Identification of QTLs for resistance to leaf and stem rusts in bread wheat (Triticum aestivum L.) using a mapping population of ‘Pamyati Azieva × Paragon’

Abstract

Leaf rust (LR) and stem rust (SR) are harmful fungal diseases of bread wheat (Triticum aestivum L.). The purpose of this study was to identify QTLs for resistance to LR and SR that are effective in two wheat-growing regions of Kazakhstan. To accomplish this task, a population of recombinant inbred lines (RILs) of ‘Pamyati Azieva × Paragon’ was grown in the northern and southeastern parts of Kazakhstan, phenotyped for LR/SR severities, and analyzed for key yield components. The study revealed a negative correlation between disease severity and plant productivity in both areas. The mapping population was genotyped using a 20,000 Illumina SNP array. A total of 4595 polymorphic SNP markers were further selected for linkage analysis after filtering based on missing data percentage and segregation distortion. Windows QTL Cartographer was applied to identify QTLs associated with LR and SR resistances in the RIL mapping population studied. Two QTLs for LR resistance and eight for SR resistance were found in the north, and the genetic positions of eight of them have matched the positions of the known Lr and Sr genes, while two QTLs for SR were novel. In the southeast, eight QTLs for LR and one for SR were identified in total. The study is an initial step of the genetic mapping of LR and SR resistance loci of bread wheat in Kazakhstan. Field trials in two areas of the country and the genotyping of the selected mapping population have allowed identification of key QTLs that will be effective in regional breeding projects for better bread wheat productivity.

QTL Mapping for Seedling and Adult Plant Resistance to Leaf and Stem Rusts in Pamyati Azieva × Paragon Mapping Population of Bread Wheat

“…The first group includes 8 out of 13 QTLs identified for SR resistance. For three of them-QSr.ipbb-2B.4 (seedling resistance to PKCTC), QSr.ipbb-6B.5 (seedling resistance to TKRTF and APR in RIBSP), and QSr.ipbb-6B.7 (seedling resistance to TKRTF)-QTLs for SR resistance with similar positions in the genome were identified in a previous work involving the PA × Par mapping population [27] and in a GWAS study using resistance data obtained from RIBSP [51]. Similar to the LR study, these findings may indicate the stability of identified QTLs.…”

“…The QTLs identified in this study were analyzed in comparison with previously reported QTLs for LR and SR resistance in the PA × Par RILs population [27] and with QTLs for LR and SR resistance at RIBSP identified using genome-wide association study (GWAS) [51]. The location of each identified QTL was compared to the genetic positions of known Lr and Sr genes (Table 9).…”

“…To meet this goal, the Pamyati Azieva × Paragon (PA × Par) RILs mapping population (MP) was studied in field and greenhouse (GH) conditions. Previously, this population was successfully used for the analysis of yield-related traits [25] and adult plant resistance to LR and SR in south-east and northern Kazakhstan in 2018 [26,27]. Hence, the current study adds the investigation of seedling resistance in the MP to LR and SR races.…”

Genome-wide association mapping for resistance to leaf, stem, and yellow rusts of common wheat under field conditions of South Kazakhstan

“…Linkage mapping has been commonly used to identify QTLs associated with resistance to SR (Wang et al, 2015;Chen et al, 2018), LR (Xue et al, 2018;Kthiri et al, 2018), and YR (Zeng et al, 2019). This method was also successfully applied in QTL mapping for LR and SR resistance in Kazakhstan (Genievskaya et al, 2019). However, linkage mapping has certain disadvantages, the most substantial of which is low allele richness and prolonged identification of resistant QTLs due to the long time required for the construction of a mapping population as well as the large sample sizes (Beavis, 1998;Xu et al, 2017).…”

Identification of quantitative trait loci of agronomic traits in bread wheat using a Pamyati Azieva × Paragon mapping population harvested in three regions of Kazakhstan

“…In this regard, RIL populations have been widely used in QTL mapping studies. For instance, RILs have successfully been used for the identification and validation of QTLs underpinning the traits of agronomic importance in staple cereals such as wheat ( Börner et al., 2002 ; Griffiths et al., 2012 ; Ma et al., 2014 ; Ma et al, 2015 ; El-Feki et al, 2018 ; Onyemaobi et al, 2018 ; Tshikunde et al., 2019 ; Tura et al, 2020 ; Hu et al., 2020 ), Additionally, QTL studies of traits such as lodging ( Yu & Chen, 2013 ), grain hardness ( Sourdille et al, 1996 ), grain protein content ( Prasad et al, 2003 ) and thousand grain weight ( Varshney, Korzun & Börner, 2004 ), early heading ( Xu et al, 2005 ), yield and its components ( Kumar et al, 2007 ; Li et al, 2014 ; Shi et al., 2017 ; El-Feki et al, 2018 ; Onyemaobi et al, 2018 ; Tshikunde et al., 2019 ; Kumar et al, 2019 ; Tura et al, 2020 ; Hu et al., 2020 ; Ren et al., 2021 ), drought tolerance ( Duggan, Domitruk & Fowler, 2000 ; Tahmasebi et al, 2017 ; Du et al, 2020 ) and disease resistance ( Saini et al., 2022 ; Genievskaya et al., 2019 ; Genievskaya et al., 2020 ) in wheat were mainly based on the use of RILs. Importantly, the recently published wheat reference genome ( Appels et al, 2018 ) allows us to retrieve the list of genes within these QTL intervals, identify their physical genomic coordinates and conduct functional annotation analysis.…”