Populations of plant viruses show high levels of genetic variability due to the evolutionary mechanisms of mutation, recombination and pseudorecombination. As a consequence, viral populations evolve rapidly being able to expand their host ranges and overcome the genetic resistance of plants at a faster rate than populations of other disease-causing agents. Begomoviruses (genus Begomovirus, family Geminiviridae) are highly prone to both intra and interspecific recombination. In fact, several recently published studies indicate that most of the known begomovirus species have a recombinant origin. On the other hand, due to the geographical isolation of begomovirus subpopulations, it is possible that the recombination affects each one in a different extent. In this context, the present study aimed to characterize the recombination patterns in each of the major subpopulations that composes the begomovirus global metapopulation. For this, genomic sequences of begomovirus isolates collected in different locations around the world were obtained from Genbank database and analyzed using computational tools of population genetics. The metapopulation was subdivided into two to eight major subpopulations using a multivariate statistical-based approach. The sequences corresponding to the isolates of each subpopulation were analyzed for the presence and distribution of recombination breakpoints. The results obtained in this study indicate that the major begomovirus subpopulations show distinct recombination dynamics, with an evolutionary isolation determined by their geographic distribution.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
334 Leonard St
Brooklyn, NY 11211
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.