Genetic analysis of the metabolome exemplified using a rice population

Abstract

Plant metabolites are crucial for both plant life and human nutrition. Despite recent advance in metabolomics, the genetic control of plant metabolome remains largely unknown. Here, we performed a genetic analysis of the rice metabolome that provided over 2,800 highly resolved metabolic quantitative trait loci for 900 metabolites. Distinct and overlapping accumulation patterns of metabolites were observed and complex genetic regulation of metabolism was revealed in two different tissues. We associated 24 candidate genes to various metabolic quantitative trait loci by data mining, including ones regulating important morphological traits and biological processes. The corresponding pathways were reconstructed by updating in vivo functions of previously identified and newly assigned genes. This study demonstrated a powerful tool and provided a vast amount of high-quality data for understanding the plasticity of plant metabolome, which may help bridge the gap between the genome and phenome.

Keywords: Oryza sativa; gene function; metabolic profiling; recombinant inbred line.

Fig. 1.

The number of detected metabolites, distribution of the values of genetic coefficient of variation (CV), and metabolic quantitative trait loci (mQTLs) for metabolic traits. The number of metabolites detected (A) and distribution of genetic CVs of metabolites (B) in the RIL population. Red, flag leaf. Blue, germinating seed. Distribution of mQTLs in the rice genome in flag leaf (C) and germinating seed (D). The horizontal dashed line indicates the threshold for mQTL hot spots, represented by the maximum number of mQTLs expected to fall into any interval by chance alone with a genome-wide P = 0.01.

Fig. 2.

Validation of the metabolic quantitative trait loci (mQTLs) results with introgression lines (ILs). (A) Overlay heat map of the metabolite profiles of the ILs in comparison with the parental control (ZS, ZS97; MH, MH63). Blue and red indicate that the metabolite contents are decreased or increased, respectively, after the introgression of MH63 segments. The content of m0723-L (tricin O-malonylhexoside) (B), m0873-L (C-pentosyl-apigenin O-caffeoylhexoside) (C), and m0681-L (chrysoeriol O-malonylhexoside) (D) in both parents and the corresponding ILs.

Fig. 3.

Functional identification of OsMaT-2 and OsMaT-3. (A) Phylogenetic analysis of 12 BAHD acyltransferases with OsC1 as an outgroup. The neighbor-joining tree was constructed using aligned full-length amino acid sequences. Bootstrap values from 1,000 replicates are indicated at each node. (Bar: 0.1-aa substitutions per site.) GenBank accession numbers are given in SI Materials and Methods. The mRNA level of OsMaT-2 (B) and the content of m0723-L (C) in OsMaT-2 overexpressors (1–3) (T1) and ZH11. The mRNA level of OsMaT-3 (D) and the content of m0723-L (E) in OsMaT-3 overexpressors (1–3) (T1) and ZH11. All data are given as mean ± SEM (n = 3).

Fig. 4.

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.

Fig. 5.

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. The full names of metabolites’ abbreviation are given in SI Materials and Methods.