SiMSen-Seq STR sequencing across five laboratories enables lowered noise thresholds and improved allele calling

Published

June 1, 2026

Author(s)

Arvid Gynna, Maja Sidstedt, Kevin Kiesler, Adam Staadig, Carolyn Steffen, Peter Vallone, Johannes Hedman

Abstract

Unique molecular identifiers can be used in forensic STR sequencing to reduce the level of artefacts, and are thus expected to improve sensitivity for minor contributors in complex DNA mixtures. A prototype method for STR genotyping based on the SiMSen-Seq principle has previously been developed and evaluated. Here, we perform an interlaboratory study across five independent sites where the forensic SiMSen-Seq STR assay is applied at each laboratory to both single-source and mixed samples. The assay showed promising characteristics, with consistent results between laboratories and more than 90% of alleles detected with 31 pg DNA of template. Also, the assay tolerated ten times higher inhibitor concentrations compared to a commercial STR sequencing method. The combined results were used to determine stutter and noise thresholds, which were applied for allele calling, allowing an estimation of the sensitivity for minor contributor alleles in mixtures. We find that the forensic SiMSen-Seq method is robust across laboratories and different types of PCR and sequencing equipment, and allows calling of smaller minority contributor alleles than currently available non-UMI STR sequencing methods.

Citation

Forensic Science International: Genetics

Volume

86

Pub Type

Journals

Download Paper

https://doi.org/10.1016/j.fsigen.2026.103548

Local Download

Keywords

Massively parallel sequencing (MPS), short tandem repeats (STR), unique molecular identifier (UMI), interlaboratory comparison, forensic DNA analysis

Citation

Gynna, A. , Sidstedt, M. , Kiesler, K. , Staadig, A. , Steffen, C. , Vallone, P. and Hedman, J. (2026), SiMSen-Seq STR sequencing across five laboratories enables lowered noise thresholds and improved allele calling, Forensic Science International: Genetics, [online], https://doi.org/10.1016/j.fsigen.2026.103548, https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=961013 (Accessed August 9, 2026)

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