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A new stem rust resistance gene, Sr68, from Thinopyrum junceum was transferred to chromosome arm 1BS of wheat using monosomic-induced Robertsonian translocation and ph1b-induced homoeologous recombination. Stem rust, caused by Puccinia graminis f. sp. tritici (Pgt), is one of the most destructive diseases of wheat (Triticum aestivum L.). Identifying and deploying stem rust resistance (Sr) genes continues as a key strategy for managing this disease. Here, we report the identification and introgression of a novel Sr gene from wheat 'Chinese Spring' (CS)-Thinopyrum junceum group-4 chromosome (designated 4E) disomic addition line HD3505 (2n = 44) to a wheat chromosome. We first developed an F population by crossing HD3505 to a CS line monosomic for chromosome 4D (CS M4D). A stem rust-resistant F plant carrying a Robertsonian translocation chromosome was identified and consecutively backcrossed to CS ph1b and CS to produce a population of 1209 BCF plants. Three BCF plants with reduced Th. junceum chromatin (BG2133, BG5136, and BG2161) carrying the Sr gene were identified. Genomic and oligonucleotide multiplex fluorescence in situ hybridization analysis revealed that Th. junceum chromosome segments carrying the Sr gene in the three translocation lines were in the distal region of chromosome arm 1BS, with sizes of 33.22-34.51% of the translocation chromosomes. The Sr gene in the translocation lines was designated Sr68. Additionally, the translocation replaced the Gli-B1 locus, eliminating ω-gliadins that encode immunoreactive epitopes, potentially reducing gluten immunogenicity. The newly developed wheat lines with Sr68 and associated molecular markers provide new resistance resources against Ug99 and other Pgt races for wheat improvement.
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http://dx.doi.org/10.1007/s00122-025-05005-8 | DOI Listing |
Plant Genome
September 2025
Agriculture Victoria, Centre for AgriBioscience, AgriBio, Bundoora, Victoria, Australia.
Global wheat (Triticum aestivum L.) production faces significant challenges due to the destructive nature of leaf (Puccinia triticina; leaf rust [Lr]), stem (Puccinia graminis; stem rust [Sr]), and stripe (Puccinia striiformis; stripe rust [Yr]) rust diseases. Despite ongoing efforts to develop resistant varieties, these diseases remain a persistent challenge due to their highly evolving nature.
View Article and Find Full Text PDFPlant Environ Interact
October 2025
Discipline of Plant Pathology, College of Agriculture, Engineering & Science; School of Agricultural, Earth and Environmental Sciences University of KwaZulu-Natal Pietermaritzburg Republic of South Africa.
Asian soybean rust (ASR) is caused by the biotrophic fungus Syd. & P. Syd.
View Article and Find Full Text PDFPlant Genome
September 2025
Molecular Plant Breeding, Institute of Agricultural Sciences, ETH Zurich, Zurich, Switzerland.
Italian ryegrass (Lolium multiflorum Lam.) is an important forage grass, providing a major source of feed for ruminants in temperate regions. Due to its highly heterozygous and repeat-rich genome, high-quality chromosome-level genome assemblies are scarce for Italian ryegrass.
View Article and Find Full Text PDFTheor Appl Genet
August 2025
Crop Improvement and Genetics Research Unit, Western Regional Research Center, USDA-ARS, Albany, CA, 94710, USA.
A new stem rust resistance gene, Sr68, from Thinopyrum junceum was transferred to chromosome arm 1BS of wheat using monosomic-induced Robertsonian translocation and ph1b-induced homoeologous recombination. Stem rust, caused by Puccinia graminis f. sp.
View Article and Find Full Text PDFPlant Dis
August 2025
ICAR - National Bureau of Plant Genetic Resources, Divison of Genomic Resources, Lab 1, ICAR-NBPGR, Pusa Campus, New Delhi, New Delhi, DL, India, 110012;
Over the past two decades, genomic prediction (GP), also known as genomic selection (GS), has been widely adopted in plant and animal breeding programs worldwide. GP is a promising approach that utilizes genomic markers to estimate genomic-estimated breeding values (GEBVs), facilitating the selection of superior individuals. In this study, we assessed the performance of five GP models- Genomic Best Linear Unbiased Prediction (GBLUP), Reproducing Kernel Hilbert Space regression (RKHS) and Bayesian methods (BayesA, BayesB, and BayesC)-for predicting seedling and adult plant resistance (APR) to leaf/brown rust (LR), stem/black rust (SR), and yellow/stripe rust (YR) in wheat using a panel of 347 diverse germplasm accessions.
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