What Can We Learn from -Omics Approaches to Understand Clubroot Disease?

Clubroot is one of the most economically significant diseases worldwide. As a result, many investigations focus on both curing the disease and in-depth molecular studies. Although the first transcriptome dataset for the clubroot disease describing the clubroot disease was published in 2006, many different pathogen-host plant combinations have only recently been investigated and published. Articles presenting -omics data and the clubroot pathogen Plasmodiophora brassicae as well as different host plants were analyzed to summarize the findings in the richness of these datasets. Although genome data for the protist have only recently become available, many effector candidates have been identified, but their functional characterization is incomplete. A better understanding of the life cycle is clearly required to comprehend its function. While only a few proteome studies and metabolome analyses were performed, the majority of studies used microarrays and RNAseq approaches to study transcriptomes. Metabolites, comprising chemical groups like hormones were generally studied in a more targeted manner. Furthermore, functional approaches based on such datasets have been carried out employing mutants, transgenic lines, or ecotypes/cultivars of either Arabidopsis thaliana or other economically important host plants of the Brassica family. This has led to new discoveries of potential genes involved in disease development or in (partial) resistance or tolerance to P. brassicae. The overall contribution of individual experimental setups to a larger picture will be discussed in this review.

Automated summary

Clubroot is a highly significant disease worldwide, and recent studies have focused on understanding its molecular mechanisms and finding potential cures. This review analyzes -omics data and studies on the pathogen Plasmodiophora brassicae and various host plants, summarizing the findings and highlighting the importance of understanding the disease's life cycle and functional characterization of effector candidates.