Integrated Analysis of Gene Expression, SNP, InDel, and CNV Identifies Candidate Avirulence Genes in Australian Isolates of the Wheat Leaf Rust PathogenPuccinia triticina

The leaf rust pathogen,Puccinia triticina(Pt), threatens global wheat production. The deployment of leaf rust (Lr) resistance (R) genes in wheat varieties is often followed by the development of matching virulence inPtdue to presumed changes in avirulence (Avr) genes inPt. Identifying such Avr genes is a crucial step to understand the mechanisms of wheat-rust interactions. This study is the first to develop and apply an integrated framework of gene expression, single nucleotide polymorphism (SNP), insertion/deletion (InDel), and copy number variation (CNV) analysis in a rust fungus and identify candidate avirulence genes. Using a long-read basedde novogenome assembly of an isolate ofPt('Pt104') as the reference, whole-genome resequencing data of 12Ptpathotypes derived from three lineages Pt104, Pt53, and Pt76 were analyzed. Candidate avirulence genes were identified by correlating virulence profiles with small variants (SNP and InDel) and CNV, and RNA-seq data of an additional threePtisolates to validate expression of genes encoding secreted proteins (SPs). Out of the annotated 29,043 genes, 2392 genes were selected as SP genes with detectable expression levels. Small variant comparisons between the isolates identified 27-40 candidates and CNV analysis identified 14-31 candidates for each Avr gene, which when combined, yielded the final 40, 64, and 69 candidates forAvrLr1,AvrLr15,andAvrLr24, respectively. Taken together, our results will facilitate future work on experimental validation and cloning of Avr genes. In addition, the integrated framework of data analysis that we have developed and reported provides a more comprehensive approach for Avr gene mining than is currently available.