A method for detecting viruses and viral replication in vectors based on small-rna high-throughput sequencing

By using Small-RNA high-throughput sequencing technology, comparing the results with a viral reference database using bwa and Velvet software, and combining this with blastn software for comparison and coverage analysis, the applicability of traditional viral detection methods to unknown viruses has been solved, achieving highly sensitive identification of viral species and replication status.

CN118298924BActive Publication Date: 2026-06-26INST OF ZOOLOGY CHINESE ACAD OF SCI
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
INST OF ZOOLOGY CHINESE ACAD OF SCI
Filing Date
2024-04-03
Publication Date
2026-06-26

AI Technical Summary

Technical Problem

Existing virus detection methods require prior knowledge of potential pathogen sequence information, cannot effectively detect unknown viruses, and RNA degradation severely affects sequencing quality, leading to the loss of viral information.

Method used

Small-RNA high-throughput sequencing technology was used to extract total RNA, construct cDNA libraries, isolate small RNA fragments, and identify virus species and replication status by comparing them with viral reference databases using bwa and Velvet software, combined with blastn software for comparison and coverage analysis.

Benefits of technology

It achieves highly sensitive detection of unknown viruses, avoids the influence of RNA degradation, and can accurately identify virus types and replication status in low-abundance samples. It is suitable for pathogen monitoring of vector-borne infectious diseases and identification of animal viruses.

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Abstract

The application discloses a method for detecting viruses and virus replication in media based on Small-RNA high-throughput sequencing. The application belongs to the technical field of virus detection, and the method for identifying virus types in a to-be-detected sample by Small-RNA sequencing developed by the application comprises the following steps: 1) extracting total RNA from a virus-infected to-be-detected sample, constructing a cDNA library, and separating small RNA sequence fragments from the cDNA library; 2) downloading virus sequences and classification databases from GenBank, and comparing the small RNA sequence fragments with virus sequence files; 3) comparing a contigs3 file with a virus nucleic acid database, selecting sequences with the minimum e value in the comparison results in the contigs3 file, calculating the coverage of the contigs3 sequences in corresponding virus genomes, distinguishing virus information with a coverage threshold, and deducing the virus source of the small RNA sequence.
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