DOI: 10.5061/dryad.11p3v
title: Data from: Looking into the past – the reaction of three grouse species to climate change over the last million years using whole genome sequences

description: Tracking past population fluctuations can give insight into current levels
 of genetic variation present within species. Analysing population dynamics
 over larger time scales can be aligned to known climatic changes to
 determine the response of species to varying environments. Here, we
 applied the Pairwise Sequentially Markovian Coalescent (PSMC) model to
 infer past population dynamics of three widespread grouse species; black
 grouse, willow grouse and rock ptarmigan. This allowed the tracking of the
 effective population size (Ne) of all three species beyond 1 Mya,
 revealing that i) early Pleistocene cooling (~2.5 Mya) caused an increase
 in the willow grouse and rock ptarmigan populations, ii) the mid-Brunhes
 event (~430 kya) and following climatic oscillations decreased the Ne of
 willow grouse and rock ptarmigan, but increased the Ne of black grouse and
 iii) all three species reacted differently to the last glacial maximum
 (LGM) – black grouse increased prior to it, rock ptarmigan experienced a
 severe bottleneck and willow grouse was maintained at large population
 size. We postulate that the varying PSMC signal throughout the LGM depicts
 only the local history of the species. Nevertheless, the large population
 fluctuations in willow grouse and rock ptarmigan indicate that both
 species are opportunistic breeders while black grouse tracks the climatic
 changes more slowly and is maintained at lower Ne. Our results highlight
 the usefulness of the PSMC approach in investigating species’ reaction to
 climate change in the deep past, but also that caution should be taken in
 drawing general conclusions about the recent past.
description: Willow grouse autosomal
 consensus sequenceWillow grouse autosomal
 consensus sequence used as input for PSMC. The file was generated from a
 filtered bam file using the samtools mpileup, bcftools and vcfutils.pl
 (vcf2fq) pipeline (downgrading mapping quality for reads containing
 excessive mismatches (-C) to 50, minimum read depth (-d) set to 1/3 of the
 mean genome coverage (22) and maximum read depth (-D) set to twice the
 mean genome coverage (136)). All non-autosomal sites were
 discarded.L.lago.autosomes.fq.gzRock ptarmigan autosomal consensus sequenceRock ptarmigan autosomal consensus sequence used as input for PSMC. The file was generated from a filtered bam file using the samtools mpileup, bcftools and vcfutils.pl (vcf2fq) pipeline (downgrading mapping quality for reads containing excessive mismatches (-C) to 50, minimum read depth (-d) set to 1/3 of the mean genome coverage (33) and maximum read depth (-D) set to twice the mean genome coverage (202)). All non-autosomal sites were discarded.L.muta.autosomes.fq.gzBlack grouse autosome consensus sequenceBlack grouse autosome consensus sequence used as input for PSMC. The file was generated from a filtered bam file using the samtools mpileup, bcftools and vcfutils.pl (vcf2fq) pipeline (downgrading mapping quality for reads containing excessive mismatches (-C) to 50, minimum read depth (-d) set to 1/3 of the mean genome coverage (28) and maximum read depth (-D) set to twice the mean genome coverage (171)). All non-autosomal sites were discarded.T.tetrix.autosomes.fq.gzLastZ output filesLastZ output files for the alignment of each autosome of each grouse species and its respective chicken chromosome. Gg - chicken, Ll - willow grouse, Lm - rock ptarmigan and Tt - black grouse. Each LastZ (v1.03.54) run was applied with the following parameters: --ydrop=9400, --hspthresh=4500, --gappedthresh=3000 and –notransition. The 'nmatch' and 'nmismatch' columns (7 and 8 respectively in the output files) were used to calculate the mutation rate according to the formula: (sum of mismatches / [sum of matches + mismatches]) / 2x41.88; where 41.88 is the divergence time (million years) between chicken and the three grouse species.LastZ.zipWillow grouse autosomal heterozygous sitesA vcf file containing the autosomal heterozygous sites of the willow grouse individual. It was generated by the default samtools mpileup and bcftools pipeline. Filtering was performed by vcffilter (from the vcflib suite: https://github.com/ekg/vcflib) to keep only heterozygous sites with read depth between 22 and 136 and mapping quality above 20. Indels were removed by vcftools (v0.1.13), using the '--remove-indels' function.L.lago.auto.het.vcf.gzRock ptarmigan autosomal heterozygous sitesA vcf file containing the autosomal heterozygous sites of the rock ptarmigan individual. It was generated by the default samtools mpileup and bcftools pipeline. Filtering was performed by vcffilter (from the vcflib suite: https://github.com/ekg/vcflib) to keep only heterozygous sites with read depth between 33 and 202 and mapping quality above 20. Indels were removed by vcftools (v0.1.13), using the '--remove-indels' function.L.muta.auto.het.vcf.gzBlack grouse autosomal heterozygous sitesA vcf file containing the autosomal heterozygous sites of the black grouse individual. It was generated by the default samtools mpileup and bcftools pipeline. Filtering was performed by vcffilter (from the vcflib suite: https://github.com/ekg/vcflib) to keep only heterozygous sites with read depth between 28 and 171 and mapping quality above 20. Indels were removed by vcftools (v0.1.13), using the '--remove-indels' function.T.tetrix.auto.het.vcf.gz