PMID- 31039449 OWN - NLM STAT- MEDLINE DCOM- 20200401 LR - 20200401 IS - 1567-7257 (Electronic) IS - 1567-1348 (Linking) VI - 73 DP - 2019 Sep TI - Evaluating an automated clustering approach in a perspective of ongoing surveillance of porcine reproductive and respiratory syndrome virus (PRRSV) field strains. PG - 295-305 LID - S1567-1348(18)30899-2 [pii] LID - 10.1016/j.meegid.2019.04.014 [doi] AB - Porcine reproductive and respiratory syndrome virus (PRRSV) has a major economic impact on the swine industry. The important genetic diversity needs to be considered for disease management. In this regard, information on the circulating endemic strains and their dispersal patterns through ongoing surveillance is beneficial. The objective of this project was to classify Quebec PRRSV ORF5 sequences in genetic clusters and evaluate stability of clustering results over a three-year period using an in-house automated clustering system. Phylogeny based on maximum likelihood (ML) was first inferred on 3661 sequences collected in 1998-2013 (Run 1). Then, sequences collected between January 2014 and September 2016 were sequentially added into 11 consecutive runs, each one covering a three-month period. For each run, detection of clusters, which were defined as groups of >/=15 sequences having a>/=70% rapid bootstrap support (RBS) value, was automated in Python. Cluster stability was described for each cluster and run based on the number of sequences, RBS value, maximum pairwise distance and agreement in sequence assignment to a specific cluster. First and last run identified 29 and 33 clusters, respectively. In the last run, about 77% of the sequences were classified by the system. Most clusters were stable through time, with sequences attributed to one cluster in Run 1 staying in the same cluster for the 11 remaining runs. However, some initial groups were further subdivided into subgroups with time, which is important for monitoring since one specific wild-type cluster increased from 0% in 2007 to 45% of all sequences in 2016. This automated classification system will be integrated into ongoing surveillance activities, to facilitate communication and decision-making for stakeholders of the swine industry. CI - Copyright (c) 2019. Published by Elsevier B.V. FAU - Lambert, Marie-Eve AU - Lambert ME AD - Laboratoire d'epidemiologie et de medecine porcine (LEMP), Faculty of Veterinary Medicine, Universite de Montreal, St. Hyacinthe, Quebec, Canada; Swine and Poultry Infectious Diseases Research Center (CRIPA), Faculty of Veterinary Medicine, Universite de Montreal, St. Hyacinthe, Quebec, Canada. Electronic address: marie-eve.lambert@umontreal.ca. FAU - Arsenault, Julie AU - Arsenault J AD - Laboratoire d'epidemiologie et de medecine porcine (LEMP), Faculty of Veterinary Medicine, Universite de Montreal, St. Hyacinthe, Quebec, Canada; Swine and Poultry Infectious Diseases Research Center (CRIPA), Faculty of Veterinary Medicine, Universite de Montreal, St. Hyacinthe, Quebec, Canada. Electronic address: julie.arsenault@umontreal.ca. FAU - Audet, Pascal AU - Audet P AD - Laboratoire d'epidemiologie et de medecine porcine (LEMP), Faculty of Veterinary Medicine, Universite de Montreal, St. Hyacinthe, Quebec, Canada; Swine and Poultry Infectious Diseases Research Center (CRIPA), Faculty of Veterinary Medicine, Universite de Montreal, St. Hyacinthe, Quebec, Canada. Electronic address: pascal.audet@umontreal.ca. FAU - Delisle, Benjamin AU - Delisle B AD - Laboratoire d'epidemiologie et de medecine porcine (LEMP), Faculty of Veterinary Medicine, Universite de Montreal, St. Hyacinthe, Quebec, Canada; Swine and Poultry Infectious Diseases Research Center (CRIPA), Faculty of Veterinary Medicine, Universite de Montreal, St. Hyacinthe, Quebec, Canada. Electronic address: benjamin.delisle@umontreal.ca. FAU - D'Allaire, Sylvie AU - D'Allaire S AD - Laboratoire d'epidemiologie et de medecine porcine (LEMP), Faculty of Veterinary Medicine, Universite de Montreal, St. Hyacinthe, Quebec, Canada; Swine and Poultry Infectious Diseases Research Center (CRIPA), Faculty of Veterinary Medicine, Universite de Montreal, St. Hyacinthe, Quebec, Canada. Electronic address: sylvie.dallaire@umontreal.ca. LA - eng PT - Journal Article PT - Research Support, Non-U.S. Gov't DEP - 20190427 PL - Netherlands TA - Infect Genet Evol JT - Infection, genetics and evolution : journal of molecular epidemiology and evolutionary genetics in infectious diseases JID - 101084138 RN - 0 (RNA, Viral) RN - 0 (Viral Proteins) SB - IM MH - Animals MH - Cluster Analysis MH - Genetic Variation/genetics MH - Open Reading Frames/genetics MH - Phylogeny MH - Porcine Reproductive and Respiratory Syndrome/*virology MH - Porcine respiratory and reproductive syndrome virus/*genetics MH - RNA, Viral/genetics MH - Swine MH - Viral Proteins/genetics OTO - NOTNLM OT - Classification OT - ORF5 OT - PRRS OT - Phylogeny OT - Surveillance EDAT- 2019/05/01 06:00 MHDA- 2020/04/02 06:00 CRDT- 2019/05/01 06:00 PHST- 2018/11/23 00:00 [received] PHST- 2019/04/06 00:00 [revised] PHST- 2019/04/18 00:00 [accepted] PHST- 2019/05/01 06:00 [pubmed] PHST- 2020/04/02 06:00 [medline] PHST- 2019/05/01 06:00 [entrez] AID - S1567-1348(18)30899-2 [pii] AID - 10.1016/j.meegid.2019.04.014 [doi] PST - ppublish SO - Infect Genet Evol. 2019 Sep;73:295-305. doi: 10.1016/j.meegid.2019.04.014. Epub 2019 Apr 27.