Abstract
Microgeographic adaptation provides a particularly interesting context for understanding the genetic basis of phenotypic divergence and may also present unique empirical challenges. In particular, plant adaptation to extreme soil mosaics may generate barriers to gene flow or shifts in mating system that confound simple genomic scans for adaptive loci. Here, we combine three approaches – quantitative trait locus (QTL) mapping of candidate intervals in controlled crosses, population resequencing (PoolSeq) and analyses of wild recombinant individuals – to investigate one trait associated with Mimulus guttatus (yellow monkeyflower) adaptation to geothermal soils in Yellowstone National Park. We mapped a major QTL causing dense leaf trichomes in thermally adapted plants to a <50-kb region of linkage Group 14 (Tr14) previously implicated in trichome divergence between independent M. guttatus populations. A PoolSeq scan of Tr14 region revealed a cluster of six genes, coincident with the inferred QTL peak, with high allele frequency differences sufficient to explain observed phenotypic differentiation. One of these, the R2R3 MYB transcription factor Migut.N02661, is a plausible functional candidate and was also strongly associated (r2 = 0.27) with trichome phenotype in analyses of wild-collected admixed individuals. Although functional analyses will be necessary to definitively link molecular variants in Tr14 with trichome divergence, our analyses are a major step in that direction. They point to a simple, and parallel, genetic basis for one axis of Mimulus guttatus adaptation to an extreme habitat, suggest a broadly conserved genetic basis for trichome variation across flowering plants and pave the way for further investigations of this challenging case of microgeographic incipient speciation.
Original language | English |
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Pages (from-to) | 5647-5662 |
Number of pages | 16 |
Journal | Molecular Ecology |
Volume | 25 |
Issue number | 22 |
DOIs | |
State | Published - Nov 1 2016 |
Keywords
- adaptation
- admixture
- population genomics
- quantitative trait locus mapping