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Updated: Jun 11, 2025

Author Spotlight: Enhanced Histone PTM Isomer Identification Through LC-TIMS-ToF MS/MS and PASEF
Published on: January 12, 2024
Histone modifications of circulating nucleosomes are associated with changes in cell-free DNA fragmentation patterns
Jinyue Bai1,2,3, Peiyong Jiang1,2,3,4, Lu Ji1,2,3
1Centre for Novostics, Hong Kong Science Park, Pak Shek Kok, New Territories, Hong Kong Special Administrative Region, China.
FRAGmentomics-based Histone modification Analysis (FRAGHA) links cell-free DNA (cfDNA) fragmentation patterns to histone modifications, enabling accurate tissue of origin analysis for diagnostics. This novel approach improves liquid biopsy accuracy for various diseases.
Area of Science:
- Molecular Biology
- Genomics
- Biochemistry
Background:
- Analyzing cell-free DNA (cfDNA) tissue of origin is crucial for research and diagnostics.
- Existing methods like bisulfite treatment or immunoprecipitation often lead to DNA loss.
- cfDNA fragmentomics offers a promising avenue, but tools for assessing tissue contributions are needed.
Purpose of the Study:
- To develop a novel approach for analyzing cfDNA tissue contributions using fragmentomic features.
- To identify characteristic fragmentation patterns associated with specific histone modifications.
- To establish FRAGmentomics-based Histone modification Analysis (FRAGHA) for improved liquid biopsy.
Main Methods:
- Developed FRAGmentomics-based Histone modification Analysis (FRAGHA) to analyze cfDNA fragmentation patterns.
- Identified tissue-specific histone H3 lysine 27 acetylation (H3K27ac) and H3 lysine 4 trimethylation (H3K4me3) associated signals.
- Utilized machine learning algorithms with fragmentation patterns for disease detection enhancement.
Main Results:
- FRAGHA showed strong correlation between placenta-specific H3K27ac signal and fetal DNA fraction (r=0.96).
- Liver-specific H3K27ac signal correlated with donor DNA in transplant recipients (r=0.92) and was elevated in hepatocellular carcinoma (HCC).
- Elevated erythroblast- and colon-specific H3K27ac signals were observed in β-thalassemia major and colorectal cancer, respectively.
- Machine learning model using H3K27ac patterns achieved an AUC of 0.97 for HCC detection.
- Distinct fragmentomic patterns were observed for cfDNA from H3K27ac and H3K4me3 regions.
Conclusions:
- FRAGHA effectively analyzes cfDNA tissue contributions by linking fragmentomics to histone modifications.
- This method demonstrates potential for non-invasive diagnostics in various conditions, including cancer and transplantation.
- The study expands the utility of cfDNA fragmentomics and histone modification analysis in liquid biopsy applications.
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