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ORIGINAL RESEARCH article

Front. Plant Sci.

Sec. Plant Genetics, Epigenetics and Chromosome Biology

This article is part of the Research TopicIntegrative Regulatory Layers in Plant Stress Adaptation: From Epigenetics to Proteome IntegrityView all 3 articles

A Comprehensive Landscape of the Gossypium arboreum circRNAome under Multiple Abiotic Stresses

Provisionally accepted
Liangdan  FeiLiangdan FeiYifan  ZhouYifan ZhouTao  HuangTao HuangKun  WangKun Wang*
  • Wuhan University, Wuhan, China

The final, formatted version of the article will be published soon.

Circular RNAs (circRNAs) serve as key post-transcriptional regulators in plant stress adaptation. Here, we comprehensively characterize the circRNA landscape of cotton (Gossypium arboreum) under multiple abiotic stresses condition using RNase R-enhanced sequencing. Through a stringent KNIFE-based algorithm pipeline, we identified 4,365 high-confidence circRNAs. Mechanistically, circRNA biogenesis was associated with long flanking introns and exhibited complex patterns of alternative splicing, revealing conserved production propensities but dynamic splice sites across species. Nuclear circRNAs frequently exhibited expression patterns decoupled from their host genes, typically in a stress-specific manner. By integrating miRNA-seq data, we constructed a circRNA-miRNA-mRNA regulatory network and found it centered mainly on cotton-specific miRNAs. Notably, we discovered an extraordinary dominance of chloroplast-derived circRNAs, accounting for over 80% of the total circRNAs repertoire. These chloroplast circRNAs clustered dominantly at clustering at the 3' terminus of the photosynthetic gene psbA gene, suggesting a specialized post-transcriptional regulatory mechanism within the chloroplast. This study provides a high-resolution cotton circRNA atlas and highlights psbA-derived circRNAs as potential molecular targets for improving environmental resilience in crop.

Keywords: abiotic stress, ceRNA network, chloroplast, circRNA, Gossypium arboreum, PsbA

Received: 20 Jan 2026; Accepted: 13 Feb 2026.

Copyright: © 2026 Fei, Zhou, Huang and Wang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Kun Wang

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