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Background Fe-deficiency chlorosis (FDC) of Asian pear plants is widespread, but little is known about the association between the microbial communities in the rhizosphere soil and leaf chlorosis. The leaf mineral concentration, leaf subcellular structure, soil physiochemical properties, and bacterial species community and distribution had been analysed to gain insights into the FDC in Asian pear plant. Results The total Fe in leaves with Fe-deficiency was positively correlated with total K, Mg, S, Cu, Zn, Mo and Cl contents, but no differences of available Fe (AFe) were detected between the rhizosphere soil of chlorotic and normal plants. Degraded ribosomes and degraded thylakloid stacks in chloroplast were observed in chlorotic leaves. The annotated microbiome indicated that there were 5 kingdoms, 52 phyla, 94 classes, 206 orders, 404 families, 1,161 genera, and 3,043 species in the rhizosphere soil of chlorotic plants; it was one phylum less and one order, 11 families, 59 genera, and 313 species more than in that of normal plant. Bacterial community and distribution patterns in the rhizosphere soil of chlorotic plants were distinct from those of normal plants and the relative abundance and microbiome diversity were more stable in the rhizosphere soils of normal than in chlorotic plants. Three ( Nitrospira defluvii , Gemmatirosa kalamazoonesis , and Sulfuricella denitrificans ) of the top five species ( N. defluvii , G. kalamazoonesis , S. denitrificans , Candidatus Nitrosoarchaeum koreensis , and Candidatus Koribacter versatilis ). were the identical and aerobic in both rhizosphere soils, but their relative abundance decreased by 48, 37, and 22%, respectively, and two of them ( G. aurantiaca and Ca. S. usitatus ) were substituted by an ammonia-oxidizing soil archaeon, Ca. N. koreensis and a nitrite and nitrate reduction related species, Ca. K. versatilis in that of chlorotic plants, which indicated the adverse soil aeration in the rhizosphere soil of chlorotic plants. A water-impermeable tables was found to reduce the soil aeration, inhibit root growth, and cause some absorption root death from infection by Fusarium solani . Conclusions It was waterlogging or/and poor drainage of the soil may inhibit Fe uptake not the amounts of AFe in the rhizosphere soil of chlorotic plants that caused FDC in this study.

For pathogens infecting single host species evolutionary trade-offs have previously been demonstrated between pathogen-induced mortality rates and transmission rates. It remains unclear, however, how such trade-offs impact sub-lethal pathogen-inflicted damage, and whether these trade-offs even occur in broad host-range pathogens. Here, we examine changes over the past 110 years in symptoms induced in maize by the broad host-range pathogen, maize streak virus (MSV). Specifically, we use the quantified symptom intensities of cloned MSV isolates in differentially resistant maize genotypes to phylogenetically infer ancestral symptom intensities and check for phylogenetic signal associated with these symptom intensities. We show that whereas symptoms reflecting harm to the host have remained constant or decreased, there has been an increase in how extensively MSV colonizes the cells upon which transmission vectors feed. This demonstrates an evolutionary trade-off between amounts of pathogen-inflicted harm and how effectively viruses position themselves within plants to enable onward transmission.

Background Iron (Fe) is an essential micronutrient for plant growth and development. Iron deficiency chlorosis (IDC), caused by calcareous soils or high soil pH, can limit iron availability, negatively affecting soybean ( Glycine max ) yield. This study leverages genome-wide association study (GWAS) and a genome-wide epistatic study (GWES) with previous gene expression studies to identify regions of the soybean genome important in iron deficiency tolerance. Results A GWAS and a GWES were performed using 460 diverse soybean PI lines from 27 countries, in field and hydroponic iron stress conditions, using more than 36,000 single nucleotide polymorphism (SNP) markers. Combining this approach with available RNA-sequencing data identified significant markers, genomic regions, and novel genes associated with or responding to iron deficiency. Sixty-nine genomic regions associated with IDC tolerance were identified across 19 chromosomes via the GWAS, including the major-effect quantitative trait locus (QTL) on chromosome Gm03. Cluster analysis of significant SNPs in this region deconstructed this historically prominent QTL into four distinct linkage blocks, enabling the identification of multiple candidate genes for iron chlorosis tolerance. The complementary GWES identified SNPs in this region interacting with nine other genomic regions, providing the first evidence of epistatic interactions impacting iron deficiency tolerance. Conclusions This study demonstrates that integrating cutting edge genome wide association (GWA), genome wide epistasis (GWE), and gene expression studies is a powerful strategy to identify novel iron tolerance QTL and candidate loci from diverse germplasm. Crops, unlike model species, have undergone selection for thousands of years, constraining and/or enhancing stress responses. Leveraging genomics-enabled approaches to study these adaptations is essential for future crop improvement.

• In Arabidopsis, the high-affinity K⁺ transporter HAK5 is the major pathway for root K⁺ uptake when below 100 μM; HAK5 responds to Low-K⁺ (LK) stress by strongly and rapidly increasing its expression during K⁺-deficiency. Therefore, positive regulators of HAK5 expression have the potential to improve K⁺ uptake under LK. • Here, we show that mutants of the transcription factor MYB77 share a LK-induced leaf chlorosis phenotype, lower K⁺ content, and lower Rb⁺ uptake of the hak5 mutant, but not the shorter root growth, and that overexpression of MYB77 enhanced K⁺ uptake and improved tolerance to LK stress. • Furthermore, we demonstrated that MYB77 positively regulates the expression of HAK5, by binding to the HAK5 promoter and enhances high-affinity K⁺ uptake of roots. • As such, our results reveal a novel pathway for enhancing HAK5 expression under LK stress, and provides a candidate for increasing the tolerance of plants to LK.

Background Iron deficiency chlorosis (IDC) is an abiotic stress in soybean [Glycine max (L.) Merr.] that causes significant yield reductions. Symptoms of IDC include interveinal chlorosis and stunting of the plant. While there are management practices that can overcome these drastic yield losses, the preferred way to manage IDC is growing tolerant soybean varieties. To develop varieties tolerant to IDC, breeders may easily phenotype up to thousands of candidate soybean lines every year for severity of symptoms related to IDC, a task traditionally done with a 1–5 visual rating scale. The visual rating scale is subjective and, because it is time consuming and laborious, can typically only be accomplished once or twice during a growing season. Results The goal of this study was to use an unmanned aircraft system (UAS) to improve field screening for tolerance to soybean IDC. During the summer of 2017, 3386 plots were visually scored for IDC stress on two different dates. In addition, images were captured with a DJI Inspire 1 platform equipped with a modified dual camera system which simultaneously captures digital red, green, blue images as well as red, green, near infrared (NIR) images. A pipeline was created for image capture, orthomosaic generation, processing, and analysis. Plant and soil classification was achieved using unsupervised classification resulting in 95% overall classification accuracy. Within the plant classified canopy, the green, yellow, and brown plant pixels were classified and used as features for random forest and neural network models. Overall, the random forest and neural network models achieved similar misclassification rates and classification accuracy, which ranged from 68 to 77% across rating dates. All 36 trials in the field were analyzed using a linear model for both visual score and UAS image-based scores on both dates. In 32 of the 36 tests on date 1 and 33 of 36 trials on date 2, the LSD associated with UAS image-based scores was lower than the LSD associated with visual scores, indicating the image-based scores provided more precise measurements of IDC severity. Conclusions Overall, the UAS was able to capture differences in IDC stress and may be used for evaluations of candidate breeding lines in a soybean breeding program. This system was both more efficient and precise than traditional scoring methods.

Summary Tomato chlorosis virus (ToCV) causes an important disease that primarily affects tomato, although it has been found infecting other economically important vegetable crops and a wide range of wild plants. First described in Florida (USA) and associated with a ‘yellow leaf disorder’ in the mid‐1990s, ToCV has been found in 35 countries and territories to date, constituting a paradigmatic example of an emergent plant pathogen. ToCV is transmitted semipersistently by whiteflies (Hemiptera: Aleyrodidae) belonging to the genera Bemisia and Trialeurodes. Whitefly transmission is highly efficient and cases of 100% infection are frequently observed in the field. To date, no resistant or tolerant tomato plants are commercially available and the control of the disease relies primarily on the control of the insect vector. Taxonomy Tomato chlorosis virus is one of the 14 accepted species in the genus Crinivirus, one of the four genera in the family Closteroviridae of plant viruses. Virion and genome properties The genome of ToCV is composed of two molecules of single‐stranded positive‐sense RNA, named RNA1 and RNA2, separately encapsidated in long, flexuous, rod‐like virions. As has been shown for other closterovirids, ToCV virions are believed to have a bipolar structure. RNA1 contains four open reading frames (ORFs) encoding proteins associated with virus replication and suppression of gene silencing, whereas RNA2 contains nine ORFs encoding proteins putatively involved in encapsidation, cell‐to‐cell movement, gene silencing suppression and whitefly transmission. Host range In addition to tomato, ToCV has been found to infect 84 dicot plant species belonging to 25 botanical families, including economically important crops. Transmission Like all species within the genus Crinivirus, ToCV is semipersistently transmitted by whiteflies, being one of only two criniviruses transmitted by members of the genera Bemisia and Trialeurodes. Disease symptoms Tomato ‘yellow leaf disorder’ syndrome includes interveinal yellowing and thickening of leaves. Symptoms first develop on lower leaves and then advance towards the upper part of the plant. Bronzing and necrosis of the older leaves are accompanied by a decline in vigour and reduction in fruit yield. In other hosts the most common symptoms include interveinal chlorosis and mild yellowing on older leaves. Control Control of the disease caused by ToCV is based on the use of healthy seedlings for transplanting, limiting accessibility of alternate host plants that can serve as virus reservoirs and the spraying of insecticides for vector control. Although several wild tomato species have been shown to contain genotypes resistant to ToCV, there are no commercially available resistant or tolerant tomato varieties to date.

Background Ratoon sugarcane is susceptible to chlorosis, characterized by chlorophyll loss, poor growth, and a multitude of nutritional deficiency mainly occurring at young stage. Chlorosis would significantly reduce the cane production. The molecular mechanism underlying this phenomenon remains unknown. We analyzed the transcriptome and metabolome of chlorotic and non-chlorotic sugarcane leaves of the same age from the same field to gain molecular insights into this phenomenon. Results The agronomic traits, such as plant height and the number of leaf, stalk node, and tillers declined in chlorotic sugarcane. Chlorotic leaves had substantially lower chlorophyll content than green leaves. A total of 11,776 differentially expressed genes (DEGs) were discovered in transcriptome analysis. In the KEGG enriched chlorophyll metabolism pathway, sixteen DEGs were found, eleven of which were down-regulated. Two photosynthesis pathways were also enriched with 32 genes downregulated and four genes up-regulated. Among the 81 enriched GO biological processes, there were four categories related to metal ion homeostasis and three related to metal ion transport. Approximately 400 metabolites were identified in metabolome analysis. The thirteen differentially expressed metabolites (DEMs) were all found down-regulated. The phenylpropanoid biosynthesis pathway was enriched in DEGs and DEMs, indicating a potentially vital role for phenylpropanoids in chlorosis. Conclusions Chlorophyll production, metal ion metabolism, photosynthesis, and some metabolites in the phenylpropanoid biosynthesis pathway were considerably altered in chlorotic ratoon sugarcane leaves. Our finding revealed the relation between chlorosis and these pathways, which will help expand our mechanistic understanding of ratoon sugarcane chlorosis.

In soybean variety development and genetic improvement projects, iron deficiency chlorosis (IDC) is visually assessed as an ordinal response variable. Linear Mixed Models for Genomic Prediction (GP) have been developed, compared, and used to select continuous plant traits such as yield, height, and maturity, but can be inappropriate for ordinal traits. Generalized Linear Mixed Models have been developed for GP of ordinal response variables. However, neither approach addresses the most important questions for cultivar development and genetic improvement: How frequently are the ‘wrong’ genotypes retained, and how often are the ‘correct’ genotypes discarded? The research objective reported herein was to compare outcomes from four data modeling and six algorithmic modeling GP methods applied to IDC using decision metrics appropriate for variety development and genetic improvement projects. Appropriate metrics for decision making consist of specificity, sensitivity, precision, decision accuracy, and area under the receiver operating characteristic curve. Data modeling methods for GP included ridge regression, logistic regression, penalized logistic regression, and Bayesian generalized linear regression. Algorithmic modeling methods include Random Forest, Gradient Boosting Machine, Support Vector Machine, K-Nearest Neighbors, Naïve Bayes, and Artificial Neural Network. We found that a Support Vector Machine model provided the most specific decisions of correctly discarding IDC susceptible genotypes, while a Random Forest model resulted in the best decisions of retaining IDC tolerant genotypes, as well as the best outcomes when considering all decision metrics. Overall, the predictions from algorithmic modeling result in better decisions than from data modeling methods applied to soybean IDC.

In China, Tomato chlorosis virus (ToCV) and Tomato yellow leaf curl virus (TYLCV) are widely present in tomato plants. The epidemiology of these viruses is intimately associated with their vector, the whitefly ( Bemisia tabaci MED). However, how a ToCV+TYLCV mixed infection affects viral acquisition by their vector remains unknown. In this study, we examined the growth parameters of tomato seedlings, including disease symptoms and the heights and weights of non-infected, singly infected and mixed infected tomato plants. Additionally, the spatio-temporal dynamics of the viruses in tomato plants, and the viral acquisition and transmission by B. tabaci MED, were determined. The results demonstrated that: (i) ToCV+TYLCV mixed infections induced tomato disease synergism, resulting in a high disease severity index and decreased stem heights and weights; (ii) as the disease progressed, TYLCV accumulated more in upper leaves of TYLCV-infected tomato plants than in lower leaves, whereas ToCV accumulated less in upper leaves of ToCV-infected tomato plants than in lower leaves; (iii) viral accumulation in ToCV+TYLCV mixed infected plants was greater than in singly infected plants; and (iv) B. tabaci MED appeared to have a greater TYLCV, but a lower ToCV, acquisition rate from mixed infected plants compared with singly infected plants. However, mixed infections did not affect transmission by whiteflies. Thus, ToCV+TYLCV mixed infections may induce synergistic disease effects in tomato plants.

‘Candidatus Liberibacter asiaticus’ (CLas) is the pathogenic bacterium that causes the disease Huanglongbing (HLB) in citrus and some model plants, such as Nicotiana benthamiana. After infection, CLas releases a set of effectors to modulate host responses. One of these critical effectors is Sec-delivered effector 1 (SDE1), which induces chlorosis and cell death in N. benthamiana. In this study, we revealed the DEAD-box RNA helicase (DDX3) interacts with SDE1. Gene silencing study revealed that knockdown of the NbDDX3 gene triggers leaf chlorosis, mimicking the primary symptom of CLas infection in N. benthamiana. The interactions between SDE1 and NbDDX3 were localized in the cell membrane. Overexpression of SDE1 resulted in suppression of NbDDX3 gene expression in N. benthamiana, which suggests a critical role of SDE1 in modulating NbDDX3 expression. Furthermore, we verified the interaction of SDE1 with citrus DDX3 (CsDDX3), and demonstrated that the expression of the CsDDX3 gene was significantly reduced in HLB-affected yellowing and mottled leaves of citrus. Thus, we provide molecular evidence that the downregulation of the host DDX3 gene is a crucial mechanism of leaf chlorosis in HLB-affected plants. The identification of CsDDX3 as a critical target of SDE1 and its association with HLB symptom development indicates that the DDX3 gene is an important target for gene editing, to interrupt the interaction between DDX3 and SDE1, and therefore interfere host susceptibility.