Skip to main content
ARS Home » Midwest Area » St. Paul, Minnesota » Cereal Disease Lab » Research » Publications at this Location » Publication #272842
Title: Using hierarchical clustering of secreted protein families to classify and rank candidate effectors of rust fungi

Author
item SAUNDERS, D.G.O. - Sainsbury Laboratory
item WIN, J - Sainsbury Laboratory
item CANO, L.M. - Sainsbury Laboratory
item Szabo, Les
item KAMOUN, S - Sainsbury Laboratory
item RAFFAELE, S - Sainsbury Laboratory

Submitted to: PLOS ONE
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 12/6/2011
Publication Date: 1/6/2012
Citation: Saunders, D., Win, J., Cano, L., Szabo, L.J., Kamoun, S., Raffaele, S. 2012. Using hierarchical clustering of secreted protein families to classify and rank candidate effectors of rust fungi. PLoS One. 7(1):e29847.

Interpretive Summary: Rust fungi are one of the largest groups of plant pathogens and caused significant loss in production in the U.S. and worldwide. Recently, the genomes of two rust fungi were sequenced, which provides new tools for better understanding these pathogens and screening for effective disease resistance genes. A pipeline was designed to help indentify candidate fungal effector genes that produce virulence factors and trigger plant resistance responses. This pipeline was used to analyze the genomic data from two rust fungi, wheat stem rust pathogen (Puccinia graminis f. sp. tritici) and the poplar leaf rust pathogen (Melampsora larici-populina). Using this approach, sixteen families of candidate effector genes identified and three families were characterized in more detail. This method provides a new tool to identify candidate fungal effector genes for further testing using functional analysis.

Technical Abstract: Rust fungi are obligate biotrophic pathogens causing considerable damage on crop plants. P. graminis f. sp. tritici, the causal agent of wheat stem rust, and M. larici-populina, the poplar rust pathogen, have strong deleterious impact on wheat and poplar wood production, respectively. The recently released genome sequence of these two rust pathogens enables a complete analysis of candidate effector genes as an initial step towards probing plant germplasm for novel resistance components. We designed a comprehensive in silico analysis pipeline to identify the putative effector repertoire from two newly sequenced filamentous plant pathogen genomes. Known effector proteins show at least one of the following properties: (i) secretion signals, (ii) similarity to haustorial proteins, (iii) are small and cysteine rich, (iv) contain a known effector motif or a nuclear localization signal, (v) are encoded by genes with long intergenic regions, (vi) contain internal repeats, and (vii) contain PFAM domains enriched in secretomes. We used Markov clustering and hierarchical clustering to classify rust protein families and rank them according to their likelihood of being effectors. Using this approach, we identified sixteen families of candidate effectors and we examined in detail three families that illustrate typical effector properties and that we considered of high value for functional characterization. This study revealed a diverse set of candidate effectors, including families of haustorial expressed secreted proteins and small cysteine-rich proteins. Our comprehensive classification of the candidate effectors is a starting point for experimental validation and functional screening for in planta activities.