Résumé
Close to 50% of the world cotton is produced under rainfed conditions, and in Africa, about 95% of the cotton farms are rainfed. Recent cropping seasons have shown the devastating effect of drought on cotton crops in different countries worldwide. These recent trends and future prospects suggest complicated times not only for the rainfed farmers, but also for those that depend on stored water. While the effect of water deficit on the development on the cotton plant is well documented, breeding for tolerance to water deficit has been a goal for many years. The complex nature of the concept of “drought tolerance”, its complex inheritance and low heritability, and the difficulty in precisely phenotyping the trait have made this goal challenging. To circumvent these problems, emphasis have been put on the use of morphological and/or physiological traits associated to tolerance as proxies. While cotton exhibits high levels of variability for such traits, no consistent correlation between these traits and field tolerance to water stress has been demonstrated. Molecular markers have been proposed as tools to assist breeding efforts. While early efforts have suffered technical limitations, the advent of high throughput genotyping and high throughput precision phenotyping technologies hold promises for improved precision and possibly identifying more robust marker/traits associations. A Genome-Wide Association Study (GWAS) was undertaken, in which phenotypic data for the root system architecture and above-ground growth parameters under contrasting water regimes of 269 accessions of Upland cotton were generated. The panel was genotyped using a 63K SNP Chip, and a Linkage Disequilibrium (LD)-based GWAS approach was used to identify markers associated to morpho-physiological parameters associated with adaptation to water stress. The root analyses allowed clustering the RSA traits of the panel into 5 morphotypes, while the GWAS identified markers associated with RSA traits that displayed additive and pleiotropic effects. Interestingly, 4 makers explained 40% of variability for the area explored by the roots and 28% of variability for total root length. The characterization of plant growth parameters and relevant physiological parameters/indices under contrasting water regimes was undertaken on the PhenoArch High Throughput Phenotyping Platform (HTPP) (LEPSE, Montpellier, France). The GWAS analysis identified 50 and 47 SNPs associated with 8 characters under well-watered (WW) and water-deficit (WD) growth conditions, respectively, individually explaining low phenotypic variation. Despite the absence of Genotype x Scenario interactions, only rare cases of common markers in the WW and WD conditions were detected for a given character. Biomass accumulation was used as an indicator of plant growth, and while the dynamics of biomass accumulation under contrasting water regimes displayed clear differences between genotypes, no co-localization of QTLs for biomass accumulation and morphological or biochemical parameters usually associated to tolerance to water stress was observed. The integration of data from the root system analysis with those obtained on the PhenoArch HTPP failed to identify co-localized QTLs for root traits and characters measured on the platform. Overall, the study allowed identifying Upland cotton genotypes with characters, such as more stable biomass accumulation under water deficit or displaying well developed root systems, that could prove useful for breeding for varieties with improved tolerance to water deficit. Furthermore, the GWAS study allowed identifying a small number of markets associated with important RSA traits.