PLoS ONE (Jan 2019)

The population genetic structure approach adds new insights into the evolution of plant LTR retrotransposon lineages.

  • Vanessa Fuentes Suguiyama,
  • Luiz Augusto Baciega Vasconcelos,
  • Maria Magdalena Rossi,
  • Cibele Biondo,
  • Nathalia de Setta

DOI
https://doi.org/10.1371/journal.pone.0214542
Journal volume & issue
Vol. 14, no. 5
p. e0214542

Abstract

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Long terminal repeat retrotransposons (LTR-RTs) in plant genomes differ in abundance, structure and genomic distribution, reflecting the large number of evolutionary lineages. Elements within lineages can be considered populations, in which each element is an individual in its genomic environment. In this way, it would be reasonable to apply microevolutionary analyses to understand transposable element (TE) evolution, such as those used to study the genetic structure of natural populations. Here, we applied a Bayesian method to infer genetic structure of populations together with classical phylogenetic and dating tools to analyze LTR-RT evolution using the monocot Setaria italica as a model species. In contrast to a phylogeny, the Bayesian clusterization method identifies populations by assigning individuals to one or more clusters according to the most probabilistic scenario of admixture, based on genetic diversity patterns. In this work, each LTR-RT insertion was considered to be one individual and each LTR-RT lineage was considered to be a single species. Nine evolutionary lineages of LTR-RTs were identified in the S. italica genome that had different genetic structures with variable numbers of clusters and levels of admixture. Comprehensive analysis of the phylogenetic, clusterization and time of insertion data allowed us to hypothesize that admixed elements represent sequences that harbor ancestral polymorphic sequence signatures. In conclusion, application of microevolutionary concepts in genome evolution studies is suitable as a complementary approach to phylogenetic analyses to address the evolutionary history and functional features of TEs.