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

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 to 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 phenotypic variance explained (PVE) markers (allele-specific quantitative PCR [AQP]) 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 (MAS) of FHB resistance and provide a starting point for fine mapping and marker-based cloning of the resistance genes.

Using UAV-Based Temporal Spectral Indices to Dissect Changes in the Stay-Green Trait in Wheat

Stay-green (SG) in wheat is a beneficial trait that increases yield and stress tolerance. However, conventional phenotyping techniques limited the understanding of its genetic basis. Spectral indices (SIs) as non-destructive tools to evaluate crop temporal senescence provide an alternative strategy. Here, we applied SIs to monitor the senescence dynamics of 565 diverse wheat accessions from anthesis to maturation stages over 2 field seasons. Four SIs (normalized difference vegetation index, green normalized difference vegetation index, normalized difference red edge index, and optimized soil-adjusted vegetation index) were normalized to develop relative stay-green scores (RSGS) as the SG indicators. An RSGS-based genome-wide association study identified 47 high-confidence quantitative trait loci (QTL) harboring 3,079 single-nucleotide polymorphisms associated with SG and 1,085 corresponding candidate genes. Among them, 15 QTL overlapped or were adjacent to known SG-related QTL/genes, while the remaining QTL were novel. Notably, a set of favorable haplotypes of SG-related candidate genes such as TraesCS2A03G1081100, TracesCS6B03G0356400, and TracesCS2B03G1299500 are increasing following the Green Revolution, further validating the feasibility of the pipeline. This study provided a valuable reference for further quantitative SG and genetic research in diverse wheat panels.

Favorable Loci Identified for Stripe Rust Resistance in Chinese Winter Wheat Accessions via Genome-Wide Association Study

Stripe rust (or yellow rust), caused by Puccinia striiformis f. sp. tritici (Pst), is one of the most devastating diseases of wheat worldwide. Currently, the utilization of resistant cultivars is the most viable way to reduce yield losses. In this study, a panel of 188 wheat accessions from China was evaluated for stripe rust resistance, and genome-wide association studies were performed using high-quality Diversity Arrays Technology markers. According to the phenotype and genotype data, a total of 26 significant marker-trait associations were identified, representing 18 quantitative trait loci (QTLs) on chromosomes 1B, 2A, 2B, 3A, 3B, 5A, 5B, 6B, 7B, and 7D. Of the 18 QTLs, almost all were associated with adult plant resistance (APR) except QYr.nwsuaf-6B.2, which was associated with all-stage resistance (also known as seedling resistance). Three of the 18 QTLs were mapped far from previously identified Pst resistance genes and QTLs and were considered potentially new loci. The other 15 QTLs were mapped close to known resistance genes and QTLs. Subsequent haplotype analysis for QYr.nwsuaf-2A and QYr.nwsuaf-7B.3 revealed the degrees of resistance of the panel in the APR stage. In summary, the favorable alleles identified in this study may be useful in breeding for disease resistance to stripe rust.

Genome-wide association analysis of tan spot disease resistance in durum wheat accessions from Tunisia

Background: Tunisia harbors a rich collection of unexploited durum wheat landraces (Triticum durum ssp. durum) that have been gradually replaced by elite cultivars since the 1970s. These landraces represent an important potential source for broadening the genetic background of elite durum wheat cultivars and for the introgression of novel genes for key traits, including disease resistance, into these cultivars. Methods: In this study, single nucleotide polymorphism (SNP) markers were used to investigate the genetic diversity and population structure of a core collection of 235 durum wheat accessions consisting mainly of landraces. The high phenotypic and genetic diversity of the fungal pathogen Pyrenophora tritici-repentis (cause of tan spot disease of wheat) in Tunisia allowed the assessment of the accessions for tan spot resistance at the adult plant stage under field conditions over three cropping seasons. A genome-wide association study (GWAS) was performed using a 90k SNP array. Results: Bayesian population structure analysis with 9191 polymorphic SNP markers classified the accessions into two groups, where groups 1 and 2 included 49.79% and 31.49% of the accessions, respectively, while the remaining 18.72% were admixtures. Principal coordinate analysis, the unweighted pair group method with arithmetic mean and the neighbor-joining method clustered the accessions into three to five groups. Analysis of molecular variance indicated that 76% of the genetic variation was among individuals and 23% was between individuals. Genome-wide association analyses identified 26 SNPs associated with tan spot resistance and explained between 8.1% to 20.2% of the phenotypic variation. The SNPs were located on chromosomes 1B (1 SNP), 2B (4 SNPs), 3A (2 SNPs), 3B (2 SNPs), 4A (2 SNPs), 4B (1 SNP), 5A (2 SNPs), 5B (4 SNPs), 6A (5 SNPs), 6B (2 SNPs), and 7B (1 SNP). Four markers, one on each of chromosomes 1B, and 5A, and two on 5B, coincided with previously reported SNPs for tan spot resistance, while the remaining SNPs were either novel markers or closely related to previously reported SNPs. Eight durum wheat accessions were identified as possible novel sources of tan spot resistance that could be introgressed into elite cultivars. Conclusion: The results highlighted the significance of chromosomes 2B, 5B, and 6A as genomic regions associated with tan spot resistance.

Genome-Wide Association Study of Asian and European Common Wheat Accessions for Yield-Related Traits and Stripe Rust Resistance

Identifying novel loci of yield-related traits and resistance to stripe rust (caused by Puccinia striiformis f. sp. tritici) in wheat will help in breeding wheat that can meet projected demands in diverse environmental and agricultural practices. We performed a genome-wide association study with 24,767 single nucleotide polymorphisms (SNPs) in 180 wheat accessions that originated in 16 Asian or European countries between latitudes 30°N and 45°N. We detected seven accessions with desirable yield-related traits and 42 accessions that showed stable, high degrees of stripe rust resistance in multienvironment field assessments. A marker-trait association analysis of yield-related traits detected 18 quantitative trait loci (QTLs) in at least two test environments and two QTLs related to stripe rust resistance in at least three test environments. Five of these QTLs were identified as potentially novel QTLs by comparing their physical locations with those of known QTLs in the Chinese Spring (CS) reference genome RefSeq v1.1 published by the International Wheat Genome Sequencing Consortium; two were for spike length, one was for grain number per spike, one was for spike number, and one was for stripe rust resistance at the adult plant stage. We also identified 14 candidate genes associated with the five novel QTLs. These QTLs and candidate genes will provide breeders with new germplasm and can be used to conduct marker-assisted selection in breeding wheat with improved yield and stripe rust resistance.

Meta-analysis of the quantitative trait loci associated with agronomic traits, fertility restoration, disease resistance, and seed quality traits in pigeonpea (Cajanus cajan L.)

A meta-analysis of quantitative trait loci (QTLs), associated with agronomic traits, fertility restoration, disease resistance, and seed quality traits was conducted for the first time in pigeonpea (Cajanus cajan L.). Data on 498 QTLs was collected from 9 linkage mapping studies (involving 21 biparental populations). Of these 498, 203 QTLs were projected onto "PigeonPea_ConsensusMap_2022," saturated with 10,522 markers, which resulted in the prediction of 34 meta-QTLs (MQTLs). The average confidence interval (CI) of these MQTLs (2.54 cM) was 3.37 times lower than the CI of the initial QTLs (8.56 cM). Of the 34 MQTLs, 12 high-confidence MQTLs with CI (≤5 cM) and a greater number of initial QTLs (≥5) were utilized to extract 2255 gene models, of which 105 were believed to be associated with different traits under study. Furthermore, eight of these MQTLs were observed to overlap with several marker-trait associations or significant SNPs identified in previous genome-wide association studies. Furthermore, synteny and ortho-MQTL analyses among pigeonpea and four related legumes crops, such as chickpea, pea, cowpea, and French bean, led to the identification of 117 orthologous genes from 20 MQTL regions. Markers associated with MQTLs can be employed for MQTL-assisted breeding as well as to improve the prediction accuracy of genomic selection in pigeonpea. Additionally, MQTLs may be subjected to fine mapping, and some of the promising candidate genes may serve as potential targets for positional cloning and functional analysis to elucidate the molecular mechanisms underlying the target traits.

Genetic analysis of stripe rust resistance in the common wheat line Kfa/2*Kachu under a Chinese rust environment

KEY MESSAGE

We mapped a new race-specific seedling stripe rust resistance gene on wheat chromosome 5BL and a new APR locus QYr.hazu-2BS from CIMMYT wheat line Kfa/2*Kachu. Breeding resistant wheat (Triticum aestivum) varieties is the most economical and efficient way to manage wheat stripe rust, but requires the prior identification of new resistance genes and development of associated molecular markers for marker-assisted selection. To map stripe rust resistance loci in wheat, we used a recombinant inbred line population generated by crossing the stripe rust-resistant parent 'Kfa/2*Kachu' and the susceptible parent 'Apav#1'. We employed genotyping-by-sequencing and bulked segregant RNA sequencing to map a new race-specific seedling stripe rust resistance gene, which we designated YrK, to wheat chromosome arm 5BL. TraesCS5B02G330700 encodes a receptor-like kinase and is a high-confidence candidate gene for YrK based on virus-induced gene silencing results and the significant induction of its expression 24 h after inoculation with wheat stripe rust. To assist breeding, we developed functional molecular markers based on the polymorphic single nucleotide polymorphisms in the coding sequence region of YrK. We also mapped four adult plant resistance (APR) loci to wheat chromosome arms 1BL, 2AS, 2BS and 4AL. Among these APR loci, we determined that QYr.hazu-1BL and QYr.hazu-2AS are allelic to the known pleiotropic resistance gene Lr46/Yr29/Pm39 and the race-specific gene Yr17, respectively. However, QYr.hazu-2BS is likely a new APR locus, for which we converted closely linked SNP polymorphisms into breeder-friendly Kompetitive allele-specific PCR (KASP) markers. In the present study, we provided new stripe rust resistance locus/gene and molecular markers for wheat breeder to develop rust-resistant wheat variety.

Genome wide association and haplotype analyses for the crease depth trait in bread wheat (Triticum aestivum L.)

Wheat grain has a complex structure that includes a crease on one side, and tissues within the crease region play an important role in nutrient transportation during wheat grain development. However, the genetic architecture of the crease region is still unclear. In this study, 413 global wheat accessions were resequenced and a method was developed for evaluating the phenotypic data of crease depth (CD). The CD values exhibited continuous and considerable large variation in the population, and the broad-sense heritability was 84.09%. CD was found to be positively correlated with grain-related traits and negatively with quality-related traits. Analysis of differentiation of traits between landraces and cultivars revealed that grain-related traits and CD were simultaneously improved during breeding improvement. Moreover, 2,150.8-Mb genetic segments were identified to fall within the selective sweeps between the landraces and cultivars; they contained some known functional genes for quality- and grain-related traits. Genome-wide association study (GWAS) was performed using around 10 million SNPs generated by genome resequencing and 551 significant SNPs and 18 QTLs were detected significantly associated with CD. Combined with cluster analysis of gene expression, haplotype analysis, and annotated information of candidate genes, two promising genes TraesCS3D02G197700 and TraesCS5A02G292900 were identified to potentially regulate CD. To the best of our knowledge, this is the first study to provide the genetic basis of CD, and the genetic loci identified in this study may ultimately assist in wheat breeding programs.

A major yellow rust resistance QTL on chromosome 6A shows increased frequency in recent Norwegian spring wheat cultivars and breeding lines

KEY MESSAGE

A major yellow rust resistance QTL, QYr.nmbu.6A, contributed consistent adult plant resistance in field trials across Europe, China, Kenya and Mexico. Puccinia striiformis f. sp. tritici, causing wheat yellow rust (YR), is one of the most devastating biotrophic pathogens affecting global wheat yields. Owing to the recent epidemic of the PstS10 race group in Europe, yellow rust has become a reoccurring disease in Norway since 2014. As all stage resistances (ASR) (or seedling resistances) are usually easily overcome by pathogen evolution, deployment of durable adult plant resistance (APR) is crucial for yellow rust resistance breeding. In this study, we assessed a Nordic spring wheat association mapping panel (n = 301) for yellow rust field resistance in seventeen field trials from 2015 to 2021, including nine locations in six countries across four different continents. Nine consistent QTL were identified across continents by genome-wide association studies (GWAS). One robust QTL on the long arm of chromosome 6A, QYr.nmbu.6A, was consistently detected in nine out of the seventeen trials. Haplotype analysis of QYr.nmbu.6A confirmed significant QTL effects in all tested environments and the effect was also validated using an independent panel of new Norwegian breeding lines. Increased frequency of the resistant haplotype was found in new varieties and breeding lines in comparison to older varieties and landraces, implying that the resistance might have been selected for due to the recent changes in the yellow rust pathogen population in Europe.

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.

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.

The selection and application of peduncle length QTL QPL_6D.1 in modern wheat (Triticum aestivum L.) breeding

QPL_6D.1b displayed an additive effect with Rht-B1b and Rht-D1b in reducing wheat plant height and peduncle length, which confers shorter peduncle length and more kernels per spike, and had been broadly selected by Chinese modern wheat cultivars. Peduncle length (PL), as the key component of wheat plant height (PH), plays critical role in determining wheat lodging resistance and wheat pathogen resistance; then, its breeding selection and genetic basis remain largely unclear. Here the PH and PL were investigated in 406 wheat accessions in eight environments. In this study, a PL preferentially QTL QPL_6D.1 was identified in six environments by GWAS, which explained 13.6-24.2% of wheat PL variations in natural population. The allele QPL_6D.1b displayed a significantly additive effect with Rht-B1b and Rht-D1b in controlling PH and PL and could freely combined with Rht-B1b and Rht-D1b in current wheat cultivars. Haplotypic analysis demonstrates the QPL_6D.1b has been selected by Chinese modern wheat cultivar and confers shorter PL and more kernels per spike, highlighting its potentials in wheat breeding.

Genome-wide association study for grain zinc concentration in bread wheat (Triticum aestivum L.)

Introduction

Zinc (Zn) deficiency causes serious diseases in people who rely on cereals as their main food source. However, the grain zinc concentration (GZnC) in wheat is low. Biofortification is a sustainable strategy for reducing human Zn deficiency.

Methods

In this study, we constructed a population of 382 wheat accessions and determined their GZnC in three field environments. Phenotype data was used for a genome-wide association study (GWAS) using a 660K single nucleotide polymorphism (SNP) array, and haplotype analysis identified an important candidate gene for GZnC.

Results

We found that GZnC of the wheat accessions showed an increasing trend with their released years, indicating that the dominant allele of GZnC was not lost during the breeding process. Nine stable quantitative trait loci (QTLs) for GZnC were identified on chromosomes 3A, 4A, 5B, 6D, and 7A. And an important candidate gene for GZnC, namely, TraesCS6D01G234600, and GZnC between the haplotypes of this gene showed, significant difference (P ≤ 0.05) in three environments.

Discussion

A novel QTL was first identified on chromosome 6D, this finding enriches our understanding of the genetic basis of GZnC in wheat. This study provides new insights into valuable markers and candidate genes for wheat biofortification to improve GZnC.

Genome-wide association studies of peduncle length in wheat under rain-fed and irrigating field conditions

Drought is one of the most destructive environmental factors limiting wheat production and food security globally. Peduncle length (PLE) is an important morphological trait to determine plant architecture, photosynthate transport, and yield formation, which is also considered a useful index for drought tolerance in wheat. However, the genetic basis of wheat PLE is not well studied at present. Here, a large-scale genome-wide association study (GWAS) of PLE was performed using a panel of 282 wheat accessions with the Wheat 660K SNP array genotyping under rain-fed and irrigating field conditions. Totally, 1,301 significant marker-trait associations (MTAs) were identified using the threshold of p-value < 4.16 × 10^-4, five of which were high-confidence. Furthermore, combining GWAS intervals, previously reported QTLs, expression levels, homologous genes, and selected sweep analysis, a total of 5 candidate genes were detected to associate with drought stress. Moreover, the expression levels of TraesCS2A02G082100 were significantly up-regulated under drought conditions and co-localized in the selected sweep region, suggesting it is a drought-responsive gene. Our results shed light on the genetic basis underlying wheat drought tolerance, which accelerates the marker-assistant selection and genetic improvement through genomic breeding in wheat.

Fine Mapping of Stripe-Rust-Resistance Gene YrJ22 in Common Wheat by BSR-Seq and MutMap-Based Sequencing

Identification and accurate mapping of new resistance genes are essential for gene pyramiding in wheat breeding. The YrJ22 gene is a dominant stripe-rust-resistance gene located at the distal end of chromosome 2AL, which was identified in a leading Chinese-wheat variety, Jimai 22, showing high resistance to CYR32, a prevalent race of Puccinia striiformis tritici (Pst) in China. In the current study, 15 F₁ and 2273 F₂ plants derived from the cross of Jimai 22/Avocet S were used for the fine-mapping of YrJ22. The RNA-Seq of resistant and susceptible bulks of F₂ plants (designated BSR-Seq) identified 10 single-nucleotide polymorphisms (SNP) in a 12.09 Mb physical interval on chromosome 2AL. A total of 1022 EMS-induced M₃ lines of Jimai 22 were screened, to identify susceptible mutants for MutMap analysis. Four CAPS markers were developed from SNPs identified using BSR-Seq and MutMap. A linkage map for YrJ22 was constructed with 11 CAPS/STS and three SSR markers. YrJ22 was located at a 0.9 cM genetic interval flanked by markers H736 and H400, corresponding to a 340.46 kb physical region (768.7-769.0 Mb), including 13 high-confidence genes based on the Chinese Spring reference genome. TraesCS2A01G573200 is a potential candidate-gene, according to linkage and quantitative real-time PCR (qPCR) analyses. The CAPS marker H732 designed from an SNP in TraesCS2A01G573200 co-segregated with YrJ22. These results provide a useful stripe-rust-resistance gene and molecular markers for marker-assisted selection in wheat breeding and for further cloning of the gene.

A gain-of-function allele of a DREB transcription factor gene ameliorates drought tolerance in wheat

Drought is a major environmental factor limiting wheat production worldwide. However, the genetic components underlying wheat drought tolerance are largely unknown. Here, we identify a DREB transcription factor gene (TaDTG6-B) by genome-wide association study that is tightly associated with drought tolerance in wheat. Candidate gene association analysis revealed that a 26-bp deletion in the TaDTG6-B coding region induces a gain-of-function for TaDTG6-BDel574, which exhibits stronger transcriptional activation, protein interactions, and binding activity to dehydration-responsive elements (DRE)/CRT cis-elements than the TaDTG6-BIn574 encoded by the allele lacking the deletion, thus conferring greater drought tolerance in wheat seedlings harboring this variant. Knockdown of TaDTG6-BDel574 transcripts attenuated drought tolerance in transgenic wheat, whereas its overexpression resulted in enhanced drought tolerance without accompanying phenotypic abnormalities. Furthermore, the introgression of the TaDTG6-BDel574 elite allele into drought-sensitive cultivars improved their drought tolerance, thus providing a valuable genetic resource for wheat breeding. We also identified 268 putative target genes that are directly bound and transcriptionally regulated by TaDTG6-BDel574. Further analysis showed that TaDTG6-BDel574 positively regulates TaPIF1 transcription to enhance wheat drought tolerance. These results describe the genetic basis and accompanying mechanism driving phenotypic variation in wheat drought tolerance, and provide a novel genetic resource for crop breeding programs.

Genome-wide meta-analysis of QTL for morphological related traits of flag leaf in bread wheat

Flag leaf is an important organ for photosynthesis of wheat plants, and a key factor affecting wheat yield. In this study, quantitative trait loci (QTL) for flag leaf morphological traits in wheat reported since 2010 were collected to investigate the genetic mechanism of these traits. Integration of 304 QTLs from various mapping populations into a high-density consensus map composed of various types of molecular markers as well as QTL meta-analysis discovered 55 meta-QTLs (MQTL) controlling morphological traits of flag leaves, of which 10 MQTLs were confirmed by GWAS. Four high-confidence MQTLs (MQTL-1, MQTL-11, MQTL-13, and MQTL-52) were screened out from 55 MQTLs, with an average confidence interval of 0.82 cM and a physical distance of 9.4 Mb, according to the definition of hcMQTL. Ten wheat orthologs from rice (7) and Arabidopsis (3) that regulated leaf angle, development and morphogenesis traits were identified in the hcMQTL region using comparative genomics, and were speculated to be potential candidate genes regulating flag leaf morphological traits in wheat. The results from this study provides valuable information for fine mapping and molecular markers assisted selection to improve morphological characters in wheat flag leaf.

Rational Nanomedicine Design Enhances Clinically Physical Treatment-Inspired or Combined Immunotherapy

Independent of tumor type and non-invasive or minimally-invasive feature, current physical treatments including ultrasound therapy, microwave ablation (MWA), and radiofrequency ablation (RFA) are widely used as the local treatment methods in clinics for directly killing tumors and activating systematic immune responses. However, the activated immune responses are inadequate and incompetent for tumor recession, and the incomplete thermal ablation even aggravates the immunosuppressive tumor microenvironment (ITM), resulting in the intractable tumor recurrence and metastasis. Intriguingly, nanomedicine provides a powerful platform as they can elevate energy utilization efficiency and augment oncolytic effects for mitigating ITM and potentiating the systematic immune responses. Especially after combining with clinical immunotherapy, the anti-tumor killing effect by activating or enhancing the human anti-tumor immune system is reached, enabling the effective prevention against tumor recurrence and metastasis. This review systematically introduces the cutting-edge progress and direction of nanobiotechnologies and their corresponding nanomaterials. Moreover, the enhanced physical treatment efficiency against tumor progression, relapse, and metastasis via activating or potentiating the autologous immunity or combining with exogenous immunotherapeutic agents is exemplified, and their rationales are analyzed. This review offers general guidance or directions to enhance clinical physical treatment from the perspectives of immunity activation or magnification.

Population transcriptomic analysis identifies the comprehensive lncRNAs landscape of spike in wheat (Triticum aestivum L.)

BACKGROUND

Long noncoding RNAs (lncRNAs) are emerging as the important regulators involving in growth and development as well as stress response in plants. However, current lncRNA studies were mainly performed at the individual level and the significance of it is not well understood in wheat.

RESULTS

In this study, the lncRNA landscape of wheat spike was characterized through analysing a total of 186 spike RNA-seq datasets from 93 wheat genotypes. A total of 35,913 lncRNAs as well as 1,619 lncRNA-mRNA pairs comprised of 443 lncRNAs and 464 mRNAs were obtained. Compared to coding genes, these lncRNAs displayed rather low conservation among wheat and other gramineous species. Based on re-sequencing data, the genetic variations of these lncRNA were investigated and obvious genetic bottleneck were found on them during wheat domestication process. Furthermore, 122 lncRNAs were found to act as ceRNA to regulate endogenous competition. Finally, association and co-localization analysis of the candidate lncRNA-mRNA pairs identified 170 lncRNAs and 167 target mRNAs significantly associated with spike-related traits, including lncRNA.127690.1/TraesCS2A02G518500.1 (PMEI) and lncRNA.104854.1/TraesCS6A02G050300.1 (ATG5) associated with heading date and spike length, respectively.

CONCLUSIONS

This study reported the lncRNA landscape of wheat spike through the population transcriptome analysis, which not only contribute to better understand the wheat evolution from the perspective of lncRNA, but also lay the foundation for revealing roles of lncRNA playing in spike development.

Genome-wide association study revealed TaHXK3-2A as a candidate gene controlling stomatal index in wheat seedlings

Stomata are important channels for the control of gas exchange between plants and the atmosphere. To examine the genetic architecture of wheat stomatal index, we performed a genome-wide association study (GWAS) using a panel of 539 wheat accessions and 450 678 polymorphic single nucleotide polymorphisms (SNPs) that were detected using wheat-specific 660K SNP array. A total of 130 SNPs were detected to be significantly associated with stomatal index in both leaf surfaces of wheat seedlings. These significant SNPs were distributed across 16 chromosomes and involved 2625 candidate genes which participate in stress response, metabolism and cell/organ development. Subsequent bulk segregant analysis (BSA), combined with GWAS identified one major haplotype on chromosome 2A, that is responsible for stomatal index on the abaxial leaf surface. Candidate gene association analysis revealed that genetic variation in the promoter region of the hexokinase gene TaHXK3-2A was significantly associated with the stomatal index. Moreover, transgenic analysis confirmed that TaHXK3-2A overexpression in wheat decreased the size of leaf pavement cells but increased stomatal density through the glucose metabolic pathway, resulting in drought sensitivity among TaHXK3-2A transgenic lines due to an increased transpiration rate. Taken together, these results provide valuable insights into the genetic control of the stomatal index in wheat seedlings.

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

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.

QTL Mapping of Adult Plant Resistance to Stripe Rust in a Doubled Haploid Wheat Population

Stripe rust caused by Puccinia striiformis Westend. f. sp. tritici. is a major bread wheat disease worldwide with yield losses of up to 100% under severe disease pressure. The deployment of resistant cultivars with adult plant resistance to the disease provides a long-term solution to stripe rust of wheat. An advanced line from the International Winter Wheat Improvement Program (IWWIP) 130675 (Avd/Vee#1//1-27-6275/Cf 1770/3/MV171-C-17466) showed a high level of adult plant resistance to stripe rust in the field. To identify the adult plant resistance genes in this elite line, a mapping population of 190 doubled haploid (DH) lines was developed from a cross between line 130675 and the universal stripe rust-susceptible variety Avocet S. The DH population was evaluated at precision wheat stripe rust phenotyping platform, in Izmir during 2019, 2020, and 2021 cropping seasons under artificial inoculations. Composite interval mapping (CIM) identified two stable QTLs QYr.rcrrc-3B.1, and QYr.rcrrc-3B.2, which were detected in multiple years. In addition to these two QTLs, five more QTLs, QYr.rcrrc-1B, QYr.rcrrc-2A, QYr.rcrrc-3A, QYr.rcrrc-5A, and QYr.rcrrc-7D, were identified, which were specific to the cropping year (environment). All QTLs were derived from the resistant parent, except QYr.rcrrc-3A. The significant QTLs explained 3.4-20.6% of the phenotypic variance. SNP markers flanking the QTL regions can be amenable to marker-assisted selection. The best DH lines with high yield, end-use quality, and stripe rust resistance can be used for further selection for improved germplasm. SNP markers flanking the QTL regions can aid in identifying such lines.

A genome-wide association study revealed the genetic variation and candidate genes for grain copper content in bread wheat (Triticum aestivum L.)

As an essential microelement, copper plays a crucial role in the human body. However, the grains of bread wheat, a major crop food, contain a low copper content. Here, a diversity panel of 443 wheat accessions cultivated in four environments was used to analyse grain copper content by ICAP-7000, and the genetic variation in grain copper content was examined using a 660 K single nucleotide polymorphism chip. Phenotypic analysis indicated that the grain copper content varied between 2.58 mg kg^-1 and 13.65 mg kg^-1. A genome-wide association study identified 12 QTLs associated with grain copper content that showed significance in at least two environments on chromosomes 1A, 1D, 3D, 4A, 5A, 5D, 6B, 6D, 7A and 7D. Through haplotype analysis, the phenotypic difference between the haplotypes of three genes, TraesCS5D01G282300, TraesCS6B01G052900 and TraesCS7D01G146600, showed significance (P ⩽ 0.05) in four environments. They were considered to be important candidate genes for grain copper content in wheat. In addition, we detected that the grain copper content gradually decreased with release years among wheat accessions in China, and the percentage of favourable alleles showed a similar trend. Analysing the changes in grain copper content with yield factors, we found that the dilute effect was mainly caused by thousand kernel weight. This study provides useful information on the genetic basis for grain copper content, and thus helps in improving the wheat grain quality.

Unravelling consensus genomic regions associated with quality traits in wheat using meta-analysis of quantitative trait loci

Meta-analysis in wheat for three major quality traits identified 110 meta-QTL (MQTL) with reduced confidence interval (CI). Five GWAS validated MQTL (viz., 1A.1, 1B.2, 3B.4, 5B.2, and 6B.2), each involving more than 20 initial QTL and reduced CI (95%) (< 2 cM), were selected for quality breeding programmes. Functional characterization including candidate gene mining and expression analysis discovered 44 high confidence candidate genes associated with quality traits. A meta-analysis of quantitative trait loci (QTL) associated with dough rheology properties, nutritional traits, and processing quality traits was conducted in wheat. For this purpose, as many as 2458 QTL were collected from 50 interval mapping studies published during 2013-2020. Of the total QTL, 1126 QTL were projected onto the consensus map saturated with 249,603 markers which led to the identification of 110 meta-QTL (MQTL). These MQTL exhibited an 18.84-fold reduction in the average CI compared to the average CI of the initial QTL (ranging from 14.87 to 95.55 cM with an average of 40.35 cM). Of the 110, 108 MQTL were physically anchored to the wheat reference genome, including 51 MQTL verified with marker-trait associations (MTAs) reported from earlier genome-wide association studies. Candidate gene (CG) mining allowed the identification of 2533 unique gene models from the MQTL regions. In-silico expression analysis discovered 439 differentially expressed gene models with > 2 transcripts per million expressions in grains and related tissues, which also included 44 high-confidence CGs involved in the various cellular and biochemical processes related to quality traits. Nine functionally characterized wheat genes associated with grain protein content, high-molecular-weight glutenin, and starch synthase enzymes were also found to be co-localized with some of the MQTL. Synteny analysis between wheat and rice MQTL regions identified 23 wheat MQTL syntenic to 16 rice MQTL associated with quality traits. Furthermore, 64 wheat orthologues of 30 known rice genes were detected in 44 MQTL regions. Markers flanking the MQTL identified in the present study can be used for marker-assisted breeding and as fixed effects in the genomic selection models for improving the prediction accuracy during quality breeding. Wheat orthologues of rice genes and other CGs available from MQTLs can be promising targets for further functional validation and to better understand the molecular mechanism underlying the quality traits in wheat.

Genome-Wide Association Study Reveals the Genetic Basis of Five Quality Traits in Chinese Wheat

Bread wheat is a highly adaptable food crop grown extensively around the world and its quality genetic improvement has received wide attention. In this study, the genetic loci associated with five quality traits including protein content (PC), gluten content (GC), baking value (BV), grain hardness (HA), and sedimentation value (SV) in a population of 253 Chinese wheat grown in Inner Mongolia were investigated through genome wide association mapping. A total of 103 QTL containing 556 SNPs were significantly related to the five quality traits based on the phenotypic data collected from three environments and BLUP data. Of these QTL, 32 QTL were continuously detected under at least two experiments. Some QTL such as qBV3D.2/qHA3D.2 on 3D, qPC5A.3/qGC5A on 5A, qBV5D/qHA5D on 5D, qBV6B.2/qHA6B.3 on 6B, and qBV6D/qHA6D.1 on 6D were associated with multiple traits. In addition, distribution of favorable alleles of the stable QTL in the association panel and their effects on five quality traits were validated. Analysis of existing transcriptome data revealed that 34 genes were specifically highly expressed in grains during reproductive growth stages. The functions of these genes will be characterized in future experiments. This study provides novel insights into the genetic basis of quality traits in wheat.

Genome-Wide Association and Genomic Prediction for Stripe Rust Resistance in Synthetic-Derived Wheats

Stripe rust caused by Puccnina striiformis (Pst) is an economically important disease attacking wheat all over the world. Identifying and deploying new genes for Pst resistance is an economical and long-term strategy for controlling Pst. A genome-wide association study (GWAS) using single nucleotide polymorphisms (SNPs) and functional haplotypes were used to identify loci associated with stripe rust resistance in synthetic-derived (SYN-DER) wheats in four environments. In total, 92 quantitative trait nucleotides (QTNs) distributed over 65 different loci were associated with resistance to Pst at seedling and adult plant stages. Nine additional loci were discovered by the linkage disequilibrium-based haplotype-GWAS approach. The durable rust-resistant gene Lr34/Yr18 provided resistance in all four environments, and against all the five Pst races used in this study. The analysis identified several SYN-DER accessions that carried major genes: either Yr24/Yr26 or Yr32. New loci were also identified on chr2B, chr5B, and chr7D, and 14 QTNs and three haplotypes identified on the D-genome possibly carry new alleles of the known genes contributed by the Ae. tauschii founders. We also evaluated eleven different models for genomic prediction of Pst resistance, and a prediction accuracy up to 0.85 was achieved for an adult plant resistance, however, genomic prediction for seedling resistance remained very low. A meta-analysis based on a large number of existing GWAS would enhance the identification of new genes and loci for stripe rust resistance in wheat. The genetic framework elucidated here for stripe rust resistance in SYN-DER identified the novel loci for resistance to Pst assembled in adapted genetic backgrounds.

Variation in cis-regulation of a NAC transcription factor contributes to drought tolerance in wheat

Drought is a major environmental factor limiting wheat production worldwide, and developing drought-tolerant cultivars is a central challenge for wheat breeders globally. Therefore, it is important to identify genetic components determining drought tolerance in wheat. In this study, we identified a wheat NAC gene (TaNAC071-A) that is tightly associated with drought tolerance by a genome-wide association study. Knockdown of TaNAC071-A in wheat attenuated plant drought tolerance, whereas its overexpression significantly enhanced drought tolerance through improved water-use efficiency and increased expression of stress-responsive genes. This heightened water-saving mechanism mitigated the yield loss caused by water deficit. Further candidate gene association analysis showed that a 108-bp insertion in the promoter of TaNAC071-A alters its expression level and contributes to variation in drought tolerance among wheat accessions. This insertion contains two MYB cis-regulatory elements (CREs) that can be directly bound by the MYB transcription activator, TaMYBL1, thereby leading to increased TaNAC071-A expression and plant drought tolerance. Importantly, introgression of this 108-bp insertion allele, TaNAC071-A^In-693, into drought-sensitive cultivars could improve their drought tolerance, demonstrating that it is a valuable genetic resource for wheat breeding. Taken together, our findings highlight a major breakthrough in determining the genetic basis underlying phenotypic variation in wheat drought tolerance and showcase the potential of exploiting CRE-containing indels for improving important agronomical traits.

Broadening the horizon of crop research: a decade of advancements in plant molecular genetics to divulge phenotype governing genes

Advancements in sequencing, genotyping, and computational technologies during the last decade (2011-2020) enabled new forward-genetic approaches, which subdue the impediments of precise gene mapping in varied crops. The modern crop improvement programs rely heavily on two major steps-trait-associated QTL/gene/marker's identification and molecular breeding. Thus, it is vital for basic and translational crop research to identify genomic regions that govern the phenotype of interest. Until the advent of next-generation sequencing, the forward-genetic techniques were laborious and time-consuming. Over the last 10 years, advancements in the area of genome assembly, genotyping, large-scale data analysis, and statistical algorithms have led faster identification of genomic variations regulating the complex agronomic traits and pathogen resistance. In this review, we describe the latest developments in genome sequencing and genotyping along with a comprehensive evaluation of the last 10-year headways in forward-genetic techniques that have shifted the focus of plant research from model plants to diverse crops. We have classified the available molecular genetic methods under bulk-segregant analysis-based (QTL-seq, GradedPool-Seq, QTG-Seq, Exome QTL-seq, and RapMap), target sequence enrichment-based (RenSeq, AgRenSeq, and TACCA), and mutation-based groups (MutMap, NIKS algorithm, MutRenSeq, MutChromSeq), alongside improvements in classical mapping and genome-wide association analyses. Newer methods for outcrossing, heterozygous, and polyploid plant genetics have also been discussed. The use of k-mers has enriched the nature of genetic variants which can be utilized to identify the phenotype-causing genes, independent of reference genomes. We envisage that the recent methods discussed herein will expand the repertoire of useful alleles and help in developing high-yielding and climate-resilient crops.

Two decades of association mapping: Insights on disease resistance in major crops

Climate change across the globe has an impact on the occurrence, prevalence, and severity of plant diseases. About 30% of yield losses in major crops are due to plant diseases; emerging diseases are likely to worsen the sustainable production in the coming years. Plant diseases have led to increased hunger and mass migration of human populations in the past, thus a serious threat to global food security. Equipping the modern varieties/hybrids with enhanced genetic resistance is the most economic, sustainable and environmentally friendly solution. Plant geneticists have done tremendous work in identifying stable resistance in primary genepools and many times other than primary genepools to breed resistant varieties in different major crops. Over the last two decades, the availability of crop and pathogen genomes due to advances in next generation sequencing technologies improved our understanding of trait genetics using different approaches. Genome-wide association studies have been effectively used to identify candidate genes and map loci associated with different diseases in crop plants. In this review, we highlight successful examples for the discovery of resistance genes to many important diseases. In addition, major developments in association studies, statistical models and bioinformatic tools that improve the power, resolution and the efficiency of identifying marker-trait associations. Overall this review provides comprehensive insights into the two decades of advances in GWAS studies and discusses the challenges and opportunities this research area provides for breeding resistant varieties.

Meta-QTLs and candidate genes for stripe rust resistance in wheat

In bread wheat, meta-QTL analysis was conducted using 353 QTLs that were available from earlier studies. When projected onto a dense consensus map comprising 76,753 markers, only 184 QTLs with the required information, could be utilized leading to identification of 61 MQTLs spread over 18 of the 21 chromosomes (barring 5D, 6D and 7D). The range for mean R2 (PVE %) was 1.9% to 48.1%, and that of CI was 0.02 to 11.47 cM; these CIs also carried 37 Yr genes. Using these MQTLs, 385 candidate genes (CGs) were also identified. Out of these CGs, 241 encoded known R proteins and 120 showed differential expression due to stripe rust infection at the seedling stage; the remaining 24 CGs were common in the sense that they encoded R proteins as well as showed differential expression. The proteins encoded by CGs carried the following widely known domains: NBS-LRR domain, WRKY domains, ankyrin repeat domains, sugar transport domains, etc. Thirteen breeders' MQTLs (PVE > 20%) including four pairs of closely linked MQTLs are recommended for use in wheat molecular breeding, for future studies to understand the molecular mechanism of stripe rust resistance and for gene cloning.

High-resolution genome-wide association study and genomic prediction for disease resistance and cold tolerance in wheat

High-resolution genome-wide association study (GWAS) facilitated QTL fine mapping and candidate gene identification, and the GWAS based genomic prediction models were highly predictive and valuable in wheat genomic breeding. Wheat is a major staple food crop and provides more than one-fifth of the daily calories and dietary proteins for humans. Genome-wide association study (GWAS) and genomic selection (GS) for wheat stress resistance and tolerance related traits are critical to understanding their genetic architecture for improvement of breeding selection efficiency. However, the insufficient marker density in previous studies limited the utility of GWAS and GS in wheat genomic breeding. Here, we conducted a high-resolution GWAS for wheat leaf rust (LR), yellow rust (YR), powdery mildew (PM), and cold tolerance (CT) by genotyping a panel of 768 wheat cultivars using genotyping-by-sequencing. Among 153 quantitative trait loci (QTLs) identified, 81 QTLs were delimited to ≤ 1.0 Mb intervals with three validated using bi-parental populations. Furthermore, 837 stress resistance-related genes were identified in the QTL regions with 12 showing induced expression by YR and PM pathogens. Genomic prediction using 2608, 4064, 3907, and 2136 pre-selected SNPs based on GWAS and genotypic correlations between the SNPs showed high prediction accuracies of 0.76, 0.73, and 0.78 for resistance to LR, YR, and PM, respectively, and 0.83 for resistance to cold damage. Our study laid a solid foundation for large-scale QTL fine mapping, candidate gene validation and GS in wheat.

Large-scale integration of meta-QTL and genome-wide association study discovers the genomic regions and candidate genes for yield and yield-related traits in bread wheat

Based on the large-scale integration of meta-QTL and Genome-Wide  Association Study, 76 high-confidence MQTL regions and 237 candidate genes that affected wheat yield and yield-related traits were discovered. Improving yield and yield-related traits are key goals in wheat breeding program. The integration of accumulated wheat genetic resources provides an opportunity to uncover important genomic regions and candidate genes that affect wheat yield. Here, a comprehensive meta-QTL analysis was conducted on 2230 QTL of yield-related traits obtained from 119 QTL studies. These QTL were refined into 145 meta-QTL (MQTL), and 89 MQTL were verified by GWAS with different natural populations. The average confidence interval (CI) of these MQTL was 2.92 times less than that of the initial QTL. Furthermore, 76 core MQTL regions with a physical distance less than 25 Mb were detected. Based on the homology analysis and expression patterns, 237 candidate genes in the MQTL involved in photoperiod response, grain development, multiple plant growth regulator pathways, carbon and nitrogen metabolism and spike and flower organ development were determined. A novel candidate gene TaKAO-4A was confirmed to be significantly associated with grain size, and a CAPS marker was developed based on its dominant haplotype. In summary, this study clarified a method based on the integration of meta-QTL, GWAS and homology comparison to reveal the genomic regions and candidate genes that affect important yield-related traits in wheat. This work will help to lay a foundation for the identification, transfer and aggregation of these important QTL or candidate genes in wheat high-yield breeding.

Identification and validation of a novel locus, Qpm-3BL, for adult plant resistance to powdery mildew in wheat using multilocus GWAS

BACKGROUND

Powdery mildew (PM), one of the major diseases in wheat, severely damages yield and quality, and the most economical and effective way to address this issue is to breed disease-resistant cultivars. Accordingly, 371 landraces and 266 released cultivars in Henan Province were genotyped by a 660 K microarray and phenotyped for adult plant resistance (APR) to PM from 2017 to 2020, and these datasets were used to conduct multilocus genome-wide association studies (GWASs).

RESULTS

Thirty-six varieties showed stable APR in all the environments, and eleven quantitative trait nucleotides (QTNs) were found by multiple methods across multiple environments and best linear unbiased prediction (BLUP) values to be significantly associated with APR. Among these stable QTNs, four were previously reported, three were newly discovered in this study, and the others need to be further investigated. The major and newly discovered QTN, Qpm-3BL, was located at chr03BL_AX-109,052,670, while another newly discovered QTN, Qpm-1BL, was located between chr01BL_AX-108,771,002 and chr01BL_AX-110,117,322. Five and eight landraces were identified to be resistant based on Qpm-1BL (haplotype TC) and Qpm-3BL (allele T), respectively. To validate Qpm-3BL, a new kompetitive allele-specific PCR (KASP) marker was developed to scan 155 F₂ individuals, and the average resistance score supported the value of Qpm-3BL in marker-assisted breeding. Near Qpm-3BL, PmBMYD was identified by KEGG, gene expression and comparative genomics analyses to be a candidate. Its resistance mechanism may involve gene tandem repeats.

CONCLUSIONS

This study reveals a previously unknown gene for PM resistance that is available for marker-assisted breeding.

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

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 F_2:3 families and F_6:7 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.

Utilization of a Wheat50K SNP Microarray-Derived High-Density Genetic Map for QTL Mapping of Plant Height and Grain Traits in Wheat

Plant height is significantly correlated with grain traits, which is a component of wheat yield. The purpose of this study is to investigate the main quantitative trait loci (QTLs) that control plant height and grain-related traits in multiple environments. In this study, we constructed a high-density genetic linkage map using the Wheat50K SNP Array to map QTLs for these traits in 198 recombinant inbred lines (RILs). The two ends of the chromosome were identified as recombination-rich areas in all chromosomes except chromosome 1B. Both the genetic map and the physical map showed a significant correlation, with a correlation coefficient between 0.63 and 0.99. However, there was almost no recombination between 1RS and 1BS. In terms of plant height, 1RS contributed to the reduction of plant height by 3.43 cm. In terms of grain length, 1RS contributed to the elongation of grain by 0.11 mm. A total of 43 QTLs were identified, including eight QTLs for plant height (PH), 11 QTLs for thousand grain weight (TGW), 15 QTLs for grain length (GL), and nine QTLs for grain width (GW), which explained 1.36–33.08% of the phenotypic variation. Seven were environment-stable QTLs, including two loci (Qph.nwafu-4B and Qph.nwafu-4D) that determined plant height. The explanation rates of phenotypic variation were 7.39–12.26% and 20.11–27.08%, respectively. One QTL, Qtgw.nwafu-4B, which influenced TGW, showed an explanation rate of 3.43–6.85% for phenotypic variation. Two co-segregating KASP markers were developed, and the physical locations corresponding to KASP_AX-109316968 and KASP_AX-109519968 were 25.888344 MB and 25.847691 MB, respectively. Qph.nwafu-4B, controlling plant height, and Qtgw.nwafu-4B, controlling TGW, had an obvious linkage relationship, with a distance of 7–8 cM. Breeding is based on molecular markers that control plant height and thousand-grain weight by selecting strains with low plant height and large grain weight. Another QTL, Qgw.nwafu-4D, which determined grain width, had an explanation rate of 3.43–6.85%. Three loci that affected grain length were Qgl.nwafu-5A, Qgl.nwafu-5D.2, and Qgl.nwafu-6B, illustrating the explanation rates of phenotypic variation as 6.72–9.59%, 5.62–7.75%, and 6.68–10.73%, respectively. Two QTL clusters were identified on chromosomes 4B and 4D.

Genomic Approaches to Identify Molecular Bases of Crop Resistance to Diseases and to Develop Future Breeding Strategies

Plant diseases are responsible for substantial crop losses each year and affect food security and agricultural sustainability. The improvement of crop resistance to pathogens through breeding represents an environmentally sound method for managing disease and minimizing these losses. The challenge is to breed varieties with a stable and broad-spectrum resistance. Different approaches, from markers to recent genomic and 'post-genomic era' technologies, will be reviewed in order to contribute to a better understanding of the complexity of host-pathogen interactions and genes, including those with small phenotypic effects and mechanisms that underlie resistance. An efficient combination of these approaches is herein proposed as the basis to develop a successful breeding strategy to obtain resistant crop varieties that yield higher in increasing disease scenarios.

Pre-harvest sprouting in cereals: genetic and biochemical mechanisms

With the growth of the global population and the increasing frequency of natural disasters, crop yields must be steadily increased to enhance human adaptability to risks. Pre-harvest sprouting (PHS), a term mainly used to describe the phenomenon in which grains germinate on the mother plant directly before harvest, is a serious global problem for agricultural production. After domestication, the dormancy level of cultivated crops was generally lower than that of their wild ancestors. Although the shortened dormancy period likely improved the industrial performance of cereals such as wheat, barley, rice, and maize, the excessive germination rate has caused frequent PHS in areas with higher rainfall, resulting in great economic losses. Here, we systematically review the causes of PHS and its consequences, the major indicators and methods for PHS assessment, and emphasize the biological significance of PHS in crop production. Wheat quantitative trait loci functioning in the control of PHS are also comprehensively summarized in a meta-analysis. Finally, we use Arabidopsis as a model plant to develop more complete PHS regulatory networks for wheat. The integration of this information is conducive to the development of custom-made cultivated lines suitable for different demands and regions, and is of great significance for improving crop yields and economic benefits.

Wheat Stripe Rust Grading by Deep Learning With Attention Mechanism and Images From Mobile Devices

Wheat stripe rust is one of the main wheat diseases worldwide, which has significantly adverse effects on wheat yield and quality, posing serious threats on food security. Disease severity grading plays a paramount role in stripe rust disease management including breeding disease-resistant wheat varieties. Manual inspection is time-consuming, labor-intensive and prone to human errors, therefore, there is a clearly urgent need to develop more effective and efficient disease grading strategy by using automated approaches. However, the differences between wheat leaves of different levels of stripe rust infection are usually tiny and subtle, and, as a result, ordinary deep learning networks fail to achieve satisfying performance. By formulating this challenge as a fine-grained image classification problem, this study proposes a novel deep learning network C-DenseNet which embeds Convolutional Block Attention Module (CBAM) in the densely connected convolutional network (DenseNet). The performance of C-DenseNet and its variants is demonstrated via a newly collected wheat stripe rust grading dataset (WSRgrading dataset) at Northwest A&F University, Shaanxi Province, China, which contains a total of 5,242 wheat leaf images with 6 levels of stripe rust infection. The dataset was collected by using various mobile devices in the natural field condition. Comparative experiments show that C-DenseNet with a test accuracy of 97.99% outperforms the classical DenseNet (92.53%) and ResNet (73.43%). GradCAM++ network visualization also shows that C-DenseNet is able to pay more attention to the key areas in making the decision. It is concluded that C-DenseNet with an attention mechanism is suitable for wheat stripe rust disease grading in field conditions.