DOI: 10.5061/dryad.fqz612k1r
title: Data from: Continuous variation in the shell colour of the snail <em>Cepaea nemoralis</em> is associated with the colour locus of the supergene

description: While the shell of the land snail Cepaea nemoralis is typically classed as
 yellow, pink or brown, the reality is that colour variation is
 continuously distributed. To further understand the origin of the
 continuous variation we used crosses of C. nemoralis to compare
 quantitative measures of the colour with the inferred genotype of the
 underlying supergene locus. We also used a recently developed linkage map
 to find quantitative trait loci (QTL) that may influence colour. The
 results show that the colour locus of the supergene – at around 31.385 cM
 on linkage group 11 – is involved in determining the quantitative
 chromatic differences that are perceptible to human vision. We also found
 some evidence that variation within colour classes may be due to allelic
 variation at or around the supergene. There are likely other unlinked loci
 involved in determining colour within classes, but confirmation will
 require greater statistical power. Although not investigated here,
 environmental factors, including diet, may also impact upon variation
 within colour types.
description: <em>Shell reflectance measures:</em>
 The shell ground colour of the two parents and 73 offspring from
 cross C451 x C452, and the parents and 32 offspring from cross C102 x C103
 was measured using an Ocean Optics spectrometer (model USB2000+UV-VIS-ES),
 with a Xenon light source (DT- MINI-2-GS UV-VIS-NIR), in the range of
 300-700 nm. To establish the baseline light spectrum standard, a WS-1
 diffuse white reflectance was used, with total darkness used to establish
 the standard for the dark spectrum (Taylor et al. 2016). The probe was
 held at a 45° incidence angle, about 2 mm from the shell (Davison et al.
 2019), using the underside of the shell, because there is nearly always an
 unbanded region and it is usually least damaged. Ocean Optics SpectraSuite
 2.0.162 was used to collect the data, with an integration time of 750
 msec, a boscar width of 5, and an average of 10 scans. To account for
 experimental error and slight spatial differences in shell colour, the
 reflectance of each shell was measured six times, randomising the order,
 with the software light calibration updated every third
 measurement. Following collection, the unprocessed reflectance spectra
 data were binned and smoothed into 5 nm categories using Pavo version
 2.7.0 (Maia et al. 2013; Maia 2019).  Reflectance
 spectra were then plotted, deriving the 95% CI for the means of each
 group. Subsequent analyses were performed using R version 4.0.5 (31 March
 2021), following the method of Delhey et al. (2015), and the same as
 previously (Davison et al., 2019). In brief, in order to estimate
 variation in shell colours, a psychophysical framework of avian colour
 vision developed by Delhey et al. (2015) and Vorobyev et al. (Vorobyev
 & Osorio, 1998; Vorobyev et al., 1998) was used to assess whether
 chromatic differences between reflectance spectra exceed a discrimination
 threshold, or “just noticeable difference” (JND), which can be perceived
 by a receiver, such as an avian predator. As previously, to analyze
 chromatic variation, the quantum catches for each cone type were converted
 into three chromatic coordinates (x, y, and z), where Euclidean distances
 between points reflect perceptual differences. Then, to identify the main
 axes of chromatic variation, we carried out a principal components
 analysis (PCA) on the chromatic coordinates (x, y, and z), using a
 covariance matrix rather than a correlation matrix because it preserves
 the perceptual distances (JNDs) (Delhey et al., 2015). The methods of
 Delhey were also used to assess achromatic variation, “brightness” or
 luminance variation, by computing achromatic contrast between each
 reflectance spectrum and a reference, corresponding to a dark spectrum,
 and using the same noise-to-signal ratio. Two-sample t-tests were
 subsequently used to compare the means of different sample sets (e.g.,
 pink/yellow, or pink1/pink2). <em>Genotyping
 data:</em> A ~10x depth whole genome sequence was
 generated using Illumina sequencing of the parents and offspring (Johansen
 et al. 2023), here we reused the same data but for a different purpose.
 Previously, FASTP v0.23.2 software was used in pre-processing of fastq
 files, specifically to check the quality, and for adapter trimming and
 quality filtering of the reads. Then, fastq files were aligned to the
 <em>C. nemoralis</em> genome using the Burrows-Wheeler
 Alignment method (Li and Durbin 2009) in bwa v0.7.17-r1188, using default
 settings and marking low-quality alignments (-M). Samtools v1.11 was used
 to sort and compress the sam files to bam files, then bcftools v1.10
 (Danecek et al. 2011) was used to call variants, outputting a variant call
 format (vcf) file for all individuals that were in the cross. To identify
 loci that were heterozygous in the yellow parent C452
 (<em>C<sup>Y3</sup>C<sup>Y4</sup></em>), we derived a vcf file for tig00045252, a contig that is perfectly associated with the colour locus in that cross (Johansen et al. 2023). Then, we identified all single nucleotide polymorphisms (SNPs) on tig00045252, only retaining those SNPs that were heterozygous in the yellow parent C452 and homozygous in the pink parent C451. By inspecting the offspring genotypes, we were able to infer whether individuals were either pink1/pink2 (<em>C<sup>P1</sup>C<sup>Y3</sup></em>^^ / <em>C<sup>P1</sup>C<sup>Y4</sup></em>), or yellow1/yellow2 (<em>C<sup>Y2</sup>C<sup>Y3</sup></em> / <em>C<sup>Y2</sup>C<sup>Y4</sup></em>).
description: # Data from: Continuous variation in the shell colour of the snail *Cepaea
 nemoralis* is associated with the colour locus of the supergene
 [https://doi.org/10.5061/dryad.fqz612k1r](https://doi.org/10.5061/dryad.fqz612k1r) The files presented here are the raw data from the spectrophotometry and the SNPs used to infer offspring genotype  ## Description of the data and file structure Table_S2.csv shows the phenotype and genotype of snails in the C451 x C452 cross, using SNPs on tig00045252 to infer four types of offspring phenotype/genotype, pink1/pink2 (*CP1CY3* / *CP1CY4*), or yellow1/yellow2 (*CY2CY3* / *CY2CY4*). The position and genotype of each allele is shown. Table_S3.csv shows the raw and processed reflectance data for samples used in this study. Snail ID is the same as in Table_S2.csv. Variables are the same as those first defined in Davison et al 2019 ([https://doi.org/10.1038/s41437-019-0189-z](https://doi.org/10.1038/s41437-019-0189-z)). ## Sharing/Access information Further information on the crosses and resources used are available in the following articles: [Davison et al 2024](https://bmcgenomics.biomedcentral.com/articles/10.1186/s12864-024-10505-w), [Johansen et al 2023](https://www.nature.com/articles/s41437-023-00648-z), [Ramos-Gonzalez et al 2019](https://www.nature.com/articles/s41437-019-0190-6), and [Richards et al 2013](https://onlinelibrary.wiley.com/doi/10.1111/mec.12262).