Delineation of molecular determinants for FR900359 inhibition of Gq/11 unlocks inhibition of Gαs.

Heterotrimeric G proteins are essential mediators of intracellular signaling of G protein-coupled receptors. The Gq/11 subfamily consists of Gq, G11, G14, and G16 proteins, of which all but G16 are inhibited by the structurally related natural products YM-254890 and FR900359. These inhibitors act by preventing the GDP/GTP exchange, which is necessary for activation of all G proteins. A homologous putative binding site for YM-254890/FR900359 can also be found in members of the other three G protein families, Gs, Gi/o, and G12/13, but none of the published analogs of YM-254890/FR900359 have shown any inhibitory activity for any of these. To explain why the YM-254890/FR900359 scaffold only inhibits Gq/11/14, the present study delineated the molecular selectivity determinants by exchanging amino acid residues in the YM-254890/FR900359-binding site in Gq and Gs We found that the activity of a Gs mutant with a Gq-like binding site for YM-254890/FR900359 can be inhibited by FR900359, and a minimum of three mutations are necessary to introduce inhibition in Gs In all, this suggests that although the YM-254890/FR900359 scaffold has proven unsuccessful to derive Gs, Gi/o, and G12/13 inhibitors, the mechanism of inhibition between families of G proteins is conserved, opening up the possibility of targeting by other, novel inhibitor scaffolds. In lack of a selective Gαs inhibitor, FR900359-sensitive Gαs mutants may prove useful in studies where delicate control over Gαs signaling would be of the essence.

Genomic Prediction Using Prior Quantitative Trait Loci Information Reveals a Large Reservoir of Underutilised Blackleg Resistance in Diverse Canola (Brassica napus L.) Lines.

Genomic prediction is becoming a popular plant breeding method to predict the genetic merit of lines. While some genomic prediction results have been reported in canola, none have been evaluated for blackleg disease. Here, we report genomic prediction for seedling emergence, survival rate, and internal infection), using 532 Spring and Winter canola lines. These lines were phenotyped in two replicated blackleg disease nurseries grown at Wickliffe and Green Lake, Victoria, Australia. A transcriptome genotyping-by-sequencing approach revealed 98,054 single nucleotide polymorphisms (SNPs) after quality control. We assessed various genomic prediction scenarios based on Genomic Best Linear Unbiased Prediction (GBLUP), BayesR and BayesRC, which can make use of prior quantitative trait loci information, via cross-validation. Clustering based on genomic relationships showed that Winter and Spring lines were genetically distinct, indicating limited gene flow between sets. Genetic correlations within traits between Spring and Winter lines ranged from 0.68 and 0.90 (mean = 0.76). Based on GBLUP in the whole population, moderate to high genomic prediction accuracies were achieved within environments (0.35-0.74) and were reduced across environments (0.28-0.58). Prediction accuracy within the Spring set ranged from 0.30-0.69, and from 0.19-0.71 within the Winter set. The BayesR model resulted in slightly lower accuracy to GBLUP. The proportion of genetic variance explained by known blackleg quantitative trait loci (QTL) was < 30%, indicating that there is a large reservoir of genetic variation in blackleg traits that remains to be discovered, but can be captured with genomic prediction. However, providing prior information of known QTL in the BayesRC method resulted in an increased prediction accuracy for survival and internal infection, particularly with Spring lines. Overall, these promising results indicate that genomic prediction will be a valuable tool to make use of all genetic variation to improve blackleg resistance in canola.

Increases in the evolutionary potential of upper thermal limits under warmer temperatures in two rainforest Drosophila species.

Tropical and subtropical species represent the majority of biodiversity. These species are predicted to lack the capacity to evolve higher thermal limits in response to selection imposed by climatic change. However, these assessments have relied on indirect estimates of adaptive capacity, using conditions that do not reflect environmental changes projected under climate change. Using a paternal half-sib full-sib breeding design, we estimated the additive genetic variance and narrow-sense heritability for adult upper thermal limits in two rainforest-restricted species of Drosophila reared under two thermal regimes, reflecting increases in seasonal temperature projected for the Wet Tropics of Australia and under standard laboratory conditions (constant 25°C). Estimates of additive genetic variation and narrow-sense heritability for adult heat tolerance were significantly different from zero in both species under projected summer, but not winter or constant, thermal regimes. In contrast, significant broad-sense genetic variation was apparent in all thermal regimes for egg-to-adult viability. Environment-dependent changes in the expression of genetic variation for adult upper thermal limits suggest that predicting adaptive responses to climate change will be difficult. Estimating adaptive capacity under conditions that do not reflect future environmental conditions may provide limited insight into evolutionary responses to climate change.