AI Article Synopsis

  • Asian soybean rust (ASR), caused by the fungus Phakopsora pachyrhizi, has potential crop losses over 80% and currently lacks durable resistance in soybean cultivars.
  • The study utilized laser capture microdissection, RNA sequencing, and bioinformatics to identify thousands of expressed contigs and a secretome of 851 proteins, revealing potential effector candidates.
  • Some of these effector candidates were found to suppress plant immunity during early infection stages, supporting their role in facilitating ASR infection in soybeans.

Article Abstract

Asian soybean rust (ASR), caused by the obligate biotrophic fungus Phakopsora pachyrhizi, can cause losses greater than 80%. Despite its economic importance, there is no soybean cultivar with durable ASR resistance. In addition, the P. pachyrhizi genome is not yet available. However, the availability of other rust genomes, as well as the development of sample enrichment strategies and bioinformatics tools, has improved our knowledge of the ASR secretome and its potential effectors. In this context, we used a combination of laser capture microdissection (LCM), RNAseq and a bioinformatics pipeline to identify a total of 36 350 P. pachyrhizi contigs expressed in planta and a predicted secretome of 851 proteins. Some of the predicted secreted proteins had characteristics of candidate effectors: small size, cysteine rich, do not contain PFAM domains (except those associated with pathogenicity) and strongly expressed in planta. A comparative analysis of the predicted secreted proteins present in Pucciniales species identified new members of soybean rust and new Pucciniales- or P. pachyrhizi-specific families (tribes). Members of some families were strongly up-regulated during early infection, starting with initial infection through haustorium formation. Effector candidates selected from two of these families were able to suppress immunity in transient assays, and were localized in the plant cytoplasm and nuclei. These experiments support our bioinformatics predictions and show that these families contain members that have functions consistent with P. pachyrhizi effectors.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6638266PMC
http://dx.doi.org/10.1111/mpp.12405DOI Listing

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