IC4R001-Metabolomics-2013-24259710

Project Title

A phenomics approach detected differential epigenetic growth regulation between inbreds and their hybrid in Oryza sativa.

The Background of This Project

• Plants are highly enriched in specific metabolites with extensive quantitative and qualitative variation both among and within different plant species (1, 2). Understanding the genes involved in metabolism and dissection of the metabolic pathway are essential to improve plant adaptation to environmental stresses, to improve food quality, and to increase crop yield. Recent advance in metabolomics together with transcriptomics and gene/metabolite coexpression networks analyses has proven to be powerful in functional gene elucidation, although it is specified for transcriptionally regulated genes with limited throughput so far.
• A large number of metabolic quantitative trait loci (mQTLs) have been identified based on linkage maps using low-density markers, such as restriction fragment length polymorphism and simple sequence repeat markers (3–5). However, the underlying genes remain elusive because of the relatively low resolution of the genetic maps associated with these markers. In addition to the species-specific accumulation of the metabolites in plant, tissue-specific accumulation of metabolites, especially secondary metabolites, are of special importance for the survival and ad- aptation of plant species. Although the genetics of tissue-specific regulation gene expression across the tissues as revealed by expression quantitative trait locus analysis is one of the major topics in animal and plant, the genetics of tissue-specific metabolome is somewhat overlooked (5, 6). Despite the advance in metabolomics (2), the genetic control of the plant metabolome is still largely unknown.
• In this project, the researchers report a genetic analysis of rice metabolome combining metabolic profiling (12) with an ultrahigh-density genetic map (13) using a recombinant inbred line (RIL) population. We demonstrated that the high-resolution mapping of the large number of mQTLs may greatly accelerate gene identification and pathway elucidation for metabolites, which will enhance our understanding of the genetic and biochemical basis of the metabolome and also be valuable for crop genetic improvement through metabolomics-assisted breeding.

Plant Culture & Treatment

• The mapping population consisted of 210 recombinant inbred lines (RILs) derived from a cross between ZS97 and MH63, the parents of Shanyou 63, the most widely cultivated hybrid in China. Seventy-one introgression lines (ILs) generated from the same parents as the RILs were used for validating the metabolic quantitative trait locus (mQTL) results. The rice plants examined under field conditions were grown in normal rice-growing seasons in the Experimental Station of Huazhong Agricultural University (Wuhan, China). All seeds were planted in a seed bed in mid-May, and transplanted to the field in mid-June. The planting density was 16.5 cm between plants in a row, and the rows were 26 cm apart. Field management, including irrigation, fertilizer application, and pest control, followed essentially the normal agricultural practice. Leaves of the plants were harvested for genomic DNA extraction.
  
  

Figure. 4 Typical pathway model for metabolic pathway reconstruction.

Research Findings

• Figure 4 describes typical pathway model for metabolic pathway reconstruction. (A) QTL mapping results of m0681-L (chrysoeriol O-malonylhexoside), m0444-L (apigenin O-hexoside), m0508-L (chrysoeriol O-hexoside), m0722-L (apigenin O-rutinoside), and m0760-L (chrysoeriol O-rutinoside). (B) QTL mapping results of m0400-L (apigenin C-pentoside) and m0885-L (C-pentosyl-apigenin O-feruloylhexoside). (C) The candidate genes of the aforementioned metabolites.
  
  

Figure. 5 Reconstructed rice metabolic pathways based on the metabolomics and metabolic quantitative trait locus (mQTL) analysis.

• Figure 5 describes the reconstructed rice metabolic pathways based on the metabolomics and metabolic quantitative trait locus (mQTL) analysis. The candidate genes in red and blue indicate the newly mapped genes in flag leaf and germinating seed, respectively. The candidate genes in purple indicate the mapped genes in both tissues. Reported genes shown in black were mapped in this study, whereas those in gray were not. The box in light blue indicates primary metabolic pathways.
• Combining prior knowledge of pathway architecture, the chemical structure of identified/annotated metabolites and the candidate genes revealed in the study, we updated and reconstructed pathways of the corresponding metabolites in rice (Figs. 4 and 5) using the genetic logistic approach as previously described (35, 36). m0508-L (chrysoeriol 7-O-hexoside) showed only one QTL at the UGT706D1 locus, whereas m0681-L (annotated as chrysoeriol O-malonylgluco-side) mapped to UGT706D1 and OsMaT-2 loci, and m0760-L (an- notated as chrysoeriol O-rutinoside) to UGT706D1 and Os11g26950 loci (Fig. 4A and Dataset S5). This enabled us to put both OsMaT-2 and Os11g26950 downstream of UGT706D1 with different branches (Fig. 4C). This deduction also applies to the biosynthesis and modification of C-glycosyl flavones (Fig. 4 B and C). Using this strategy, the pathways were updated and reconstructed (Fig. 5).
• In the newly constructed pathways, most of the structural genes reported previously for flavonoids biosyntheses were mapped (Fig. 5). The broad substrate specificities of both CYP93G2, and UGT706D1 revealed in our study (Fig. 5 and Dataset S5) are consistent with previous studies (10, 37). OsMaT-2, a malonyl- transferase that displayed higher activity toward glycosyl flavonols such as quercetin 3-O-glucoside in vitro (20), was reannotated with its in vivo function listed as specific to glycosyl flavones (Fig. 5 and Dataset S5). In addition, genes underlying the mQTLs for primary metabolites such as LPCs, amino acids, and pyridoxine with its derivative were also mapped (Fig. 5 and Dataset S5).

Labs working on this Project

• National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan),Wuhan 430070, China
• College of Life Science and Technology,Huazhong Agricultural University, Wuhan 430070, China
• Key Laboratory of Horticultural Plant Biology (Ministry of Education), Huazhong Agricultural University, Wuhan 430070, China

Corresponding Author

Qifa Zhang (qifazh@mail.hzau.edu.cn) & Jie Luo (jie.luo@mail.hzau.edu.cn)