Adaptation multistress et régulations biologiques pour l'amélioration du rendement et de la stabilité du pois protéagineux

PeaMUST is a 9-year Biotechnology and Bioresources research project, funded under the Investments for the Future Program. The project gathered a consortium of 28 public and private partners of the pea industry (13 public laboratories, a competitiveness cluster, an interprofession, a technical institute, a public interest group and 11 major pea breeding, plant biotechnology and pea ingredient companies). Thanks to a 5.5 M€ grant, the project has tackled the development of new pea varieties with improved yield regularity and targets the increase of the pea crop area in Europe for a more sustainable agriculture. Progress towards this goal was made possible through the development of new plant material and genomic resources which were transferred to pea breeders for integration in their breeding programs.

(WP1) Genomic selection was tested on three types of peas: spring peas (PP), conventional winter peas (Phr) and photoperiodic winter peas (PHr) to evaluate the genetic gain of this breeding strategy, as compared to phenotypic selection. Training panels for the three pea types were defined, then phenotyped and genotyped, and equations to predict yield and the responses to yield limiting factors, based solely on genotypic data, were developed. The prediction accuracies of these models were evaluated in PP and Phr breeding panels that were developed in the project. Predictions were robust for yield but less accurate for the response to limiting factors, probably because these traits were estimated on a more limited number of trials. Spring pea lines derived from the first cycle of genomic selection were tested in agronomic conditions and compared to lines derived from phenotypic selection; lines from genomic selection showed a similar performance to lines from phenotypic selection. These encouraging results, showed the promising nature of this selection method which, in reducing the time required to select interesting lines in breeding programs, could help accelerate breeding cycles.

(WP2) Pea and fababean plant materials (Near-Isogenic Lines, Recombinant Inbred Lines…) were produced for validation or detection of stress resistance QTL. Towards this aim, genomic resources were generated for these two species (SNPs, exome sequencing, RNA sequences…). In pea, main frost and Aphanomyces euteiches resistance QTL previously identified were validated. Confidence intervals of a major frost tolerance QTL and a major Aphanomyces euteiches resistance QTL were reduced (< 0.2 cM in the case of Aphanomyces), and the physical regions underlying those QTLs were identified. Some combinations of Aphanomyces resistance QTL in pea NILs showed an increased effect on limiting pathogen development. Some NILs evaluation also confirmed the effect of a major Aphanomyces resistance QTL to limit yield reduction in highly infested fields. In fababean, three RIL populations and the reference collection were evaluated for bruchid, frost and/or Aphanomyces resistance (genotyping and/or phenotyping). Proteomics, VOCs (Volatile Organic Compounds) and RNAseq were obtained for RIL families to identify molecular pathways underlying bruchid and Aphanomyces resistance. Genetic maps for the three RIL populations were constructed, and syntenic relationships between pea and fababean resistance QTL were studied.

(WP3) PeaMUST also focused on the effect of plant shoot and/or root architecture on multi-stress tolerance. For this, the project relied on the one hand on naturally existing variability through a collection of genetic resources (AMS collection for “Architecture and Multi-Stress”); and on the other hand, new material was produced with the introgression of 6 mutations known to affect shoot and/or root architecture in three cultivars. Complementary novel mutation TILLING screens were done. The AMS collection was genotyped and phenotyped for various stresses (drought, Aphanomyces euteiches, frost, and other stresses occurring during field trials), and despite experimental problems in some trials, stress resistance QTLs were identified through Genome-Wide Association Studies (GWAS). Studies were also conducted on cell wall composition. Introgression mutants were evaluated for their agronomical performance and behavior towards a series of stresses. A sub-sample of 17 lines (“Best of”) was further tested for drought tolerance on a high-throughput phenotyping platform. Inoculation strategies relying on Rhizobium leguminosarum strains combined or not with LCO (Lipochitooligosaccharides) nodulation factors were tested for their effect on plant stress tolerance. Some combinations were tested in the field, but trials were compromised by insect attacks. Some of the combinations were also tested in controlled conditions for resistance to Aphanomyces and for tolerance to water stress in a high-throughput phenotyping platform.

(WP4) To validate some of the PeaMUST results, a candidate gene validation platform was set-up in the project with three complementary approaches: TILLING, VIGS (Virus Induced Gene Silencing) and obtaining HD SNP markers for GWAS (Genome-Wide Association Studies). Studies conducted on VIGS proved the susceptibility of both pea aerial and roots compartments and thus the efficiency of this technique on both the aerial and root parts. Unfortunately it proved inefficient in cold conditions, but the observed persistence of VIGS silencing after 15 weeks confirmed the interest of this technique for disease resistance candidate validation. A TILLING mutants collection for the Hr winter pea genotype 336/11 was built.

(WP5) Recently registered pea cultivars were evaluated for yield and adaptation to diverse stresses in a multi-local field network of over 40 environments during 3 years (2013-2015). Agronomic and multi-criteria analyses on this three-year experimental network highlighted the better performances of the conventional winter type in most tested areas. A second series of trials was set-up in 2018-2019 with more recent cultivars and genotypes deriving from the genomic selection work of the project. Some pea crop models were improved and/or implemented throughout the years for limiting factor diagnosis (DiagVar-pois), pea crop simulations in various pedo-climatic conditions (Azodyn-pea) and links between pea crops and weed management (FlorSys). Economical analyses of the barriers and levers to the diffusion of new pea varieties were also realized, and two series of seed biochemical analyses were conducted to characterize seed technological properties of various genotypes.

(WP6) The smooth progress of the project was aided by an efficient data management and computing. A data repository was created specifically for the project that made all data available to partners directly after their production, in accordance to consortium agreement rules, and facilitated data integration in public and private repositories. The latest genotyping and sequencing technologies were used for producing the numerous genomic resources on pea and faba bean (exome capture SNP detection and genotyping databases on large pea and faba bean panels, transcriptome unigene resources in faba bean).

(WP7) Regular meetings brought together the partners of the project. A large attendance was achieved at Annual Meetings which ensured efficient communication between the partners. Regular Executive Committee and Governing Council meetings ensured good advancement of the scientific activities.

(WP8) Dissemination of the project results was made through the diffusion of brochures, newsletters, booklets, scientific papers, and the creation of a project website and twitter account. Over the years, training sessions were organized for students and project partners, sometimes in collaboration with other PIA projects. The project results were presented in numerous national and international conferences where posters and oral papers were communicated. In 2019, PeaMUST benefited from a large exposure in the international scientific community by organizing the 9th edition of the International Conference on Legume Genetics and Genomics in Dijon, one of the major international events in this field of research.