DOI: 10.5061/dryad.vdncjsz4d
title: Data from: Inferring the strength of directional selection on armor plates in Lake Washington stickleback while accounting for migration and drift

description: Contemporary evolution allows us to investigate how natural selection
 drives phenotypic and genotypic evolution in nature. Recent advances in
 molecular genetics have identified causative genes underlying adaptive
 traits, enabling estimation of selection coefficients at these loci.
 However, estimating selection is challenging when populations receive
 migrants from genetically and phenotypically distinct populations. With
 genome-wide data now allowing estimation of migration rates and effective
 population sizes, these demographic parameters can be integrated into
 models for measuring selection. In Lake Washington, USA, the frequency of
 the completely plated morph of the threespine stickleback (Gasterosteus
 aculeatus) increased from 1957 to 2005, plausibly due to increased trout
 predation pressure caused by enhanced water clarity. Here, we estimated
 the selection coefficient at a major locus responsible for the plate morph
 using historical data, taking migration and genetic drift into
 consideration. Model-based predictions of present allele frequencies were
 tested with samples collected in 2022. Consistent with directional
 selection, the completely plated morphs and the underlying allele have
 increased since 2005, but to higher frequencies than predicted, suggesting
 a recent increase in selection. Thus, integrating molecular genetics,
 population genomics, and simulations enables the estimation of selection
 strength while considering migration and drift, to reveal directional
 selection in nature.
description: # Data from: Inferring the strength of directional selection on armor
 plates in Lake Washington stickleback while accounting for migration and
 drift In Lake Washington, USA, the frequency of the completely plated
 morph of the threespine stickleback (Gasterosteus aculeatus) increased
 from 1957 to 2005. Here, we sampled the stickleback in 2022 and
 investigated the temporal change in plate evolution together with
 previously published 2016 data. #### General information 1. Title of
 Dataset: Inferring the strength of directional selection on armor plates
 in Lake Washington stickleback while accounting for migration and drift 2.
 Author Information * Principal Investigator\ Name: Jun Kitano\
 Institution: National Institute of Genetics\ Address: Mishima, Shizuoka,
 Japan\ Email: [jkitano@nig.ac.jp](mailto:jkitano@nig.ac.jp) * Data
 curation\ Name: Yo Yamasaki\ Institution: National Institute of Genetics\
 Address: Mishima, Shizuoka, Japan\ Email:
 [yamasaki@nig.ac.jp](mailto:yamasaki@nig.ac.jp) 1. Date of data
 collection: 1957-2022 2. Geographic location of data collection: Lake
 Washington, WA, USA. 3. Information about funding sources that supported
 the collection of the data * NIG Summer Internship Program * JSPS Kakenhi
 (22H04983, 20J01503, 21H02542, and 22KK0105) * JST CREST (JPMJCR20S2) ##
 Description of the data and file structure There are four categories of
 datasets. Details of data collection methods are described in the
 manuscripts. #### 1. Morphological and genotype data collected from Lake
 Washington sticklebacks. **Files in 1_LakeWA_morphology_genotypes.zip** *
 1_1_1_LakeWA_platenumber_distribution_1957_2022.tsv\ Number of individuals
 for each plate number for each year. Data during 1957 to 1976 were
 obtained from published literatures. The detailed number of individuals
 with more than 12 plates in 1968/1969 is unknown. *
 1_1_2_LakeWA_platemorph_distribution_1957_2022.tsv Number of individuals
 for each plate morph for each year. Data during 1957 to 1976 were obtained
 from published literatures. * 1_2_lakeWA_Callele_freq.tsv\ Allele
 frequency changes of the complete Eda allele frequency from 2005 to 2022.
 Stn382 marker was used for genotyping. Data of 2005 and 2016 were from
 Kitano et al. 2008 and Archambeault et al. 2020 respectively. *
 1_3_1_LakeWA_platenumber_genotypes_SL_raw_2005_2016_2022.tsv\ Plate
 number, plate morph, standard length (SL), and genotypes at the Eda locus
 for each individual collected in 2005, 2016, and 2022. Loci other than
 Stn382 were not genotyped in 2005. *
 1_3_2_LakeWA_genotype_2005_2016_2022_trimmed.tsv\ Plate number and
 genotypes for each individual. This file is generated from the 1_3_1 file
 by removing individuals that showed NA in plate number or genotype in 2016
 and 2022. * 1_3_3_LakeWA_SL_2005_2016_2022_trimmed.tsv\ Plate number and
 SL for each individual. This file is generated from the 1_3_1 file by
 removing individuals that showed NA in plate number or SL. #### Note *
 Missing data is coded as NA. * Mean of columns is as follows; ``` - Year:
 Collected year - No_samples: Observed sample numbers - LPN: Left Plate
 Number - C_allele_freq: Allele frequency of Complete allele in locus
 Stn382 - ID: Sample identifier - Sex: Code of sex. F = Female, M = Male. -
 Plate_Morph: Code of classified plate morph. C = Complete, P = Partial, L
 = Low. - SL: Standard Length - Stn382: Genotypes of genetic marker Stn382.
 C = Complete, L = Low. - LP3621: Genotypes of genetic marker LP3621. C =
 Complete, L = Low. - Cnv770: Genotypes of genetic marker Cnv770. C =
 Complete, L = Low. - Stn381: Genotypes of genetic marker Stn381. C =
 Complete, L = Low. - LP13173: Genotypes of genetic marker LP13173. C =
 Complete, L = Low. - ln_SL: Natural logarithm transformed standard length
 ``` #### 2. Files used for Fastsimcoal2. **Files in 2_Fastsimcoal2.zip**
 Three tested models were included. Contents of three files in each model
 is as follows. * .obs: Observed allele frequency spectrum. * .tpl:
 Structure of demographic model. * .est: Explored parameter range. #### 3.
 Scripts used for SLiM forward simulations and ABC estimation **Files in
 3_FowardSimulation.zip** * 3_1_LW_monomorphic.slim\ In this script, we
 assumed that the complete Eda allele is fixed in the Puget Sound marine
 population and low Eda allele is fixed in the Kelsey Creek freshwater
 population. * 3_2_LW_polymorphic.slim\ In this script, we used observed
 the complete Eda allele frequency in both the Puget Sound marine
 population and the Kelsey Creek freshwater population. *
 3_3_LW_SLiM_iteration.ipynb\ This script was written for estimating
 selection coefficient and dominance coefficient by ABC and plotting the
 results. #### 4. Data of artificial light at night (ALAN) **Files in
 4_ALAN.zip** * 4_1_VIIRS_annual_reflectance_apr_sep.csv\ Light reflectance
 at night in each location collected in summer season (April to September)
 from 2016 to 2022. * 4_2_VIIRS_annual_reflectance_oct_mar.csv\ Light
 reflectance at night in each location collected in winter season (October
 to March) from 2016 to 2022. Note * Unit is "nW cm ⁻² sr ⁻¹"
 #### Sharing/Access information 1. Licenses/restrictions placed on the
 data: CC0 1.0 Universal (CC0 1.0) Public Domain 2. Links to publications
 that cite or use the data:\ Yamasaki, Y.Y., Yamaguchi, R., Nagano, A.J.,
 Chen, B.-J., Musto, N., Archambeault, S., Peichel, C.L., Schulien, J.A.,
 Code, T.J., Beauchamp, D.A., Kitano, J.\ Evolving Armor Plates in the Lake
 Washington Threespine Stickleback #### Links to other publicly accessible
 locations of the data: * [Data from: Adaptation via pleiotropy and
 linkage: association mapping reveals a complex genetic architecture within
 the stickleback Eda locus](https://doi.org/10.5061/dryad.05qfttf0j) *
 Original source of 2016 data. #### Data was derived from the following
 sources: * [Adaptation via pleiotropy and linkage: Association mapping
 reveals a complex genetic architecture within the stickleback Eda
 locus](https://doi.org/10.1002/evl3.175) * [Reverse Evolution of Armor
 Plates in the Threespine
 Stickleback](https://doi.org/10.1016/j.cub.2008.04.027) #### Code/Software
 Softwares and Versions * Fastsimcoal2: 2.6 * SLiM: 3.3