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Article

Molecular Tools for qPCR Identification and STR-Based Individual Identification of Panthera pardus (Linnaeus, 1758)

by
Karolina Mahlerová
1,2,3,*,
Lenka Vaňková
1,2 and
Daniel Vaněk
1,2,4,5,*
1
Institute for Environmental Studies, Charles University, 128 01 Prague, Czech Republic
2
Forensic DNA Service, 170 00 Prague, Czech Republic
3
Department of Ecology, Faculty of Environmental Sciences, Czech University of Life Sciences, 165 00 Prague, Czech Republic
4
Department of Legal Forensic Medicine, Bulovka University Hospital, 180 00 Prague, Czech Republic
5
Department of Forensic Medicine, Second Faculty of Medicine, Charles University, 120 00 Prague, Czech Republic
*
Authors to whom correspondence should be addressed.
Genes 2026, 17(1), 45; https://doi.org/10.3390/genes17010045
Submission received: 20 October 2025 / Revised: 5 December 2025 / Accepted: 10 December 2025 / Published: 31 December 2025
(This article belongs to the Special Issue Advances in Forensic Genetics and DNA)
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Versions Notes

Abstract

Background/Objectives The leopard (Panthera pardus), an apex predator listed in CITES Appendix I and classified as Vulnerable by the IUCN, is undergoing severe population declines driven by habitat loss, human–wildlife conflict, and illegal trade. Rapid and reliable species and individual identification is critical for conservation and forensic applications, particularly when analyzing highly processed or degraded seized wildlife products, where morphological identification is often impossible. We aimed to develop and validate a robust multiplex quantitative real-time PCR (qPCR) assay combined with a short tandem repeat (STR) system for the species-specific detection and individual identification of P. pardus. Methods The qPCR assay (Ppar Qplex) was designed to target a mitochondrial Cytochrome b (Cyt b) fragment for species confirmation, a nuclear marker (PLP) for general Feliformia detection and quantification, and an artificial internal positive control (IPC) to monitor PCR inhibition. The assay’s performance was validated for robustness, specificity, sensitivity, repeatability, and reproducibility, utilizing DNA extracted from 30 P. pardus individuals (hair and feces) and tested against 18 related Feliformia species and two outgroups. Individual identification was achieved using a set of 18 STR loci and a sex determination system adapted from previously published Panthera panels. Results Validation demonstrated high specificity for the Ppar Qplex: mitochondrial amplification occurred exclusively in P. pardus samples. The nuclear marker consistently amplified across all 18 tested Feliformia species but not the outgroups. The assay showed high analytical sensitivity, successfully detecting DNA at concentrations as low as 1 pg/µL, with consistent results confirmed across different sample types, replicates, and independent users. Furthermore, the STR multiplex successfully generated 30 unique individual profiles using the 18 polymorphic loci and the sex determination system. Conclusions The combined qPCR assay and STR system provide a fast, sensitive, and highly specific molecular framework for rapid leopard detection, quantification, and individual identification from a wide range of sample types. These tools strengthen forensic capacity to combat wildlife crime and provide critical data to support evidence-based conservation management of P. pardus. P. pardus, an apex predator listed in CITES Appendix I and classified as Vulnerable by the IUCN, is undergoing severe population declines driven by habitat loss, human–wildlife conflict, and illegal trade. Rapid and reliable identification of seized specimens is therefore critical for conservation and forensic applications, mainly when products are highly processed. We developed and validated a multiplex quantitative real-time PCR (qPCR) assay targeting the mitochondrial gene Cytochrome b (Cyt b) for species-specific detection. The assay was tested on verified leopard individuals and validated across 18 Feliformia and two outgroup species (Homo sapiens, Canis lupus familiaris). Analytical performance was assessed through robustness, specificity, sensitivity, repeatability, and reproducibility. Mitochondrial amplification occurred exclusively in leopard samples, while nuclear markers amplified consistently across Feliformia but not in outgroup species. The assay’s limit of DNA detection is 1 pg/µL and produces consistent results across replicates, tested types of samples (hair, feces), and independent users, with internal controls confirming the absence of inhibition. In addition, we present the results of successful individual identification using the set of 18 STR loci and the sex determination system. The developed qPCR and STR systems provide a fast, sensitive, and specific solution for leopard detection and quantification, reinforcing forensic efforts against wildlife crime and supporting conservation of P. pardus.

1. Introduction

The leopard (P. pardus), an apex predator with a wide distribution across Africa and Asia, is listed in Appendix I of the Convention on International Trade in Endangered Species of Wild Fauna and Flora (CITES) and classified as Vulnerable by the International Union for Conservation of Nature (IUCN) [1,2,3]. There are eight recognized subspecies of P. pardus—Panthera pardus pardus (Sub-Saharan Africa), P. p. fusca (Indian subcontinent), P. p. melas (Java, Indonesia), P. p. nimr (Arabian Peninsula), P. p. saxicolor (syn. tulliana; Turkey, Iran, Caucasus region), P. p. orientalis (Russian Far East, Northeastern China), P. p. kotiya (Sri Lanka), and P. p. delacouri (Mainland Southeast Asia) [4].
Despite its broad range of geographical distribution and ecological versatility, inhabiting environments from grassland plains and deserts to alpine areas and even the fringes of large cities [1,5,6,7,8], the species is undergoing substantial population declines, consequently leading to a patchier distribution of the previously continuous area of distribution [1,7]. The decline is driven by a combination of factors, including habitat loss and fragmentation, human–wildlife conflict, prey depletion, and the pressures associated with expanding human populations [9,10,11,12]. Furthermore, like other Panthera species (Panthera tigris, P. leo, P. onca, P. uncia) also listed in Appendix I [2], leopards are impacted by overharvesting and illegal wildlife trade [11]. Their body parts are exploited for ceremonial use, traditional Chinese medicine (TCM) [2,13,14,15,16,17], and poorly managed trophy hunting [18]. These threats remain active and pervasive, with little evidence of mitigation, suggesting a continued risk of population decline without targeted conservation interventions [1,6]. Illegal trade represents a significant but poorly quantified threat to leopard populations. It is estimated that 4500–7000 individuals are harvested annually for their skins, which are widely used in traditional and cultural regalia, particularly in parts of Africa [19]. Approximately 5000 skins, carcasses, stuffed, and live leopards were seized across Asia from 2000 to 2018 [20]. Leopard bones increasingly substitute for tiger bones in traditional Asian medicine, and claws and teeth are traded as amulets or curios, highlighting the species’ exploitation across multiple markets [21,22].
Moreover, leopards represent the most frequently reported carnivore involved in human–wildlife conflict globally; their broad ecological niche and adaptability, including a flexible diet and tolerance of human presence, make them particularly prone to conflict with people, as they readily prey on livestock and occasionally threaten human safety [23,24,25,26,27]. This adaptability, which enables leopards to utilize agricultural lands and even urban environments more than any other large carnivore [1,7], further increases exposure to anthropogenic threats, including conflict-driven persecution and illegal hunting for trade. Therefore, rapid and reliable identification of leopards is essential for both conservation research and forensic investigations aimed at combating wildlife crime.
Traditional species and individual identification approaches have relied on morphological traits, such as coat pattern recognition from camera-trap images, pugmark analysis, or morphometric assessment of skulls, claws, hair, and teeth [28,29,30,31,32,33,34,35,36]. While these methods have proven valuable for ecological and conservation monitoring, including population estimation and movement tracking [35,37], they are limited when applied to confiscated wildlife products, which often consist of isolated or processed parts such as powders, bone parts, or TCM [21,22,38,39]. Molecular tools offer robust alternatives while also supporting and enhancing traditional approaches [40]. Mitochondrial DNA barcoding (e.g., Cyt b, COI, 16S) has been extensively used to confirm species identity from degraded or processed samples [40,41,42,43]. The DNA barcodes target standardized regions with interspecific variability exceeding intraspecific variability, enabling species discrimination through comparison with reference databases such as GenBank or the Barcode of Life Data System [40,41,42]. Furthermore, nuclear markers such as microsatellites (STRs) and single-nucleotide polymorphisms (SNPs) allow not only species confirmation but also individual identification, population assignment, and geographic origin tracing [21]. Such molecular approaches are now standard in wildlife forensics and conservation genetics, providing critical evidence in law enforcement and a foundation for effective population management.
Real-time quantitative PCR (qPCR) is a potent tool for wildlife forensics, offering rapid, sensitive, and cost-efficient species detection [44,45,46]. Previous leopard assays have relied on end-point PCR without DNA quantification, lacked inhibition controls [45], and often used amplicons too large for degraded forensic samples [47,48,49], limiting their applicability. We developed a multiplex qPCR assay specifically for P. pardus that combines mitochondrial DNA amplification for species confirmation, combined with a nuclear DNA marker for broader detection of Feliformia. The assay is enabling reliable detection from low-concentration samples while simultaneously assessing sample quality through the inclusion of an internal positive control (IPC) and quantity for downstream analyses. The assay is complemented by an individual identification STR system based on 14 nuclear loci and a sex determination system, extending its application beyond species confirmation to population-level monitoring and utilizing already existing Panthera genus multiplexes. Together, these tools provide a robust framework for rapid, specific, and sensitive leopard identification, enhancing the capacity to investigate illegal trade and supporting evidence-based conservation management of P. pardus.

2. Materials and Methods

2.1. Specimens Used for the Analyses

The development of a quantification system using real-time PCR and STR plex was tested on 30 P. pardus individuals (18 females and 12 males) using hair samples. Eight samples came from P. p. kotiya, three from P. p. orientalis, and two from P. p. saxicolor. The remaining analyzed samples were marked as P. pardus without any subspecies information. Furthermore, the real-time PCR quantification plex (Ppar Qplex) was tested for specificity on an additional 18 species of Feliformia (Acinonyx jubatus, Caracal caracal, Cryptoprocta ferox, Civettictis civetta, Felis catus, Herpailurus yagouaroundi, Leopardus tigrinus, Leopardus weidii, Leptailurus serval, Lynx lynx, Lynx rufus, Otocolobus manual, Panthera leo, Panthera onca, Panthera tigris, Panthera uncia, Prionailurus bengalensis, and Puma concolor) (source material hair and feces). Hair and feces samples were provided by the Czech zoological gardens and the Czech Environmental Inspectorate. The protection of animals used for scientific purposes, as stated by Directive 2010/63/EU of the European Parliament and of the Council of 22 September 2010, was fully respected. No animal was harmed for the purpose of sample collection. Hair samples were stored dry at ambient temperature before DNA extraction, and feces were stored in DNA/RNA Shield (Zymo Research, Irvine, CA, USA). DNA was extracted from fecal and hair samples using the Quick-DNA Microprep Plus Kit (Zymo Research, USA) following the manufacturer’s protocol. The extracted DNA was quantified using Qubit 4 Fluorometer (ThermoFisher Scientific, Waltham, MA, USA) prior to further analysis.

2.2. Quantification System and Species Identification (Ppar Qplex)

Species-specific primers targeting the mtDNA fragment of Cyt b of P. pardus were manually designed using BioEdit [50] from publicly available sequences of 16 species of Feliformia, including five individuals of P. pardus obtained from NCBI [51,52] and tested against NCBI BLASTn, web interface [53]. The TaqMan probe was manually designed using Primer Express v3.0.1 (ThermoFisher Scientific, Waltham, MA, USA) and tested against NCBI BLAST [53] for specificity. The existing Llyn Qplex [46] was adapted to create the P. pardus-specific qPCR multiplex by replacing the mitochondrial target with a newly designed Cyt b primer–probe set. The P. pardus specific primers and TaqMan probe were evaluated alongside the original Feliformia-specific nuclear marker (PLP) and internal positive control (IPC) primers and TaqMan probes using the Multiple Primer Analyzer tool (Thermo Fisher Scientific, Waltham, MA, USA) to detect potential primer–dimer interactions prior to multiplex optimization (Table 1). The mitochondrial Cyt b gene was selected as the assay target due to its high interspecific variability, strong phylogenetic signal within mammals, and demonstrated suitability for forensic species identification from degraded DNA [54,55].
The qPCR reaction was performed in a total volume of 10 μL consisting of 5 μL of 2× TaqMan Multiplex Master Mix (ThermoFisher Scientific, Waltham, MA, USA), 0.5 μL of 20× qPpar mtDNA Assay mix, 0.5 μL of 20× qPpar nDNA Assay mix, 0.5 μL of 20× qPpar IPC [46], 1 μL of IPC 0.1 pg/μL, 1.5 μL of DNase/RNase-Free Water (Zymo Research, Irvine, CA, USA), and 1 μL of DNA template. Amplification was conducted on QuantStudio™ 5 Real-Time PCR System (ThermoFisher Scientific, Waltham, MA, USA) under the following cycling conditions: 95 °C 20 s; 50× 95 °C 10 s; 60 °C 25 s. The data were analyzed using Design & Analysis Software v2.8.0 (ThermoFisher Scientific, Waltham, MA, USA). Each run included a positive control (a selected individual of P. pardus used consistently across all test runs), a negative control consisting of DNase/RNase-Free Water (Zymo Research, Irvine, CA, USA), and other Feliformia species to test specificity. All reactions were performed in technical duplicates per sample to ensure reproducibility.

2.3. Validation of the Ppar Qplex

The validation of the Ppar Qplex assay included assessments of robustness, specificity, sensitivity, repeatability, and reproducibility. Robustness was evaluated by modifying the annealing temperature. Specificity was tested across 20 species. Sensitivity was assessed using a dilution series of P. pardus DNA. Repeatability was evaluated using multiple individuals of P. pardus, and reproducibility was examined by comparing assay performance between two laboratory technicians.

2.4. STRplex Design and Individual Identification

DNA profiles of P. pardus individuals were generated using multiplex STR panels and allelic ladders originally designed for P. tigris [56] and P. leo [57]. The original STR marker nomenclature was retained to maintain consistency and clarity, with “Ptig” denoting loci derived from the P. tigris panel and “Pleo” for those from the P. leo panel. The PCR amplification conditions and capillary electrophoresis parameters closely followed previously published protocols for both P. tigris and P. leo [56,57]. Fragment analysis was conducted via capillary electrophoresis using the SeqStudio™ 3200 Genetic Analyzer System (ThermoFisher Scientific, USA). The data were subsequently analyzed using the genotyping software GeneMapper v5 (ThermoFisher Scientific, USA). Each run included a positive control (a selected individual of P. pardus used consistently across all test runs) and a negative control consisting of DNase/RNase-Free Water (Zymo Research, USA).

3. Results

3.1. Quantification and Species Identification

P. pardus was identified using quantitative real-time PCR using the Ppar Qplex. Amplification of a 164 bp fragment of the mitochondrial Cyt b gene (red curve) confirmed the presence of P. pardus DNA in the sample. Amplification of a 132 bp Feliformia fragment of the proteolipid protein (PLP) gene (blue curve) provides broader taxonomic confirmation. The internal positive control (IPC), a synthetic 261 bp fragment, was detected via the green curve and confirmed reaction integrity while flagging potential PCR inhibition (Figure 1). Concurrent amplification of all three targets (Figure 1) confirms species identity, taxonomic relevance, and sample quality. Furthermore, DNA was quantified using the Ppar Qplex quantification system based on four standards: S1: 0.06 ng/μL nDNA; S2: 0.012 ng/μL nDNA, S3: 0.0024 ng/μL nDNA; and S4: 0.00048 ng/μL nDNA.

3.2. Results of Validation of the Ppar Qplex

3.2.1. Robustness

Modifying the annealing temperature tested the assay’s robustness. The optimal temperature was 60 °C. Deviations of ±2 °C did not result in failure, and all targets (Cyt b, PLP, IPC) were amplified. Deviations greater than ±4 °C failed to amplify targets, demonstrating the assay’s thermal sensitivity.

3.2.2. Specificity

All samples were diluted to 1 ng/µL and tested across 20 species. Nuclear DNA amplification was observed exclusively in Feliformia species (18 tested species), with no amplification in outgroup species (H. sapiens, C. l. familiaris). Mitochondrial DNA was amplified solely in Panthera pardus, confirming the high specificity of the mtDNA primers; nDNA was amplified across all Feliformia species and was not amplified in the two outgroup species.

3.2.3. Sensitivity

DNA extracted from P. pardus was diluted to concentrations of 1 pg/µL, 10 pg/µL, 100 pg/µL, and 1 ng/µL. Both mitochondrial and nuclear markers, as well as an internal positive control, were successfully amplified across all dilutions. Analytical sensitivity was further evaluated using serial dilutions (1 pg/µL, 10 pg/µL, and 100 pg/µL) of DNA from eight related species (A. jubatus, C. caracal, F. catus, L. serval, L. lynx, P. leo, P. tigris, and P. concolor). Amplification of nDNA was successful across all concentrations.

3.2.4. Repeatability

Assay repeatability was assessed using DNA extracts from 4 P. pardus individuals tested in triplicate. All replicates, including negative controls, showed consistent results, confirming assay repeatability.

3.2.5. Reproducibility

The assay was independently performed by two laboratory technicians using the same set of 10 samples. Results were consistent across all runs, verifying reproducibility across users and sessions.

3.3. Individual Identification

In total, 30 individuals were analyzed using the STR multiplex assays [56,57], resulting in 30 unique STR profiles. Each profile consisted of 18 variable polymorphic loci (Figure 2 and Figure 3) and a sex determination system. The statistical evaluation was done using software STRAF, v2.2.2 [58]. Allele frequencies and full forensic parameters are provided in Supplementary Materials S1 and S2 (SM_S1, SM_S2).
The optimal DNA input concentration for STR-based individual analysis was determined to be ~10 pg of nDNA (example DNA profile of male P. pardus is shown in Figure 4, and the corresponding alleles are shown in Table 2). Four STR loci (Ptig15, Ptig18, Ptig8, and Ptig11) were found to be monomorphic, yielding alleles 11.1, 3, 6.1, and 15, respectively, in all tested individuals. Additionally, P. p. kotiya subspecies yielded monomorphic status in STR loci Ptig6 (allele 8) and Pleo2 (allele 13). Furthermore, Table 3 presents the repeat structure and flanking-region differences between allele 7 of P. tigris and allele 6.1 of P. pardus. Notably, the P. pardus allele contains a single-base insertion in the 3′ flanking region, which was consistently detected in all sequenced individuals (n = 12).

4. Discussion

Reliable species and individual identification are fundamental to species protection. In case of the leopard, the urgency is heightened due to the declining trend of the overall population, causing patchier distribution, their involvement in human–wildlife conflict, and the continuing demand for body parts in the illegal wildlife trade. Leopards are among the most exploited felids globally, with thousands of skins, bones, and derivatives estimated to enter the illegal market annually, as the species is of growing forensic concern due to the substitution of its bones for tiger in TCM [11,13,14,19,20,21,22,23].
Traditional morphological approaches are often ineffective for identifying processed wildlife products, where molecular tools provide a valuable and reliable complementary solution for forensic species identification [21,38,39]. For instance, combining morphological analyses of hair with molecular identification can improve the ability of forensic experts to provide evidence provide species-level evidence in support of justice and more effectively combat wildlife crime [28]. In the case of leopards, molecular identification has previously been attempted using species-specific primers [48,49,59,60]. However, some of these assays have proven unreliable [49], and the reliance on species-specific amplicons larger than 220 bp [48,49] is problematic, particularly when working with forensic or wildlife monitoring samples that are often low-yielding or highly degraded. Another limitation of published species-specific primers is the testing of specificity beyond sympatrically occurring species [60].
The Ppar Qplex developed in this study addresses key challenges in the forensic analysis of seized wildlife products, which frequently yield low amounts of DNA and are tested across 18 Feliformia species and 2 outgroup species. The Ppar Qplex assay targets fragments of Cyt b (164 bp), enabling species-level identification of P. pardus with high specificity even from limited template material, while the Feliformia-targeted nuclear marker provided accurate DNA quantification, essential for reliable downstream genotyping. Including an artificial internal positive control further enhanced assay performance by detecting PCR inhibition, a common issue in degraded or processed samples such as hides, hair, or powdered bone. Moreover, the presented STR multiplex demonstrates high sensitivity and robustness across various conditions, and the assay provides a strong foundation for forensic casework. While there is a multiplex qPCR assay available that differentiates between several species of Feliformia, including P. tigris, P. leo, P. pardus, and A. jubatus based on melting temperatures [45], this system is unable to detect low quantity/quality template DNA and is unable to quantify the presented sample. Comparable amplification-based qPCR assays have been successfully applied to lion and tiger bones [44] and lynx feces [46]. Our adaptation of amplification-based quantitative real-time PCR extends this approach to leopard, enabling species confirmation and DNA quantification. Beyond law enforcement, a rapid, simple, species-specific, and individual identification tool can help with leopard monitoring and detection from low-yielding, degraded, and mixed samples. Expanding toward source materials such as scent marks, scats, or urine detected in the wild is beneficial for species conservation and monitoring, as proven in species such as P. tigris [61]. However, the dataset of tested degraded samples remains limited; although fecal samples were included, which are typically considered degraded DNA sources due to fragmentation, inhibitors, and environmental exposure, future validation on a wider range of highly degraded wildlife products would further strengthen the assay’s forensic applicability.
In addition to the qPCR system, we demonstrate the applicability of the Pleo STRplex [57] and Ptig STRplex [56] kits as robust genetic tools for conservation and forensic applications within the genus Panthera, which includes lions, tigers, jaguars, and leopards. This broad utility is due to the kits targeting specific short tandem repeats (STRs) that are conserved across these species, although some loci exhibit limited variability due to monomorphic status. The degree of monomorphism can vary across Panthera species and subspecies [57]. For example, P. p. kotiya has shown monomorphic status at two additional STR loci, which remain polymorphic in other P. pardus subspecies. This likely reflects the effects of long-term geographic isolation and reduced genetic diversity associated with the endemic status of the Sri Lankan leopard [62].
Importantly, universal STR marker kits provide a substantial advantage over species-specific DNA assays. Their cross-species utility enables reliable analysis even when the exact species origin of a sample is unknown, streamlining laboratory workflows and broadening their applicability [46,56,57,63,64]. This is particularly valuable in forensic science (e.g., identifying individuals from confiscated wildlife products such as tiger bones or leopard skins without prior species knowledge) [65], conservation genetics as shown on other Panthera species [66] (e.g., assessing population structure and genetic diversity to guide conservation strategies), and zoological research (e.g., confirming species identity or investigating parentage in captive breeding programs [67]). By enabling efficient and cost-effective testing across a broader spectrum of samples, these universal STR multiplexes transform the analytical process and establish themselves as powerful tools for genetic research and conservation within the genus Panthera.

5. Conclusions

The presented multiplex qPCR assay and STR system provide a robust framework for addressing the intertwined challenges of species protection, wildlife conflict, and wildlife trade. By enabling both species and individual identification from a wide range of sample types, including low-yielding samples, these tools strengthen law enforcement capacity, support conservation monitoring, and ultimately contribute to the survival of P. pardus.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/genes17010045/s1, SM_S1: forensic parameters; SM_S2: allele frequencies.

Author Contributions

Conceptualization: D.V. and L.V.; methodology: D.V., L.V. and K.M.; validation: K.M. and L.V.; formal analysis: K.M., L.V. and D.V.; data curation: K.M. and L.V.; writing—original draft preparation: K.M., L.V. and D.V.; writing—review and editing: L.V., K.M. and D.V.; visualization: L.V. and K.M.; supervision: D.V. and L.V. All authors have read and agreed to the published version of the manuscript.

Funding

The Ministry of the Interior of the Czech Republic supported this work through the Program Strategic Support for the Development of Security Research 2019–2025 (IMPAKT 1) [grant number VJ01010026].

Institutional Review Board Statement

Not applicable. This study did not involve live animals or humans. Hair and fecal samples were obtained from the Czech zoological gardens and the Czech Environmental Inspectorate, in accordance with Directive 2010/63/EU on the protection of animals used for scientific purposes.

Informed Consent Statement

Not applicable.

Data Availability Statement

The data presented in this study are available upon request from the corresponding author due to the funding agency’s request.

Acknowledgments

Hair and fecal samples were obtained from the Czech Environmental Inspectorate and the following zoological gardens.

Conflicts of Interest

The authors declare that they have no conflicts of interest.

References

  1. Stein, A.B.; Athreya, V.; Gerngross, P.; Balme, G.; Henschel, P.; Karanth, U.; Miquelle, D.; Rostro-Garcia, S.; Kamler, J.F.; Laguardia, A.; et al. The IUCN Red List of Threatened Species: Panthera pardu; The IUCN Red List of Threatened Species™. 2020, e.T15954A163991139. Available online: https://dx.doi.org/10.2305/IUCN.UK.2020-1.RLTS.T15954A163991139.en (accessed on 1 September 2025).
  2. CITES Appendices I, II and III. Convention on International Trade in Endangered Species of Wild Fauna and Flora. Available online: https://cites.org/eng/app/appendices.php (accessed on 1 September 2025).
  3. IUCN The IUCN Red List of Threatened Species, Version 2024-3. Available online: https://www.iucnredlist.org (accessed on 1 September 2025).
  4. Kitchener, A.; Breitenmoser, C.; Eizirik, E.; Gentry, A.; Werdelin, L.; Wilting, A.; Yamaguchi, N.; Abramov, A.; Christiansen, P.; Driscoll, C.; et al. A Revised Taxonomy of the Felidae: The Final Report of the Cat Classification Task Force of the IUCN/SSC Cat Specialist Group. Cat News 2017, 80. Available online: https://repository.si.edu/handle/10088/32616 (accessed on 1 September 2025).
  5. Nowell, K.; Jackson, P. Wild Cats—Status Survey and Conservation Action Plan; IUCN: Gland, Switzerland, 1996; ISBN 2-8317-0045-0. [Google Scholar]
  6. Ministry of Environment and Tourism (MET). Botswana National Leopard (Panthera pardus) Management and Action Plan 2024–2034; Ministry of Environment and Tourism (MET): Windhoek, Namibia, 2024; p. 65. Available online: https://cites.org/sites/default/files/documents/E-AC33-Inf-22_0.pdf (accessed on 1 September 2025).
  7. Jacobson, A.P.; Gerngross, P.; Lemeris, J.R., Jr.; Schoonover, R.F.; Anco, C.; Breitenmoser-Würsten, C.; Durant, S.M.; Farhadinia, M.S.; Henschel, P.; Kamler, J.F.; et al. Leopard (Panthera pardus) Status, Distribution, and the Research Efforts across Its Range. PeerJ 2016, 4, e1974. [Google Scholar] [CrossRef] [PubMed]
  8. Green, R. Wild Cat Species of the World; Basset Publications: Plymouth, UK, 1991; ISBN 0-946873-93-3. [Google Scholar]
  9. Selvan, K.M.; Lyngdoh, S.; Habib, B.; Gopi, G.V. Population Density and Abundance of Sympatric Large Carnivores in the Lowland Tropical Evergreen Forest of Indian Eastern Himalayas. Mamm. Biol. 2014, 79, 254–258. [Google Scholar] [CrossRef]
  10. Thorn, M.; Green, M.; Scott, D.; Marnewick, K. Characteristics and Determinants of Human-Carnivore Conflict in South African Farmland. Biodivers. Conserv. 2013, 22, 1715–1730. [Google Scholar] [CrossRef]
  11. Datta, A.; Anand, M.O.; Naniwadekar, R. Empty Forests: Large Carnivore and Prey Abundance in Namdapha National Park, North-East India. Biol. Conserv. 2008, 141, 1429–1435. [Google Scholar] [CrossRef]
  12. Hatton, J.; Couto, M.; Oglethorpe, J. Biodiversity and War: A Case Study of Mozambique; Biodiversity Support Program: Washington, DC, USA, 2017; ISBN 0099002280. [Google Scholar]
  13. Williams, V.L.; Loveridge, A.J.; Newton, D.J.; Macdonald, D.W. A Roaring Trade? The Legal Trade in Panthera leo Bones from Africa to East-Southeast Asia. PLoS ONE 2017, 12, e0185996. [Google Scholar] [CrossRef]
  14. Williams, V.; Newton, D.; Loveridge, A.; Macdonald, D. Bones of Conection: An Assessment of the South African Trade in African Lion Panthera leo Bones and Other Body Parts; TRAFFIC: Cambridge, UK, 2015; p. 128. [Google Scholar]
  15. Balme, G.; Rogan, M.; Thomas, L.; Pitman, R.; Mann, G.; Whittington-Jones, G.; Midlane, N.; Broodryk, M.; Broodryk, K.; Campbell, M.; et al. Big Cats at Large: Density, Structure, and Spatio-temporal Patterns of a Leopard Population Free of Anthropogenic Mortality. Popul. Ecol. 2019, 61, 256–267. [Google Scholar] [CrossRef]
  16. Li, J.; Lu, Z. Snow Leopard Poaching and Trade in China 2000–2013. Biol. Conserv. 2014, 176, 207–211. [Google Scholar] [CrossRef]
  17. Wong, R.; Krishnasamy, K. Skin and Bones Unresolved: An Analysis of Tiger Seizures from 2000–2018; Southeast Asia Regional Office: Petaling Jaya, Selangor, Malaysia, 2019. [Google Scholar]
  18. Balme, G.A.; Slotow, R.; Hunter, L.T.B. Impact of Conservation Interventions on the Dynamics and Persistence of a Persecuted Leopard (Panthera pardus) Population. Biol. Conserv. 2009, 142, 2681–2690. [Google Scholar] [CrossRef]
  19. Stein, A.B.; Athreya, V.; Society, W.C.; Gerngross, P.; Balme, G. Panthera Pardus. The IUCN Red List of Threatened Species 2016 Red List Assessment Assessment Information. 2016. Available online: https://www.iucnredlist.org/species/pdf/163991139 (accessed on 1 September 2025).
  20. Environmental Investigative Agency (EIA). Down to the Bone: China’s Alarming Trade in Leopard Bones; Environmental Investigative Agency (EIA): Washington, DC, USA, 2018; pp. 1–8. [Google Scholar]
  21. Karmacharya, D.; Sherchan, A.M.; Dulal, S.; Manandhar, P.; Manandhar, S.; Joshi, J.; Bhattarai, S.; Bhatta, T.R.; Awasthi, N.; Sharma, A.N.; et al. Species, Sex and Geo-Location Identification of Seized Tiger (Panthera tigris tigris) Parts in Nepal—A Molecular Forensic Approach. PLoS ONE 2018, 13, e0201639. [Google Scholar] [CrossRef]
  22. Alves, R.R.N.; Pinto, L.C.L.; Barboza, R.R.D.; Souto, W.M.S.; Oliveira, R.E.M.C.C.; Vieira, W.L.S. A Global Overview of Carnivores Used in Traditional Medicines. In Animals in Traditional Folk Medicine; Springer: Berlin/Heidelberg, Germany, 2013; pp. 171–206. [Google Scholar]
  23. Kesch, M.K.; Bauer, D.T.; Loveridge, A.J. Break on Through to the Other Side: The Effectiveness of Game Fencing to Mitigate Human—Wildlife Conflict. Afr. J. Wildl. Res. 2015, 45, 76. [Google Scholar] [CrossRef]
  24. Seoraj-Pillai, N.; Pillay, N. A Meta-Analysis of Human–Wildlife Conflict: South African and Global Perspectives. Sustainability 2016, 9, 34. [Google Scholar] [CrossRef]
  25. Woodroffe, R.; Thirgood, S.; Rabinowitz, A. The Impact of Human–Wildlife Conflict on Natural Systems. In People and Wildlife; Woodroffe, R., Thirgood, S., Rabinowitz, A., Eds.; Cambridge University Press: Cambridge, UK, 2005; pp. 1–12. [Google Scholar]
  26. Kissui, B.M. Livestock Predation by Lions, Leopards, Spotted Hyenas, and Their Vulnerability to Retaliatory Killing in the Maasai Steppe, Tanzania. Anim. Conserv. 2008, 11, 422–432. [Google Scholar] [CrossRef]
  27. Marker, L.L.; Dickman, A.J. Factors Affecting Leopard (Panthera pardus) Spatial Ecology, with Particular Reference to Namibian Farmlands. Afr. J. Wildl. Res. 2005, 35, 105–115. [Google Scholar]
  28. Tremori, T.M.; Antonio, L.U.; Godoy Cardena, M.M.S.; Gwinnett, C.; Davidson, A.; do Amaral, J.B.; Fridman, C.; Rocha, N.S. Forensic Genetics Associated with Hair Analysis as a Tool for Jaguar (Panthera onca) Identification. Glob. Ecol. Conserv. 2024, 52, e02956. [Google Scholar] [CrossRef]
  29. Pavithra, R.; Thunnisa, A.M.; Vasanthakumari, D.; Udhayan, A. Unveiling a Novel Morphometric Approach in Claws and Canines for Species Discrimination and Age Stratification in Leopard (Panthera pardus fusca). Sci. Nat. 2025, 112, 4. [Google Scholar] [CrossRef]
  30. Miththapala, S.; Seidensticker, J.; Phillips, L.G.; Fernando, S.B.U.; Smallwood, J.A. Identification of Individual Leopards (Panthera pardus kotiya) Using Spot Pattern Variation. J. Zool. 1989, 218, 527–536. [Google Scholar] [CrossRef]
  31. Wattegedera, M.; Silva, D.; Sooriyabandara, C.; Wimaladasa, P.; Siriwardena, R.; Piyasena, M.; Marasinghe, R.M.S.L.R.P.; Hathurusinghe, B.M.; Nilanthi, R.M.R.; Gunawardena, S.; et al. A Multi-Point Identification Approach for the Recognition of Individual Leopards (Panthera pardus kotiya). Animals 2022, 12, 660. [Google Scholar] [CrossRef]
  32. Margaret, E. Sims Cranial Morphology of Five Felids: Acinonyx jubatus, Panthera onca, Panthera pardus, Puma concolor, Uncia uncia. Russ. J. Theriol. 2012, 11, 157–170. [Google Scholar]
  33. Knecht, L. The Use of Hair Morphology in the Identification of Mammals. In Wildlife Forensics; Wiley: Hoboken, NJ, USA, 2011; pp. 129–143. [Google Scholar]
  34. Picek, L.; Belotti, E.; Bojda, M.; Bufka, L.; Cermak, V.; Dula, M.; Dvorak, R.; Hrdy, L.; Jirik, M.; Kocourek, V.; et al. CzechLynx: A Dataset for Individual Identification and Pose Estimation of the Eurasian Lynx. arXiv 2025, arXiv:2506.04931. [Google Scholar] [CrossRef]
  35. Sharma, S.; Jhala, Y.; Sawarkar, V.B. Identification of Individual Tigers (Panthera tigris) from Their Pugmarks. J. Zool. 2005, 267, 9–18. [Google Scholar] [CrossRef]
  36. Lang, A.J.; Engler, T.; Martin, T. Dental Topographic and Three-dimensional Geometric Morphometric Analysis of Carnassialization in Different Clades of Carnivorous Mammals (Dasyuromorphia, Carnivora, Hyaenodonta). J. Morphol. 2022, 283, 91–108. [Google Scholar] [CrossRef] [PubMed]
  37. Karanth, K.U. Estimating Tiger Panthera Tigris Populations from Camera-Trap Data Using Capture—Recapture Models. Biol. Conserv. 1995, 71, 333–338. [Google Scholar] [CrossRef]
  38. Mondol, S.; Kumar, N.S.; Gopalaswamy, A.; Sunagar, K.; Karanth, K.U.; Ramakrishnan, U. Identifying Species, Sex and Individual Tigers and Leopards in the Malenad-Mysore Tiger Landscape, Western Ghats, India. Conserv. Genet. Resour. 2015, 7, 353–361. [Google Scholar] [CrossRef]
  39. Mondol, S.; Sridhar, V.; Yadav, P.; Gubbi, S.; Ramakrishnan, U. Tracing the Geographic Origin of Traded Leopard Body Parts in the Indian Subcontinent with DNA-based Assignment Tests. Conserv. Biol. 2015, 29, 556–564. [Google Scholar] [CrossRef]
  40. Hebert, P.D.N.; Cywinska, A.; Ball, S.L.; DeWaard, J.R. Biological Identifications through DNA Barcodes. Proc. R. Soc. Lond. B Biol. Sci. 2003, 270, 313–321. [Google Scholar] [CrossRef]
  41. Dawnay, N.; Ogden, R.; McEwing, R.; Carvalho, G.R.; Thorpe, R.S. Validation of the Barcoding Gene COI for Use in Forensic Genetic Species Identification. Forensic Sci. Int. 2007, 173, 1–6. [Google Scholar] [CrossRef]
  42. Mitani, T.; Akane, A.; Tokiyasu, T.; Yoshimura, S.; Okii, Y.; Yoshida, M. Identification of Animal Species Using the Partial Sequences in the Mitochondrial 16S rRNA Gene. Leg. Med. 2009, 11, S449–S450. [Google Scholar] [CrossRef]
  43. Hsieh, H.-M.; Chiang, H.-L.; Tsai, L.-C.; Lai, S.-Y.; Huang, N.-E.; Linacre, A.; Lee, J.C.-I. Cytochrome b Gene for Species Identification of the Conservation Animals. Forensic Sci. Int. 2001, 122, 7–18. [Google Scholar] [CrossRef]
  44. Vankova, L.; Vanek, D. DNA-Based Identification of Big Cats and Traditional Chinese Medicine Artifacts in the Czech Republic. Forensic Sci. Int. Genet. Suppl. Ser. 2022, 8, 122–124. [Google Scholar] [CrossRef]
  45. Henger, C.S.; Straughan, D.J.; Xu, C.C.Y.; Nightingale, B.R.; Kretser, H.E.; Burnham-Curtis, M.K.; McAloose, D.; Seimon, T.A. A New Multiplex qPCR Assay to Detect and Differentiate Big Cat Species in the Illegal Wildlife Trade. Sci. Rep. 2023, 13, 9796. [Google Scholar] [CrossRef]
  46. Mahlerová, K.; Alaverdyan, J.; Vaňková, L.; Vaněk, D. Molecular Tools for Lynx Spp. qPCR Identification and STR-Based Individual Identification of Eurasian Lynx (Lynx lynx) in Forensic Casework. Methods Protoc. 2025, 8, 47. [Google Scholar] [CrossRef]
  47. Cao, J.; Xu, J.; Liu, R.; Yu, K.; Wang, C. Specific PCR Detection of Tiger, Leopard, and Lion Ingredients from Test Samples. J. AOAC Int. 2011, 94, 1200–1205. [Google Scholar] [CrossRef] [PubMed]
  48. Mukherjee, N.; Mondol, S.; Andheria, A.; Ramakrishnan, U. Rapid Multiplex PCR Based Species Identification of Wild Tigers Using Non-Invasive Samples. Conserv. Genet. 2007, 8, 1465–1470. [Google Scholar] [CrossRef]
  49. Maroju, P.A.; Yadav, S.; Kolipakam, V.; Singh, S.; Qureshi, Q.; Jhala, Y. Schrodinger’s Scat: A Critical Review of the Currently Available Tiger (Panthera tigris) and Leopard (Panthera pardus) Specific Primers in India, and a Novel Leopard Specific Primer. BMC Genet. 2016, 17, 37. [Google Scholar] [CrossRef] [PubMed]
  50. Hall, T.A. BioEdit: A User-Friendly Biological Sequence Alignment Editor and Analysis Program for Windows 95/98/NT. Nucleic Acids Symp. Ser. 1999, 41, 95–98. [Google Scholar]
  51. O’Leary, N.A.; Cox, E.; Holmes, J.B.; Anderson, W.R.; Falk, R.; Hem, V.; Tsuchiya, M.T.N.; Schuler, G.D.; Zhang, X.; Torcivia, J.; et al. Exploring and Retrieving Sequence and Metadata for Species across the Tree of Life with NCBI Datasets. Sci. Data 2024, 11, 732. [Google Scholar] [CrossRef]
  52. Sayers, E.W.; Beck, J.; Bolton, E.E.; Brister, J.R.; Chan, J.; Comeau, D.C.; Connor, R.; DiCuccio, M.; Farrell, C.M.; Feldgarden, M.; et al. Database Resources of the National Center for Biotechnology Information. Nucleic Acids Res. 2024, 52, D33–D43. [Google Scholar] [CrossRef]
  53. Altschul, S.F.; Gish, W.; Miller, W.; Myers, E.W.; Lipman, D.J. Basic Local Alignment Search Tool. J. Mol. Biol. 1990, 215, 403–410. [Google Scholar] [CrossRef]
  54. Tobe, S.S.; Kitchener, A.C.; Linacre, A.M.T. Reconstructing Mammalian Phylogenies: A Detailed Comparison of the Cytochrome b and Cytochrome Oxidase Subunit I Mitochondrial Genes. PLoS ONE 2010, 5, e14156. [Google Scholar] [CrossRef]
  55. Farag, M.R.; El Bohi, K.M.; Khalil, S.R.; Alagawany, M.; Arain, M.A.; Sharun, K.; Tiwari, R.; Dhama, K. Forensic Applications of Mitochondrial Cytochrome b Gene in the Identification of Domestic and Wild Animal Species. J. Exp. Biol. Agric. Sci. 2020, 8, 1–8. [Google Scholar] [CrossRef]
  56. Vaněk, D.; Ehler, E.; Vaňková, L. Technical Note: Development of DNA Quantitation and STR Typing Systems for Panthera Tigris Species Determination and Individual Identification in Forensic Casework. Eur. J. Environ. Sci. 2021, 11, 113–118. [Google Scholar] [CrossRef]
  57. Vankova, L.; Alaverdyan, J.; Vanek, D. Developmental Validation of DNA Quantitation System, Extended STR Typing Multiplex, and Database Solutions for Panthera Leo Genotyping. Life 2025, 15, 664. [Google Scholar] [CrossRef] [PubMed]
  58. Gouy, A.; Zieger, M. STRAF—A Convenient Online Tool for STR Data Evaluation in Forensic Genetics. Forensic Sci. Int. Genet. 2017, 30, 148–151. [Google Scholar] [CrossRef]
  59. Mondol, S.; R, N.; Athreya, V.; Sunagar, K.; Selvaraj, V.M.; Ramakrishnan, U. A Panel of Microsatellites to Individually Identify Leopards and Its Application to Leopard Monitoring in Human Dominated Landscapes. BMC Genet. 2009, 10, 79. [Google Scholar] [CrossRef]
  60. Sugimoto, T.; Nagata, J.; Aramilev, V.V.; Belozor, A.; Higashi, S.; McCullough, D.R. Species and Sex Identification from Faecal Samples of Sympatric Carnivores, Amur Leopard and Siberian Tiger, in the Russian Far East. Conserv. Genet. 2006, 7, 799–802. [Google Scholar] [CrossRef]
  61. Caragiulo, A.; Pickles, R.S.A.; Smith, J.A.; Smith, O.; Goodrich, J.; Amato, G. Tiger (Panthera tigris) Scent DNA: A Valuable Conservation Tool for Individual Identification and Population Monitoring. Conserv. Genet. Resour. 2015, 7, 681–683. [Google Scholar] [CrossRef]
  62. Kittle, A.M.; Watson, A.C.; Cushman, S.A.; Macdonald, D.W. Forest Cover and Level of Protection Influence the Island-Wide Distribution of an Apex Carnivore and Umbrella Species, the Sri Lankan Leopard (Panthera pardus kotiya). Biodivers. Conserv. 2018, 27, 235–263. [Google Scholar] [CrossRef]
  63. Williamson, J.E.; Huebinger, R.M.; Sommer, J.A.; Louis, E.E.; Barber, R.C. Development and Cross-species Amplification of 18 Microsatellite Markers in the Sumatran Tiger (Panthera tigris sumatrae). Mol. Ecol. Notes 2002, 2, 110–112. [Google Scholar] [CrossRef]
  64. Menotti-Raymond, M.; David, V.A.; Lyons, L.A.; Schäffer, A.A.; Tomlin, J.F.; Hutton, M.K.; O’Brien, S.J. A Genetic Linkage Map of Microsatellites in the Domestic Cat (Felis catus). Genomics 1999, 57, 9–23. [Google Scholar] [CrossRef]
  65. Gupta, S.K.; Bhagavatula, J.; Thangaraj, K.; Singh, L. Establishing the Identity of the Massacred Tigress in a Case of Wildlife Crime. Forensic Sci. Int. Genet. 2011, 5, 74–75. [Google Scholar] [CrossRef]
  66. Wultsch, C.; Caragiulo, A.; Dias-Freedman, I.; Quigley, H.; Rabinowitz, S.; Amato, G. Genetic Diversity and Population Structure of Mesoamerican Jaguars (Panthera onca): Implications for Conservation and Management. PLoS ONE 2016, 11, e0162377. [Google Scholar] [CrossRef]
  67. Webster, M.S.; Reichart, L. Use of Microsatellites for Parentage and Kinship Analyses in Animals. In Methods in Enzymology; Academic Press: New York, NY, USA, 2005; pp. 222–238. [Google Scholar]
Genes 17 00045 g001
Figure 1. Quantitative real-time PCR (Ppar Qplex) amplification curves targeting mitochondrial and nuclear DNA. The assay detects P. pardus-specific mitochondrial DNA (qPpardusM; red), Feliformia-specific nuclear DNA (qPpardusN; blue), and an internal positive control (qPpardusC; IPC; green): (a) Amplification from P. leo DNA extract shows nuclear and IPC signals but no amplification of the P. pardus-specific target (qPpardusM Ct: Underdetection, qPpardusN Ct: 33, qPpardusC Ct: 21). (b) Amplification from P. pardus DNA extract, showing positive signals for all three targets (qPpardusM Ct: 21, qPpardusN Ct: 31, qPpardusC Ct: 20).
Figure 1. Quantitative real-time PCR (Ppar Qplex) amplification curves targeting mitochondrial and nuclear DNA. The assay detects P. pardus-specific mitochondrial DNA (qPpardusM; red), Feliformia-specific nuclear DNA (qPpardusN; blue), and an internal positive control (qPpardusC; IPC; green): (a) Amplification from P. leo DNA extract shows nuclear and IPC signals but no amplification of the P. pardus-specific target (qPpardusM Ct: Underdetection, qPpardusN Ct: 33, qPpardusC Ct: 21). (b) Amplification from P. pardus DNA extract, showing positive signals for all three targets (qPpardusM Ct: 21, qPpardusN Ct: 31, qPpardusC Ct: 20).
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Figure 2. Allele frequencies (Y-axis: total number of observations per allele) observed in 30 P. pardus individuals across STR loci Ptig3, Ptig6, Ptig5, Ptig16, Ptig10, Ptig9, Pleo24, Pleo30, Pleo22, Pleo31, Pleo32, and Pleo33.
Figure 2. Allele frequencies (Y-axis: total number of observations per allele) observed in 30 P. pardus individuals across STR loci Ptig3, Ptig6, Ptig5, Ptig16, Ptig10, Ptig9, Pleo24, Pleo30, Pleo22, Pleo31, Pleo32, and Pleo33.
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Figure 3. Allele frequencies (absolute number on Y-axis) for alleles observed for P. pardus individuals in the most polymorphic loci Ptig17 and Pleo23 (n = 30).
Figure 3. Allele frequencies (absolute number on Y-axis) for alleles observed for P. pardus individuals in the most polymorphic loci Ptig17 and Pleo23 (n = 30).
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Figure 4. An example of the resulting DNA profiles for a male individual of P. pardus, including labels indicating which electropherogram peaks correspond to each locus.
Figure 4. An example of the resulting DNA profiles for a male individual of P. pardus, including labels indicating which electropherogram peaks correspond to each locus.
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Table 1. Primers and probes used in Ppar Qplex (* newly designed primers).
Table 1. Primers and probes used in Ppar Qplex (* newly designed primers).
Primer/Probe NameFinal ConcentrationSequence (5′-3′)PCR Product SizeSpecificityTaqMan Probe Fluorescent LabelDesign
(mM)(bp =
Base Pairs)
qPparM_F5AGACATGGAACATTGGAGTC164 bpCyt b (mtDNA)---*
qPparM_R5TCAGATTCATTCTACTAGGTCAATC---*
qPparM_probe1.7CAACCGTAATTACCAACCTCCprobeVIC*
qPparC_F5CTGCTAGGTTTAGCGCGTGAC261 bpIPC---[46]
qPparC_R5GGGGACCATGCTTGCG---[46]
qPparC_probe1.7TGCACGATTCAAGCACGATprobeNED[46]
qPparN_F3.3AGTCCACTTCTCATTGCCCCTT132 bp PLP (nDNA)---[46]
qPparN_R3.3ACCTTCCCTGAGTTCTCCATACC---[46]
qPparN_probe1.7CTCACCAGACCTGTTAGGAprobe6-FAM[46]
Table 2. Resulting allele calls for a male individual of P. pardus.
Table 2. Resulting allele calls for a male individual of P. pardus.
P. pardus
MultiplexLocusAlleles
PtigPlex1Ptig312, 13
Ptig1728.1, 35.4
Ptig1511.1, 11.1
Ptig67, 8
Ptig183, 3
Ptig510, 10
ZNFXYM
PtigPlex2Ptig1613, 14
Ptig1023, 23
Ptig914, 15
Ptig86.1, 6.1
Ptig1115, 15
SRY M
PleoPlex1Pleo2419, 20
Pleo3022, 22
Pleo2356, 57
Pleo227.3, 7.3
Pleo3121, 22
Pleo3214, 14
Pleo3315, 15
Table 3. STR sequence difference of P. tigris and P. pardus for the selected locus Ptig 8. Please note the single base insertion in the flanking region of P. pardus allele 6.1. The same insertion was found across all individuals sequenced (n = 12).
Table 3. STR sequence difference of P. tigris and P. pardus for the selected locus Ptig 8. Please note the single base insertion in the flanking region of P. pardus allele 6.1. The same insertion was found across all individuals sequenced (n = 12).
P. tigrisP. pardus
Ptig 8  (ATCTAT)n (ATC)nalelle 7 — 6 × (ATCTAT) + 2 × (ATC)alelle 6.1 5 × (ATCTAT) + 2 × (ATC) + 1 bp insertion
GCTGAT ATCTAT ATCTAT ATCTAT ATCTAT ATC ATCTAT ATC ATCTAT ATTTTT CCCCC TCTCGCTGAT ATCTAT ATCTAT ATCTAT ATC ATCTAT ATC ATCTAT ATTTTT TCCCC CTC
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Mahlerová, K.; Vaňková, L.; Vaněk, D. Molecular Tools for qPCR Identification and STR-Based Individual Identification of Panthera pardus (Linnaeus, 1758). Genes 2026, 17, 45. https://doi.org/10.3390/genes17010045

AMA Style

Mahlerová K, Vaňková L, Vaněk D. Molecular Tools for qPCR Identification and STR-Based Individual Identification of Panthera pardus (Linnaeus, 1758). Genes. 2026; 17(1):45. https://doi.org/10.3390/genes17010045

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Mahlerová, Karolina, Lenka Vaňková, and Daniel Vaněk. 2026. "Molecular Tools for qPCR Identification and STR-Based Individual Identification of Panthera pardus (Linnaeus, 1758)" Genes 17, no. 1: 45. https://doi.org/10.3390/genes17010045

APA Style

Mahlerová, K., Vaňková, L., & Vaněk, D. (2026). Molecular Tools for qPCR Identification and STR-Based Individual Identification of Panthera pardus (Linnaeus, 1758). Genes, 17(1), 45. https://doi.org/10.3390/genes17010045

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