Tag Archives: Microbe-Host

Comparative R-Genes Project

Our current understanding of how polymorphism is maintained relies on models of obligate pairwise species interactions but at least half of all plant pathogens have multiple hosts. This raises the possibility that pathogens drive convergent evolution in co-occurring plants. We propose to test this hypothesis by studying co-occurring Brassicaceae plant species, and how shared plant pathogens can potentially maintain ancient balanced polymorphism of resistance genes in plants. Arabidopsis thaliana has long been the plant model for genetics. We will focus on a set of approximately 180 natural plant populations in the southern France (Midi-Pyrenees) that contain A. thaliana, as well as two closely related weedy Brassicaceae; Cardamine hirsuta and Erophila verna. Our major aim is to unravel the genetic architecture and evolutionary dynamics behind all the R genes shared among these three species. We do this by sequencing all R genes in natural populations of co-occurring C. hirsuta, A. thaliana and E. verna plants. This project has 4 specific aims.
1. Reconstruction of R gene evolution. We will isolate DNA and perform R-gene enrichment sequencing (RENSeq) on 60 natural populations of co-occurring Arabidopsis thaliana, Erophila verna and Cardamine hirsuta, collected in Southern France. After orthologous genes have been detected among the three species, several statistical approaches can be applied to study the evolution of those R genes. We propose to explain evolutionary dynamics observed in these R genes through functional characterization from an ecological perspective (component 2), physiological costs of maintaining resistance in the absence of disease (component 3) and genomic and functional constraints of these R genes (component 4).
2. Functional Ecology of homologs. Shared pathogens are likely driving some of the R gene evolution dynamics we have observed in the past in A. thaliana (Karasov, Kniskern, et al., 2014a; Karasov, Horton, et al., 2014). Pathogen effectors will be isolates in the co-occurring pathobiomes with effector enrichment sequencing (PATHSeq) and metagenomics. We propose a two-tiered approach to test how shared pathogens and their effectors might shape R gene evolution. Transient expression on R- avr protein pairs of a small set of divergently evolving R genes will be performed to study what effectors interact with different homologs, and ancestral protein reconstruction on these R genes will be performed to understand how neofunctionalization of homologs could lead to potential differences in Avr recognition.
3. Physiological burden of resistance. Fitness trade-offs exist for carrying the resistance allele in absence of disease, as demonstrated for RPM1 (Stahl, Dwyer, Mauricio, Kreitman, & Bergelson, 1999) and RPS 5 (Karasov, Kniskern, et al., 2014a) although we also demonstrated an exemption with RPS2 (MacQueen, Sun, & Bergelson, 2016). We will test the costs of carrying functional R alleles (candidates of interest derived from first two components of this grant) by creating isogenic lines in all three species, and test fitness effects of disease resistance in climate cell and common garden experiments in the field.
4. Genomic and functional constraints. Does any given R gene recognize a set of effectors, or only one? Do they function as direct recognition proteins, or are they guarding other plant receptors to initiate a defence response? Are they located in tandem repeats, and where in the genome? Both genomic location and genetic architecture can influence the evolution of a gene. Single copy homologs have less freedom to diversify, and genes in recombination hotspots are more likely to undergo rapid evolution. In this component, we are taking a closer look at the genomic and functional constraints of R gene homologs through bio-informatics approaches and functional characterization of protein/protein interactions to establish roles of different R genes. We will perform a phenotype free joint GWAS on geographically linked plant and P. syringae pairs to gain insights in the genomic scale at which this diffuse evolution across different species occurs.