Genetic Diversity Assessment of Portuguese Cultivated Vicia faba L. through IRAP Markers

Genetic and Metabolite Variability among Commercial Varieties and Advanced Lines of Vicia faba L

Vicia faba L. (faba bean) is one of the most promising pulse crops due to its nutritional value and high nitrogen fixation capacity. The aim of the present study was to compare the genetic diversity and the seed metabolite profiles of five genetic materials of faba bean. Specifically, three newly developed advanced lines (KK18, KK14 and KK10) and two commercial cultivars (POLIKARPI and TANAGRA), were evaluated for this purpose. Genetic diversity among populations was assessed by SCoT molecular markers. Through UPGMA dendrogram, genetic distances between populations were estimated. Untargeted metabolomics analysis of the seeds was performed employing GC/EI/MS. The cultivar POLYKARPI exhibited the highest polymorphism. All varieties showed a higher within-cultivars and advanced lines variability than between. POLYKARPI and KK14 had the lowest genetic distances, while KK18 and TANAGRA presented the highest ones. The advanced line KK18 displayed the best nutritional profile, the highest concentration of desirable metabolites (lactic acid and trehalose), the lowest concentration of anti-nutritional factors (oxalic acid) and the lowest concentration of saturated fatty acids (palmitic and stearic acid). According to the results of the present study, KK18 line is a very promising material for further exploration and utilization in breeding programs.

IRAP-analysis for evaluating the genetic stability of endemic and endangered species of the Western Caucasus flora in the collection in vitro

The characterization of genetic diversity is one of the main components of the genetic resources collection and management. Molecular markers are the most effective tool for characterizing and assessing genetic diversity in plant collections. IRAP (inter-retrotransposons amplified polymorphism) markers have proven to be some of the most effective for characterizing and evaluating germplasm, confirming the genetic fidelity of in vitro preserved cultivars and species. In this regard, the aim of this work is to test several IRAP primers to identify genetic polymorphism and study the genetic fidelity of three rare and endemic flora species of the Western Caucasus during in vitro conservation. Approbation of 16 IRAP-primers on the investigated species was carried out for Eryngium maritimum L., Galanthus woronowii Losinsk. and Campanula sclerophylla Kolak. The results made it possible to select the most efficient of them for genetic fidelity analysis of micropropagated plants. Out of 16 IRAP primers 8 amplified PCR products in Eryngium maritimum. In Galanthus woronowii as well 8 of 16 IRAP primers resulted in the amplification with the number of DNA fragments ranging from 2 to 12. In Campanula sclerophylla 9 of 16 IRAP primers amplified 1 to 11 fragments, depending on the marker. The results of the genotyping of regenerants were compared with data on stock in situ plants, which were the source of explants for in vitro conservation. In total, 60 regenerants for each species of the natural flora of the Western Caucasus were involved in the study. The results obtained demonstrated no genetic changes of the regenerants in all the studied species. These results were confirmed using ISSR analysis of an extended sample set of microplants for each species. The results obtained can serve as evidence of a low probability of genetic disorders during in vitro propagation and conservation of the species Eryngium maritimum L., Galanthus woronowii Losinsk. and Campanula sclerophylla Kolak.

Root traits of European Vicia faba cultivars-Using machine learning to explore adaptations to agroclimatic conditions

Faba bean (Vicia faba L.) is an important source of protein, but breeding for increased yield stability and stress tolerance is hampered by the scarcity of phenotyping information. Because comparisons of cultivars adapted to different agroclimatic zones improve our understanding of stress tolerance mechanisms, the root architecture and morphology of 16 European faba bean cultivars were studied at maturity. Different machine learning (ML) approaches were tested in their usefulness to analyse trait variations between cultivars. A supervised, that is, hypothesis-driven, ML approach revealed that cultivars from Portugal feature greater and coarser but less frequent lateral roots at the top of the taproot, potentially enhancing water uptake from deeper soil horizons. Unsupervised clustering revealed that trait differences between northern and southern cultivars are not predominant but that two cultivar groups, independently from major and minor types, differ largely in overall root system size. Methodological guidelines on how to use powerful ML methods such as random forest models for enhancing the phenotypical exploration of plants are given.