Identifying the components in Spl11-mediated defense pathway and determining the relationship between Spl11 and other defense signaling genes in rice

Ubiquitination has recently been shown to be involved in programmed cell death (PCD) in plants. Spl11 encodes an E3 ubiquitin ligase with U-Box and ARM repeat domains which negatively regulates PCD and disease resistance in rice. To identify new components in Spl11-mediated cell death pathway, a suppressor screen was performed using the spl11 mutant GR5717 and EMS as a mutagen. The spontaneous lesion formation observed in GR5717 was found to be completely suppressed in one suppressor, whereas, two other suppressors showed partial suppression. Broad-spectrum resistance in GR5717 was found to be abolished in all the suppressors. To map the genes involved in this suppression phenomenon, three F2 mapping populations were generated using the suppressor lines and spl11 mutant line TP309spl11. Two F2 populations show 3:1 ratio of segregation for suppression phenotype to lesion mimic phenotype whereas one shows 13:3 ratio, indicating either single-gene Mendelian inheritance or inheritance of one dominant and one recessive genes. Simultaneously F2 populations are also being generated to test for diallelism among different suppressors. Further, genetic analysis to study the relationship between Spl11 and other defense signaling genes such as NPR1, SGT1, RAR1 and Rac1 has been undertaken. Crosses between spl11 knockdown or Spl11 overexpression lines and other defense mutants are being generated. Overall, ubiquitination mediated defense mechanisms will be elucidated through these studies in rice which is the world’s most important food crop.USDA-CSREE

vcf2gwas: Python API for comprehensive GWAS analysis using GEMMA

MOTIVATION: Genome-wide association study (GWAS) requires a researcher to perform a multitude of different actions during analysis. From editing and formatting genotype and phenotype information to running the analysis software to summarizing and visualizing the results. A typical GWAS workflow poses a significant challenge of utilizing the command-line, manual text-editing and requiring knowledge of one or more programming/scripting languages, especially for newcomers. RESULTS: vcf2gwas is a package that provides a convenient pipeline to perform all of the steps of a traditional GWAS workflow by reducing it to a single command-line input of a Variant Call Format file and a phenotype data file. In addition, all the required software is installed with the package. vcf2gwas also implements several useful features enhancing the reproducibility of GWAS analysis. AVAILABILITY AND IMPLEMENTATION: The source code of vcf2gwas is available under the GNU General Public License. The package can be easily installed using conda. Installation instructions and a manual including tutorials can be accessed on the package website at https://github.com/frankvogt/vcf2gwas. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online

What natural variation can teach us about resistance durability

Breeding a crop variety to be resistant to a pathogen usually takes years. This is problematic because pathogens, with short generation times and fluid genomes, adapt quickly to overcome resistance. The triumph of the pathogen is not inevitable, however, as there are numerous examples of durable resistance, particularly in wild plants. Which factors then contribute to such resistance stability over millennia? We review current knowledge of wild and agricultural pathosystems, detailing the importance of genetic, species and spatial heterogeneity in the prevention of pathogen outbreaks. We also highlight challenges associated with increasing resistance diversity in crops, both in light of pathogen (co-)evolution and breeding practices. Historically it has been difficult to incorporate heterogeneity into agriculture due to reduced efficiency in harvesting. Recent advances implementing computer vision and automation in agricultural production may improve our ability to harvest mixed genotype and mixed species plantings, thereby increasing resistance durability

Host-associated microbe PCR (hamPCR) enables convenient measurement of both microbial load and community composition

The ratio of microbial population size relative to the amount of host tissue, or ‘microbial load’, is a fundamental metric of colonization and infection, but it cannot be directly deduced from microbial amplicon data such as 16S rRNA gene counts. Because existing methods to determine load, such as serial dilution plating, quantitative PCR, and whole metagenome sequencing add substantial cost and/or experimental burden, they are only rarely paired with amplicon sequencing. We introduce host-associated microbe PCR (hamPCR), a robust strategy to both quantify microbial load and describe interkingdom microbial community composition in a single amplicon library. We demonstrate its accuracy across multiple study systems, including nematodes and major crops, and further present a cost-saving technique to reduce host overrepresentation in the library prior to sequencing. Because hamPCR provides an accessible experimental solution to the well-known limitations and statistical challenges of compositional data, it has far-reaching potential in culture-independent microbiology

OsWRKY67 Plays a Positive Role in Basal and XA21-Mediated Resistance in Rice

WRKY proteins play important roles in transcriptional reprogramming in plants in response to various stresses including pathogen attack. In this study, we functionally characterized a rice WRKY gene, OsWRKY67, whose expression is upregulated against pathogen challenges. Activation of OsWRKY67 by T-DNA tagging significantly improved the resistance against two rice pathogens, Magnaporthe oryzae and Xanthomonas oryzae pv. oryzae (Xoo). Reactive oxygen species (ROS) rapidly accumulated in OsWRKY67 activation mutant lines in response to elicitor treatment, compared with the controls. Overexpression of OsWRKY67 in rice confirmed enhanced disease resistance, but led to a restriction of plant growth in transgenic lines with high levels of OsWRKY67 protein. OsWRKY67 RNAi lines significantly reduced resistance to M. oryzae and Xoo isolates tested, and abolished XA21-mediated resistance, implying the possibility of broad-spectrum resistance from OsWRKY67. Transcriptional activity and subcellular localization assays indicated that OsWRKY67 is present in the nucleus where it functions as a transcriptional activator. Quantitative PCR revealed that the pathogenesis-related genes, PR1a, PR1b, PR4, PR10a, and PR10b, are upregulated in OsWRKY67 overexpression lines. Therefore, these results suggest that OsWRKY67 positively regulates basal and XA21-mediated resistance, and is a promising candidate for genetic improvement of disease resistance in rice

The E3 Ligase APIP10 Connects the Effector AvrPiz-t to the NLR Receptor Piz-t in Rice

<div><p>Although nucleotide-binding domain, leucine-rich repeat (NLR) proteins are the major immune receptors in plants, the mechanism that controls their activation and immune signaling remains elusive. Here, we report that the avirulence effector AvrPiz-t from <i>Magnaporthe oryzae</i> targets the rice E3 ligase APIP10 for degradation, but that APIP10, in return, ubiquitinates AvrPiz-t and thereby causes its degradation. Silencing of <i>APIP10</i> in the non-<i>Piz-t</i> background compromises the basal defense against <i>M</i>. <i>oryzae</i>. Conversely, silencing of <i>APIP10</i> in the <i>Piz-t</i> background causes cell death, significant accumulation of Piz-t, and enhanced resistance to <i>M</i>. <i>oryzae</i>, suggesting that APIP10 is a negative regulator of Piz-t. We show that APIP10 promotes degradation of Piz-t via the 26S proteasome system. Furthermore, we demonstrate that AvrPiz-t stabilizes Piz-t during <i>M</i>. <i>oryzae</i> infection. Together, our results show that APIP10 is a novel E3 ligase that functionally connects the fungal effector AvrPiz-t to its NLR receptor Piz-t in rice.</p></div

Knockdown of <i>APIP10</i> expression compromises basal defense in rice.

<p>(<b>A</b>), (<b>B</b>) PTI-induced reactive oxygen species (ROS) burst in three independently transformed NPB <i>APIP10</i> RNAi and NPB lines. The mean of the three lines was used for data analysis. (<b>F</b>), (<b>G</b>) PTI-induced ROS burst in NPB <i>Piz-t</i>:<i>HA</i> and NPB <i>Piz-t</i>:<i>HA APIP10</i> RNAi lines. Rice leaf disks were treated with 100 nM flg22, 8 nM chitin (<i>hexa-N</i>-acetyl-chitohexaose), or water. ROS were detected using a luminol-chemiluminescence assay. Error bars, s.e.m. (<i>n</i> = 3). (<b>C</b>), (<b>H</b>) Induction of defense-related genes <i>OsKS4</i> and <i>OsPAL</i> at 3 h post incubation (hpi) in either water, chitin, or flg22, respectively; white bars indicate NPB lines in C and NPB <i>Piz-t</i>:<i>HA</i> in H, and grey bars indicate <i>APIP10</i> RNAi plants in respective backgrounds. qPCR was performed using gene-specific primers. Values are means and error bars, s.e.m. (<i>n</i> = 3). (<b>D</b>), (<b>I</b>) Infection assay: rice leaves of 6-week-old plants were inoculated with the virulent isolate RB22; the leaves were photographed 9 d post inoculation (dpi). (<b>E</b>), (<b>J</b>). Relative fungal growth (left) and sporulation (right) were measured 9 dpi. Values are means, error bars are s.e.m. (<i>n =</i> 8, *P<0.05)</p

Ubiquitination of AvrPiz-t by APIP10 and suppression of APIP10 E3 ubiquitin ligase activity by AvrPiz-t <i>in vitro</i>.

<p>(<b>A</b>) <i>In vitro</i> ubiquitination assay of GST:AvrPiz-t:HA by MBP:APIP10 fusion protein. Ubiquitination of AvrPiz-t by APIP10 was detected by immunoblot with the anti-HA antibody. GST:AvrPi-ta:HA was used as a negative control to determine the specificity of AvrPiz-t ubiquitination by APIP10. The experiments were performed at least three times with similar results. (<b>B</b>) Suppression of the APIP10 E3 ubiquitin ligase activity by AvrPiz-t. E3 activity of APIP10 in the presence of AvrPiz-t or AvrPi-ta was determined by immunoblot with the anti-Myc antibody. (<b>C</b>) Immunoblot with anti-MBP antibody to determine the amount of MBP-APIP10 or MBP protein loaded in each lane.</p

AvrPiz-t and APIP10 degrade each other in <i>N</i>. <i>benthamiana</i>.

<p>(<b>A</b>) Degradation of GFP:AvrPiz-t:HA with co-expression of Myc:APIP10 in <i>N</i>. <i>benthamiana</i>. Myc:APIP10 or Myc:APIP10 dRING was co-expressed with GFP:AvrPiz-t:HA by agro-infiltration. Tissues were harvested 2 days after infiltration. MG132 (50 μM) was infiltrated with DMSO as a control at 18 h before sampling. Tap tag protein was expressed as an internal control and was detected by immunoblot with the peroxidase anti-peroxidase (PAP). The transcriptional level of each gene was determined by semi-quantitative (sq)-PCR. dRING denotes APIP10 dRING. The experiments were performed at least three times with similar results. (<b>B</b>) Degradation of APIP10 when it is co-expressed with the AvrPiz-t protein in <i>N</i>. <i>benthamiana</i>. Tissues were harvested 3 days after infiltration. MG132 (50 μM) was infiltrated with DMSO as a control at 18 h before sampling. The experiments were performed at least three times with similar results.</p