Álvarez-Urdiola Raquel, Matus José Tomás, González-Miguel Víctor Manuel, Bernardo-Faura Martí, Riechmann José Luis
Centre for Research in Agricultural Genomics (CRAG) CSIC-IRTA-UAB-UB, Campus UAB, Cerdanyola del Vallès, 08193 Barcelona, Spain.
Institute for Integrative Systems Biology (I2SysBio), Universitat de València-CSIC, Paterna, 46908 Valencia, Spain.
J Exp Bot. 2025 Jul 2;76(10):2743-2762. doi: 10.1093/jxb/eraf005.
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.
通过转录组分析,已对拟南芥早期花发育背后复杂的基因调控格局进行了广泛研究,并且通过对关键转录因子全基因组结合情况的分析,推导出了控制花器官发育的基因网络。相比之下,人们对花发育过程中蛋白质组的动态特性了解得要少得多。在本研究中,我们对早期花发育不同阶段的花蛋白质组进行了表征,并将其与无偏差的转录本表达数据相关联。使用基于APETALA1(AP1)的花诱导系统进行鸟枪法蛋白质组学和转录本分析。开发了一个用于处理时间进程蛋白质组学数据的特定分析流程。总共鉴定出8924种蛋白质和23069种转录本。共表达分析表明,RNA-蛋白质对聚集在各种表达模式模块中。观察到RNA和蛋白质水平变化之间总体呈正相关,但也鉴定出了基因表达变化呈反相关的RNA-蛋白质对亚组,并且发现这些亚组在激素响应途径中富集。此外,本文报道的RNA-seq数据集进一步扩展了对早期花发育过程中表达发生变化的基因的鉴定,并且将其与先前发表的AP1 ChIP-seq数据集相结合,能够鉴定出AP1的其他直接且高可信度的靶标。