Revisiting single cell analysis in forensic science

Abstract Forensic science has yet to take full advantage of single cell analysis. Its greatest benefit is the ability to alleviate the challenges associated with DNA mixture analysis, which remains a significant hurdle in forensic science. Many of the factors that cause complexity in mixture interpr...

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Autores principales:	Davis R. L. Watkins, Dan Myers, Hannah E. Xavier, Michael A. Marciano
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/3a11999e2a26467bb5eeb1488d84f7e9
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spelling	oai:doaj.org-article:3a11999e2a26467bb5eeb1488d84f7e92021-12-02T18:17:54ZRevisiting single cell analysis in forensic science10.1038/s41598-021-86271-62045-2322https://doaj.org/article/3a11999e2a26467bb5eeb1488d84f7e92021-03-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-86271-6https://doaj.org/toc/2045-2322Abstract Forensic science has yet to take full advantage of single cell analysis. Its greatest benefit is the ability to alleviate the challenges associated with DNA mixture analysis, which remains a significant hurdle in forensic science. Many of the factors that cause complexity in mixture interpretation are absent in single cell analyses—multiple contributors, varied levels of contribution, and allele masking. This study revisits single cell analyses in the context of forensic identification, introducing previously unseen depth to the characterization of data generated from single cells using a novel pipeline that includes recovery of single cells using the DEPArray NxT and amplification using the PowerPlex Fusion 6c kit with varied PCR cycles (29, 30, and 31). The resulting allelic signal was assessed using analytical thresholds of 10, 100, and 150RFU. The mean peak heights across the sample sets generally increased as cycle number increased, 75.0 ± 85.3, 147.1 ± 172.6, and 226.1 ± 298.2 RFU, for 29, 30, and 31 cycles, respectively. The average proportion of allele/locus dropout was most significantly impacted by changes in the detection threshold, whereas increases in PCR cycle number had less impact. Overall data quality improved notably when increasing PCR from 29 to 30 cycles, less improvement and more volatility was introduced at 31 cycles. The average random match probabilities for the 29, 30, and 31 cycle sets at 150RFU are 1 in 2.4 × 1018 ± 1.46 × 1019, 1 in 1.49 × 1025 ± 5.8 × 1025, and 1 in 1.83 × 1024 ± 8.09 × 1024, respectively. This demonstrates the current power of single cell analysis in removing the need for complex mixture analysis.Davis R. L. WatkinsDan MyersHannah E. XavierMichael A. MarcianoNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-12 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Davis R. L. Watkins Dan Myers Hannah E. Xavier Michael A. Marciano Revisiting single cell analysis in forensic science
description	Abstract Forensic science has yet to take full advantage of single cell analysis. Its greatest benefit is the ability to alleviate the challenges associated with DNA mixture analysis, which remains a significant hurdle in forensic science. Many of the factors that cause complexity in mixture interpretation are absent in single cell analyses—multiple contributors, varied levels of contribution, and allele masking. This study revisits single cell analyses in the context of forensic identification, introducing previously unseen depth to the characterization of data generated from single cells using a novel pipeline that includes recovery of single cells using the DEPArray NxT and amplification using the PowerPlex Fusion 6c kit with varied PCR cycles (29, 30, and 31). The resulting allelic signal was assessed using analytical thresholds of 10, 100, and 150RFU. The mean peak heights across the sample sets generally increased as cycle number increased, 75.0 ± 85.3, 147.1 ± 172.6, and 226.1 ± 298.2 RFU, for 29, 30, and 31 cycles, respectively. The average proportion of allele/locus dropout was most significantly impacted by changes in the detection threshold, whereas increases in PCR cycle number had less impact. Overall data quality improved notably when increasing PCR from 29 to 30 cycles, less improvement and more volatility was introduced at 31 cycles. The average random match probabilities for the 29, 30, and 31 cycle sets at 150RFU are 1 in 2.4 × 1018 ± 1.46 × 1019, 1 in 1.49 × 1025 ± 5.8 × 1025, and 1 in 1.83 × 1024 ± 8.09 × 1024, respectively. This demonstrates the current power of single cell analysis in removing the need for complex mixture analysis.
format	article
author	Davis R. L. Watkins Dan Myers Hannah E. Xavier Michael A. Marciano
author_facet	Davis R. L. Watkins Dan Myers Hannah E. Xavier Michael A. Marciano
author_sort	Davis R. L. Watkins
title	Revisiting single cell analysis in forensic science
title_short	Revisiting single cell analysis in forensic science
title_full	Revisiting single cell analysis in forensic science
title_fullStr	Revisiting single cell analysis in forensic science
title_full_unstemmed	Revisiting single cell analysis in forensic science
title_sort	revisiting single cell analysis in forensic science
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/3a11999e2a26467bb5eeb1488d84f7e9
work_keys_str_mv	AT davisrlwatkins revisitingsinglecellanalysisinforensicscience AT danmyers revisitingsinglecellanalysisinforensicscience AT hannahexavier revisitingsinglecellanalysisinforensicscience AT michaelamarciano revisitingsinglecellanalysisinforensicscience
_version_	1718378267639021568

Revisiting single cell analysis in forensic science

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