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Published on: June 21, 2018
An evaluation of the PowerSeq™ Auto System: A multiplex short tandem repeat marker kit compatible with massively
Xiangpei Zeng1, Jonathan King1, Spencer Hermanson2
1Institute of Applied Genetics, Department of Molecular and Medical Genetics, University of North Texas Health Science Center, 3500 Camp Bowie Blvd., Fort Worth, Texas 76107, USA.
Massively parallel sequencing (MPS) using the PowerSeq Auto System offers a powerful alternative for short tandem repeat (STR) typing in forensic genetics. This advanced method improves mixture analysis and detects intra-repeat variations, surpassing traditional capillary electrophoresis limitations.
Area of Science:
- Forensic Genetics
- Molecular Biology
- Genomics
Background:
- Capillary electrophoresis (CE) is standard for short tandem repeat (STR) typing but has limitations in multiplexing and detecting intra-repeat variations.
- Massively parallel sequencing (MPS) presents a promising alternative technology for enhanced STR analysis.
Purpose of the Study:
- To evaluate the prototype PowerSeq Auto System with 23 STR loci and amelogenin using Illumina MiSeq for forensic DNA typing.
- To assess the system's performance in terms of sensitivity, reproducibility, mixture analysis, and casework applicability.
Main Methods:
- Evaluation of the PowerSeq Auto System on the Illumina MiSeq platform.
- Testing with varying DNA input amounts, including low template DNA.
- Assessment of reproducibility across multiple experiments.
- Analysis of simulated forensic samples, including single-source and mixture DNA.
Main Results:
- Complete STR profiles were achieved with as little as 62 pg of input DNA.
- High reproducibility was observed in typing experiments for individuals.
- Partial STR profiles of minor contributors were detectable in mixtures up to 19:1 ratios.
- The system successfully generated full or partial profiles from diverse forensic samples.
Conclusions:
- The PowerSeq Auto System on Illumina MiSeq provides results concordant with current CE-based methods.
- MPS-based STR typing facilitates improved mixture deconvolution and detection of intra-repeat variations, offering advantages over length-based analysis.
