DOI: 10.5061/dryad.8931zcs50
title: Data from: Evaluating inbreeding and assessing the risk of outbreeding depression in genetic rescue of the endangered marsh fritillary (<em>Euphydryas aurinia</em>)

description: Restoring genetic diversity through assisted migration is increasingly
 recognized as a crucial strategy to counteract inbreeding depression and
 boost genetic variation in small and fragmented populations, yet concerns
 about outbreeding depression often hinder its application. This dataset
 contains whole-genome variant data generated to evaluate inbreeding
 patterns and inform assessments of outbreeding depression risk in the
 marsh fritillary (Euphydryas aurinia). It includes multiple SNP datasets
 representing successive stages of processing: raw variant calls, a
 quality-filtered dataset, a phased dataset for selection scans, an
 LD-pruned dataset suitable for population-structure analyses, and a
 dataset specifically filtered for runs-of-homozygosity (ROH) inference. We
 identify substantial inbreeding in the investigated populations (FROH
 approaching 40%), historical gene flow, recent divergence times between
 populations, and a low likelihood of local adaptation. Together, these
 results provide an example where genetic rescue could be undertaken
 successfully by transplanting individuals across populations with minimal
 outbreeding depression risks.
description: # Data from: Evaluating inbreeding and assessing the risk of outbreeding
 depression in genetic rescue of the endangered marsh fritillary
 (*Euphydryas aurinia*) Dataset DOI:
 [10.5061/dryad.8931zcs50](https://doi.org/10.5061/dryad.8931zcs50) ##
 Description of the data and file structure This dataset contains the
 processed genomic datasets, variant call files, sample metadata, and the
 curated reference genome used in the paper “Evaluating inbreeding and
 assessing the risk of outbreeding depression in genetic rescue using
 whole-genome sequence data” by Tengstedt et al. The study evaluates
 inbreeding patterns and informs assessments of outbreeding depression risk
 in the marsh fritillary (*Euphydryas aurinia*). All data derive from
 whole-genome resequencing of individuals sampled in Denmark under
 appropriate collection permits. The dataset is intended to enable full
 reproducibility of the analyses in the associated study. ### Files and
 variables **Curated reference genome** EupAur.fa: The final curated
 reference genome assembly (NCBI BioProject PRJNA1026358) used for read
 mapping and variant calling. **Raw SNP calls** Marsh_raw.vcf.gz: Variant
 calls produced from mapped Illumina reads using SAMtools/BCFtools. These
 files represent the unfiltered SNP dataset prior to quality control. Note
 that this file contains four Glanville fritillary individuals, which were
 only filtered out in the subsequent filtering steps. **Quality-filtered
 SNP dataset**
 Marsh_filtered.sansGlanville.minGQ30.minDP10.maxDP70.miss1.HWE14.vcf.gz: A
 VCF file containing variants retained after filtering on genotype quality,
 depth, missingness, ss, and Hardy-Weinberg equilibrium. This file is the
 primary dataset utilized for the various analyses described in our paper.
 **LD-pruned dataset**
 Marsh_filtered.sansGlanville.minGQ30.minDP10.maxDP70.miss1.HWE14.LD-pruned.recode.vcf.gz: A reduced SNP set generated through linkage disequilibrium pruning with PLINK. This file is suitable for population structure inference and comparative analyses requiring unlinked variants. **Phased dataset** Marsh_filtered.sansGlanville.minGQ30.minDP10.maxDP70.miss1.HWE14.phased.vcf.gz: A statistically phased version of the quality-filtered SNP dataset. This file is used for selection scans. **OH-filtered dataset** Marsh_filtered.sansGlanville.minGQ30.minDP10.maxDP70.miss1.HWE14.MappabilityMask.RepeatMask.ann.vcf.gz: A SNP dataset filtered specifically for detecting runs of homozygosity (ROH), with filtering parameters optimized to retain only the most reliable variant calls. **Sample metadata** popmap.txt: A tab-delimited file listing individual sample IDs and their corresponding population. ## Code/software The VCF files can be opened and analyzed using various bioinformatics tools and software; some of the most common include BCFtools and VCFtools.