Identification of Wheat Leaf Rust Resistance Genes in Chinese Wheat Cultivars and the Improved Germplasms

Abstract

Leaf rust is an important wheat disease that is a significant hindrance for wheat production in most areas of the world. Breeding resistant cultivars can effectively and economically control the disease. In the present study, a wheat collection consisting of 100 cultivars from China and 18 improved germplasms from global landrace donors together with 36 known single Lr gene lines were tested with 20 strains of Puccinia triticina Eriks. in the seedling stage to postulate the Lr gene in the cultivars and germplasms. In addition, 12 diagnostic molecular markers specific to 10 Lr genes were used to detect the presence of the Lr genes in the wheat collection. Resistance to leaf rust of these cultivars at the adult plant stage was tested in fields under natural infection during the 2016 to 2018 cropping seasons in Baoding, Hebei Province. The gene postulation combined with molecular marker detection showed that six Lr genes (Lr1, Lr26, Lr33, Lr34, Lr45, and Lr46) were identified in 44 wheat accessions, including 37 cultivars and seven improved germplasms. Among the 44 wheat accessions postulated with Lr genes, Lr1 was present in four accessions, Lr26 in 12 accessions, Lr33 in two accessions, Lr34 in 14 accessions, Lr45 in three accessions, and Lr46 in 16 accessions. In the collection of 118 cultivars/germplasms, 34 wheat lines displayed adult-plant resistance carrying Lr34, Lr46, and/or underdetermined genes. Therefore, a high level of leaf rust resistance can be achieved through the combination of all-stage resistance and adult-plant resistance genes together in wheat cultivars.

Pathogen-induced alterations in methylome during Lr48-mediated APR in wheat (Triticum aestivum L.) 

“…ASR provides race-speci c resistance during seedling stage to the adult stage, whereas APR provides resistance only at the adult stage. In wheat, APR genes for leaf rust have been classi ed by some in two groups, one group including 7 genes (Lr12, Lr13, Lr22a/b, Lr35, Lr37, Lr48 and Lr49) that are race-speci c and hypersensitive and the other group having 8 genes (Lr34, Lr46, Lr67, Lr68, Lr74, Lr75, Lr77 and Lr78) that are race-nonspeci c and non-hypersensitive , 41,42 . Other workers recognized only the 8 non-race-speci c non-hypersensitive genes as APR genes 43,44 .…”

“…It has also been shown that while ASR is qualitative in nature following Flor's gene-for-gene relationship, APR is quantitative in nature, where an individual APR gene or QTL perhaps functions along with a number of minor genes. As many as ~80 QTLs were known for APR for leaf rust as in the year 2014 42 ; 170 more such genes must have been reported since then (manuscript under preparation). After recognizing the pathogen, like ASR, APR also initiates a defense response involving signal transduction and spatial/temporal differential expression of a large number of defense genes 43 .…”

Identification of known leaf rust resistance genes in bread wheat cultivars from China

“…E'mai 17, E'mai 12, Xi'nong 126, Shaannong 981, Shaanmai 1591 and Shaanmai 175 had other known Lr genes or unknown Lr genes. Lr34, Lr46, Lr67 and Lr68 are APR Lr genes, the molecular markers co-segregated with or closely linked to these were used to test these cultivars (Wu et al 2019). E'mai 17 carried Lr26 and Lr13, and this cultivar was found to have slow rusting based on the FDS.…”

“…Gebrewahid et al (2017) identified twelve Lr genes, 1, 26, 3ka, 11, 10, 2b, 13, 21, 34, 37, 44, and 46 in eighty-three Chinese common wheat cultivars using eighteen Pt races. Wu et al (2019) postulated six Lr genes (1, 26, 33, 34, 45 and 46) in forty-four wheat accessions using twenty Pt races.…”

Residual Self-Calibration and Self-Attention Aggregation Network for Crop Disease Recognition

“…The occurrence of crop diseases has a certain negative impact on agricultural production. If crop diseases are not discovered in time, it will increase the risk of food loss [1], especially for some major food crops, such as corn, rice, wheat, etc., which are key to meeting human living needs and promoting productivity development. Therefore, it is of great practical significance to explore an intelligent, low-cost, and highly accurate method to implement crop disease recognition.…”