagic larval duration and because all its developmental stages have previously been found near adult habitats. Genetic analyses based on microsatellites countered our prediction and a biophysical dispersal model showed that oceanographic transport was a good explanation for the patterns observed. Adult sub-populations separated by up to 300 km of coastline displayed no genetic differentiation, revealing a single connected population with larvae potentially dispersing long distances over hundreds of km. Despite this, parentage analysis performed on recruits from one focal site within the Marine Park of Arrábida (Portugal), revealed self-recruitment levels of 2.5% and 7.7% in 2011 and 2012, respectively, suggesting that both long- and short-distance dispersal play an important role in the replenishment of these populations. Population differentiation and patterns of dispersal, which were highly variable between years, could be linked to the variability inherent in local oceanographic processes. Overall, our measures of connectivity based on genetic and oceanographic data highlight the relevance of long-distance dispersal in determining the degree of connectivity, even in species with short pelagic larval durations.