An integrated genomic and metabolomic framework for cell wall biology in rice

BMC Genomics

Liangcai Peng⁴  Staffan Persson¹  Sebastian Klie²  Yangting Wang³  Lingqiang Wang³  Guosheng Xie³  Fen Tu⁴  Jing Zhang³  Mingliang Zhang³  Yongqing Feng³  Weihua Zou³  Kai Guo⁴ 

[1] School of Botany, University of Melbourne, Melbourne, VIC 3010, Australia;Max-Planck-Institute for Molecular Plant Physiology, Am Mühlenberg 1, 14476 Potsdam, Germany;College of Plant Science and Technology, Huazhong Agricultural University, Wuhan, Hubei 430070, P. R. China;College of Life Science and Technology, Huazhong Agricultural University, Wuhan, Hubei 430070, P. R. China

关键词: Metabolomics;    Co-expression network;    Cell wall;    Rice;   

Others  :  1216475
DOI  :  10.1186/1471-2164-15-596

 received in 2013-10-02, accepted in 2014-07-09,  发布年份 2014

【 摘 要 】

Background

Plant cell walls are complex structures that full-fill many diverse functions during plant growth and development. It is therefore not surprising that thousands of gene products are involved in cell wall synthesis and maintenance. However, functional association for the majority of these gene products remains obscure. One useful approach to infer biological associations is via transcriptional coordination, or co-expression of genes. This approach has proved useful for several biological processes. Nevertheless, combining co-expression with other large-scale measurements may improve the biological inferences.

Results

In this study, we used a combined approach of co-expression and cell wall metabolomics to obtain new insight into cell wall synthesis in rice. We initially created a weighted gene co-expression network from publicly available datasets, and then established a comprehensive cell wall dataset by determining cell wall compositions from 29 tissues that almost cover the whole life cycle of rice. We subsequently combined the datasets through the conversion of co-expressed gene modules into eigen-vectors, representing expression profiles for the genes in the modules, and performed comparative analyses against the cell wall contents. Here, we made three major discoveries. First, we confirmed our approach by finding primary and secondary wall cellulose biosynthesis modules, respectively. Second, we found co-expressed modules that strongly correlated with re-organization of the secondary cell walls and with modifications and degradation of hemicellulosic structures. Third, we inferred that at least one module is likely to play a regulatory role in the production of G-rich lignification.

Conclusions

Here, we integrated transcriptomic associations and cell wall metabolism and found that certain co-expressed gene modules are positively correlated with distinct cell wall characteristics. We propose that combining multiple data-types, such as coordinated transcription and cell wall analyses, may be a useful approach to glean new insight into biological processes. The combination of multiple datasets, as illustrated here, can further improve the functional inferences that typically are generated via a single type of datasets. In addition, our data extend the typical co-expression approach to allow deeper insight into cell wall biology in rice.

【 授权许可】

   
2014 Guo et al.; licensee BioMed Central Ltd.

【 图 表 】

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