Characterization of new physiological traits to support breeding for post-flowering drought tolerance in sorghum – SorDrought

Root phenotyping was conducted through two complementary approaches: (1) field-based shovelomics to image the upper root system after excavation, and (2) laser ablation tomography to analyse anatomical features of crown root segments sampled from node four. These phenotyping efforts were deployed in Senegal (Bambey) and in three additional locations in the south of France. On each site, accessions representing the global diversity and elite varieties / parental lines were analysed. Additional populations derived from elite lines and donor lines presenting contrasting root properties (rhizosheath) are currently under evaluation in controlled conditions in Senegal.

To assess drought response, micro-CT and optical imaging were used to visualize embolism spread within the vascular system of different genotypes. Transpiration efficiency was measured using a lysimetric platform, while rhizosheath formation was quantified by calculating the ratio of aggregated soil mass to root mass (RS/RT).

As the Sordrought project will generate information on the molecular and genetic factors contributing to the variability of physiologically relevant traits, genomic prediction models taking advantage of this information will be developed. A bibliographic review of the current genomic prediction models (either in plant, animal and human genetics) able to use functional annotation has been performed. Based on this review, alternative approaches are being explored using a published maize dataset (Ali et al., 2025, The Plant Genome 18, e20553. doi.org/10.1002/tpg2.20553).

Diversity panels and elite sorghum lines were characterized for root architecture (using shovelomics) and root anatomy (via laser ablation tomography and AI-based segmentation) under field conditions in both West Africa and Europe. Transpiration efficiency was assessed using lysimetric platforms, and rhizosheath formation was quantified in controlled environments. These analyses enabled the identification of contrasting lines for these traits, as well as biparental populations (BCNAM) for genetic studies. These populations were subsequently phenotyped for the same traits in both field and laboratory settings. Data are currently being analysed to identify genomic regions (QTL) controlling these traits and to develop sister lines differing for these QTL in a common genetic background, which will be used to evaluate their contribution to drought tolerance.

In parallel, we employed two independent techniques, micro-CT and optical imaging, to directly visualize embolism spread in the vascular system. For the first time, we established the spectrum of embolism resistance across major crops. Sorghum emerged as one of the most embolism-resistant species, with an average P50 of -4.0 ± 0.2 MPa, significantly more negative than values reported for barley (-2.4 ± 0.2 MPa), wheat (-2.2 ± 0.2 MPa), soybean (-1.85 ± 0.1 MPa), or maize (-1.9 ± 0.1 MPa). Furthermore, we quantified intraspecific variability in embolism resistance among sorghum genotypes, revealing significant differences between lines.

In terms of genetic value prediction, the relevance of a Bayesian statistical model initially developed for genetic mapping purposes has been tested. Its relevance has been explored for a set of functional annotations varying from 1 to 30 taking into account their informativeness using the Gini Index. Preliminary results are encouraging, the performances of this model exceeding, in certain conditions, the ones of the standard GBLUP model but also the ones of models taking advantage of functional annotations (MultiBlup, BayresRC).

Genetic analyses will identify genomic regions and candidate genes underlying key drought tolerance traits. The molecular mechanisms controlling these traits will then be investigated in detail.

Lines contrasting for QTL associated with these traits will be evaluated in field trials under various stress scenarios to assess their contribution to water stress resilience. Finally, the integration of these physiological and molecular data into genomic prediction models will be evaluated to enhance their accuracy. Regarding the genomic prediction model that has been developed, its performance on complementary datasets for which a larger set of genotypes and markers are available (rice dataset: 2600 genotypes x several millions SNP) and presenting different population structures (Sorghum BCNAM population) will be tested. Additionally, the properties of the model will be tested for different functional annotations topology (with different levels of overlap).

Ultimately, SorDrought will provide breeders with innovative tools to develop a new generation of cereals, leveraging novel physiological traits to improve sorghum yield and resilience in both Europe and West Africa.

Cereals are of global importance for food security and their production is dramatically impacted by climate change. Increased occurrence of severe drought events is one of the main factors responsible for this impact. Sorghum, one of the most drought tolerant cereals, is key for food security in West Africa and, due to its agronomic and technological properties, is expected to contribute to crop diversification in Europe. There is a large variability for water stress tolerance in sorghum, but the underlying physiological and genetic mechanisms are still poorly understood. Moreover, there is an urgent need to study mechanistic traits whose function can be clearly physiologically defined, rather than standard functional traits to explain crops responses to increasing drought conditions. The aim of the SorDrought project is to identify and characterize mechanistic traits contributing to drought tolerance in sorghum, decipher their genetic control and evaluate how these traits could be used to improve breeding efficiency in sorghum. We will focus on post flowering water stress, which is the main constraint both in the European and West African contexts and will target traits that improve water use efficiency and preserve the integrity of the hydraulic pathway to maintain yield under stress.
The SorDrought project will use elite genotype from the selection programmes in Europe and West Africa, diversity panels covering the world diversity and multiparental populations that will allow us both to perform genetic analyses and will provide a way to quickly introgress interesting alleles in elite germplasm for breeding.
To achieve its objectives, SorDrought will mobilize a consortium that has strong expertise in the phenotyping and physiology of target adaptative traits and in genetic analyses of complex agronomical traits and its use in breeding. SorDrought was co-constructed by researchers from 3 public laboratories and breeders from 2 seed companies as well as ISRA/CERAAS, the regional hub for research on dryland cereals in West Africa. It will promote collaboration and exchanges between researchers from public and private sector in France and Africa and will provide breeders with knowledge, tools and expertise to create a new generation of cereal crops integrating new physiological traits to improve performance and resilience both for Europe and Africa.