Development of a multiplex forensic identity panel for massively parallel sequencing and its systematic optimization using design of experiments.

The application of massively parallel sequencing (MPS) in forensic sciences enables high-resolution short tandem repeat (STR) genotyping for the characterization of biological evidence. While MPS supports multiplexing of a large number of forensic markers, the performance of an MPS-STR panel depends on good primer design and optimal PCR conditions. However, conventional strategies for multifactorial assay optimization are labor-intensive and do not necessarily allow the experimenter to identify optimum factor settings. Here we describe our new multiplex PCR assay, monSTR, which supports the simultaneous amplification of 21 forensic markers followed by targeted sequencing on the Illumina MiSeq. The selection of STR markers adapts on the expanded European Standard Set (ESS), including the highly polymorphic locus SE33, for compatibility with existing forensic DNA databases. Primer engineering involved bioinformatics tools to create a multiplex-compatible primer set. Primer quality was evaluated in silico and in vitro. We demonstrate the systematic optimization of multiplex PCR thermocycling conditions using Design of Experiments (DOE) methodology. The objective was to yield a specific, balanced, low-noise amplification of forensic targets. A central composite face design of experiments enabled an efficient simultaneous investigation of multiple critical process parameters and their interactions. Optimal multiplex PCR conditions were predicted using software-aided modelling based on DOE data. Verification experiments suggested a balanced, reproducible amplification of all markers with reduced formation of artefacts. Fully concordant STR profiles were obtained for the investigated reference samples even with challenging input DNA concentrations. We found that application of DOE principles enabled an experimentally practical and economically justifiable assay development and optimization, even beyond the field of forensic genetics.