Revisiting single cell analysis in forensic science.

Area of Science:

• Forensic Science
• Genetics
• Molecular Biology

Background:

• DNA mixture analysis presents significant challenges in forensic identification due to complexities like multiple contributors and allele masking.
• Single cell analysis offers a promising approach to overcome these limitations by isolating individual cells.

Purpose of the Study:

• To evaluate the effectiveness of single cell analysis in forensic identification.
• To characterize data generated from single cells using a novel analysis pipeline.
• To assess the impact of varying PCR cycles and analytical thresholds on data quality and interpretation.

Main Methods:

• Recovery of single cells using the DEPArray NxT.
• Amplification using the PowerPlex Fusion 6c kit with 29, 30, and 31 PCR cycles.
• Assessment of allelic signal using analytical thresholds of 10, 100, and 150 RFU.

Main Results:

• Mean peak heights increased with higher PCR cycle numbers (29: 75.0 RFU, 30: 147.1 RFU, 31: 226.1 RFU).
• Allele/locus dropout was primarily influenced by the detection threshold, with less impact from PCR cycle number.
• Data quality improved significantly from 29 to 30 PCR cycles, with increased volatility at 31 cycles.
• High random match probabilities were achieved, indicating strong discriminatory power.

Conclusions:

• Single cell analysis effectively simplifies forensic DNA mixture interpretation.
• The developed pipeline provides robust data for forensic identification.
• Optimizing PCR cycles and detection thresholds is crucial for maximizing data quality and minimizing dropout.