Reconsidering the Lessons Learned from the 1970 Southern Corn Leaf Blight Epidemic.

The southern corn leaf blight epidemic of 1970 caused estimated losses of ~16% for the US corn crop, equivalent to ~$8 billion in current terms. The epidemic was caused by the prevalence of Texas male sterile cytoplasm (cms-T), used to produce most of the hybrid corn seed planted that year, combined with the emergence of a novel race of the fungus Cochliobolus heterostrophus that was exquisitely virulent on cms-T corn. Remarkably, the epidemic lasted just a single year. This episode has often been portrayed in the literature and textbooks over the last 50 years as a catastrophic mistake perpetrated by corn breeders and seed companies of the time who did not understand or account for the dangers of crop genetic uniformity. In this perspective article, we aim to present an alternative interpretation of these events. First, we contend that, rather than being caused by a grievous error on the part of the corn breeding and seed industry, this epidemic was a particularly unfortunate, unusual and unlucky consequence of a technological advancement intended to improve the efficiency of corn seed production for America's farmers. Second, we tell the story of the resolution of the epidemic as an example of timely, meticulous applied research in the public sector for the public good.

The quantification of southern corn leaf blight disease using deep UV fluorescence spectroscopy and autoencoder anomaly detection techniques.

Southern leaf blight (SLB) is a foliar disease caused by the fungus Cochliobolus heterostrophus infecting maize plants in humid, warm weather conditions. SLB causes production losses to corn producers in different regions of the world such as Latin America, Europe, India, and Africa. In this paper, we demonstrate a non-destructive method to quantify the signs of fungal infection in SLB-infected corn plants using a deep UV (DUV) fluorescence spectrometer, with a 248.6 nm excitation wavelength, to acquire the emission spectra of healthy and SLB-infected corn leaves. Fluorescence emission spectra of healthy and diseased leaves were used to train an Autoencoder (AE) anomaly detection algorithm-an unsupervised machine learning model-to quantify the phenotype associated with SLB-infected leaves. For all samples, the signature of corn leaves consisted of two prominent peaks around 450 nm and 325 nm. However, SLB-infected leaves showed a higher response at 325 nm compared to healthy leaves, which was correlated to the presence of C. heterostrophus based on disease severity ratings from Visual Scores (VS). Specifically, we observed a linear inverse relationship between the AE error and the VS (R2 = 0.94 and RMSE = 0.935). With improved hardware, this method may enable improved quantification of SLB infection versus visual scoring based on e.g., fungal spore concentration per unit area and spatial localization.

Mitigating Illumination-, Leaf-, and View-Angle Dependencies in Hyperspectral Imaging Using Polarimetry.

Automation of plant phenotyping using data from high-dimensional imaging sensors is on the forefront of agricultural research for its potential to improve seasonal yield by monitoring crop health and accelerating breeding programs. A common challenge when capturing images in the field relates to the spectral reflection of sunlight (glare) from crop leaves that, at certain solar incidences and sensor viewing angles, presents unwanted signals. The research presented here involves the convergence of 2 parallel projects to develop a facile algorithm that can use polarization data to decouple light reflected from the surface of the leaves and light scattered from the leaf's tissue. The first project is a mast-mounted hyperspectral imaging polarimeter (HIP) that can image a maize field across multiple diurnal cycles throughout a growing season. The second project is a multistatic fiber-based Mueller matrix bidirectional reflectance distribution function (mmBRDF) instrument which measures the polarized light-scattering behavior of individual maize leaves. The mmBRDF data was fitted to an existing model, which outputs parameters that were used to run simulations. The simulated data were then used to train a shallow neural network which works by comparing unpolarized 2-band vegetation index (VI) with linearly polarized data from the low-reflectivity bands of the VI. Using GNDVI and red-edge reflection ratio we saw an improvement of an order of magnitude or more in the mean error (ϵ) and a reduction spanning 1.5 to 2.7 in their standard deviation (ϵσ) after applying the correction network on the HIP sensor data.

Natural variation in the pattern-triggered immunity response in plants: Investigations, implications and applications.

The pattern-triggered immunity (PTI) response is triggered at the plant cell surface by the recognition of microbe-derived molecules known as microbe- or pathogen-associated molecular patterns or molecules derived from compromised host cells called damage-associated molecular patterns. Membrane-localized receptor proteins, known as pattern recognition receptors, are responsible for this recognition. Although much of the machinery of PTI is conserved, natural variation for the PTI response exists within and across species with respect to the components responsible for pattern recognition, activation of the response, and the strength of the response induced. This review describes what is known about this variation. We discuss how variation in the PTI response can be measured and how this knowledge might be utilized in the control of plant disease and in developing plant varieties with enhanced disease resistance.

The ZmWAKL-ZmWIK-ZmBLK1-ZmRBOH4 module provides quantitative resistance to gray leaf spot in maize.

Gray leaf spot (GLS), caused by the fungal pathogens Cercospora zeae-maydis and Cercospora zeina, is a major foliar disease of maize worldwide (Zea mays L.). Here we demonstrate that ZmWAKL encoding cell-wall-associated receptor kinase-like protein is the causative gene at the major quantitative disease resistance locus against GLS. The ZmWAKLY protein, encoded by the resistance allele, can self-associate and interact with a leucine-rich repeat immune-related kinase ZmWIK on the plasma membrane. The ZmWAKLY/ZmWIK receptor complex interacts with and phosphorylates the receptor-like cytoplasmic kinase (RLCK) ZmBLK1, which in turn phosphorylates its downstream NADPH oxidase ZmRBOH4. Upon pathogen infection, ZmWAKLY phosphorylation activity is transiently increased, initiating immune signaling from ZmWAKLY, ZmWIK, ZmBLK1 to ZmRBOH4, ultimately triggering a reactive oxygen species burst. Our study thus uncovers the role of the maize ZmWAKL-ZmWIK-ZmBLK1-ZmRBOH4 receptor/signaling/executor module in perceiving the pathogen invasion, transducing immune signals, activating defense responses and conferring increased resistance to GLS.

Identification of loci conferring resistance to 4 foliar diseases of maize.

Foliar diseases of maize are among the most important diseases of maize worldwide. This study focused on 4 major foliar diseases of maize: Goss's wilt, gray leaf spot, northern corn leaf blight, and southern corn leaf blight. QTL mapping for resistance to Goss's wilt was conducted in 4 disease resistance introgression line populations with Oh7B as the common recurrent parent and Ki3, NC262, NC304, and NC344 as recurrent donor parents. Mapping results for Goss's wilt resistance were combined with previous studies for gray leaf spot, northern corn leaf blight, and southern corn leaf blight resistance in the same 4 populations. We conducted (1) individual linkage mapping analysis to identify QTL specific to each disease and population; (2) Mahalanobis distance analysis to identify putative multiple disease resistance regions for each population; and 3) joint linkage mapping to identify QTL across the 4 populations for each disease. We identified 3 lines that were resistant to all 4 diseases. We mapped 13 Goss's wilt QTLs in the individual populations and an additional 6 using joint linkage mapping. All Goss's wilt QTL had small effects, confirming that resistance to Goss's wilt is highly quantitative. We report several potentially important chromosomal bins associated with multiple disease resistance including 1.02, 1.03, 3.04, 4.06, 4.08, and 9.03. Together, these findings indicate that disease QTL distribution is not random and that there are locations in the genome that confer resistance to multiple diseases. Furthermore, resistance to bacterial and fungal diseases is not entirely distinct, and we identified lines resistant to both fungi and bacteria, as well as loci that confer resistance to both bacterial and fungal diseases.

Qmatey: an automated pipeline for fast exact matching-based alignment and strain-level taxonomic binning and profiling of metagenomes.

Metagenomics is a powerful tool for understanding organismal interactions; however, classification, profiling and detection of interactions at the strain level remain challenging. We present an automated pipeline, quantitative metagenomic alignment and taxonomic exact matching (Qmatey), that performs a fast exact matching-based alignment and integration of taxonomic binning and profiling. It interrogates large databases without using metagenome-assembled genomes, curated pan-genes or k-mer spectra that limit resolution. Qmatey minimizes misclassification and maintains strain level resolution by using only diagnostic reads as shown in the analysis of amplicon, quantitative reduced representation and shotgun sequencing datasets. Using Qmatey to analyze shotgun data from a synthetic community with 35% of the 26 strains at low abundance (0.01-0.06%), we revealed a remarkable 85-96% strain recall and 92-100% species recall while maintaining 100% precision. Benchmarking revealed that the highly ranked Kraken2 and KrakenUniq tools identified 2-4 more taxa (92-100% recall) than Qmatey but produced 315-1752 false positive taxa and high penalty on precision (1-8%). The speed, accuracy and precision of the Qmatey pipeline positions it as a valuable tool for broad-spectrum profiling and for uncovering biologically relevant interactions.

Characterization of integration sites and transfer DNA structures in Agrobacterium-mediated transgenic events of maize inbred B104.

In maize, the community-standard transformant line B104 is a useful model for dissecting features of transfer DNA (T-DNA) integration due to its compatibility with Agrobacterium-mediated transformation and the availability of its genome sequence. Knowledge of transgene integration sites permits the analysis of the genomic environment that governs the strength of gene expression and phenotypic effects due to the disruption of an endogenous gene or regulatory element. In this study, we optimized a fusion primer and nested integrated PCR (FPNI-PCR) technique for T-DNA detection in maize to characterize the integration sites of 89 T-DNA insertions in 81 transformant lines. T-DNA insertions preferentially occurred in gene-rich regions and regions distant from centromeres. Integration junctions with and without microhomologous sequences as well as junctions with de novo sequences were detected. Sequence analysis of integration junctions indicated that T-DNA was incorporated via the error-prone repair pathways of nonhomologous (predominantly) and microhomology-mediated (minor) end-joining. This report provides a quantitative assessment of Agrobacterium-mediated T-DNA integration in maize with respect to insertion site features, the genomic distribution of T-DNA incorporation, and the mechanisms of integration. It also demonstrates the utility of the FPNI-PCR technique, which can be adapted to any species of interest.

Hybrid spatial-temporal Mueller matrix imaging spectropolarimeter for high throughput plant phenotyping.

Many correlations exist between spectral reflectance or transmission with various phenotypic responses from plants. Of interest to us are metabolic characteristics, namely, how the various polarimetric components of plants may correlate to underlying environmental, metabolic, and genotypic differences among different varieties within a given species, as conducted during large field experimental trials. In this paper, we overview a portable Mueller matrix imaging spectropolarimeter, optimized for field use, by combining a temporal and spatial modulation scheme. Key aspects of the design include minimizing the measurement time while maximizing the signal-to-noise ratio by mitigating systematic error. This was achieved while maintaining an imaging capability across multiple measurement wavelengths, spanning the blue to near-infrared spectral region (405-730 nm). To this end, we present our optimization procedure, simulations, and calibration methods. Validation results, which were taken in redundant and non-redundant measurement configurations, indicated that the polarimeter provides average absolute errors of (5.3±2.2)×10-3 and (7.1±3.1)×10-3, respectively. Finally, we provide preliminary field data (depolarization, retardance, and diattenuation) to establish baselines of barren and non-barren Zea maize hybrids (G90 variety), as captured from various leaf and canopy positions during our summer 2022 field experiments. Results indicate that subtle variations in retardance and diattenuation versus leaf canopy position may be present before they are clearly visible in the spectral transmission.

Exploring the Relationship Between Pattern-Triggered Immunity and Quantitative Resistance to Xanthomonas vasicola pv. vasculorum in Maize.

Bacterial leaf streak (BLS) of maize is an emerging foliar disease of maize in the Americas. It is caused by the gram-negative nonvascular bacterium Xanthomonas vasicola pv. vasculorum. There are no chemical controls available for BLS, and thus, host resistance is crucial for managing X. vasicola pv. vasculorum. The objective of this study was to examine the genetic determinants of resistance to X. vasicola pv. vasculorum in maize, as well as the relationship between other defense-related traits and BLS resistance. Specifically, we examined the correlations among BLS severity, severity for three fungal diseases, flg-22 response, hypersensitive response, and auricle color. We conducted quantitative trait locus (QTL) mapping for X. vasicola pv. vasculorum resistance using the maize recombinant inbred line population Z003 (B73 × CML228). We detected three QTLs for BLS resistance. In addition to the disease resistance QTL, we detected a single QTL for auricle color. We observed significant, yet weak, correlations among BLS severity, levels of pattern-triggered immunity response and leaf flecking. These results will be useful for understanding resistance to X. vasicola pv. vasculorum and mitigating the impact of BLS on maize yields.

A leucine-rich repeat receptor kinase gene confers quantitative susceptibility to maize southern leaf blight.

Southern leaf blight (SLB), caused by the necrotrophic fungal pathogen Cochliobolus heterostrophus (anamorph Bipolaris maydis), is a major foliar disease which causes significant yield losses in maize worldwide. A major quantitative trait locus, qSLB3.04 , conferring recessive resistance to SLB was previously mapped on maize chromosome 3. Using a combination of map-based cloning, association analysis, ethyl methanesulfonate and transposon mutagenesis, and CRISPR-Cas9 editing, we demonstrate that a leucine-rich repeat receptor-like kinase gene which we have called ChSK1 (Cochliobolus heterostrophus Susceptibility Kinase 1) at qSLB3.04 causes increased susceptibility to SLB. Genes of this type have generally been associated with the defense response. We present evidence that ChSK1 may be associated with suppression of the basal immune response. These findings contribute to our understanding of plant disease susceptibility genes and the potential to use them for engineering durable disease resistance.

Two pathogen loci determine Blumeria graminis f. sp. tritici virulence to wheat resistance gene Pm1a.

Blumeria graminis f. sp. tritici (Bgt) is a globally important fungal pathogen of wheat that can rapidly evolve to defeat wheat powdery mildew (Pm) resistance genes. Despite periodic regional deployment of the Pm1a resistance gene in US wheat production, Bgt strains that overcome Pm1a have been notably nonpersistent in the United States, while on other continents, they are more widely established. A genome-wide association study (GWAS) was conducted to map sequence variants associated with Pm1a virulence in 216 Bgt isolates from six countries, including the United States. A virulence variant apparently unique to Bgt isolates from the United States was detected in the previously mapped gene AvrPm1a (BgtE-5612) on Bgt chromosome 6; an in vitro growth assay suggested no fitness reduction associated with this variant. A gene on Bgt chromosome 8, Bgt-51526, was shown to function as a second determinant of Pm1a virulence, and despite < 30% amino acid identity, BGT-51526 and BGTE-5612 were predicted to share > 85% of their secondary structure. A co-expression study in Nicotiana benthamiana showed that BGTE-5612 and BGT-51526 each produce a PM1A-dependent hypersensitive response. More than one member of a B. graminis effector family can be recognized by a single wheat immune receptor, and a two-gene model is necessary to explain virulence to Pm1a.

Characterization of a Host-Specific Toxic Activity Produced by Bipolaris cookei, Causal Agent of Target Leaf Spot of Sorghum.

Target leaf spot (TLS) of sorghum, caused by the necrotrophic fungus Bipolaris cookei, can cause severe yield loss in many parts of the world. We grew B. cookei in liquid culture and observed that the resulting culture filtrate (CF) was differentially toxic when infiltrated into the leaves of a population of 288 diverse sorghum lines. In this population, we found a significant correlation between high CF sensitivity and susceptibility to TLS. This suggests that the toxin produced in culture may play a role in the pathogenicity of B. cookei in the field. We demonstrated that the toxic activity is light sensitive and, surprisingly, insensitive to pronase, suggesting that it is not proteinaceous. We identified the two sorghum genetic loci most associated with the response to CF in this population. Screening seedlings with B. cookei CF could be a useful approach for prescreening germplasm for TLS resistance.

Quantitative disease resistance: Multifaceted players in plant defense.

In contrast to large-effect qualitative disease resistance, quantitative disease resistance (QDR) exhibits partial and generally durable resistance and has been extensively utilized in crop breeding. The molecular mechanisms underlying QDR remain largely unknown but considerable progress has been made in this area in recent years. In this review, we summarize the genes that have been associated with plant QDR and their biological functions. Many QDR genes belong to the canonical resistance gene categories with predicted functions in pathogen perception, signal transduction, phytohormone homeostasis, metabolite transport and biosynthesis, and epigenetic regulation. However, other "atypical" QDR genes are predicted to be involved in processes that are not commonly associated with disease resistance, such as vesicle trafficking, molecular chaperones, and others. This diversity of function for QDR genes contrasts with qualitative resistance, which is often based on the actions of nucleotide-binding leucine-rich repeat (NLR) resistance proteins. An understanding of the diversity of QDR mechanisms and of which mechanisms are effective against which classes of pathogens will enable the more effective deployment of QDR to produce more durably resistant, resilient crops.

Genome-wide association study for morphological traits and resistance to Peryonella pinodes in the USDA pea single plant plus collection.

Peas (Pisum sativum) are the second most cultivated pulse crop in the world. They can serve as human food, fodder, and cover crop. The most serious foliar disease of pea cultivars worldwide is Ascochyta blight, which can be caused by several pathogens. Of these, Peyronella pinodes is the most aggressive and prevalent worldwide. Several traits, including resistance to Peyronella pinodes, stem diameter, internode length between nodes 2-3 and 5-6, and area of 7th leaf, were measured in 269 entries of the pea single plant plus collection. The heritability (H2) of the morphological traits was relatively high, while disease resistance had low heritability. Using 53,196 single-nucleotide polymorphism markers to perform a genome-wide association study to identify genomic loci associated with variation in all the traits measured, we identified 27 trait-locus associations, 5 of which were associated with more than 1 trait.

Multistatic fiber-based system for measuring the Mueller matrix bidirectional reflectance distribution function.

Bidirectionality effects can be a significant confounding factor when measuring hyperspectral reflectance data. The bidirectional reflectance distribution function (BRDF) can effectively characterize the reflectivity of surfaces to correct remote sensing measurements. However, measuring BRDFs can be time-consuming, especially when collecting Mueller matrix BRDF (mmBRDF) measurements of a surface via conventional goniometric techniques. In this paper, we present a system for collecting mmBRDF measurements using static optical fiber detectors that sample the hemisphere surrounding an object. The entrance to each fiber contains a polarization state analyzer configuration, allowing for the simultaneous acquisition of the Stokes vector intensity components at many altitudinal and azimuthal viewing positions. We describe the setup, calibration, and data processing used for this system and present its performance as applied to mmBRDF measurements of a ground glass diffuser.

Multi-Omics Analyses Reveal the Regulatory Network and the Function of ZmUGTs in Maize Defense Response.

Maize is one of the major crops in the world; however, diseases caused by various pathogens seriously affect its yield and quality. The maize Rp1-D21 mutant (mt) caused by the intragenic recombination between two nucleotide-binding, leucine-rich repeat (NLR) proteins, exhibits autoactive hypersensitive response (HR). In this study, we integrated transcriptomic and metabolomic analyses to identify differentially expressed genes (DEGs) and differentially accumulated metabolites (DAMs) in Rp1-D21 mt compared to the wild type (WT). Genes involved in pathogen-associated molecular pattern (PAMP)-triggered immunity (PTI) and effector-triggered immunity (ETI) were enriched among the DEGs. The salicylic acid (SA) pathway and the phenylpropanoid biosynthesis pathway were induced at both the transcriptional and metabolic levels. The DAMs identified included lipids, flavones, and phenolic acids, including 2,5-DHBA O-hexoside, the production of which is catalyzed by uridinediphosphate (UDP)-dependent glycosyltransferase (UGT). Four maize UGTs (ZmUGTs) homologous genes were among the DEGs. Functional analysis by transient co-expression in Nicotiana benthamiana showed that ZmUGT9250 and ZmUGT5174, but not ZmUGT9256 and ZmUGT8707, partially suppressed the HR triggered by Rp1-D21 or its N-terminal coiled-coil signaling domain (CCD21). None of the four ZmUGTs interacted physically with CCD21 in yeast two-hybrid or co-immunoprecipitation assays. We discuss the possibility that ZmUGTs might be involved in defense response by regulating SA homeostasis.