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Genomic and transcriptomic analyses reveal polygenic architecture for ecologically important traits in aspen (Populus tremuloides Michx.)
  • +5
  • Jennifer Lind-Riehl,
  • Christopher Cole,
  • Clay Morrow,
  • Hilary Barker,
  • Carolina Bernhardsson,
  • Kennedy Rubert-Nason,
  • Pär Ingvarsson,
  • Richard Lindroth
Jennifer Lind-Riehl
University of Wisconsin-Madison

Corresponding Author:jenniferfaith.lind@gmail.com

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Christopher Cole
University of Wisconsin Madison
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Clay Morrow
University of Wisconsin-Madison
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Hilary Barker
University of Wisconsin-Madison
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Carolina Bernhardsson
Uppsala Universitet
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Kennedy Rubert-Nason
University of Wisconsin Madison
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Pär Ingvarsson
Sveriges lantbruksuniversitet
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Richard Lindroth
University of Wisconsin Madison Graduate School
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Abstract

Intraspecific genetic variation in foundation species such as aspen (Populus tremuloides Michx.) shapes their impact on forest structure and function. Identifying genes underlying ecologically important traits is key to understanding that impact. Previous studies using single-locus genome-wide association (GWA) analyses to identify candidate genes have identified fewer genes than anticipated for highly heritable quantitative traits. Mounting evidence suggests that polygenic control of quantitative traits is largely responsible for this “missing heritability” phenomenon. Our research characterized the genetic architecture of 35 ecologically important traits using a common garden of aspen through genomic and transcriptomic analyses. A multilocus association model revealed that most traits displayed a polygenic architecture, with most variation explained by loci with small effects (likely below the detection levels of single-locus GWA methods). Consistent with a polygenic architecture, our single-locus GWA analyses found only 38 significant SNPs in 22 genes across 15 traits. Next, we used differential expression analysis on a subset of aspen genets with divergent concentrations of salicinoid phenolic glycosides (key defense traits). This complementary method to traditional GWA discovered 1,243 differentially expressed genes for a polygenic trait. Soft clustering analysis revealed three gene clusters (241 candidate genes) involved in secondary metabolite biosynthesis and regulation. Our results support the omnigenic model that complex traits are largely controlled by many small effect loci, most of which may not have obvious connections to the traits of interest. Our work reveals that ecologically important traits governing higher-order community- and ecosystem-level attributes of a foundation forest tree species have complex underlying genetic structures and will require methods beyond traditional GWA analyses to unravel.
07 Jun 2023Submitted to Ecology and Evolution
13 Jun 2023Submission Checks Completed
13 Jun 2023Assigned to Editor
13 Jun 2023Review(s) Completed, Editorial Evaluation Pending
19 Jun 2023Editorial Decision: Revise Minor
31 Aug 20231st Revision Received
31 Aug 2023Submission Checks Completed
31 Aug 2023Assigned to Editor
31 Aug 2023Review(s) Completed, Editorial Evaluation Pending
04 Sep 2023Editorial Decision: Accept