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Published on: March 5, 2017
Comparative transcriptome analysis of sesame flower organs and potential functional analysis of the MIKC-MADS gene
Qiyuan An1, Hongsen Cheng1, Huijie Sun1
1Liaoning Research Institute of Cash Crops, Liaoyang, 111000, China.
Background:
Sesame (Sesamum indicum L.) is an important oilseed crop; the comprehensive transcriptional landscape and regulatory networks underlying its floral organogenesis remain largely uncharacterized. A comprehensive understanding of gene expression dynamics among different floral organs is essential for elucidating the regulatory mechanisms underlying flower development.
Results:
To address this, we conducted a comparative transcriptome analysis of four floral organs (sepals, petals, stamens, and carpels) using RNA-seq. Based on commonly used criteria (|log2FC| ≥ 1, FDR < 0.05), pairwise comparisons identified 5,685 to 10,253 differentially expressed genes (DEGs) among organs. Functional enrichment analysis showed that these DEGs were mainly associated with metabolic processes, catalytic activity, and intracellular components. Notably, KEGG pathway analysis revealed that a subset of DEGs was significantly enriched in plant hormone signal transduction, MAPK signaling pathways, ABC transporters, and starch and sucrose metabolism. Core genes from eight hormone signaling pathways exhibited distinct organ-specific expression patterns, suggesting a coordinated network orchestrating organ differentiation. Complementing these findings, we identified 18 MIKC-MADS genes; promoter analysis indicated an enrichment of cis-elements responsive to hormones and stress, linking hormonal signals to transcriptional regulation. Expression pattern analysis further supported the conservation of the classical ABCDE model of floral organ identity in sesame, with class A (SiAP1), class B (SiPI/SiAP3), class C (SiAG), class D (SiSHP2), and class E (SiSEP) genes displaying strict organ-specific expression.
Conclusions:
This study provides a transcriptomic atlas for sesame floral organs, characterizes potential hormone signaling networks and MIKC-MADS regulatory associations, and presents genetic resources that may be useful for future functional genomics and molecular breeding.
