Nested Association Mapping to Identify Stripe Rust Resistance in Spring Wheat
Notice bibliographique
Résumé
Stripe rust, caused by Puccinia striiformis Westend. f. sp. tritici Erikss. (Pst), is one of the most devastating diseases affecting wheat (Triticum aestivum L.). It is one of the five ‘priority one’ diseases for which a minimum level of resistance is required when registering a wheat cultivar with desirable traits. Among all the available management approaches, genetic resistance is the most effective, easy-to-use, and environmentally friendly approach to combating stripe rust. Researchers are fighting a never-ending war against the ever-evolving dynamic population of the pathogen. Thus, the continuous identification of new sources of resistance is essential for breeding resistant wheat cultivars. In this study, we developed three nested association mapping (NAM) populations (n = 741, 575, and 1098), consisting of 16 RIL families. These populations were developed in the genetic background of susceptible wheat cultivars Avocet, Vesper, and Cardale by crossing with 6, 6, and 4 new, diverse, and resistant source lines, respectively. Comprehensive phenotypic evaluations of the NAM populations were conducted in multiple environments to quantify disease severity. Following phenotypic evaluation, all lines were genotyped using a wheat 7K SNP assay, generating a robust marker dataset for genetic analyses. Linkage maps for each RIL family were constructed, and these were further integrated into a consensus map to facilitate joint QTL mapping for each NAM population. Major QTL were defined as those explaining more than 20% of the phenotypic variance, whereas stable QTL were consistently detected across multiple environments. 34 major and stable QTL were identified from 16 RIL families using composite interval mapping (CIM). The most significant and stable QTL from individual families were QYr.lrdc-7B.2, QYr.lrdc-7D (RIL family 3: Avocet/P2382), QYr.lrdc-5D (RIL family 5: Avocet/P2432), QYr.lrdc-1A.1 (RIL family 8: Vesper/P2686), QYr.lrdc-7B.1, QYr.lrdc-7B.2 (RIL family 10: Vesper/P2688), QYr.lrdc-2B (RIL family 12: Vesper/P2265), and QYr.lrdc-2B (RIL family 16: Cardale/P2703), with the phenotypic variance explained (PVE) ranging from 31% to 62%. Joint mapping of NAM populations 1, 2, and 3 was carried out to identify 20, 21, and 14 QTL, respectively. In the individual family analyses, we were able to detect family-specific loci; however, the power was limited because each family only segregated for a subset of alleles. By combining all families into the NAM framework, we increased both mapping resolution and statistical power. Furthermore, several QTL were only revealed through joint mapping, demonstrating the added power of combining information across families. The overlapping chromosomal regions across multiple RIL families indicate genomic regions consistently contributing stripe rust resistance. These results show that NAM population is a powerful tool for dissecting complex traits and discovering new resistance alleles. The major-effect QTL and their linked molecular markers offer valuable resources for marker-assisted selection. Overall, the study provides a clear understanding of the genetic architecture of stripe rust resistance in wheat to accelerate the Canadian wheat breeding program.
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 | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| 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 ».