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Dryad

Rooting out genetic structure of invasive wild pigs in Texas

Cite this dataset

Mangan, Anna et al. (2021). Rooting out genetic structure of invasive wild pigs in Texas [Dataset]. Dryad. https://doi.org/10.5061/dryad.cz8w9gj49

Abstract

Invasive wild pigs (Sus scrofa), also called feral swine or wild hogs, are recognized as among the most destructive invasive species in the world. Throughout the United States, invasive wild pigs have expanded rapidly over the past 30 years with populations now established in 38 states. Of the estimated 6.9 million wild pigs distributed throughout the United States, Texas supports approximately 40% of the population and similarly bears disproportionate ecological and economic costs. Genetic analyses are an effective tool for understanding invasion pathways and tracking dispersal of invasive species such as wild pigs and have been used recently in California and Florida, USA, which have similarly long-established populations and high densities of wild pigs. Our goals were to use molecular approaches to elucidate invasion and migration processes shaping wild pig populations throughout Texas, compare our results with patterns of genetic structure observed in California and Florida, and provide insights for effective management of this invasive species. We used a high-density single nucleotide polymorphism (SNP) array to evaluate population genetic structure. Genetic clusters of wild pigs throughout Texas demonstrate 2 distinct patterns: weakly resolved, spatially dispersed clusters and well-resolved, spatially localized clusters. The disparity in patterns of genetic structure suggests disparate processes are differentially shaping wild pig populations in various localities throughout the state. Our results differed from the patterns of genetic structure observed in California and Florida, which were characterized by localized genetic clusters. These differences suggest distinct biological and perhaps anthropogenic processes are shaping genetic structure in Texas. Further, these disparities demonstrate the need for location-specific management strategies for controlling wild pig populations and mitigating associated ecological and economic costs.

Methods

We obtained a variety of sample types (i.e., hair, pinna, and kidney) collected across 101 Texas counties from euthanized wild pigs that were sampled ancillary to population reduction and damage mitigation conducted by the United States Department of Agriculture (USDA) Animal and Plant Health Inspection Service (APHIS) Wildlife Services (WS) Feral Swine Damage Management Program between May 2012 and March 2019. We submitted samples to the National Feral Swine Genetic Archive (USDA APHIS WS National Wildlife Research Center) for analysis along with corresponding metadata, which included sex, age class, date of collection, and collection location (county and spatial coordinates rounded to the hundredth of a degree to protect the anonymity of private landowners while providing spatial accuracy within ~1.1 km). Given that genetic samples were collected secondarily to legally authorized control of wild pigs, sample collection was exempted from Institutional Animal Care and Use Committee review.

We extracted genomic DNA with a commerically available magnetic bead recovery kit (MagMax, Thermo Fisher Scientific, Waltham, MA, USA) using the MagMax Processor (Applied Biosystems, Waltham, MA, USA). We then genotyped samples using the GeneSeek Genomic Profiler for Porcine HD (GeneSeek, a Neogen Corporation, Lincoln, NE, USA; Illumina, San Diego, CA, USA), a commerically available genotyping array with 62,128 biallelic, autosomal single nucleotide polymorphism (SNP) mapped to the SScofa 11.1 genome assembly (Warr et al. 2019). We used SNP & Variation Suite version 8.8.3 (Golden Helix, Bozeman, MT, USA) to implement standard quality control measures for SNP data. Specifically, we pruned loci with low call rates (<95%) and minor allele frequencies (MAF) <0.05 (11,800 loci pruned), then removed individuals with low genotype call rates (<95%; 25 samples pruned) and finally, evaluated linkage disequilibrium (LD) among markers and pruned closely linked loci (r2 > 50%; window size = 50, window increment = 5) within chromosomes (20,505 loci pruned).