QTL mapping of adult-plant resistance to leaf rust in the Chinese landraces Pingyuan 50/Mingxian 169 using the wheat 55K SNP array

Leaf rust (LR) is a destructive foliar disease of common wheat (Triticum aestivum L.) worldwide. Growing resistant cultivars with adult plant resistance (APR) are the ideal way to control the disease. The aim of the present study was to map quantitative trait loci (QTL) for leaf rust resistance using 137 doubled-haploid (DH) lines derived from the Pingyuan 50 × Mingxian 169 cross. The same population was previously tested for stripe rust (YR) and powdery mildew (PM) response, and the data were reassessed to determine the presence of QTL with pleiotropic effects. Phenotyping for leaf rust response was conducted in six environments at Baoding in Hebei province and Zhoukou in Henan province. The DH lines were genotyped using the wheat 55K SNP array and additional SSR markers. Eight QTLs for LR resistance were identified in the present study using the inclusive composite interval mapping (ICIM). The flanking sequences of all the SNP probes were subjected to BLAST against the Chinese Spring reference sequence to determine physical positions. Six LR resistance loci were contributed by Pingyuan 50, but QLr.hebau-2DS2 and QLr.hebau-3AL were from Mingxian 169. QLr.hebau-3DS, a new and stable QTL detected in all environments, explained 4.2–20.0% of the phenotypic variation. Another new QTL, QLr.hebau-3AL detected in four environments had a PVE (phenotypic variance explained) of 5.7–10.1%. QLr.hebau-1BL, QLr.hebau-2DS2, and QLr.hebau-7DL are new loci. Two QTLs showed potential pleiotropic effects on disease response. QTL on chromosome 7DL might be pleiotropic to LR and PM, and the QTL on 5DL might confer pleiotropic resistance to LR and YR. Kompetitive allele-specific PCR (KASP) markers for QLr.hebau-3AL and QLr.hebau-3DS were successfully developed and validated. The QTL identified with their flanking markers and in the present study could be useful for fine mapping, candidate gene mining, and marker-assisted selection (MAS).