Genetic and phenotypic characterization of global Lupinus albus genetic resources for the development of a CORE collection
Tanwar, U. K.; Tomaszewska, M.; Czepiel, K.; Neji, M.; Jamil, H.; Rocchetti, L.; Pieri, A.; Bitocchi, E.; Bellucci, E.; Pipan, B.; Meglic, V.; Kroc, M.; Papa, R.; Susek, K.
Show abstract
Lupinus albus is a food grain legume recognized for its high levels of seed protein (30-40%) and oil (6-13%), and its adaptability to different climatic and soil conditions. To develop the next generation of L. albus cultivars, we need access to well-characterized, genetically and phenotypically diverse germplasm. Here we evaluated more than 2000 L. albus accessions with passport data based on 35 agro-morphological traits to develop Intelligent CORE Collections. The reference CORE (R-CORE), representing global diversity, exemplified the genotypic variation of cultivars, breeding/research materials, landraces and wild relatives. A subset of 300 R-CORE accessions was selected as a training CORE (T-CORE), representing the diversity in the entire collection. We divided the L. albus R-CORE into four phenotypic groups (A1, A2, A3 and B) based on principal component analysis, with groups A3 and B distinguished by pod shattering and seed ornamentation, respectively. The coefficient of additive genetic variation differed across morphological traits, phenotypic groups, geographic regions, and according to biological status. These CORE collections will facilitate agricultural research by identifying the genes responsible for desirable traits in crop improvement programs, and by shedding light on the use of orphan genetic resources for origin and domestication studies in L. albus. Understanding the variation in these genetic resources will allow us to develop sustainable tools and technologies that address global challenges such as providing healthy and sustainable diets for all, and contrasting the current climate change crisis.
Matching journals
The top 4 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Multi-location trials and population-based genotyping reveal high diversity and adaptation to breeding environments in a large collection of red clover 97%
- Newly developed MAGIC population allows identification of strong associations and candidate genes for anthocyanin pigmentation in eggplant 96%
- High-throughput phenotyping reveals multiple drought responses of wild and cultivated Phaseolinae beans 96%
Similar papers in this journal
- Comprehensive genotyping of Brazilian Cassava (Manihot esculenta Crantz) Germplasm Bank: insights into diversification and domestication 96%
- Genetic analysis of global faba bean germplasm maps agronomic traits and identifies strong selection signatures for geographical origin 95%
- Genetic characterization of cucumber genetic resources in the NARO Genebank indicates their multiple dispersal trajectories to the East 95%
Similar papers in this journal
- Painting the diversity of a world's favourite fruit: A next generation catalogue of cultivated bananas 96%
- Understanding photothermal interactions will help expand production range and increase genetic diversity of lentil (Lens culinaris Medik.) 95%
- Epistatic Modifiers Influence the Expression of Continual Flowering in Strawberry 94%
Similar papers in this journal
- Genome-wide association studies in a diverse strawberry collection unveil loci controlling agronomic and fruit quality traits 97%
- Harnessing genome prediction in Brassica napus through a nested association mapping population 95%
- Genome-wide development of intra- and inter-specific transferable SSR markers and construction of a dynamic web resource for yam molecular breeding: Y2MD 95%
Similar papers in this journal
- Identification of High Blanchability Donors, Candidate genes and Markers in Groundnut 96%
- New QTLs involved in the control of stigma position in tomato 95%
- Chromosome-Scale Assemblies of Flowering Dogwood Cultivars Enable Identification of Candidate Genes Regulating Anthocyanin Biosynthesis in Leaves and Bracts 95%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.