bioRxivGenomicsPreprint
Transposons modulate transcriptomic and phenotypic variation via the formation of circular RNAs in maize
Lu CheniD, Pei ZhangiD, Yuan FaniD, Juan HuangiD, Qiong LuiD, Qing LiiD, Jianbing YaniD, Gary J. MuehlbaueriD, Patrick S. SchnableiD, Mingqiu DaiiD, Lin LiiD
Abstract
Circular RNAs (circRNAs) are covalently closed, single-stranded RNA molecules. Recent studies in human showed that circRNAs can arise via transcription of reverse complementary pairs of transposons. Given the prevalence of transposons in the maize genome and dramatic genomic variation driven by transposons, we hypothesize that transposons in maize may be involved in the formation of circRNAs and further modulate phenotypic variation. To test our hypothesis, we performed circRNA-Seq on B73 seedling leaves and integrate these data with 977 publicly available mRNA-Seq datasets. We uncovered 1,551 high-confidence maize circRNAs, which show distinct genomic features as compared to linear transcripts. Comprehensive analyses demonstrated that LINE1-like elements (LLE) and their Reverse Complementary Pairs (LLERCPs) are significantly enriched in the flanking regions of circRNAs. Interestingly, the accumulation of circRNA transcripts increases, while the accumulation of linear transcripts decreases as the number of LLERCPs increases. Furthermore, genes with LLERCP-mediated circRNAs are enriched among loci that are associated with phenotypic variation. These results suggest that LLERCPs can modulate phenotypic variation by the formation of circRNAs. As a proof of concept, we showed that the presence/absence variation of LLERCPs could result in expression variation of one cicrRNA, circ352, and further related to plant height through the interaction between circRNA and functional linear transcript. Our first glimpse of circRNAs uncovers a new role for transposons in the modulation of transcriptomic and phenotypic variation via the formation of circRNAs.
- organism: plant (other)
- assay: bulk RNA-seq
- research focus: gene regulatory network inference
- research focus: differential expression
- research focus: database / resource
- approach: statistical model
- approach: experimental assay
- Citations
- 4
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