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Updated: Oct 25, 2025

Mapping Mammalian 3D Genome Interactions with Micro-C-XL
Published on: November 3, 2023
Enhanced mixture interpretation with macrohaplotypes based on long-read DNA sequencing
Jianye Ge1,2, Jonathan King3, Sammed Mandape3
1Center for Human Identification, University of North Texas Health Science Center, Fort Worth, TX, USA. Jianye.Ge@unthsc.edu.
Abstract:
Deconvoluting mixture samples is one of the most challenging problems confronting DNA forensic laboratories. Efforts have been made to provide solutions regarding mixture interpretation. The probabilistic interpretation of Short Tandem Repeat (STR) profiles has increased the number of complex mixtures that can be analyzed. A portion of complex mixture profiles, particularly for mixtures with a high number of contributors, are still being deemed uninterpretable. Novel forensic markers, such as Single Nucleotide Variants (SNV) and microhaplotypes, also have been proposed to allow for better mixture interpretation. However, these markers have both a lower discrimination power compared with STRs and are not compatible with CODIS or other national DNA databanks worldwide. The short-read sequencing (SRS) technologies can facilitate mixture interpretation by identifying intra-allelic variations within STRs. Unfortunately, the short size of the amplicons containing STR markers and sequence reads limit the alleles that can be attained per STR. The latest long-read sequencing (LRS) technologies can overcome this limitation in some samples in which larger DNA fragments (including both STRs and SNVs) with definitive phasing are available. Based on the LRS technologies, this study developed a novel CODIS compatible forensic marker, called a macrohaplotype, which combines a CODIS STR and flanking variants to offer extremely high number of haplotypes and hence very high discrimination power per marker. The macrohaplotype will substantially improve mixture interpretation capabilities. Based on publicly accessible data, a panel of 20 macrohaplotypes with sizes of ~ 8 k bp and the maximum high discrimination powers were designed. The statistical evaluation demonstrates that these macrohaplotypes substantially outperform CODIS STRs for mixture interpretation, particularly for mixtures with a high number of contributors, as well as other forensic applications. Based on these results, efforts should be undertaken to build a complete workflow, both wet-lab and bioinformatics, to precisely call the variants and generate the macrohaplotypes based on the LRS technologies.
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