*Article* **Systems Metabolic Alteration in a Semi-Dwarf Rice Mutant Induced by** *OsCYP96B4* **Gene Mutation**

**Limiao Jiang 1,2,\*,**†**, Rengasamy Ramamoorthy 3,**†**, Srinivasan Ramachandran <sup>4</sup> and Prakash P. Kumar 3,5,\***


Received: 26 November 2019; Accepted: 8 March 2020; Published: 11 March 2020

**Abstract:** Dwarfism and semi-dwarfism are among the most valuable agronomic traits in crop breeding, which were adopted by the "Green Revolution". Previously, we reported a novel semi-dwarf rice mutant (*oscyp96b4*) derived from the insertion of a single copy of *Dissociator (Ds)* transposon into the gene *OsCYP96B4*. However, the systems metabolic effect of the mutation is not well understood, which is important for understanding the gene function and developing new semi-dwarf mutants. Here, the metabolic phenotypes in the semi-dwarf mutant (M) and ectopic expression (ECE) rice line were compared to the wild-type (WT) rice, by using nuclear magnetic resonance (NMR) metabolomics and quantitative real-time polymerase chain reaction (qRT-PCR). Compared with WT, ECE of the *OsCYP96B4* gene resulted in significant increase of γ-aminobutyrate (GABA), glutamine, and alanine, but significant decrease of glutamate, aromatic and branched-chain amino acids, and some other amino acids. The ECE caused significant increase of monosaccharides (glucose, fructose), but significant decrease of disaccharide (sucrose); induced significant changes of metabolites involved in choline metabolism (phosphocholine, ethanolamine) and nucleotide metabolism (adenosine, adenosine monophosphate, uridine). These metabolic profile alterations were accompanied with changes in the gene expression levels of some related enzymes, involved in GABA shunt, glutamate and glutamine metabolism, choline metabolism, sucrose metabolism, glycolysis/gluconeogenesis pathway, tricarboxylic acid (TCA) cycle, nucleotide metabolism, and shikimate-mediated secondary metabolism. The semi-dwarf mutant showed corresponding but less pronounced changes, especially in the gene expression levels. It indicates that *OsCYP96B4* gene mutation in rice causes significant alteration in amino acid metabolism, carbohydrate metabolism, nucleotide metabolism, and shikimate-mediated secondary metabolism. The present study will provide essential information for the *OsCYP96B4* gene function analysis and may serve as valuable reference data for the development of new semi-dwarf mutants.

**Keywords:** rice; dwarfism; *OsCYP96B4*; metabolomics; NMR; qRT-PCR

#### **1. Introduction**

Rice (*Oryza sativa* L.) is an important staple food for more than half of the global population [1]. Its sustainable production is critical to the world's food security and the health of the ever-increasing global population. Although nitrogen fertilization is essential for improving grain yield, the increasing usage rate will lead to increased plant height [2,3]. The resulting taller plants are prone to lodging caused by wind/rain, which will increase the difficulty of harvest, promote pre-harvest germination and fungal contamination, and ultimately lead to significant reduction in grain yield and quality [2,4].

As adopted by the "Green Revolution" [2], dwarfism and semi-dwarfism are among the most valuable agronomic traits in crop breeding [5,6]. The semi-dwarfism in rice enhances their lodging resistance (e.g., to wind and rain), improves harvest index (i.e., grain/straw ratio) and enhances biomass production [2]. Therefore, a wide range of studies have been done on the development of rice semi-dwarf mutants [3,6–8], which can be broadly categorized into phytohormone-dependent (e.g., brassinosteroids- or gibberellins-related) and phytohormone-independent mutants [6]. Previously, we reported a novel phytohormone-independent semi-dwarf rice mutant derived from the insertion of a single copy of transposon *Dissociator (Ds)* into the gene *OsCYP96B4* (*Oryza sativa CytochromeP450 96B4*), which resulted in defects in cell elongation and pollen germination [5]. As one of the largest protein-encoding gene families in plants, the cytochrome P450 (CYP) superfamily plays important roles in plant growth, development, and responses to biotic and abiotic stresses [9]. CYP96B subfamily belongs to the CYP96 family of the CYP86 clan. Recently, the functions of the CYP96B subfamily have been gradually revealed. CYP96B5 hydroxylates alkanes to primary alcohols and is involved in rice leaf cuticular wax synthesis [10]. *OsCYP96B4* is involved in secondary cell wall formation in rice [11], associated with the growth and drought stress responses in rice [12], and may be an important regulator of plant growth that affects plant height in rice [6]. However, to the best of our knowledge, currently, the systems metabolic effect of the *OsCYP96B4* gene mutation in rice is unclear, which is important for understanding the gene function and developing new semi-dwarf mutants.

Metabolomics is useful in characterizing the systems metabolic changes of biological systems to genetic modification or environmental stimuli [13–16]. Nuclear magnetic resonance (NMR) and mass spectrometry (MS) are the two dominant high-throughput analytical platforms employed in metabolomics, possessing their own advantages and providing complementary metabolic information [17]. For NMR analysis, it shows very high reproducibility, requires minimal sample preparation, detects in a non-selective manner and favors unambiguous metabolite identification [17]. Metabolomics has been widely applied in evaluating the metabolic response of plants to gene manipulation and biotic/abiotic stresses, e.g., the insertion of a moss Na<sup>+</sup> transporter gene in rice and barley [18], the influence of *SUB1A* gene during submergence stress in rice [19], *Tri5* gene deletion in *Fusarium graminearum* [20], antisense thioredoxin s (*anti-trx-s*) introduction to wheat for pre-harvest sprouting resistance [21], *Fusarium oxysporum* inoculation in chickpea roots [22], brown planthopper infestation in pest-susceptible and -resistant rice plants [23]. Metabolomics has also been used to characterize the metabolic phenotypes of plant dwarf and semi-dwarf mutants, e.g., BW312 barley (*Hordeum vulgare*) semi-dwarf mutant [24], dwarf banana (*Musa* spp.; Musaceae) variants [25], tomato (*Solanum lycopersicum* L.) dwarf cultivar Micro-Tom [26], a dwarf genotype of soybean named MiniMax [27], and dwarfed *tcd2* (*totally cyanide deficient 2*) mutants of *Sorghum bicolor* (L.) Moench [28]. Such studies indicate that there are significant metabolic profile alterations in the dwarf/semi-dwarf mutant plants. However, to the best of our knowledge, currently, there is no metabolomics study on the dwarf rice.

In the present study, we investigated the differences in the metabolome and related gene expression levels among the *oscyp96b4* semi-dwarf mutant (M), ectopic expression (ECE), and wild-type (WT) rice using NMR-based metabolomics and quantitative real-time polymerase chain reaction (qRT-PCR). We aimed to (1) characterize the metabolic phenotypes of the mutant rice and (2) elucidate the systems metabolic effect of the mutation by integrating the metabolomics and gene expression data. The analysis

provides essential information on the *OsCYP96B4* gene function and may serve as reference data for the development of new semi-dwarf mutants.

### **2. Results**

#### *2.1. Metabolite Profiling in Wild-Type and Mutant Rice*

In the 1H NMR spectra of rice extracts, a total of 42 abundant metabolites were assigned (Table S1) according to 2D NMR experiments and literature reports [29]. Typical 1D 1H NMR spectra of WT, M, and ECE rice extracts were shown in Figure 1. The NMR spectra contain signals mainly from amino acids and derivatives, choline metabolism-related metabolites, carbohydrate metabolites, tricarboxylic acid (TCA) cycle intermediates, nucleotide metabolites, N-methylnicotinate, nicotinamide mononucleotide, lipid, formate, methylamine, mono-methyl phosphate, and methanol.

**Figure 1.** Representative 800 MHz 1H NMR spectra for the extracts of 2-week-old seedling shoots (without roots) from (**a**) the wild type, (**b**) the *oscyp96b4* semi-dwarf mutant, and (**c**) the *OsCYP96B4* ectopic expression rice lines. The dotted regions δ0.5−3.1 and δ5.5−9.61 were vertically expanded 4 and 32 times respectively, compared to the region δ3.1-4.5. Metabolite keys: 1, isoleucine; 2, leucine; 3, valine; 4, lipid; 5, threonine; 6, lysine; 7, alanine; 8, arginine; 9, γ-aminobutyrate; 10, glutamate; 11, glutamine; 12, malate; 13, succinate; 14, 2-oxoglutarate; 15, citrate; 16, methylamine; 17, aspartate; 18, asparagine; 19, ethanolamine; 20, choline; 21, phosphocholine; 22, β-glucose; 23, α-glucose; 24, methanol; 25, mono-methyl phosphate; 26, sucrose; 27, uridine; 28, uridine 5- -monophosphate (UMP); 29, allantoin; 30, uridine diphosphate glucuronic acid (UDP glucuronate); 31, adenosine; 32, adenosine monophosphate (AMP); 33, fumarate; 34, tyrosine; 35, histidine; 36, tryptophan; 37, phenylalanine; 38, N-methylnicotinate (trigonelline, NMNA); 39, nicotinamide mononucleotide (nicotinamide ribotide, NMN); 40, formate; 41, β-D-fructopyranose; 42, β-D-fructofuranose.
