Nunatak colonization by flightless beetles
Data files
Jul 14, 2026 version files 154.14 MB
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adapter_sequence.fasta
539 B
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ak_dem_30s.asc
59.82 MB
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consensus_tree.sh
1.02 KB
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Figure1_map.R
1.01 KB
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filteredsnps.p.fst_summary.tsv
1.21 KB
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filteredsnps.p.treemix.gz
31.35 KB
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filteredsnps.vcf
11.08 MB
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fst_heatmap_script.R
766 B
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lituyae_mtDNA.arp
9 KB
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lituyae_mtDNA.nex
9.50 KB
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lituyae_sNMF.R
4.71 KB
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LituyaePopulations.txt
2.39 KB
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migration_edges.sh
948 B
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mtdna_fst.csv
613 B
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populations.snps.vcf
83.16 MB
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populations.sumstats_summary.tsv
5.23 KB
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read_demultiplexing.sh
699 B
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read_mapping.sh
633 B
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README.md
4.25 KB
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shapefile.txt
371 B
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SNPfiltR_pipeline.R
1.63 KB
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Treemix_AIC_scores.R
282 B
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TreeMix_bootstrapping_script.py
2.42 KB
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trimmomatic.sh
569 B
Abstract
The process of recolonizing alpine habitats following ice retreat remains poorly understood. We examined the dispersal of a flightless ground beetle, Nebria lituyae, into and between nunatak habitats of the Juneau Icefield using genetic data. Eleven populations were sampled, for a total of 161 individuals. We measured genetic diversity at a mitochondrial gene (COI) and in the nuclear genome using genotype-by-sequencing (GBS) to identify 2931 single nucleotide variants (SNPs). We measured genomic diversity and performed analyses to determine population structure and the pattern of evolutionary divergence. We infer that most nunatak populations were colonized by a single external population, given their genetic similarity and relative divergence; genetic diversity was generally preserved in nuclear genomes, with a stronger reduction in mitochondrial diversity. However, two nunatak sites have many unique alleles, suggesting independent colonization from distinct sources. We find evidence of very recent migration to one of these nunatak populations, suggesting a dynamic process of movement through time.
Dataset DOI: 10.5061/dryad.5hqbzkhmn
This readme file contains a catalog, annotated with descriptions, of all data and scripts utilized in our study.
All raw data files can be opened and viewed with a standard text editor.
Data
1. Geographical Data
- ak_dem_30s.asc : elevation raster for the Juneau Icefields
- shapefile.txt : Tabular text file listing populations and their geographical coordinates
2. Mitochondrial Data
- mtdna_fst.csv : output of pairwise FST statistics produced on mitochondrial COI sequence data, for use in drawing a heatmap. Populations are labeled with the following site names: WhitePass, Camp18, Camp17, Camp10, IvyRdg, SundayPt, MtRob, JuncturePk, TakuSW, Atlin, and CraterLk
- lituyae_mtDNA.nex : PopArt input file with mitochondrial COI sequence data, haplotype frequencies and geographical data
- lituyae_mtDNA.arp : Arlequin input file with mitochondrial COI sequence data and haplotype frequencies
3. Nuclear GBS Data
- populations.snps.vcf : Raw vcf output of variant calling pipeline Stacks
- filteredsnps.vcf : Output of SNPfiltR, includes all steps. Used to produce diversity and divergence statistics, admixture anlaysis, and Treemix trees
- filteredsnps.p.treemix.gz: treemix input file, converted from the filteredsnps.vcf file
- populations.sumstats_summary.tsv : summary statistics on all sites, including diversity with standard error. See statistics for all sites
- filteredsnps.p.fst_summary.tsv : pairwise Fst statistics produced on filtered SNP data, for use in drawing a heatmap. Populations are labeled with the following site names: Camp10, Camp17, JuncturePk, TakuSW, MtRob, WhitePass, Atlin, CraterLk, IvyRdg, SundayPt, and Camp18
- LituyaePopulations.txt : the population map file for use in read mapping
Scripts
1. Read and SNP Processing
- trimmomatic.sh : trims raw reads of fastq files using Trimmomatic-0.36, removing Illumina adapters as specified in the file adapter_sequence.fasta
- adapter_sequence.fasta: Illumina adapter file for use in the trimmomatic.sh script
- read_demultiplexing.sh : runs the process_radtags component of the Stacks pipeline on the sequencer output file, then produces a compiled quality control report on the demultiplexed sample files with fastqc and multiqc
- read_mapping.sh: runs the denovo_map.pl stacks command, completing the stacks pipeline. Run on the sample .fq produced after trimming; uses the LituyaePopulations mapping file. Outputs a single vcf
- SNPfiltR_pipeline.R : run on the denovo_map.pl output file, populations.snps.vcf in R; outputs filtered_snps.vcf after a variety of filtering steps with accompanying visualizations. Omit the minor allele frequency filtering step (maf) to produce the input vcf for GADMA divergence timing
2. Population Structure and Demographic History
- consensus_tree.sh: performs bootstrap resampling on the filteredsnps.vcf file, then uses Stacks to convert bootstraps into .treemix files; these steps are contained in the TreeMix_bootstrapping_scipt.py. Treemix is run on these input files, and the resulting trees are converted to Newick tree format and a consensus tree produced using SumTrees; outputs consensus_tree.nwk
- TreeMix_bootstrapping_script.py : Produces resampled .treemix files from a .vcf file, used in the consensus_tree.sh script
- migration_edges.sh: performs runs of treemix with different numbers of migration edges to produce log-likelihood scores for these models) - not necessary to run, since pre-calculated values are present in the Treemix_AIC_scores.R script
- Treemix_AIC_scores.R: visualization of relative AIC scores by number of migration edges
- lituyae_sNMF.R: admixture analysis, takes filteredsnps.vcf as input; can customize value of K1 to visualize lower clustering levels, with consistent colors for those visualizations also included
3. Figure plotting
- Figure1_map.R: R script to generate google map of sample sites
- fst_heatmap_script.R: R script to generate heat maps for GBS and mitochondrial measurements of FST
