Microsatellite genotyping and computational inference for genetic management of the Eurasian wild boar (Sus scrofa L., 1758): strengths, limitations, and integrative applications
6 affiliations
- 1Department of Microbiology and Immunobiology, Faculty of Biological Sciences, Kazimierz Wielki University, Bydgoszcz, Poland
- 2Doctoral School, Kazimierz Wielki University, Bydgoszcz, Poland
- 3Department of Veterinary Medicine, University of Sassari, Sassari, Italy
- 4National Biodiversity Future Center – NBFC, Palermo, Italy
- 5Department of Chemistry and Bioscience, Aalborg University, Aalborg, Denmark
- 6Department of Genetics, Faculty of Biological Sciences, Kazimierz Wielki University, Bydgoszcz, Poland
Abstract
Microsatellite markers, commonly referred to as short tandem repeats (STRs) or simple sequence repeats, have been extensively utilized in population genetic studies of the Eurasian wild boar (Sus scrofa L., 1758), particularly for assessing genetic diversity, population structure, connectivity, relatedness, and admixture with domestic pigs (Sus scrofa domesticus L., 1758). Despite the increasing availability of single nucleotide polymorphism (SNP)-based and whole-genome approaches, STR datasets remain valuable because of their high polymorphism, relatively low cost, and compatibility with legacy monitoring data. This review provides a critical synthesis of the use of microsatellite genotyping in wild boar research, with particular emphasis on the computational inference frameworks used to translate multi-locus genotypes into management-relevant information. We discuss the application of STR data to diversity and inbreeding metrics, clustering and assignment analyses, effective population size and bottleneck inference, parentage and kinship reconstruction, admixture detection, landscape genetics, and disease-related interpretation. Special emphasis is placed on the assumptions and limitations of microsatellite-based inference, including marker panel size and comparability, sampling design, allele binning, null alleles, genotyping error, allele-size homoplasy, and the temporal scale of interpretation. The review highlights that STRs provide substantial insights into recent and fine-scale population processes, regional monitoring, and preliminary admixture screening, whereas dense SNP panels or whole-genome data are required for precise introgression quantification, adaptive inference, complex demographic reconstruction, and deep phylogeographic analysis. Used within an integrative framework that combines genomic, landscape, epidemiological, and long-term monitoring data, STRs remain a cost-effective and informative component of genetic monitoring for S. scrofa across heterogeneous and human-modified landscapes.
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BibTeX
@article{lipa2026microsatellite,
title = {{Microsatellite genotyping and computational inference for genetic management of the Eurasian wild boar (Sus scrofa L., 1758): strengths, limitations, and integrative applications}},
author = {Wojciech Lipa and Laura Iacolina and Artur Dzialuk},
journal = {BioTechnologia},
year = {2026},
month = sep,
doi = {10.5114/bta/226392},
url = {https://doi.org/10.5114/bta/226392},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Microsatellite genotyping and computational inference for genetic management of the Eurasian wild boar (Sus scrofa L., 1758): strengths, limitations, and integrative applications
AU - Wojciech Lipa
AU - Laura Iacolina
AU - Artur Dzialuk
PY - 2026
DA - 2026/09/09
JO - BioTechnologia
DO - 10.5114/bta/226392
UR - https://doi.org/10.5114/bta/226392
AB - Microsatellite markers, commonly referred to as short tandem repeats (STRs) or simple sequence repeats, have been extensively utilized in population genetic studies of the Eurasian wild boar (Sus scrofa L., 1758), particularly for assessing genetic diversity, population structure, connectivity, relatedness, and admixture with domestic pigs (Sus scrofa domesticus L., 1758). Despite the increasing availability of single nucleotide polymorphism (SNP)-based and whole-genome approaches, STR datasets remain valuable because of their high polymorphism, relatively low cost, and compatibility with legacy monitoring data. This review provides a critical synthesis of the use of microsatellite genotyping in wild boar research, with particular emphasis on the computational inference frameworks used to translate multi-locus genotypes into management-relevant information. We discuss the application of STR data to diversity and inbreeding metrics, clustering and assignment analyses, effective population size and bottleneck inference, parentage and kinship reconstruction, admixture detection, landscape genetics, and disease-related interpretation. Special emphasis is placed on the assumptions and limitations of microsatellite-based inference, including marker panel size and comparability, sampling design, allele binning, null alleles, genotyping error, allele-size homoplasy, and the temporal scale of interpretation. The review highlights that STRs provide substantial insights into recent and fine-scale population processes, regional monitoring, and preliminary admixture screening, whereas dense SNP panels or whole-genome data are required for precise introgression quantification, adaptive inference, complex demographic reconstruction, and deep phylogeographic analysis. Used within an integrative framework that combines genomic, landscape, epidemiological, and long-term monitoring data, STRs remain a cost-effective and informative component of genetic monitoring for S. scrofa across heterogeneous and human-modified landscapes.
SN - 0860-7796
SN - 2353-9461
ER -