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. 2017 Nov 10;8(11):319.
doi: 10.3390/genes8110319.

Human Organ Tissue Identification by Targeted RNA Deep Sequencing to Aid the Investigation of Traumatic Injury

Affiliations

Human Organ Tissue Identification by Targeted RNA Deep Sequencing to Aid the Investigation of Traumatic Injury

Erin Hanson et al. Genes (Basel). .

Abstract

Molecular analysis of the RNA transcriptome from a putative tissue fragment should permit the assignment of its source to a specific organ, since each will exhibit a unique pattern of gene expression. Determination of the organ source of tissues from crime scenes may aid in shootings and other investigations. We have developed a prototype massively parallel sequencing (MPS) mRNA profiling assay for organ tissue identification that is designed to definitively identify 10 organ/tissue types using a targeted panel of 46 mRNA biomarkers. The identifiable organs and tissues include brain, lung, liver, heart, kidney, intestine, stomach, skeletal muscle, adipose, and trachea. 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. We also demonstrate the ability of the assay to successful identify the tissue source of origin using a single blind study.

Keywords: forensic science; human organ tissue; mRNA; massively parallel sequencing; tissue identification.

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Conflict of interest statement

The authors declare no conflict of interest. The funding sponsors had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, and in the decision to publish the results.

Figures

Figure 1
Figure 1
Gene Expression Heat Map of 48 Tissue-Specific Markers in 10 Tissues (Skeletal muscle, Trachea, Lung, Kidney, Intestine, Heart, Adipose, Brain, Liver, and Stomach). Y-axis—biomarkers (genes); X-axis—tissue samples. Green represents higher expression, red represents lower expression. Clusters of up-regulated gene expression of a group of biomarkers specific to the target tissue are highlighted with blue circles.
Figure 2
Figure 2
Gene Expression Profiles for Different Individual Tissue Types Using the 46-plex Targeted RNA Sequencing Assay. Read counts for 46 tissue specific genes are shown for individual tissue samples (A) brain; (B) lung, (C) liver, (D) skeletal muscle, (E) heart. Colored bars represent expression of tissue-specific biomarkers within the target tissues (grey—brain, pink—lung, purple—liver, blue—skeletal muscle, red—heart). Y-axis—read counts, X-axis—tissue-specific genes (order of markers left to right is the same as shown in Table 1 from top to bottom).
Figure 3
Figure 3
Tissue-Specific Gene Expression Exemplified by Individual Gene Candidates amongst 35 Tissue Samples. Read counts for individual biomarkers (A) UMOD (uromodulin), kidney specific; (B) ADIPOQ, adipose specific; (C) DEFA5, intestine specific; (D) PGA4, stomach specific; (E) BPIFB1, trachea specific, are shown amongst a set of 35 tissue samples (Brain (BRN), N = 5), lung (LUN, N = 3), liver (LIV, N = 4), skeletal Muscle (SKMUS, N = 4), heart (HRT, N = 4), kidney (KID, N = 3), adipose (ADI, N = 2), small intestine (SMINT, N = 4), stomach (STM, N = 3), trachea (TRA, N = 3). Colored bars represent biomarker expression (i.e., read counts) in the target tissue: light green—kidney, yellow—adipose, brown—intestine, blue—stomach, dark green—trachea). Y-axis—read counts, X-axis—tissue samples.
Figure 4
Figure 4
Dendrogram of Single Source Tissue Samples Clustering According to Similarities in Gene Expression. The gene expression correlation distance between samples is indicated by the length of the vertical branch points on the Y-axis.
Figure 5
Figure 5
Identified Biomarker Expression Classes in Two- and Three-Tissue Admixed Samples. The percent contributions for individual biomarkers were calculated (reads per biomarker/total reads per sample). The percentages from each group of tissue-specific biomarkers were combined to determine the percentage of reads per sample attributable to each tissue class. Percent reads attributable to each biomarker group are listed and represented by color: grey—brain, pink—lung, dark green—trachea, purple—liver, blue—skeletal muscle, dark red—heart muscle, red—heart, light green—kidney, brown—intestine, blue—stomach. (A) binary tissue mixtures, (B) ternary tissue mixtures. Brain (BRN), lung (LUN), trachea (TRA), liver (LIV), skeletal Muscle (SKM and MUS), heart muscle (HRM), heart (HRT), kidney (KID), intestine (INT), stomach (STM), small intestine (SMTINT).

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