Historic recombination in a durum wheat breeding panel enables high-resolution mapping of Fusarium head blight resistance quantitative trait loci

Abstract

The durum wheat line DT696 is a source of moderate Fusarium head blight (FHB) resistance. Previous analysis using a bi-parental population identified two FHB resistance quantitative trait loci (QTL) on chromosome 5A: 5A1 was co-located with a plant height QTL, and 5A2 with a major maturity QTL. A Genome-Wide Association Study (GWAS) of DT696 derivative lines from 72 crosses based on multienvironment FHB resistance, plant height, and maturity phenotypic data was conducted to improve the mapping resolution and further elucidate the genetic relationship of height and maturity with FHB resistance. The Global Tetraploid Wheat Collection (GTWC) was exploited to identify durum wheat lines with DT696 allele and additional recombination events. The 5A2 QTL was confirmed in the derivatives, suggesting the expression stability of the 5A2 QTL in various genetic backgrounds. The GWAS led to an improved mapping resolution rendering the 5A2 interval 10 Mbp shorter than the bi-parental QTL mapping interval. Haplotype analysis using SNPs within the 5A2 QTL applied to the GTWC identified novel haplotypes and recombination breakpoints, which could be exploited for further improvement of the mapping resolution. This study suggested that GWAS of derivative breeding lines is a credible strategy for improving mapping resolution.

Separation of the effects of two reduced height (Rht) genes and genomic background to select for less Fusarium head blight of short-strawed winter wheat (Triticum aestivum L.) varieties

“…For anther retention, in addition to Rht-D1b , several medium- and small-effect QTL were detected in genomic regions including chromosomes 2A, 3A, 4A, 5A and 7A. Previous studies also identified QTL for anther retention on chromosomes 3A (Muqaddasi et al 2019 ), 4A (Buerstmayr and Buerstmayr 2015 ) and 5A (Buerstmayr and Buerstmayr 2015 ; Steiner et al 2019a ; Sari et al 2020 ; Xu et al 2020 ). These QTL, representing the genomic background, contribute to the adjustments of anther retention, particularly within Rht genes groups.…”

“…In addition to Rht-D1 , a larger number of small-loci controlling FHB severity were identified on other genomic regions such as 2A, 2B, 4A, 5A, 6A, 6B and 7B, which were considered as genomic background contributing the variation of FHB severity among semi-dwarf genotypes. Several FHB resistance QTL were also reported on chromosomes 2A (He et al 2016a ; Gadaleta et al 2019 ), 2B (Sari et al 2018 ; Ollier et al 2020 ), 4A (He et al 2016a ; Zhang et al 2021 ; Nannuru et al 2022 ), 5A (Steiner et al 2019a ; Ruan et al 2020 ; Sari et al 2020 ; Nannuru et al 2022 ), 6A (Ruan et al 2020 ), 6B (Cuthbert et al 2007 ; Ollier et al 2020 ) and 7B (Sari et al 2018 ; Ollier et al 2020 ). In addition, FHB resistance QTL on chromosomes 5A and 7B explained more than 7% of the genetic variation each and can be considered as important locally adapted QTL to improve FHB resistance in European winter wheat.…”

Potential of Genomic Selection and Integrating “Omics” Data for Disease Evaluation in Wheat

“…Phenotyping over multiple environments is routinely conducted to identify superior FHB resistant germplasm. Phenotypic selection has been successful in spite of interactions between FHB resistance loci and the environment, and the unfavorable association of FHB resistance with agronomic traits such as plant height (PH) and maturity [32][33][34][35].…”

“…The undesirable association between agronomic traits such as plant height (PH) and heading date (HD) with FHB resistance is a challenge for the application of GS. There is compelling evidence supporting the negative correlation between FHB resistance and PH and HD, which is often reflected as the co-localization of PH and HD QTL with FHB resistance QTL [32,34,35,93]. The dwarfing alleles of Rht-B1 and Rht-D1 have been associated with FHB susceptibility [94,95].…”

“…Thus, it seems realistic to develop program-specific breeder SNP chips that captures the available haplotypes at a reasonable cost. The decision on what SNPs to be included in the breeder chip could be based on the estimation of LD decay over genetic distances inferred from high-density QTL mapping studies [34,35,143] or comprehensive haplotype mapping of wheat diversity panels [136,144]. Thus, in addition to high-throughput phenotyping, advances in genotyping technologies are also shaping the future of GS including SNP arrays and DNA/RNA sequencing.…”