bioRxivPlant Biology
Polymorphic Inverted Repeats near coding genes impact chromatin topology and phenotypic traits in Arabidopsis thaliana
A. L. Arce, R. Mencia, D. A. Cambiagno, P. L. Lang, C. Liu, H. A. Burbano, D. Weigel, P. A. Manavella
Abstract
Transposons are mobile elements that are commonly silenced to protect eukaryotic genome integrity. In plants, transposable elements (TEs) can be activated during stress conditions and subsequently insert into gene-rich regions. TE-derived inverted repeats (IRs) are commonly found near plant genes, where they affect host gene expression with potentially positive effects on adaptation. However, the molecular mechanisms by which these IRs control gene expression is unclear in most cases. Here, we identify in the Arabidopsis thaliana genome hundreds of IRs located near genes that are transcribed by RNA Polymerase II, resulting in the production of 24-nt small RNAs that trigger methylation of the IRs. The expression of these IRs is associated with drastic changes in the local 3D chromatin organization, which alter the expression pattern of the hosting genes. Notably, the presence and structure of many IRs differ between A. thaliana accessions. Capture-C sequencing experiments revealed that such variation changes short-range chromatin interactions, which translates into changes in gene expression patterns. CRISPR/Cas9-mediated disruption of two of such IRs leads to a switch in genome topology and gene expression, with phenotypic consequences. Our data demonstrate that the insertion of an IR near a gene provides an anchor point for chromatin interactions that can profoundly impact the activity of neighboring loci. This turns IRs into powerful evolutionary agents that can contribute to rapid adaptation.
- organism: Arabidopsis
- assay: DNA methylation
- assay: ChIP-seq
- assay: CRISPR screen
- research focus: chromatin & epigenetic regulation
- research focus: gene regulatory network inference
- research focus: development & morphogenesis
- approach: experimental assay
- approach: statistical model
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