Comparative Metabolomic And Transcriptomic Analysis Reveals A Coexpression Network of The Carotenoid Metabolism Pathway In The Panicle of Setaria Italica

Abstract [Background]The grains of foxtail millet are enriched in carotenoids, which endow this plant with a yellow color and extremely high nutritional value. However, the underlying molecular regulation mechanism and gene coexpression network remain unclear.[Methods] The carotenoid species and content were detected by HPLC for two foxtail millet varieties at three panicle development stages. Based on a homologous sequence BLAST analysis, these genes related to carotenoid metabolism were identified from the foxtail millet genome database. The conserved protein domains, chromosome locations, gene structures and phylogenetic trees were analyzed using bioinformatics tools. RNA-seq was performed for these samples to identify differentially expressed genes (DEGs). A Pearson correlation analysis was performed between the expression of genes related to carotenoid metabolism and the content of carotenoid metabolites. Furthermore, the expression levels of the key DEGs were verified by qRT-PCR. The gene coexpression network was constructed by a weighted gene coexpression network analysis (WGCNA).[Result] The major carotenoid metabolites in the panicles of DHD and JG21 were lutein and β-carotene. These carotenoid metabolite contents sharply decreased during the panicle development stage. The lutein and β-carotene contents were highest at the S1 stage of DHD, with values of 11.474 μg/100 mg and 12.524 μg/100 mg, respectively. Fifty-four genes related to carotenoid metabolism were identified in the foxtail millet genome. Cis-acting element analysis showed that these gene promoters mainly contain ‘light-responsive’ and ‘ABA-responsive’ elements. In the carotenoid metabolic pathways, SiHDS, SiHMGS3, SiPDS and SiNCED1 were more highly expressed in the panicle of foxtail millet. The expression of SiCMT, SiAACT3, SiPSY1, SiZEP1/2, and SiCCD8c/8d was significantly correlated with the lutein content. The expression of SiCMT, SiHDR, SiIDI2, SiAACT3, SiPSY1, and SiZEP1/2 was significantly correlated with the content of β-carotene. WGCNA showed that the coral module was highly correlated with lutein and β-carotene, and 13 structural genes from the carotenoid biosynthetic pathway were identified. Network visualization revealed 25 intramodular hub genes that putatively control carotenoid metabolism.[Conclusion] Based on the integrative analysis of the transcriptomics and carotenoid metabonomics, we found that DEGs related to carotenoid metabolism had a stronger correlation with the key carotenoid metabolite content. The correlation analysis and WGCNA identified and predicted the gene regulation network related to carotenoid metabolism. These results lay the foundation for exploring the key target genes regulating carotenoid metabolism flux in the panicle of foxtail millet. We hope that these target genes could be used to genetically modify millet to enhance the carotenoid content in the future.

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Identification of key genes and regulators associated with carotenoid metabolism in apricot (Prunus armeniaca) fruit using weighted gene coexpression network analysis

BMC Genomics ◽

10.1186/s12864-019-6261-5 ◽

2019 ◽

Vol 20 (1) ◽

Cited By ~ 4

Author(s):

Lina Zhang ◽

Qiuyun Zhang ◽

Wenhui Li ◽

Shikui Zhang ◽

Wanpeng Xi

Keyword(s):

Network Analysis ◽

Coexpression Network ◽

Carotenoid Content ◽

Pcr Analysis ◽

Gene Coexpression Network ◽

Gene Coexpression ◽

Carotenoid Metabolism ◽

Total Carotenoid Content ◽

Key Genes ◽

Coexpression Network Analysis

Abstract Background Carotenoids are a class of terpenoid pigments that contribute to the color and nutritional value of many fruits. Their biosynthetic pathways have been well established in a number of plant species; however, many details of the regulatory mechanism controlling carotenoid metabolism remain to be elucidated. Apricot is one of the most carotenoid-rich fruits, making it a valuable system for investigating carotenoid metabolism. The purpose of this study was to identify key genes and regulators associated with carotenoid metabolism in apricot fruit based on transcriptome sequencing. Results During fruit ripening in the apricot cultivar ‘Luntaixiaobaixing’ (LT), the total carotenoid content of the fruit decreased significantly, as did the levels of the carotenoids β-carotene, lutein and violaxanthin (p < 0.01). RNA sequencing (RNA-Seq) analysis of the fruit resulted in the identification of 44,754 unigenes and 6916 differentially expressed genes (DEGs) during ripening. Among these genes, 33,498 unigenes were annotated using public protein databases. Weighted gene coexpression network analysis (WGCNA) showed that two of the 13 identified modules (‘blue’ and ‘turquoise’) were highly correlated with carotenoid metabolism, and 33 structural genes from the carotenoid biosynthetic pathway were identified. Network visualization revealed 35 intramodular hub genes that putatively control carotenoid metabolism. The expression levels of these candidate genes were determined by quantitative real-time PCR analysis, which showed ripening-associated carotenoid accumulation. This analysis revealed that a range of genes (NCED1, CCD1/4, PIF3/4, HY5, ERF003/5/12, RAP2–12, AP2, AP2-like, BZR1, MADS14, NAC2/25, MYB1R1/44, GLK1/2 and WRKY6/31/69) potentially affect apricot carotenoid metabolism during ripening. Based on deciphering the molecular mechanism involved in ripening, a network model of carotenoid metabolism in apricot fruit was proposed. Conclusions Overall, our work provides new insights into the carotenoid metabolism of apricot and other species, which will facilitate future apricot functional studies and quality breeding through molecular design.

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Potential targets and molecular mechanism of miR-331-3p in hepatocellular carcinoma identified by weighted gene coexpression network analysis

Bioscience Reports ◽

10.1042/bsr20200124 ◽

2020 ◽

Vol 40 (6) ◽

Author(s):

Qingjia Chi ◽

Xinge Geng ◽

Kang Xu ◽

Chunli Wang ◽

Han Zhao

Keyword(s):

Hepatocellular Carcinoma ◽

Network Analysis ◽

Molecular Mechanism ◽

Target Genes ◽

Coexpression Network ◽

Gene Coexpression Network ◽

Hub Genes ◽

Gene Coexpression ◽

Tumor Tissues ◽

Coexpression Network Analysis

Abstract Hepatocellular carcinoma (HCC) is one of the most common malignant tumor. miR-331-3p has been reported relevant to the progression of HCC, but the molecular mechanism of its regulation is still unclear. In the study, we comprehensively studied the role of miR-331-3p in HCC through weighted gene coexpression network analysis (WGCNA) based on The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO) and Oncomine. WGCNA was applied to build gene co-expression networks to examine the correlation between gene sets and clinical characteristics, and to identify potential biomarkers. Five hundred one target genes of miR-331-3p were obtained by overlapping differentially expressed genes (DEGs) from the TCGA database and target genes predicted by miRWalk. The critical turquoise module and its eight key genes were screened by WGCNA. Enrichment analysis was implemented based on the genes in the turquoise module. Moreover, 48 genes with a high degree of connectivity were obtained by protein–protein interaction (PPI) analysis of the genes in the turquoise module. From overlapping genes analyzed by WGCNA and PPI, two hub genes were obtained, namely coatomer protein complex subunit zeta 1 (COPZ1) and elongation factor Tu GTP binding domain containing 2 (EFTUD2). In addition, the expression of both hub genes was also significantly higher in tumor tissues compared with normal tissues, as confirmed by analysis based on TCGA and Oncomine. Both hub genes were correlated with poor prognosis based on TCGA data. Receiver operating characteristic (ROC) curve validated that both hub genes exhibited excellent diagnostic efficiency for normal and tumor tissues.

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