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Bacterial leaf streak of rice, caused by Xanthomonas oryzae pv. oryzicola (Xoc) is an increasingly important yield constraint in this staple crop. A mesophyll colonizer, Xoc differs from X. oryzae pv. oryzae (Xoo), which invades xylem to cause bacterial blight of rice. Both produce multiple distinct TAL effectors, type III-delivered proteins that transactivate effector-specific host genes. A TAL effector finds its target(s) via a partially degenerate code whereby the modular effector amino acid sequence identifies nucleotide sequences to which the protein binds. Virulence contributions of some Xoo TAL effectors have been shown, and their relevant targets, susceptibility (S) genes, identified, but the role of TAL effectors in leaf streak is uncharacterized. We used host transcript profiling to compare leaf streak to blight and to probe functions of Xoc TAL effectors. We found that Xoc and Xoo induce almost completely different host transcriptional changes. Roughly one in three genes upregulated by the pathogens is preceded by a candidate TAL effector binding element. Experimental analysis of the 44 such genes predicted to be Xoc TAL effector targets verified nearly half, and identified most others as false predictions. None of the Xoc targets is a known bacterial blight S gene. Mutational analysis revealed that Tal2g, which activates two genes, contributes to lesion expansion and bacterial exudation. Use of designer TAL effectors discriminated a sulfate transporter gene as the S gene. Across all targets, basal expression tended to be higher than genome-average, and induction moderate. Finally, machine learning applied to real vs. falsely predicted targets yielded a classifier that recalled 92% of the real targets with 88% precision, providing a tool for better target prediction in the future. Our study expands the number of known TAL effector targets, identifies a new class of S gene, and improves our ability to predict functional targeting.

Clavibacter michiganensis subsp. nebraskensis (Cmn), the causal organism of Goss's wilt and leaf blight of maize, can be detected in the phyllosphere of its host prior to disease development. We compared the morphology and pathogenicity of 37 putative isolates of Cmn recovered from asymptomatic and symptomatic maize leaves. Thirty-three of the isolates produced mucoid orange colonies, irrespective of the source of isolation and all but four of these isolates were pathogenic on maize. The remaining 4 isolates recovered from asymptomatic leaves had large fluidal yellow colonies, and were non-pathogenic on maize. Isolates varied in their aggressiveness on a susceptible hybrid of maize but no significant differences in aggressiveness were detected between epiphytic isolates and those recovered from diseased maize tissues. The genomics of Cmn is poorly understood; therefore as a first step to determining what genes may play a role in virulence, we compared 33 putative virulence gene sequences from 6 pathogenic and a non-pathogenic isolate recovered from the phyllosphere. Sequence polymorphisms were detected in 5 genes, cellulase A, two endoglucanases, xylanase B and a pectate lyase but there was no relationship with pathogenicity. Further research is needed to determine what genes play a role in virulence of Cmn. Our data show however, that the virulence factors in Cmn likely differ from those reported for the closely related subspecies michiganensis and sepedonicus.

Phytophthora sojae is a soil-borne oomycete and the causal agent of Phytophthora root and stem rot (PRR) in soybean ( Glycine max [L.] Merrill). Yield losses attributed to P . sojae are devastating in disease-conducive environments, with global estimates surpassing 1.1 million tonnes annually. Historically, management of PRR has entailed host genetic resistance (both vertical and horizontal) complemented by disease-suppressive cultural practices (e.g., oomicide application). However, the vast expansion of complex and/or diverse P . sojae pathotypes necessitates developing novel technologies to attenuate PRR in field environments. Therefore, the objective of the present study was to couple high-throughput sequencing data and deep learning to elucidate molecular features in soybean following infection by P . sojae . In doing so, we generated transcriptomes to identify differentially expressed genes (DEGs) during compatible and incompatible interactions with P . sojae and a mock inoculation. The expression data were then used to select two defense-related transcription factors (TFs) belonging to WRKY and RAV families. DNA Affinity Purification and sequencing (DAP-seq) data were obtained for each TF, providing putative DNA binding sites in the soybean genome. These bound sites were used to train Deep Neural Networks with convolutional and recurrent layers to predict new target sites of WRKY and RAV family members in the DEG set. Moreover, we leveraged publicly available Arabidopsis ( Arabidopsis thaliana ) DAP-seq data for five TF families enriched in our transcriptome analysis to train similar models. These Arabidopsis data-based models were used for cross-species TF binding site prediction on soybean. Finally, we created a gene regulatory network depicting TF-target gene interactions that orchestrate an immune response against P . sojae . Information herein provides novel insight into molecular plant-pathogen interaction and may prove useful in developing soybean cultivars with more durable resistance to P . sojae .

Plant disease resistance genes are widely used in agriculture to reduce disease outbreaks and epidemics and ensure global food security. In soybean, Rps (Resistance to Phytophthora sojae ) genes are used to manage Phytophthora sojae , a major oomycete pathogen that causes Phytophthora stem and root rot (PRR) worldwide. This study aims to identify temporal changes in P. sojae pathotype complexity, diversity, and Rps gene efficacy. Pathotype data was collected from 5121 isolates of P. sojae , derived from 29 surveys conducted between 1990 and 2019 across the United States, Argentina, Canada, and China. This systematic review shows a loss of efficacy of specific Rps genes utilized for disease management and a significant increase in the pathotype diversity of isolates over time. This study finds that the most widely deployed Rps genes used to manage PRR globally, Rps1a , Rps1c and Rps1k , are no longer effective for PRR management in the United States, Argentina, and Canada. This systematic review emphasizes the need to widely introduce new sources of resistance to P. sojae , such as Rps3a , Rps6 , or Rps11 , into commercial cultivars to effectively manage PRR going forward. Rps genes are used to manage the major soybean pathogen Phytophthora sojae , which causes Phytophthora stem and root rot (PRR). Here, the authors show that widely used Rps genes are no longer effective for managing PRR in the United States, Canada and Argentina.

Phyllachora maydis is a fungal pathogen causing tar spot of corn ( Zea mays L.), a new and emerging, yield-limiting disease in the United States. Since being first reported in Illinois and Indiana in 2015, P. maydis can now be found across much of the corn growing regions of the United States. Knowledge of the epidemiology of P. maydis is limited but could be useful in developing tar spot prediction tools. The research presented here aims to elucidate the environmental conditions necessary for the development of tar spot in the field and the creation of predictive models to anticipate future tar spot epidemics. Extended periods (30-day windowpanes) of moderate mean ambient temperature (18–23 °C) were most significant for explaining the development of tar spot. Shorter periods (14- to 21-day windowpanes) of moisture (relative humidity, dew point, number of hours with predicted leaf wetness) were negatively correlated with tar spot development. These weather variables were used to develop multiple logistic regression models, an ensembled model, and two machine learning models for the prediction of tar spot development. This work has improved the understanding of P. maydis epidemiology and provided the foundation for the development of a predictive tool for anticipating future tar spot epidemics.

Genomes of the rice (Oryza sativa) xylem and mesophyll pathogens Xanthomonas oryzae pv. oryzae (Xoo) and pv. oryzicola (Xoc) encode numerous secreted transcription factors called transcription activator-like (TAL) effectors. In a few studied rice varieties, some of these contribute to virulence by activating corresponding host susceptibility genes. Some activate disease resistance genes. The roles of X. oryzae TAL effectors in diverse rice backgrounds, however, are poorly understood. Xoo TAL effectors that promote infection by activating SWEET sucrose transporter genes were expressed in TAL effector-deficient X. oryzae strain X11-5A, and assessed in 21 rice varieties. Some were also tested in Xoc on variety Nipponbare. Several Xoc TAL effectors were tested in X11-5A on four rice varieties. Xoo TAL effectors enhanced X11-5A virulence on most varieties, but to varying extents depending on the effector and variety. SWEET genes were activated in all tested varieties, but increased virulence did not correlate with activation level. SWEET activators also enhanced Xoc virulence on Nipponbare. Xoc TAL effectors did not alter X11-5A virulence. SWEET-targeting TAL effectors contribute broadly and non-tissue-specifically to virulence in rice, and their function is affected by host differences besides target sequences. Further, the utility of X11-5A for characterizing individual TAL effectors in rice was established.

For soybean, novel single dominant Resistance to Phytophthora sojae ( Rps) genes are sought to manage Phytophthora root and stem rot. In this study, resistance to P. sojae was mapped individually in four recombinant inbred line (RIL) populations derived from crosses of the susceptible cultivar Williams with PI 407985, PI 408029, PI 408097, and PI424477 previously identified as putative novel sources of disease resistance. Each population was screened for resistance with five to seven isolates of P. sojae separately over multiple F 7 –F 10 generations. Additionally, three of the populations were screened with inoculum from the combination of three P. sojae isolates (PPR), which comprised virulence to 14 Rps genes. Over 2,300 single-nucleotide polymorphism markers were used to construct genetic maps in each population to identify chromosomal regions associated with resistance to P. sojae . Resistance segregated as one or two genes to the individual isolates and one gene toward PPR in each population and mapped to chromosomes 3, 13, or 18 in one or more of the four RIL populations. Resistance to five isolates mapped to the same chromosome 3 region are as follows: OH7 (PI 424477 and PI408029), OH12168, OH7/8, PPR (PI 407985), and 1.S.1.1 (PI408029). The resistance regions on chromosome 13 also overlapped for OH1, OH25, OH-MIA (PI424477), PPR (PI 424477, PI 407985, and PI 408097), PPR and OH0217 (PI 408097), and OH4 (PI 408029), but were distinct for each population suggesting multiple genes confer resistance. Two regions were identified on chromosome 18 but all appear to map to known loci; notably, resistance to the combined inoculum (PPR) did not map at this locus. However, there are putative new alleles in three of four populations, three on chromosome 3 and two on chromosome 13 based on mapping location but also known virulence in the isolate used. This characterization of all the Rps genes segregating in these populations to these isolates will be informative for breeding, but the combined inoculum was able to map a novel loci. Furthermore, within each of these P. sojae isolates, there was virulence to more than the described Rps genes, and the effectiveness of the novel genes requires testing in larger populations.

Engineered nucleases that cleave specific DNA sequences in vivo are valuable reagents for targeted mutagenesis. Here we report a new class of sequence-specific nucleases created by fusing transcription activator-like effectors (TALEs) to the catalytic domain of the FokI endonuclease. Both native and custom TALE-nuclease fusions direct DNA double-strand breaks to specific, targeted sites.

Genomes of the rice ( Oryza sativa ) xylem and mesophyll pathogens X anthomonas oryzae pv. oryzae ( Xoo ) and pv. oryzicola ( Xoc ) encode numerous secreted transcription factors called transcription activator‐like ( TAL ) effectors. In a few studied rice varieties, some of these contribute to virulence by activating corresponding host susceptibility genes. Some activate disease resistance genes. The roles of X . oryzae TAL effectors in diverse rice backgrounds, however, are poorly understood. Xoo TAL effectors that promote infection by activating SWEET sucrose transporter genes were expressed in TAL effector‐deficient X. oryzae strain X11‐5A, and assessed in 21 rice varieties. Some were also tested in Xoc on variety Nipponbare. Several Xoc TAL effectors were tested in X11‐5A on four rice varieties. Xoo TAL effectors enhanced X11‐5A virulence on most varieties, but to varying extents depending on the effector and variety. SWEET genes were activated in all tested varieties, but increased virulence did not correlate with activation level. SWEET activators also enhanced Xoc virulence on Nipponbare. Xoc TAL effectors did not alter X11‐5A virulence. SWEET ‐targeting TAL effectors contribute broadly and non‐tissue‐specifically to virulence in rice, and their function is affected by host differences besides target sequences. Further, the utility of X11‐5A for characterizing individual TAL effectors in rice was established.

Bacterial leaf streak of rice, caused by Xanthomonas oryzae pv. oryzicola (Xoc) is an increasingly important yield constraint in this staple crop. A mesophyll colonizer, Xoc differs from X. oryzae pv. oryzae (Xoo), which invades xylem to cause bacterial blight of rice. Both produce multiple distinct TAL effectors, type III-delivered proteins that transactivate effector-specific host genes. A TAL effector finds its target(s) via a partially degenerate code whereby the modular effector amino acid sequence identifies nucleotide sequences to which the protein binds. Virulence contributions of some Xoo TAL effectors have been shown, and their relevant targets, susceptibility (S) genes, identified, but the role of TAL effectors in leaf streak is uncharacterized. We used host transcript profiling to compare leaf streak to blight and to probe functions of Xoc TAL effectors. We found that Xoc and Xoo induce almost completely different host transcriptional changes. Roughly one in three genes upregulated by the pathogens is preceded by a candidate TAL effector binding element. Experimental analysis of the 44 such genes predicted to be Xoc TAL effector targets verified nearly half, and identified most others as false predictions. None of the Xoc targets is a known bacterial blight S gene. Mutational analysis revealed that Tal2g, which activates two genes, contributes to lesion expansion and bacterial exudation. Use of designer TAL effectors discriminated a sulfate transporter gene as the S gene. Across all targets, basal expression tended to be higher than genome-average, and induction moderate. Finally, machine learning applied to real vs. falsely predicted targets yielded a classifier that recalled 92% of the real targets with 88% precision, providing a tool for better target prediction in the future. Our study expands the number of known TAL effector targets, identifies a new class of S gene, and improves our ability to predict functional targeting.