DOI: 10.5061/dryad.9zw3r22jr
title: Data from: Genomic and transcriptomic analyses reveal polygenic architecture for ecologically-important functional traits in aspen (Populus tremuloides Michx.)

description: 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 30 ecologically
 important traits using a common garden of aspen through genomic and
 transcriptomic analyses. A multilocus association model revealed that most
 traits displayed a highly 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 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.
description: <strong>WisAsp_Tree_Trait_BLUPs</strong><br><br>Rank-transformed BLUPs (best linear unbiased predictors) of ecologically important tree traits, formatted for GWAS analyses<br><br><strong>WisAsp_MAF005 bed file</strong> WisAsp bed file for genome-wide association analyses (single-locus, multi-trait, and multilocus) using PLINK and GEMMA<br><br><strong>WisAsp_MAF005 bim file</strong> WisAsp bim file for genome-wide association analyses (single-locus, multi-trait, and multilocus) using PLINK and GEMMA<br><br><strong>WisAsp_MAF005 fam file</strong> WisAsp bim file for genome-wide association analyses (single-locus, multi-trait, and multilocus) using PLINK and GEMMA<br><br><strong>gemma_bslmm_MAF005 script file</strong><br><br>Script to run GEMMA's BSLMM model on a high through-put computing system<br><br><strong>WisAsp_Expression_Counts.csv</strong><br><br>Gene expression count data formatted for differential expression analysis<br><br><strong>WisAsp_Expression_Sample_Table.csv</strong><br><br>Differential expression experimental design information formatted for differential expression analysis<br><br><strong>Dryad_Lind-Riehl_etal_MolEcol_2023_metadata.xlsx</strong><br><br>Metadata for WisAsp genomic and transcriptomic data files
description: # WisAsp genomic and transcriptomic data from: Genomic and transcriptomic
 analyses reveal polygenic architecture for ecologically-important
 functional traits in aspen (Populus tremuloides Michx.) *** This dataset
 includes input files containing phenotypic, genomic, and transcriptomic
 data from a common garden of Populus tremuloides genets. The data were
 used to perform genome-wide association (GWA) analyses in PLINK
 (single-locus GWA) and GEMMA (multilocus GWA) and differential expression
 analyses in DESeq2. ## Description of the data and file structure
 WisAsp\_Tree\_Trait\_BLUPs WisAsp\_Tree\_Trait\_BLUPs.txt Rank-transformed
 BLUPs (best linear unbiased predictors) of ecologically important tree
 traits, formatted for GWAS analyses using PLINK and GEMMA; The first two
 columns are sample sequence identifiers followed by columns of BLUP values
 (one column for each trait); see the metadata file for more information on
 the traits WisAsp\_MAF005 bed file WisAsp\_MAF005.bed WisAsp bed file for
 genome-wide association analyses (single-locus, multi-trait, and
 multilocus) using PLINK and GEMMA WisAsp\_MAF005 bim file
 WisAsp\_MAF005.bim WisAsp bim file for genome-wide association analyses
 (single-locus, multi-trait, and multilocus) using PLINK and GEMMA
 WisAsp\_MAF005 fam file WisAsp\_MAF005.fam WisAsp bim file for genome-wide
 association analyses (single-locus, multi-trait, and multilocus) using
 PLINK and GEMMA gemma\_bslmm\_MAF005 script file gemma\_bslmm\_MAF005.sh
 Script to run GEMMA's BSLMM model on a high through-put computing
 system WisAsp\_Expression\_Counts input file
 WisAsp\_Expression\_Counts.csv Gene expression count data formatted for
 differential expression analysis using DESeq2
 WisAsp\_Expression\_Sample\_Table input reference file
 WisAsp\_Expression\_Sample\_Table.csv Differential expression experimental
 design information formatted for differential expression analysis using
 DESeq2 Metadata file Dryad\_Lind-Riehl\_etal\_MolEcol\_2023\_metadata.xlsx
 Metadata for WisAsp genomic and transcriptomic data files including
 specifics on how data were obtained; also includes a tab entitled
 "Tree trait file" that lists the trait column number assignment,
 category, names, abbreviations, and units ## Sharing/Access information
 Raw DNA sequence data for all samples included in the genome-wide
 association analyses are available through the European Nucleotide Archive
 under accession number PRJEB30919. Raw RNA sequence data for all samples
 included in the differential expression analysis are available through the
 National Center for Biotechnology Information’s Sequence Read Archive
 under accession number PRJNA851830.