Genomic preselection with genotyping-bysequencing increases performance of commercial oil palm hybrid crosses

Background: There is great potential for the genetic improvement of oil palm yield. Traditional progeny tests allow accurate selection but limit the number of individuals evaluated. Genomic selection (GS) could overcome this constraint. We estimated the accuracy of GS prediction of seven oil yield components using A × B hybrid progeny tests with almost 500 crosses for training and 200 crosses for independent validation. Genotyping-by-sequencing (GBS) yielded +5000 single nucleotide polymorphisms (SNPs) on the parents of the crosses. The genomic best linear unbiased prediction method gave genomic predictions using the SNPs of the training and validation sets and the phenotypes of the training crosses. The practical impact was illustrated by quantifying the additional bunch production of the crosses selected in the validation experiment if genomic preselection had been applied in the parental populations before progeny tests. Results: We found that prediction accuracies for cross values plateaued at 500 to 2000 SNPs, with high (0.73) or low (0.28) values depending on traits. Similar results were obtained when parental breeding values were predicted. GS was able to capture genetic differences within parental families, requiring at least 2000 SNPs with less than 5% missing data, imputed using pedigrees. Genomic preselection could have increased the selected hybrids bunch production by more than 10%. Conclusions: Finally, preselection for yield components using GBS is the first possible application of GS in oil palm. This will increase selection intensity, thus improving the performance of commercial hybrids. Further research is required to increase the benefits from GS, which should revolutionize oil palm breeding. (Résumé d'auteur

South Green bioinformatics platform : Plateforme collaborative de bioinformatique verte héraultaise

Drivers and other road users often encounter situations where priority is unclear or ambiguous, but must be resolved, for example, after arriving at an intersection nearly simultaneously. The participants in such scenarios reach agreement by communicating; while instinctive to humans, this is a significant challenge for autonomous vehicles. Currently, the nature of interaction for resolving ambiguous road situations between pedestrians and autonomous vehicles remains mostly in the realm of speculation, for which no direct means for expressing intent and acknowledgment has yet been established. This thesis approaches the challenge by contributing a model and approach for planning that can produce actions that are expressive and encode certain aspects of intent; the result is communicative in that vehicle-pedestrian coordination arises via a negotiation of intent in a prototypical unsignalized intersection crossing scenario. We deliberately construct a prototypical crossing setting with a vehicle and one pedestrian at an unsignalized intersection such that there is substantial ambiguity in crossing order. A decision-theoretic model is then used for capturing this scenario along with its ambiguity as uncertainty arising from non-determinism and partial observability. We solve the problem by first proposing a Markov decision process to express the interaction at the intersection. Next, we focus on the partial-observability and include it in the model to generate a sequence of vehicle actions by solving via a state-of-the-art online solver. We implement the approach on a self-driving Ford Lincoln MKZ platform and examine an experimental setting involving real-time interaction. The experiment shows that the method achieves safe and efficient navigation. We analyze the resulting policy in detail in simulation and examine the coupled behavior of the vehicle and pedestrian, interpreting evidence for implicit communication that emerges as the two resolve ambiguity to achieve safe and efficient navigation

Genotyping-by-sequencing reveals the effects of riverscape, climate and interspecific introgression on the genetic diversity and local adaptation of the endangered Mexican golden trout (Oncorhynchus chrysogaster)

International audienceHow environmental and anthropogenic factors influence genetic variation and local adaptation is a central issue in evolutionary biology. The Mexican golden trout (Oncorhynchus chrysogaster), one of the southernmost native salmonid species in the world, is susceptible to climate change, habitat perturbations and the competition and hybridization with exotic rainbow trout (O. mykiss). The present study aimed for the first time to use genotyping-by-sequencing to explore the effect of genetic hybridization with O. mykiss and of riverscape and climatic variables on the genetic variation among O. chrysogaster populations. Genotyping-by-sequencing (GBS) was applied to generate 9767 single nucleotide polymorphisms (SNPs), genotyping 272 O. chrysogaster and O. mykiss. Population genomics analyses were combined with landscape ecology approaches into a riverine context (riverscape genetics). The clustering analyses detected seven different genetic groups (six for O. chryso-gater and one for aquaculture O. mykiss) and a small amount of admixture between aquaculture and native trout with only two native genetic clusters showing exotic introgression. Latitude and precipitation of the driest month had a significant negative effect on genetic diversity and evidence of isolation by river resistance was detected, suggesting that the landscape heterogeneity was preventing trout dispersal, both for native and exotic individuals. Moreover, several outlier SNPs were identified as potentially implicated in local adaptation to local hydroclimatic variables. Overall, this study suggests that O. chrysogater may require conservation planning given (i) exotic introgression from O. mykiss locally threatening O. chryso-gater genetic integrity, and (ii) putative local adaptation but low genetic diversity and hence probably reduced evolutionary potential especially in a climate change context

Genome-wide analysis in Hevea brasiliensis laticifers revealed species-specific post-transcriptional regulations of several redox-related genes

Abstract MicroRNA-mediated post-transcriptional regulation has been reported on ROS production and scavenging systems. Although microRNAs first appeared highly conserved among plant species, several aspects of biogenesis, function and evolution of microRNAs were shown to differ. High throughput transcriptome and degradome analyses enable to identify small RNAs and their mRNA targets. A non-photosynthetic tissue particularly prone to redox reactions, laticifers from Hevea brasiliensis, revealed species-specific post-transcriptional regulations. This paper sets out to identify the 407 genes of the thirty main redox-related gene families harboured by the Hevea genome. There are 161 redox-related genes expressed in latex. Thirteen of these redox-related genes were targeted by 11 microRNAs. To our knowledge, this is the first report on a mutation in the miR398 binding site of the cytosolic CuZnSOD. A working model was proposed for transcriptional and post-transcriptional regulation with respect to the predicted subcellular localization of deduced proteins

Spatio-temporal population genetic structure, relative to demographic and ecological characteristics, in the freshwater snail Biomphalaria pfeifferi in Man, western Côte d'Ivoire

Combining the analysis of spatial and temporal variation when investigating population structure enhances our capacity for unravelling the biotic and abiotic factors responsible for microevolutionary change. This work aimed at measuring the spatial and temporal genetic structure of populations of the freshwater snail Biomphalaria pfeifferi (the intermediate host of the trematode Schistosoma mansoni) in relation to the mating system (self-fertilization), demography, parasite prevalence and some ecological parameters. Snail populations were sampled four times in seven human-water contact sites in the Man region, western Côte d'Ivoire, and their variability was measured at five microsatellite loci. Limited genetic diversity and high selfing rates were observed in the populations studied. We failed to reveal an effect of demographic and ecological parameters on within-population diversity, perhaps as a result of a too small number of populations. A strong spatial genetic differentiation was detected among populations. The temporal differentiation within populations was high in most populations, though lower than the spatial differentiation. All estimates of effective population size were lower than seven suggesting a strong effect of genetic drift. However, the genetic drift was compensated by high gene flow. The genetic structure within and among populations reflected that observed in other selfing snail species, relying on high selfing rates, low effective population sizes, environmental stochasticity and high gene flow