mRNA MPS tissue identification assay to aid in the investigation of traumatic injuries
| Autor: | Cordula Haas, Jack Ballantyne, Andrea Patrizia Salzmann, Barbara Fliss, Sabine Hess, Guro Dørum, Erin K. Hanson |
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| Přispěvatelé: | University of Zurich, Ballantyne, Jack |
| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
Pathology
medicine.medical_specialty Candidate gene Adipose tissue 340 Law Spleen 610 Medicine & health Biology 01 natural sciences Pathology and Forensic Medicine Transcriptome 03 medical and health sciences 0302 clinical medicine 510 Mathematics 1311 Genetics Gene expression medicine Genetics 030216 legal & forensic medicine Messenger RNA Massive parallel sequencing 010401 analytical chemistry RNA 10218 Institute of Legal Medicine 0104 chemical sciences 2734 Pathology and Forensic Medicine medicine.anatomical_structure |
| DOI: | 10.5167/uzh-178566 |
| Popis: | Molecular analysis of the RNA transcriptome from a putative tissue fragment should permit assignment to a specific organ since each tissue will exhibit a unique pattern of gene expression. Determination of the organ source of tissues from crime scenes may aid in shooting and stabbing investigations. We have developed a new prototype massively parallel sequencing (MPS) mRNA profiling assay for organ tissue identification, designed to definitively identify 13 organ/tissue types using a targeted panel of 48 mRNA biomarkers. The identifiable organs and tissues include brain, spinal cord, lung, trachea, liver, skeletal muscle, heart, kidney, adipose, intestine, stomach, skin and spleen. The biomarkers were chosen after iterative specificity testing of numerous candidate genes in various tissue types. The assay is very specific with little cross reactivity with non-targeted tissue, and can detect RNA mixtures from different tissues, including two- to five-tissue admixtures. The sensitivity of the assay was evaluated as well as assay reproducibility between library preparations and sequencing runs. We also demonstrate the ability of the assay to successfully identify the tissue source of origin in cadaver samples, tissue samples with varying post mortem intervals (PMI) and mock and bona fide casework samples. We are using the data to train a multivariate statistical model that predicts the tissue type based on the mRNA profile. By considering co-expression of markers the model can recognize distinct expression patterns in each tissue. |
| Databáze: | OpenAIRE |
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