INVESTIGADORES
GISMONDI Maria Ines
congresos y reuniones científicas
Título:
USE OF NEW BIOINFORMATICS TOOLS APPLIED TO A REGIONAL EVOLUTIONARY STUDY OF FMDV IN THE 2000-2001 EPIDEMICS IN ARGENTINA
Autor/es:
KÖNIG G; CABANNE GS; MARCOS A; GISMONDI MI; PYBUS O; PÉREZ AM
Lugar:
Bangkok
Reunión:
Congreso; 2019 Meeting of the Global Foot-and-mouth Disease Research Alliance; 2019
Institución organizadora:
GFRA
Resumen:
Several diseases affecting livestock are produced by RNA viruses. These viruses replicate with a relatively high copy error rate. Foot and Mouth Disease Virus (FMDV) is one of them. The work presented aimed to apply a set of bioinformatics tools to understand the transmission of FMDV in the county of Mar Chiquita region, Buenos Aires province, Argentina.We analyzed the almost complete genome sequence (around 8000 bases) of 21 isolates collected along three months and no further than 40 km apart. These local sequences were compared with other national samples in order to identify temporal and recombination signals using TempEst and RDP4 software. Phylogenetic network analysis was performed using SplitsTree software. We also added time and localization of the samples as additional epidemiological information to study the evolving dynamics of the virus using BEAST software,based on Bayesian statistics. The 21 genomic sequences of the viruses isolated in Mar Chiquita showed a high level of similarity among them, with no signal of recombination. The results also showed that the genome of these isolates had an evolving rate of 9 x10-4 substitutions per site, similarly to previously reported rates in analysis of viruses collected in a small time window. Additionally, the 5´UTR (untranslated) region had a variability index higher than the national average. The phylodynamic analysis indicated a monophyletic group for all these isolates, with the time to most recent common ancestor (TCMRA) of about three months previous to the first Mar Chiquita isolate. Besides, the phylogenetic tree presented structural similarities with the network genealogy.The use of these robust bioinformatics tools in this study allowed us to determine a probable scenario of local virus transmission.
