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Identification of the body fluid donors from mixture stains using bulk transcriptomes data.
Huan Yu1, Jiayan Li1, Jiaxin Ji1
1School of Forensic Medicine, Shanxi Medical University, No. 55 Wenhua Street, Yuci District, Jinzhong, Shanxi 030619, China.
Briefings in Bioinformatics
|December 12, 2025
Summary
This study demonstrates that bulk transcriptomes data can effectively deconvolute complex biological mixtures, aiding in identifying body fluid donors at crime scenes. This novel approach enhances mixture deconvolution for forensic investigations.
Area of Science:
- Forensic Science
- Molecular Biology
- Bioinformatics
Background:
- Mixture deconvolution is crucial in forensic science but challenging, especially with multiple contributors.
- RNA-based genotyping aids in assigning body fluids, but transcriptome sequencing is underutilized for mixture deconvolution.
Purpose of the Study:
- To investigate the feasibility of using bulk transcriptomes data for deconvoluting biological mixtures.
- To develop and validate a novel approach for identifying body fluid donors in multi-body-fluid mixtures using transcriptomic data.
Main Methods:
- Developed computational deconvolution methods to infer body fluid proportions from bulk transcriptomes data.
- Utilized robust regression-based deconvolution with unnormalized expression profiles.
- Tested the method on both in-silico and real biological mixtures.
Main Results:
- Body fluid compositions of mixtures were determined with high accuracy.
- Single Nucleotide Polymorphisms (SNPs) corresponding to specific donors were successfully extracted.
- High likelihood ratios and strong evidentiary weight were achieved for individual donor identification.
Conclusions:
- Bulk transcriptomes data are a viable tool for identifying mixture contributors in forensic contexts.
- This study provides new avenues for advancing mixture deconvolution techniques.
- The developed method offers accurate identification of body fluid donors from complex mixtures.
