Published August 11, 2020 | Version v1
Dataset Open

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

  • 1. University of Louisiana at Lafayette
  • 2. University of California, Berkeley
  • 3. University of South Florida
  • 4. Northern Arizona University

Description

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.

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 provided by: University of Louisiana at Lafayette
Crossref Funder Registry ID: http://dx.doi.org/10.13039/100008520

Funding provided by: University of South Florida
Crossref Funder Registry ID: http://dx.doi.org/10.13039/100008900

Funding provided by: National Science Foundation
Crossref Funder Registry ID: http://dx.doi.org/10.13039/100000001
Award Number: IOS-1558035,OIA-1920858

Funding provided by: Northern Arizona University
Crossref Funder Registry ID: http://dx.doi.org/10.13039/100008883

Funding provided by: American Genetics Association
Crossref Funder Registry ID:

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Additional details

Related works

Is cited by
10.1093/jhered/esaa015 (DOI)