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  • 1.
    Staadig, Adam
    et al.
    Linköpings universitet, Institutionen för biomedicinska och kliniska vetenskaper, Avdelningen för molekylär medicin och virologi. Linköpings universitet, Medicinska fakulteten. Natl Board Forens Med, Dept Forens Genet & Forens Toxicol, S-58758 Linkoping, Sweden.
    Hedman, Johannes
    Swedish Police Author, Natl Forens Ctr, S-58194 Linkoping, Sweden; Lund Univ, Sweden.
    Tillmar, Andreas
    Linköpings universitet, Institutionen för biomedicinska och kliniska vetenskaper, Avdelningen för molekylär medicin och virologi. Linköpings universitet, Medicinska fakulteten. Natl Board Forens Med, Dept Forens Genet & Forens Toxicol, S-58758 Linkoping, Sweden.
    Applying Unique Molecular Indices with an Extensive All-in-One Forensic SNP Panel for Improved Genotype Accuracy and Sensitivity2023Ingår i: Genes, E-ISSN 2073-4425, Vol. 14, nr 4, artikel-id 818Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    One of the major challenges in forensic genetics is being able to detect very small amounts of DNA. Massively parallel sequencing (MPS) enables sensitive detection; however, genotype errors may exist and could interfere with the interpretation. Common errors in MPS-based analysis are often induced during PCR or sequencing. Unique molecular indices (UMIs) are short random nucleotide sequences ligated to each template molecule prior to amplification. Applying UMIs can improve the limit of detection by enabling accurate counting of initial template molecules and removal of erroneous data. In this study, we applied the FORCE panel, which includes similar to 5500 SNPs, with a QIAseq Targeted DNA Custom Panel (Qiagen), including UMIs. Our main objective was to investigate whether UMIs can enhance the sensitivity and accuracy of forensic genotyping and to evaluate the overall assay performance. We analyzed the data both with and without the UMI information, and the results showed that both genotype accuracy and sensitivity were improved when applying UMIs. The results showed very high genotype accuracies (>99%) for both reference DNA and challenging samples, down to 125 pg. To conclude, we show successful assay performance for several forensic applications and improvements in forensic genotyping when applying UMIs.

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  • 2.
    Staadig, Adam
    et al.
    Linköpings universitet, Institutionen för biomedicinska och kliniska vetenskaper, Avdelningen för molekylär medicin och virologi. Linköpings universitet, Medicinska fakulteten. Natl Board Forens Med, Dept Forens Genet & Forens Toxicol, Linkoping, Sweden.
    Tillmar, Andreas
    Linköpings universitet, Institutionen för biomedicinska och kliniska vetenskaper, Avdelningen för molekylär medicin och virologi. Linköpings universitet, Medicinska fakulteten. Natl Board Forens Med, Dept Forens Genet & Forens Toxicol, Linkoping, Sweden.
    Evaluation of microhaplotypes in forensic kinship analysis from a Swedish population perspective2021Ingår i: International journal of legal medicine, ISSN 0937-9827, E-ISSN 1437-1596, Vol. 135, nr 4, s. 1151-1160Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    The development of massively parallel sequencing (MPS) technology has enabled the discovery of several new types of forensic markers where microhaplotypes are one of these promising novel genetic markers. Microhaplotypes are, commonly, less than 300 nucleotides in length and consist of two or more closely linked single-nucleotide polymorphisms (SNPs). In this study, we have examined a custom-made QIAseq Microhaplotype panel (Qiagen), including 45 different microhaplotype loci. DNA libraries were prepared according to the GeneRead DNAseq Targeted Panels V2 library preparation workflow (Qiagen) and sequenced on a MiSeq FGx instrument (Verogen). We evaluated the performance of the panel based on 75 samples of Swedish origin and haplotype frequencies were established. We performed sensitivity studies and could detect haplotypes at input amounts down to 0.8 ng. We also studied mixture samples with two contributors for which haplotypes, for the minor contributor, were detectable down to the level of 1:100. Furthermore, we executed kinship simulations to evaluate the usefulness of this panel in kinship analysis. The results showed that both paternity and full sibling cases can clearly be solved. When simulating a half sibling versus unrelated case scenario, there were, however, some overlap of the likelihood ratio distributions potentially resulting in inconclusiveness. To conclude, the results of this initial study are promising for further implementation of this microhaplotype assay into the forensic field, although we noticed some primer design issues that could be optimized, which possibly would increase the power of the assay.

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  • 3.
    Junker, Klara
    et al.
    National Forensic Centre, Sweden.
    Staadig, Adam
    Linköpings universitet, Institutionen för klinisk och experimentell medicin, Avdelningen för hematopoes och utvecklingsbiologi. Linköpings universitet, Medicinska fakulteten. National Board of Forensic Medicine, Sweden.
    Sidstedt, Maja
    National Forensic Centre, Sweden; Lund Univ, Sweden.
    Tillmar, Andreas
    Linköpings universitet, Institutionen för klinisk och experimentell medicin, Avdelningen för hematopoes och utvecklingsbiologi. Linköpings universitet, Medicinska fakulteten. National Board of Forensic Medicine, Sweden.
    Hedman, Johannes
    National Forensic Centre, Sweden; Lund Univ, Sweden.
    Phenotype prediction accuracy: A Swedish perspective2019Ingår i: Forensic Science International: Genetics Supplement Series, ISSN 1875-1768, E-ISSN 1875-175X, Vol. 7, nr 1, s. 384-386Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Methods for SNP-based phenotype prediction have recently been developed, but prediction accuracy data for several populations and regions are missing. We analysed the accuracy of hair and eye colour predictions for 111 individuals residing in Sweden, using the ForenSeq system and the MiSeq FGx instrument (Verogen). Observed colours were compared to predicted colours, using the colour with the highest probability value for each prediction. Overall, 80% of eye colour predictions were correct, but the system failed to predict intermediate/green eye colour in our cohort. For hair colour, 58% of predictions were correct, and the majority of incorrect predictions were related to brown hair. To assess if prediction accuracy could be improved by the exclusion of predictions with low probabilities, we applied a threshold of amp;gt;= 0.7. The threshold improved eye colour prediction, from 80% to 85% correct predictions, whereas hair colour prediction accuracy was virtually unaffected (58% versus 57% correct predictions). In summary, the phenotype prediction accuracy was acceptable in our cohort and the use of a threshold was only useful for eye colour predictions.

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