Ultrasensitive sequencing of STR markers utilizing unique molecular identifiers and the SiMSen-Seq methodShow others and affiliations
2024 (English)In: Forensic Science International: Genetics, ISSN 1872-4973, E-ISSN 1878-0326, Vol. 71, article id 103047Article in journal (Refereed) Published
Abstract [en]
Massively parallel sequencing (MPS) is increasingly applied in forensic short tandem repeat (STR) analysis. The presence of stutter artefacts and other PCR or sequencing errors in the MPS-STR data partly limits the detection of low DNA amounts, e.g., in complex mixtures. Unique molecular identifiers (UMIs) have been applied in several scientific fields to reduce noise in sequencing. UMIs consist of a stretch of random nucleotides, a unique barcode for each starting DNA molecule, that is incorporated in the DNA template using either ligation or PCR. The barcode is used to generate consensus reads, thus removing errors. The SiMSen-Seq (Simple, multiplexed, PCR-based barcoding of DNA for sensitive mutation detection using sequencing) method relies on PCR-based introduction of UMIs and includes a sophisticated hairpin design to reduce unspecific primer binding as well as PCR protocol adjustments to further optimize the reaction. In this study, SiMSen-Seq is applied to develop a proof-of-concept seven STR multiplex for MPS library preparation and an associated bioinformatics pipeline. Additionally, machine learning (ML) models were evaluated to further improve UMI allele calling. Overall, the seven STR multiplex resulted in complete detection and concordant alleles for 47 single-source samples at 1 ng input DNA as well as for low-template samples at 62.5 pg input DNA. For twelve challenging mixtures with minor contributions of 10 pg to 150 pg and ratios of 1–15% relative to the major donor, 99.2% of the expected alleles were detected by applying the UMIs in combination with an ML filter. The main impact of UMIs was a substantially lowered number of artefacts as well as reduced stutter ratios, which were generally below 5% of the parental allele. In conclusion, UMI-based STR sequencing opens new means for improved analysis of challenging crime scene samples including complex mixtures. © 2024 The Authors
Place, publisher, year, edition, pages
Elsevier Ireland Ltd , 2024. Vol. 71, article id 103047
National Category
Bioinformatics (Computational Biology)
Identifiers
URN: urn:nbn:se:ri:diva-72751DOI: 10.1016/j.fsigen.2024.103047Scopus ID: 2-s2.0-85189897942OAI: oai:DiVA.org:ri-72751DiVA, id: diva2:1858297
Note
We thank Froste Svensson for input on the bioinformatics pipeline and Nelly Gyll\u00F6 Lind and Markus Andr\u00E9 Soma for practical assistance in pre-studies. This study was funded by VINNOVA: Project title \u201CUltrak\u00E4nsliga analyser f\u00F6r b\u00E4ttre h\u00E4lsa och kriminalteknik (ULTRA-UDI)\u201D and reference number 2020\u201304141, and V\u00E4stra G\u00F6talandsregionen RUN 2021\u201300059. Anders St\u00E5hlberg was funded by Region V\u00E4stra G\u00F6taland; Swedish Cancer Society [22\u20132080]; Swedish Childhood Cancer Foundation [2022\u20130030]; Swedish Research Council [2021\u201301008]; the Swedish state under the agreement between the Swedish government and the county councils, the ALF-agreement [965065]; Sweden's Innovation Agency [2018\u201300421, 2020\u201304141] and the Sj\u00F6berg Foundation. Points of view in this document are those of the NIST-affiliated authors and do not necessarily represent the official position or policies of the U.S. Department of Commerce. Certain equipment, instruments, software, or materials are identified in this paper to specify the experimental procedure adequately. Such identification is not intended to imply recommendation or endorsement of any product or service by NIST, nor is it intended to imply that the materials or equipment identified are necessarily the best available for the purpose. All work performed at NIST has been reviewed and approved by the U. S. National Institute of Standards and Technology Research Protections Office. This study was determined to be \u201Cnot human subjects research\u201D (often referred to as research not involving human subjects) as defined in U. S. Department of Commerce Regulations, 15 CFR 27, also known as the Common Rule (45 CFR 46, Subpart A), for the Protection of Human Subjects by the NIST Human Research Protections Office and therefore not subject to oversight by the NIST Institutional Review Board (MML-16\u20130080). All data handling performed in Sweden was done in accordance with approval no 2023\u201305921\u20131 from the Swedish Ethical Review Authority. A.S. is co-inventor of the SiMSen-Seq technology that is patent protected (U.S. Serial No.:15/552,618). A.S. declares stock ownership and is a board member in Tulebovaasta, Iscaff Pharma and SiMSen Diagnostics. G.J. declares employment and stock ownership in SiMSen Diagnostics.
2024-05-162024-05-162025-09-23Bibliographically approved