AUTHOR=Li Jingrui , Fan Mi , Zhang Xiaomeng , Yang Liling , Hou Guangguang , Yang Lei , Li Na , Xuan Shuxin , Zhao Jianjun TITLE=Integratedly analyzed quantitative proteomics with transcriptomics to discover key genes via fg-1 non-heading mutant in the early heading stage of Chinese cabbage JOURNAL=Frontiers in Plant Science VOLUME=15 YEAR=2024 URL=https://www.frontiersin.org/journals/plant-science/articles/10.3389/fpls.2024.1467006 DOI=10.3389/fpls.2024.1467006 ISSN=1664-462X ABSTRACT=

Leaf heading is an important agronomic trait of Chinese cabbage, which directly affects its yield. Leaf heading formation in Chinese cabbage is controlled by its internal genotype and external environmental factors, the underlying mechanism of which remains poorly understood. To discover the leaf heading formation mechanism more deeply, this study analyzed the correlation between proteomic and transcriptomic data in the leaf heading formation mutant fg-1 generated by EMS. iTRAQ-based quantitative proteomics techniques were performed to identify the protein expression profiles during the key periods of the early heading stage in the section of the soft leaf apical region (section a) and the whole leaf basal region (section d). We first identified 1,246 differentially expressed proteins (DEPs) in section a and 1,055 DEPs in section d. Notably, transcriptome–proteome integrated analysis revealed that 207 and 278 genes showed consistent trends at the genes’ and proteins’ expression levels in section a and section d, respectively. KEGG analyses showed that the phenylpropanoid biosynthesis pathway was enriched in both sections a and d. Furthermore, 86 TFs exhibited co-upregulation or co-downregulation, and seven out of 86 were involved in plant hormone synthesis and signal transduction pathways. This indicates that they are potentially related to the leaf heading formation in Chinese cabbage. Taken together, we have identified several key early-heading-formation-related factors via integration analysis of the transcriptomics and proteomics data. This provides sufficient gene resources to discover the molecular mechanism of leaf heading formation.