*4.4. Metabolic Pathway Analysis*

Based on the differential metabolites and transcripts, the comprehensive metabolic responses in rice plants induced by *OsCYP96B4* gene mutation were mapped onto relevant metabolic pathways, with reference to the KEGG pathway database [65].

#### **5. Conclusions**

In the present study, the combination of NMR-based metabolomics and qRT-PCR analyses revealed that there were systems alteration in the metabolic phenotypes of semi-dwarf mutant (M) and ectopic expression (ECE) rice lines in comparison with the wild-type (WT) rice, as a result of the *OsCYP96B4* gene mutation. Such changes included the significant effect on amino acid metabolism (e.g., GABA shunt, glutamate and glutamine metabolism, branched-chain amino acid metabolism, choline metabolism), carbohydrate metabolism (e.g., sucrose metabolism, TCA cycle), nucleotide metabolism, and shikimate-mediated secondary metabolism. The present findings provide useful information on understanding the *OsCYP96B4* gene function possibly pertaining to the metabolism and dwarfism, which may be helpful for the development of valuable new semi-dwarf plant mutants in the future.

*Int. J. Mol. Sci.* **2020**, *21*, 1924

**Supplementary Materials:** The following are available online at http://www.mdpi.com/1422-0067/21/6/1924/s1, Figure S1: PCA scores plots derived from 1H NMR spectra of rice plant extracts from different groups; Figure S2: Permutation test results (with 200 permutations) for PLS-DA models (with 2 components) derived from 1H NMR spectra of rice plant extracts from different groups; Figure S3: Representative phenotypes of the 2-week-old (A) *oscyp96b4* semi-dwarf mutant (M), (B) *OsCYP96B4* ectopic expression (ECE), and (C) wild-type (WT) rice plants; Table S1: 1H and 13C NMR assignment for metabolites in rice plant extracts; Table S2: OPLS-DA loadings correlation coefficients; Table S3: Primers for quantitative real-time PCR analysis on selected genes.

**Author Contributions:** Conceptualization, L.J., R.R. and P.P.K.; Data curation, L.J., R.R. and S.R.; Formal analysis, L.J., R.R. and S.R.; Funding acquisition, L.J. and P.P.K.; Investigation, L.J., R.R. and S.R.; Methodology, L.J. and R.R.; Project administration, L.J. and P.P.K.; Resources, L.J., S.R. and P.P.K.; Software, L.J. and R.R.; Supervision, L.J. and P.P.K.; Validation, L.J. and R.R.; Visualization, L.J. and R.R.; Writing—original draft, L.J.; Writing—review & editing, L.J., R.R., S.R. and P.P.K. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research was funded by National University of Singapore (R-180-000-016-733; NRF-CRP7-2010-02), Huazhong University of Science and Technology (513-3004513113), and the Chinese Academy of Sciences (KJZD-EW-G20-01).

**Acknowledgments:** We acknowledge the help of Siyi Guo and Toshiro Ito (Temasek Life Sciences Laboratory) for the use of Geno/Grinder®. Limiao Jiang gratefully acknowledges Huiru Tang (Fudan University) for the kind help on facilitating this collaborative study and thanks Caixiang Liu (Wuhan Institute of Physics and Mathematics) for the useful discussion.

**Conflicts of Interest:** The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.
