Assessment of molecular markers and marker-assisted selection for drought tolerance in barley (Hordeum vulgare L.)
2024
Akmaral Baidyussen | Gulmira Khassanova | Maral Utebayev | Satyvaldy Jatayev | Rystay Kushanova | Sholpan Khalbayeva | Aigul Amangeldiyeva | Raushan Yerzhebayeva | Kulpash Bulatova | Carly Schramm | Peter Anderson | Colin L. D. Jenkins | Kathleen L. Soole | Yuri Shavrukov
This review updates the present status of the field ofmolecular markers and marker-assisted selection (MAS), using the example ofdrought tolerance in barley. The accuracy of selected quantitative traitloci (QTLs), candidate genes and suggested markers was assessed in the barleygenome cv. Morex. Six commonstrategies are described for molecular marker development, candidate geneidentification and verification, and their possible applications in MAS toimprove the grain yield and yield components in barley under droughtstress. These strategies are based onthe following five principles: (1) Molecular markers are designated as genomic‘tags’, and their ‘prediction’ is strongly dependent on their distance from acandidate gene on genetic or physical maps; (2) plants react differently underfavourable and stressful conditions or depending on their stage of development;(3) each candidate gene must be verified by confirming its expression in therelevant conditions, e.g., drought; (4) the molecular marker identified must bevalidated for MAS for tolerance to drought stress and improved grain yield; and(5) the small number of molecular markers realized for MAS in breeding, fromamong the many studies targeting candidate genes, can be explained by thecomplex nature of drought stress, and multiple stress-responsive genes in eachbarley genotype that are expressed differentially depending on many otherfactors.
Afficher plus [+] Moins [-]Mots clés AGROVOC
Informations bibliographiques
Cette notice bibliographique a été fournie par Institute of Agricultural Information, Chinese Academy of Agricultural Sciences
Découvrez la collection de ce fournisseur de données dans AGRIS