Abstract
Biological traces found at crime scenes are analysed not only to genetically identify the donor(s) but also to determine the composition of the stain. For some cases, it is essential to associate a body fluid with a donor. Especially in mixed body fluid stains, but also in body fluid stains that appear to be single-source, this may be of importance. Linking a DNA profile (sub-source level) with evidence from a presumptive test or mRNA analysis (source level) is not straightforward. Our results support that associating donors and body fluids by means of comparing mixture ratios in RNA and DNA is not recommended. We introduce a set of 35 coding region SNPs (cSNPs) in body fluid-specific mRNA transcripts that represent a direct link between the body fluids and their donors. The discrimination power of the cSNPs was estimated based on allele frequencies calculated from a population sample (n = 188), and we investigated the practical application of the cSNPs in different scenarios. The results demonstrate that more cSNPs are needed to improve the discrimination power. However, the findings are promising as we were able to associate donors with body fluids in mixtures of different body fluids as well as in stains where both donors have contributed the same body fluid, e.g. a blood-blood mixture. In addition, the cSNP assay can be used for body fluid identification. The results of this proof-of-concept study support the use of cSNPs to assign body fluids to the respective donors.
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References
Virkler K, Lednev IK (2009) Analysis of body fluids for forensic purposes: from laboratory testing to non-destructive rapid confirmatory identification at a crime scene. Forensic Sci Int 188(1–3):1–17. https://doi.org/10.1016/j.forsciint.2009.02.013
Juusola J, Ballantyne J (2003) Messenger RNA profiling: a prototype method to supplant conventional methods for body fluid identification. Forensic Sci Int 135(2):85–96
Haas C, Klesser B, Maake C, Bar W, Kratzer A (2009) mRNA profiling for body fluid identification by reverse transcription endpoint PCR and realtime PCR. Forensic Sci Int: Gen 3(2):80–88. https://doi.org/10.1016/j.fsigen.2008.11.003
Hanson E, Ingold S, Haas C, Ballantyne J (2018) Messenger RNA biomarker signatures for forensic body fluid identification revealed by targeted RNA sequencing. Forensic Sci Int: Gen 34:206–221. https://doi.org/10.1016/j.fsigen.2018.02.020
Gill P (2014) Chapter 2—a deep analysis of the basic causes of interpretation errors. In: Gill P (ed) Misleading DNA evidence. Academic Press, San Diego, pp 21–65. https://doi.org/10.1016/B978-0-12-417214-2.00002-4
Gill P, Hicks T, Butler JM, Connolly E, Gusmão L, Kokshoorn B, Morling N, van Oorschot RAH, Parson W, Prinz M, Schneider PM, Sijen T, Taylor D (2018) DNA commission of the international society for forensic genetics: assessing the value of forensic biological evidence—guidelines highlighting the importance of propositions. Forensic Sci Int: Gen 36:189–202. https://doi.org/10.1016/j.fsigen.2018.07.003
Cook R, Evett IW, Jackson G, Jones P, Lambert J (1998) A hierarchy of propositions: deciding which level to address in casework. Sci Justice 38(4):231–239
Taylor D (2016) Probabilistically determining the cellular source of DNA derived from differential extractions in sexual assault scenarios. Forensic Sci Int: Gen 24:124–135. https://doi.org/10.1016/j.fsigen.2016.06.012
Taylor D, Abarno D, Hicks T, Champod C (2016) Evaluating forensic biology results given source level propositions. Forensic Sci Int: Gen 21:54–67. https://doi.org/10.1016/j.fsigen.2015.11.009
de Zoete J, Oosterman W, Kokshoorn B, Sjerps M (2016) Cell type determination and association with the DNA donor. Forensic Sci Int: Gen 25:97–111. https://doi.org/10.1016/j.fsigen.2016.08.004
Harteveld J, Lindenbergh A, Sijen T (2013) RNA cell typing and DNA profiling of mixed samples: can cell types and donors be associated? Sci Justice J Forensic Sci Soc 53(3):261–269. https://doi.org/10.1016/j.scijus.2013.02.001
Ingold S, Haas C, Dørum G, Hanson E, Ballantyne J (2017) Association of a body fluid with a DNA profile by targeted RNA/DNA deep sequencing. Forensic Sci Int Genet Suppl Ser 6:e112–e113. https://doi.org/10.1016/j.fsigss.2017.09.037
Zerbino DR, Achuthan P, Akanni W, Amode MR, Barrell D, Bhai J, Billis K, Cummins C, Gall A, Girón CG, Gil L, Gordon L, Haggerty L, Haskell E, Hourlier T, Izuogu OG, Janacek SH, Juettemann T, To JK, Laird MR, Lavidas I, Liu Z, Loveland JE, Maurel T, McLaren W, Moore B, Mudge J, Murphy DN, Newman V, Nuhn M, Ogeh D, Ong CK, Parker A, Patricio M, Riat HS, Schuilenburg H, Sheppard D, Sparrow H, Taylor K, Thormann A, Vullo A, Walts B, Zadissa A, Frankish A, Hunt SE, Kostadima M, Langridge N, Martin FJ, Muffato M, Perry E, Ruffier M, Staines DM, Trevanion SJ, Aken BL, Cunningham F, Yates A, Flicek P (2018) Ensembl 2018. Nucleic Acids Res 46(D1):D754–D761. https://doi.org/10.1093/nar/gkx1098
DePristo MA, Banks E, Poplin R, Garimella KV, Maguire JR, Hartl C, Philippakis AA, del Angel G, Rivas MA, Hanna M, McKenna A, Fennell TJ, Kernytsky AM, Sivachenko AY, Cibulskis K, Gabriel SB, Altshuler D, Daly MJ (2011) A framework for variation discovery and genotyping using next-generation DNA sequencing data. Nat Genet 43(5):491–498. https://doi.org/10.1038/ng.806
McKenna A, Hanna M, Banks E, Sivachenko A, Cibulskis K, Kernytsky A, Garimella K, Altshuler D, Gabriel S, Daly M, DePristo MA (2010) The genome analysis toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. Genome Res 20(9):1297–1303. https://doi.org/10.1101/gr.107524.110
Van der Auwera GA, Carneiro MO, Hartl C, Poplin R, Del Angel G, Levy-Moonshine A, Jordan T, Shakir K, Roazen D, Thibault J, Banks E, Garimella KV, Altshuler D, Gabriel S, DePristo MA (2013) From FastQ data to high confidence variant calls: the genome analysis toolkit best practices pipeline. Curr Protoc Bioinformatics 43(11):10–33. https://doi.org/10.1002/0471250953.bi1110s43
Gill P, Phillips C, McGovern C, Bright J-A, Buckleton J (2012) An evaluation of potential allelic association between the STRs vWA and D12S391: implications in criminal casework and applications to short pedigrees. Forensic Sci Int: Gen 6(4):477–486. https://doi.org/10.1016/j.fsigen.2011.11.001
Warnes G, Gorjanc G, Leisch F, Man M (2013) Genetics: population genetics. R package version 1(3):8.1
Tillmar AO, Egeland T, Lindblom B, Holmlund G, Mostad P (2011) Using X-chromosomal markers in relationship testing: calculation of likelihood ratios taking both linkage and linkage disequilibrium into account. Forensic Sci Int: Gen 5(5):506–511. https://doi.org/10.1016/j.fsigen.2010.11.004
Fisher R (1951) Standard calculations for evaluating a blood-group system. Heredity 5(1):95–102
Sensabaugh G (1982) Biochemical markers of individuality. In: Saferstein R (ed) Handbook of forensic science. Prentice Hall Inc, Upper Saddle River, pp 338–415
Ewing B, Green P (1998) Base-calling of automated sequencer traces using phred. II. Error probabilities. Genome Res 8(3):186–194
Gimelbrant A, Hutchinson JN, Thompson BR, Chess A (2007) Widespread monoallelic expression on human autosomes. Science 318(5853):1136–1140
Buckland PR (2004) Allele-specific gene expression differences in humans. Hum Mol Genet 13 Spec No 2:R255-260. doi:https://doi.org/10.1093/hmg/ddh227
The 1000 Genomes Project Consortium (2015) A global reference for human genetic variation. Nature 526:68–74. https://doi.org/10.1038/nature15393
Sanchez JJ, Phillips C, Borsting C, Balogh K, Bogus M, Fondevila M, Harrison CD, Musgrave-Brown E, Salas A, Syndercombe-Court D, Schneider PM, Carracedo A, Morling N (2006) A multiplex assay with 52 single nucleotide polymorphisms for human identification. Electrophoresis 27(9):1713–1724. https://doi.org/10.1002/elps.200500671
Evett I, Weir BS (1998) Interpreting DNA evidence: statistical genetics for forensic scientists. Oxford University Press, Incorporated, Oxford
Weir BS (1996) Genetic data analysis II: methods for discrete population genetic data. Sinauer Associates, Sunderland
Acknowledgements
We thank Samuel Koller for support with the MiSeq instrument, Giancarlo Russo and Andres Nussbaum for help with data analysis and all volunteers who provided samples for this study.
Funding
This study was funded by the European Union Seventh Framework Programme (FP7/2007-2013) under grant agreement no. 285487 (EUROFORGEN-NoE) and the National Institute of Justice (NIJ), Office of Justice Programs, U.S. Department of Justice (Award No. 2014-DN-BX-K019). The funding agencies had no role in study design, data analysis and interpretation and in manuscript preparation and submission. The opinions, findings and conclusions or recommendations are those of the authors and do not necessarily reflect those of the funding agencies.
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The sampling was approved by the local ethics commission (Kantonale Ethikkommission Zürich, KEK), declaration of no objection no. 24-2015.
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Ingold, S., Dørum, G., Hanson, E. et al. Assigning forensic body fluids to donors in mixed body fluids by targeted RNA/DNA deep sequencing of coding region SNPs. Int J Legal Med 134, 473–485 (2020). https://doi.org/10.1007/s00414-020-02252-w
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DOI: https://doi.org/10.1007/s00414-020-02252-w