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.

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.

SNPs.gz
SNPs used for generating linkage map (for QTL analysis) and estimating genomic relationship matrices

Pedigree.txt
Pedigree data for generating linkage map, required input for Lep-Map3
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

QTL.map.txt
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


Pheno.QTL.csv
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”.

Geno.QTL.csv
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


QTL_analysis.R
Rscript for QTL analysis and adjusting linkage group numbering and marker order to be consistent with the previous Littorina linkage map.

Pheno.txt
Phenotypic data used for variance partitioning. First column gives the individual ID

GRM_LG.zip
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.


Variance_partitioning.R
Rscript for variance partitioning across linkage groups.