dr. andres perez - tempero-spatial sequence analysis, bayesian phylodynamic methods on 1-7-4 prrsv

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Applications of Bayesian phylodynamic methods to the investigation of the recent 1-7-4 PRRSv outbreak Andres Perez, DVM, PhD Endowed Chair of Global Animal Health and Food Safety College of Veterinary Medicine University of Minnesota [email protected]

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Novel analytic tools for surveillance, diagnosis and control of PRRS in endemic settings

Applications of Bayesian phylodynamic methods to the investigation of the recent 1-7-4 PRRSv outbreak

Andres Perez, DVM, PhDEndowed Chair of Global Animal Health and Food SafetyCollege of Veterinary MedicineUniversity of [email protected]

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Swine Group, University of MinnesotaMoh AlkhamisAndres PerezMike MurtaughXiong WangBob MorrisonTeam workSwine Health Monitoring ProgramFour anonymous participants

Paton et al. 2005. Selection of foot and mouth disease vaccine strains- a reviewIntroduction

Suppose that we have sequences from 8 farms (1 per farm)Each square represents one nucleotide of the sequence

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Paton et al. 2005. Selection of foot and mouth disease vaccine strains- a reviewIntroduction

Alignment

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Paton et al. 2005. Selection of foot and mouth disease vaccine strains- a reviewMatrix of (nt) differences123456722312454452113643322731342486551535

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Paton et al. 2005. Selection of foot and mouth disease vaccine strains- a review(nt) Genetic distance123456720.33330.1670.33340.8330.6670.66750.3330.1670.16760.6670.50.50.3330.33370.50.1670.50.6670.3330.667810.8330.8330.1670.8330.50.833

Genetic distance (GD)GD = (nt, aa) differences / (nt, aa) comparedProbability of finding one (nt, aa) difference when two strains are compared

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Paton et al. 2005. Selection of foot and mouth disease vaccine strains- a reviewPhylogenetic treesBecause sequences theoretically split into two descendant sequences, phylogenetic trees are typically assumed to be bifurcatingTopology: branching pattern of a treeTaxa: any kind of taxonomic units (eg.: virus sequences)

Unrooted treeRooted tree

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Paton et al. 2005. Selection of foot and mouth disease vaccine strains- a reviewPhylogenetic treesIf 4 taxa are being compared, there are 15 and 3 possible rooted and unrooted tree topologies, respectively

From Nei and Kumar, 2000

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Paton et al. 2005. Selection of foot and mouth disease vaccine strains- a reviewPhylogenetic treesWhen 10 taxa are being compared, the number of possible rooted topologies is 34,459,425 and the number of possible bifurcating unrooted topologies is 2,027,025

Only one of them is the true topology

Reconstructed or inferred trees: trees built from observed sequences

Traditional methods to infer a tree (distance, parsimony, likelihood) ignore the associated epidemiological information (space, time of identification, associated data)

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Paton et al. 2005. Selection of foot and mouth disease vaccine strains- a reviewBayesian phylogenetic methods

http://www.nbcnews.com/science/such-deep-roots-you-have-how-little-red-riding-hoods-2D11591047http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0078871

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Paton et al. 2005. Selection of foot and mouth disease vaccine strains- a review

Bayesian phylogenetic methods

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Correlation of alternative metrics of PRRSv relatedness, namely, difference (%) in the number of nucleotides (X axis) and considering phylogenetic evolution (Y axis).

Correlation is quite bad

Phylogenetic methodsSimilarly, we can use phylogenetic methods to infer:Most likely time of emergence of the strain;Past probability of spread between systems and between type of farmsPopulation (viral) size

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Data6,774 ORF 5 sequencesJanuary 1998 April 20155 independent systems (coded AE)Type of farm (sow, growing pig farms)Selected 1-7-4 PRRSv using a maximum likelihood algorithm

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Results

Some (n= 288) related sequences (based on ML) collected between September 2003-March 2015

Most (n=241) are 1-7-4 sequences obtained between Jan 2014 and Mar 2015

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ResultsIncrease in population size in 2014

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ResultsHistory of spread between systems

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ResultsHistory of spread between types of farms

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Dynamic representation

Future plansContinue enrollment of systemsStandardization and optimization of protocols for data collection and sharingImplementation of analytical tools into IT system designated by the SHICProvide near real time interpretation of resultsContribute to PRRS control at a national scale

Thank you