Dataset Information

Forensic Body Fluid Identification by Analysis of Multiple RNA Markers Using NanoString Technology.

ABSTRACT: RNA analysis has become a reliable method of body fluid identification for forensic use. Previously, we developed a combination of four multiplex quantitative PCR (qRT-PCR) probes to discriminate four different body fluids (blood, semen, saliva, and vaginal secretion). While those makers successfully identified most body fluid samples, there were some cases of false positive and negative identification. To improve the accuracy of the identification further, we tried to use multiple markers per body fluid and adopted the NanoString nCounter system instead of a multiplex qRT-PCR system. After measuring tens of RNA markers, we evaluated the accuracy of each marker for body fluid identification. For body fluids, such as blood and semen, each body fluid-specific marker was accurate enough for perfect identification. However, for saliva and vaginal secretion, no single marker was perfect. Thus, we designed a logistic regression model with multiple markers for saliva and vaginal secretion and achieved almost perfect identification. In conclusion, the NanoString nCounter is an efficient platform for measuring multiple RNA markers per body fluid and will be useful for forensic RNA analysis.

SUBMITTER: Park JL

PROVIDER: S-EPMC3897857 | biostudies-other | 2013 Dec

REPOSITORIES: biostudies-other

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Forensic Body Fluid Identification by Analysis of Multiple RNA Markers Using NanoString Technology.

Park Jong-Lyul JL Park Seong-Min SM Kim Jeong-Hwan JH Lee Han-Chul HC Lee Seung-Hwan SH Woo Kwang-Man KM Kim Seon-Young SY

Genomics & informatics 20131231 4

RNA analysis has become a reliable method of body fluid identification for forensic use. Previously, we developed a combination of four multiplex quantitative PCR (qRT-PCR) probes to discriminate four different body fluids (blood, semen, saliva, and vaginal secretion). While those makers successfully identified most body fluid samples, there were some cases of false positive and negative identification. To improve the accuracy of the identification further, we tried to use multiple markers per b ...[more]

PMID: 24465241

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Project description:The identification of body fluids is an essential tool for clarifying the course of events at a criminal site. The analytical problem is the fact that the biological material has been very often exposed to detrimental exogenous influences. Thereby, the molecular substrates used for the identification of the traces may become degraded. So far, most protocols utilize cell specific proteins or RNAs. Instead of measuring these more sensitive compounds this paper describes the application of the differential DNA-methylation. As a result of two genome wide screenings with the Illumina HumanMethylation BeadChips 27 and 450k we identified 150 candidate loci revealing differential methylation with regard to the body fluids venous blood, menstrual blood, vaginal fluid, saliva and sperm. Among them we selected 9 loci as the most promising markers. For the final determination of the methylation degree we applied the SNuPE-method. Because the degree of methylation might be modified by various endogenous and exogenous factors, we tested each marker with approximately 100 samples of each target fluid in a validation study. The stability of the detection procedure is proved in various simulated forensic surroundings according to standardized conditions. We studied the potential influence of 12 relatively common tumors on the methylation of the 9 markers. For this purpose the target fluids of 34 patients have been analysed. Only the cervix carcinoma might have an remarkable effect because impairing the signal of both vaginal markers. Using the Illumina MiSeq device we tested the potential influence of cis acting sequence variants on the methylation degree of the 9 markers in the specific body fluid DNA of 50 individuals. For 4 marker loci we observed such an influence either by sole SNPs or haplotypes. The identification of each target fluid is possible in arbitrary mixtures with the remaining four body fluids. The sensitivity of the individual body fluid tests is in the same range as for the forensic STR-analysis. It is the first forensic body fluid protocol which considers the exogenic and endogenic parameters potentially interfering with the true results.

Project description:The human microbiome contributes significantly to the genetic content of the human body. Genetic and environmental factors help shape the microbiome, and as such, the microbiome can be unique to an individual. Previous studies have demonstrated the potential to use microbiome profiling for forensic applications; however, a method has yet to identify stable features of skin microbiomes that produce high classification accuracies for samples collected over reasonably long time intervals. A novel approach is described here to classify skin microbiomes to their donors by comparing two feature types: Propionibacterium acnes pangenome presence/absence features and nucleotide diversities of stable clade-specific markers. Supervised learning was used to attribute skin microbiomes from 14 skin body sites from 12 healthy individuals sampled at three time points over a >2.5-year period with accuracies of up to 100% for three body sites. Feature selection identified a reduced subset of markers from each body site that are highly individualizing, identifying 187 markers from 12 clades. Classification accuracies were compared in a formal model testing framework, and the results of this analysis indicate that learners trained on nucleotide diversity perform significantly better than those trained on presence/absence encodings. This study used supervised learning to identify individuals with high accuracy and associated stable features from skin microbiomes over a period of up to almost 3 years. These selected features provide a preliminary marker panel for future development of a robust and reproducible method for skin microbiome profiling for forensic human identification.IMPORTANCE A novel approach is described to attribute skin microbiomes, collected over a period of >2.5 years, to their individual hosts with a high degree of accuracy. Nucleotide diversities of stable clade-specific markers with supervised learning were used to classify skin microbiomes from a particular individual with up to 100% classification accuracy for three body sites. Attribute selection was used to identify 187 genetic markers from 12 clades which provide the greatest differentiation of individual skin microbiomes from 14 skin sites. This study performs skin microbiome profiling from a supervised learning approach and obtains high classification accuracy for samples collected from individuals over a relatively long time period for potential application to forensic human identification.

Dataset Information

Forensic Body Fluid Identification by Analysis of Multiple RNA Markers Using NanoString Technology.

Publications

Forensic Body Fluid Identification by Analysis of Multiple RNA Markers Using NanoString Technology.

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