Mapping Quantitative Trait Loci Associated with Agronomic Traits and Disease Resistance in a Canadian Spring Wheat Mapping Population
Notice bibliographique
Résumé
Due to reduced genotyping costs and high-throughput technologies, marker assisted selection has become a valuable tool for plant breeders, allowing for identifying traits of interest in screened germplasm. Marker assisted selection requires the identification of stable, and consistent quantitative trait loci (QTL) that will become reliable markers. The Canada Western Red Spring (CWRS) class of common wheat (T. aestivum) is the most produced class of wheat in western Canada and requires a complex arrangement of agronomic traits and adequate disease resistance. The objective of this thesis was to identify QTL associated with economically important diseases in western Canada such as stripe rust (Puccinia striiformis f. sp. tritici), leaf rust (Puccinia triticina), and the leaf spot complex, and agronomic traits that are important to producers and end users including earliness, grain yield, protein content and gluten strength. A total of 208 recombinant inbred lines derived from crossing Canadian spring wheat (T. aestivum) cultivars ‘Peace’ and ‘Carberry’ were evaluated from 2014 to 2017 in disease nurseries located in Alberta and British Columbia, and conventional and organic yield trials in 2016 and 2017 in Edmonton, Alberta and genotyped with DArTseq markers. Using the least squares means of the combined environments, three QTL associated with stripe rust, four QTL associated with leaf rust, and three QTL associated with leaf spotting were identified. We confirm the presence of a stripe rust QTL on chromosome 4B, with the allele conferring resistance contributed by ‘Carberry’, that has been previously reported by others. We also identified two QTL associated with stripe rust and leaf rust on chromosome 2A, in which the alleles conferring resistance were contributed by ‘Peace’, corresponding with previous studies that identified QTL on chromosome 2A that were contributed by a close relative of ‘Peace’. Phenotyping of agronomic traits was conducted in conventional and organic environments to identify consistent QTL across management systems. We identified thirty-eight QTL for nine agronomic traits and QTL clusters on chromosomes 4B and 7D were identified consistently across conventional and organic environments. The largest QTL was identified as an allele contributed by ‘Carberry’, and is most likely the Rht-B1b height reducing gene, due to explaining 53% of the total phenotypic variance and being located on 4B. The second largest QTL was located on chromosome 1A and associated with sedimentation volume and explained 41% of the total phenotypic variance. Results from this study suggest that ‘Carberry’ could be an attractive germplasm for breeders to enhance resistance against stripe rust and leaf spot with minor resistance alleles, and ‘Peace’ consistently contributed an allele on 7D that reduced plant height by six centimeters, and maturity by two days, but reduced grain yield by 300 kg ha-1. Minor effect QTL with LOD scores as low as 3.4 were consistently identified across management-specific environments and suggests that stable QTL may not need to be large in effect.
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 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,002 | 0,000 |
| Communication savante | 0,001 | 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 ».