Genome editing of a rice CDP-DAG synthase confers multipathogen resistance.

The discovery and application of genome editing introduced a new era of plant breeding by giving researchers efficient tools for the precise engineering of crop genomes1. Here we demonstrate the power of genome editing for engineering broad-spectrum disease resistance in rice (Oryza sativa). We first isolated a lesion mimic mutant (LMM) from a mutagenized rice population. We then demonstrated that a 29-base-pair deletion in a gene we named RESISTANCE TO BLAST1 (RBL1) caused broad-spectrum disease resistance and showed that this mutation caused an approximately 20-fold reduction in yield. RBL1 encodes a cytidine diphosphate diacylglycerol synthase that is required for phospholipid biosynthesis2. Mutation of RBL1 results in reduced levels of phosphatidylinositol and its derivative phosphatidylinositol 4,5-bisphosphate (PtdIns(4,5)P2). In rice, PtdIns(4,5)P2 is enriched in cellular structures that are specifically associated with effector secretion and fungal infection, suggesting that it has a role as a disease-susceptibility factor3. By using targeted genome editing, we obtained an allele of RBL1, named RBL1Δ12, which confers broad-spectrum disease resistance but does not decrease yield in a model rice variety, as assessed in small-scale field trials. Our study has demonstrated the benefits of editing an LMM gene, a strategy relevant to diverse LMM genes and crops.

High-density mapping of durable and broad-spectrum stripe rust resistance gene Yr30 in wheat.

KEY MESSAGE: The durable stripe rust resistance gene Yr30 was fine-mapped to a 610-kb region in which five candidate genes were identified by expression analysis and sequence polymorphisms. The emergence of genetically diverse and more aggressive races of Puccinia striiformis f. sp. tritici (Pst) in the past twenty years has resulted in global stripe rust outbreaks and the rapid breakdown of resistance genes. Yr30 is an adult plant resistance (APR) gene with broad-spectrum effectiveness and its durability. Here, we fine-mapped the YR30 locus to a 0.52-cM interval using 1629 individuals derived from residual heterozygous F5:6 plants in a Yaco"S"/Mingxian169 recombinant inbred line population. This interval corresponded to a 610-kb region in the International Wheat Genome Sequencing Consortium (IWGSC) RefSeq version 2.1 on chromosome arm 3BS harboring 30 high-confidence genes. Five genes were identified as candidate genes based on functional annotation, expression analysis by RNA-seq and sequence polymorphisms between cultivars with and without Yr30 based on resequencing. Haplotype analysis of the target region identified six haplotypes (YR30_h1-YR30_h6) in a panel of 1215 wheat accessions based on the 660K feature genotyping array. Lines with YR30_h6 displayed more resistance to stripe rust than the other five haplotypes. Near-isogenic lines (NILs) with Yr30 showed a 32.94% higher grain yield than susceptible counterparts when grown in a stripe rust nursery, whereas there was no difference in grain yield under rust-free conditions. These results lay a foundation for map-based cloning Yr30.

Evaluation of Stripe Rust Resistance and Chip Detection Resistance Genes in 286 Xinjiang Wheat Cultivars and Breeding Lines.

Wheat stripe rust is a destructive disease worldwide, caused by Puccinia striiformis f. sp. tritici (Pst). Resistance breeding is the most effective method of controlling stripe rust. Xinjiang is a relatively independent epidemic region of wheat stripe rust in China. In recent years, wheat stripe rust in this area has shown an upward trend. Therefore, the purpose of this study was to evaluate the resistance level of wheat cultivars (lines) to the prevalent Pst races and determine the genetic background of stripe rust resistance genes in Xinjiang. Six predominant Pst races in China were used to study resistance of 286 wheat cultivars (lines) at both seedling under controlled conditions and adult-plant stages under field conditions. In the seedling tests, 175 (61.19%) entries were resistant to races CYR23, 125 (43.71%) to CYR29, 153 (53.50%) to CYR31, 88 (30.77%) to CYR32, 174 (60.84%) to CYR33, and 98 (34.27%) to CYR34. Among the resistant entries, 23 (8.04%) were resistant to all six races. In the field test, 135 (47.20%) entries were resistant to the tested mixed races. Through comparing the responses in the seedling and adult-plant stages, 109 (38.11%) entries were found to have adult-plant resistance (APR), and 14 (4.90%) entries have all-stage resistance (ASR). The 286 wheat entries were also tested using a wheat breeder chip containing 12 Yr resistance loci. Among these entries, 44 (15.38%) were found to have single gene, 221 (77.27%) have two or more genes, and 21 (7.34%) have none of the 12 genes, including 144 (50.35%) with Yr30 and 5 (1.75%) with YrSP. Entries with two or more genes have stronger resistance to Pst. Overall, the majority of entries have all-stage and/or adult-plant resistance, but their genes for resistance in addition to the 12 tested Yr genes need to be determined. It is also necessary to introduce more effective resistance genes in the breeding programs to improve stripe rust resistance in wheat cultivars in Xinjiang.

Identification of two novel QTL for Fusarium head blight resistance in German wheat cultivar Centrum.

Fusarium head blight (FHB) is a devastating disease that occurs in warm and humid environments. The German wheat Centrum has displayed moderate to high levels of FHB resistance in the field for many years. In this study, an F6:8 recombinant inbred line (RIL) population derived from cross Centrum × Xinong 979 was evaluated for FHB response following point inoculation in five environments. The population and parents were genotyped using the GenoBaits Wheat 16 K Panel. Stable quantitative trait loci (QTL) associated with FHB resistance in Centrum were mapped on chromosome arms 2DS and 5BS. The most effective QTL, located in 2DS, was identified as a new chromosome region represented by a 1.4 Mb interval containing 17 candidate genes. Another novel QTL was mapped in chromosome arm 5BS of a 5BS-7BS translocation chromosome. In addition, two environmentally-sensitive QTL were mapped on chromosome arms 2BL from Centrum and 5AS from Xinong 979. Polymorphisms of flanking allele-specifc quantitative PCR (AQP) markers AQP-6 for QFhb.nwafu-2DS and 16K-13073 for QFhb.nwafu-5BS were validated in a panel of 217 cultivars and breeding lines. These markers could be useful for marker-assisted selection of FHB resistance and also provide a starting point for fine mapping and marker-based cloning of the resistance genes.

Rapid and Sensitive Detection of Fungicide-Resistant Crop Fungal Pathogens Using an Isothermal Amplification Refractory Mutation System.

Fungicide abuse leads to the emergence of fungicide-resistant fungal pathogens, thus posing a threat to agriculture and food safety. Here, we developed an isothermal amplification refractory mutation system (termed iARMS) allowing us to resolve genetic mutations, enabling rapid, sensitive, and potentially field-applicable detection of fungicide-resistant crop fungal pathogens. iARMS yielded a limit of detection of 25 aM via a cascade signal amplification strategy of recombinase polymerase amplification (RPA) and Cas12a-mediated collateral cleavage at 37 °C within 40 min. Specificity for fungicide-resistant Puccinia striiformis (P. striiformis) detection was guaranteed by RPA primers and the flexible sequence of gRNA. The iARMS assay allowed us to detect as low as 0.1% cyp51-mutated P. striiformis that showed resistance to the demethylase inhibitor (DMI), which was 50 times more sensitive than the sequencing techniques. Thus, it is promising for the discovery of rare fungicide-resistant isolates. We applied iARMS to investigate the emergence of fungicide-resistant P. striiformis in western China and found that its proportion was over 50% in Qinghai, Sichuan, and Xinjiang Province. iARMS can serve as a molecular diagnostic tool for crop diseases and facilitate precision plant disease management.

Core root-associated prokaryotic community and its relationship to host traits across wheat varieties.

The root-associated microbiomes play important roles in plant growth. However, it is largely unknown how wheat variety evolutionary relatedness shapes each subcommunity in the root microbiome and, in turn, how these microbes affect wheat yield and quality. Here we studied the prokaryotic communities associated with the rhizosphere and root endosphere in 95 wheat varieties at regreening and heading stages. The results indicated that the less diverse but abundant core prokaryotic taxa occurred among all varieties. Among these core taxa, we identified 49 and 108 heritable amplicon sequence variants, whose variations in relative abundances across the root endosphere and rhizosphere samples were significantly affected by wheat variety. The significant correlations between phylogenetic distance of wheat varieties and prokaryotic community dissimilarity were only observed in non-core and abundant subcommunities in the endosphere samples. Again, wheat yield was only significantly associated with root endosphere microbiota at the heading stage. Additionally, wheat yield could be predicted using the total abundance of 94 prokaryotic taxa as an indicator. Our results demonstrated that the prokaryotic communities in the root endosphere had higher correlations with wheat yield and quality than those in the rhizosphere; thus, managing root endosphere microbiota, especially core taxa, through agronomic practices and crop breeding, is important for promoting wheat yield and quality.

High transparent conductive Ga-doped ZnO-based multilayer thin films with embedded ultrathin TiN layer deposited in oxygen-containing atmosphere.

To avoid metal layer oxidation during the deposition of transparent conductive oxide (TCO)/metal/TCO multilayer films in an oxygen-containing atmosphere, the ultra-thin (<10 nm) titanium nitride (TiN) layer has been proposed to replace metal embedding in gallium-doped zinc oxide (GZO) film for the development of indium-free transparent electrodes. The effects of TiN thickness on the structure, morphology, electrical, and optical properties of GZO/TiN/GZO multilayer thin films deposited in argon-oxygen mixtures on glass substrates by magnetron sputtering are investigated. The experimental results reveal that multilayers with the 8 nm-thick TiN layer have the optimal performance (figure of merit of 2.75 × 10-1 Ω-1): resistivity of 4.68 × 10-5â€…Ω cm, and optical transmittance of above 91% in the visible region, which is superior to the sandwich film with the metal embedded layer.

High density mapping of wheat stripe rust resistance gene QYrXN3517-1BL using QTL mapping, BSE-Seq and candidate gene analysis.

KEY MESSAGE: Fine mapping of a major stripe rust resistance locus QYrXN3517-1BL to a 336 kb region that includes 12 candidate genes. Utilization of genetic resistance is an effective strategy to control stripe rust disease in wheat. Cultivar XINONG-3517 (XN3517) has remained highly resistant to stripe rust since its release in 2008. To understand the genetic architecture of stripe rust resistance, Avocet S (AvS) × XN3517 F6 RIL population was assessed for stripe rust severity in five field environments. The parents and RILs were genotyped by using the GenoBaits Wheat 16 K Panel. Four stable QTL from XINONG-3517 were detected on chromosome arms 1BL, 2AL, 2BL, and 6BS, named as QYrXN3517-1BL, QYrXN3517-2AL, QYrXN3517-2BL, and QYrXN3517-6BS, respectively. Based on the Wheat 660 K array and bulked segregant exome sequencing (BSE-Seq), the most effective QTL on chromosome 1BL is most likely different from the known adult plant resistance gene Yr29 and was mapped to a 1.7 cM region [336 kb, including twelve candidate genes in International Wheat Genome Sequencing Consortium (IWGSC) RefSeq version 1.0]. The 6BS QTL was identified as Yr78, and the 2AL QTL was probably same as QYr.caas-2AL or QYrqin.nwafu-2AL. The novel QTL on 2BL was effective in seedling stage against the races used in phenotyping. In addition, allele-specifc quantitative PCR (AQP) marker nwafu.a5 was developed for QYrXN3517-1BL to assist marker-assisted breeding.

Development of breeder chip for gene detection and molecular-assisted selection by target sequencing in wheat.

Wheat is an essential food crop and its high and stable yield is suffering from great challenges due to the limitations of current breeding technology and various stresses. Accelerating molecularly assisted stress-resistance breeding is critical. Through a meta-analysis of published loci in wheat over the last two decades, we selected 60 loci with main breeding objectives, high heritability, and reliable genotyping, such as stress resistance, yield, plant height, and resistance to spike germination. Then, using genotyping by target sequencing (GBTS) technology, we developed a liquid phase chip based on 101 functional or closely linked markers. The genotyping of 42 loci was confirmed in an extensive collection of Chinese wheat cultivars, indicating that the chip can be used in molecular-assisted selection (MAS) for target breeding goals. Besides, we can perform the preliminary parentage analysis with the genotype data. The most significant contribution of this work lies in translating a large number of molecular markers into a viable chip and providing reliable genotypes. Breeders can quickly screen germplasm resources, parental breeding materials, and intermediate materials for the presence of excellent allelic variants using the genotyping data by this chip, which is high throughput, convenient, reliable, and cost-efficient. Supplementary Information: The online version contains supplementary material available at 10.1007/s11032-023-01359-3.

Genome-wide association study reveals the genetic variation and candidate gene for grain calcium content in bread wheat.

KEY MESSAGE: This study provides important information on the genetic basis of GCaC in wheat, thus contributing to breeding efforts to improve the nutrient quality of wheat. Calcium (Ca) plays important roles in the human body. Wheat grain provides the main diet for billions of people worldwide but is low in Ca content. Here, grain Ca content (GCaC) of 471 wheat accessions was determined in four field environments. A genome-wide association study (GWAS) was performed to reveal the genetic basis of GCaC using the phenotypic data form four environments and a wheat 660 K single nucleotide polymorphism (SNP) array. Twelve quantitative trait locus (QTLs) for GCaC were identified on chromosomes 1A, 1D, 2A, 3B, 6A, 6D, 7A, and 7D, which was significant in at least two environments. Haplotype analysis revealed that the phenotypic difference between the haplotypes of TraesCS6D01G399100 was significant (P ≤ 0.05) across four environments, suggesting it as an important candidate gene for GCaC. This research enhances our understanding of the genetic architecture of GCaC for further improving the nutrient quality of wheat.

Reduction of Rhizoctonia cerealis Infection on Wheat Through Host- and Spray-Induced Gene Silencing of an Orphan Secreted Gene.

Rhizoctonia cerealis is a soilborne fungus that can cause sharp eyespot in wheat, resulting in massive yield losses found in many countries. Due to the lack of resistant cultivars, fungicides have been widely used to control this pathogen. However, chemical control is not environmentally friendly and is costly. Meanwhile, the lack of genetic transformation tools has hindered the functional characterization of virulence genes. In this study, we attempted to characterize the function of virulence genes by two transient methods, host-induced gene silencing (HIGS) and spray-induced gene silencing (SIGS), which use RNA interference to suppress the pathogenic development. We identified ten secretory orphan genes from the genome. After silencing these ten genes, only the RcOSP1 knocked-down plant significantly inhibited the growth of R. cerealis. We then described RcOSP1 as an effector that could impair wheat biological processes and suppress pathogen-associated molecular pattern-triggered immunity in the infection process. These findings confirm that HIGS and SIGS can be practical tools for researching R. cerealis virulence genes. [Formula: see text] Copyright © 2022 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.

Countrywide inter-epidemic region migration pattern suggests the role of southwestern population in wheat stripe rust epidemics in China.

Understanding countrywide pathogen population structure and inter-epidemic region spread is crucial for deciphering crop potential losses. Wheat stripe rust caused by Puccinia striiformis f. sp. tritici is a destructive disease that affects worldwide wheat production, widespread in China, representing largest epidemic region globally. This study aimed to understand the population structure and migration route of P. striiformis f. sp. tritici across China based on sampling from 15 provinces representing six epidemic zones, viz., over-summering, over-wintering, eastern, Yun-Gui, Xinjiang and Tibet epidemic regions. High genotypic diversity was recorded in over-summering, Tibet and over-wintering epidemic regions. Epidemic regions partly explain population subdivision with variable divergence (FST  = 0.005-0.344). Xinjiang and Tibet epidemic regions were independent epidemic zones with least sharing of genotypes. Among other epidemic zones, i.e. over-summering, over-wintering, eastern and Yun-Gui epidemic zones, re-sampling MLGs, clustering-based structure, DAPC analyses, relative migration and low divergence (FST from 0.006 to 0.073) revealed frequent geneflow. Yun-Gui epidemic regions, with a potential for both over-summering and over-wintering, could play an important role in causing epidemics in main wheat-cultivating areas of China. High diversity, recombination signatures and inter-epidemic region migration patterns need to be considered in host-resistant cultivar development in China and neighbouring countries, considering risk of long-distance migration capacity of pathogen.

Accuracy improvement of single-sample calibration laser-induced breakdown spectroscopy with self-absorption correction.

The single sample calibration laser-induced breakdown spectroscopy (SSC-LIBS) is quite suitable for the fields where the standard sample is hard to obtain, including space exploration, geology, archaeology, and jewelry identification. But in practice, the self-absorption effect of plasma destroys the linear relationship of spectral intensity and element concentration based on the Lomakin-Scherbe formula which is the guarantee of the high accuracy of the SSC-LIBS. Thus, the self-absorption effect limits the quantitative accuracy of SSC-LIBS greatly. In this work, an improved SSC-LIBS with self-absorption correction (SSC-LIBS with SAC) is proposed for the promotion of quantitative accuracy of SSC-LIBS. The SSC-LIBS with SAC can correct the intensity ratio of spectral lines in the calculation of SSC-LIBS through relative self-absorption coefficient K without complicated preparatory information. The alloy samples and pressed ore samples were used to verify the effect of the SSC-LIBS with SAC. Compared with SSC-LIBS, for alloy samples, the average RMSEP and average ARE of SSC-LIBS with SAC decreased from 0.83 wt.% and 13.75% to 0.40 wt.% and 4.06%, respectively. For the pressed ore samples, the average RMSEP and average ARE of SSC-LIBS with SAC decreased from 4.77 wt.% and 90.48% to 2.34 wt.% and 14.60%. The experimental result indicates that SSC-LIBS with SAC has a great improvement of quantitative accuracy and better universality compared with traditional SSC-LIBS, which is a mighty promotion of the wide application of SSC-LIBS.

Classification of steel using laser-induced breakdown spectroscopy combined with deep belief network.

The identification of steels is a crucial step in the process of recycling and reusing steel waste. Laser-induced breakdown spectroscopy (LIBS) coupled with machine learning is a convenient method to classify the types of materials. LIBS can generate characteristic spectra of various samples as input variable for steel classification in real time. However, the performance of classification model is limited to the complex input due to similar chemical composition in samples and nonlinearity problems between spectral intensities and elemental concentrations. In this study, we developed a method of LIBS coupled with deep belief network (DBN), which is suitable to deal with a nonlinear problem, to classify 13 brands of special steels. The performance of the training and validation sets were used as the standard to optimize the structure of DBN. For different input, such as the intensities of full-spectra signals and characteristic spectra lines, the accuracies of the optimized DBN model in the training, validation, and test set are all over 98%. Moreover, compared with the self-organizing maps, linear discriminant analysis (LDA), k-nearest neighbor (KNN) and back-propagation artificial neural networks (BPANN), the result of the test set showed that the optimized DBN model performed second best (98.46%) in all methods using characteristic spectra lines as input. The test accuracy of the DBN model could reach 100% and the maximum accuracy of other methods ranged from 62.31% to 96.16% using full-spectra signals as input. This study demonstrates that DBN can extract representative feature information from high-dimensional input, and that LIBS coupled with DBN has great potential for steel classification.

Epistatic interaction effect between chromosome 1BL (Yr29) and a novel locus on 2AL facilitating resistance to stripe rust in Chinese wheat Changwu 357-9.

KEY MESSAGE: Four stable QTL for adult plant resistance were identified in wheat line Changwu 357-9, including a new QTL on 2AL showing significant interaction with Yr29 to reduce stripe rust severity. Stripe rust (yellow rust) is a serious disease of bread wheat (Triticum aestivum L.) worldwide. Genetic resistance is considered the most economical, effective and environmentally friendly method to control the disease and to minimize the use of fungicides. The current study focused on characterizing the components of stripe rust resistance and understanding the interactions in Changwu 357-9 (CW357-9)/Avocet S RIL population. A genetic linkage map constructed using a new GenoBaits Wheat 16K Panel and the 660K SNP array had 5104 polymorphic SNP markers spanning 3533.11 cM. Four stable QTL, consistently identified across five environments, were detected on chromosome arms 1BL, 2AL, 3DS, and 6BS in Changwu357-9. The most effective QTL QYrCW357-1BL was Yr29. The 6BS QTL was identified as Yr78, which has been combined with the 1BL QTL in many wheat cultivars and breeding lines. The novel QTL on 2AL with moderate effect showed a stable and significant epistatic interaction with Yr29. The QTL on 3DL should be same as QYrsn.nwafu-3DL and enriches the overall stripe rust resistance gene pool for breeding. Polymorphisms of flanking AQP markers AX-110020417 (for QYrCW357-1BL), AX-110974948 (for QYrCW357-2AL), AX-109466386 (for QYrCW357-3DL), and AX-109995005 (for QYrCW357-6BS) were evaluated in a diversity panel including 225 wheat cultivars and breeding lines. These results suggested that these high-throughput markers could be used to introduce QYrCW357-1BL, QYrCW357-2AL, QYrCW357-3DL, and QYrCW357-6BS into commercial wheat cultivars. Combinations of these genes with other APR QTL should lead to higher levels of stripe rust resistance along with the beneficial effects of multi-disease resistance gene Yr29 on improving resistance to other diseases.

Enhanced stripe rust resistance obtained by combining Yr30 with a widely dispersed, consistent QTL on chromosome arm 4BL.

KEY MESSAGE: YrFDC12 and PbcFDC, co-segregated in chromosome 4BL, and significantly interacted with Yr30/Pbc1 to enhance stripe rust resistance and to promote pseudo-black chaff development. Cultivars with durable resistance are the most popular means to control wheat stripe rust. Durable resistance can be achieved by stacking multiple adult plant resistance (APR) genes that individually have relatively small effect. Chinese wheat cultivars Ruihua 520 (RH520) and Fengdecun 12 (FDC12) confer partial APR to stripe rust across environments. One hundred and seventy recombinant inbred lines from the cross RH520 × FDC12 were used to determine the genetic basis of resistance and identify genomic regions associated with stripe rust resistance. Genotyping was carried out using 55 K SNP array, and eight quantitative trait loci (QTL) were detected on chromosome arms 2AL, 2DS, 3BS, 4BL, 5BL (2), and 7BL (2) by inclusive composite interval mapping. Only QYr.nwafu-3BS from RH520 and QYr.nwafu-4BL.2 (named YrFDC12 for convenience) from FDC12 were consistent across the four testing environments. QYr.nwafu-3BS is likely the pleiotropic resistance gene Sr2/Yr30. YrFDC12 was mapped in a 2.1-cM interval corresponding to 12 Mb and flanked by SNP markers AX-111121224 and AX-89518393. Lines harboring both Yr30 and YrFDC12 displayed higher resistance than the parents and expressed pseudo-black chaff (PBC) controlled by loci Pbc1 and PbcFDC12, which co-segregated with Yr30 and YrFDC12, respectively. Both marker-based and pedigree-based kinship analyses revealed that YrFDC12 was inherited from founder parent Zhou 8425B. Fifty-four other wheat cultivars shared the YrFDC12 haplotype. These results suggest an effective pyramiding strategy to acquire highly effective, durable stripe rust resistance in breeding.

Populations of Puccinia striiformis f. sp. tritici in Winter Spore Production Regions Spread from Southwestern Oversummering Areas in China.

Stripe rust, caused by Puccinia striifomis f. sp. tritici (Pst), is one of the most destructive wheat diseases in China. Understanding the interregional dispersal of Pst inoculum is important for controlling the disease. In the present study, wheat stripe rust samples collected from the winter spore production and oversummering regions in November 2018 to March 2019 were studied through virulence testing and molecular characterization. From 296 isolates, 96 races were identified using a set of 19 Chinese wheat cultivars and 111 races were identified using 18 Yr single-gene lines as differentials. The isolates from Hubei province in the winter spore production area had the highest similarity in virulence with those from eastern Yunnan in the oversummering area. Molecular characterization using 13 simple-sequence repeat and 43 Kompetitive allele specific PCR-single nucleotide polymorphism markers supported the conclusion that the Pst populations in the winter spore production regions were from Guizhou and eastern Yunnan, key oversummering areas in the southwest. Furthermore, an analysis of wind movement at the 700-hPa high altitude also supported the conclusion of spore dispersal from the southwestern oversummering region to the south-central winter spore production region. The results of this study provide an epidemiological basis for deploying various effective resistance genes in different regions to control stripe rust.

Genome-Wide Association Study on Root System Architecture and Identification of Candidate Genes in Wheat (Triticum aestivum L.).

The root tissues play important roles in water and nutrient acquisition, environmental adaptation, and plant development. In this study, a diversity panel of 388 wheat accessions was collected to investigate nine root system architecture (RSA) traits at the three-leaf stage under two growing environments: outdoor pot culture (OPC) and indoor pot culture (IPC). Phenotypic analysis revealed that root development was faster under OPC than that under IPC and a significant correlation was observed between the nine RSA traits. The 660K single-nucleotide polymorphism (SNP) chip was used for a genome-wide association study (GWAS). Significant SNPs with a threshold of -log10 (p-value) ≥ 4 were considered. Thus, 36 quantitative trait loci (QTLs), including 13 QTL clusters that were associated with more than one trait, were detected, and 31 QTLs were first identified. The QTL clusters on chromosomes 3D and 5B were associated with four and five RSA traits, respectively. Two candidate genes, TraesCS2A01G516200 and TraesCS7B01G036900, were found to be associated with more than one RSA trait using haplotype analysis, and preferentially expressed in the root tissues. These favourable alleles for RSA traits identified in this study may be useful to optimise the root system in wheat.

A large-scale genomic association analysis identifies the candidate causal genes conferring stripe rust resistance under multiple field environments.

The incorporation of resistance genes into wheat commercial varieties is the ideal strategy to combat stripe or yellow rust (YR). In a search for novel resistance genes, we performed a large-scale genomic association analysis with high-density 660K single nucleotide polymorphism (SNP) arrays to determine the genetic components of YR resistance in 411 spring wheat lines. Following quality control, 371 972 SNPs were screened, covering over 50% of the high-confidence annotated gene space. Nineteen stable genomic regions harbouring 292 significant SNPs were associated with adult-plant YR resistance across nine environments. Of these, 14 SNPs were localized in the proximity of known loci widely used in breeding. Obvious candidate SNP variants were identified in certain confidence intervals, such as the cloned gene Yr18 and the major locus on chromosome 2BL, despite a large extent of linkage disequilibrium. The number of causal SNP variants was refined using an independent validation panel and consideration of the estimated functional importance of each nucleotide polymorphism. Interestingly, four natural polymorphisms causing amino acid changes in the gene TraesCS2B01G513100 that encodes a serine/threonine protein kinase (STPK) were significantly involved in YR responses. Gene expression and mutation analysis confirmed that STPK played an important role in YR resistance. PCR markers were developed to identify the favourable TraesCS2B01G513100 haplotype for marker-assisted breeding. These results demonstrate that high-resolution SNP-based GWAS enables the rapid identification of putative resistance genes and can be used to improve the efficiency of marker-assisted selection in wheat disease resistance breeding.

Refined mapping of stripe rust resistance gene YrP10090 within a desirable haplotype for wheat improvement on chromosome 6A.

KEY MESSAGE: A large genomic region spanning over 300 Mb on chromosome 6A under intense artificial selection harbors multiple loci associated with favorable traits including stripe rust resistance in wheat. The development of resistance cultivars can be an optimal strategy for controlling wheat stripe rust disease. Although loci for stripe rust resistance have been identified on chromosome 6A in previous studies, it is unclear whether these loci span a common genetic interval, and few studies have attempted to analyze the haplotype changes that have accompanied wheat improvement over the period of modern breeding. In this study, we used F2:3 families and F6:7 recombinant inbred lines (RILs) derived from a cross between a resistant CIMMYT wheat accession P10090 and the susceptible landrace Mingxian 169 to improve the resolution of the QTL on chromosome 6A. The co-located QTL, designated as YrP10090, was flanked by SNP markers AX-94460938 and AX-110585473 with a genetic interval of 3.5 cM, however, corresponding to a large physical distance of over 300 Mb in RefSeq v.1.0 (positions 107.1-446.5 Mb). More than 1,300 SNP markers in this genetic region were extracted for haplotype analysis in a panel of 1,461 worldwide common wheat accessions, and three major haplotypes (Hap1, Hap2, and Hap3) were identified. The favorable haplotype Hap1 associated with stripe rust resistance exhibited a large degree of linkage disequilibrium. Selective sweep analyses were performed between different haplotype groups, revealing specific genomic regions with strong artificial selection signals. These regions harbored multiple desirable traits associated with resilience to environmental stress, different yield components, and quality characteristics. P10090 and its derivatives that carry the desirable haplotype can provide a concrete foundation for bread wheat improvement including the genomic selection.