LABEL: fast and accurate lineage assignment with assessment of H5N1 and H9N2 influenza A hemagglutinins.
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.
Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America.
Samuel S
SS
Shepard
Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America.
C Todd
CT
Davis
Laboratory of Virus Evolution in Program of Emerging Infectious Diseases, Duke-NUS Graduate Medical School, Singapore, Singapore ; Center for Infectious Diseases, The University of Texas School of Public Health, Houston, Texas, United States of America.
Justin
J
Bahl
Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America.
Pierre
P
Rivailler
Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America.
Ian A
IA
York
Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America.
Ruben O
RO
Donis
D000818:Animals; D001499:Bayes Theorem; D019070:Cell Lineage; D002645:Chickens; D019143:Evolution, Molecular; D019267:Hemagglutinin Glycoproteins, Influenza Virus / Q000032:analysis* / Q000235:genetics; D053124:Influenza A Virus, H5N1 Subtype / Q000145:classification / Q000235:genetics / Q000472:pathogenicity; D053127:Influenza A Virus, H9N2 Subtype / Q000145:classification / Q000235:genetics / Q000472:pathogenicity*; D005585:Influenza in Birds / Q000235:genetics / Q000821:virology*; D010802:Phylogeny; D011201:Poultry Diseases / Q000821:virology*; D017422:Sequence Analysis, DNA; D012984:Software
D019267:Hemagglutinin Glycoproteins, Influenza Virus