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A massively parallel sequencing assay of microhaplotypes for mixture deconvolution

NCJ Number
Forensic Science International Genetics Supplement Series Volume: 7 Issue: 1 Dated: 2019 Pages: 522-524
Date Published
3 pages

This study evaluated the mixture performance of a 74 microhap locus-assay on the Ion S5™ and compared the results to size-based and sequence-based STR analysis.


Microhaplotypes (microhaps or MHs) are markers characterized by a set of single nucleotide polymorphisms (SNPs) within an expanse of 300 bp exhibiting multiple allelic combinations. Microhap alleles within a locus have all the same size, do not generate stutter artifacts, and have low mutation rates. These features complement short tandem repeats (STRs) for human identification and mixture deconvolution. The analysis of microhaps is improved by massively parallel sequencing (MPS) that enables the determination of the parental SNP haplotypes by clonal sequencing of each strand. In the current research, the detection limit of the panel was tested and the panel’s performance evaluated in parallel with the GlobalFiler™ and Precision ID GlobalFiler™ NGS STR Panel v2 kits. A set of two-to-five person mixtures was simulated at different contribution ratios and amounts of DNA (1 ng and 10 ng) to mimic casework-like samples. The 74-locus panel was sensitive down to 50 pg of input DNA. Size-based STR mixture analysis was challenging, but was improved by MPS when the allele sequence of the minor contributor was different from the overlapping stutter of the major. For two-person mixtures, full microhap profile of the minor donor could be reported at 1:10 ratio, with minimal allele/locus dropout at 20:1, and more significant dropout at higher mixture ratios. For three-to-five person mixtures, full microhap profiles were obtained for all minor donors, with the exception of a few loci that underperformed at imbalanced mixture ratios. These findings suggest that microhaps can improve mixture deconvolution and supplement STR typing analysis. (publisher abstract modified)



Date Published: January 1, 2019