DOI: 10.5061/dryad.83f17
title: Data from: Genomic clustering of adaptive loci during parallel evolution of an Australian wildflower

description: The buildup of the phenotypic differences that distinguish species has
 long intrigued biologists. These differences are often inherited as stable
 polymorphisms that allow the co-segregation of adaptive variation within
 species, and facilitate the differentiation of complex phenotypes between
 species. It has been suggested that the clustering of adaptive loci could
 facilitate this process but evidence is still scarce. Here we used QTL
 analysis to study the genetic basis of phenotypic differentiation between
 coastal populations of the Australian wildflower Senecio lautus. We found
 that a genomic region consistently governs variation in several of the
 traits that distinguish these contrasting forms. Additionally, some of the
 taxon specific traits controlled by this QTL cluster have evolved
 repeatedly during the adaptation to the same habitats, suggesting that it
 could mediate divergence between locally adapted forms. This cluster
 contains footprints of divergent natural selection across the range of S.
 lautus, which suggests that it could have been instrumental for the rapid
 diversification of this species.
description: Genotype calls and
 genetic divergence from bulk segregant analysis of
 survivorship.We show results of the
 analysis of Bulk Segregant Analysis (BSA) of survivorship in reciprocal
 transplants between sand dune and rocky headland environments at Lennox
 Head (NSW, Australia) as performed with the Popoolation2 software. RADseq
 genotypes were mapped the a genome draft. For each SNP (defined by the
 position along the genomic contig where it was mapped) and genomic
 comparison between two pools of survivors from contrasting environments we
 show the identity and read counts for the major allele (maa) in the two
 populations (i.e. pop1 is the pool of sand dune survivors and pop2 is the
 pool of headland survivors). We also show the value of Fst, as calculated
 by Popoolation2, as well as the p-value of a fisher exact test of allelic
 differentiation (FET). Finally, in the last column we show if the SNPs had
 outlier Fst values (i.e. upper 5% tail of the distribution) and presented
 significantly different allelic frequencies in the FET (Bonferroni
 corrected p-value lower than 5%). Survivors from each environment where
 included in three different pools which were sequenced individually.
 Therefore we had three different comparisons between pools of survivors
 (i.e. F8-A-S-Dune_vs_F8-A-S-Headland, F8-B-S-Dune_vs_F8-B-S-Headland, and
 F8-C-S-Dune_vs_F8-C-S-Headland).Fst_BSA.txtGenotype calls and genetic divergence between parapatric populations.We show results of the analysis of differentiation between parapatric pairs of parapatric populations as performed with the Popoolation2 software. RADseq genotypes were mapped the a genome draft. For each SNP (defined by the position along the genomic contig where it was mapped) and genomic comparison between two parapatric populations we show the identity and read counts for the major allele (maa) in the two populations (ie.. pop1 is the dune population and pop2 is the headland population). We also show the value of Fst, as calculated by Popoolation2, as well as the p-value of a fisher exact test of allelic differentiation (FET). Finally, in the last column we show if the SNPs had outlier Fst values (i.e. upper 5% tail of the distribution) and presented significantly different allelic frequencies in the FET (Bonferroni corrected p-value lower than 5%).Fst_Parapatric.txt