DOI: 10.5061/dryad.ts351
title: Data from: Unique evolutionary trajectories in repeated adaptation to hydrogen sulphide-toxic habitats of a neotropical fish (Poecilia mexicana)

description: Replicated ecological gradients are prime systems to study processes of
 molecular evolution underlying ecological divergence. Here, we
 investigated the repeated adaptation of the neotropical fish Poecilia
 mexicana to habitats containing toxic hydrogen sulphide (H2S) and compared
 two population pairs of sulphide-adapted and ancestral fish by sequencing
 population pools of &gt;200 individuals (Pool-Seq). We inferred the
 evolutionary processes shaping divergence and tested the hypothesis of
 increase of parallelism from SNPs to molecular pathways. Coalescence
 analyses showed that the divergence occurred in the face of substantial
 bidirectional gene flow. Population divergence involved many short, widely
 dispersed regions across the genome. Analyses of allele frequency spectra
 suggest that differentiation at most loci was driven by divergent
 selection, followed by a selection-mediated reduction of gene flow.
 Reconstructing allelic state changes suggested that selection acted mainly
 upon de novo mutations in the sulphide-adapted populations. Using a
 corrected Jaccard index to quantify parallel evolution, we found a
 negligible proportion of statistically significant parallel evolution of
 Jcorr = 0.0032 at the level of SNPs, divergent genome regions (Jcorr =
 0.0061) and genes therein (Jcorr = 0.0091). At the level of metabolic
 pathways, the overlap was Jcorr = 0.2545, indicating increasing
 parallelism with increasing level of biological integration. The majority
 of pathways contained positively selected genes in both sulphide
 populations. Hence, adaptation to sulphidic habitats necessitated
 adjustments throughout the genome. The largely unique evolutionary
 trajectories may be explained by a high proportion of de novo mutations
 driving the divergence. Our findings favour Gould's view that
 evolution is often the unrepeatable result of stochastic events with
 highly contingent effects.
description: SNP FST
 fileThis is the pairwise fst
 output for individual snps. The non-informative sites have been
 suppressed, so all the rows are the SNPs that meet the coverage criteria.
 the columns are: col1: scaffold number col2: SNP position on scaffold
 col3: number of snps in window (because the window size was set to 1 to
 get individual SNP estimates, all values should be 1) col4: fraction of
 the window covered (more relevant for sliding window analyses) col5: mean
 coverage at SNP over all four populations col6: pairwise Fst for
 Tac-C:Tac-S col7: pairwise Fst for Tac-C:Puy-C col8: pairwise Fst for
 Tac-C:Puy-S col9: pairwise Fst for Tac-S:Puy-C col10: pairwise Fst for
 Tac-S:Puy-S col11: pairwise Fst for Puy-C:Puy-S population codes: 1=Tac-C,
 2=Tac-S, 3=Puy-C, 4=Puy-S Note that the Fst values that are 0.000000000
 are not polymorphic SNPs for a given pairwise comparison. For example, snp
 'NW_006799939.1 19911' has an Fst of 0.00000000 in the
 Tac-C:Tac-S comparison because it is not polymorphic between Tac-C and
 Tac-S. From the sync file: NW_006799939.1 19911 A 21:0:0:0:0:0
 21:0:0:0:0:0 39:0:0:2:0:0 37:0:0:5:0:0 you can see that Tac-C and Tac-S
 are fixed for the A allele (21 counts in each). The only reason it is
 included as a SNP in the .fst file is because it is polymorphic in the
 Puy-C & Puy-S populations (and polmorhic in the comparison across Tac
 & Puy).Tac-C_Tac-S_Puy-C_Puy-S.fstFisher's exact test dataThis is the fisher's exact test output for each SNP, in each pairwise comparison. The same SNP definition ws used as for the .fst output, so these are the FET results for the same snps included in the Fst output. The structure of the file is the same as for Tac-C_Tac-S_Puy-C_Puy-S.fst. Instead of Fst values, the numbers are -log10 P-values.Tac-C_Tac-S_Puy-C_Puy-S.fet1kb window FSTThis file contains the output of the 1000bp sliding window Fst analysis. Structure of the output file is similar to Tac-C_Tac-S_Puy-C_Puy-S.fst: col1: reference contig (chromosome) col2: mean position of the sliding window col3: number of SNPs found in the window (not considering sites with a deletion) col4: fraction of the window which has a sufficient coverage (min. coverage &lt;= cov &lt;= max. coverage) in every population; col5: average minimum coverage in all populations col6: 1:2 the pairwise Fst for population 1 and 2 col7: 1:3 the pairwise Fst for population 1 and 3 ....Tac-C_Tac-S_Puy-C_Puy-S.1000.fstPuy-C Tajima's DTajima's D output for 1000bp windows for Puy-C. There is no option in the script to suppress the non-informative windows, so there are lots of windows with "na" that fail the coverage criteria so no calculation is made.Puy-C.DPuy-S Tajima's DTajima's D output for 1000bp windows for Puy-S. There is no option in the script to suppress the non-informative windows, so there are lots of windows with "na" that fail the coverage criteria so no calculation is made.Puy-S.DTac-C Tajima's DTajima's D output for 1000bp windows for Tac-C. There is no option in the script to suppress the non-informative windows, so there are lots of windows with "na" that fail the coverage criteria so no calculation is made.Tac-C.DTac-S Tajima's DTajima's D output for 1000bp windows for Tac-S. There is no option in the script to suppress the non-informative windows, so there are lots of windows with "na" that fail the coverage criteria so no calculation is made.Tac-S.DinfilePuy68 for MigrateData input file for Migrate-N analysisinfilePuy68.txtinfileTac67 for Migrate-NData input file for Migrate-NinfileTac67.txtparmfile Migrate-NParameter file used for both population pairsparmfile.txtAllele frequency estimates from PoolSeq analysisPopoolation output file containing the read count data for polymorphic sites. The first column is the scaffold number (chr), the second the position on the scaffold (pos), the third is the base in the reference genome (rc), number of alleles (allele_count), allelic states (allele_states), number of deletions (deletion_sum), whether the snp is variable among populations or against the reference (snp_type), the major alleles in the populations in the order Tac-C, Tac-S, Puy-C, Puy-S (major_alleles(maa)), the same for minor alleles (minor_alleles(mia)), alleles frequency estimates of the major allele expressed as ratio of reads for the respective population (maa_1, maa_2, maa_3, maa_4), and the same for the minor alleles (mia_1, mia_2, mia_3, mia_4)Tac-C_Tac-S_Puy-C_Puy-S_rc