DOI: 10.5061/dryad.zgmsbccb4
title: Data from: Genetic variation for adaptive traits is associated with polymorphic inversions in Littorina saxatilis

description: Chromosomal inversion polymorphisms, segments of chromosomes that are
 flipped in orientation and occur in reversed order in some individuals,
 have long been recognized to play an important role in local adaptation.
 They can reduce recombination in heterozygous individuals and thus help to
 maintain sets of locally adapted alleles. In a wide range of organisms,
 populations adapted to different habitats differ in frequency of inversion
 arrangements. However, getting a full understanding of the importance of
 inversions for adaptation requires confirmation of their influence on
 traits under divergent selection. Here, we studied a marine snail,
 Littorina saxatilis, that has evolved ecotypes adapted to wave exposure or
 crab predation. These two types occur in close proximity on different
 parts of the shore. Gene flow between them exists in contact zones.
 However, they exhibit strong phenotypic divergence in several traits under
 habitat-specific selection, including size, shape and behaviour. We used
 crosses between these ecotypes to identify genomic regions that explain
 variation in these traits by using QTL analysis and variance partitioning
 across linkage groups. We could show that previously detected inversion
 regions contribute to adaptive divergence. Some inversions influenced
 multiple traits suggesting that they contain sets of locally adaptive
 alleles. Our study also identified regions without known inversions that
 are important for phenotypic divergence. Thus, we provide a more complete
 overview of the importance of inversions in relation to the remaining
 genome.
description: Parental snails were
 collected on the Swedish West Coast at Ängklåvebukten (58.8697°,
 11.1197°), where both ecotypes occur in close proximity. Two virgin
 Crab-females were crossed with two Wave-males resulting in two
 F1-families. F1-families were crossed to produce the F2 generation which
 was genotyped and phenotyped. DNA was extracted from a small piece of foot and
 targeted re-sequencing was performed using a total of 25,000 (120 bp)
 enrichment probes. Phenotypes measured included weight, shell length, shell
 thickness (mean of three measurements per snail), relative thickness
 (thickness/shell length), size independent parameters describing shell
 shape and the aperture, shell colour, and boldness behaviour (Bold.Score =
 log of time until crawling out after disturbance, higher Bold.Score means
 an individual is less bold) that were previously found to differ between
 ecotypes.
description: <strong>SNPs.gz</strong><br> SNPs used for
 generating linkage map (for QTL analysis) and estimating genomic
 relationship matrices
 <strong>Pedigree.txt</strong><br> Pedigree data
 for generating linkage map, required input for Lep-Map3<br> First
 line is the family name, second individual name, third and fourth are the
 father and mother. Line 5 is the sex of each individual (1 male, 2 female,
 0 unknown). Last line is 0, not used
 <strong>QTL.map.txt</strong><br> Linkage map
 used for QTL analysis Row names correspond to markerIDs
 in “Geno.QTL.csv” 1.  column: contig; 2. column:
 position; 3. column: Marker name; 4. column: Linkage group of the newly
 generated map; 5. column: Linkage group in previous map (based on crossing
 Crab ecotype individuals); 6. column: Map position in the new
 map
 <strong> Pheno.QTL.csv</strong><br> Phenotypes
 for QTL analysis in the format for the Rpackage “qtl”
 The first column (“ind”) gives the individual ID, the last column
 (“id”) matches the phenotypic data to the genetic data in
 “Geno.QTL.csv”.
 <strong>Geno.QTL.csv</strong><br> Genotypic
 data used for QTL analysis in the format required for the Rpackage
 “qtl” First column: Individual id to match genotypic
 data with phenotypic data in a separate file (Pheno.QTL.csv); remaining
 columns: genotypes (phased data obtained from Lep-Map3); first row: marker
 IDs; second row gives the linkage group; third row: cM positions of
 markers 
 <strong>QTL_analysis.R</strong><br> Rscript for
 QTL analysis and adjusting linkage group numbering and marker order to be
 consistent with the previous <em>Littorina</em> linkage
 map. <strong>Pheno.txt</strong><br>
 Phenotypic data used for variance partitioning. First column gives the
 individual ID
 <strong>GRM_LG.zip</strong><br> Inverse of
 genomic relationship matrices in ASReml format based on marker of a focal
 linkage group X (Ginv_LGX.txt) or excluding markers of a focal linkage
 group (Ginv_LGXNOT.txt). GRM.txt: Genomic relationship
 matrix between individuals based on genetic markers of all linkage groups.
 Individual IDs are the same as in Pheno.txt
 GRM.inv.txt: Inverse of GRM.txt in ASReml format.
  <strong>Variance_partitioning.R</strong><br>
 Rscript for variance partitioning across linkage groups.