Network preservation analysis to identify transcriptional biomarkers related to flowering in Crocus sativus.

IF 16.4 1区化学 Q1 CHEMISTRY, MULTIDISCIPLINARY

Accounts of Chemical Research Pub Date : 2024-07-28 DOI:10.14715/cmb/2024.70.7.9

Mahsa Eshaghi, Sajad Rashidi-Monfared

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引用次数: 0

Abstract

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.

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通过网络保存分析确定与番红花开花相关的转录生物标记。

番红花（Crocus sativus L.）是众所周知的观赏地生植物，也是珍贵香料和次生代谢物的来源。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差异和保护模式。在此，我们通过包含开花和不开花样本基因表达谱的 RNA-Seq 数据，探索了开花过程的调控基因。持续模块分析发现了三个与开花过程相关的重要非持续模块，即粉色、绿色和蓝色。还发现了与非保留模块相关的几个中心基因，如 PIA1、NAC90、ALY3、Sus3、MYB31、ARF5/MP、MYB31、HD-ZIP、SEP3d、OR_B、AGL6a、bZIP(TGA1) 和 GRAS。这些候选基因可被视为开花过程的关键诊断生物标记。在此，我们还比较了 WGCNA 和 NetRep 两种模块保存分析方法。这些方法的结果与非保存模块一致。与 WGCNA 模块保存方法相比，NetRep 方法速度更快（11 倍），效率更高（每次比较运行超过 10000 次排列）。差异表达基因（DEGs）筛选显示，许多中枢基因在非开花样本中比在开花样本中下调。我们的发现揭示了西红花开花过程的调控机制，可以开发转录生物标记，为通过开花诱导提高西红花产量铺平道路。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Accounts of Chemical Research 化学-化学综合

CiteScore

31.40

自引率

1.10%

发文量

312

审稿时长

2 months

期刊介绍： Accounts of Chemical Research presents short, concise and critical articles offering easy-to-read overviews of basic research and applications in all areas of chemistry and biochemistry. These short reviews focus on research from the author’s own laboratory and are designed to teach the reader about a research project. In addition, Accounts of Chemical Research publishes commentaries that give an informed opinion on a current research problem. Special Issues online are devoted to a single topic of unusual activity and significance. Accounts of Chemical Research replaces the traditional article abstract with an article "Conspectus." These entries synopsize the research affording the reader a closer look at the content and significance of an article. Through this provision of a more detailed description of the article contents, the Conspectus enhances the article's discoverability by search engines and the exposure for the research.