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Low-host double MDA workflow for uncultured ASFV positive blood and serum sample sequencing
Chengjun Zhang1,2, Tangyu Cheng1,2, Dongfan Li2,3
1State Key Laboratory of Agricultural Microbiology, Huazhong Agricultural University, Wuhan, China.
Frontiers in Veterinary Science
|October 7, 2022
Summary
This study presents an improved method for sequencing African swine fever virus (ASFV) from uncultured samples, significantly reducing background DNA. This technique enhances whole-genome sequencing efficiency for ASFV surveillance and research.
Area of Science:
- Virology
- Genomics
- Molecular Biology
Background:
- African swine fever (ASF) is a severe, contagious disease caused by the African swine fever virus (ASFV).
- Whole-genome sequencing of ASFV is crucial for understanding viral evolution, transmission, and mutation.
- Analyzing uncultured samples is challenging due to high levels of contaminating host DNA, impacting sequencing efficiency.
Purpose of the Study:
- To develop an effective strategy for reducing background DNA in uncultured ASFV samples.
- To optimize a workflow compatible with next-generation sequencing (NGS) and targeted sequencing (TGS) technologies.
- To enable efficient whole-genome sequencing of ASFV from challenging clinical specimens.
Main Methods:
- An improved C18 spacer Multiple Displacement Amplification (MDA) combined with a host DNA exhaustion strategy was employed.
- The workflow was designed to remove non-ASFV DNA, thereby enriching for viral genetic material.
- Developed custom software for real-time base calling and analysis of ASFV TGS sequencing reads on a cloud server.
Main Results:
- Successfully sequenced two uncultured ASFV-positive samples using the developed workflow.
- Demonstrated a significant reduction in the percentage of background DNA compared to conventional methods.
- The new method proved effective for both NGS and TGS platforms.
Conclusions:
- The improved C18 spacer MDA-combined host DNA exhaustion strategy is highly effective for ASFV whole-genome sequencing from uncultured samples.
- This approach conserves sequencing resources and improves data quality.
- The integrated software facilitates rapid analysis of sequencing data, aiding in ASFV surveillance and control efforts.

