Department of Plant Biotechnology, Faculty of Agriculture, Tarbiat Modares University, Tehran, Iran.
Cell Mol Biol (Noisy-le-grand). 2024 Jul 28;70(7):66-72. doi: 10.14715/cmb/2024.70.7.9.
Crocus sativus L. is known as an ornamental geophyte and a source of valuable spice and secondary metabolites. Network preservation module analysis is one of the best approaches to revealing special features of different conditions. It can determine patterns of divergence and conservation between transcriptome data. Herein, we explored the regulatory genes of the flowering process by RNA-Seq data containing flowering and non-flowering samples in gene expression profiles. Persevered module analysis revealed three significant non-persevered modules related to the flowering process, namely pink, green, and blue. Several hub genes associated with non-preserved modules such as PIA1, NAC90, ALY3, Sus3, MYB31, ARF5/MP, MYB31, HD-ZIP, SEP3d, OR_B, AGL6a, bZIP(TGA1) and GRAS were identified. These candidate genes can be considered key diagnostic biomarkers for the flowering process. Here, we also compared two approaches, WGCNA and NetRep for module preservation analysis. The results of these methods were consistent with non-preserved modules. NetRep was a faster (11 times) and more efficient (run more than 10000 permutations for each comparison) method than WGCNA module preservation. Differential expression genes (DEGs) screening showed that many hub genes were downregulated in non-flowering than flowering samples. Our finding revealed regulatory mechanisms of the flowering process in C. sativus as can be developed transcriptional biomarkers which could pave the way for promoting saffron yield via flowering induction.
番红花（Crocus sativus L.）作为一种观赏球根花卉和珍贵香料及次生代谢物的来源而广为人知。网络保存模块分析是揭示不同条件下特殊特征的最佳方法之一。它可以确定转录组数据之间的分歧和保存模式。在这里，我们通过包含开花和不开花样本的基因表达谱中的 RNA-Seq 数据，探索了开花过程的调控基因。持久模块分析揭示了三个与开花过程相关的显著非持久模块，分别为粉色、绿色和蓝色。几个与非保存模块相关的枢纽基因，如 PIA1、NAC90、ALY3、Sus3、MYB31、ARF5/MP、MYB31、HD-ZIP、SEP3d、OR_B、AGL6a、bZIP(TGA1)和 GRAS 被鉴定出来。这些候选基因可以被认为是开花过程的关键诊断生物标志物。在这里，我们还比较了两种方法，WGCNA 和 NetRep 进行模块保存分析。这两种方法的结果与非保存模块一致。与 WGCNA 相比，NetRep 是一种更快（快 11 倍）和更有效的方法（对于每个比较，运行超过 10000 次随机排列）。差异表达基因（DEGs）筛选表明，许多枢纽基因在不开花样本中的表达水平低于开花样本。我们的研究结果揭示了番红花开花过程的调控机制，可以开发出转录生物标志物，为通过诱导开花来提高番红花产量铺平道路。
