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A quantifiler™ trio-based HRM screening assay for the accurate prediction of single source versus mixed biological samples

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Abstract

At present, the forensic DNA workflow is not capable of providing information about the contributor status (single source vs. multiple contributors) of evidentiary samples prior to end-point analysis. This exacerbates the challenges inherent to mixtures and low-template DNA samples. If additional sample information could be provided earlier in the workflow, protocols could be implemented to mitigate these challenges. An integrated Quantiplex®- high resolution melt (HRM) assay was shown to be effective in distinguishing between single source and mixture DNA samples; however, integration of the HRM assay into a more commonly used chemistry would be beneficial to the practitioner community. Thus, the assay was redesigned as an integrated Quantifiler™ Trio-HRM assay, which included the identification of a new DNA-binding dye, an increased reaction volume, and the establishment of new data analysis and standard curve metrics for all targets. This redesigned assay produced quantification values and qualitative values that were comparable to those produced when the same samples were tested using the standard Quantifiler™ Trio chemistry and settings. Further, STR profiles generated with quantification values produced from the integrated Quantifiler™ Trio-HRM assay and standard Quantifiler™ Trio chemistry were complete and fully concordant. Most importantly, the integrated Quantifiler™ Trio-HRM assay was able to accurately predict whether a sample was single source or a mixture 79.2% of the time, demonstrating the potential of this approach. With the incorporation of an expanded training set for prediction modeling, and completion of critical developmental validation studies, this assay could prove useful to the forensic DNA practitioner community.

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Data availability

The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

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Acknowledgements

National Institute of Justice, Grant Award No: 2019-DU-BX-0003

Funding

The research leading to these results received funding from the NIJ under Grant Agreement No 2019-DU-BX-0003.

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Authors and Affiliations

  1. Department of Forensic Science, Virginia Commonwealth University, 1015 Floyd Avenue, Richmond, VA, 23284, USA

    Dayanara Torres, Chastyn Smith, Andrea L. Williams, Jordan O. Cox, Sarah J. Seashols-Williams & Tracey Dawson Green

  2. Integrative Life Sciences, Virginia Commonwealth University, 1000 Cary Street, Richmond, VA, 23284, USA

    Chastyn Smith

  3. Department of Statistical Sciences & Operations Research, Virginia Commonwealth University, 1015 Floyd Avenue, Richmond, VA, 23284, USA

    Edward L. Boone

Authors
  1. Dayanara Torres
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  2. Chastyn Smith
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  3. Andrea L. Williams
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  4. Jordan O. Cox
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  5. Sarah J. Seashols-Williams
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  6. Edward L. Boone
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  7. Tracey Dawson Green
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Contributions

All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by Dayanara Torres, Chastyn Smith and Andrea Williams. The first draft of the manuscript was written by Chastyn Smith and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Chastyn Smith.

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Ethics approval

This study was performed in line with the principles of the Declaration of Helsinki. Approval was granted by the Institutional Review Board (IRB) of Virginia Commonwealth University (VCU) protocol (HM20002931) on 01/03/2023.

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Informed consent was obtained from all individual participants included in the study.

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Torres, D., Smith, C., Williams, A.L. et al. A quantifiler™ trio-based HRM screening assay for the accurate prediction of single source versus mixed biological samples. Int J Legal Med 137, 1639–1651 (2023). https://doi.org/10.1007/s00414-023-03070-6

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  • DOI: https://doi.org/10.1007/s00414-023-03070-6

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