Leaf rust caused by the fungus f. sp. is one of the most dangerous diseases of common wheat. Infections caused by fungal pathogens reduce the quantity and quality of yields of many cereal species. The most effective method to limit plant infection is to use cultivars that show rust resistance. Genetically conditioned horizontal-type resistance (racial-nonspecific) is a desirable trait because it is characterized by more stable expression compared to major (R) genes that induce racially specific resistance, often overcome by pathogens. Horizontal resistance is conditioned by the presence of slow rust genes, which include genes and . This study aimed to identify markers linked to both genes in 64 common wheat lines and to develop multiplex PCR reaction conditions that were applied to identify both genes simultaneously. The degree of infestation of the analyzed lines was also assessed in field conditions during the growing season of 2017 and 2018. Simple sequence repeat anchored-polymerase chain reaction (SSR-PCR) marker was identified during analysis in line PHR 4947. The presence of a specific sequence has also been confirmed in multiplex PCR analyses. In addition to gene , gene was identified in this genotype. Lines PHR 4947 and PHR 4819 were characterized by the highest leaf rust resistance in field conditions. During STS-PCR analyses, the marker of gene was identified in most of the analyzed lines. This marker was not present in the following genotypes: PHR 4670, PHR 4800, PHR 4859, PHR 4907, PHR 4922, PHR 4949, PHR 4957, PHR 4995, and PHR 4997. The presence of a specific sequence has also been confirmed in multiplex PCR analyses. Genotypes carrying the markers of the analyzed gene showed good resistance to leaf rust in field conditions in both 2017 and 2018. Research has demonstrated that marker assisted selection (MAS) and multiplex PCR techniques are excellent tools for selecting genotypes resistant to leaf rust.
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http://dx.doi.org/10.1515/biol-2021-0018 | DOI Listing |
Phytopathology
January 2025
Agricultural University of Hebei, 289 Lingyusi, Baoding, Baoding, Hebei, China, 071001;
Wheat leaf rust, caused by Erikss. (), is one of the most devastating diseases in common wheat ( L.) globally.
View Article and Find Full Text PDFFront Plant Sci
December 2024
Genebank Department, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Seeland, Germany.
Wheat ( spp.) is one of the most important cereal crops in the world. Several diseases affect wheat production and can cause 20-80% yield loss annually.
View Article and Find Full Text PDFTheor Appl Genet
December 2024
Plant Breeding Institute, School of Life and Environmental Sciences, The University of Sydney, Cobbitty, NSW, 2570, Australia.
We analysed the chromosomal structures of two wheat-Thinopyrum intermedium addition lines Z4 and Z5 and resolved the linkage relationship between the leaf rust and stripe rust resistance genes in Z4. Wheat addition lines Z4 and Z5 carrying rust resistance genes from Thinopyrum intermedium (JJJJStSt, 2n = 6x = 42) together with three wheat lines involved in the production of these addition lines were analysed by rust response, 90K SNP genotyping, and molecular cytogenetic analysis. Seedling leaf rust (LR) responses to five diverse pathotypes indicated that the LR resistance gene(s) was located in translocation chromosome T3DS-3AS.
View Article and Find Full Text PDFTheor Appl Genet
December 2024
Hungarian Research Network (HUN-REN), Centre for Agricultural Research, Agricultural Institute, Martonvásár, 2462, Hungary.
GBS read coverage analysis identified a Robertsonian chromosome from two Thinopyrum subgenomes in wheat, conferring leaf and stripe rust resistance, drought tolerance, and maintaining yield stability. Agropyron glael (GLAEL), a Thinopyrum intermedium × Th. ponticum hybrid, serves as a valuable genetic resource for wheat improvement.
View Article and Find Full Text PDFFront Plant Sci
December 2024
College of Agronomy, College of Mechanical and Electronic Engineering, Shandong Agricultural University, Taian, Shandong, China.
In order to achieve precise discrimination of leaf diseases in the Maize/Soybean intercropping system, i.e. leaf spot disease, rust disease, mixed leaf diseases, this study utilized hyperspectral imaging and deep learning algorithms for the classification of diseased leaves of maize and soybean.
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