Genome-Wide Association Studies In Plant Pathosystems: Toward an Ecological Genomics Approach

Abstract

The emergence and re-emergence of plant pathogenic microorganisms are processes that imply perturbations in both host and pathogen ecological niches. Global change is largely assumed to drive the emergence of new etiological agents by altering the equilibrium of the ecological habitats which in turn places hosts more in contact with pathogen reservoirs. In this context, the number of epidemics is expected to increase dramatically in the next coming decades both in wild and crop plants. Under these considerations, the identification of the genetic variants underlying natural variation of resistance is a pre-requisite to estimate the adaptive potential of wild plant populations and to develop new breeding resistant cultivars. On the other hand, the prediction of pathogen's genetic determinants underlying disease emergence can help to identify plant resistance alleles. In the genomic era, whole genome sequencing combined with the development of statistical methods led to the emergence of Genome Wide Association (GWA) mapping, a powerful tool for detecting genomic regions associated with natural variation of disease resistance in both wild and cultivated plants. However, GWA mapping has been less employed for the detection of genetic variants associated with pathogenicity in microbes. Here, we reviewed GWA studies performed either in plants or in pathogenic microorganisms (bacteria, fungi and oomycetes). In addition, we highlighted the benefits and caveats of the emerging joint GWA mapping approach that allows for the simultaneous identification of genes interacting between genomes of both partners. Finally, based on co-evolutionary processes in wild populations, we highlighted a phenotyping-free joint GWA mapping approach as a promising tool for describing the molecular landscape underlying plant - microbe interactions.

The genetics underlying natural variation of plant–plant interactions, a beloved but forgotten member of the family of biotic interactions

“…Finally, in agreement with other types of biotic interactions (Bartoli and Roux, ), the majority of QTL mapping studies ( n = 39) revealed a complex genetic architecture associated with plant–plant interactions (Figure ). The quantitative genetic architecture is highly diverse among plant–plant interacting systems, ranging from the identification of few medium‐effect QTLs to the identification of up to tens of small‐effect QTLs (Frachon et al ., ).…”

Genome‐wide association studies on the phyllosphere microbiome: Embracing complexity in host–microbe interactions

“…Most GWAS of plant–microbial interactions have focused on how plant genotype shapes pairwise interactions with a single microbial taxon. Representative examples can be found in the 35 GWAS of direct pathogen challenge collated by Bartoli and Roux (), or the 13 GWAS of disease resistance in maize collated by Xiao et al . ().…”

“…Although regions of 16S ribosomal RNA (rRNA) have been used most often, they afford poor resolution at the level of genera or finer clades. This limitation can be circumvented by using faster‐evolving genes to gain deeper taxonomic resolution (Bartoli and Roux, ). For example, gyraseB sequences allow pathogenic and commensal OTUs within a microbial genus to be distinguished (Barret et al ., ).…”

Plant adaptation and speciation studied by population genomic approaches

“…It seems common that genetic pathways of R‐genes confer trade‐off with growth or fitness, perhaps due to their large energetic cost (Tian, Traw, Chen, Kreitman, & Bergelson, ). Recently, GWAS of pathogen‐resistant phenotypes have also been performed in other species, including Glycine , Brassica , Medicago , Hordeum , Oryza , Setaria , Sorghum , Pisum , and Zea (reviewed in Bartoli & Roux, ), which may further clarify how common R‐genes are involved in fitness trade‐offs with other traits.…”