Exploratory QTL analyses of some pepper physiological traits in two environments

behind phenotypic differences and led to selection of genotypes having favourable traits. Continuous monitoring of environmental conditions has also become an accessible option. Rather than single trait evaluation, we would prefer smarter approaches capable of evaluating multiple, often correlated and time dependent traits simultaneously as a function of genes (QTLs) and environmental inputs, where we would The use of molecular breeding techniques has increased insight into the genetics like to include intermediate genomic information as well. In this paper, an exploratory QTL analysis over two environments was undertaken using available genetic and phenotypic data from segregating recombinant inbred lines (RIL) of pepper (Capsicum annuum). We focused on vegetative traits, e.g. stem length, speed of stem development, number of internodes etc. We seek to improve the estimation of allelic values of these traits under the two environments and determine possible QTL x E interaction. Almost identical QTLs are detected for each trait under the two environments but with varying LOD scores. No clear evidence was found for presence of QTL by environment interactions, despite differences in phenotypes and in magnitude of QTLs expression. Within the EU project SPICY (Voorrips et al., 2010 this issue), a larger number of environments will be studied and more advanced statistical analysis tools will be considered. The correlation between the traits will also be modelled. The identification of markers for the important QTL (Nicolaï et al., 2010 this issue) will improve the speed and accuracy of genomic prediction of these complex phenotype

Discovery of a large set of SNP and SSR genetic markers by high-throughput sequencing of pepper (Capsicum annuum)

Genetic markers based on single nucleotide polymorphisms (SNPs) are in increasing demand for genome mapping and fingerprinting of breeding populations in crop plants. Recent advances in high-throughput sequencing provide the opportunity for whole-genome resequencing and identification of allelic variants by mapping the reads to a reference genome. However, for many species, such as pepper (Capsicum annuum), a reference genome sequence is not yet available. To this end, we sequenced the C. annuum cv. "Yolo Wonder" transcriptome using Roche 454 pyrosequencing and assembled de novo 23,748 isotigs and 60,370 singletons. Mapping of 10,886,425 reads obtained by the Illumina GA II sequencing of C. annuum cv. "Criollo de Morclos 334" to the "Yolo Wonder" transcriptome allowed for SNP identification. By setting a threshold value that allows selecting reliable SNPs with minimal loss of information, 11,849 reliable SNPs spread across 5919 isotigs were identified. In addition, 853 single sequence repeats were obtained. This information has been made available online

Evaluation expérimentale de stratégies de déploiement de gènes de résistance pour la gestion durable des nématodes à galles

Dans le cadre de projets soutenus par l'ANR Systerra et le GIS PICLeg (projets "Sysbiotel" et "Neoleg") menés en collaboration entre l'INRA PACA, l'IRD, l'APREL, la Chambre d'Agriculture du 06 et des entreprises privées de sélection de semences, plusieurs stratégies de déploiement de gènes de résistance ont été évaluées pendant 3 ans sur le terrain en conditions agronomiques pour mettre au point une gestion raisonnée des cultivars résistants permettant de gérer de manière durable les problèmes de nématodes à galles des racines. L'alternance des gènes de résistance dans la rotation et le "pyramiding" de gènes dans un même cultivar se sont révélés extrêmement efficaces pour supprimer l'émergence de populations virulentes et réduire les taux d'infestation du sol de plus de 80% en 3 ans. Un nouveau projet INRA "Gedunem", mis en place dans le cadre du Métaprogramme INRA SMaCH (Sustainable Management of Crop Health), vise maintenant à associer ces innovations variétales aux autres méthodes de lutte disponibles (gestion de l'interculture, plantes non hôtes, prophylaxie) afin de maintenir une pression parasitaire faible, tout en évaluant ces nouveaux systèmes de culture du point de vue agronomique et socio-économique

Crop growth models for the -omics era: the EU-SPICY project

The prediction of phenotypic responses from genetic and environmental information is an area of active research in genetics, physiology and statistics. Rapidly increasing amounts of phenotypic information become available as a consequence of high throughput phenotyping techniques, while more and cheaper genotypic data follow from the development of new genotyping platforms. , A wide array of -omics data can be generated linking genotype and phenotype. Continuous monitoring of environmental conditions has become an accessible option. This wealth of data requires a drastic rethinking of the traditional quantitative genetic approach to modeling phenotypic variation in terms of genetic and environmental differences. Where in the past a single phenotypic trait was partitioned in a genetic and environmental component by analysis of variance techniques, nowadays we desire to model multiple, interrelated and often time dependent, phenotypic traits as a function of genes (QTLs) and environmental inputs, while we would like to include transcription information as well. The EU project 'Smart tools for Prediction and Improvement of Crop Yield' (KBBE-2008-211347), or SPICY, aims at the development of genotype-to-phenotype models that fully integrate genetic, genomic, physiological and environmental information to achieve accurate phenotypic predictions across a wide variety of genetic and environmental configurations. Pepper (Capsicum annuum) is chosen as the model crop, because of the availability of genetically characterized populations and of generic models for continuous crop growth and greenhouse production. In the presentation the objectives and structure of SPICY as well as its philosophy will be discussed

QTL analyses on genotype-specific component traits in a crop simulation model for capsicum annuum L.

Abstract: QTL for a complex trait like yield tend to be unstable across environments and show QTL by environment interaction. Direct improvement of complex traits by selecting on QTL is therefore difficult. For improvement of complex traits, crop growth models can be useful, as such models can dissect a target trait into a number of component traits. QTL for the component traits are assumed to be more stable across environments. The target trait can be reconstructed from its component traits together with environmental inputs. Instead of observed component traits, QTL fits for component traits may be used when QTL explain a reasonable proportion of the variation in the components. We applied this dissection approach to the target trait total shoot biomass for a population of 149 recombinant inbred lines from the intraspecific cross of Capsicum annuum ‘Yolo Wonder’ and ‘Criollo de Morelos 334’. A simple LINTUL-type simulation model was used, with rate of change of leaf area index and light use efficiency as genotype specific component traits. These two component traits were determined in four phenotyping experiments (spring and autumn cultivations in the Netherlands and Spain), and subjected to QTL analysis. Seven QTL were found for both component traits. For leaf area index development rate 40 to 50% of the observed variance was explained by the QTL, while this was slightly lower for light use efficiency (23-39%). Using the QTL fitted values of the component traits following QTL analysis, the crop simulation model explained 27-43% of the observed variation in total shoot biomass, which was higher than the variation explained by the QTL for total shoot biomass itself for most experiments. The approach of dissecting a complex trait into its component traits is therefore a promising one. Next step is to extend the model with biomass partitioning

Historical Contingencies Modulate the Adaptability of Rice Yellow Mottle Virus

The rymv1-2 and rymv1-3 alleles of the RYMV1 resistance to Rice yellow mottle virus (RYMV), coded by an eIF(iso)4G1 gene, occur in a few cultivars of the Asiatic (Oryza sativa) and African (O. glaberrima) rice species, respectively. The most salient feature of the resistance breaking (RB) process is the converse genetic barrier to rymv1-2 and rymv1-3 resistance breakdown. This specificity is modulated by the amino acid (glutamic acid vs. threonine) at codon 49 of the Viral Protein genome-linked (VPg), a position which is adjacent to the virulence codons 48 and 52. Isolates with a glutamic acid (E) do not overcome rymv1-3 whereas those with a threonine (T) rarely overcome rymv1-2. We found that isolates with T49 had a strong selective advantage over isolates with E49 in O. glaberrima susceptible cultivars. This explains the fixation of the mutation T49 during RYMV evolution and accounts for the diversifying selection estimated at codon 49. Better adapted to O. glaberrima, isolates with T49 are also more prone than isolates with E49 to fix rymv1-3 RB mutations at codon 52 in resistant O. glaberrima cultivars. However, subsequent genetic constraints impaired the ability of isolates with T49 to fix rymv1-2 RB mutations at codons 48 and 52 in resistant O. sativa cultivars. The origin and role of the amino acid at codon 49 of the VPg exemplifies the importance of historical contingencies in the ability of RYMV to overcome RYMV1 resistance