Back to Presentations

From SNP Mixtures to Separated Genotypes

M. W. Perlin, "From SNP Mixtures to Separated Genotypes", Promega's Thirty Seventh International Symposium on Human Identification, Providence, RI, 27-Oct-2026.

Poster

Download Poster

Abstract

Single nucleotide polymorphism (SNP) sequencing is increasingly used in forensic genetics and forensic investigative genetic genealogy (FIGG). However, SNP mixture interpretation remains a challenging problem.

Unlike highly polymorphic STR markers, SNPs are usually bi-allelic, so contributors frequently overlap at the same two alleles. Consequently, many different contributor genotype combinations can appear very similar in a mixture, making contributor separation and evidential interpretation difficult.

We developed a hierarchical Bayesian method that separates contributor genotypes from SNP next-generation sequencing (NGS) mixture data. The method jointly analyzes all loci in a mixture, estimates contributor genotypes and mixture proportions, and produces posterior genotype probability distributions for each contributor.

Rather than giving a single definite genotype, these distributions describe the possible contributor genotypes and how much probability each receives after analyzing the sequencing data. They summarize the evidence contained in the data, quantify uncertainty, and can be used directly for likelihood-ratio (LR) calculations and forensic comparisons.

The SNP genotype separation method was applied to SNP sequence data generated using the Verogen ForenSeq DNA Signature Prep Kit (Primer Set B) processed through the MiSeq FGx sequencing platform. Analyses used only the panel's 94 identity SNP loci distributed across 23 chromosomes.

Despite the relatively small number of markers, contributor genotypes were successfully separated from mixed samples and produced substantial evidential support. In a two-person 25:75 mixture, the separated 25% contributor produced approximately 20 ban of log(LR) support. In a three-person 1:4:4 mixture, a separated 44% contributor yielded about 12 ban of support.

These results demonstrate that probabilistic separation and LR-based interpretation of forensic SNP mixtures are feasible using a small genome-wide SNP panel.

The approach extends probabilistic DNA interpretation beyond STR markers and provides a framework for using SNP evidence in forensic casework. Because STR and SNP loci represent independent sources of genetic information, available evidential support from both marker systems can be combined.

The SNP results reported here were obtained from just 94 identity SNP loci, whereas modern FIGG applications routinely analyze hundreds of thousands of SNP markers. These findings therefore suggest a path toward highly informative probabilistic interpretation of complex SNP mixtures in investigative genetic genealogy and other large-scale human identification sequencing applications.

Acknowledgement

The author thanks the Cybergenetics and Kern Regional Crime Laboratory NGS validation team for generating and organizing the sequencing data used in this study.

References

1. Perlin MW, Legler MM, Spencer CE, Smith JL, Allan WP, Belrose JL, Duceman BW. Validating TrueAllele® DNA mixture interpretation. Journal of Forensic Sciences. 2011;56(6):1430-1447.
2. Legler M, Bracamontes J, Van Buren M. TrueAllele® Casework validation of the Verogen ForenSeq DNA Signature Prep Kit Primer Set B and the MiSeq FGx. Poster presentation, 34th International Symposium on Human Identification, Denver, Colorado, September 2023.

Links

• Promega's Thirty Seventh International Symposium on Human Identification - Website