Chronology of transcriptome and proteome expression during early Arabidopsis flower development
The complex gene regulatory landscape underlying early flower development in Arabidopsis has been extensively studied through transcriptome profiling, and gene networks controlling floral organ development have been derived from the analyses of genome-wide binding of key transcription factors. In co...
| Autores: | , , , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2025 |
| País: | España |
| Institución: | Consejo Superior de Investigaciones Científicas (CSIC) |
| Repositorio: | DIGITAL.CSIC. Repositorio Institucional del CSIC |
| OAI Identifier: | oai:digital.csic.es:10261/398925 |
| Acceso en línea: | http://hdl.handle.net/10261/398925 https://api.elsevier.com/content/abstract/scopus_id/105010286555 |
| Access Level: | acceso abierto |
| Palabra clave: | APETALA1 Arabidopsis Co-expression analysis Flower development Proteome Target genes Transcriptome |
| Sumario: | The complex gene regulatory landscape underlying early flower development in Arabidopsis has been extensively studied through transcriptome profiling, and gene networks controlling floral organ development have been derived from the analyses of genome-wide binding of key transcription factors. In contrast, the dynamic nature of the proteome during the flower development process is much less understood. In this study, we characterized the floral proteome at different stages during early flower development and correlated it with unbiased transcript expression data. Shotgun proteomics and transcript profiling were conducted using an APETALA1 (AP1)-based floral induction system. A specific analysis pipeline to process the time-course proteomics data was developed. In total, 8924 proteins and 23 069 transcripts were identified. Co-expression analysis revealed that RNA-protein pairs clustered in various expression pattern modules. An overall positive correlation between RNA and protein level changes was observed, but subgroups of RNA-protein pairs with anti-correlated gene expression changes were also identified and found to be enriched in hormone-responsive pathways. In addition, the RNA-seq dataset reported here further expanded the identification of genes whose expression changes during early flower development, and its combination with previously published AP1 ChIP-seq datasets allowed the identification of additional direct and high-confidence targets of AP1. |
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