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Using FastID to analyze complex SNP mixtures from indoor dust

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Forensically relevant single nucleotide polymorphisms (SNPs) can provide valuable supplemental information to short tandem repeats (STRs) for investigative leads, and genotyping can now be streamlined using massively parallel sequencing (MPS).… Click to show full abstract

Forensically relevant single nucleotide polymorphisms (SNPs) can provide valuable supplemental information to short tandem repeats (STRs) for investigative leads, and genotyping can now be streamlined using massively parallel sequencing (MPS). Dust is an attractive evidence source, as it accumulates on undisturbed surfaces, often is overlooked by perpetrators, and contains sufficient human DNA for analysis. To assess whether SNPs genotyped from indoor dust using MPS could be used to detect known household occupants, 13 households were recruited and provided buccal samples from each occupant and dust from five predefined indoor locations. Thermo Fisher Scientific Precision ID Identity and Ancestry Panels were utilized for SNP genotyping, and sequencing was completed using Illumina® chemistry. FastID, a software developed to permit mixture analysis and identity searching, was used to assess whether known occupants could be detected from associated household dust samples. A modified “subtraction” method was also used in FastID to estimate the percentage of alleles in each dust sample contributed by known and unknown occupants. On average, 72% of autosomal SNPs were recovered from dust samples. When using FastID, (a) 93% of known occupants were detected in at least one indoor dust sample and could not be excluded as contributors to the mixture, and (b) non‐contributor alleles were detected in 54% of dust samples (29 ± 11 alleles per dust sample). Overall, this study highlights the potential of analyzing human DNA present in indoor dust to detect known household occupants, which could be valuable for investigative leads.

Keywords: indoor dust; dust; dust samples; snp; using fastid; dust using

Journal Title: Journal of Forensic Sciences
Year Published: 2023

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