ORIGINAL ARTICLE Genetic Resources (2020), 1 (2), 29–41 DOI: 10.46265/genresj.BNHB8715 https://www.genresj.org ISSN: 2708-3764 Robust microsatellite markers for hybrid analysis between domesticated pigs and wild boar Donovan Anderson*,a, Yuki Negishi a, Rio Toma a, Junco Nagata b, Hidetoshi Tamate c and Shingo Kaneko a,d a Symbiotic Systems Science and Technology, Fukushima University, Fukushima City, Fukushima, Japan b Forestry and Forest Products Research Institute, Ibaraki, Tsukuba, Japan c Department of Biology, Yamagata University, Yamagata City, Yamagata, Japan d Institute of Environmental Radioactivity, Fukushima University, Fukushima City, Fukushima, Japan Abstract: Hybridization between wild boar (Sus scrofa) and their domestic relative, pigs, is a global issue and gene flow between these populations has been known to negatively impact biodiversity with increased aggression, litter sizes, and growth. However, establishing a cost-effective analysis for long-term monitoring of possible gene flow of wild pigs into wild boar populations is challenging due to common alleles at multiple loci and often it is difficult to distinguish boar specific lineages. Therefore, there is a need to select loci with lineage specific alleles for hybrid detection. To determine these loci, we calculated allele frequencies and polymorphism measurements from successfully amplified microsatellite loci with DNA extracted from domestic pigs and wild boar populations from the period prior to, and after, the evacuations and disasters in Fukushima, Japan, in 2011, which resulted in an uncontrolled release of domestic pigs. Thirty-two microsatellite loci showed pig putative alleles suggesting these selected loci can be useful genetic markers. Seventeen loci successfully distinguished pig and wild boar hybridization in Fukushima populations. Identified loci from this study provide a cost-efficient tool for genetic analysis and will provide a wealth of information on how an uncontrolled release of domestic livestock from natural or anthropogenic disasters may impact their wild relatives. Keywords: microsatellite, hybridization, alleles, pigs, polymorphism Citation: Anderson, D., Negishi, Y., Toma, R., Nagata, J., Tamate, H., Kaneko, S. (2020). Robust microsatellite markers for hybrid analysis between domesticated pigs and wild boar. Genetic Resources 1 (2), 29–41. doi: 10.46265/genresj.BNHB8715. © Copyright 2020 the Authors. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Introduction Hybridization between wild species and their do- mesticated relatives has been detected in multiple environments across the globe (Pierpaoli et al, 2003; Godinho et al, 2011; Goedbloed et al, 2013a). In- vasive species and hybridized individuals compete with native populations, and cause negative impacts to biodiversity (Rhymer and Simberloff, 1996; Randi, 2008; Harrison and Larson, 2014). Invasive pigs are known to successfully disperse in wild environments and cause considerable impact on the gene pool of native wild boar populations (Vernesi et al, 2003; Kout- sogiannouli et al, 2010; Goedbloed et al, 2013b). Multi- ple countries have implemented management programs to reduce wild boar population expansion (Waithman et al, 1999; Scandura et al, 2008; Saito et al, 2011), but hybrid individuals may have in- creased litter sizes, aggression, and growth rates (Goedbloed et al, 2013b; Dzialuk et al, 2018). Areas of suspected hybridization between invasive pigs and wild boar populations should be continuously moni- tored to understand the extent of introgression of pig genes in the wild boar gene pool. Microsatellite marker analysis is a well-established monitoring tool to evaluate possible introgression of invasive species and hybridization detection (Nijman et al, 2003; Randi, 2008; Uemura et al, 2018). The selection of reliable microsatellite markers by optimizing amplification protocols prior to monitoring a target population is of great importance because it has consequences for subsequent genotyping (Hoffman and Amos, 2005; Kolodziej et al, 2012). However, Received: 22.06.2020 Accepted: 30.11.2020 Published online: 29.12.2020 ∗Corresponding author: Donovan Anderson (s1871003@ipc.fukushima-u.ac.jp) https://www.genresj.org https://www.dx.doi.org/10.46265/genresj.BNHB8715 https://www.genresj.org https://www.dx.doi.org/10.46265/genresj.BNHB8715 mailto:s1871003@ipc.fukushima-u.ac.jp 30 Anderson et al Genetic Resources (2020), 1 (2), 29–41 genotyping hybrid individuals (e.g. crossed pig and boar) can be challenging due to common or shared alleles at multiple loci (Larson et al, 2005; Grossi et al, 2006; Choi et al, 2014) and it is necessary to select suitable loci with lineage specific alleles for hybridization detection. Validating appropriate microsatellite markers with possible hybridized wild boar and the pigs involved in the hybridization will provide the necessary genetic composition data to develop a cost-efficient monitoring tool to evaluate the introgression of pig genes to the wild boar gene pool. Such cost-efficient analyses have provided monitoring opportunities to estimate abundancy of hybrids (Qi et al, 2010; Matsumoto et al, 2019), population characteristics (Goedbloed et al, 2013a; Sharma et al, 2013) and local genetic structures (Tadano et al, 2016; Touma et al, 2020) in animals. Genetic diversity and ancestry of wild boar have been well studied, including areas of South East Asia, and information from hybridization occurrences with domes- tic pigs is of increasing interest due to possible genetic alterations (Choi et al, 2014; Todesco et al, 2016). Wild boar populations inhabiting Fukushima prefecture, in Japan, are suggested to be threatened by hybridiza- tion following the uncontrolled release of domesticated pigs after mandated evacuations due to the Fukushima nuclear disasters in 2011 (Okuda et al, 2018; Ander- son et al, 2019). Additionally, hybridization in this area has not altered the morphological characteristics of wild boar (Anderson et al, 2019) and possible hybrids can only be detected using DNA. Thus, estimating appropri- ate genotypes of wild boar from the period prior to 2011, after 2011, and from domestic pigs in this area, with microsatellite markers will provide an important source of information for better understanding hybridization effects with native species following such events. Ade- quate selection of microsatellite markers from this area will establish a cost-efficient tool to easily distinguish if a wild boar population has been impacted by hybridiza- tion. In this study, we selected robust microsatellite markers used in European and Asian pig studies (Rohrer et al, 1994; Krause et al, 2002; Karlskov-Mortensen et al, 2007; FAO, 2011) that could differentiate wild boar or pig alleles. Our goal for this study was two-fold: First, we aimed to select useful microsatellite mark- ers for hybrid analysis between domesticated pig and wild boar populations; and second, to use these loci to perform a preliminary check of the introgression of pig alleles into wild boar populations in Fukushima prefecture following the disasters in 2011. Materials and Methods Analysed samples and DNA extraction Thirty-one muscle tissue samples were collected from three populations (hereafter referred to as Pop1, Pop2 and Pop3) and were selected based on mitochondrial DNA (mtDNA) haplotype and year sampled. Sample haplotype and date were prioritized for optimal determi- nation of reliable microsatellite screening of hybridiza- tion between wild boar and domesticated pigs after the Fukushima disasters in 2011. Pop1 samples were from 10 unrelated domestic pigs (Sus scrofa domesti- cus) that were collected from a local pig slaughter- house or local markets within Fukushima prefecture in 2016-2017. Pop2 samples were from 13 wild boar (Sus scrofa) muscle samples that were collected in 2003- 2004, prior to the evacuations and Fukushima disasters, from a wild boar population in northern Ibaraki pre- fecture, south of Fukushima prefecture. The mtDNA analysis has shown that this population is the same haplotype (D42172) and has extremely high genetic similarity to the wild boar population in eastern Fukushima prefecture (Nagata et al, 2006). Pop3 samples were collected in 2015-2016, after the Fukushima disasters, from eight suggested hy- bridized wild boar that had a typical mtDNA haplotype of pig (suggested pig ancestor in maternal lineage; MK801664, see Anderson et al (2019)). All animals were legally culled by licensed hunters, and this entire study was approved by Fukushima Uni- versity’s Institutional Animal Care and Use Commit- tee. All experiments were performed in accordance with relevant guidelines and regulations. All samples were stored individually at −20 ◦C in 99.5% ethanol until extraction. Total genomic DNA was ex- tracted from muscle tissue using the Gentra Pure- gene Tissue Kit (QIAGEN), according to manufacturer’s instructions. Microsatellite loci genotyping A total of 52 unlinked microsatellite loci were se- lected from previously developed phage libraries (Rohrer et al, 1994; Krause et al, 2002; Karlskov- Mortensen et al, 2007) and recommended microsatellite markers from the Food and Agriculture Organisation of the United Nations database (FAO, 2011) and screened for amplification success on all 31 samples. PCR amplification was performed in 5 µL reactions using the QIAGEN Multiplex PCR Kit (QIAGEN) and a protocol for fluorescent dye-label (Blacket et al, 2012). Each sample reaction contained 10 to 20 ng of genomic template DNA, 2.5 µL of Multiplex PCR Master Mix, 0.1 µM of forward primer, 0.2 µM of reverse primer, and 0.1 µM of fluorescently labeled primer. Amplification conditions consisted of 95 ◦C for 15 minutes followed by 33 cycles of denaturation at 94 ◦C for 30 seconds, annealing at 57 ◦C for 1.5 minutes, and extension at 72 ◦C for 1 minute and an extension at 60 ◦C for 30 minutes. All thermal cycling conditions used in T100 thermal cycler (Bio-Rad Laboratories, Inc., Hercules, CA, USA). Product sizes were determined using an ABI PRISM 3130 Genetic Analyzer and GeneMapper software (Applied Biosystems, Foster City, CA, USA). Characterization of microsatellite markers Successful markers were identified after our initial screening by clear peak patterns following amplifica- tions. Number of alleles (NA), observed heterozygosity Genetic Resources (2020), 1 (2), 29–41 Markers for pig and wild boar hybridization 31 Table 1. Characteristics of 32 microsatellite markers selected. Ta = annealing temperature Locus Primer sequence (5’ → 3’) Forward/Reverse Repeat motif Range of alleles (bp) Ta (◦C) Fluorescent label Genebank accession No. Sw632 TGGGTTGAAAGATTTCCCAA (AC)21 115-138 55 FAM AF225099 GGAGTCAGTACTTTGGCTTGA S0090 CCAAGACTGCCTTGTAGGTGAATA (AC)24 227-253 55 FAM M95002 GCTATCAAGTATTGTACCATTAGG Sw24 CTTTGGGTGGAGTGTGTGC (GT)13 99-135 55 VIC AF235245 ATCCAAATGCTGCAAGCG Swr1941 AGAAAGCAATTTGATTTGCATAATC (TG)20 215-255 55 VIC AF253904 ACAAGGACCTACTGTATAGCACAGG Sw857 TGAGAGGTCAGTTACAGAAGACC (CA)22 165-187 55 NED AF225105 GATCCTCCTCCAAATCCCAT S0228 GGCATAGGCTGGCAGCAACA (AC)17 93-112 55 PET L29195 AGCCCACCTCATCTTATCTACACT Sw2008 CAGGCCAGAGTAGCGTGC (GT)25 148-170 55 FAM AF253773 CAGTCCTCCCAAAAATAACATG Sw240 AGAAATTAGTGCCTCAAATTGG (TG)17 164-186 55 VIC AF235246 AAACCATTAAGTCCCTAGCAAA S0097 GACCTATCTAATGTCATTATAGT (AC)28 135-155 55 NED M95020 TTCCTCCTAGAGTTGACAAACTT UMNp147 GCCTTCGTTACATGGCATTC (GT)23 151-167 58 PET AF511119 TCTCTGTGAGGTCATGGTGG UMNp239 CTTACAAAACCACCACCATCG (AC)18 96-112 60 FAM AF511146 TCAATATCAACATTGCGTGTTG UMNp296 CAGGGAACTCTCTTCAATATCC (TG)13 151-181 58 NED AF511184 ACATTTGATTTCCAAAGTTGTG UMNp298 GCTATAAGAACCGCCTCATTG (GT)22 157-169 58 NED AF511185 TGTGTGCTGCTGAAGCATG UMNp351 TCAGTGTCACCCCTCATCAC (AC)15 143-169 58 FAM AF511222 TCTCCTTGACCTTCTAAGCACC UMNp358 AAGTCATTTCACACCTCTGTGC (CA)22 160-176 58 VIC AF511230 CGTTGCAGTTACTATTCCAAGC UMNp362 GATGTGTAGCTGATTTGCAATG (AC)21 125-135 60 PET AF511231 GACAAGAATCTGAAAAGGAGCG UMNp381 CCGATTAGACCCCTAGTCTGG (AC)22 169-185 60 NED AF511244 Continued on next page 32 Anderson et al Genetic Resources (2020), 1 (2), 29–41 Table 1 continued Locus Primer sequence (5’ → 3’) Forward/Reverse Repeat motif Range of alleles (bp) Ta (◦C) Fluorescent label Genebank accession No. CAGATTAGCGTTCCCTGTTTG UMNp405 CAGAGTTCACCTCTCCCTTTAC (AC)21 148-162 62 VIC AF511255 TCCTTGCTGAGTCCCAGG UMNp442 ATCCAAGCTGCTGAAGTTGG (TG)12 122-124 60 NED AF511283 AAACATTTCCACAAGAAAATGG UMNp453 TCATTCTCTATCTCAAGATGCATG (AC)17 122-140 58 PET AF511291 CTGAGGTACCTTTGCCTAGAGG UMNp480 AGTGATTTCTGCCCAGGATG (TG)21 143-155 58 VIC AF511308 CCTAGGAATTTCCCTCTGCC UMNp485 CCTCAGGCTCAGCTCTGC (TG)17 187-213 57 PET AF511313 GTTGTCCGTGAGTCCCTAGC UMNp489 AAGCACCATAGGAGAAGACTGG (AC)12 115-141 60 PET AF511317 CTCGGAAGCAAGTAAGTGGG UMNp494 CTGCCTGATTGGCACATTAG (AC)23 114-142 60 FAM AF511320 GGTAATGGGAAAGCCTAGCC UMNp500 TGAGGCTATCACCTGCAGTG (AG)24 229-251 60 FAM AF511324 GACTGAACCCTTAACAGATGGG UMNp502 TGGCAAACGTTGCTTTAGG (GT)22 164-172 60 VIC AF511325 TAGGGAAATATCTGAAATCTAAAATG UMNp509 AAACTACATCCATTCTCTTGGG (GT)21 138-164 60 FAM AF511328 GTTGTGCCAGTTACACTTCTGC UMNp511 GATCACTGTGTGAGTGCATGC (GT)14 107-117 60 VIC AF511329 AACAGAGTTCCATTTTGCGG UMNp539 CAACGTTGCTGTGGCTGTAG (CA)32 171-181 60 NED AF511346 TTCTGGTTTATGGTTCCCATG UMNp548 TCCAAGTTAGACTGCCTGCC (CA)14 172-180 60 NED AF511353 ACTGCTGCTTATTTCTCAAGGG UMNp610 CTTTGGCTCAATCTCATTCATG (AC)33 168-178 60 VIC AF511389 TGGGCTTTTGAAAATTTAAATG UMNp640 TATGCCATGTGCGTGGTC (AC)13 123-145 60 FAM AF511399 ACAAACTGCACCACAGAATAGC Genetic Resources (2020), 1 (2), 29–41 Markers for pig and wild boar hybridization 33 (HO), and expected heterozygosity (HE) were calcu- lated using GenAIEX version 6.5 (Peakall and Smouse, 2012) for successfully amplified loci. Calculation of inbreeding coefficients (FIS) and test of deviation from Hardy–Weinberg equilibrium (HWE) for polymorphic loci were tested using FSTAT version 2.9.3 (Goudet, 1995). Allele frequency in each locus for Pop1, Pop2, and Pop3 was calculated using GenAlEx ver- sion 6.41 (Peakall and Smouse, 2006). Genetic differ- entiation among Pop1, Pop2, and Pop3 (i.e. differen- tiation among pig, wild boar, and hybrids) was eval- uated using AMOVA, calculating pairwise codominant genotypic distances (Smouse and Peakall, 1999), and performing principal coordinates analysis (PCoA) using GenAlEx version 6.41 (Peakall and Smouse, 2006). Results Of the initial 52 microsatellite loci selected, 32 loci were successfully amplified with all wild boar and pig samples. Marker information is provided in Table 1. Twenty loci were eliminated based on low amplification success or unclear peak patterns in wild boar DNA samples collected from Pop2 and Pop3. Polymorphism measurements for the 32 amplified microsatellite loci in Pop1, Pop2, and Pop3 are summarized in Table 2. For Pop1, HO and HE per locus ranged from 0.10 to 1.00 (mean, 0.64) and from 0.10 to 0.82 (mean, 0.65), respectively. The range of FIS was -0.46 to 0.47 (mean, 0). For Pop2, HO and HE per locus ranged from 0.00 to 0.77 (mean, 0.36) and from 0.00 to 0.73 (mean, 0.39), respectively. The range of FIS was -0.28 to 0.85 (mean, 0.07). For Pop3, the HO and HE per locus ranged from 0.00 to 0.88 (mean, 0.45) and from 0.00 to 0.76 (mean, 0.44), respectively. The range of FIS was -0.62 to 1.00 (mean, -0.01). All 32 loci showed no evidence of significant deviation from HWE (P > 0.05). In total, 231 putative alleles were identified that ranged from 1 to 8 per locus (mean, 4), as outlined in Table 2 (No. alleles). The mean number of alleles was 5.1, 3.2, and 3.3 for Pop1, Pop2, and Pop3, respectively. Of the 231 alleles, 52 (23%) were putative to the wild boar populations and 95 (41%) were putative to domestic pigs (Table 3). Additionally, 68 (30%) alleles were shared by pigs and one of the wild boar populations or by all three populations. Among the 68 shared alleles, 21 were shared by pigs and the wild boar population from the period after the Fukushima disasters in 2011 (bolded alleles in Table 4), indicating introgression of pig genes into the wild boar gene pool. The allele frequencies of amplified microsatellite markers, including those that distinguished these shared alleles between Pop1 and Pop3, are provided in Table 4. AMOVA suggested strong genetic differentiation between the three populations (FST = 0.318, p < 0.001). Genetic differentiation is also well-supported by clear divisions among the three populations with PCoA (Figure 1). Pop1 is uniquely distinguished along the first axis and Pop2/Pop3 are distinguished along the second axis. Furthermore, codominant genotypic distances describe 35.40% and 7.4% of the variation with the first and second axes, respectively. Taken together, our data strongly indicate genetic differentiation of pigs, wild boar from the period prior to, and after, the disasters in Fukushima in 2011. Discussion All 32 loci selected from previous studies (Rohrer et al, 1994; Krause et al, 2002; Karlskov-Mortensen et al, 2007; FAO, 2011) showed pig putative alleles sug- gesting they can be useful for wild boar and pig hy- brid analysis in Fukushima and elsewhere. The pres- ence of pig-specific alleles at certain loci depends on the genetic composition of the target population and the pig population involved in the hybridization. In this study, pig samples were from slaughterhouses and farms nearby the evacuated area to improve the likeli- hood of detecting newly introgressive pig alleles in the hybridized wild boar. One of the pigs sampled had the mtDNA haplotype that was the same as hybrid wild boar in Fukushima (Anderson et al, 2019), and the sampled pig population in this study had high genetic variation (mean NA = 5.1). Therefore, we were confident in the representation of the pig ge- netic composition involved in the hybridization for this study and were able to distinguish an appropriate set of markers for hybrid analysis. Our selective use of markers with low frequencies of common alleles in source pig individuals and target wild boar populations is highly suggested for cost-effective analysis. The highest number of alleles was observed in the pig population, which was expected because of human mediated translocations of domestic populations with high genetic diversity (Scandura et al, 2008; Yang et al, 2017). Additionally, if the 95 pig putative alleles were excluded, then 27% of the detected alleles were shared by all three populations in this study (Table 3). The high percentage of shared alleles between pig and wild boar verifies the challenge of identifying appropriate markers for hybridization analysis. Seventeen of the 32 microsatellite loci distinguished hybridization between pigs and wild boar in this study and these can be used as robust markers, specifically for wild boar populations in Fukushima. These seventeen markers detected at least one of the 21 alleles that were only shared between Pop1 and Pop3 (bolded alleles in Table 4). Alleles only shared by Pop1 and Pop3, and not detected in Pop2, would suggest that the alleles were introgressive through mixing of pigs and wild boar during the period after the 2011 evacuations and Fukushima disasters. The higher percent of total shared alleles between Pop1 and Pop3 (9%), compared to Pop1 and Pop2 (4%), indicates that there is likely more genetic mixing between Pop1 and Pop3 (Table 3), which would also support the hypothesis of hybridization occurring after disasters in 2011. 34 Anderson et al Genetic Resources (2020), 1 (2), 29–41 Table 2. Polymorphism measurements of microsatellite loci of each sampled population. n = No. samples, NA = No. alleles, HO = observed heterozygosity, HE = heterozygosity, FIS = breeding coefficient Locus Pop1 (n = 10) Pop2 (n = 13) Pop3 (n = 8) NA HO HE FIS NA HO HE FIS NA HO HE FIS Sw632 5 0.80 0.79 -0.01 2 0.38 0.50 0.23 3 0.50 0.40 -0.25 S0090 6 0.90 0.77 -0.17 2 0.08 0.07 -0.04 3 0.43 0.36 -0.20 Sw24 6 0.56 0.77 0.27 4 0.31 0.39 0.21 6 0.88 0.76 -0.15 Swr1941 5 0.60 0.72 0.16 2 0.15 0.26 0.41 2 0.14 0.13 -0.08 Sw857 6 1.00 0.75 -0.33 3 0.31 0.27 -0.14 3 0.38 0.32 -0.17 S0228 5 0.40 0.59 0.32 5 0.77 0.69 -0.11 4 0.38 0.66 0.44 Sw2008 5 0.90 0.70 -0.29 4 0.31 0.38 0.19 3 0.63 0.48 -0.31 Sw240 6 0.70 0.77 0.08 2 0.31 0.43 0.28 3 0.50 0.55 0.10 S0097 6 0.60 0.79 0.24 4 0.38 0.48 0.19 4 0.63 0.63 0.01 UMNp147 7 0.80 0.81 0.01 4 0.08 0.51 0.85 3 0.13 0.23 0.45 UMNp239 4 0.50 0.62 0.19 4 0.62 0.56 -0.10 4 0.75 0.68 -0.10 UMNp296 7 0.80 0.81 0.01 3 0.69 0.61 -0.14 5 0.75 0.66 -0.14 UMNp298 6 0.80 0.76 -0.05 3 0.23 0.21 -0.10 2 0.13 0.49 0.75 UMNp351 5 0.40 0.76 0.47 5 0.62 0.49 -0.26 3 0.50 0.57 0.12 UMNp358 7 0.60 0.81 0.25 4 0.31 0.33 0.08 2 0.50 0.38 -0.33 UMNp362 2 0.30 0.38 0.20 1 0.00 0.00 N/A 1 0.00 0.00 N/A UMNp381 2 0.10 0.10 -0.05 5 0.62 0.73 0.15 3 0.13 0.23 0.45 UMNp405 3 0.40 0.34 -0.19 1 0.00 0.00 N/A 2 0.13 0.12 -0.07 UMNp442 3 0.30 0.27 -0.13 1 0.00 0.00 N/A 2 0.00 0.22 1.00 UMNp453 6 0.80 0.73 -0.10 2 0.08 0.07 -0.04 1 0.00 0.00 N/A UMNp480 5 0.80 0.60 -0.34 2 0.31 0.36 0.13 2 0.38 0.30 -0.23 UMNp485 6 0.80 0.61 -0.32 3 0.38 0.52 0.26 3 0.88 0.54 -0.62 UMNp489 4 0.56 0.52 -0.07 3 0.54 0.48 -0.13 5 0.86 0.65 -0.31 UMNp494 4 0.50 0.59 0.15 4 0.62 0.48 -0.28 4 0.75 0.67 -0.12 UMNp500 5 0.70 0.76 0.07 4 0.46 0.63 0.27 6 0.88 0.64 -0.37 UMNp502 4 0.80 0.67 -0.20 5 0.31 0.34 0.09 5 0.50 0.50 0.00 UMNp509 5 0.70 0.67 -0.05 4 0.38 0.49 0.21 5 0.63 0.50 -0.25 UMNp511 4 0.90 0.62 -0.46 4 0.77 0.67 -0.16 4 0.38 0.62 0.39 UMNp539 8 0.70 0.82 0.14 3 0.46 0.41 -0.12 4 0.63 0.55 -0.13 UMNp548 3 0.50 0.51 0.01 2 0.15 0.36 0.57 2 0.13 0.12 -0.07 UMNp610 6 0.60 0.72 0.17 3 0.15 0.14 -0.06 4 0.38 0.41 0.09 UMNp640 7 0.70 0.70 -0.01 3 0.69 0.54 -0.27 4 0.75 0.65 -0.16 Table 3. Number of putative and shared alleles by population with putative allele origin. Percentage indicates proportion of alleles related to total alleles detected in this study. Population(s) Putative allele origin Number of alleles (% of total alleles) Pop1 (pig) Pig 95 (41%) Pop2 (wild boar) Wild boar 18 (8%) Pop3 (hybrid boar) Pig and/or wild boar 16 (7%) Shared Pop1 and Pop2 Pig and/or wild boar 10 (4%) Shared Pop1 and Pop3 Pig 21 (9%) Shared Pop2 and Pop3 Wild boar 34 (15%) Shared Pop1, Pop2, and Pop3 Pig and/or wild boar 37 (16%) Total alleles 231 Genetic Resources (2020), 1 (2), 29–41 Markers for pig and wild boar hybridization 35 Table 4. Allele frequencies for selected microsatellite markers. Pop1 n=10; Pop2 n=13; Pop3 n=8. AlleleP indicates putative pig alleles. AlleleB indicates putative wild boar alleles. Bolded alleles indicate pig alleles putatively introgressed into the wild boar population. Locus Allele Frequency Locus Allele Frequency Pop1 Pop2 Pop3 Pop1 Pop2 Pop3 Sw2008 102B 0 0.15 0.69 UMNp362 124P 0.25 0 0 106B 0 0.77 0.19 126P 0.75 0 0 108 0.05 0.04 0 132B 0 1 1 110P 0.25 0 0 UMNp381 165P 0.05 0 0.06 112 0.45 0.04 0 167B 0 0.35 0 114P 0.1 0 0.13 173 0.95 0.27 0.88 116P 0.15 0 0 175B 0 0.08 0.06 Sw24 121 0 0 0.06 179B 0 0.27 0 123P 0.28 0 0 181B 0 0.04 0 125 0.06 0.77 0.13 UMNp405 140 0 0 0.06 127B 0 0.08 0.06 144 0.15 1 0.94 129 0.33 0.08 0.38 148P 0.05 0 0 131 0.17 0.08 0.25 156P 0.8 0 0 133P 0.11 0 0 UMNp442 118 0 0 0.13 135P 0.06 0 0 120 0.1 1 0.88 139 0 0 0.13 122P 0.85 0 0 Sw240 107P 0.1 0 0 124P 0.05 0 0 111P 0.4 0 0 UMNp453 122 0.05 0.96 1 113P 0.15 0 0 130P 0.05 0 0 119B 0 0.69 0.5 132P 0.1 0 0 121P 0.1 0 0 134P 0.1 0 0 123P 0.1 0 0 136 0.3 0.04 0 125 0.15 0.31 0.44 138P 0.4 0 0 127 0 0 0.06 UMNp480 136P 0.15 0 0 Sw632 160 0 0.5 0.75 138B 0 0.77 0.81 172P 0.25 0 0 144P 0.6 0 0 174 0.2 0.5 0.19 146 0.1 0.23 0.19 180P 0.25 0 0 148P 0.1 0 0 182P 0.15 0 0.06 152P 0.05 0 0 184P 0.15 0 0 UMNp485 185B 0 0.58 0.38 Sw857 156P 0.05 0 0 193B 0 0.38 0.56 164P 0.15 0 0 195B 0 0.04 0 166P 0.35 0 0 203P 0.1 0 0 168 0.05 0.12 0.06 207P 0.6 0 0 170 0.3 0.85 0.81 209P 0.1 0 0 172 0.1 0.04 0.13 211P 0.05 0 0.06 219P 0.05 0 0 225P 0.1 0 0 Continued on next page 36 Anderson et al Genetic Resources (2020), 1 (2), 29–41 Table 4 continued Locus Allele Frequency Locus Allele Frequency Pop1 Pop2 Pop3 Pop1 Pop2 Pop3 Swr1941 224B 0 0.85 0.93 UMNp489 116P 0.11 0 0.07 228 0.3 0.15 0.07 126P 0.67 0 0.07 232P 0.4 0 0 128 0.11 0.65 0.5 234P 0.15 0 0 130 0.11 0.04 0 236P 0.1 0 0 134 0 0 0.07 238P 0.05 0 0 140B 0 0.31 0.29 S0090 252P 0.05 0 0 UMNp494 108P 0.5 0 0 254 0.35 0.96 0.79 114 0 0 0.06 256 0.15 0.04 0.07 126B 0 0.15 0.31 258P 0.2 0 0.14 128B 0 0.12 0.19 260P 0.2 0 0 130 0.4 0.69 0.44 262P 0.05 0 0 132P 0.05 0 0 S0097 230P 0.1 0 0 134P 0.05 0 0 232P 0.2 0 0 141B 0 0.04 0 238 0 0 0.13 UMNp500 219P 0.3 0 0 240B 0 0.08 0 221P 0.15 0 0 244B 0 0.04 0 223 0.05 0.12 0.06 250P 0.3 0 0 225P 0.3 0 0.13 252B 0 0.69 0.5 227B 0 0.54 0.56 254P 0.1 0 0 229 0 0 0.13 256P 0.25 0 0.06 237B 0 0.12 0.06 258P 0.05 0 0 239B 0 0.23 0.06 260B 0 0.19 0.31 245P 0.2 0 0 S0228 239P 0.6 0 0 UMNp502 156 0.2 0.81 0.69 241P 0.05 0 0 158 0.05 0.04 0.06 243B 0 0.42 0 160 0.45 0.04 0.06 245 0.05 0.04 0 162P 0.3 0 0 247B 0 0.23 0.19 164 0 0 0.13 251 0 0 0.19 166B 0 0.08 0.06 255B 0 0.27 0.13 168B 0 0.04 0 257 0.2 0.04 0.5 UMNp509 133 0 0 0.06 259P 0.1 0 0 141B 0 0.08 0.13 UMNp147 141P 0.3 0 0 143B 0 0.12 0.69 147P 0.1 0 0 145B 0 0.69 0.06 148P 0.05 0 0 147P 0.05 0 0 149P 0.2 0 0 151 0.4 0.12 0 153B 0 0.04 0.06 153P 0.4 0 0.06 157P 0.2 0 0 155P 0.1 0 0 159 0.05 0.23 0.88 157P 0.05 0 0 163 0 0 0.06 165B 0 0.65 0 167 0.1 0.08 0 Continued on next page Genetic Resources (2020), 1 (2), 29–41 Markers for pig and wild boar hybridization 37 Table 4 continued Locus Allele Frequency Locus Allele Frequency Pop1 Pop2 Pop3 Pop1 Pop2 Pop3 UMNp239 90B 0 0.54 0.31 UMNp511 98 0 0 0.13 92P 0.35 0 0 102B 0 0.46 0.56 94P 0.5 0 0.13 106P 0.35 0 0.13 96P 0.1 0 0 108 0.1 0.12 0.19 98P 0.05 0 0.13 110 0.5 0.31 0 104B 0 0.38 0.44 112 0.05 0.12 0 106B 0 0.04 0 UMNp539 159P 0.05 0 0 108B 0 0.04 0 161P 0.05 0 0 UMNp296 147B 0 0.15 0.06 165P 0.25 0 0 149P 0.1 0 0.06 167 0.05 0.23 0.19 151P 0.15 0 0 169P 0.2 0 0 155P 0.2 0 0.06 171 0.05 0.04 0 159P 0.3 0 0 173 0.25 0.73 0.63 161P 0.05 0 0 175 0 0 0.13 167P 0.15 0 0 177P 0.1 0 0.06 171 0.05 0.35 0.44 UMNp548 168P 0.65 0 0.06 177B 0 0.5 0.38 170 0.25 0.23 0 UMNp298 153 0.25 0.88 0.56 176B 0 0.77 0.94 155 0.2 0.08 0.44 178P 0.1 0 0 167 0.35 0.04 0 UMNp610 162P 0.45 0 0.06 169P 0.05 0 0 164 0.2 0.92 0.75 185P 0.1 0 0 166B 0 0.04 0 191P 0.05 0 0 170B 0 0.04 0.06 UMNp351 130P 0.1 0 0 174P 0.15 0 0.13 136P 0.3 0 0 178P 0.05 0 0 140 0.3 0.15 0.56 180P 0.05 0 0 142 0.2 0.08 0 186P 0.1 0 0 144P 0.1 0 0.13 UMNp640 113P 0.05 0 0 156B 0 0.04 0 117 0.45 0.23 0.38 162B 0 0.69 0.31 119 0 0 0.06 166B 0 0.04 0 121P 0.3 0 0 UMNp358 154 0.05 0.81 0.75 127 0.05 0.62 0.44 158 0.25 0.08 0.25 129P 0.05 0 0.13 160P 0.2 0 0 135P 0.05 0 0 164P 0.05 0 0 137P 0.05 0 0 166B 0 0.08 0 139B 0 0.15 0 168B 0 0.04 0 169P 0.05 0 0 170P 0.15 0 0 172P 0.25 0 0 38 Anderson et al Genetic Resources (2020), 1 (2), 29–41 The loci identified in this study (Table 4) provide a unique tool to contribute to determining a timeline of hybridization for these populations. Similar frequencies of pig alleles in other wild boar populations may suggest early stages of hybridization, as our data indicates recent occurrence of hybridization in Fukushima prefecture, following the release of domestic pigs into the wild boar populations in 2011 (Okuda et al, 2018). Additionally, the identified loci can contribute to determining if the introgressive alleles are being retained or lost due to natural causes (e.g. backcross) in the hybridized wild boar population using introgressive allele frequencies over time. Studies have been published to determine wild boar and pig hybridization hotspots, recent occurrences, and genetic impacts using variable genetic markers, such as mtDNA sequence (Ishiguro et al, 2002; McCann et al, 2014), RAD-seq analysis (Goddard and Hayes, 2007; Iacolina et al, 2018) or microsatellite markers (Murakami et al, 2014). However, Next Generation Sequencing (NGS), such as RAD-seq, have disadvantages including that a large amount of high quality DNA is required, and the amount of data to be analyzed becomes demanding. Therefore, general genetic markers, such as microsatellite mark- ers, are still useful for analysis of degraded DNA ex- tracted from feces in the field and old specimens of bones (Kierepka et al, 2016). Selected robust markers from our study will show their advantages in future hy- brid analysis and are cost-effective for immediate or continuous monitoring for small sample sizes or DNA analysis of degraded samples. Also, comparing NGS and microsatellite marker data from a common popula- tion in future studies will not only give more in- depth information about that target population, but will more clearly show the advantages and disadvan- tages of each marker. Data Availability Statement The data that support the findings of this study are available from the corresponding author upon reasonable request. Acknowledgements Thanks to Dr Hiroko Ishiniwa and Dr Kei Okuda for support with sampling. Additionally, we are thankful to all prefectural hunters for their support in obtaining samples. Funding for this study was partially provided by the Nippon Life Insurance Foundation. Author contributions DA and SK contributed to the writing, drafting, and execution of the manuscript. DA, YN and SK, contributed to data analysis and interpertation. All authors contributed to study design, revision, and approval of the submitted manuscript. All authors declare that the submitted work is their own and that copyright has not been breached in seeking its publication. Additionally, the submitted work has not been previously published and is not being considered elsewhere. Conflict of interest statement The authors declare no conflict of interest. References Anderson, D., Toma, R., Negishi, Y., Okuda, K., Ishiniwa, H., Hinton, T. G., Nanba, K., Tamate, H. B., and Kaneko, S. (2019). Mating of escaped domestic pigs with wild boar and possibility of their offspring migration after the Fukushima Daiichi Nuclear Power Plant accident. Scientific Reports 9, 11537. doi: https: //doi.org/10.1038/s41598-019-47982-z Blacket, M. J., Robin, C., Good, R. T., Lee, S. F., and Miller, A. D. (2012). Universal primers for fluorescent labelling of PCR fragments-an efficient and cost-effective approach to genotyping by fluo- rescence. Molecular Ecology Resources 12(3), 456– 463. doi: https://dx.doi.org/10.1111/j.1755-0998. 2011.03104.x Choi, S. K., Lee, J. E., Kim, Y. J., Min, M. S., Voloshina, I., Myslenkov, A., Oh, J. G., Kim, T. H., Markov, N., Seryodkin, I., Ishiguro, N., Yu, L., Zhang, Y. P., Lee, H., and Kim, K. S. (2014). Genetic structure of wild boar (Sus scrofa) populations from East Asia based on microsatellite loci analyses. BMC Genetics 15, 85. doi: https://doi.org/10.1186/1471-2156-15-85 Dzialuk, A., Zastempowska, E., Skórzewski, R., Twarużek, M., and Grajewski, J. (2018). High domestic pig contribution to the local gene pool of free-living European wild boar: a case study in Poland. Mammal Research 63(1), 65–71. doi: https://dx.doi.org/10.1007/s13364-017-0331-3 FAO (2011). Molecular genetic characterization of animal genetic resources. FAO Animal Production and Health Guidelines 9. url: http://www.fao.org/3/ i2413e/i2413e00.pdf. Goddard, M. E. and Hayes, B. J. (2007). Genomic selection. Journal of Animal Breeding and Genetics 124(6), 323–330. doi: https://dx.doi.org/10.1111/j. 1439-0388.2007.00702.x Godinho, R., Llaneza, L., Blanco, J. C., Lopes, S., Álvares, F., Garćıa, E. J., Palacios, V., Cortés, Y., Talegón, J., and Ferrand, N. (2011). Genetic evidence for multiple events of hybridization between wolves and domestic dogs in the Iberian Peninsula. Molecular Ecology 20(24), 5154–5166. doi: https://dx.doi.org/10.1111/ j.1365-294x.2011.05345.x Goedbloed, D. J., Megens, H. J., Hooft, P. V., Herrero- Medrano, J. M., Lutz, W., Alexandri, P., Crooijmans, R. P. M. A., Groenen, M., Wieren, S. E. V., Ydenberg, R. C., and Prins, H. H. T. (2013a). Genome- wide single nucleotide polymorphism analysis reveals recent genetic introgression from domestic pigs into Northwest European wild boar populations. Molecular Ecology 22(3), 856–866. doi: 10.1111/j.1365-294x. 2012.05670.x https://doi.org/10.1038/s41598-019-47982-z https://doi.org/10.1038/s41598-019-47982-z https://dx.doi.org/10.1111/j.1755-0998.2011.03104.x https://dx.doi.org/10.1111/j.1755-0998.2011.03104.x https://doi.org/10.1186/1471-2156-15-85 https://dx.doi.org/10.1007/s13364-017-0331-3 http://www.fao.org/3/i2413e/i2413e00.pdf http://www.fao.org/3/i2413e/i2413e00.pdf https://dx.doi.org/10.1111/j.1439-0388.2007.00702.x https://dx.doi.org/10.1111/j.1439-0388.2007.00702.x https://dx.doi.org/10.1111/j.1365-294x.2011.05345.x https://dx.doi.org/10.1111/j.1365-294x.2011.05345.x https://doi.org/10.1111/j.1365-294x.2012.05670.x 10.1111/j.1365-294x.2012.05670.x Genetic Resources (2020), 1 (2), 29–41 Markers for pig and wild boar hybridization 39 Figure 1. Principal Coordinates Analysis Plot of Pop1 (grey circle), Pop2 (black diamond), and Pop3 (black triangle) based on codominant genotypic distances. Axis 1 explains 35.4% of the variance and axis 2 explains 7.49% of the variance. Goedbloed, D. J., van Hooft, P., Megens, H.-J., Langen- beck, K., Lutz, W., Crooijmans, R. P., van Wieren, S. E., Ydenberg, R. C., and Prins, H. H. (2013b). Rein- troductions and genetic introgression from domestic pigs have shaped the genetic population structure of Northwest European wild boar. BMC Genetics 14(1), 43–43. doi: https://dx.doi.org/10.1186/1471-2156- 14-43 Goudet, J. (1995). FSTAT (Version 1.2): A Computer Program to Calculate F-Statistics. Journal of Heredity 86(6), 485–486. doi: https://dx.doi.org/10.1093/ oxfordjournals.jhered.a111627 Grossi, S. F., Lui, J. F., Garcia, J. E., and Meirelles, F. V. (2006). Genetic diversity in wild (Sus scrofa scrofa) and domestic (Sus scrofa domestica) pigs and their hybrids based on polymorphism of a fragment of the D-loop region in the mitochondrial DNA. Genetics and Molecular Research 5(4), 564–568. Harrison, R. G. and Larson, E. L. (2014). Hybridization, Introgression, and the Nature of Species Boundaries. Journal of Heredity 105(S1), 795–809. doi: https:// dx.doi.org/10.1093/jhered/esu033 Hoffman, J. I. and Amos, W. (2005). Microsatellite genotyping errors: detection approaches, common sources and consequences for paternal exclusion. Molecular Ecology 14(2), 599–612. doi: https://dx. doi.org/10.1111/j.1365-294x.2004.02419.x Iacolina, L., Pertoldi, C., Amills, M., Kusza, S., Megens, H.-J., Bâlteanu, V. A., Bakan, J., Cubric-Curik, V., Oja, R., Saarma, U., Scandura, M., Šprem, N., and Stronen, A. V. (2018). Hotspots of recent hybridization between pigs and wild boars in Europe. Scientific Reports 8(1), 1–10. doi: https://dx.doi.org/10.1038/ s41598-018-35865-8 Ishiguro, N., Naya, Y., Horiuchi, M., and Shinagawa, M. (2002). A Genetic Method to Distinguish Crossbred Inobuta from Japanese Wild Boars. Zoological Science 19(11), 1313–1319. doi: https://dx.doi.org/10.2108/ zsj.19.1313 Karlskov-Mortensen, P., Hu, Z. L., Gorodkin, J., Reecy, J. M., and Fredholm, M. (2007). Identification of 10 882 porcine microsatellite sequences and virtual mapping of 4528 of these sequences. Animal Genetics 38(4), 401–405. doi: https://dx.doi.org/10.1111/j. 1365-2052.2007.01609.x Kierepka, E. M., Unger, S. D., Keiter, D. A., Beasley, J. C., Rhodes, O. E., Cunningham, F. L., and Piaggio, A. J. (2016). Identification of robust microsatellite markers for wild pig fecal DNA. The Journal of Wildlife Management 80(6), 1120–1128. doi: https://dx.doi. org/10.1002/jwmg.21102 Kolodziej, K., Theissinger, K., Brün, J., Schulz, H. K., and Schulz, R. (2012). Determination of the minimum number of microsatellite markers for individual genotyping in wild boar (Sus scrofa) using a test with close relatives. European Journal of Wildlife Research 58(3), 621–628. doi: https://dx.doi.org/10. 1007/s10344-011-0588-9 Koutsogiannouli, E. A., Moutou, K. A., Sarafidou, T., Stamatis, C., and Mamuris, Z. (2010). Detection of hybrids between wild boars (Sus scrofa scrofa) and domestic pigs (Sus scrofa f. domestica) in Greece, using the PCR-RFLP method on melanocortin- 1 receptor (MC1R) mutations. Mammalian Biol- ogy 75(1), 69–73. doi: https://dx.doi.org/10.1016/j. mambio.2008.08.001 Krause, E., Morrison, L., Reed, K. M., and Alexander, L. J. (2002). Radiation hybrid mapping of 273 previously unreported porcine microsatellites. Animal Genetics 33(6), 477–485. doi: https://dx.doi.org/10.1046/j. 1365-2052.2002.00938\ 9.x Larson, G., Dobney, K., Albarella, U., Fang, M., Matisoo-Smith, E., Robins, J., Lowden, S., Finlayson, H., Brand, T., Willerslev, E., Rowley-Conwy, F., Andersson, L., and Cooper, A. (2005). Worldwide phylogeography of wild boar reveals multiple centers of pig domestication. Science 307(5715), 1618–1621. doi: 10.1126/science.1106927 Matsumoto, Y., Takagi, T., Koda, R., Tanave, A., Yamashiro, A., and Tamate, H. B. (2019). Evaluation of introgressive hybridization among Cervidae in Japan’s Kinki District via two novel genetic markers developed from public NGS data. Ecology and https://dx.doi.org/10.1186/1471-2156-14-43 https://dx.doi.org/10.1186/1471-2156-14-43 https://dx.doi.org/10.1093/oxfordjournals.jhered.a111627 https://dx.doi.org/10.1093/oxfordjournals.jhered.a111627 https://dx.doi.org/10.1093/jhered/esu033 https://dx.doi.org/10.1093/jhered/esu033 https://dx.doi.org/10.1111/j.1365-294x.2004.02419.x https://dx.doi.org/10.1111/j.1365-294x.2004.02419.x https://dx.doi.org/10.1038/s41598-018-35865-8 https://dx.doi.org/10.1038/s41598-018-35865-8 https://dx.doi.org/10.2108/zsj.19.1313 https://dx.doi.org/10.2108/zsj.19.1313 https://dx.doi.org/10.1111/j.1365-2052.2007.01609.x https://dx.doi.org/10.1111/j.1365-2052.2007.01609.x https://dx.doi.org/10.1002/jwmg.21102 https://dx.doi.org/10.1002/jwmg.21102 https://dx.doi.org/10.1007/s10344-011-0588-9 https://dx.doi.org/10.1007/s10344-011-0588-9 https://dx.doi.org/10.1016/j.mambio.2008.08.001 https://dx.doi.org/10.1016/j.mambio.2008.08.001 https://dx.doi.org/10.1046/j.1365-2052.2002.00938\_9.x https://dx.doi.org/10.1046/j.1365-2052.2002.00938\_9.x https://doi.org/10.1126/science.1106927 40 Anderson et al Genetic Resources (2020), 1 (2), 29–41 Evolution 9(10), 5605–5616. doi: https://dx.doi.org/ 10.1002/ece3.5131 McCann, B. E., Malek, M. J., Newman, R. A., Schmit, B. S., Swafford, S. R., Sweitzer, R. A., and Simmons, R. B. (2014). Mitochondrial diversity supports multiple origins for invasive pigs. The Journal of Wildlife Management 78(2), 202–213. doi: https://dx. doi.org/10.1002/jwmg.651 Murakami, K., Yoshikawa, S., Konishi, S., Ueno, Y., Watanabe, S., and Mizoguchi, Y. (2014). Evaluation of genetic introgression from domesticated pigs into the Ryukyu wild boar population on Iriomote Island in Japan. Animal Genetics 45(4), 517–523. doi: https: //dx.doi.org/10.1111/age.12157 Nagata, J., Maruyama, T., Asada, M., Ochiai, K., Yamazaki, K., Yamada, F., Kawaji, N., and Yasuda, M. (2006). Genetic characteristics of the wild boars in Tochigi prefecture and neighboring prefectures. Wildlife in Tochigi Pref 32, 58–62. Nijman, I. J., Otsen, M., Verkaar, E. L. C., de Ruijter, C., Hanekamp, E., Ochieng, J. W., Shamshad, S., Rege, J. E. O., Hanotte, O., Barwegen, M. W., Sulawati, T., and Lenstra, J. A. (2003). Hybridization of banteng (Bos javanicus) and zebu (Bos indicus) revealed by mitochondrial DNA, satellite DNA, AFLP and microsatellites. Heredity 90(1), 10–16. doi: https: //dx.doi.org/10.1038/sj.hdy.6800174 Okuda, K., Toma, R., Negishi, Y., Hinton, T. G., Smyser, T. J., Tamate, H. B., and Kaneko, S. (2018). Did domestic pigs that escaped after the Fukushima Daiichi nuclear power plant accident cause genetic contamination of the wild boar population? Japanese Journal of Conservation Ecology 23(1), 137–144. doi: https://doi.org/10.18960/hozen.23.1\ 137 Peakall, R. and Smouse, P. E. (2006). genalex 6: genetic analysis in Excel. Population genetic software for teaching and research. Molecular Ecology Notes 6(1), 288–295. doi: https://dx.doi.org/10.1111/j. 1471-8286.2005.01155.x Peakall, R. and Smouse, P. E. (2012). GenAlEx 6.5: genetic analysis in Excel. Population genetic software for teaching and research–an update. Bioinformatics 28(19), 2537–2539. doi: https://dx.doi.org/10.1093/ bioinformatics/bts460 Pierpaoli, M., Birò, Z. S., Herrmann, M., Hupe, K., Fernandes, M., Ragni, B., Szemethy, L., and Randi, E. (2003). Genetic distinction of wildcat (Felis silvestris) populations in Europe, and hybridization with domestic cats in Hungary. Molecular Ecology 12(10), 2585–2598. doi: 10.1046/j.1365-294x.2003. 01939.x Qi, X. B., Jianlin, H., Wang, G., Rege, J. E. O., and Hanotte, O. (2010). Assessment of cattle genetic introgression into domestic yak populations using mitochondrial and microsatellite DNA markers. Animal Genetics 41(3), 242–252. doi: https://dx.doi. org/10.1111/j.1365-2052.2009.01989.x Randi, E. (2008). Detecting hybridization between wild species and their domesticated relatives. Molecular Ecology 17(1), 285–293. doi: https://doi.org/10. 1111/j.1365-294X.2007.03417.x Rhymer, J. M. and Simberloff, D. (1996). Extinction by hybridization and introgression. Annual Review of Ecology and Systematics 27(1), 83–109. doi: https: //dx.doi.org/10.1146/annurev.ecolsys.27.1.83 Rohrer, G. A., Alexander, L. J., Keele, J. W., Smith, T. P., and Beattie, C. W. (1994). A microsatellite linkage map of the porcine genome. Genetics 136(1), 231– 245. Saito, M., Momose, H., and Mihira, T. (2011). Both environmental factors and countermeasures affect wild boar damage to rice paddies in Boso Peninsula, Japan. Crop Protection 30(8), 1048–1054. doi: https: //dx.doi.org/10.1016/j.cropro.2011.02.017 Scandura, M., Iacolina, L., Crestanello, B., Pecchioli, E., di Benedetto, M. F., Russo, V., Davoli, R., Apollonio, M., and Bertorelle, G. (2008). Ancient vs. recent processes as factors shaping the genetic variation of the European wild boar: are the effects of the last glaciation still detectable? Molecular Ecology 17(7), 1745–1762. doi: https://dx.doi.org/10.1111/j.1365- 294x.2008.03703.x Sharma, S., Dutta, T., Maldonado, J. E., Wood, T. C., Panwar, H. S., and Seidensticker, J. (2013). Spatial genetic analysis reveals high connectivity of tiger (Panthera tigris) populations in the Satpura-Maikal landscape of Central India. Ecology and Evolution 3(1), 48–60. doi: https://dx.doi.org/10.1002/ece3. 432 Smouse, P. E. and Peakall, R. (1999). Spatial autocorrelation analysis of individual multiallele and multilocus genetic structure. Heredity 82(5), 561– 573. doi: https://dx.doi.org/10.1038/sj.hdy.6885180 Tadano, R., Nagai, A., and Moribe, J. (2016). Local- scale genetic structure in the Japanese wild boar (Sus scrofa leucomystax): insights from autosomal microsatellites. Conservation Genetics 17(5), 1125– 1135. doi: https://dx.doi.org/10.1007/s10592-016- 0848-z Todesco, M., Pascual, M. A., Owens, G. L., Ostevik, K. L., Moyers, B. T., Hübner, S., Heredia, S. M., Hahn, M. A., Caseys, C., Bock, D. G., and Rieseberg, L. H. (2016). Hybridization and extinction. Evolutionary Applications 9(7), 892–908. doi: https://dx.doi.org/ 10.1111/eva.12367 Touma, S., Arakawa, A., and Oikawa, T. (2020). Evaluation of the genetic structure of indigenous Okinawa Agu pigs using microsatellite markers. Asian- Australasian Journal of Animal Sciences 33(2), 212– 218. doi: https://dx.doi.org/10.5713/ajas.19.0034 Uemura, Y., Yoshimi, S., and Hata, H. (2018). Hybridiza- tion between two bitterling fish species in their sympatric range and a river where one species is native and the other is introduced. PLoS One 13(9), e0203423. doi: https://doi.org/10.1371/ journal.pone.0203423 Vernesi, C., Crestanello, B., Pecchioli, E., Tartari, D., Caramelli, D., Hauffe, H., and Bertorelle, G. (2003). https://dx.doi.org/10.1002/ece3.5131 https://dx.doi.org/10.1002/ece3.5131 https://dx.doi.org/10.1002/jwmg.651 https://dx.doi.org/10.1002/jwmg.651 https://dx.doi.org/10.1111/age.12157 https://dx.doi.org/10.1111/age.12157 https://dx.doi.org/10.1038/sj.hdy.6800174 https://dx.doi.org/10.1038/sj.hdy.6800174 https://doi.org/10.18960/hozen.23.1\_137 https://dx.doi.org/10.1111/j.1471-8286.2005.01155.x https://dx.doi.org/10.1111/j.1471-8286.2005.01155.x https://dx.doi.org/10.1093/bioinformatics/bts460 https://dx.doi.org/10.1093/bioinformatics/bts460 https://doi.org/10.1046/j.1365-294x.2003.01939.x 10.1046/j.1365-294x.2003.01939.x https://dx.doi.org/10.1111/j.1365-2052.2009.01989.x https://dx.doi.org/10.1111/j.1365-2052.2009.01989.x https://doi.org/10.1111/j.1365-294X.2007.03417.x https://doi.org/10.1111/j.1365-294X.2007.03417.x https://dx.doi.org/10.1146/annurev.ecolsys.27.1.83 https://dx.doi.org/10.1146/annurev.ecolsys.27.1.83 https://dx.doi.org/10.1016/j.cropro.2011.02.017 https://dx.doi.org/10.1016/j.cropro.2011.02.017 https://dx.doi.org/10.1111/j.1365-294x.2008.03703.x https://dx.doi.org/10.1111/j.1365-294x.2008.03703.x https://dx.doi.org/10.1002/ece3.432 https://dx.doi.org/10.1002/ece3.432 https://dx.doi.org/10.1038/sj.hdy.6885180 https://dx.doi.org/10.1007/s10592-016-0848-z https://dx.doi.org/10.1007/s10592-016-0848-z https://dx.doi.org/10.1111/eva.12367 https://dx.doi.org/10.1111/eva.12367 https://dx.doi.org/10.5713/ajas.19.0034 https://doi.org/10.1371/journal.pone.0203423 https://doi.org/10.1371/journal.pone.0203423 Genetic Resources (2020), 1 (2), 29–41 Markers for pig and wild boar hybridization 41 The genetic impact of demographic decline and reintroduction in the wild boar (Sus scrofa): A microsatellite analysis. Molecular Ecology 12(3), 585– 595. doi: https://dx.doi.org/10.1046/j.1365-294x. 2003.01763.x Waithman, J. D., Sweitzer, R. A., Vuren, D. V., Drew, J. D., Brinkhaus, A. J., Gardner, I. A., and Boyce, W. M. (1999). Range Expansion, Population Sizes, and Management of Wild Pigs in California. The Journal of Wildlife Management 63(1), 298–298. doi: https://dx.doi.org/10.2307/3802513 Yang, B., Cui, L., Perez-Enciso, M., Traspov, A., Crooijmans, R. P. M. A., Zinovieva, N., Schook, L. B., Archibald, A., Gatphayak, K., Knorr, C., Triantafyllidis, A., Alexandri, P., Semiadi, G., Hanotte, O., Dias, D., Dovč, P., Uimari, P., Iacolina, L., Scandura, M., Groenen, M. A. M., Huang, L., and Megens, H.- J. (2017). Genome-wide SNP data unveils the globalization of domesticated pigs. Genetics Selection Evolution 49(1), 71–71. doi: https://dx.doi.org/10. 1186/s12711-017-0345-y https://dx.doi.org/10.1046/j.1365-294x.2003.01763.x https://dx.doi.org/10.1046/j.1365-294x.2003.01763.x https://dx.doi.org/10.2307/3802513 https://dx.doi.org/10.1186/s12711-017-0345-y https://dx.doi.org/10.1186/s12711-017-0345-y Introduction Materials and Methods Analysed samples and DNA extraction Microsatellite loci genotyping Characterization of microsatellite markers Results Discussion Data Availability Statement Author contributions Conflict of interest statement