Genome-Wide Association Analysis of Stable Stripe Rust Resistance Loci in a Chinese Wheat Landrace Panel Using the 660K SNP Array

Abstract

Stripe rust (caused by Puccinia striiformis f. sp. tritici) is one of the most severe diseases affecting wheat production. The disease is best controlled by developing and growing resistant cultivars. Chinese wheat (Triticum aestivum) landraces have excellent resistance to stripe rust. The objectives of this study were to identify wheat landraces with stable resistance and map quantitative trait loci (QTL) for resistance to stripe rust from 271 Chinese wheat landraces using a genome-wide association study (GWAS) approach. The landraces were phenotyped for stripe rust responses at the seedling stage with two predominant Chinese races of P. striiformis f. sp. tritici in a greenhouse and the adult-plant stage in four field environments and genotyped using the 660K wheat single-nucleotide polymorphism (SNP) array. Thirteen landraces with stable resistance were identified, and 17 QTL, including eight associated to all-stage resistance and nine to adult-plant resistance, were mapped on chromosomes 1A, 1B, 2A, 2D, 3A, 3B, 5A, 5B, 6D, and 7A. These QTL explained 6.06–16.46% of the phenotypic variation. Five of the QTL, QYrCL.sicau-3AL, QYrCL.sicau-3B.4, QYrCL.sicau-3B.5, QYrCL.sicau-5AL.1 and QYrCL.sicau-7AL, were likely new. Five Kompetitive allele specific PCR (KASP) markers for four of the QTL were converted from the significant SNP markers. The identified wheat landraces with stable resistance to stripe rust, significant QTL, and KASP markers should be useful for breeding wheat cultivars with durable resistance to stripe rust.

Genome-Wide Association Mapping of Resistance to Warrior (-) Yellow Rust Race at the Seedling Stage in Current Central and Northern European Winter Wheat Germplasm

“…The 6 SNP loci (Table 1) associated with the severity of yellow rust infection (based on the average of infection type in the experiments) represented QTL with small effects (R 2 less than 10%). Such low-effect QTL for resistance to yellow rust at the seedling stage were also identified in the U.S. elite spring wheat lines [19], the German MAGIC winter wheat population [20], and a Chinese wheat landrace association panel [5]. About 50% of the lines in our study showed moderate resistance to both Warrior (-) races at the seedling stage, indicating the presence of a relatively large number of genes with a moderate effect.…”

“…While several studies [5,15,19,20] have identified similar QTL controlling resistance to yellow rust at both seedling and adult stages, suggesting the presence of resistance genes for all stages, others [39,40], including our study, have not found common QTL or representative SNP loci between these two developmental stages. This divergence may be because many other loci contribute more to resistance in the fields in response to a population of pathotypes, while in seedling tests there is only a limited response to a few races.…”

“…The correlation coefficients between the seedling and adult plant stages were low (-0.01 to 0.25) because most lines were susceptible at the seedling stage but resistant in the field trials. Such a low correlation (0.19 and 0.46) was also found in the studies by Yao et al [5] and Rollar et al [20]. The discrepancy could be due to the interaction between host and pathogen at the seedling stage in the greenhouse and at the adult plant stage in the field.…”

“…When leaves are covered by uredinia, photosynthesis is severely limited and continuous production of urediniospors deprives host plants of water and nutrients, reducing plant growth, number of ears and grains per ear, and test weight. The disease can result in an average loss of 13% of grain yield [3] and up to 100% in fields planted with highly susceptible cultivars under extreme yellow rust-friendly weather conditions [4,5]. Chlorosis or necrosis (hypersensitive reaction) is a disease symptom in resistant plants [6].…”

Genome-wide association study of coleoptile length with Shanxi wheat

“…To facilitate the identification of genes in functional regions, the chromosomal region was delimited at 6.11 Mb ( Yao et al, 2021 ). Genes within the target region were identified using the genome browser (JBrowse) on the WheatOmics-bata website 1 ( Ma et al, 2021 ).…”