Abstract
BackgroundPorcine reproductive and respiratory syndrome (PRRS) is a major threat to the swine industry. It is caused by the PRRS virus (PRRSV). Determination and comparison of the nucleotide sequences of PRRSV strains provides useful information in support of control initiatives or epidemiological studies on transmission patterns. The alignment of sequences is the first step in analyzing sequence data, with multiple algorithms being available, but little is known on the impact of this methodological choice. Here, a study was conducted to evaluate the impact of different alignment algorithms on the resulting aligned sequence dataset and on practical issues when applied to a large field database of PRRSV open reading frame (ORF) 5 sequences collected in Quebec, Canada, from 2010 to 2014. Five multiple sequence alignment programs were compared: Clustal W, Clustal Omega, Muscle, T-Coffee and MAFFT.ResultsThe resulting alignments showed very similar results in terms of average pairwise genetic similarity, proportion of pairwise comparisons having ≥97.5% genetic similarity and sum of pairs (SP) score, except for T-Coffee where increased length of aligned datasets as well as limitation to handle large datasets were observed.ConclusionsBased on efficiency at minimizing the number of gaps in different dataset sizes with default open gap values as well as the capability to handle a large number of sequences in a timely manner, the use of Clustal Omega might be recommended for the management of PRRSV extensive database for both research and surveillance purposes.
Highlights
Porcine reproductive and respiratory syndrome (PRRS) is a major threat to the swine industry
Since January 2010, a sharing agreement with 97% of all Quebec swine veterinarians have ensured that all PRRS virus (PRRSV) ORF5 sequences obtained from their field submissions to the veterinary diagnostic laboratory of the Université de Montréal or to two other private laboratories were automatically transferred to the Laboratoire d’épidémiologie et de médecine porcine (LEMP)
Once the plateau was reached for the three parameters, all algorithms converged to a similar number of gaps introduced (i.e. 3) for datasets with ≤1191 sequences, except for T-Coffee which introduced more gaps
Summary
Porcine reproductive and respiratory syndrome (PRRS) is a major threat to the swine industry. Porcine reproductive and respiratory syndrome virus (PRRSV) infection has a major economic impact on the swine production with annual cost estimated at $664 M for the US industry [1]. A pairwise nucleotide sequence similarity ≥97.5% is the threshold often used to indicate if two sequences are considered similar and likely to originate from a same source [5, 6] This threshold is used into molecular-based interactive tools for field investigations on sources of contamination [7]. These tools are used to generate hypotheses about how a specific herd got infected which can orient the implementation of Lambert et al BMC Veterinary Research (2019) 15:135 specific preventive measures to avoid further introduction and spread of the virus
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