This is the first identification of QTLs underlying resistance in Cucumis melo to an isolate of Pseudoperonospora cubensis identified as Clade 2/mating type A1. Pseudoperonospora cubensis, causal organism of cucurbit downy mildew (CDM), causes severe necrosis and defoliation on Cucumis melo (melon). A recombinant inbred line population (N = 169) was screened against an isolate of P. cubensis (Clade 2/mating type A1) in replicated greenhouse and growth chamber experiments. SNPs (n = 5633 bins) identified in the RIL population were used for quantitative trait loci (QTL) mapping. A single major QTL on chromosome 10 (qPcub-10.3-10.4) was consistently associated with resistance across all experiments, while a second major QTL on chromosome 8 (qPcub-8.3) was identified only in greenhouse experiments. These two major QTLs were identified on the same chromosomes (8 and 10) but in different locations as two major QTLs (qPcub-8.2 and qPcub-10.1) previously identified for resistance to P. cubensis Clade 1/mating type A2. Kompetitive allele-specific PCR (KASP) markers were developed for these four major QTLs and validated in the RIL population through QTL mapping. These markers will provide melon breeders a high-throughput genotyping toolkit for development of melon cultivars with broad tolerance to CDM.
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http://dx.doi.org/10.1007/s00122-023-04333-x | DOI Listing |
J Sci Food Agric
January 2025
Research Center of Buckwheat Industry Technology, College of Life Science, Guizhou Normal University, Huaxi University Town, Gui'an New District, China.
Background: Tartary buckwheat (Fagopyrum tartaricum) is particularly vulnerable to pre-harvest sprouting (PHS) due to its extended flowering and fruiting cycle, especially during periods of prolonged rainfall. This susceptibility has significant adverse effects on yield, quality and post-harvest processing. In this study, a recombinant inbred lines (RILs) population (XJ-RILs) was developed from a cross between the PHS-susceptible Tartary buckwheat variety 'Xiaomiqiao' (female parent) and the highly PHS-resistant variety 'Jinqiaomai 2' (male parent).
View Article and Find Full Text PDFBMC Genomics
January 2025
Crop Institute, Jiangxi Academy of Agricultural Sciences, Nanchang, 330200, China.
Leaf is the main photosynthetic organ at the seedling stage of rapeseed and leaf size is a crucial agronomic trait affecting rapeseed yield. Understanding the genetic mechanisms underlying leaf size is therefore important for rapeseed breeding. In this study, QTL mapping for three traits related to leaf size, i.
View Article and Find Full Text PDFPlant Dis
January 2025
State Fruit Experiment Station, Missouri State University, Mountain Grove, Missouri, United States;
Powdery mildew, caused by the fungus , is one of the primary causes of grape yield loss across the globe. While numerous resistance loci have been identified in various grapevine species, the genetic determinants of susceptibility to remain largely unexplored. Understanding the genetics of susceptibility for pathogenesis is equally important for developing durable resistance grapevines against this pathogen.
View Article and Find Full Text PDFBMC Plant Biol
January 2025
The Institute of Plant Sciences and Genetics, Faculty of Agriculture, The Hebrew University of Jerusalem, Rehovot, 7610001, Israel.
Background: Plant breeding research heavily relies on wild species, which harbor valuable traits for modern agriculture. This work employed a new introgression population derived from Solanum pennellii (LA5240), a wild tomato native to Peru, composed of 1,900 genotyped backcross inbred lines (BILs_BC2S6) in the tomato inbreds LEA and TOP cultivated genetic backgrounds. This Peruvian accession was found resistant to the most threatening disease of tomatoes today, caused by the tobamovirus tomato brown rugose fruit virus (ToBRFV).
View Article and Find Full Text PDFJ Genet Genomics
January 2025
Department of Botany and Plant Sciences, University of California, Riverside, CA 92521, USA. Electronic address:
The QTL by environment interaction (Q×E) effect is hard to detect because there are no effective ways to control the genomic background. In this study, we propose a novel linear mixed model that simultaneously analyzes data from multiple environments to detect Q×E interactions. This model incorporates two different kinship matrices derived from the genome-wide markers to control both main and interaction polygenic background effects.
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