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Copyright (c) 2024 Mahsa Eshaghi, Sajad Rashidi-Monfared
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
The undersigned hereby assign all rights, included but not limited to copyright, for this manuscript to CMB Association upon its submission for consideration to publication on Cellular and Molecular Biology. The rights assigned include, but are not limited to, the sole and exclusive rights to license, sell, subsequently assign, derive, distribute, display and reproduce this manuscript, in whole or in part, in any format, electronic or otherwise, including those in existence at the time this agreement was signed. The authors hereby warrant that they have not granted or assigned, and shall not grant or assign, the aforementioned rights to any other person, firm, organization, or other entity. All rights are automatically restored to authors if this manuscript is not accepted for publication.Network preservation analysis to identify transcriptional biomarkers related to flowering in Crocus sativus
Corresponding Author(s) : Sajad Rashidi-Monfared
Cellular and Molecular Biology,
Vol. 70 No. 7: Issue 7
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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