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  • Title: A microhaplotypes panel for massively parallel sequencing analysis of DNA mixtures.
    Author: Chen P, Deng C, Li Z, Pu Y, Yang J, Yu Y, Li K, Li D, Liang W, Zhang L, Chen F.
    Journal: Forensic Sci Int Genet; 2019 May; 40():140-149. PubMed ID: 30836262.
    Abstract:
    Massively parallel sequencing (MPS) technology enables the simultaneous analysis of different kinds of forensic genetic markers as well as the detection of the alleles with minor contributions in a highly unbalanced DNA mixture. In our previous study, we presented a novel set of microhaplotype loci and evaluated their application value in analyzing the DNA mixtures. However, several issues remain unclear, for example (i) whether the major or the minor donor in an unbalanced DNA mixture can be compared with a known suspect, (ii) whether the proportion of each contributor in a DNA mixture can be inferred, (iii) whether the captured alleles can be assigned to the major or the minor donor. To further address these issues, during the present study, we increased the number of loci in a single multiplex system to 25 (all the microhaplotypes have a length less than 50 bp). The DNA samples of 60 unrelated Han Chinese individuals, 40 artificially made DNA mixtures with different mixing proportions were analyzed with MPS by using the microhaplotypes panel. By comparing the population genetic data of the 25 microhaplotypes in 26 populations from 1000 Genome Project (1000 G), the microhaplotypes were found to have similar high Ae values in different populations. The likelihood ratios were further employed to compare the mixtures and known suspects. The major contributor could be well identified in both balanced and unbalanced samples. The minor contributor could also be identified if capturing enough loci. When we divided the microhaplotypes into different subgroups, significant correlation was found between the allele depth ratio and the gradual mixing ratios. The allele depth patterns in balanced, mildly imbalanced and severely imbalanced mixtures were clarified, and we found that certain loci could be discriminated from the contributors and they could be used for direct individual identification.
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