10.5061/DRYAD.W9GHX3FM8
Kooyers, Nicholas
0000-0003-3398-7377
University of Louisiana at Lafayette
Blackman, Benjamin
University of California, Berkeley
Donofrio, Abigail
University of South Florida
Holeski, Liza
Northern Arizona University
Data from: The genetic architecture of plant defense tradeoffs in a common
monkeyflower
Dryad
dataset
2020
Mimulus guttatus (common yellow monkeyflower)
Erythranthe guttata
quantitative trait loci (QTL)
plant functional strategies
phenylpropanoid glycosides Subject area: Genomics and gene mapping
Quantitative genetics and Mendelian inheritance
University of Louisiana at Lafayette
https://ror.org/01x8rc503
University of South Florida
https://ror.org/032db5x82
National Science Foundation
https://ror.org/021nxhr62
IOS-1558035,OIA-1920858
Northern Arizona University
https://ror.org/0272j5188
American Genetics Association
2020-08-11T00:00:00Z
2020-08-11T00:00:00Z
en
https://doi.org/10.1093/jhered/esaa015
33337070608 bytes
9
CC0 1.0 Universal (CC0 1.0) Public Domain Dedication
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.
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.