Short tandem repeats, or STRs, are stretches of DNA in which a short sequence of two to six base pairs repeats over and over. The number of repeats at any given locus varies from person to person, which is precisely what makes STRs the backbone of modern forensic DNA profiling. Because these repeat counts are inherited, one copy from each parent, they allow investigators to compare a crime scene sample with a suspect’s profile, or to establish biological relationships in paternity cases. But the statistics underpinning those comparisons are only valid if laboratories know how common each repeat variant, or allele, is in the relevant population. A profile match that looks overwhelming in one population may carry different weight in another, which is why population-specific frequency databases are a cornerstone of ethical and accurate forensic practice.

The research team, led by Brajesh Kumar and Amitabh Biswas of Galgotias University’s School of Forensic Sciences, together with colleagues from the Central Forensic Science Laboratory in Chandigarh, Ingenomics India, and the Regional Forensic Science Laboratory in Jabalpur, used the Ingenomics AutoProfiler STR Kit to amplify all 24 markers simultaneously. This six-dye multiplex system, which was independently validated for forensic applications, covers the expanded set of loci now favored internationally, including the highly variable SE33 and Penta E markers alongside familiar names such as FGA, vWA, and TH01. Genotyping was carried out by capillary electrophoresis, and the resulting allele calls were subjected to statistical analysis using established population genetics software, including Arlequin, GenAlEx, and PowerStats.

The headline numbers are striking. Across the 24 loci, the probability of match, which expresses the chance that two randomly selected unrelated individuals share the same genotype, ranged from 0.012 to 0.186. Inverted into its more familiar form, the power of discrimination ranged from 0.814 to 0.988, meaning the best markers could distinguish between any two individuals in the population with near certainty. SE33 topped the list with a discrimination power of 0.988, followed closely by Penta E at 0.983 and FGA at 0.962. At the other end of the spectrum, CSF1PO at 0.814 and D2S441 at 0.844 were comparatively modest performers, a pattern consistent with their lower allelic diversity in populations worldwide.

Polymorphism information content, a measure of how informative a marker is for linkage and identity analysis, ranged from 0.601 to 0.933, with the majority of loci exceeding 0.7, a threshold conventionally regarded as indicating high polymorphism. Gene diversity values, which capture the expected heterozygosity at each locus, spanned 0.666 to 0.939, confirming that the Santhal sample carries substantial genetic variability. Observed and expected heterozygosities were calculated for every locus, and tests against Hardy-Weinberg equilibrium were performed to verify that allele frequencies behave as expected under random mating, a critical quality check before any forensic statistic can be considered reliable.

For paternity testing, the study’s parameters matter even more directly. The power of exclusion, the probability that a randomly selected man would be excluded as the biological father of a child, ranged from 0.428 to 0.913 across individual loci, with SE33 and Penta E showing the strongest exclusion capacity. The typical paternity index varied from 1.667 to 11.667, again led by the most polymorphic markers, including SE33, Penta E, and D12S391. When the loci were combined, the results became extraordinary: the combined power of exclusion reached 0.999999999991, the combined paternity index stood at 3.51 multiplied by ten to the tenth power, and the combined probability of match fell to 2.41 multiplied by ten to the power of negative 28. The combined power of discrimination, rounded, was effectively 1. In practical terms, the chance that two unrelated Santhal individuals would share an identical 24-locus profile is so vanishingly small that a matching profile constitutes evidence of identity at a level few other forms of forensic evidence can approach.

Why does population-specific data of this kind matter so much? Forensic statistics rest on the product rule: the rarity of a full profile is estimated by multiplying the frequencies of the individual alleles, an operation that assumes statistical independence within the population under consideration. If a population has a history of endogamy, consanguinity, or founder effects, as many isolated or semi-isolated communities do, allele frequencies can drift in ways that inflate or deflate match probabilities. The Santhal, an Austroasiatic-speaking tribal community with a distinct demographic history in eastern India, are precisely the kind of population for which generic national databases may not be adequate. By generating a dedicated allele frequency dataset, the study gives forensic practitioners in Bihar and neighboring states a defensible statistical foundation when the source of a sample may belong to this community.

The work also contributes to the broader scientific picture of Indian genetic diversity. Previous studies have documented STR polymorphism in Chhattisgarh, Himachal Pradesh, northwestern India, and among the Sindhi population, and genomic research on Austroasiatic speakers has highlighted the role of landscape barriers and sex-specific admixture in shaping their genetic structure. Each new population dataset refines the map of how genetic variation is distributed across the subcontinent, and the Santhal data will allow comparisons that illuminate both forensic and anthropological questions. The authors note that the 24 loci are highly informative not only for individual identification but also for kinship analysis, extending their utility to disaster victim identification, missing persons investigations, and complex relationship testing.

The study was approved by the Institutional Ethics Committee of Apex Hospital in Varanasi, and the authors report no conflicts of interest and no external funding. All participants were unrelated volunteers who consented to contribute samples, and the authors acknowledge their role in enabling the research. The sampling strategy, restricted to unrelated individuals, is essential for Hardy-Weinberg testing and for ensuring that the frequency estimates reflect the general population rather than clustered family lineages.

As DNA evidence continues to expand its role in the Indian judicial system, studies like this one quietly underpin every statistic that appears in a courtroom report. A match probability of ten to the negative 28 is only as credible as the allele frequency table behind it, and that table must reflect the population to which a suspect or victim belongs. With the Santhal community now represented in the forensic literature by a rigorously characterized 24-locus dataset, investigators and courts in Bihar gain a resource that makes DNA statistics for this population both more accurate and more defensible. It is a reminder that the power of forensic genetics depends not just on the chemistry of amplification and detection, but on the patient, community-by-community work of measuring human variation itself.

Subject of Research: Forensic genetic profiling of autosomal STR markers in the Santhal tribal population of Bihar, India

Article Title: Allele frequency distribution and forensic efficiency parameters of 24 autosomal STR markers in the santhal tribal community of Bihar, India

Article References: Kumar, B., Biswas, A., Dixit, S., Sharma, S., & Shrivastava, P. (2026). Allele frequency distribution and forensic efficiency parameters of 24 autosomal STR markers in the santhal tribal community of Bihar, India. The Science of Nature, 113(6), Article 125. https://doi.org/10.1007/s00114-026-02176-2

Image Credits: AI Generated

DOI: 10.1007/s00114-026-02176-2

Keywords: forensic genetics, STR markers, Santhal, allele frequency, paternity testing, population genetics, India, DNA profiling, Hardy-Weinberg equilibrium, power of discrimination, tribal population, polymorphism