A genomic map of climate adaptation in Mediterranean cattle breeds.

Domestic species such as cattle (Bos taurus taurus and B. t. indicus) represent attractive biological models to characterize the genetic basis of short-term evolutionary response to climate pressure induced by their post-domestication history. Here, using newly generated dense SNP genotyping data, we assessed the structuring of genetic diversity of 21 autochtonous cattle breeds from the whole Mediterranean basin and performed genome-wide association analyses with covariables discriminating the different Mediterranean climate subtypes. This provided insights into both the demographic and adaptive histories of Mediterranean cattle. In particular, a detailed functional annotation of genes surrounding variants associated with climate variations highlighted several biological functions involved in Mediterranean climate adaptation such as thermotolerance, UV protection, pathogen resistance or metabolism with strong candidate genes identified (e.g., NDUFB3, FBN1, METTL3, LEF1, ANTXR2 and TCF7). Accordingly, our results suggest that main selective pressures affecting cattle in Mediterranean area may have been related to variation in heat and UV exposure, in food resources availability and in exposure to pathogens, such as anthrax bacteria (Bacillus anthracis). Furthermore, the observed contribution of the three main bovine ancestries (indicine, European and African taurine) in these different populations suggested that adaptation to local climate conditions may have either relied on standing genomic variation of taurine origin, or adaptive introgression from indicine origin, depending on the local breed origins. Taken together, our results highlight the genetic uniqueness of local Mediterranean cattle breeds and strongly support conservation of these populations.

Extensive QTL and association analyses of the QTLMAS2009 Data.

BACKGROUND: We applied a range of genome-wide association (GWA) methods to map quantitative trait loci (QTL) in the simulated dataset provided by the QTLMAS2009 workshop to derive a comprehensive set of results. A Gompertz curve was modelled on the yield data and showed good predictive properties. QTL analyses were done on the raw measurements and on the individual parameters of the Gompertz curve and its predicted growth for each interval. Half-sib and variance component linkage analysis revealed QTL with different modes of inheritance but with low resolution. This was complemented by association studies using single markers or haplotypes, and additive, dominance, parent-of-origin and epistatic QTL effects. All association analyses were done on phenotypes pre-corrected for pedigree effects. These methods detected QTL positions with high concordance to each other and with greater refinement of the linkage signals. Two-locus interaction analysis detected no epistatic pairs of QTL. Overall, using stringent thresholds we identified QTL regions using linkage analyses, corroborated by 6 individual SNPs with significant effects as well as two putatively imprinted SNPs. CONCLUSIONS: We obtained consistent results across a combination of intra- and inter- family based methods using flexible linear models to evaluate a variety of models. The Gompertz curve fitted the data really well, and provided complementary information on the detected QTL. Retrospective comparisons of the results with actual data simulated showed that best results were obtained by including both yield and the parameters from the Gompertz curve despite the data being simulated using a logistic function.

A two-step approach combining the Gompertz growth model with genomic selection for longitudinal data.

BACKGROUND: We used the Gompertz growth curve to model a simulated longitudinal dataset provided by the QTLMAS2009 workshop and applied genomic evaluation to the derived model parameters and to a model-predicted trait value. RESULTS: Prediction of phenotypic information from the Gompertz curve allowed us to obtain genomic breeding value estimates for a time point with no phenotypic records. Despite that the true model used to simulate the data was the logistic growth model, the Gompertz model provided a good fit of the data. Genomic breeding values calculated from predicted phenotypes were highly correlated with the breeding values obtained by directly using the respective observed phenotypes. The accuracies between the true and estimated breeding value at time 600 were above 0.93, even though t600 was outside the time range used when fitting the data. The analysis of the parameters of the Gompertz curve successfully discriminated regions with QTL affecting the asymptotic final value, but it was less successful in finding QTL affecting the other parameters of the logistic growth curve. In this study we estimated the proportion of SNPs affecting a given trait, in contrast with previously reported implementations of genomic selection in which this parameter was assumed to be known without error. CONCLUSIONS: The two-step approach used to combine curve fitting and genomic selection on longitudinal data provided a simple way for combining these two complex tasks without any detrimental effect on breeding value estimation.

Linkage between dynamics and catalysis in a thermophilic-mesophilic enzyme pair.

A fundamental question is how enzymes can accelerate chemical reactions. Catalysis is not only defined by actual chemical steps, but also by enzyme structure and dynamics. To investigate the role of protein dynamics in enzymatic turnover, we measured residue-specific protein dynamics in hyperthermophilic and mesophilic homologs of adenylate kinase during catalysis. A dynamic process, the opening of the nucleotide-binding lids, was found to be rate-limiting for both enzymes as measured by NMR relaxation. Moreover, we found that the reduced catalytic activity of the hyperthermophilic enzyme at ambient temperatures is caused solely by a slower lid-opening rate. This comparative and quantitative study of activity, structure and dynamics revealed a close link between protein dynamics and catalytic turnover.