Genome-wide association mapping for root cone angle in rice

Background: Plant root systems play a major role in anchoring and in water and nutrient uptake from the soil. The root cone angle is an important parameter of the root system architecture because, combined with root depth, it helps to determine the volume of soil explored by the plant. Two genes, DRO1 and SOR1, and several QTLs for root cone angle have been discovered in the last 5 years. Results: To find other QTLs linked to root cone angle, a genome-wide association mapping study was conducted on two panels of 162 indica and 169 japonica rice accessions genotyped with two sets of SNP markers (genotyping-by-sequencing set with approximately 16,000 markers and high-density-rice-array set with approximately 300,000 markers). The root cone angle of all accessions was measured using a screen protractor on images taken after 1 month of plant growth in the Rhizoscope phenotyping system. The distribution of the root cone angle in the indica panel was Gaussian, but several accessions of the japonica panel (all the bulus from Indonesia and three temperate japonicas from Nepal or India) appeared as outliers with a very wide root cone angle. The data were submitted to association mapping using a mixed model with control of structure and kinship. A total of 15 QTLs for the indica panel and 40 QTLs for the japonica panel were detected. Genes underlying these QTLs (+/−50 kb from the significant markers) were analyzed. We focused our analysis on auxin-related genes, kinases, and genes involved in root developmental processes and identified 8 particularly interesting genes. Conclusions: The present study identifies new sources of wide root cone angle in rice, proposes ways to bypass some drawbacks of association mapping to further understand the genetics of the trait and identifies candidate genes deserving further investigation. (Résumé d'auteur

GT-RootS: An integrated software for automated root system measurement from high-throughput phenotyping platform images

International audienceGT-RootS (Global Traits of Root System) is an automated Java-based open-source solution we are developing for processing root system images provided by the Rhizoscope, a CIRAD phenotyping platform dedicated to dense cereal plants. Two types of use are proposed. The fully-automated mode applies a predefined standard processing pipeline to a preselected set of images while the semi-automated mode allows the user to interactively check and correct intermediate processing results to a specific image. In both cases, GT-RootS combines a local adaptive thresholding algorithm and a similarity indicator to automatically separate the root system from a complex background without user intervention. A covering house-shaped polygon is then defined in the axis system of the root ellipse from vertical weighted density profiles. This canonical shape is composed of both upper trapezoid and lower rectangular compartments from which upper and lower heights, global width and local offset, root system cone angulation and spatial densities can be easily evaluated and displayed. GT-RootS measurements were compared both to expert evaluations and to two other estimation methods on a set of 64 images of a dense Japonica rice root system of 30-days-old plants. We demonstrate also that GT-RootS satisfies the requirements of high-throughput analyses: short processing time (around 30 images per hour on a low-end computer), measurement accuracy and repeatability, and user bias eradication

Cardinal temperatures variability within a tropical japonica rice diversity panel

Air temperature is one of the most critical climatic factors controlling rice growth, development, and production in current and future climatic scenarii predicting increasingly frequent situations of extreme and/or fluctuating temperatures. With its large spectrum of geographical origins and cropping areas, one can credit tropical japonica rice subspecies of a probable genetic diversity of its response to air temperature, which is of major interest for the breeding of better adapted rice varieties. A panel of 195 rice accessions (175 japonica plus 20 reference cultivars) was studied in controlled environment to estimate cardinal (base, optimum, and maximum) temperatures based on the monitoring of the elongation rate (LERmax) of the sixth leaf on the main stem in response to six fixed thermal treatments ranging from 16 to 35 °C. A dedicated statistical framework was elaborated for estimating LERmax, cardinal temperature and related uncertainties. Developed statistical framework enhanced the precision of cardinal temperatures estimated compared to previously reported methods, especially for base temperature. Maximum temperature was trickier to estimate and will require further studies. A significant genotypic variability for base and optimal temperature was pointed out, suggesting tropical japonica subspecies represents a relevant genetic pool to breed for rice genotypes adapted to various thermal situations. These results also suggested that using genotype-dependent cardinal temperature values should enhance the way crop growth models account for genotype × environment interactions hence their predictive value in current and future climatic conditions