Cross-Platform Workflow for the Promega PowerSeq 46GY System

Massively parallel sequencing (MPS) technologies have been extensively evaluated by forensic genomic Research and Development laboratories for the past ten years. Results from these studies have routinely demonstrated the benefits afforded by use of these enhanced technologies and have helped progress the adoption of MPS in forensic genomic laboratories that process biological evidence. The commercial availability of MPS kits targeting forensic loci, developmental validation studies, and NDIS acceptance across multiple MPS kits and platforms illustrate the progress in reliability and adoption of MPS technologies in forensic laboratories. However, due to the financial investment necessary for acquiring a MPS instrument, forensic laboratories are likely to have only one MPS platform available in their laboratory once the decision to implement this technology is made. Since there are multiple platforms and chemistries, cross-platform workflows are needed to enable sharing of MPS data generated across the forensic genomics community.

A set of samples (n=18) and dilution series with DNA input amounts ranging from 1ng to 62.5pg of DNA were amplified with the Promega PowerSeq 46GY System, generating PCR products for autosomal and Y-STR loci designed to be 140 to 300 base-pairs in size. These PCR products were used for two separate library preparation workflows to enable sequencing on both the Verogen MiSeq FGx System and the Ion Torrent Ion S5 System. Raw data generated by each workflow were then analyzed with three separate bioinformatic pipelines, which included STRait Razor, GeneMarkerHTS software, and Ion Torrent plugins available on the Ion Torrent Server. In addition to evaluating concordance across library preparation/sequencing workflows and across bioinformatic pipelines, data previously generated for these samples with Verogen’s ForenSeq DNA Signature Prep Kit were available for concordance assessment. Performance metrics, including read depth, strand balance, and noise, were evaluated for each of these samples and used to identify potential effects of methodology-based biases on the generated profiles.

Data generated from these samples support that each of these MPS workflows yields reliable results for the analysis of biological evidence. However, fully understanding the system used and potential areas of discordance would be helpful for implementing a robust system community wide. The experience and resources developed during this study could assist other forensic laboratories interested in building their own cross-platform workflow for current commercially- available kits.