Header

UZH-Logo

Maintenance Infos

mRNA MPS tissue identification assay to aid in the investigation of traumatic injuries


Hanson, Erin; Dorum, Guro; Salzmann, Andrea; Fliss, Barbara; Hess, Sabine; Haas, Cordula; Ballantyne, Jack (2019). mRNA MPS tissue identification assay to aid in the investigation of traumatic injuries. Forensic Science International: Genetics Supplement Series, 7(1):25-26.

Abstract

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.

Abstract

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.

Statistics

Citations

Altmetrics

Downloads

0 downloads since deposited on 09 Jan 2020
0 downloads since 12 months

Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:04 Faculty of Medicine > Institute of Legal Medicine
Dewey Decimal Classification:340 Law
610 Medicine & health
510 Mathematics
Scopus Subject Areas:Health Sciences > Pathology and Forensic Medicine
Life Sciences > Genetics
Uncontrolled Keywords:Pathology and Forensic Medicine, Genetics
Language:English
Date:1 December 2019
Deposited On:09 Jan 2020 15:12
Last Modified:22 Apr 2020 21:45
Publisher:Elsevier
ISSN:1875-175X
OA Status:Closed
Publisher DOI:https://doi.org/10.1016/j.fsigss.2019.09.012

Download

Closed Access: Download allowed only for UZH members