Mapping QTLs for different traits in conventional and organic management systems and evaluating the effects of Lr34/Yr18 and Lr37/Yr17 in a Canadian western hard spring wheat population
Notice bibliographique
Résumé
Canadian western red spring wheat (CWRS) has been predominantly cultivated class in Western Canada, because of its premium quality attributes and excellent adaptability to the relatively short growing season. Early maturity, short plant stature, higher grain yield, protein content and dough strength, and moderate to high levels of resistance to stem rust, leaf rust, stripe rust, common bunt, and fusarium head blight are important breeding objectives in western Canada. In the first study, we evaluated a mapping population of 168 recombinant inbred lines derived from a cross between two CWRS cultivars ‘Peace’ and ‘CDC Stanley’ for agronomic and quality traits under organic and conventional managements from 2016 to 2017. Days to heading and maturity, grain yield and protein content, thousand kernel weight (TKW) and test weight expressed high broad-sense heritability across two management systems. The population was genotyped with 90K single nucleotide polymorphism (SNP) array and quantitative trait loci (QTL) analysis was performed. However, only six of 50 QTLs could be detected across two management systems. The phenotypic variance explained for each trait varied from 0.5 – 23.3 % in conventional and 1.3 – 25.9 % in organic environment. A QTL on chromosome 2D was associated with multiple traits (plant height, grain yield, grain protein content and test weight in conventional and days to maturity, grain yield and plant height in organic environment), which is possibly due to tight linkage of multiple loci on this chromosomal segment, whereas another coincidental QTL on 4B for grain yield and protein content in conventional management system could be due to pleiotropic effect. We also validated a major pre-harvest sprouting (PHS) resistance QTL Qphs-usask-4A in the mapping population. PHS resistant genotypes possessed significantly higher falling number, however standardized methods are required to examine the effect of Qphs-usask-4A.The second study was to investigate the combined effects of Lr34/Yr18 and Lr37/Yr17 genes on disease resistance in the same mapping population. Lines with only Lr34/Yr18 expressed reduced plant height, SDS sedimentation and yield penalty, possibly due to genetic linkage or pleiotropic effects of co-expression of leaf tip necrosis on flag leaf and rust resistance. The presence of Lr37/Yr17 was not associated with reduction in grain yield or end-use quality. In the breeding practice, we failed to integrate Lr34/Yr18 and Lr37/Yr17 genes with considerable grain yield, protein content, dough strength and early maturity, which was most likely due to insufficient population size. Thus, whole-scale dependence on markers in a marker-assisted selection program will likely eliminate desirable genotypes. Nonetheless, five lines with substantial disease resistance conferred by the Lr34/Yr18 and/or Lr37/Yr17 resistance alleles and improved agronomic and quality characters remain in the breeding process that has potential to become parental materials.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».