Data from: Admixture mapping of quantitative traits in Populus hybrid zones: power and limitations

Uncovering the genetic architecture of species differences is of central importance for understanding the origin and maintenance of biological diversity. Admixture mapping can be used to identify the number and effect sizes of genes that contribute to the divergence of ecologically important traits, even in taxa that are not amenable to laboratory crosses due to their long generation time or other limitations. Here, we apply admixture mapping to naturally occurring hybrids between two ecologically divergent Populus species. We map quantitative trait loci (QTL) for eight leaf morphological traits using 77 mapped microsatellite markers from all 19 chromosomes of Populus. We apply multivariate linear regression analysis allowing the modeling of additive and non-additive gene action and identify several candidate genomic regions associated with leaf morphology using an information-theoretic approach. We perform simulation studies to assess the power and limitations of admixture mapping of quantitative traits in natural hybrid populations for a variety of genetic architectures and modes of gene action. Our results indicate that (1) admixture mapping has considerable power to identify the genetic architecture of species differences if sample sizes and marker densities are sufficiently high, (2) modeling of non-additive gene action can help to elucidate the discrepancy between genotype and phenotype sometimes seen in interspecific hybrids, and (3) the genetic architecture of leaf morphological traits in the studied Populus species involves complementary and overdominant gene action, providing the basis for rapid adaptation of these ecologically important forest trees.R code for single-locus and multivariate regression analyses used for "Admixture mapping in Populus"R code to obtain candidate QTL and parameter estimates. Runs with example input files 'linkage_Ita_f.edited', 'linkage_Ita_ss.edited', 'Marker.csv', and 'phenotypes_Ita.txt'.AdmixtureMapping.RMicrosatellite genotype data for all individuals from four Populus hybrid zonesGenotypic data are in 2 rows for each individual, in a slightly modified Structure input format. Columns: individual number; source population (Italy, Austria, Hungary, Spain); individual ID; species assignment (0, hybrid; 1, P. alba; 2, P. tremula); use population flag in Structure (0, no; 1, yes); followed by microsatellite fragment sizes for 77 loci (-9, missing data; 222, band absent for dominant markers).Genotypes.csvPhenotype measurements for all 22 traits and all individuals from four Populus hybrid zonesColumns: individual number; source population (Italy, Austria, Hungary, Spain); individual ID; species assignment (H, hybrid; A, P. alba; T, P. tremula); followed by phenotypes for all 22 phenotypic traits measured/calculated. Phenotype measurements represent averages over 5 leaves measured per tree.Phenotypes.csvResult of Structure run for Italy, using linkage model (Input file for R code; text file)Columns: individual number; individual ID; percent missing data; proportion of ancestry from cluster 1 (P. tremula); proportion of ancestry from cluster 2 (P. alba); followed by their 90% probability intervals.linkage_Ita_f.editedResult of Structure run for Italy, using linkage model, site-by-site output (Input file for R code; text file)Columns: individual number; locus number; followed by 4 columns for LSA estimates (probability that both alleles are from P. alba; probability that first allele is from P. alba, second from P. tremula; probability that first allele is from P. tremula, second from P. alba; probability that both alleles are from P. tremula).linkage_Ita_ss.editedInformation on microsatellite markers used (Input file for R code)Columns: locus number; abbreviated locus name used in this study; locus name published; chromosome; position on chromosome in bp; position in bp/200,000 as proxy for cM; marker type (dominant or co-dominant).Marker.csvPhenotype measurements for Italy, admixed individuals only, 8 mapping traits (Input file for R code)Rows give measurements for individuals in the same order as in Structure files; columns give 8 main phenotypic traits used for admixture mapping. Phenotype measurements represent averages over 5 leaves measured per tree.phenotypes_Ita.tx