DOI: 10.5061/dryad.8pk0p2nzm
title: Data from: Genomes of Galápagos mockingbirds reveal the impact of island size and past demography on inbreeding and genetic load in contemporary populations

description: Restricted range size brings about noteworthy genetic consequences that
 may affect the viability of a population and eventually its extinction.
 Particularly, the question if an increase in inbreeding can avert the
 accumulation of genetic load via purging is hotly debated in the
 conservation genetic field. Insular populations with limited range sizes
 represent an ideal setup for relating range size to these genetic factors.
 Leveraging a set of 8 differently sized populations of Galápagos
 mockingbirds (Mimus) we investigated how island size shaped effective
 population size (Ne), inbreeding, and genetic load. We assembled a genome
 of M. melanotis and genotyped 3 individuals per population by whole genome
 resequencing. Demographic inference showed that the Ne of most populations
 remained high after the colonisation of the archipelago 1 - 2 Mya. Ne
 decline in M. parvulus happened only 10 - 20 Kya, while the critically
 endangered M. trifasciatus showed a longer history of reduced Ne. Despite
 these historical fluctuations, the current island size determines Ne in a
 linear fashion. In contrast, significant inbreeding coefficients, derived
 from runs of homozygosity, were identified only in the 4 smallest
 populations. Index of additive genetic load suggested purging in M.
 parvulus, where the smallest populations showed the lowest load. By
 contrast, M. trifasciatus carried the highest genetic load, possibly due
 to a recent rapid bottleneck. Overall, our study demonstrates a complex
 effect of demography on inbreeding and genetic load, providing
 implications in conservation genetics in general and in a conservation
 project of M. trifasciatus in particular.
description: We extracted genomic DNA using the MasterPure DNA Purification
 Kit (Lucigen). PCR-free sequencing libraries were prepared by the
 Norwegian Sequencing Centre and sequenced on Illumina HiSeqX10 in a
 pair-end mode. We used Trimmomatic (v. 0.36, Bolger) to remove adapters
 and trim low-quality base pairs from raw reads. Quality-filtered reads of
 at least 120bp (minimum base quality Phred score of 15) were mapped onto
 our <em>M. melanotis</em> reference genome by BWA–mem (v.
 0.7.15) (Li & Durbin 2009). We removed duplicated reads by Picard
 (v. 2.8.1). Variant calling was done by GATK (v. 3.7) (McKenna et al.
 2010) with a series of stringent filtering steps to minimise the presence
 of false genotypes. Reliable biallelic SNPs were obtained following the
 GATK best practices for hard filtering as described in DePristo et al.
 (2011). We also excluded sites that either exceeded the average coverage
 depth per individual by more than two standard deviations, showed excess
 heterozygosity (p &lt;0.05 as determined by VCFTools (v. 0.1.16;
 Danecek et al. 2011), or had more than 25% missing data. We also excluded
 sites found within repetitive regions and, finally, invariant sites with
 low quality (QUAL &lt; 15). Such filtering resulted in a vcf file
 containing ~8 M bi-allelic SNPs
description: # Data from: Genomes of Galápagos mockingbirds reveal the impact of island
 size and past demography on inbreeding and genetic load in contemporary
 populations
 [https://doi.org/10.5061/dryad.8pk0p2nzm](https://doi.org/10.5061/dryad.8pk0p2nzm) ## Description of the data and file structure #### File: all_gala.vcf.gz **Description:** Variant calling format of SNPs of 24 samples of mockingbirds from Galapagos. This dataset contains genotypes of 24 individuals of mockingbirds from Galapagos. The data were generated as follows: We extracted genomic DNA using MasterPure DNA Purification Kit (Lucigen). PCR-free sequencing libraries were prepared by the Norwegian Sequencing Centre and sequenced on Illumina HiSeqX10 in a pair-end mode. We used Trimmomatic (v. 0.36, Bolger[ et al. 2014](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4103590/)) to remove adapters and trim low-quality base pairs from raw reads. Quality-filtered reads of at least 120bp (minimum base quality Phred score of 15) were mapped onto our *M. melanotis* reference genome by BWA – mem (v. 0.7.15) (Li & Durbin 2009). We removed duplicated reads by Picard (v. 2.8.1) ([Broad Institute 2018](https://github.com/broadinstitute/picard/issues/808#issuecomment-368812396)). Variant calling was done by GATK (v. 3.7) (McKenna et al. 2010) with a series of stringent filtering steps to minimise the presence of false genotypes. Reliable biallelic SNPs were obtained following the GATK best practices for hard filtering as described in DePristo et al. (2011). We also excluded sites that either exceeded the average coverage depth per individual by more than two standard deviations, showed excess heterozygosity (p &lt;0.05 as determined by VCFTools (v. 0.1.16; Danecek et al. 2011), or had more than 25% missing data. We also excluded sites found within repetitive regions and, finally, invariant sites with low quality (QUAL &lt; 15). Such filtering resulted in a vcf file containing ~8 M bi-allelic SNPs. VCF file contains following samples: | Individual\_code | Population\_code | Population | Species | | :--------------- | :--------------- | :------------------- | :-------------- | | 9-254 | C | Champion by Floreana | M. trifasciatus | | 9-256 | C | Champion by Floreana | M. trifasciatus | | 7-270 | C | Champion by Floreana | M. trifasciatus | | 3-MocD01 | D | Darwin | M. parvulus | | 4-MocD02 | D | Darwin | M. parvulus | | 1-D13 | D | Darwin | M. parvulus | | 10-272 | F | Gardner by Floreana | M. trifasciatus | | 11-276 | F | Gardner by Floreana | M. trifasciatus | | 12-280 | F | Gardner by Floreana | M. trifasciatus | | 5-364 | I | Isabela | M. parvulus | | 11-143370 | I | Isabela | M. parvulus | | 10-143380 | I | Isabela | M. parvulus | | 9-143182 | M | Marchena | M. parvulus | | 12-143192 | M | Marchena | M. parvulus | | 6-208 | M | Marchena | M. parvulus | | 1-MocP01 | P | Pinta | M. parvulus | | 3-P16 | P | Pinta | M. parvulus | | 2-MocP17 | P | Pinta | M. parvulus | | 7-MocX01 | S | Santa Cruz | M. parvulus | | 8-MocX05 | S | Santa Cruz | M. parvulus | | 4-140 | S | Santa Cruz | M. parvulus | | 5-MocW01 | W | Wolf | M. parvulus | | 6-MocW09 | W | Wolf | M. parvulus | | 2-W25 | W | Wolf | M. parvulus | ## Code/software You can view the data with bcftools. [https://samtools.github.io/bcftools/bcftools.html](https://samtools.github.io/bcftools/bcftools.html) The data were generated by this pipeline: [https://github.com/vlkofly/Fastq-to-vcf](https://github.com/vlkofly/Fastq-to-vcf) ## Access information Other publicly accessible locations of the data: * NA Data was derived from the following sources: * Sequences that were used to generate the genotypes are stored in Genebank NCBI under project PRJNA668877:  SRX9284599-SRX9284573