Optimizing a human forensic STR panel for non-invasive genetic monitoring of chimpanzees (Pan troglodytes).
5 affiliations
- 1Department of Ecology and Conservation Biology, Texas A&M University, College Station, TX, USA. [email protected].
- 2Department of Ecology and Conservation Biology, Texas A&M University, College Station, TX, USA.
- 3Department of Ecology and Evolutionary Biology, University of California, Los Angeles, CA, USA.
- 4Department of Ecosystem Science and Management, University of Northern British Columbia, Prince George, British Columbia, Canada.
- 5Department of Ecology and Conservation Biology, Texas A&M University, College Station, TX, USA. [email protected].
Abstract
Objective
Accurate molecular genotyping is essential for conservation genetics, population monitoring, pedigree reconstruction, and wildlife forensic investigations in endangered primates. Although SNP-based approaches are increasingly available, microsatellites remain among the most practical tools for non-invasive individual identification because of their high allelic diversity and strong discriminatory power from relatively few loci. Here, we present a standardized optimization framework for adapting the human forensic GlobalFiler™ PCR Amplification Kit to non-invasive chimpanzee genotyping.Results
Using blood and fecal DNA from captive and wild chimpanzees in Cameroon, we integrated DNA quality screening, chimpanzee-specific allele binning, replicate consensus genotyping, statistical evaluation of locus performance, and composite marker ranking to develop a robust 16-locus panel for individual identification. Estimated marginal means were calculated from the fitted beta regression models to assess amplification success, allelic dropout, and false allele rates across sample types and loci. These metrics, combined with measures of discriminatory power, identified D10S1248, FGA, D2S441, and D3S1358 as the highest-performing loci. The optimized panel achieved 95.4% amplification success with low allelic dropout (0.08) and false allele (0.02) rates. It identified 64 unique individuals (39 males and 25 females) and showed high discriminatory power (PID(sibs) = 1.2 × 10⁻⁶). This workflow is easily transferable and can complement SNP genotyping, metabarcoding, microbiome analyses, and other molecular approaches in a wide range of non-invasive genetic studies.
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BibTeX
@article{paul2026optimizing,
title = {{Optimizing a human forensic STR panel for non-invasive genetic monitoring of chimpanzees (Pan troglodytes).}},
author = {Shrutarshi Paul and Fabrice Kentatchime and Tyler Andres-Bray and Tista Ghosh and Giovana Naira Pereira Couto and Kevin Njabo and Mary Katherine Gonder},
journal = {BMC research notes},
year = {2026},
month = sep,
doi = {10.1186/s13104-026-07997-y},
url = {https://europepmc.org/article/MED/42958581},
note = {CC BY},
}
RIS
TY - JOUR
TI - Optimizing a human forensic STR panel for non-invasive genetic monitoring of chimpanzees (Pan troglodytes).
AU - Shrutarshi Paul
AU - Fabrice Kentatchime
AU - Tyler Andres-Bray
AU - Tista Ghosh
AU - Giovana Naira Pereira Couto
AU - Kevin Njabo
AU - Mary Katherine Gonder
PY - 2026
DA - 2026/09/09
JO - BMC research notes
DO - 10.1186/s13104-026-07997-y
UR - https://europepmc.org/article/MED/42958581
AB - Objective Accurate molecular genotyping is essential for conservation genetics, population monitoring, pedigree reconstruction, and wildlife forensic investigations in endangered primates. Although SNP-based approaches are increasingly available, microsatellites remain among the most practical tools for non-invasive individual identification because of their high allelic diversity and strong discriminatory power from relatively few loci. Here, we present a standardized optimization framework for adapting the human forensic GlobalFiler™ PCR Amplification Kit to non-invasive chimpanzee genotyping.Results Using blood and fecal DNA from captive and wild chimpanzees in Cameroon, we integrated DNA quality screening, chimpanzee-specific allele binning, replicate consensus genotyping, statistical evaluation of locus performance, and composite marker ranking to develop a robust 16-locus panel for individual identification. Estimated marginal means were calculated from the fitted beta regression models to assess amplification success, allelic dropout, and false allele rates across sample types and loci. These metrics, combined with measures of discriminatory power, identified D10S1248, FGA, D2S441, and D3S1358 as the highest-performing loci. The optimized panel achieved 95.4% amplification success with low allelic dropout (0.08) and false allele (0.02) rates. It identified 64 unique individuals (39 males and 25 females) and showed high discriminatory power (PID(sibs) = 1.2 × 10⁻⁶). This workflow is easily transferable and can complement SNP genotyping, metabarcoding, microbiome analyses, and other molecular approaches in a wide range of non-invasive genetic studies.
SN - 1756-0500
ER -