Effector Genes in Magnaporthe oryzae Triticum as Potential Targets for Incorporating Blast Resistance in Wheat.

Wheat blast (WB), caused by Magnaporthe oryzae Triticum pathotype, recently emerged as a destructive disease that threatens global wheat production. Because few sources of genetic resistance have been identified in wheat, genetic transformation of wheat with rice blast resistance genes could expand resistance to WB. We evaluated the presence/absence of homologs of rice blast effector genes in Triticum isolates with the aim of identifying avirulence genes in field populations whose cognate rice resistance genes could potentially confer resistance to WB. We also assessed presence of the wheat pathogen AVR-Rmg8 gene and identified new alleles. A total of 102 isolates collected in Brazil, Bolivia, and Paraguay from 1986 to 2018 were evaluated by PCR using 21 pairs of gene-specific primers. Effector gene composition was highly variable, with homologs to AvrPiz-t, AVR-Pi9, AVR-Pi54, and ACE1 showing the highest amplification frequencies (>94%). We identified Triticum isolates with a functional AvrPiz-t homolog that triggers Piz-t-mediated resistance in the rice pathosystem and produced transgenic wheat plants expressing the rice Piz-t gene. Seedlings and heads of the transgenic lines were challenged with isolate T25 carrying functional AvrPiz-t. Although slight decreases in the percentage of diseased spikelets and leaf area infected were observed in two transgenic lines, our results indicated that Piz-t did not confer useful WB resistance. Monitoring of avirulence genes in populations is fundamental to identifying effective resistance genes for incorporation into wheat by conventional breeding or transgenesis. Based on avirulence gene distributions, rice resistance genes Pi9 and Pi54 might be candidates for future studies.

In pursuit of a better world: crop improvement and the CGIAR.

The CGIAR crop improvement (CI) programs, unlike commercial CI programs, which are mainly geared to profit though meeting farmers' needs, are charged with meeting multiple objectives with target populations that include both farmers and the community at large. We compiled the opinions from >30 experts in the private and public sector on key strategies, methodologies, and activities that could the help CGIAR meet the challenges of providing farmers with improved varieties while simultaneously meeting the goals of: (i) nutrition, health, and food security; (ii) poverty reduction, livelihoods, and jobs; (iii) gender equality, youth, and inclusion; (iv) climate adaptation and mitigation; and (v) environmental health and biodiversity. We review the crop improvement processes starting with crop choice, moving through to breeding objectives, production of potential new varieties, selection, and finally adoption by farmers. The importance of multidisciplinary teams working towards common objectives is stressed as a key factor to success. The role of the distinct disciplines, actors, and their interactions throughout the process from crop choice through to adoption by farmers is discussed and illustrated.

VNTR Typing of the Bacterial Rice Pathogen Burkholderia glumae Reveals the Coexistence of Several Diverging Lineages in a Single Field in Colombia.

Burkholderia glumae is responsible for the panicle blight disease of rice. This disease is present worldwide and can result in significant drop in yields. To estimate the genetic diversity of the bacterial strains present in a rice paddy field in Colombia, we sampled 109 strains from infected panicles. To detect fine genetic relationships among related haplotypes, and to overcome a very low nucleotide diversity detected in previous studies, we designed primers to amplify and sequence several highly variable minisatellite loci, or variable number tandem repeats (VNTRs), as well as part of the Toxoflavin toxA gene in all strains. Results show that the toxA nucleotide diversity defined four lineages and was similar to that detected in several fields in Japan; data suggest that B. glumae has spread from Asia to America without major loss of genetic diversity, and that five VNTR loci discriminated the strains within the field revealing single and multi-infections of the rice panicles with a wide distribution of the haplotypes among the different plots. Even though disease levels vary considerably from year to year, the bacterial genetic diversity is maintained within a field. We do not detect any geographical structuring within the field, nor any effect of the rice cultivar on the observed diversity. The consequences on the origin and evolution of the bacteria are discussed.

Allelic variation for broad-spectrum resistance and susceptibility to bacterial pathogens identified in a rice MAGIC population.

Quantitative trait loci (QTL) that confer broad-spectrum resistance (BSR), or resistance that is effective against multiple and diverse plant pathogens, have been elusive targets of crop breeding programmes. Multiparent advanced generation intercross (MAGIC) populations, with their diverse genetic composition and high levels of recombination, are potential resources for the identification of QTL for BSR. In this study, a rice MAGIC population was used to map QTL conferring BSR to two major rice diseases, bacterial leaf streak (BLS) and bacterial blight (BB), caused by Xanthomonas oryzae pathovars (pv.) oryzicola (Xoc) and oryzae (Xoo), respectively. Controlling these diseases is particularly important in sub-Saharan Africa, where no sources of BSR are currently available in deployed varieties. The MAGIC founders and lines were genotyped by sequencing and phenotyped in the greenhouse and field by inoculation with multiple strains of Xoc and Xoo. A combination of genomewide association studies (GWAS) and interval mapping analyses revealed 11 BSR QTL, effective against both diseases, and three pathovar-specific QTL. The most promising BSR QTL (qXO-2-1, qXO-4-1 and qXO-11-2) conferred resistance to more than nine Xoc and Xoo strains. GWAS detected 369 significant SNP markers with distinguishable phenotypic effects, allowing the identification of alleles conferring disease resistance and susceptibility. The BSR and susceptibility QTL will improve our understanding of the mechanisms of both resistance and susceptibility in the long term and will be immediately useful resources for rice breeding programmes.

Advancing common bean (Phaseolus vulgaris L.) disease detection with YOLO driven deep learning to enhance agricultural AI.

Common beans (CB), a vital source for high protein content, plays a crucial role in ensuring both nutrition and economic stability in diverse communities, particularly in Africa and Latin America. However, CB cultivation poses a significant threat to diseases that can drastically reduce yield and quality. Detecting these diseases solely based on visual symptoms is challenging, due to the variability across different pathogens and similar symptoms caused by distinct pathogens, further complicating the detection process. Traditional methods relying solely on farmers' ability to detect diseases is inadequate, and while engaging expert pathologists and advanced laboratories is necessary, it can also be resource intensive. To address this challenge, we present a AI-driven system for rapid and cost-effective CB disease detection, leveraging state-of-the-art deep learning and object detection technologies. We utilized an extensive image dataset collected from disease hotspots in Africa and Colombia, focusing on five major diseases: Angular Leaf Spot (ALS), Common Bacterial Blight (CBB), Common Bean Mosaic Virus (CBMV), Bean Rust, and Anthracnose, covering both leaf and pod samples in real-field settings. However, pod images are only available for Angular Leaf Spot disease. The study employed data augmentation techniques and annotation at both whole and micro levels for comprehensive analysis. To train the model, we utilized three advanced YOLO architectures: YOLOv7, YOLOv8, and YOLO-NAS. Particularly for whole leaf annotations, the YOLO-NAS model achieves the highest mAP value of up to 97.9% and a recall of 98.8%, indicating superior detection accuracy. In contrast, for whole pod disease detection, YOLOv7 and YOLOv8 outperformed YOLO-NAS, with mAP values exceeding 95% and 93% recall. However, micro annotation consistently yields lower performance than whole annotation across all disease classes and plant parts, as examined by all YOLO models, highlighting an unexpected discrepancy in detection accuracy. Furthermore, we successfully deployed YOLO-NAS annotation models into an Android app, validating their effectiveness on unseen data from disease hotspots with high classification accuracy (90%). This accomplishment showcases the integration of deep learning into our production pipeline, a process known as DLOps. This innovative approach significantly reduces diagnosis time, enabling farmers to take prompt management interventions. The potential benefits extend beyond rapid diagnosis serving as an early warning system to enhance common bean productivity and quality.

Interspecific common bean population derived from Phaseolus acutifolius using a bridging genotype demonstrate useful adaptation to heat tolerance.

Common bean (Phaseolus vulgaris L.) is an important legume crop worldwide and is a major nutrient source in the tropics. Common bean reproductive development is strongly affected by heat stress, particularly overnight temperatures above 20°C. The desert Tepary bean (Phaseolus acutifolius A. Gray) offers a promising source of adaptative genes due to its natural acclimation to arid conditions. Hybridization between both species is challenging, requiring in vitro embryo rescue and multiple backcrossing cycles to restore fertility. This labor-intensive process constrains developing mapping populations necessary for studying heat tolerance. Here we show the development of an interspecific mapping population using a novel technique based on a bridging genotype derived from P. vulgaris, P. Acutifolius and P. parvifolius named VAP1 and is compatible with both common and tepary bean. The population was based on two wild P. acutifolius accessions, repeatedly crossed with Mesoamerican elite common bush bean breeding lines. The population was genotyped through genotyping-by-sequencing and evaluated for heat tolerance by genome-wide association studies. We found that the population harbored 59.8% introgressions from wild tepary, but also genetic regions from Phaseolus parvifolius, a relative represented in some early bridging crosses. We found 27 significative quantitative trait loci, nine located inside tepary introgressed segments exhibiting allelic effects that reduced seed weight, and increased the number of empty pods, seeds per pod, stem production and yield under high temperature conditions. Our results demonstrate that the bridging genotype VAP1 can intercross common bean with tepary bean and positively influence the physiology of derived interspecific lines, which displayed useful variance for heat tolerance.

Population genomic analysis reveals geographic structure and climatic diversification for Macrophomina phaseolina isolated from soybean and dry bean across the United States, Puerto Rico, and Colombia.

Macrophomina phaseolina causes charcoal rot, which can significantly reduce yield and seed quality of soybean and dry bean resulting from primarily environmental stressors. Although charcoal rot has been recognized as a warm climate-driven disease of increasing concern under global climate change, knowledge regarding population genetics and climatic variables contributing to the genetic diversity of M. phaseolina is limited. This study conducted genome sequencing for 95 M. phaseolina isolates from soybean and dry bean across the continental United States, Puerto Rico, and Colombia. Inference on the population structure using 76,981 single nucleotide polymorphisms (SNPs) revealed that the isolates exhibited a discrete genetic clustering at the continental level and a continuous genetic differentiation regionally. A majority of isolates from the United States (96%) grouped in a clade with a predominantly clonal genetic structure, while 88% of Puerto Rican and Colombian isolates from dry bean were assigned to a separate clade with higher genetic diversity. A redundancy analysis (RDA) was used to estimate the contributions of climate and spatial structure to genomic variation (11,421 unlinked SNPs). Climate significantly contributed to genomic variation at a continental level with temperature seasonality explaining the most variation while precipitation of warmest quarter explaining the most when spatial structure was accounted for. The loci significantly associated with multivariate climate were found closely to the genes related to fungal stress responses, including transmembrane transport, glycoside hydrolase activity and a heat-shock protein, which may mediate climatic adaptation for M. phaseolina. On the contrary, limited genome-wide differentiation among populations by hosts was observed. These findings highlight the importance of population genetics and identify candidate genes of M. phaseolina that can be used to elucidate the molecular mechanisms that underly climatic adaptation to the changing climate.

Genetic Analyses and Genomic Predictions of Root Rot Resistance in Common Bean Across Trials and Populations.

Root rot in common bean is a disease that causes serious damage to grain production, particularly in the upland areas of Eastern and Central Africa where significant losses occur in susceptible bean varieties. Pythium spp. and Fusarium spp. are among the soil pathogens causing the disease. In this study, a panel of 228 lines, named RR for root rot disease, was developed and evaluated in the greenhouse for Pythium myriotylum and in a root rot naturally infected field trial for plant vigor, number of plants germinated, and seed weight. The results showed positive and significant correlations between greenhouse and field evaluations, as well as high heritability (0.71-0.94) of evaluated traits. In GWAS analysis no consistent significant marker trait associations for root rot disease traits were observed, indicating the absence of major resistance genes. However, genomic prediction accuracy was found to be high for Pythium, plant vigor and related traits. In addition, good predictions of field phenotypes were obtained using the greenhouse derived data as a training population and vice versa. Genomic predictions were evaluated across and within further published data sets on root rots in other panels. Pythium and Fusarium evaluations carried out in Uganda on the Andean Diversity Panel showed good predictive ability for the root rot response in the RR panel. Genomic prediction is shown to be a promising method to estimate tolerance to Pythium, Fusarium and root rot related traits, indicating a quantitative resistance mechanism. Quantitative analyses could be applied to other disease-related traits to capture more genetic diversity with genetic models.

Understanding the complexity of disease-climate interactions for rice bacterial panicle blight under tropical conditions.

Bacterial panicle blight (BPB) caused by Burkholderia glumae is one of the main concerns for rice production in the Americas since bacterial infection can interfere with the grain-filling process and under severe conditions can result in high sterility. B. glumae has been detected in several rice-growing areas of Colombia and other countries of Central and Andean regions in Latin America, although evidence of its involvement in decreasing yield under these conditions is lacking. Analysis of different parameters in trials established in three rice-growing areas showed that, despite BPB presence, severity did not explain the sterility observed in fields. PCR tests for B. glumae confirmed low infection in all sites and genotypes, only 21.4% of the analyzed samples were positive for B. glumae. Climate parameters showed that Montería and Saldaña registered maximum temperature above 34°C, minimum temperature above 23°C, and Relative Humidity above 80%, conditions that favor the invasion model described for this pathogen in Asia. Our study found that in Colombia, minimum temperature above 23°C during 10 days after flowering is the condition that correlates with disease incidence. Therefore, this correlation, and the fact that Montería and Saldaña had a higher level of infected samples according to PCR tests, high minimum temperature, but not maximum temperature, seems to be determinant for B. glumae colonization under studied field conditions. This knowledge is a solid base line to design strategies for disease control, and is also a key element for breeders to develop strategies aimed to decrease the effect of B. glumae and high night-temperature on rice yield under tropical conditions.

Resistance to Multiple Temperate and Tropical Stem and Sheath Diseases of Rice.

Stem rot and aggregated sheath spot are the two major stem and sheath diseases affecting rice (Oryza sativa L.) in temperate areas. A third fungal disease, sheath blight, is a major disease in tropical areas. Resistance to these diseases is a key objective in rice breeding programs but phenotyping is challenged by the confounding effects of phenological and morphological traits such as flowering time (FT) and plant height (PH). This study sought to identify quantitative trait loci (QTL) for resistance to these three diseases after removing the confounding effects of FT and PH. Two populations of advanced breeding germplasm, one with 316 tropical japonica and the other with 325 indica genotypes, were evaluated in field and greenhouse trials for resistance to the diseases. Phenotypic means for field and greenhouse disease resistance, adjusted by FT and PH, were analyzed for associations with 29,000 single nucleotide polymorphisms (SNPs) in tropical japonica and 50,000 SNPs in indica. A total of 29 QTL were found for resistance that were not associated with FT or PH. Multilocus models with selected resistance-associated SNPs were fitted for each disease to estimate their effects on the other diseases. A QTL on chromosome 9 accounted for more than 15% of the phenotypic variance for the three diseases. When resistance-associated SNPs at this locus from both the tropical japonica and indica populations were incorporated into the model, resistance was improved for all three diseases with little impact on FT and PH.

Quantitative and qualitative influence of inoculation methods on in planta growth of rice blast fungus.

ABSTRACT Molecular analyses of early disease events require infected plant tissue in which the pathogen is present in high quantities and interacts with the plant in a way found in the field. In this study, a quantitative polymerase chain reaction (Q-PCR) assay was developed to determine an "infection ratio" of fungal to plant cells in infected tissues. This assay was used to evaluate four inoculation methods (spray, mist, dip, and sheath) as well as use of whole plants or excised parts. Fluorescence stereomicroscopy was used to follow individual lesions developing from appressoria to macroscopic symptoms. Disease progression and outcomes were documented from 24 to 96 h postinoculation (hpi), as well as effectiveness of Pi-ta-mediated resistance. Even at 96 hpi, fungus proliferated well ahead of visible plant damage, especially in veins. Developing lesions sometimes were surrounded by greener areas in detached leaves. Spray inoculation was not sufficient for detecting fungal gene expression in planta before 96 h. Alternatively, a leaf sheath assay produced infected tissues containing 10 to 30% fungal DNA by 34 h. Used together, Q-PCR quantification and fluorescence stereomicroscopy will facilitate studies of early plant invasion because infection density and fungal growth stages are directly observed, not assumed from incubation time.

Interaction transcriptome analysis identifies Magnaporthe oryzae BAS1-4 as Biotrophy-associated secreted proteins in rice blast disease.

Biotrophic invasive hyphae (IH) of the blast fungus Magnaporthe oryzae secrete effectors to alter host defenses and cellular processes as they successively invade living rice (Oryza sativa) cells. However, few blast effectors have been identified. Indeed, understanding fungal and rice genes contributing to biotrophic invasion has been difficult because so few plant cells have encountered IH at the earliest infection stages. We developed a robust procedure for isolating infected-rice sheath RNAs in which approximately 20% of the RNA originated from IH in first-invaded cells. We analyzed these IH RNAs relative to control mycelial RNAs using M. oryzae oligoarrays. With a 10-fold differential expression threshold, we identified known effector PWL2 and 58 candidate effectors. Four of these candidates were confirmed to be fungal biotrophy-associated secreted (BAS) proteins. Fluorescently labeled BAS proteins were secreted into rice cells in distinct patterns in compatible, but not in incompatible, interactions. BAS1 and BAS2 proteins preferentially accumulated in biotrophic interfacial complexes along with known avirulence effectors, BAS3 showed additional localization near cell wall crossing points, and BAS4 uniformly outlined growing IH. Analysis of the same infected-tissue RNAs with rice oligoarrays identified putative effector-induced rice susceptibility genes, which are highly enriched for sensor-transduction components rather than typically identified defense response genes.

Recent progress in the characterization of molecular determinants in the Xanthomonas axonopodis pv. manihotis-cassava interaction.

Cassava bacterial blight, caused by Xanthomonas axonopodis pv. manihotis (Xam), is a widespread disease that affects cassava (Manihot esculenta Crantz). Studies on the pathogen population structure, pathogen diagnosis, identification and expression of plant genes involved in resistance have been carried out. Different molecular techniques were developed to assess the genetic diversity among the Xampopulations. Characterization of Xam population dynamics over time had enable us to determine the different factors that are associated with resistance breakdown and those that influence the genetic structure or virulence phenotypes of the pathogen's population. Methods for detecting the pathogen in vegetative planting materials and true seeds were developed and contributed to reduce the impact of the disease. To better understand the genetics of resistance a quantitative trait loci (QTLs) approach was developed. Using a PCR-based strategy with degenerate primers we isolated two resistance gene candidates in cassava. We also characterized a region of a chromosome rich in R-gene like sequence. In this review we also report the main results obtained by transcript profiling methodologies, cDNA-AFLP and ESTs developed by the authors to characterize the genes involved in disease resistance. All together these techniques allowed the identification of molecular markers either associated to CBB resistance or that may represent putative genes involved in disease resistance. This article reviews current knowledge on the molecular cassava-Xam interactions.

Identification of genes in cassava that are differentially expressed during infection with Xanthomonas axonopodis pv. manihotis.

SUMMARY The cDNA-amplified fragment length polymorphism approach was used to identify differentially expressed transcripts from cassava infected by Xanthomonas axonopodis pv. manihotis (Xam). Approximately 3600 transcript-derived fragments (TDFs) were screened of which 340 were isolated. The nucleotide sequences of 250 TDFs were analysed and assembled into contigs and singletons. The amino acid sequences of their predicted products were compared with entries in databases and 63 of these clones showed homology to known plant genes. Of these, 32 showed similarity to plant defence proteins. Fifty-one TDFs corresponded to proteins of unknown function and 106 did not match any sequence in the public databases. Quantitative reverse transcription PCR was carried out with a selected set of gene transcripts that demonstrated an increase of expression during the infection. These results point out candidate genes that are associated with cassava resistance to Xam and reinforce the idea of a complex process occurring during this plant-pathogen interaction.

Análisis de expresión génica durante la respuesta de defensa de la yuca a la bacteriosis vascular (Añublo Bacteriano) / Gene expression analysis during cassava defense response to bacterial blight disease

La bacteriosis vascular de la yuca es una destructiva enfermedad en Sur América y África, causada por la bacteria Xanthomonas axonopodis pv. manihotis (Xam). Produce pérdidas entre el 12 por cien y 100 por cien de los cultivos. Algunos estudios se han realizado a nivel bioquímico y citoquímico para conocer las respuestas de defensa de la yuca a Xam; sin embargo,las bases moleculares de los mecanismos de defensa no han sido aún caracterizadas. Con el propósito de identificar genes diferencialmente expresados durante la respuesta de la planta al patógeno, se ha construido una librería sustractiva, usando el método de Sustracción Diferencial en Cadena (DSC), con 1536 clones de dos variedades resistentes(MBRA 685 y SG 107-35). De esta librería fueron seleccionados al azar 110 clones para ser secuenciados y realizar búsquedas de similitud en bases de datos públicas. El análisis de secuencia mostró 14 clones con similitud a genes previamente reportados como involucrados en procesos de defensa en plantas, 70 clones con similitud a genes de plantas sin función conocida o que no presentaron similitud, representando nuevos genes potencialmente involucrados en las respuestas de defensa de la yuca. Finalmente fueron construidos microarreglos de ADNc, usando los clones seleccionados de las librerías sustractivas para confirmar su expresión diferencial durante el desarrollo dela infección.