Genomic selection refers to the use of genotypic information for predicting breeding values of selection candidates. A prediction formula is calibrated with the genotypes and phenotypes of reference individuals constituting the calibration set. The size and the composition of this set are essential parameters affecting the prediction reliabilities. The objective of this study was to maximize reliabilities by optimizing the calibration set. Different criteria based on the diversity or on the prediction error variance (PEV) derived from the realized additive relationship matrix-best linear unbiased predictions model (RA-BLUP) were used to select the reference individuals. For the latter, we considered the mean of the PEV of the contrasts between each selection candidate and the mean of the population (PEVmean) and the mean of the expected reliabilities of the same contrasts (CDmean). These criteria were tested with phenotypic data collected on two diversity panels of maize (Zea mays L.) genotyped with a 50k SNPs array. In the two panels, samples chosen based on CDmean gave higher reliabilities than random samples for various calibration set sizes. CDmean also appeared superior to PEVmean, which can be explained by the fact that it takes into account the reduction of variance due to the relatedness between individuals. Selected samples were close to optimality for a wide range of trait heritabilities, which suggests that the strategy presented here can efficiently sample subsets in panels of inbred lines. A script to optimize reference samples based on CDmean is available on request.A MONG the different methods that use molecular markers for selection, genomic selection (GS) has received considerable attention in the last decade. The objective of this approach is to predict the breeding values of candidates based on their molecular marker genotypes. A prediction formula is developed using the genotypes and phenotypes of reference individuals forming a calibration set (Meuwissen

An understanding of the genetic determinism of frost tolerance is a prerequisite for the development of frost tolerant cultivars for cold northern areas. In legumes, it is not known to which extent vernalization requirement or photoperiod responsiveness are necessary for the development of frost tolerance. In pea (Pisum sativum L.) however, the flowering locus Hr is suspected to influence winter frost tolerance by delaying floral initiation until after the main winter freezing periods have passed. The objective of this study was to dissect the genetic determinism of frost tolerance in pea by QTL analysis and to assess the genetic linkage between winter frost tolerance and the Hr locus. A population of 164 recombinant inbred lines (RILs), derived from the cross Champagne x Terese was evaluated both in the greenhouse and in field conditions to characterize the photoperiod response from which the allele at the Hr locus was inferred. In addition, the population was also assessed for winter frost tolerance in 11 field conditions. Six QTL were detected, among which three were consistent among the different experimental conditions, confirming an oligogenic determinism of frost tolerance in pea. The Hr locus was found to be the peak marker for the highest explanatory QTL of this study. This result supports the hypothesis of the prominent part played by the photoperiod responsiveness in the determinism of frost tolerance for this species. The consistency of three QTL makes these positions interesting targets for marker-assisted selection.

Background In the last decade, metabolomics has emerged as a powerful diagnostic and predictive tool in many branches of science. Researchers in microbes, animal, food, medical and plant science have generated a large number of targeted or non-targeted metabolic profiles by using a vast array of analytical methods (GC–MS, LC–MS, 1H-NMR….). Comprehensive analysis of such profiles using adapted statistical methods and modeling has opened up the possibility of using single or combinations of metabolites as markers. Metabolic markers have been proposed as proxy, diagnostic or predictors of key traits in a range of model species and accurate predictions of disease outbreak frequency, developmental stages, food sensory evaluation and crop yield have been obtained.Aim of review(i) To provide a definition of plant performance and metabolic markers, (ii) to highlight recent key applications involving metabolic markers as tools for monitoring or predicting plant performance, and (iii) to propose a workable and cost-efficient pipeline to generate and use metabolic markers with a special focus on plant breeding.Key messageUsing examples in other models and domains, the review proposes that metabolic markers are tending to complement and possibly replace traditional molecular markers in plant science as efficient estimators of performance.

BackgroundEuropean Flint maize inbred lines are used as a source of adaptation to cold in most breeding programs in Northern Europe. A deep understanding of their adaptation strategy could thus provide valuable clues for further improvement, which is required in the current context of climate change. We therefore compared six inbreds and two derived Flint x Dent hybrids for their response to one-week at low temperature (10 °C day/7 or 4 °C night) during steady-state vegetative growth.ResultsLeaf growth was arrested during chilling treatment but recovered fast upon return to warm temperature, so that no negative effect on shoot biomass was measured. Gene expression analyses of the emerging leaf in the hybrids suggest that plants maintained a ‘ready-to-grow’ state during chilling since cell cycle genes were not differentially expressed in the division zone and genes coding for expansins were on the opposite up-regulated in the elongation zone. In photosynthetic tissues, a strong reduction in PSII efficiency was measured. Chilling repressed chlorophyll biosynthesis; we detected accumulation of the precursor geranylgeranyl chlorophyll a and down-regulation of GERANYLGERANYL REDUCTASE (GGR) in mature leaf tissues. Excess light energy was mostly dissipated through fluorescence and constitutive thermal dissipation processes, rather than by light-regulated thermal dissipation. Consistently, only weak clues of xanthophyll cycle activation were found. CO2 assimilation was reduced by chilling, as well as the expression levels of genes encoding phosphoenolpyruvate carboxylase (PEPC), pyruvate orthophosphate dikinase (PPDK), and the small subunit of Rubisco. Accumulation of sugars was correlated with a strong decrease of the specific leaf area (SLA).ConclusionsAltogether, our study reveals good tolerance of the photosynthetic machinery of Northern European maize to chilling and suggests that growth arrest might be their strategy for fast recovery after a mild stress.Electronic supplementary materialThe online version of this article (doi:10.1186/s12870-016-0909-y) contains supplementary material, which is available to authorized users.