Evidence map›Paper›PMID 40295995›Full record

ArticleBMC genomics2025

Species-specific RNA barcoding technology for rapid and accurate identification of four types of influenza virus.

Shuai Jiang, Yunyun Ding, Gaili Zhao, Shunxing Ye, Shucan Liu, Yan Yin, Zeqi Li, Xiaoxiao Zou, Daolong Xie, Changqiao You and 1 more

Abstract read
In one paragraph

Article in BMC genomics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Shuai Jiang *College of Biology, Hunan University, Changsha, Hunan, 410082, China.
Yunyun Ding *College of Biology, Hunan University, Changsha, Hunan, 410082, China.
Gaili ZhaoCollege of Biology, Hunan University, Changsha, Hunan, 410082, China.
Shunxing YeCollege of Bioscience and Biotechnology, Hunan Agricultural University, Changsha, Hunan, 410128, China.
Shucan LiuCollege of Biology, Hunan University, Changsha, Hunan, 410082, China.
Yan YinCollege of Biology, Hunan University, Changsha, Hunan, 410082, China.
Zeqi LiCollege of Biology, Hunan University, Changsha, Hunan, 410082, China.
Xiaoxiao ZouCollege of Biology, Hunan University, Changsha, Hunan, 410082, China.
Daolong XieCollege of Biology, Hunan University, Changsha, Hunan, 410082, China.
Changqiao YouCollege of Biology, Hunan University, Changsha, Hunan, 410082, China. hnuycq@hnu.edu.cn.
Xinhong GuoCollege of Biology, Hunan University, Changsha, Hunan, 410082, China. gxh@hnu.edu.cn.

Funding

China Postdoctoral Science Foundation 2021M701160Key Research & Development Project of Nanhua Biomedical H202191490139National Natural Science Foundation of China 32372124The Undergraduate Innovation and Entrepreneurship Training Program XCX2024138
6 · The paper itself

Abstract

backgroundThe influenza virus (IV) is responsible for seasonal flu epidemics. Constant mutation of the virus results in new strains and widespread reinfections across the globe, bringing great challenges to disease prevention and control. Research has demonstrated that barcoding technology efficiently and cost-effectively differentiates closely related species on a large scale. We screened and validated species-specific RNA barcode segments based on the genetic relationships of four types of IVs, facilitating their precise identification in high-throughput sequencing viral samples.

resultsThrough the analysis of single nucleotide polymorphism, population genetic characteristics, and phylogenetic relationships in the training set, 7 IVA type, 29 IVB type, 40 IVC type, and 5 IVD type barcode segments were selected. In the testing set, the nucleotide-level recall rate for all barcode segments reached 96.86%, the average nucleotide-level specificity was approximately 55.27%, the precision rate was 100%, and the false omission rate was 0%, demonstrating high accuracy, specificity, and generalization capabilities for species identification. Ultimately, all four types of IVs were visualized in a combination of one-dimensional and two-dimensional codes and stored in an online database named Influenza Virus Barcode Database (FluBarDB, http://virusbarcodedatabase.top/database/index.html ).

conclusionThis study validates the effective application of RNA barcoding technology in the detection of IVs and establishes criteria and procedures for selecting species-specific molecular markers. These advancements enhance the understanding of the genetic and epidemiological characteristics of IVs and enable rapid responses to viral genetic mutations.

Indexed as

DNA Barcoding, TaxonomicOrthomyxoviridaeRNA, ViralHumansPhylogenyPolymorphism, Single NucleotideSpecies SpecificityRNA, ViralEpidemic surveillanceInfluenza virusRNA barcoding technologySpecies identification

Identifiers

PMID40295995
PMCPMC12036255

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.