The project identified a number of mRNA transcripts in blood, semen, saliva, vaginal secretions, and teeth that undergo degradation during storage. The degradation profiles of transcripts can vary, creating an opportunity for the correlation of degradation rates with sample age. The first half of this project was spent developing transcript "databases" that were composed of degradation profiles of thousands of transcripts, with some common to all or subgroups of body fluid types, or transcripts restricted to individual body fluids or tissues. This data was produced with RNA sequencing (RNA-seq) on an Ion Torrent PGM platform, using a method that enables individual transcripts to be quantified. These experiments not only revealed the overall characteristics of mRNA degradation in dried stains, but also enabled the identification of individual transcripts whose degradation kinetics with time in storage suggested the feasibility of using RNA degradation as a measure of elapsed time. Researchers used the information obtained from the RNA-seq studies to examine the degradation of specific mRNA transcripts using qPCR. The annual report filed in December 2016 summarizes progress in developing qPCR technology that would reliably estimate the age of dried semen and bloodstains. Future research will examine the effects of the environment on this process. 3 figures, 3 tables, and 5 references
Transcriptome Sequencing of Forensically Relevant Biological Fluids and Tissues To Optimize Degradation Analysis for Sample Age Estimation
NCJ Number
252288
Date Published
December 2017
Length
11 pages
Annotation
Findings and methodology are reported for a research project with the following goals: 1) Use whole transcriptome sequencing data from fresh and aged body fluid stains to identify mRNA markers that exhibit degradation patterns that closely correlate with sample age; and 2) Develop real-time, quantitative assays (qPCR) for the mRNA markers identified from sequencing and begin the process of developing a valid method for estimating the age of evidentiary samples recovered from a crime scene.
Abstract
Date Published: December 1, 2017