Dissection of genotype-phenotype associations in rice grains using metabolome quantitative trait loci analysis

A comprehensive and large‐scale metabolome quantitative trait loci (mQTL) analysis was performed to investigate the genetic backgrounds associated with metabolic phenotypes in rice grains. The metabolome dataset consisted of 759 metabolite signals obtained from the grains of 85 lines of rice (Oryza sativa, Sasanishiki × Habataki back‐crossed inbred lines). Metabolome analysis was performed using four mass spectrometry pipelines to enhance detection of different classes of metabolites. This mQTL analysis of a wide range of metabolites highlighted an uneven distribution of 802 mQTLs on the rice genome, as well as different modes of metabolic trait (m‐trait) control among various types of metabolites. The levels of most metabolites within rice grains were highly sensitive to environmental factors, but only weakly associated with mQTLs. Coordinated control was observed for several groups of metabolites, such as amino acids linked to the mQTL hotspot on chromosome 3. For flavonoids, m‐trait variation among the experimental lines was tightly governed by genetic factors that alter the glycosylation of flavones. Many loci affecting levels of metabolites were detected by QTL analysis, and plausible gene candidates were evaluated by in silico analysis. Several mQTLs profoundly influenced metabolite levels, providing insight into the control of rice metabolism. The genomic region and genes potentially responsible for the biosynthesis of apigenin‐6,8‐di‐C‐α‐l‐ arabinoside are presented as an example of a critical mQTL identified by the analysis.     

Integrated multiple population analysis of leaf architecture traits in maize (Zea mays L.)

Leaf morphology in maize is regulated by developmental patterning along three axes: proximodistal, mediolateral, and adaxial-abaxial. Maize contains homologues of many genes identified as regulators of leaf development in other species, but their relationship to the natural variation of leaf shape remains unknown. In this study, quantitative trait loci (QTLs) for leaf angle, leaf orientation value, leaf length, and leaf width were mapped by a total of 256 F(2:3) families evaluated in three environments. Meta-analysis was used to integrate genetic maps and detect QTLs across several independent QTL studies, on the basis of the previously reported experimental results for leaf architecture traits. Candidate gene sequences for leaf architecture were mapped in the integrated consensus genetic map. In total, 21 QTLs and 17 meta-QTLs (mQTLs) were detected. Among these QTLs, qLA1-1 and qLA2 were consistently detected in five and three populations respectively, and six of seven QTLs with contributions (R(2)) >10% were integrated in mQTLs. Six key mQTLs (mQTL1-1, mQTL2-1, mQTL3-3, mQTL5-1, mQTL7-2, and mQTL8-1) with R(2) of some initial QTLs >10% included 4-6 initial QTLs associated with 2-4 traits. Therefore, the chromosome regions for six mQTLs with high QTL co-localization might be hot spots of the important QTLs for the associated traits. Fifteen key candidate genes controlling leaf architecture traits coincided with 11 corresponding mQTLs, namely DWARF4, KAN3, liguleless1, TAC1, ROT3, AS2/liguleless2, PFL2, yabby9/SE/LIC/yabby15, mwp1, CYCD3;2, and CYCB1. In particular, DWARF4, liguleless1, AS2/liguleless2, yabby9/SE/LIC/yabby15, and CYCD3;2 were mapped within the important mQTL1-1, mQTL2-1, mQTL3-3, mQTL5-1, and mQTL7-2 intervals, respectively. Fine mapping or construction of single chromosome segment lines for genetic regions of these five mQTLs is worth further study and could be put to use in marker-assisted breeding. In conclusion, the results provide useful information for further research and help to reveal the molecular mechanisms with regard to leaf architecture traits.     

Down-regulation of cinnamoyl-CoA reductase in tomato (Solanum lycopersicum L.) induces dramatic changes in soluble phenolic pools

Health-beneficial properties of many secondary plant metabolites have created much interest into the control of their biosynthesis in crop species. Phenolic compounds, including flavonoids, hydroxycinnamates, and tannins, make up an important group of such phytonutrients. They are formed via the phenylpropanoid pathway and share common precursors with lignin, an insoluble cell wall-associated polymer. In this study, the aim was to reduce lignin biosynthesis so as to enhance the availability of these precursors and, thereby, stimulate the production of soluble, potentially health-promoting, phenolic compounds in tomato (Solanum lycopersicum L.). First two tomato genes encoding cinnamoyl-CoA reductase (CCR), a key enzyme in the formation of lignin monomers, were identified and characterized. Transgenic plants exhibiting a reduced lignin content were subsequently obtained through an RNAi strategy targeting one of these genes. As anticipated, the total level of soluble phenolics was higher in stems and leaves of the transformants as compared with control plants. This was correlated with an increased antioxidant capacity of the corresponding plant extracts. Analysis of the soluble phenolic fraction by HPLC-MS revealed that vegetative organs of CCR down-regulated plants contained higher amounts of chlorogenic acid and rutin, and accumulated new metabolites undetectable in the wild type, such as N-caffeoyl putrescine and kaempferol rutinoside. In fruits, CCR down-regulation triggered the moderate accumulation of two new compounds in the flesh, but the total phenolic content was not affected. Although the prospects of exploiting such a strategy for crop improvement are limited, the results provide further insight into the control of the phenylpropanoid pathway in the Solanaceae.     

Genetical metabolomics of flavonoid biosynthesis in Populus: a case study

Genetical metabolomics [metabolite profiling combined with quantitative trait locus (QTL) analysis] has been proposed as a new tool to identify loci that control metabolite abundances. This concept was evaluated in a case study with the model tree Populus. Using HPLC, the peak abundances were analyzed of 15 closely related flavonoids present in apical tissues of two full-sib poplar families, Populus deltoides cv. S9-2 x P. nigra cv. Ghoy and P. deltoides cv. S9-2 x P. trichocarpa cv. V24, and correlation and QTL analysis were used to detect flux control points in flavonoid biosynthesis. Four robust metabolite quantitative trait loci (mQTL), associated with rate-limiting steps in flavonoid biosynthesis, were mapped. Each mQTL was involved in the flux control to one or two flavonoids. Based on the identities of the affected metabolites and the flavonoid pathway structure, a tentative function was assigned to three of these mQTL, and the corresponding candidate genes were mapped. The data indicate that the combination of metabolite profiling with QTL analysis is a valuable tool to identify control points in a complex metabolic pathway of closely related compounds.     

Metabolomics analysis and metabolite‐agronomic trait associations using kernels of wheat (Triticum aestivum) recombinant inbred lines

Plants produce numerous metabolites that are important for their development and growth. However, the genetic architecture of the wheat metabolome has not been well studied. Here, utilizing a high‐density genetic map, we conducted a comprehensive metabolome study via widely targeted LC‐MS/MS to analyze the wheat kernel metabolism. We further combined agronomic traits and dissected the genetic relationship between metabolites and agronomic traits. In total, 1260 metabolic features were detected. Using linkage analysis, 1005 metabolic quantitative trait loci (mQTLs) were found distributed unevenly across the genome. Twenty‐four candidate genes were found to modulate the levels of different metabolites, of which two were functionally annotated by in vitro analysis to be involved in the synthesis and modification of flavonoids. Combining the correlation analysis of metabolite‐agronomic traits with the co‐localization of methylation quantitative trait locus (mQTL) and phenotypic QTL (pQTL), genetic relationships between the metabolites and agronomic traits were uncovered. For example, a candidate was identified using correlation and co‐localization analysis that may manage auxin accumulation, thereby affecting number of grains per spike (NGPS). Furthermore, metabolomics data were used to predict the performance of wheat agronomic traits, with metabolites being found that provide strong predictive power for NGPS and plant height. This study used metabolomics and association analysis to better understand the genetic basis of the wheat metabolism which will ultimately assist in wheat breeding.     

Metabolomic Analysis and Phenylpropanoid Biosynthesis in Hairy Root Culture of Tartary Buckwheat Cultivars

Buckwheat, Fagopyrum tataricum Gaertn., is an important medicinal plant, which contains several phenolic compounds, including one of the highest content of rutin, a phenolic compound with anti-inflammatory properties. An experiment was conducted to investigate the level of expression of various genes in the phenylpropanoid biosynthetic pathway to analyze in vitro production of anthocyanin and phenolic compounds from hairy root cultures derived from 2 cultivars of tartary buckwheat (Hokkai T8 and T10). A total of 47 metabolites were identified by gas chromatography–time-of-flight mass spectrometry (GC-TOFMS) and subjected to principal component analysis (PCA) in order to fully distinguish between Hokkai T8 and T10 hairy roots. The expression levels of phenylpropanoid biosynthetic pathway genes, through qRT-PCR, showed higher expression for almost all the genes in T10 than T8 hairy root except for FtF3’H-2 and FtFLS-2. Rutin, quercetin, gallic acid, caffeic acid, ferulic acid, 4-hydroxybenzoic acid, and 2 anthocyanin compounds were identified in Hokkai T8 and T10 hairy roots. The concentration of rutin and anthocyanin in Hokkai T10 hairy roots of tartary buckwheat was several-fold higher compared with that obtained from Hokkai T8 hairy root. This study provides useful information on the molecular and physiological dynamic processes that are correlated with phenylpropanoid biosynthetic gene expression and phenolic compound content in F. tataricum species.     

Identification of enzymatic and regulatory genes of plant metabolism through QTL analysis in Arabidopsis

The biochemical diversity in the plant kingdom is estimated to well exceed 100,000 distinct compounds (Weckwerth, 2003) and 4000 to 20,000 metabolites per species seem likely (Fernie et al., 2004). In recent years extensive progress has been made towards the identification of enzymes and regulatory genes working in a complex network to generate this large arsenal of metabolites. Genetic loci influencing quantitative traits, e.g. metabolites or biomass, may be mapped to associated molecular markers, a method called quantitative trait locus mapping (QTL mapping), which may facilitate the identification of novel genes in biochemical pathways. Arabidopsis thaliana, as a model organism for seed plants, is a suitable target for metabolic QTL (mQTL) studies due to the availability of highly developed molecular and genetic tools, and the extensive knowledge accumulated on the metabolite profile. While intensely studied, in particular since the availability of its complete sequence, the genome of Arabidopsis still comprises a large proportion of genes with only tentative function based on sequence homology. From a total number of 33,518 genes currently listed (TAIR 9, http://www.arabidopsis.org), only about 25% have direct experimental evidence for their molecular function and biological process, while for more than 30% no biological data are available. Modern metabolomics approaches together with continually extended genomic resources will facilitate the task of assigning functions to those genes. In our previous study we reported on the identification of mQTL (Lisec et al., 2008). In this paper, we summarize the current status of mQTL analyses and causal gene identification in Arabidopsis and present evidence that a candidate gene located within the confidence interval of a fumarate mQTL (AT5G50950) encoding a putative fumarase is likely to be the causal gene of this QTL. The total number of genes molecularly identified based on mQTL studies is still limited, but the advent of multi-parallel analysis techniques for measurement of gene expression, as well as protein and metabolite abundances and for rapid gene identification will assist in the important task of assigning enzymes and regulatory genes to the growing network of known metabolic reactions.     

A genome-wide metabolic QTL analysis in Europeans implicates two loci shaped by recent positive selection

We have performed a metabolite quantitative trait locus (mQTL) study of the (1)H nuclear magnetic resonance spectroscopy ((1)H NMR) metabolome in humans, building on recent targeted knowledge of genetic drivers of metabolic regulation. Urine and plasma samples were collected from two cohorts of individuals of European descent, with one cohort comprised of female twins donating samples longitudinally. Sample metabolite concentrations were quantified by (1)H NMR and tested for association with genome-wide single-nucleotide polymorphisms (SNPs). Four metabolites' concentrations exhibited significant, replicable association with SNP variation (8.6×10(-11)相似文献   

Plant ERD2-like proteins function as endoplasmic reticulum luminal protein receptors and participate in programmed cell death during innate immunity

Plant secondary metabolites, such as those derived from the phenylpropanoid pathway, have a beneficial effect on human health. Manipulation of metabolic flux in the phenylpropanoid pathway is important for achieving enhanced production of compounds such as anthocyanins, flavonoids and isoflavonoids. Here, we describe the development of a high-throughput molecular evolution approach that can be used for catalytic improvement of at least four key phenylpropanoid pathway enzymes, within the context of the metabolic pathway. This method uses yeast cells that express plant phenylpropanoid pathway enzymes, leading to formation of a colored intermediate that can be used as a readout in high-throughput screening. Here we report the identification of improved tomato peel 4-coumarate:CoA ligase variants using this approach. We found that the wild-type enzyme is strongly allosterically inhibited by naringenin, a downstream product of the pathway. Surprisingly, at least two of the improved variants are completely insensitive to feedback inhibition by naringenin. We suggest that this inhibition is exerted through a unique and previously unrecognized allosteric domain.     

Characterization of metabolite quantitative trait loci and metabolic networks that control glucosinolate concentration in the seeds and leaves of Brassica napus

? Glucosinolates are a major class of secondary metabolites found in the Brassicaceae, whose degradation products are proving to be increasingly important for human health and in crop protection. ? The genetic and metabolic basis of glucosinolate accumulation was dissected through analysis of total glucosinolate concentration and its individual components in both leaves and seeds of a doubled-haploid (DH) mapping population of oilseed rape/canola (Brassica napus). ? The quantitative trait loci (QTL) that had an effect on glucosinolate concentration in either or both of the organs were integrated, resulting in 105 metabolite QTL (mQTL). Pairwise correlations between individual glucosinolates and prior knowledge of the metabolic pathways involved in the biosynthesis of different glucosinolates allowed us to predict the function of genes underlying the mQTL. Moreover, this information allowed us to construct an advanced metabolic network and associated epistatic interactions responsible for the glucosinolate composition in both leaves and seeds of B. napus. ? A number of previously unknown potential regulatory relationships involved in glucosinolate synthesis were identified and this study illustrates how genetic variation can affect a biochemical pathway.     

Genetic analysis of leaf morphology underlying the plant density response by QTL mapping in maize (<Emphasis Type="Italic">Zea mays</Emphasis> L.)

Maize yield increase has been strongly linked to plant population densities over time with changes in plant architecture, but the genetic basis for the plant architecture response to plant density is unknown, as is its stability across environments. To elucidate the genetic basis of the plant architecture response to density in maize, we mapped quantitative trait loci (QTLs) for leaf morphology-related traits in four sets of recombinant inbred line (RIL) populations under two plant density conditions. Forty-five QTLs for six traits were detected in both high and low plant density conditions. Thirty-seven QTLs were only detected when grown under high plant density, and 34 QTLs were only detected when grown under low plant density. Twenty-two meta-QTLs (mQTLs) were identified by meta-analysis, and mQTL1-1, mQTL3-2 and mQTL8 were identified when grown under high and low plant densities, with R ² of some initial QTLs > 10 %, suggesting the mQTLs might be hot spots of the important QTLs for the related traits under planting density stress conditions. The results presented here provide useful information for further research and the marker-assisted selection of varieties targeting increased plant density and will help to reveal the molecular mechanisms related to leaf morphology in response to density.     

Soluble and wall-bound phenolics and phenolic polymers in Musa acuminata roots exposed to elicitors from Fusarium oxysporum f.sp. cubense

The accumulation of soluble and wall-bound phenolics and phenolic polymers in Musa acuminata roots exposed to cell wall-derived elicitor from the pathogen, Fusarium oxysporum, f.sp. cubense, race four, was investigated. The root tissue from the banana cultivar "Goldfinger" was found to respond strongly and rapidly towards the elicitor through the increased synthesis of phenolic compounds. Following elicitation, the conjugated and non-conjugated phenolic metabolites in the induced root tissue were extracted and quantified. Induced phenolic synthesis was rapid and reached near maximum values after 16 h. High-performance liquid chromatography revealed both compositional and quantitative differences between induced phenolics (p-coumaric, ferulic, and sinapic acids) and those constitutively present (p-coumaric- and ferulic acid). In addition, vanillic acid was found in the ester-bound fraction and protocatechuic acid in the cell-wall bound fraction of elicited tissue. The deposition and accumulation kinetics of polymerized phenolic monomers as lignin and lignin-like polymers was quantified over a time period of 0-36 h and found to reach maximum values after 24 h. Ionization difference UV spectra of lignin indicated compositional differences in the newly synthesized lignin fraction and correlated with increased concentrations of ferulic acid and sinapic acids esters. The results show that the increased flux through the phenylpropanoid pathway resulted in the synthesis of cinnamic acid and benzoic acid derivatives that were esterified and incorporated into the cell wall fraction as part of the anti-microbial defenses activated in the root tissue.     

Tissue-Specific,Development-Dependent Phenolic Compounds Accumulation Profile and Gene Expression Pattern in Tea Plant [Camellia sinensis]

Phenolic compounds in tea plant [Camellia sinensis (L.)] play a crucial role in dominating tea flavor and possess a number of key pharmacological benefits on human health. The present research aimed to study the profile of tissue-specific, development-dependent accumulation pattern of phenolic compounds in tea plant. A total of 50 phenolic compounds were identified qualitatively using liquid chromatography in tandem mass spectrometry technology. Of which 29 phenolic compounds were quantified based on their fragmentation behaviors. Most of the phenolic compounds were higher in the younger leaves than that in the stem and root, whereas the total amount of proanthocyanidins were unexpectedly higher in the root. The expression patterns of 63 structural and regulator genes involved in the shikimic acid, phenylpropanoid, and flavonoid pathways were analyzed by quantitative real-time polymerase chain reaction and cluster analysis. Based on the similarity of their expression patterns, the genes were classified into two main groups: C1 and C2; and the genes in group C1 had high relative expression level in the root or low in the bud and leaves. The expression patterns of genes in C2-2-1 and C2-2-2-1 groups were probably responsible for the development-dependent accumulation of phenolic compounds in the leaves. Enzymatic analysis suggested that the accumulation of catechins was influenced simultaneously by catabolism and anabolism. Further research is recommended to know the expression patterns of various genes and the reason for the variation in contents of different compounds in different growth stages and also in different organs.     

Comparative analysis of metabolome of rice seeds at three developmental stages using a recombinant inbred line population

Plants are considered an important food and nutrition source for humans. Despite advances in plant seed metabolomics, knowledge about the genetic and molecular bases of rice seed metabolomes at different developmental stages is still limited. Here, using Zhenshan 97 (ZS97) and Minghui 63 (MH63), we performed a widely targeted metabolic profiling in seeds during grain filling, mature seeds and germinating seeds. The diversity between MH63 and ZS97 was characterized in terms of the content of metabolites and the metabolic shifting across developmental stages. Taking advantage of the ultra‐high‐density genetic map of a population of 210 recombinant inbred lines (RILs) derived from a cross between ZS97 and MH63, we identified 4681 putative metabolic quantitative trait loci (mQTLs) in seeds across the three stages. Further analysis of the mQTLs for the codetected metabolites across the three stages revealed that the genetic regulation of metabolite accumulation was closely related to developmental stage. Using in silico analyses, we characterized 35 candidate genes responsible for 30 structurally identified or annotated compounds, among which LOC_Os07g04970 and LOC_Os06g03990 were identified to be responsible for feruloylserotonin and l ‐asparagine content variation across populations, respectively. Metabolite?agronomic trait association and colocation between mQTLs and phenotypic quantitative trait loci (pQTLs) revealed the complexity of the metabolite?agronomic trait relationship and the corresponding genetic basis.     

Sequence diversity and differential expression of major phenylpropanoid-flavonoid biosynthetic genes among three mango varieties

Background

Mango fruits contain a broad spectrum of phenolic compounds which impart potential health benefits; their biosynthesis is catalysed by enzymes in the phenylpropanoid-flavonoid (PF) pathway. The aim of this study was to reveal the variability in genes involved in the PF pathway in three different mango varieties Mangifera indica L., a member of the family Anacardiaceae: Kensington Pride (KP), Irwin (IW) and Nam Doc Mai (NDM) and to determine associations with gene expression and mango flavonoid profiles.

Results

A close evolutionary relationship between mango genes and those from the woody species poplar of the Salicaceae family (Populus trichocarpa) and grape of the Vitaceae family (Vitis vinifera), was revealed through phylogenetic analysis of PF pathway genes. We discovered 145 SNPs in total within coding sequences with an average frequency of one SNP every 316 bp. Variety IW had the highest SNP frequency (one SNP every 258 bp) while KP and NDM had similar frequencies (one SNP every 369 bp and 360 bp, respectively). The position in the PF pathway appeared to influence the extent of genetic diversity of the encoded enzymes. The entry point enzymes phenylalanine lyase (PAL), cinnamate 4-mono-oxygenase (C4H) and chalcone synthase (CHS) had low levels of SNP diversity in their coding sequences, whereas anthocyanidin reductase (ANR) showed the highest SNP frequency followed by flavonoid 3’-hydroxylase (F3’H). Quantitative PCR revealed characteristic patterns of gene expression that differed between mango peel and flesh, and between varieties.

Conclusions

The combination of mango expressed sequence tags and availability of well-established reference PF biosynthetic genes from other plant species allowed the identification of coding sequences of genes that may lead to the formation of important flavonoid compounds in mango fruits and facilitated characterisation of single nucleotide polymorphisms between varieties. We discovered an association between the extent of sequence variation and position in the pathway for up-stream genes. The high expression of PAL, C4H and CHS genes in mango peel compared to flesh is associated with high amounts of total phenolic contents in peels, which suggest that these genes have an influence on total flavonoid levels in mango fruit peel and flesh. In addition, the particularly high expression levels of ANR in KP and NDM peels compared to IW peel and the significant accumulation of its product epicatechin gallate (ECG) in those extracts reflects the rate-limiting role of ANR on ECG biosynthesis in mango.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1784-x) contains supplementary material, which is available to authorized users.