Caveats and Future Directions
Consistent with the prediction that more rainfall results in more
pathogens, which result in more disease resistance – we find a positive
correlation between R gene counts and precipitation. However, the
distance between our observed correlation and our causal motivation is
quite large. Here we suggest two routes to bridge this gap –
independent replication and unraveling the causal chain.
Correlation does not imply causation. However, repeated independent
replication “does waggle its eyebrows suggestively and gesture
furtively while mouthing ’look over there’.” (Munroe 2009). Thus, a key
step in establishing that the correlation uncovered reflects our
biological hypothesis, rather than happenstance, would be to evaluate
the generality of this pattern. Some such evidence already exists –
similar results have been seen in RFLP based studies of a few R genes in
big bluestem and switchgrass (Rouse et al 2011, Zhu et al 2013). Testing
for this pattern in other Silphium species represents a promising
direction, as they would provide evolutionarily independent replication,
while covering a similar precipitation gradient, and could use the same
RenSeq baits developed here. Extending this study to more distant taxa
would provide further evidence supporting this hypothesis.
Functional studies of these R-genes would provide more evidence for our
motivating causal hypothesis. A complete, phased, chromosome-level
assembly of S. integrifolium will both allow for better
assessment of whether these genes are functional, and enable association
studies to determine the loci of pathogen resistance for incorporation
into breeding programs. Additional evaluation of the hypothesis that the
number of pathogens affecting Silphium (and/or the variation in their
ability to evade a specific R gene), as well as associating specific NLR
alleles to resistance to specific pathogens would allow for a more
mechanistic understanding of the association uncovered in this paper.