Plant and Cell PhysiologyEvolutionary BiologyPeer-reviewed journal article
Scenarios for the emergence of new miRNA genes in the plant Arabidopsis halleri
Flavia PavaniD, Eléanore LacosteiD, Vincent CastriciD, Sylvain LegrandiD
Abstract
MicroRNAs (miRNAs) are central players of the regulation of gene expression in Eukaryotes. The repertoires of miRNA genes vary drastically even among closely related species, indicating that they are evolutionarily labile. However, the processes by which they originate over the course of evolution and the nature of their progenitors across the genome remain poorly understood. Here we analyzed miRNA genes in Arabidopsis halleri, a plant species where we recently documented a large number of species-specific miRNA genes, likely to represent recent events of emergence. Analysis of sequence homology across the genome indicates that a diversity of sources contributes to the emergence of new miRNA genes, including inverted duplications from protein-coding genes, rearrangements of transposable element sequences and duplications of preexisting miRNA genes. Our observations indicate that the origin from protein-coding genes was less common than was previously considered. In contrast, we estimate that almost half of the new miRNA genes likely emerged from transposable elements. Miniature inverted transposable elements (MITE) seem to be particularly important contributors to new miRNA genes, with the Harbinger and Mariner transposable element superfamilies representing disproportionate sources for their emergence. We further analyzed the recent expansion of a miRNA family derived from MuDR elements, and the duplication of miRNA genes formed by two hAT transposons. Overall, our results illustrate the rapid pace at which new regulatory elements can arise from the modification of preexisting sequences in a genome, and highlight the central role of certain categories of transposable elements in this process.
- organism: Arabidopsis
- assay: DNA methylation
- research focus: chromatin & epigenetic regulation
- approach: statistical model
- Citations
- 2
- FWCI
- 0.86
- Field percentile
- top 36%
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