Optimizing the protein value of pea seeds – PEAVALUE

In WP1, a translational approach between pea and Arabidopsis will increase knowledge of the massive accumulation of seed storage proteins. WP2 will exploit natural and induced genetic variability in pea to provide the data framework required to boost the breeding of pea varieties combining protein quantity and quality. WP3 will study the intrinsic physicochemical properties of protein isolates derived from pea seeds contrasted in their protein profiles, with the aim to identify protein profiles with improved and tunable techno-functional properties.

In WP1, transcription factors involved in storage protein synthesis are identified using a translational approach between pea and Arabidopsis. In WP2, natural and TILLING-induced genetic variability is exploited to search for protein profiles with better amino acid balance. These data will be used for genome-wide association studies (GWAS) to identify alleles or genes associated with high protein value. Genetic variability for protein or amino acid composition is exploited in WP3 which focuses on the physicochemical properties of proteins (solubility, surfactant capacity, aggregation and gelation properties). Protein isolates are prepared and the intrinsic physicochemical properties of the proteins are being analyzed to identify protein profiles with improved functional properties. The PEAVALUE data will be stored in a database that can be used as a reference for the pea protein community.

It is of paramount importance to increase the use of grain legumes in the current context of climate change associated with agroecological practices, in which pea has a key role to play. Despite increasing public awareness of the desirability of increasing the consumption of pea proteins, the use of pea protein remains limited. By providing reference data on pea protein quality, PEAVALUE will serve as a launching pad towards the development of pea varieties of high protein value.

Project in progress

By producing protein-rich seeds without N-fertilizers, legumes can contribute to satisfying the growing demand for plant proteins for human and animal nutrition while reducing environmental impacts. PEAVALUE will target pea (Pisum sativum L.), one of the most important grain legume crops in Europe, which is of increasing interest for the food industry. However, the use of pea proteins is still limited, notably due to imbalanced amino acid composition and insufficient information on their intrinsic characteristics and techno-functional properties (e.g., solubility, emulsifying, gelling and aggregation properties). The PEAVALUE project aims to improve nutritional and functional properties of these pea proteins. To address this challenge, PEAVALUE will bring together three partners addressing key research aspects; on the regulation of seed protein synthesis (IJPB), genetics of nutritional seed quality (AGROECO), and physicochemical and techno-functional properties of pea proteins (PAM). The project is structured in three complementary and interconnected work packages (WP). In WP1, a translational approach between pea and Arabidopsis will increase knowledge on the accumulation of seed-specific proteins. This WP will provide insights into the functional activity of seed-expressed transcription factor genes and their roles in storage protein synthesis, leading to the identification of regulators of protein accumulation in the seed (Task 1.1). Targeted mutations (TILLING) in homologous regulatory genes will be explored in pea to identify allelic variants associated with novel protein profiles (Task 1.2), whose properties will be investigated in WP2 and WP3. WP2 will provide the data framework required to boost the breeding of pea varieties combining protein quantity and nutritional quality. In this WP, the amino acid composition of seeds from TILLING lines (WP1) will be studied, and a panel of 200 pea ecotypes will be mined for seed protein content, protein and amino acid composition (Task 2.1). Correlations between the ratios of 11S/7S globulins, vicilins/convicilins, and protein/amino acid quality indices, will be calculated to identify protein profiles or genotypes with enhanced quality (amino acid balance). These data will be used for Genome Wide Association Studies (GWAS) using a recently enriched SNP-set offering prospects for linking specific alleles or genes to high seed protein value (Task 2.2). WP3 will exploit the genetic variability revealed in WP1 and WP2 to identify protein profiles with improved globulin recovery and techno-functional properties. A standardized procedure (alkaline extraction and isoelectric precipitation) giving high protein recovery from pea flour while minimizing protein denaturation will be used. We will apply alkaline extraction to the panel of 200 pea genotypes used in WP2 with the aim of identifying, by GWAS, allelic variants or genes associated with variations in the extractability of the different globulins, which remains a limiting factor (Task 3.1). Protein isolates will be prepared from 30 genotypes contrasted in protein composition. The intrinsic physicochemical properties of the proteins, including solubility, surfactant capacity, aggregation and gelling ability, will be studied to identify protein profiles with improved and tunable techno-functional properties (Task 3.2). All the data will be (i) registered in a database that will be a reference for the grain legume community and (ii) integrated through correlation studies and multi-factorial analyses to identify protein profiles with improved nutritional and/or techno-functional properties (Task 3.3).