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Integrating transcriptome and metabolome reveals molecular networks involved in genetic and environmental variation in tobacco

文献类型： 外文期刊

作者： Liu, Pingping 1 ; Luo, Jie 2 ; Zheng, Qingxia 1 ; Chen, Qiansi 1 ; Zhai, Niu 1 ; Xu, Shengchun 2 ; Xu, Yalong 1 ; Jin, Li 1 ;

作者机构： 1.Zhengzhou Tobacco Res Inst CNTC, China Tobacco Gene Res Ctr, Zhengzhou 450001, Peoples R China

2.Zhejiang Acad Agr Sci, Cent Lab, Hangzhou 310021, Peoples R China

3.Chinese Acad Sci, Dalian Inst Chem Phys, Key Lab Separat Sci Analyt Chem, Dalian 116023, Peoples R China

4.Zhejiang Univ, Coll Agr & Biotechnol, Inst Crop Sci, Hangzhou 310058, Peoples R China

5.Zhejiang Univ, Coll Agr & Biotechnol, Inst Bioinformat, Hangzhou 310058, Peoples R China

6.Univ North Dakota, Dept Biol, Grand Forks, ND 58202 USA

关键词： tobacco; omics integration; gene regulatory networks; co-expression module; molecular network

期刊名称：DNA RESEARCH （ 影响因子：4.458； 五年影响因子：5.371 ）

ISSN： 1340-2838

年卷期： 2020 年 27 卷 2 期

页码：

收录情况： SCI

摘要： Tobacco (Nicotiana tabacum) is one of the most widely cultivated commercial non-food crops with significant social and economic impacts. Here we profiled transcriptome and metabolome from 54 tobacco samples (2-3 replicates; n=151 in total) collected from three varieties (i.e. genetic factor), three locations (i.e. environmental factor), and six developmental stages (i.e. developmental process). We identified 3,405 differentially expressed (DE) genes (DEGs) and 371 DE metabolites, respectively. We used quantitative real-time PCR to validate 20 DEGs, and confirmed 18/20 (90%) DEGs between three locations and 16/20 (80%) with the same trend across developmental stages. We then constructed nine co-expression gene modules and four co-expression metabolite modules , and defined seven de novo regulatory networks, including nicotine- and carotenoid-related regulatory networks. A novel two-way Pearson correlation approach was further proposed to integrate co-expression gene and metabolite modules to identify joint gene-metabolite relations. Finally, we further integrated DE and network results to prioritize genes by its functional importance and identified a top-ranked novel gene, LOC107773232, as a potential regulator involved in the carotenoid metabolism pathway. Thus, the results and systems-biology approaches provide a new avenue to understand the molecular mechanisms underlying complex genetic and environmental perturbations in tobacco.

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