The increasing sensitivity of DNA profiling techniques has enabled successful amplification from the most minimal cellular material. This means samples containing DNA from more than one contributor are being encountered far more regularly in routine casework. This is problematic as these samples produce mixed profiles that are difficult to interpret, with minor contributors often going undetected.
The SCAnDi project aims to apply single cell genomic techniques to these challenges by developing methodology to robustly generate good quality STR profiles from single cells. This approach could present a methodological shift within the field of forensic human identification (HID), mitigating the need for profile deconvolution, and enabling the identification of minor contributors that may otherwise be obscured by non-target DNA.
Single cells from multi-contributor mixtures can be isolated using fluorescence-activated cell sorting (FACS), enabling rare cells from within a mixed population to be separated and analysed individually. Once separated, whole genome amplification (WGA) methodologies can be utilised to amplify genomic DNA from individual cells to generate enough material for STR profiling through CE or NGS. However, thus far, methods for WGA have shown amplification bias and uneven coverage, leading to poor STR recovery.
Using the BD FACS Discover Imaging Cell Sorter, we have isolated single cells from a 6-contributor mixture of known donors and compared WGA methods across two commercial STR kits to assess DNA profile recovery from single cells. Our preliminary data suggests profiles can be generated that are of comparable quality to those generated from high DNA input levels with a high degree of concordance. Here we present this new data and discuss the contexts in which these methods would be advantageous to forensic science, while exploring hurdles to adoption and implementation.
The increasing sensitivity of DNA profiling techniques has enabled successful amplification from the most minimal cellular material. This means samples containing DNA from more than one contributor are being encountered far more regularly in routine casework. This is problematic as these samples produce mixed profiles that are difficult to interpret, with minor contributors often going undetected.
The SCAnDi project aims to apply single cell genomic techniques to these challenges by developing methodology to robustly generate good quality STR profiles from single cells. This approach could present a methodological shift within the field of forensic human identification (HID), mitigating the need for profile deconvolution, and enabling the identification of minor contributors that may otherwise be obscured by non-target DNA.
Single cells from multi-contributor mixtures can be isolated using fluorescence-activated cell sorting (FACS), enabling rare cells from within a mixed population to be separated and analysed individually. Once separated, whole genome amplification (WGA) methodologies can be utilised to amplify genomic DNA from individual cells to generate enough material for STR profiling through CE or NGS. However, thus far, methods for WGA have shown amplification bias and uneven coverage, leading to poor STR recovery.
Using the BD FACS Discover Imaging Cell Sorter, we have isolated single cells from a 6-contributor mixture of known donors and compared WGA methods across two commercial STR kits to assess DNA profile recovery from single cells. Our preliminary data suggests profiles can be generated that are of comparable quality to those generated from high DNA input levels with a high degree of concordance. Here we present this new data and discuss the contexts in which these methods would be advantageous to forensic science, while exploring hurdles to adoption and implementation.
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PhD Candidate, Earlham Institute
Edie Holmes is a PhD candidate at the Earlham Institute. Her research focuses on developing single-cell techniques to resolve complex forensic samples. Her project aims to integrate cutting-edge genomic research into forensic science, combining single-cell isolation, phenotyping, and sequencing techniques with novel methods for human identification.
