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Updated: May 4, 2026

Transcriptome Analysis of Single Cells
Published on: April 25, 2011
Characterizing stutter in single cells and the impact on multi-cell analysis
Amber C W Vandepoele1, Natalie Novotna1, Dan Myers1
1Forensic & National Security Sciences Institute, Syracuse University, Syracuse, NY, USA.
Abstract:
Short tandem repeat analysis is a robust and reliable DNA analysis technique that aids in source identification of a biological sample. However, the interpretation, particularly when DNA mixtures are present at low levels, can be complicated by the presence of PCR artifacts most commonly referred to as stutter. The presence of stutter products can increase the difficulty of interpretation in DNA mixtures as well as low-level DNA samples down to a single cell. Stutter product formation is stochastic in nature and although methods exist that can estimate the magnitude of stutter product formation, it still is not well understood. With the increased sensitivity of forensic DNA analyses, it has become possible to obtain interpretable DNA profiles from as low as 6.6 pg of DNA, or a single human diploid cell. However, this presents an interpretational challenge because the stutter in these low-level DNA samples might stray from the expected patterns observed in high-level DNA samples. Therefore, this project focuses on characterizing stutter in single cell samples to help generate a deeper understanding of stutter and provide a guide for detecting and evaluating stutter in low-level samples. Stutter analysis was performed using data generated from 180 single cells isolated with the DEPArrayTM NxT, amplified using the PowerPlex Fusion 6 C amplification kit at 29 or 30 cycles. Stutter was successfully characterized in single cells and stutter percentages were highly elevated compared to high-level samples where the variance increased as the number of cells being analyzed decreased leading to potential high stutter at low DNA levels. Using empirical and simulated (resampled) data, this study also reinforces historically relevant patterns in stutter product formation and demonstrates the relative differences in stutter in n-1, n-2 and n + 1 stutter product formation in simple, complex and compound repeats.
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