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Bhadauria, V.

Publications and source records attributed to Bhadauria, V..

3 recordsLinked to original sources

Inactivating a β1 subunit of SnRK1 promotes broad-spectrum disease resistance in rice

Rice is a staple crop for over half of the worlds population, and its sustainable production is vital to ensure global food security. However, rice is highly susceptible to several devastating fungal diseases1, including blast disease caused by Magnaporthe oryzae, sheath blight by Rhizoctonia solani, false smut by Ustilaginoidea virens, brown spot by Bipolaris oryzae, bakanae by Fusarium fujikuroi, and head blight by F. graminearum. The mechanisms underlying the susceptibility of rice to these fungal diseases remain unclear. Here, we report that the {beta} subunit of SnRK1, SnRK1{beta}1A, confers broad-spectrum susceptibility to these fungal diseases. Our findings reveal that diverse rice fungal pathogens have convergently evolved an effector, Gas2, which interacts with SnRK1{beta}1A to prevent its ubiquitination-mediated degradation and promotes its nuclear translocation. While SnRK1{beta}1A is expressed at low levels in healthy plants, its expression is markedly induced upon fungal infections, facilitating susceptibility by inhibiting SnRK11, the subunit of SnRK1, whose overexpression has been shown to enhance broad-spectrum resistance in rice2. Notably, rice lines with disrupted SnRK1{beta}1A are resistant to multiple fungal diseases without compromising growth and yield in the field. Together, this study demonstrates that broad-spectrum disease resistance in crops can be achieved by disrupting inducible susceptibility genes whose encoded proteins are targeted by effectors conserved in multiple pathogens.

plant biology↗

The effector recognition by synthetic sensor NLR receptors requires the concerted action of multiple interfaces within and outside the integrated domain

Plant sensor nucleotide-binding leucine-rich repeat (NLR) receptors detect pathogen effectors through their integrated domains (IDs). The RGA5 sensor NLR recognizes its corresponding effectors AVR-Pia and AVR1-CO39 from the blast fungus Magnaporthe oryzae through direct binding to its heavy metal-associated (HMA) ID to trigger the RGA4 helper NLR-dependent resistance in rice. Here we report a mutant of RGA5 named RGA5HMA5 that confers complete resistance in transgenic rice plants to the M. oryzae strains expressing the noncorresponding effector AVR-PikD. RGA5HMA5 carries three engineered interfaces, two of which lie in the HMA ID and the other in the C-terminal Lys-rich stretch tailing the ID. However, the RGA5 variants having one or two of the three interfaces, including replacing all the Lys residues with Glu residues in the Lys-rich stretch, failed to activate RGA4-dependent cell death of rice protoplasts. Altogether, this work demonstrates that sensor NLRs require a concerted action of multiple surfaces within and outside the IDs to both recognize noncorresponding effectors and activate helper NLR-mediated resistance, and has implications in structure-guided designing of sensor NLRs.

plant biology↗

Crop Information Engine and Research Assistant (CIERA) for managing genealogy, phenotypic and genotypic data for breeding programs

BackgroundWith the advent of next-generation marker platforms and phenomics in crop breeding programs, the volume of both the genotypic and phenotypic data produced has increased exponentially. Often the data remain underutilized if not properly collated, managed and accessed. Effective management of the data is paramount to making sound and timely decision on cross planning in order to accelerate genetic gain ({Delta}G) in crops for disease resistance, agronomic and end-use quality traits.\n\nResultsTo address the challenges in managing and efficient utilization of the sheer volume of data generated in a crop breeding program, we developed an electronic information system called the Crop Information Engine and Research Assistant (CIERA). The CIERA, written in Visual Basic, runs on the Microsoft Windows operating system and requires the .Net Framework 4.7 as well as the MySQL Community Server 5.7. The highly intuitive graphical user interface of CIERA includes user-friendly query tools to facilitate the collation of data across relevant phenotypic environments from its phenotypic data management database and can combine that information with the genealogy and genetic data from its genealogy management and genetic data management databases, respectively.\n\nConclusionsUsing CIERA, breeders can build a comprehensive profile of germplasm, within a few minutes, to assist them in planning crosses for enhancing genetic gain by selecting superior lines for crosses.

bioinformatics↗