Identification of haplotypes associated with resistance to Fusarium graminearum in spring oat (Avena sativa L.)

Author:

Sørensen Espen Sannes12ORCID,Windju Susanne1,Jansen Constantin1,Sonesson Anna Kristina3,Lillemo Morten2ORCID,Alsheikh Muath12

Affiliation:

1. Graminor AS Ridabu Norway

2. Department of Plant Science Norwegian University of Life Sciences Ås Norway

3. Nofima AS Ås Norway

Abstract

AbstractFusarium head blight (FHB) is the predominant disease in oat in Norway caused by the fungus Fusarium graminearum. It causes yield loss, reduced seed quality, reduced germination ability and accumulation of deoxynivalenol (DON). The FHB resistance is quantitative, and most genes have small effect. Markers with verified effect in the breeding program could further enhance the resistance breeding. This study aims to use a large and diverse population of 541 lines to identify quantitative trait loci (QTL) associated to FHB resistance in a genome‐wide association study (GWAS) and verify their effect in independent breeding material. The material has been tested in six environments over three years and two locations in spawn inoculated and mist irrigated disease trials. The traits tested were germination ability and DON accumulation. A total of 15 significant QTL‐regions were detected across 12 different linkage groups. Haplotypes for each region was constructed and the effect of the alleles in each environment was calculated, which identified the most likely resistant and susceptible alleles. Five QTL‐regions were validated showing consistent effect in the GWAS population and the breeding material. Stacking of the resistant alleles of these regions from zero to five showed significant decrease in DON values and increased germination ability. The haplotype information of a set of historical and modern Nordic varieties were analysed, and the results could be used to select parents for future crossings. The validated haplotypes from this study can be used either to do marker assisted selection (MAS) or improve genomic prediction models in breeding programs.

Funder

Norges Forskningsråd

Publisher

Wiley

Subject

Plant Science,Genetics,Agronomy and Crop Science

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