bioRxivPlant BiologyPreprint
Antirrhinum flower shape: unravelling gene expression across developmental axes and boundaries
Ana Maria CunhaiD, João RaimundoiD, Alexandra VerweijiD, Desmond J. BradleyiD, Enrico CoeniD, Maria Manuela Ribeiro CostaiD
Abstract
O_LIZygomorphic flowers in Antirrhinum majus arise from coordinated patterning along the dorsoventral and proximal-distal axes, but the transcriptional programs that pattern these axes to generate the complex corolla morphology remain poorly understood. C_LIO_LIWe performed comparative transcriptomic analyses of dorsal and ventral petals across developmental stages, combined with expression profiling in floral symmetry mutants, to identify genes potentially associated with dorsal identity (AmCYC-dependent) and ventral identity (AmDIV-dependent), and to map their spatial dynamics along the proximal-distal axis. Axis-specific and boundary-localized expression patterns were validated by in situ hybridisation. C_LIO_LIWe identified dorsal-specific candidate targets of AmCYC and ventral-specific genes regulated by AmDIV, including factors with regionally restricted expression along the proximal-distal axis. We further found that a conserved NGATHA-LIKE1-BRASSINAZOLE-RESISTANT 1-miR164 module, known for primordia growth regulation in Arabidopsis, has been co-opted in Antirrhinum to act as a potential spatiotemporal regulator of AmCUP, a target of AmDIV, thereby contributing to the complex shape of the Antirrhinum flower. C_LIO_LIOur results provide new insight into the gene regulatory landscape underlying zygomorphic flower development and highlight specific regulatory modules that may coordinate axis patterning with boundary establishment in the corolla. This work establishes a framework for further understanding how developmental gene networks shape a complex corolla morphology and offers new targets for functional and evolutionary investigation of floral diversity. C_LI
- organism: plant (other)
- assay: bulk RNA-seq
- research focus: gene regulatory network inference
- approach: statistical model
- Citations
- 0
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