Alcaide_etal_PeerJ_MHC_classI_alignment

This alignment was used in the analysis of the paper in PeerJ by M. Alcaide, M. Liu and S. Edwards entitled "Major Histocompatibility Complex class I evolution in songbirds: universal primers, rapid evolution and base compositional shifts in exon 3". The alignment begins on the first position of the codon and was made according to methods described in the paper. Taxa without Genbank numbers are original data; Genbank nubmers for these sequences can be found on Genbank. Taxa with Genbank numbers were taken from Genbank

Kenyon et al_playback data set

Kenyon et al_playback data se

Kenyon et al_main data set

Kenyon et al_main data se

Greenish Warbler De Novo Assembly Draft

De Novo Assembly of a whole-genome sequencing library from one Phylloscopus trochiloides viridanus bird (SRA accession number: SRX473141). De Novo Assembly was carried out in the CLC genomic workbench and following the default parameters set by the developer

Greenish warbler sequences and SNPs mapped on zebra finch genome

Greenish warbler sequences mapped on zebra finch genome assembly (pink annotations). The physical location of SNP markers is also indicated. Grey annotations refer to the set of 81,034 SNPs with data in at least 80% of individuals (N=95 birds). Yellow annotations refer to the subset of 2,334 SNPs with no missing data and minimum coverage = 3 reads. Blue annotations refer to the 1,827 SNP markers used during the chromosome-by-chromosome introgression analysis. These assemblies can be inspected in the free version of the Geneious genomic workbench, which can be downloaded from http://www.geneious.com/download

metadata for Figure S1 (whole-genome PCA)

This file contains metadata for greenish warbler individuals used in the whole-genome PCA analysis (Figure S1). The R script in this package uses this information to color points in the PCA

scripts: converting GBS reads to genotypes

This text file contains scripts and notes for the steps used in converting raw Illumina GBS sequencing reads to individual genotypes (at both variant and invariant sites) across the genome. The resulting genotype files (in "012NA" format) were then used as input into R, for the rest of the analysis and production of figures

Greenish Warbler VCF files: invariant and SNPs

This folder contains 31 files in the VCF format. Each contains genotypic information for a single chromosome (or chromosome fragment) for all individuals in the two GBS (genotype by sequencing) plates in the study. The files have names corresponding to "GW_Lane5plusLiz.GWref.genotypes.allSites.chr*.infoSites.vcf"; the * represents the chromosome name. All sites, both variant and invariant, where there was a total of more than 10 sequencing reads among all individuals were included. The chromosomes refer to those in the Zebra Finch assembly (version 3.2.4; Warren et al. 2010). For details of how these VCF files were produced and how they were then used, see the associated paper (Irwin et al., in review, Molecular Ecology) and this file in this same Dryad package: "GW_islands_of_diff_processing_scripts.txt

metadata for the outgroup analysis

This file is required for conducting the 9-sample analysis using the R script provided in this package. The file provides the names of each individual, the location code, the "group" (used for coloring points in various plots) and "Fst_group" (used for defining groups in the Fst analysis), and the "plot_order" (not used in the present paper)

SiteStats and WindowStats R files

This folder contains files containing locus-based statistics ("SiteStats") and window-based statistics (WindowStats) for each chromosome. These files can be produced by the R script (in this package), and they can also be used by that script (whether the script saves and/or loads SiteStats and WindowStats files can be adjusted in that script using the setting for "calculate_or_load_stats" and the related settings below that). Producing these files can take days of processing time; I have included them here so you can produce most of the figures in the paper, by running the R script below the heading "GENOME-WIDE plots". That script will call the appropriate files (as long as you have designated a path/folder structure that matches the R script). Files are included for both the "45-sample" analysis and the "nine_taxa.one_per_taxon" analysis