Skip to main content
Dryad logo

Data from: The genetic architecture of plant defense tradeoffs in a common monkeyflower

Citation

Kooyers, Nicholas; Blackman, Benjamin; Donofrio, Abigail; Holeski, Liza (2020), Data from: The genetic architecture of plant defense tradeoffs in a common monkeyflower, Dryad, Dataset, https://doi.org/10.5061/dryad.w9ghx3fm8

Abstract

Determining how adaptive combinations of traits arose requires understanding the prevalence and scope of genetic constraints. Frequently observed phenotypic correlations between plant growth, defenses, and/or reproductive timing have led researchers to suggest that pleiotropy or strong genetic linkage between variants affecting independent traits is pervasive. Alternatively, these correlations could arise via independent mutations in different genes for each trait and extensive correlational selection. Here we evaluate these alternatives by conducting a QTL mapping experiment involving a cross between two populations of common monkeyflower (Mimulus guttatus) that differ in growth rate as well as total concentration and arsenal composition of plant defense compounds, phenylpropanoid glycosides (PPGs). We find no evidence that pleiotropy underlies correlations between defense and growth rate. However, there is a strong genetic correlation between levels of total PPGs and flowering time that is largely attributable to a single shared QTL. While this result suggests a role for pleiotropy/close linkage, several other QTLs also contribute to variation in total PPGs. Additionally, divergent PPG arsenals are influenced by a number of smaller-effect QTLs that each underlie variation in one or two PPGs. This result indicates that chemical defense arsenals can be finely-adapted to biotic environments despite sharing a common biochemical precursor. Together, our results show correlations between defense and life history traits are influenced by pleiotropy or genetic linkage, but genetic constraints may have limited impact on future evolutionary responses, as a substantial proportion of variation in each trait is controlled by independent loci.

Usage Notes

This entry provides all trait data (.csv) for the parent lines, F1 lines and F2 lines described in the manuscript. It also provides an the rQTL format input files for the F2 mapping population.  Please see the readme files for details on each file.

Funding

University of Louisiana at Lafayette

University of South Florida

National Science Foundation, Award: IOS-1558035,OIA-1920858

Northern Arizona University

American Genetics Association