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ARS Home » Midwest Area » Ames, Iowa » Corn Insects and Crop Genetics Research » Research » Publications at this Location » Publication #387968

Research Project: Host and Pathogen Signaling in Cereal-Fungal Interactions

Location: Corn Insects and Crop Genetics Research

Title: An interolog-based barley interactome as an integration framework for immune signaling

Author
item VELASQUEZ-ZAPATA, VALERIA - Iowa State University
item ELMORE, J. MITCH - Iowa State University
item Fuerst, Gregory
item Wise, Roger

Submitted to: Genetics
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 4/4/2022
Publication Date: 4/18/2022
Citation: Velasquez-Zapata, V., Elmore, J., Fuerst, G.S., Wise, R.P. 2022. An interolog-based barley interactome as an integration framework for immune signaling. Genetics. 221(2):iyac056. https://doi.org/10.1093/genetics/iyac056.
DOI: https://doi.org/10.1093/genetics/iyac056

Interpretive Summary: Powdery mildew fungi infect more than 9,500 agronomic and horticultural plant species. In order to prevent economic loss due to diseases caused by powdery mildew, plant breeders incorporate disease resistance genes into varieties that are grown for food, feed, fuel and fiber. One of these resistance genes provides instructions for assembly of the barley MLA immune receptor, an ancestral cereal protein that confers recognition to powdery mildew, stem and stripe rust, rice blast and Victoria blight. However, in order to function properly, these immune receptors must interact with other helper proteins during the different stages of fungal infection and plant defense. USDA-ARS and Iowa State University scientists used a combination of computer- and laboratory-based methods to predict over 66,000 possible protein-protein interactions in barley. This network of proteins was then combined with a catalogue of barley gene activity in order to assemble the molecular building blocks associated with resistance to the powdery mildew pathogen, in addition to those proteins that interact with the MLA immune receptor. These discoveries provide a foundation for further research into the complex molecular components that control disease resistance in crops. Impact: Application of genome-scale protein-protein interaction data will enable bench scientists to quickly put together relevant biological networks to model disease resistance responses. This will promote new investigations from lab to fields, critical to breeders and growers that use disease resistance to produce better crops.

Technical Abstract: The barley MLA nucleotide-binding leucine-rich-repeat (NLR) receptor and its orthologs confer recognition specificity to many fungal diseases, including powdery mildew, stem-, and stripe rust. We used interolog inference to construct a barley protein interactome (Hordeum vulgare predicted interactome, HvInt) comprising 66,133 edges and 7,181 nodes, as a foundation to explore signaling networks associated with MLA. HvInt was compared with the experimentally validated Arabidopsis interactome of 11,253 proteins and 73,960 interactions, verifying that the 2 networks share scale-free properties, including a power-law distribution and small-world network. Then, by successive layering of defense-specific “omics” datasets, HvInt was customized to model cellular response to powdery mildew infection. Integration of HvInt with expression quantitative trait loci (eQTL) enabled us to infer disease modules and responses associated with fungal penetration and haustorial development. Next, using HvInt and infection–time–course RNA sequencing of immune signaling mutants, we assembled resistant and susceptible subnetworks. The resulting differentially coexpressed (resistant – susceptible) interactome is essential to barley immunity, facilitates the flow of signaling pathways and is linked to mildew resistance locus a (Mla) through trans eQTL associations. Lastly, we anchored HvInt with new and previously identified interactors of the MLA coiled coli + nucleotide-binding domains and extended these to additional MLA alleles, orthologs, and NLR outgroups to predict receptor localization and conservation of signaling response. These results link genomic, transcriptomic, and physical interactions during MLA-specified immunity.