DOI: 10.5061/dryad.0k6djhb6t
title: Evolution is more repeatable in the introduction than range expansion phase of colonization

description: How repeatable is evolution at genomic and phenotypic scales? We studied
 the repeatability of evolution during 8 generations of colonization using
 replicated microcosm experiments with the red flour beetle, Tribolium
 castaneum. Based on the patterns of shared allele frequency changes that
 occurred in populations from the same generation or experimental location,
 we found adaptive evolution to be more repeatable in the introduction and
 establishment phases of colonization than in the spread phase, when
 populations expand their range. Lastly, by studying changes in allele
 frequencies at conserved loci, we found evidence for the theoretical
 prediction that range expansion reduces the efficiency of selection to
 purge deleterious alleles. Overall, our results increase our understanding
 of adaptive evolution during colonization, demonstrating that evolution
 can be highly repeatable, while also showing that stochasticity still
 plays an important role.
description: # Evolution is more repeatable in the introduction than range expansion
 phase of colonization Code
 and data associated with analysis and figures. ## Sharing/Access
 information The full list of NCBI Sequence Read Archive accessions can be
 found at ##
 Code/Software Figures were generated with R, scripts split up by
 figure/analysis type. ### Details by file #### Data * BayPass_manual.pdf
 Baypass Software Manual (Version 2.1). Includes complete description of
 output files and the variables therein starting on page 21. * Z.csv * Key
 relating sequence library names to treatments. Columns are sample prefix
 and dummy variables to indicate which treatment each sample was from
 (founder, core, edge, shuffled). * baypass_r0.98_d3_L3_M30_q0.99_a35.txt,
 tribolium.covariates, tribolium.poolsize * Input files required to run
 Baypass and generate outlier loci. See BayPass_manual.pdf for more details
 about file formats. * aux_model_summary_yij_pij.out,
 aux_model_summary_betai.out, core_model_mat_omega.out * Unmodified output
 files generated by Baypass required or downstream analyses. See
 BayPass_manual.pdf for more details about file formats. *
 suppmat_outlier_df.csv * Merged information for all outlier loci including
 genome position and Bayes factors. The first columns
 (COVARIABLE,MRK,M_Beta,SD_Beta,M_Delta,BF.dB) are generated by Baypass
 (see page 23 of the BayPass_manual.pdf for description of the
 (outprefix_)summary_pij.out file format). The subsequent columns are: *
 treatment - which treatment (founder, core, edge, shuffled) the outlier
 locus the outlier was found in. * chrom - The chromosome name for the
 outlier locus * pos - The zero-indexed position of the outlier locus *
 pos2 - The one-indexed position of the outlier locus * ref_alt - The
 reference and alternate nucleotide found at the locus * freq - The
 reference allele frequency at the locus * chrom_num - Simplified
 chromosome name for the outlier locus used for plotting The following
 columns following the VCF format, some of which are redundant with the
 previous columns but were kept as a sanity check after merging several
 data frames. * CHROM - Identical to chrom * POS - Identical to pos * ID -
 Unique identifier used for filtering consisting of values from chrom, pos,
 and ref_alt * REF - The reference nucleotide found at the locus * ALT -
 The alternate nucleotide found at the locus * QUAL - Unused column
 mandatory for VCF format and kept as "." following conventions
 for the format. * FILTER - Unused column mandatory for VCF format and kept
 as "." following conventions for the format. * INFO - Additional
 information about the locus. In this case output from the Variant Effect
 Predictor (VEP) software indicting what functional part of the genome the
 locus fell into (if any). * core_freq_PCA.csv * Principal components of
 allele frequencies * GO_summary.txt * Final GO output containing p values
 averaged across genes and treatments that were discovered in. *
 go_shuffled.txt, go_founder.txt, go_edge.txt, go_core.txt * Genes
 identified with outliers used as input for GO analyses *
 go_shuffled_out.txt, go_founder_out.txt, go_edge_out.txt, go_core_out.txt
 * Output files for GO analyses #### software * fais_baypass.py * Script
 for making input for Baypass from bam files * make_files.sh * Steps for
 running Baypass * helper_functions.R * functions and file loading used in
 other scripts * go.R * Steps for selecting genes for GO analysis *
 TABLE2_allsites_catogries.R * Steps for identifying where loci of interest
 fall with respect to genome content. * get_conserved_pij.py * Helper
 script to filter for conserved loci. * FIGURE1_pca_viz.R * Steps to create
 PCA figure. * FIGURE2_baypass_BFmc.R * Steps to create outlier figure. *
 cons_pipeline.sh * Steps to indentify conserved loci. * run_mummer.sh *
 Script to run mummer * FIGURE5_conserved_sites.R * Steps to create
 distribution of allele frequencies at conserved loci.