Transferring QTL technology to the pig breeding industry (PigQTech) - a demonstration project

The aim of the project has been to demonstrate how the farm animal breeding industry can utilise gene mapping technology to accelerate genetic improvement. Previous theoretical studies had suggested that the use of marker assisted selection could potentially increase the annual improvement for quantitative traits like backfat with about 10% and for more difficult traits such as meat quality and reproduction by as much as 40-60% compared with existing technology. The work has comprised two major tasks: 1. Commercially relevant populations have been screened for segregation at QTLs identified in experimental populations. The aim has been to establish optimal strategies for QTL detection in commercial pig populations and the extent to which QTLs explaining major phenotypic differences between divergent lines used in experimental studies also explain quantitative variation within commercial lines. The results are important for specifying future strategies for finding economically valuable QTLs. 2. Marker assisted backcrossing has been used to demonstrate how a QTL allele can be introgressed from one breed to another. The work has focused on the major fatness QTL on pig chromosome 4 previously identified in a wild pig/Large White intercross. The end result was not designed to be a commercially viable product in its own right, but the process has validated a number of points of major importance for the exploitation of QTLs in livestock.

Genetic variation for carbon isotope composition in Juglans regia L.: relationships with growth, phenology and climate of origin

Among the traits of breeding interest for the common walnut tree Juglans regia L., characteristics such as timing of budbreak and leaf fall, water-use efficiency and growth performance are regarded as being of utmost relevance in Mediterranean conditions. The authors evaluated intraspecific variation in $\delta$13C (carbon isotope composition, surrogate of intrinsic water-use efficiency, WUE$_{\rm i}$) for 22 J. regia families grown in a progeny test under supplementary irrigation, and investigated whether such variation correlated with climatic indicators of native habitats. The genetic relationships between $\delta$13C, growth and phenology were also assessed during two consecutive years. Overall, the most water-use-efficient families (i.e. with higher $\delta$13C), which originated mainly from drought-prone provenance regions which have a high vapour pressure deficit and low rainfall, exhibited less height growth and smaller DBH. Using a stepwise regression procedure, $\delta$13C was included as the main explanatory variable of genotypic variation in growth traits, together with growing season duration (for DBH in both years) and flushing (for height in 2007). It was concluded that WUE$_{\rm i}$ is largely unconnected to phenology effects in the explanation of growth performance for J. regia, therefore suggesting the opportunity of simultaneously selecting for low WUE$_{\rm i}$ and extended growing period to maximise productivity in non-water-limited environments.

Progress in the Spanish National Barley Breeding Program

The Spanish Barley Breeding Program is carried out by four public research organizations, located at the most representative barley growing regions of Spain. The aim of this study is to evaluate the program retrospectively, attending to: i) the progress achieved in grain yield, and ii) the extent and impact of genotype-by-environment interaction of grain yield. Grain yields and flowering dates of 349 advanced lines in generations F8, F9 and F10, plus checks, tested at 163 trials over 11 years were analized. The locations are in the provinces of Albacete, Lleida, Valladolid and Zaragoza. The data are highly unbalanced because the lines stayed at the program for a maximum of three years. Progress was estimated using relative grain yield and mixed models (REML) to homogenize the results among years and locations. There was evident progress in the program over the period studied, with increasing relative yields in each generation, and with advanced lines surpassing the checks in the last two generations, although the rate of progress was uneven across locations. The genetic gain was greater from F8 to F9 than from F9 to F10. The largest non-purely environmental component of variance was genotype-by-location-by-year, meaning that the genotype-by-location pattern was highly unpredictable. The relationship between yield and flowering time overall was weak in the locations under study at this advanced stage of the program. The program can be continued with the same structure, although measures should be taken to explore the causes of slower progress at certain locations.

Population connectivity buffers genetic diversity loss in a seabird

Background Ancient DNA has revolutionized conservation genetic studies as it allows monitoring of the genetic variability of species through time and predicting the impact of ecosystems" threats on future population dynamics and viability. Meanwhile, the consequences of anthropogenic activities and climate change to island faunas, particularly seabirds, remain largely unknown. In this study, we examined temporal changes in the genetic diversity of a threatened seabird, the Cory"s shearwater (Calonectris borealis). Findings We analysed the mitochondrial DNA control region of ancient bone samples from the late-Holocene retrieved from the Canary archipelago (NE Atlantic) together with modern DNA sequences representative of the entire breeding range of the species. Our results show high levels of ancient genetic diversity in the Canaries comparable to that of the extant population. The temporal haplotype network further revealed rare but recurrent long-distance dispersal between ocean basins. The Bayesian demographic analyses reveal both regional and local population size expansion events, and this is in spite of the demographic decline experienced by the species over the last millennia. Conclusions Our findings suggest that population connectivity of the species has acted as a buffer of genetic losses and illustrate the use of ancient DNA to uncover such cryptic genetic events.

Can genetic algorithms explain experimental anomalies? An application to common property resources

It is common to find in experimental data persistent oscillations in the aggregate outcomes and high levels of heterogeneity in individual behavior. Furthermore, it is not unusual to find significant deviations from aggregate Nash equilibrium predictions. In this paper, we employ an evolutionary model with boundedly rational agents to explain these findings. We use data from common property resource experiments (Casari and Plott, 2003). Instead of positing individual-specific utility functions, we model decision makers as selfish and identical. Agent interaction is simulated using an individual learning genetic algorithm, where agents have constraints in their working memory, a limited ability to maximize, and experiment with new strategies. We show that the model replicates most of the patterns that can be found in common property resource experiments.

A Model-to-model analysis of the repeated Prisoners' Dilemma: genetic algorithms vs. evolutionary dynamics

We study the properties of the well known Replicator Dynamics when applied to a finitely repeated version of the Prisoners' Dilemma game. We characterize the behavior of such dynamics under strongly simplifying assumptions (i.e. only 3 strategies are available) and show that the basin of attraction of defection shrinks as the number of repetitions increases. After discussing the difficulties involved in trying to relax the 'strongly simplifying assumptions' above, we approach the same model by means of simulations based on genetic algorithms. The resulting simulations describe a behavior of the system very close to the one predicted by the replicator dynamics without imposing any of the assumptions of the analytical model. Our main conclusion is that analytical and computational models are good complements for research in social sciences. Indeed, while on the one hand computational models are extremely useful to extend the scope of the analysis to complex scenar