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LABEL: Fast and Accurate Lineage Assignment with Assessment of H5N1 and H9N2 Influenza A Hemagglutinins

Journal Article · · PLoS ONE
 [1];  [2];  [3];  [2];  [2];  [2]
  1. Centers for Disease Control and Prevention (CDC), Atlanta, GA (United States); OSTI
  2. Centers for Disease Control and Prevention (CDC), Atlanta, GA (United States)
  3. Duke-NUS Graduate Medical School (Singapore)
+ Show Author Affiliations
The evolutionary classification of influenza genes into lineages is a first step in understanding their molecular epidemiology and can inform the subsequent implementation of control measures. We introduce a novel approach called Lineage Assignment By Extended Learning (LABEL) to rapidly determine cladistic information for any number of genes without the need for time-consuming sequence alignment, phylogenetic tree construction, or manual annotation. Instead, LABEL relies on hidden Markov model profiles and support vector machine training to hierarchically classify gene sequences by their similarity to pre-defined lineages. We assessed LABEL by analyzing the annotated hemagglutinin genes of highly pathogenic (H5N1) and low pathogenicity (H9N2) avian influenza A viruses. Using the WHO/FAO/OIE H5N1 evolution working group nomenclature, the LABEL pipeline quickly and accurately identified the H5 lineages of uncharacterized sequences. Moreover, we developed an updated clade nomenclature for the H9 hemagglutinin gene and show a similarly fast and reliable phylogenetic assessment with LABEL. While this study was focused on hemagglutinin sequences, LABEL could be applied to the analysis of any gene and shows great potential to guide molecular epidemiology activities, accelerate database annotation, and provide a data sorting tool for other large-scale bioinformatic studies.
Research Organization:
Oak Ridge Institute for Science and Education (ORISE), Oak Ridge, TN (United States)
Sponsoring Organization:
Centers for Disease Control and Prevention; USDOE Office of Science (SC)
Grant/Contract Number:
SC0014664
OSTI ID:
1904881
Journal Information:
PLoS ONE, Journal Name: PLoS ONE Journal Issue: 1 Vol. 9; ISSN 1932-6203
Publisher:
Public Library of ScienceCopyright Statement
Country of Publication:
United States
Language:
English

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Cited By (7)

Genesis of avian influenza H9N2 in Bangladesh journal January 2014
Clade-level Spatial Modelling of HPAI H5N1 Dynamics in the Mekong Region Reveals New Patterns and Associations with Agro-Ecological Factors journal July 2016
Phylogenetic Clustering by Linear Integer Programming (PhyCLIP) posted_content January 2019
Nomenclature updates resulting from the evolution of avian influenza A(H5) virus clades 2.1.3.2a, 2.2.1, and 2.3.4 during 2013-2014 journal August 2015
Use of Highly Pathogenic Avian Influenza A(H5N1) Gain-Of-Function Studies for Molecular-Based Surveillance and Pandemic Preparedness journal December 2014
Erratum to: Viral deep sequencing needs an adaptive approach: IRMA, the iterative refinement meta-assembler journal October 2016
Diversity and distribution of type A influenza viruses: an updated panorama analysis based on protein sequences journal June 2019

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Related Subjects

59 BASIC BIOLOGICAL SCIENCES
Avian influenza
H5N1
hidden Markov models
influenza
influenza A virus
phylogenetic analysis
sequence alignment
viral pathogens