Multi-Trait Genome-Wide Association Studies of
Sorghum bicolor
fungal pathogens
multivariate GWAS
principal component analysis
Journal
Pathogens (Basel, Switzerland)
ISSN: 2076-0817
Titre abrégé: Pathogens
Pays: Switzerland
ID NLM: 101596317
Informations de publication
Date de publication:
30 May 2023
30 May 2023
Historique:
received:
21
04
2023
revised:
18
05
2023
accepted:
29
05
2023
medline:
28
6
2023
pubmed:
28
6
2023
entrez:
28
6
2023
Statut:
epublish
Résumé
Multivariate linear mixed models (mvLMMs) are widely applied for genome-wide association studies (GWAS) to detect genetic variants affecting multiple traits with correlations and/or different plant growth stages. Subsets of multiple sorghum populations, including the Sorghum Association Panel (SAP), the Sorghum Mini Core Collection and the Senegalese sorghum population, have been screened against various sorghum diseases such as anthracnose, downy mildew, grain mold and head smut. Still, these studies were generally performed in a univariate framework. In this study, we performed GWAS based on the principal components of defense-related multi-traits against the fungal diseases, identifying new potential SNPs (S04_51771351, S02_66200847, S09_47938177, S08_7370058, S03_72625166, S07_17951013, S04_66666642 and S08_51886715) associated with sorghum's defense against these diseases.
Identifiants
pubmed: 37375469
pii: pathogens12060779
doi: 10.3390/pathogens12060779
pmc: PMC10302846
pii:
doi:
Types de publication
Journal Article
Langues
eng
Subventions
Organisme : AFRI, NIFA, USDA
ID : 20156800423492
Organisme : Feed the Future Innovation Lab for Collaborative Research on Sorghum and Millet, a United States Agency for International Development
ID : Cooperative grant number AID-OAA-A-13-00047 with title name: Enabling marker assisted selection for sorghum disease resistance in Senegal and Niger.
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