Metabolome-based genome-wide association study of maize kernel leads to novel biochemical insights

Molecular mechanisms underlying gene regulatory variation of maize metabolic traits

Variation in gene expression levels is pervasive among individuals and races or varieties, and has substantial agronomic consequences, for example, by contributing to hybrid vigor. Gene expression level variation results from mutations in regulatory sequences (cis) and/or transcription factor (TF) activity (trans), but the mechanisms underlying cis- and/or trans-regulatory variation of complex phenotypes remain largely unknown. Here, we investigated gene expression variation mechanisms underlying the differential accumulation of the insecticidal compounds maysin and chlorogenic acid in silks of widely used maize (Zea mays) inbreds, B73 and A632. By combining transcriptomics and cistromics, we identified 1,338 silk direct targets of the maize R2R3-MYB TF Pericarp color1 (P1), consistent with it being a regulator of maysin and chlorogenic acid biosynthesis. Among these P1 targets, 464 showed allele-specific expression (ASE) between B73 and A632 silks. Allelic DNA-affinity purification sequencing identified 34 examples in which P1 allelic specific binding (ASB) correlated with cis-expression variation. From previous yeast one-hybrid studies, we identified 9 TFs potentially implicated in the control of P1 targets, with ASB to 83 out of 464 ASE genes (cis) and differential expression of 4 out of 9 TFs between B73 and A632 silks (trans). These results provide a molecular framework for understanding universal mechanisms underlying natural variation of gene expression levels, and how the regulation of metabolic diversity is established.

Exploring the influence of a single-nucleotide mutation in EIN4 on tomato fruit firmness diversity through fruit pericarp microstructure

Tomato (Solanum lycopersicum) stands as one of the most valuable vegetable crops globally, and fruit firmness significantly impacts storage and transportation. To identify genes governing tomato firmness, we scrutinized the firmness of 266 accessions from core collections. Our study pinpointed an ethylene receptor gene, SlEIN4, located on chromosome 4 through a genome-wide association study (GWAS) of fruit firmness in the 266 tomato core accessions. A single-nucleotide polymorphism (SNP) (A → G) of SlEIN4 distinguished lower (AA) and higher (GG) fruit firmness genotypes. Through experiments, we observed that overexpression of SlEIN4AA significantly delayed tomato fruit ripening and dramatically reduced fruit firmness at the red ripe stage compared with the control. Conversely, gene editing of SlEIN4AA with CRISPR/Cas9 notably accelerated fruit ripening and significantly increased fruit firmness at the red ripe stage compared with the control. Further investigations revealed that fruit firmness is associated with alterations in the microstructure of the fruit pericarp. Additionally, SlEIN4AA positively regulates pectinase activity. The transient transformation assay verified that the SNP (A → G) on SlEIN4 caused different genetic effects, as overexpression of SlEIN4GG increased fruit firmness. Moreover, SlEIN4 exerts a negative regulatory role in tomato ripening by impacting ethylene evolution through the abundant expression of ethylene pathway regulatory genes. This study presents the first evidence of the role of ethylene receptor genes in regulating fruit firmness. These significant findings will facilitate the effective utilization of firmness and ripening traits in tomato improvement, offering promising opportunities for enhancing tomato storage and transportation capabilities.

The genetic architecture of the pepper metabolome and the biosynthesis of its signature capsianoside metabolites

Capsicum (pepper) is among the most economically important species worldwide, and its fruits accumulate specialized metabolites with essential roles in plant environmental interaction and human health benefits as well as in conferring their unique taste. However, the genetics underlying differences in metabolite presence/absence and/or accumulation remain largely unknown. In this study, we carried out a genome-wide association study as well as generating and characterizing a novel backcross inbred line mapping population to determine the genetic architecture of the pepper metabolome. This genetic analysis provided over 1,000 metabolic quantitative trait loci (mQTL) for over 250 annotated metabolites. We identified 92 candidate genes involved in various mQTLs. Among the identified loci, we described and validated a gene cluster of eleven UDP-glycosyltransferases (UGTs) involved in monomeric capsianoside biosynthesis. We additionally constructed the gene-by-gene-based biosynthetic pathway of pepper capsianoside biosynthesis, including both core and decorative reactions. Given that one of these decorative pathways, namely the glycosylation of acyclic diterpenoid glycosides, contributes to plant resistance, these data provide new insights and breeding resources for pepper. They additionally provide a blueprint for the better understanding of the biosynthesis of species-specific natural compounds in general.

Prioritizing Maize Metabolic Gene Regulators through Multi-Omic Network Integration

Elucidating gene regulatory networks is a major area of study within plant systems biology. Phenotypic traits are intricately linked to specific gene expression profiles. These expression patterns arise primarily from regulatory connections between sets of transcription factors (TFs) and their target genes. Here, we integrated 46 co-expression networks, 283 protein-DNA interaction (PDI) assays, and 16 million SNPs used to identify expression quantitative trait loci (eQTL) to construct TF-target networks. In total, we analyzed ∼4.6M interactions to generate four distinct types of TF-target networks: co-expression, PDI, trans -eQTL, and cis -eQTL combined with PDIs. To functionally annotate TFs based on their target genes, we implemented three different network integration strategies. We evaluated the effectiveness of each strategy through TF loss-of function mutant inspection and random network analyses. The multi-network integration allowed us to identify transcriptional regulators of several biological processes. Using the topological properties of the fully integrated network, we identified potential functionally redundant TF paralogs. Our findings retrieved functions previously documented for numerous TFs and revealed novel functions that are crucial for informing the design of future experiments. The approach here-described lays the foundation for the integration of multi-omic datasets in maize and other plant systems.

GRAPHICAL ABSTRACT

Developing benzylisoquinoline alkaloid-enriched opium poppy via CRISPR-directed genome editing: A review

Among plant-derived secondary metabolites are benzylisoquinoline alkaloids (BIAs) that play a vital role in medicine. The most conspicuous BIAs frequently found in opium poppy are morphine, codeine, thebaine, papaverine, sanguinarine, and noscapine. BIAs have provided abundant clinically useful drugs used in the treatment of various diseases and ailments With an increasing demand for these herbal remedies, genetic improvement of poppy plants appears to be essential to live up to the expectations of the pharmaceutical industry. With the advent of clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated9 (Cas9), the field of metabolic engineering has undergone a paradigm shift in its approach due to its appealing attributes, such as the transgene-free editing capability, precision, selectivity, robustness, and versatility. The potentiality of the CRISPR system for manipulating metabolic pathways in opium poppy was demonstrated, but further investigations regarding the use of CRISPR in BIA pathway engineering should be undertaken to develop opium poppy into a bioreactor synthesizing BIAs at the industrial-scale levels. In this regard, the recruitment of RNA-guided genome editing for knocking out miRNAs, flower responsible genes, genes involved in competitive pathways, and base editing are described. The approaches presented here have never been suggested or applied in opium poppy so far.

Genome-wide identification of the sorghum OVATE gene family and revelation of its expression characteristics in sorghum seeds and leaves

The OVATE gene family plays an important role in regulating the development of plant organs and resisting stress, but its expression characteristics and functions in sorghum have not been revealed. In this study, we identified 26 OVATE genes in the sorghum BTx623 genome, which were divided into four groups and distributed unevenly across 9 chromosomes. Evolutionary analysis showed that after differentiation between sorghum and Arabidopsis, the OVATE gene family may have experienced unique expansion events, and all OVATE family members were negatively selected. Transcriptome sequencing and RT-qPCR results showed that OVATE genes in sorghum showed diverse expression characteristics, such as gene SORBl_3001G468900 and SORBl_3009G173400 were significantly expressed in seeds, while SORBI_3005G042700 and SORBI_3002G417700 were only highly expressed in L1. Meantime, in the promoter region, a large number of hormone-associated cis-acting elements were identified, and these results suggest that members of the OVATE gene family may be involved in regulating specific development of sorghum leaves and seeds. This study improves the understanding of the OVATE gene family of sorghum and provides important clues for further exploration of the function of the OVATE gene family.

Mechanical Activation of Graphite for Na-Ion Battery Anodes: Unexpected Reversible Reaction on Solid Electrolyte Interphase via X-Ray Analysis

Although sodium-ion batteries (SIBs) offer promising low-cost alternatives to lithium-ion batteries (LIBs), several challenges need to be overcome for their widespread adoption. A primary concern is the optimization of carbon anodes. Graphite, vital to the commercial viability of LIBs, has a limited capacity for sodium ions. Numerous alternatives to graphite are explored, particularly focusing on disordered carbons, including hard carbon. However, compared with graphite, most of these materials underperform in LIBs. Furthermore, the reaction mechanism between carbon and sodium ions remains ambiguous owing to the structural diversity of disordered carbon. A straightforward mechanical approach is introduced to enhance the sodium ion storage capacity of graphite, supported by comprehensive analytical techniques. Mechanically activated graphite delivers a notable reversible capacity of 290.5 mAh·g-1 at a current density of 10 mA·g-1. Moreover, it maintains a capacity of 157.7 mAh·g-1 even at a current density of 1 A·g-1, benefiting from the defect-rich structure achieved by mechanical activation. Soft X-ray analysis revealed that this defect-rich carbon employs a sodium-ion storage mechanism distinct from that of hard carbon. This leads to an unexpected reversible reaction on the solid electrolyte surface. These insights pave the way for innovative design approaches for carbon electrodes in SIB anodes.

Photoperiod-Dependent Nutrient Accumulation in Rice Cultivated in Plant Factories: A Comparative Metabolomic Analysis

Plant factories offer a promising solution to some of the challenges facing traditional agriculture, allowing for year-round rapid production of plant-derived foods. However, the effects of conditions in plant factories on metabolic nutrients remain to be explored. In this study, we used three rice accessions (KongYu131, HuangHuaZhan, and Kam Sweet Rice) as objectives, which were planted in a plant factory with strict photoperiods that are long-day (12 h light/12 h dark) or short-day (8 h light/16 h dark). A total of 438 metabolites were detected in the harvested rice grains. The difference in photoperiod leads to a different accumulation of metabolites in rice grains. Most metabolites accumulated significantly higher levels under the short-day condition than the long-day condition. Differentially accumulated metabolites were enriched in the amino acids and vitamin B6 pathway. Asparagine, pyridoxamine, and pyridoxine are key metabolites that accumulate at higher levels in rice grains harvested from the short-day photoperiod. This study reveals the photoperiod-dependent metabolomic differences in rice cultivated in plant factories, especially the metabolic profiling of taste- and nutrition-related compounds.

Dynamic metabolite QTL analyses provide novel biochemical insights into kernel development and nutritional quality improvement in common wheat

Despite recent advances in crop metabolomics, the genetic control and molecular basis of the wheat kernel metabolome at different developmental stages remain largely unknown. Here, we performed widely targeted metabolite profiling of kernels from three developmental stages (grain-filling kernels [FKs], mature kernels [MKs], and germinating kernels [GKs]) using a population of 159 recombinant inbred lines. We detected 625 annotated metabolites and mapped 3173, 3143, and 2644 metabolite quantitative trait loci (mQTLs) in FKs, MKs, and GKs, respectively. Only 52 mQTLs were mapped at all three stages, indicating the high stage specificity of the wheat kernel metabolome. Four candidate genes were functionally validated by in vitro enzymatic reactions and/or transgenic approaches in wheat, three of which mediated the tricin metabolic pathway. Metabolite flux efficiencies within the tricin pathway were evaluated, and superior candidate haplotypes were identified, comprehensively delineating the tricin metabolism pathway in wheat. Finally, additional wheat metabolic pathways were re-constructed by updating them to incorporate the 177 candidate genes identified in this study. Our work provides new information on variations in the wheat kernel metabolome and important molecular resources for improvement of wheat nutritional quality.

Integrated transcriptome and metabolome analysis reveals the regulation of phlorizin synthesis in Lithocarpus polystachyus under nitrogen fertilization

BACKGROUND

Nitrogen (N) is essential for plant growth and development. In Lithocarpus polystachyus Rehd., a species known for its medicinal and food value, phlorizin is the major bioactive compound with pharmacological activity. Research has revealed a positive correlation between plant nitrogen (N) content and phlorizin synthesis in this species. However, no study has analyzed the effect of N fertilization on phlorizin content and elucidated the molecular mechanisms underlying phlorizin synthesis in L. polystachyus.

RESULTS

A comparison of the L. polystachyus plants grown without (0 mg/plant) and with N fertilization (25, 75, 125, 175, 225, and 275 mg/plant) revealed that 75 mg N/plant fertilization resulted in the greatest seedling height, ground diameter, crown width, and total phlorizin content. Subsequent analysis of the leaves using ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) detected 150 metabolites, including 42 flavonoids, that were differentially accumulated between the plants grown without and with 75 mg/plant N fertilization. Transcriptomic analysis of the L. polystachyus plants via RNA sequencing revealed 162 genes involved in flavonoid biosynthesis, among which 53 significantly differed between the N-treated and untreated plants. Fertilization (75 mg N/plant) specifically upregulated the expression of the genes phenylalanine ammonia-lyase (PAL), 4-coumarate-CoA ligase (4CL), and phlorizin synthase (PGT1) but downregulated the expression of trans-cinnamate 4-monooxygenase (C4H), shikimate O-hydroxycinnamoyltransferase (HCT), and chalcone isomerase (CHI), which are related to phlorizin synthesis. Finally, an integrated analysis of the transcriptome and metabolome revealed that the increase in phlorizin after N fertilization was consistent with the upregulation of phlorizin biosynthetic genes. Quantitative real-time PCR (qRT‒PCR) was used to validate the RNA sequencing data. Thus, our results indicated that N fertilization increased phlorizin metabolism in L. polystachyus by regulating the expression levels of the PAL, PGT1, 5-O-(4-coumaroyl)-D-quinate 3'-monooxygenase (C3'H), C4H, and HCT genes.

CONCLUSIONS

Our results demonstrated that the addition of 75 mg/plant N to L. polystachyus significantly promoted the accumulation of flavonoids, including phlorizin, and the expression of flavonoid synthesis-related genes. Under these conditions, the genes PAL, 4CL, and PGT1 were positively correlated with phlorizin accumulation, while C4H, CHI, and HCT were negatively correlated with phlorizin accumulation. Therefore, we speculate that PAL, 4CL, and PGT1 participate in the phlorizin pathway under an optimal N environment, regulating phlorizin biosynthesis. These findings provide a basis for improving plant bioactive constituents and serve as a reference for further pharmacological studies.

Combining association with linkage mapping to dissect the phenolamides metabolism of the maize kernel

Phenolamides are important secondary metabolites in plant species. They play important roles in plant defense responses against pathogens and insect herbivores, protection against UV irradiation and floral induction and development. However, the accumulation and variation in phenolamides content in diverse maize lines and the genes responsible for their biosynthesis remain largely unknown. Here, we combined genetic mapping, protein regulatory network and bioinformatics analysis to further enhance the understanding of maize phenolamides biosynthesis. Sixteen phenolamides were identified in multiple populations, and they were all significantly correlated with one or several of 19 phenotypic traits. By linkage mapping, 58, 58, 39 and 67 QTLs, with an average of 3.9, 3.6, 3.6 and 4.2 QTLs for each trait were mapped in BBE1, BBE2, ZYE1 and ZYE2, explaining 9.47%, 10.78%, 9.51% and 11.40% phenotypic variation for each QTL on average, respectively. By GWAS, 39 and 36 significant loci were detected in two different environments, 3.3 and 2.8 loci for each trait, explaining 10.00% and 9.97% phenotypic variation for each locus on average, respectively. Totally, 58 unique candidate genes were identified, 31% of them encoding enzymes involved in amine and derivative metabolic processes. Gene Ontology term analysis of the 358 protein-protein interrelated genes revealed significant enrichment in terms relating to cellular nitrogen metabolism, amine metabolism. GRMZM2G066142, GRMZM2G066049, GRMZM2G165390 and GRMZM2G159587 were further validated involvement in phenolamides biosynthesis. Our results provide insights into the genetic basis of phenolamides biosynthesis in maize kernels, understanding phenolamides biosynthesis and its nutritional content and ability to withstand biotic and abiotic stress.

A widely targeted metabolite modificomics strategy for modified metabolites identification in tomato

The structural and functional diversity of plant metabolites is largely created via chemical modification of a basic backbone. However, metabolite modifications in plants have still not been thoroughly investigated by metabolomics approaches. In this study, a widely targeted metabolite modificomics (WTMM) strategy was developed based on ultra-high performance liquid chromatography-quadrupole-linear ion trap (UHPLC-Q-Trap) and UHPLC-Q-Exactive-Orbitrap (UHPLC-QE-Orbitrap), which greatly improved the detection sensitivity and the efficiency of identification of modified metabolites. A metabolite modificomics study was carried out using tomato as a model, and over 34,000 signals with MS2 information were obtained from approximately 232 neutral loss transitions. Unbiased metabolite profiling was also performed by utilizing high-resolution mass spectrometry data to annotate a total of 2,118 metabolites with 125 modification types; of these, 165 modified metabolites were identified in this study. Next, the WTMM database was used to assess diseased tomato tissues and 29 biomarkers were analyzed. In summary, the WTMM strategy is not only capable of large-scale detection and quantitative analysis of plant-modified metabolites in plants, but also can be used for plant biomarker development.

Depicting the genetic and metabolic panorama of chemical diversity in the tea plant

As a frequently consumed beverage worldwide, tea is rich in naturally important bioactive metabolites. Combining genetic, metabolomic and biochemical methodologies, here, we present a comprehensive study to dissect the chemical diversity in tea plant. A total of 2837 metabolites were identified at high-resolution with 1098 of them being structurally annotated and 63 of them were structurally identified. Metabolite-based genome-wide association mapping identified 6199 and 7823 metabolic quantitative trait loci (mQTL) for 971 and 1254 compounds in young leaves (YL) and the third leaves (TL), respectively. The major mQTL (i.e., P < 1.05 × 10-5, and phenotypic variation explained (PVE) > 25%) were further interrogated. Through extensive annotation of the tea metabolome as well as network-based analysis, this study broadens the understanding of tea metabolism and lays a solid foundation for revealing the natural variations in the chemical composition of the tea plant. Interestingly, we found that galloylations, rather than hydroxylations or glycosylations, were the largest class of conversions within the tea metabolome. The prevalence of galloylations in tea is unusual, as hydroxylations and glycosylations are typically the most prominent conversions of plant specialized metabolism. The biosynthetic pathway of flavonoids, which are one of the most featured metabolites in tea plant, was further refined with the identified metabolites. And we demonstrated the further mining and interpretation of our GWAS results by verifying two identified mQTL (including functional candidate genes CsUGTa, CsUGTb, and CsCCoAOMT) and completing the flavonoid biosynthetic pathway of the tea plant.

Chemical-tag-based semi-annotated metabolomics facilitates gene identification and specialized metabolic pathway elucidation in wheat

The importance of metabolite modification and species-specific metabolic pathways has long been recognized. However, linking the chemical structure of metabolites to gene function in order to explore the genetic and biochemical basis of metabolism has not yet been reported in wheat (Triticum aestivum). Here, we profiled metabolic fragment enrichment in wheat leaves and consequently applied chemical-tag-based semi-annotated metabolomics in a genome-wide association study in accessions of wheat. The studies revealed that all 1,483 quantified metabolites have at least one known functional group whose modification is tailored in an enzyme-catalyzed manner and eventually allows efficient candidate gene mining. A Triticeae crop-specific flavonoid pathway and its underlying metabolic gene cluster were elucidated in further functional studies. Additionally, upon overexpressing the major effect gene of the cluster TraesCS2B01G460000 (TaOMT24), the pathway was reconstructed in rice (Oryza sativa), which lacks this pathway. The reported workflow represents an efficient and unbiased approach for gene mining using forward genetics in hexaploid wheat. The resultant candidate gene list contains vast molecular resources for decoding the genetic architecture of complex traits and identifying valuable breeding targets and will ultimately aid in achieving wheat crop improvement.

Advancements and Prospects of Genome-Wide Association Studies (GWAS) in Maize

Genome-wide association studies (GWAS) have emerged as a powerful tool for unraveling intricate genotype-phenotype association across various species. Maize (Zea mays L.), renowned for its extensive genetic diversity and rapid linkage disequilibrium (LD), stands as an exemplary candidate for GWAS. In maize, GWAS has made significant advancements by pinpointing numerous genetic loci and potential genes associated with complex traits, including responses to both abiotic and biotic stress. These discoveries hold the promise of enhancing adaptability and yield through effective breeding strategies. Nevertheless, the impact of environmental stress on crop growth and yield is evident in various agronomic traits. Therefore, understanding the complex genetic basis of these traits becomes paramount. This review delves into current and future prospectives aimed at yield, quality, and environmental stress resilience in maize and also addresses the challenges encountered during genomic selection and molecular breeding, all facilitated by the utilization of GWAS. Furthermore, the integration of omics, including genomics, transcriptomics, proteomics, metabolomics, epigenomics, and phenomics has enriched our understanding of intricate traits in maize, thereby enhancing environmental stress tolerance and boosting maize production. Collectively, these insights not only advance our understanding of the genetic mechanism regulating complex traits but also propel the utilization of marker-assisted selection in maize molecular breeding programs, where GWAS plays a pivotal role. Therefore, GWAS provides robust support for delving into the genetic mechanism underlying complex traits in maize and enhancing breeding strategies.

Maize hydroxycinnamic acids: unveiling their role in stress resilience and human health

Maize production is pivotal in ensuring food security, particularly in developing countries. However, the crop encounters multiple challenges stemming from climatic changes that adversely affect its yield, including biotic and abiotic stresses during production and storage. A promising strategy for enhancing maize resilience to these challenges involves modulating its hydroxycinnamic acid amides (HCAAs) content. HCAAs are secondary metabolites present in plants that are essential in developmental processes, substantially contributing to defense mechanisms against environmental stressors, pests, and pathogens, and exhibiting beneficial effects on human health. This mini-review aims to provide a comprehensive overview of HCAAs in maize, including their biosynthesis, functions, distribution, and health potential applications.

Review on computer-assisted biosynthetic capacities elucidation to assess metabolic interactions and communication within microbial communities

Microbial communities thrive through interactions and communication, which are challenging to study as most microorganisms are not cultivable. To address this challenge, researchers focus on the extracellular space where communication events occur. Exometabolomics and interactome analysis provide insights into the molecules involved in communication and the dynamics of their interactions. Advances in sequencing technologies and computational methods enable the reconstruction of taxonomic and functional profiles of microbial communities using high-throughput multi-omics data. Network-based approaches, including community flux balance analysis, aim to model molecular interactions within and between communities. Despite these advances, challenges remain in computer-assisted biosynthetic capacities elucidation, requiring continued innovation and collaboration among diverse scientists. This review provides insights into the current state and future directions of computer-assisted biosynthetic capacities elucidation in studying microbial communities.

Common and specific genetic basis of metabolite-mediated drought responses in rice

Plants orchestrate drought responses at metabolic level but the genetic basis remains elusive in rice. In this study, 233 drought-responsive metabolites (DRMs) were quantified in a large rice population comprised of 510 diverse accessions at the reproductive stage. Large metabolic variations in drought responses were detected, and little correlation of metabolic levels between drought and normal conditions were observed. Interestingly, most of these DRMs could predict drought resistance in high accuracy. Genome-wide association study revealed 2522 significant association signals for 233 DRMs, and 98% (2471/2522) of the signals were co-localized with the association loci for drought-related phenotypic traits in the same population or the linkage-mapped QTLs for drought resistance in other populations. Totally, 10 candidate genes were efficiently identified for nine DRMs, seven of which harbored cis-eQTLs under drought condition. Based on comparative GWAS of common DRMs in rice and maize, representing irrigated and upland crops, we have identified three pairs of homologous genes associated with three DRMs between the two crops. Among the homologous genes, a transferase gene responsible for metabolic variation of N-feruloylputrescine was confirmed to confer enhanced drought resistance in rice. Our study provides not only genetic architecture of metabolic responses to drought stress in rice but also metabolic data resources to reveal the common and specific metabolite-mediated drought responses in different crops.

Genome-Wide Association Study for Maize Hybrid Performance in a Typical Breeder Population

Maize is one of the major crops that has demonstrated success in the utilization of heterosis. Developing high-yield hybrids is a crucial part of plant breeding to secure global food demand. In this study, we conducted a genome-wide association study (GWAS) for 10 agronomic traits using a typical breeder population comprised 442 single-cross hybrids by evaluating additive, dominance, and epistatic effects. A total of 49 significant single nucleotide polymorphisms (SNPs) and 69 significant pairs of epistasis were identified, explaining 26.2% to 64.3% of the phenotypic variation across the 10 traits. The enrichment of favorable genotypes is significantly correlated to the corresponding phenotype. In the confident region of the associated site, 532 protein-coding genes were discovered. Among these genes, the Zm00001d044211 candidate gene was found to negatively regulate starch synthesis and potentially impact yield. This typical breeding population provided a valuable resource for dissecting the genetic architecture of yield-related traits. We proposed a novel mating strategy to increase the GWAS efficiency without utilizing more resources. Finally, we analyzed the enrichment of favorable alleles in the Shaan A and Shaan B groups, as well as in each inbred line. Our breeding practice led to consistent results. Not only does this study demonstrate the feasibility of GWAS in F1 hybrid populations, it also provides a valuable basis for further molecular biology and breeding research.

Utilizing transcriptomics and metabolomics to unravel key genes and metabolites of maize seedlings in response to drought stress

BACKGROUND

Drought stress can substantially restrict maize growth and productivity, and global warming and an increasing frequency of extreme weather events are likely to result in more yield losses in the future. Therefore, unraveling the molecular mechanism underlying the response to drought stress is essential for breeding drought-resilient crops.

RESULTS

In this study, we subjected the 3-leaf-period plants of two maize inbred lines, a drought-tolerant line (si287) and a drought-sensitive line (X178), to drought stress for seven days while growing in a chamber. Subsequently, we measured physiological traits and analyzed transcriptomic and metabolic profiles of two inbred lines. Our KEGG analysis of genes and metabolites revealed significant differences in pathways related to glycolysis/gluconeogenesis, flavonoid biosynthesis, starch and sucrose metabolism, and biosynthesis of amino acids. Additionally, our joint analysis identified proline, tryptophan and phenylalanine are crucial amino acids for maize response to drought stress. Furthermore, we concentrated on tryptophan (Trp), which was found to enhance tolerance via IAA-ABA signaling, as well as SA and nicotinamide adenine dinucleotide (NAD) consequent reactive oxygen species (ROS) scavenging. We identified three hub genes in tryptophan biosynthesis, indole-3-acetaldehyde oxidase (ZmAO1, 542,228), catalase 1 (ZmCAT1, 542,369), and flavin-containing monooxygenase 6 (ZmYUC6, 103,629,142), High expression of these genes plays a significant role in regulating drought tolerance. Two metabolites related to tryptophan biosynthesis, quinolinic acid, and kynurenine improved maize tolerance to drought stress by scavenging reactive oxygen species.

CONCLUSIONS

This study illuminates the mechanisms underlying the response of maize seedlings to drought stress. Especially, it identifies novel candidate genes and metabolites, enriching our understanding of the role of tryptophan in drought stress. The identification of distinct resistance mechanisms in maize inbred lines will facilitate the exploration of maize germplasm and the breeding of drought-resilient hybrids.

PMhub 1.0: a comprehensive plant metabolome database

The Plant Metabolome Hub (PMhub), available at https://pmhub.org.cn, is a valuable resource designed to provide scientists with comprehensive information on plant metabolites. It offers extensive details about their reference spectra, genetic foundations, chemical reactions, metabolic pathways and biological functions. The PMhub contains chemical data for 188 837 plant metabolites gathered from various sources, with 1 467 041 standard/in-silico high-resolution tandem mass-spectrometry (HRMS/MS) spectra corresponding to these metabolites. Beyond its extensive literature-derived data, PMhub also boasts a sizable collection of experimental metabolites; it contains 144 366 detected features in 10 typical plant species, with 16 423 successfully annotated by using standard/in-silico HRMS/MS data, this collection is further supplemented with thousands of features gathered from reference metabolites. For each metabolite, the PMhub enables the reconstructed of a simulated network based on structural similarities and existing metabolic pathways. Unlike previous plant-specific metabolome databases, PMhub not only contains a vast amount of metabolic data but also assembles the corresponding genomic and/or transcriptomic information, incorporating multiple methods for the comprehensive genetic analysis of metabolites. To validate the practicality, we verified a synthetic pathway for N-p-coumaroyltyramine by in vitro enzymatic activity experiments. In summary, the robust functionality provided by the PMhub will make it an indispensable tool for studying plant metabolomics.

RefMetaPlant: a reference metabolome database for plants across five major phyla

Plants are unique with tremendous chemical diversity and metabolic complexity, which is highlighted by estimates that green plants collectively produce metabolites numbering in the millions. Plant metabolites play crucial roles in all aspects of plant biology, like growth, development, stress responses, etc. However, the lack of a reference metabolome for plants, and paucity of high-quality standard compound spectral libraries and related analytical tools, have hindered the discovery and functional study of phytochemicals in plants. Here, by leveraging an advanced LC-MS platform, we generated untargeted mass spectral data from >150 plant species collected across the five major phyla. Using a self-developed computation protocol, we constructed reference metabolome for 153 plant species. A 'Reference Metabolome Database for Plants' (RefMetaPlant) was built to encompass the reference metabolome, integrated standard compound mass spectral libraries for annotation, and related query and analytical tools like 'LC-MS/MS Query', 'RefMetaBlast' and 'CompoundLibBlast' for searches and profiling of plant metabolome and metabolite identification. Analogous to a reference genome in genomic research, RefMetaPlant provides a powerful platform to support plant genome-scale metabolite analysis to promote knowledge/data sharing and collaboration in the field of metabolomics. RefMetaPlant is freely available at https://www.biosino.org/RefMetaDB/.

A metabolomics study in citrus provides insight into bioactive phenylpropanoid metabolism

Citrus fruits are widely consumed worldwide in juices or as fresh and provide a broad range of phytonutrients that are important for human health. Here, a citrus multi-omics resource is presented: comprehensive metabolic profiling of various citrus species was performed and metabolic profiles were compared among species, with a focus on the phenylpropanoid metabolic pathway. A metabolite-based genome-wide association analysis (mGWAS) of 154 pummelo accessions was performed using factored spectrally transformed linear mixed models (FaST-LMM) and efficient mixed-model association eXpedited (EMMAX), and the genetic and biochemical basis of metabolomic variation was comprehensively analysed. A metabolite-single nucleotide polymorphism-gene (metabolite-SNP-gene) interaction network was constructed for pummelo, and many candidate loci controlling the synthesis and regulation of bioactive compounds were identified; among these loci, three BAHD malonyltransferases were involved in the malonylation of flavonoid glycosides. Further investigation revealed that an R2R3-MYB transcription factor CgMYB1 positively controls the metabolism of phenylpropanoid molecules, particularly the flavonoid derivatives. This study provides valuable data resources on the metabolic regulatory networks of bioactive components in citrus, in addition to demonstrating an efficient method for metabolic pathway dissection and providing targets for future breeding work with the aim of improving nutritional value.

Integrated Transcriptomic and Metabolomic Analyses Identify Critical Genes and Metabolites Associated with Seed Vigor of Common Wheat

Seed aging is a common physiological phenomenon during storage which has a great impact on seed quality. An in-depth analysis of the physiological and molecular mechanisms of wheat seed aging is of great significance for cultivating high-vigor wheat varieties. This study reveals the physiological mechanisms of wheat seed aging in two cultivars differing in seed vigor, combining metabolome and transcriptome analyses. Differences between cultivars were examined based on metabolomic differential analysis. Artificial aging had a significant impact on the metabolism of wheat seeds. A total of 7470 (3641 upregulated and 3829 downregulated) DEGs were detected between non-aging HT and LT seeds; however, 10,648 (4506 up and 6142 down) were detected between the two cultivars after aging treatment. Eleven, eight, and four key metabolic-related gene families were identified in the glycolysis/gluconeogenesis and TCA cycle pathways, starch and sucrose metabolism pathways, and galactose metabolism pathways, respectively. In addition, 111 up-regulated transcription factor genes and 85 down-regulated transcription factor genes were identified in the LT 48h group. A total of 548 metabolites were detected across all samples. Cultivar comparisons between the non-aged groups and aged groups revealed 46 (30 upregulated and 16 downregulated) and 62 (38 upregulated and 24 downregulated) DIMs, respectively. Network analysis of the metabolites indicated that glucarate O-phosphoric acid, L-methionine sulfoxide, isocitric acid, and Gln-Gly might be the most crucial DIMs between HT and LT. The main related metabolites were enriched in pathways such as glyoxylate and dicarboxylate metabolism, biosynthesis of secondary metabolites, fatty acid degradation, etc. However, metabolites that exhibited differences between cultivars were mainly enriched in carbon metabolism, the TCA cycle, etc. Through combined metabolome and transcriptome analyses, it was found that artificial aging significantly affected glycolysis/gluconeogenesis, pyruvate metabolism, and glyoxylate and dicarboxylate metabolism, which involved key genes such as ACS, F16P2, and PPDK1. We thus speculate that these genes may be crucial in regulating physiological changes in seeds during artificial aging. In addition, an analysis of cultivar differences identified pathways related to amino acid and polypeptide metabolism, such as cysteine and methionine metabolism, glutathione metabolism, and amino sugar and nucleotide sugar metabolism, involving key genes such as BCAT3, CHI1, GAUT1, and GAUT4, which may play pivotal roles in vigor differences between cultivars.

Analysis of the Genetic Diversity in Tea Plant Germplasm in Fujian Province Based on Restriction Site-Associated DNA Sequencing

Fujian province, an important tea-producing area in China, has abundant tea cultivars. To investigate the genetic relationships of tea plant cultivars in Fujian province and the characteristics of the tea plant varieties, a total of 70 tea cultivars from Fujian and other 12 provinces in China were subjected to restriction site-associated DNA sequencing (RAD-seq). A total of 60,258,975 single nucleotide polymorphism (SNP) sites were obtained. These 70 tea plant cultivars were divided into three groups based on analyzing the phylogenetic tree, principal component, and population structure. Selection pressure analysis indicated that nucleotide diversity was high in Southern China and genetically distinct from cultivars of Fujian tea plant cultivars, according to selection pressure analysis. The selected genes have significant enrichment in pathways associated with metabolism, photosynthesis, and respiration. There were ten characteristic volatiles screened by gas chromatography-mass spectrometry (GC-MS) coupled with multivariate statistical methods, among which the differences in the contents of methyl salicylate, 3-carene, cis-3-hexen-1-ol, (E)-4-hexen-1-ol, and 3-methylbutyraldehyde can be used as reference indicators of the geographical distribution of tea plants. Furthermore, a metabolome genome-wide association study (mGWAS) revealed that 438 candidate genes were related to the aroma metabolic pathway. Further analysis showed that 31 genes of all the selected genes were screened and revealed the reasons for the genetic differences in aroma among tea plant cultivars in Fujian and Southern China. These results reveal the genetic diversity in the Fujian tea plants as well as a theoretical basis for the conservation, development, and utilization of the Fujian highly aromatic tea plant cultivars.

Elucidation of the melitidin biosynthesis pathway in pummelo

Specialized plant metabolism is a rich resource of compounds for drug discovery. The acylated flavonoid glycoside melitidin is being developed as an anti-cholesterol statin drug candidate, but its biosynthetic route in plants has not yet been fully characterized. Here, we describe the gene discovery and functional characterization of a new flavonoid gene cluster (UDP-glucuronosyltransferases (CgUGTs), 1,2 rhamnosyltransferase (Cg1,2RhaT), acyltransferases (CgATs)) that is responsible for melitidin biosynthesis in pummelo (Citrus grandis (L.) Osbeck). Population variation analysis indicated that the tailoring of acyltransferases, specific for bitter substrates, mainly determine the natural abundance of melitidin. Moreover, 3-hydroxy-3-methylglutaryl-CoA reductase enzyme inhibition assays showed that the product from this metabolic gene cluster, melitidin, may be an effective anti-cholesterol statin drug candidate. Co-expression of these clustered genes in Nicotiana benthamiana resulted in the formation of melitidin, demonstrating the potential for metabolic engineering of melitidin in a heterologous plant system. This study establishes a biosynthetic pathway for melitidin, which provides genetic resources for the breeding and genetic improvement of pummelo aimed at fortifying the content of biologically active metabolites.

A comprehensive metabolomics and lipidomics atlas for the legumes common bean, chickpea, lentil and lupin

Legumes represent an important component of human and livestock diets; they are rich in macro- and micronutrients such as proteins, dietary fibers and polyunsaturated fatty acids. Whilst several health-promoting and anti-nutritional properties have been associated with grain content, in-depth metabolomics characterization of major legume species remains elusive. In this article, we used both gas chromatography-mass spectrometry (GC-MS) and liquid chromatography-mass spectrometry (LC-MS) to assess the metabolic diversity in the five legume species commonly grown in Europe, including common bean (Phaseolus vulgaris), chickpea (Cicer arietinum), lentil (Lens culinaris), white lupin (Lupinus albus) and pearl lupin (Lupinus mutabilis), at the tissue level. We were able to detect and quantify over 3400 metabolites covering major nutritional and anti-nutritional compounds. Specifically, the metabolomics atlas includes 224 derivatized metabolites, 2283 specialized metabolites and 923 lipids. The data generated here will serve the community as a basis for future integration to metabolomics-assisted crop breeding and facilitate metabolite-based genome-wide association studies to dissect the genetic and biochemical bases of metabolism in legume species.

Association mapping in bambara groundnut [Vigna subterranea (L.) Verdc.] reveals loci associated with agro-morphological traits

BACKGROUND

Genome-wide association studies (GWAS) are important for the acceleration of crop improvement through knowledge of marker-trait association (MTA). This report used DArT SNP markers to successfully perform GWAS on agro-morphological traits using 270 bambara groundnut [Vigna subterranea (L.) Verdc.] landraces sourced from diverse origins. The study aimed to identify marker traits association for nine agronomic traits using GWAS and their candidate genes. The experiment was conducted at two different locations laid out in alpha lattice design. The cowpea [Vigna unguiculata (L.) Walp.] reference genome (i.e. legume genome most closely related to bambara groundnut) assisted in the identification of candidate genes.

RESULTS

The analyses showed that linkage disequilibrium was found to decay rapidly with an average genetic distance of 148 kb. The broadsense heritability was relatively high and ranged from 48.39% (terminal leaf length) to 79.39% (number of pods per plant). The GWAS identified a total of 27 significant marker-trait associations (MTAs) for the nine studied traits explaining 5.27% to 24.86% of phenotypic variations. Among studied traits, the highest number of MTAs was obtained from seed coat colour (6) followed by days to flowering (5), while the least is days to maturity (1), explaining 5.76% to 11.03%, 14.5% to 19.49%, and 11.66% phenotypic variations, respectively. Also, a total of 17 candidate genes were identified, varying in number for different traits; seed coat colour (6), days to flowering (3), terminal leaf length (2), terminal leaf width (2), number of seed per pod (2), pod width (1) and days to maturity (1).

CONCLUSION

These results revealed the prospect of GWAS in identification of SNP variations associated with agronomic traits in bambara groundnut. Also, its present new opportunity to explore GWAS and marker assisted strategies in breeding of bambara groundnut for acceleration of the crop improvement.

Hybrid performance evaluation and genome-wide association analysis of root system architecture in a maize association population

KEY MESSAGE

The genetic architecture of RSA traits was dissected by GWAS and coexpression networks analysis in a maize association population. Root system architecture (RSA) is a crucial determinant of water and nutrient uptake efficiency in crops. However, the maize genetic architecture of RSA is still poorly understood due to the challenges in quantifying root traits and the lack of dense molecular markers. Here, an association mapping panel including 356 inbred lines were crossed with a common tester, Zheng58, and the test crosses were phenotyped for 12 RSA traits in three locations. We observed a 1.3 ~ sixfold phenotypic variation for measured RSA in the association panel. The association panel consisted of four subpopulations, non-stiff stalk (NSS) lines, stiff stalk (SS), tropical/subtropical (TST), and mixed. Zheng58 × TST has a 2.1% higher crown root number (CRN) and 8.6% less brace root number (BRN) than Zheng58 × NSS and Zheng58 × SS, respectively. Using a genome-wide association study (GWAS) with 1.25 million SNPs and correction for population structure, 191 significant SNPs were identified for root traits. Ninety (47%) of the significant SNPs showed positive allelic effects, and 101 (53%) showed negative effects. Each locus could explain 0.39% to 11.8% of phenotypic variation. By integrating GWAS results and comparing coexpression networks, 26 high-priority candidate genes were identified. Gene GRMZM2G377215, which belongs to the COBRA-like gene family, affected root growth and development. Gene GRMZM2G468657 encodes the aspartic proteinase nepenthesin-1, related to root development and N-deficient response. Collectively, our research provides progress in the genetic dissection of root system architecture. These findings present the further possibility for the genetic improvement of root traits in maize.

Plant biochemical genetics in the multiomics era

Our understanding of plant biology has been revolutionized by modern genetics and biochemistry. However, biochemical genetics can be traced back to the foundation of Mendelian genetics; indeed, one of Mendel's milestone discoveries of seven characteristics of pea plants later came to be ascribed to a mutation in a starch branching enzyme. Here, we review both current and historical strategies for the elucidation of plant metabolic pathways and the genes that encode their component enzymes and regulators. We use this historical review to discuss a range of classical genetic phenomena including epistasis, canalization, and heterosis as viewed through the lens of contemporary high-throughput data obtained via the array of approaches currently adopted in multiomics studies.

Population analysis reveals the roles of DNA methylation in tomato domestication and metabolic diversity

DNA methylation is an important epigenetic marker, yet its diversity and consequences in tomato breeding at the population level are largely unknown. We performed whole-genome bisulfite sequencing (WGBS), RNA sequencing, and metabolic profiling on a population comprising wild tomatoes, landraces, and cultivars. A total of 8,375 differentially methylated regions (DMRs) were identified, with methylation levels progressively decreasing from domestication to improvement. We found that over 20% of DMRs overlapped with selective sweeps. Moreover, more than 80% of DMRs in tomato were not significantly associated with single-nucleotide polymorphisms (SNPs), and DMRs had strong linkages with adjacent SNPs. We additionally profiled 339 metabolites from 364 diverse accessions and further performed a metabolic association study based on SNPs and DMRs. We detected 971 and 711 large-effect loci via SNP and DMR markers, respectively. Combined with multi-omics, we identified 13 candidate genes and updated the polyphenol biosynthetic pathway. Our results showed that DNA methylation variants could complement SNP profiling of metabolite diversity. Our study thus provides a DNA methylome map across diverse accessions and suggests that DNA methylation variation can be the genetic basis of metabolic diversity in plants.

QT-GWAS: A novel method for unveiling biosynthetic loci affecting qualitative metabolic traits

Although the plant kingdom provides an enormous diversity of metabolites with potentially beneficial applications for humankind, a large fraction of these metabolites and their biosynthetic pathways remain unknown. Resolving metabolite structures and their biosynthetic pathways is key to gaining biological understanding and to allow metabolic engineering. In order to retrieve novel biosynthetic genes involved in specialized metabolism, we developed a novel untargeted method designated as qualitative trait GWAS (QT-GWAS) that subjects qualitative metabolic traits to a genome-wide association study, while the conventional metabolite GWAS (mGWAS) mainly considers the quantitative variation of metabolites. As a proof of the validity of QT-GWAS, 23 and 15 of the retrieved associations identified in Arabidopsis thaliana by QT-GWAS and mGWAS, respectively, were supported by previous research. Furthermore, seven gene-metabolite associations retrieved by QT-GWAS were confirmed in this study through reverse genetics combined with metabolomics and/or in vitro enzyme assays. As such, we established that CYTOCHROME P450 706A5 (CYP706A5) is involved in the biosynthesis of chroman derivatives, UDP-GLYCOSYLTRANSFERASE 76C3 (UGT76C3) is able to hexosylate guanine in vitro and in planta, and SULFOTRANSFERASE 202B1 (SULT202B1) catalyzes the sulfation of neolignans in vitro. Collectively, our study demonstrates that the untargeted QT-GWAS method can retrieve valid gene-metabolite associations at the level of enzyme-encoding genes, even new associations that cannot be found by the conventional mGWAS, providing a new approach for dissecting qualitative metabolic traits.

Characterization of novel loci controlling seed oil content in Brassica napus by marker metabolite-based multi-omics analysis

BACKGROUND

Seed oil content is an important agronomic trait of Brassica napus (B. napus), and metabolites are considered as the bridge between genotype and phenotype for physical traits.

RESULTS

Using a widely targeted metabolomics analysis in a natural population of 388 B. napus inbred lines, we quantify 2172 metabolites in mature seeds by liquid chromatography mass spectrometry, in which 131 marker metabolites are identified to be correlated with seed oil content. These metabolites are then selected for further metabolite genome-wide association study and metabolite transcriptome-wide association study. Combined with weighted correlation network analysis, we construct a triple relationship network, which includes 21,000 edges and 4384 nodes among metabolites, metabolite quantitative trait loci, genes, and co-expression modules. We validate the function of BnaA03.TT4, BnaC02.TT4, and BnaC05.UK, three candidate genes predicted by multi-omics analysis, which show significant impacts on seed oil content through regulating flavonoid metabolism in B. napus.

CONCLUSIONS

This study demonstrates the advantage of utilizing marker metabolites integrated with multi-omics analysis to dissect the genetic basis of agronomic traits in crops.

Metabolome-Based Genome-Wide Association Study of Duck Meat Leads to Novel Genetic and Biochemical Insights

Meat is among the most consumed foods worldwide and has a unique flavor and high nutrient density in the human diet. However, the genetic and biochemical bases of meat nutrition and flavor are poorly understood. Here, 3431 metabolites and 702 volatiles in 423 skeletal muscle samples are profiled from a gradient consanguinity segregating population generated by Pekin duck × Liancheng duck crosses using metabolomic approaches. The authors identified 2862 metabolome-based genome-wide association studies (mGWAS) signals and 48 candidate genes potentially modulating metabolite and volatile levels, 79.2% of which are regulated by cis-regulatory elements. The level of plasmalogen is significantly associated with TMEM189 encoding plasmanylethanolamine desaturase 1. The levels of 2-pyrrolidone and glycerophospholipids are regulated by the gene expression of AOX1 and ACBD5, which further affects the levels of volatiles, 2-pyrrolidone and decanal, respectively. Genetic variations in GADL1 and CARNMT2 determine the levels of 49 metabolites including L-carnosine and anserine. This study provides novel insights into the genetic and biochemical basis of skeletal muscle metabolism and constitutes a valuable resource for the precise improvement of meat nutrition and flavor.

Hello darkness, my old friend: 3-KETOACYL-COENZYME A SYNTHASE4 is a branch point in the regulation of triacylglycerol synthesis in Arabidopsis thaliana

Plant lipids are important as alternative sources of carbon and energy when sugars or starch are limited. Here, we applied combined heat and darkness or extended darkness to a panel of ∼300 Arabidopsis (Arabidopsis thaliana) accessions to study lipid remodeling under carbon starvation. Natural allelic variation at 3-KETOACYL-COENZYME A SYNTHASE4 (KCS4), a gene encoding an enzyme involved in very long chain fatty acid (VLCFA) synthesis, underlies the differential accumulation of polyunsaturated triacylglycerols (puTAGs) under stress. Ectopic expression of KCS4 in yeast and plants proved that KCS4 is a functional enzyme localized in the endoplasmic reticulum with specificity for C22 and C24 saturated acyl-CoA. Allelic mutants and transient overexpression in planta revealed the differential role of KCS4 alleles in VLCFA synthesis and leaf wax coverage, puTAG accumulation, and biomass. Moreover, the region harboring KCS4 is under high selective pressure and allelic variation at KCS4 correlates with environmental parameters from the locales of Arabidopsis accessions. Our results provide evidence that KCS4 plays a decisive role in the subsequent fate of fatty acids released from chloroplast membrane lipids under carbon starvation. This work sheds light on both plant response mechanisms and the evolutionary events shaping the lipidome under carbon starvation.

The Key Metabolic Network and Genes Regulating the Fresh Fruit Texture of Jujube (Ziziphus jujuba Mill.) Revealed via Metabolomic and Transcriptomic Analysis

The texture of fresh jujube fruit is related to its popularity and commercial value. The metabolic networks and essential genes that regulate the texture of jujube (Ziziphus jujuba) fruit are still unknown. In this study, two jujube cultivars with significantly different textures were selected by a texture analyzer. The four developmental stages of the exocarp and mesocarp of jujube fruit were studied separately using metabolomic and transcriptomic analyses. Differentially accumulated metabolites were enriched in several critical pathways related to cell wall substance synthesis and metabolism. Transcriptome analysis confirmed this by finding enriched differential expression genes in these pathways. Combined analysis showed that 'Galactose metabolism' was the most overlapping pathway in two omics. Genes such as β-Gal, MYB and DOF may affect fruit texture by regulating cell wall substances. Overall, this study provides an essential reference for the establishment of texture-related metabolic and gene networks of jujube fruit.

Limitations and advantages of using metabolite-based genome-wide association studies: focus on fruit quality traits

In the last decades, linkage mapping has help in the location of metabolite quantitative trait loci (QTL) in many species; however, this approach shows some limitations. Recently, thanks to the most recent advanced in high-throughput genotyping technologies like next-generation sequencing, metabolite genome-wide association study (mGWAS) has been proposed a powerful tool to identify the genetic variants in polygenic agrinomic traits. Fruit flavor is a complex interaction of aroma volatiles and taste being sugar and acid ratio key parameter for flavor acceptance. Here, we review recent progress of mGWAS in pinpoint gene polymorphisms related to flavor-related metabolites in fruits. Despite clear successes in discovering novel genes or regions associated with metabolite accumulation affecting sensory attributes in fruits, GWAS incurs in several limitations summarized in this review. In addition, in our own work, we performed mGWAS on 194 Citrus grandis accessions to investigate the genetic control of individual primary and lipid metabolites in ripe fruit. We have identified a total of 667 associations for 14 primary metabolites including amino acids, sugars, and organic acids, and 768 associations corresponding to 47 lipids. Furthermore, candidate genes related to important metabolites related to fruit quality such as sugars, organic acids and lipids were discovered.

Widely untargeted metabolomic profiling unearths metabolites and pathways involved in leaf senescence and N remobilization in spring-cultivated wheat under different N regimes

Progression of leaf senescence consists of both degenerative and nutrient recycling processes in crops including wheat. However, the levels of metabolites in flag leaves in spring-cultivated wheat, as well as biosynthetic pathways involved under different nitrogen fertilization regimes, are largely unknown. Therefore, the present study employed a widely untargeted metabolomic profiling strategy to identify metabolites and biosynthetic pathways that could be used in a wheat improvement program aimed at manipulating the rate and onset of senescence by handling spring wheat (Dingxi 38) flag leaves sampled from no-, low-, and high-nitrogen (N) conditions (designated Groups 1, 2, and 3, respectively) across three sampling times: anthesis, grain filling, and end grain filling stages. Through ultrahigh-performance liquid chromatography-tandem mass spectrometry, a total of 826 metabolites comprising 107 flavonoids, 51 phenol lipids, 37 fatty acyls, 37 organooxygen compounds, 31 steroids and steroid derivatives, 18 phenols, and several unknown compounds were detected. Upon the application of the stringent screening criteria for differentially accumulated metabolites (DAMs), 28 and 23 metabolites were differentially accumulated in Group 1_vs_Group 2 and Group 1_vs_Group 3, respectively. From these, 1-O-Caffeoylglucose, Rhoifolin, Eurycomalactone;Ingenol, 4-Methoxyphenyl beta-D-glucopyranoside, and Baldrinal were detected as core conserved DAMs among the three groups with all accumulated higher in Group 1 than in the other two groups. Kyoto Encyclopedia of Genes and Genomes pathway analysis revealed that tropane, piperidine, and pyridine alkaloid biosynthesis; acarbose and validamycin biosynthesis; lysine degradation; and biosynthesis of alkaloids derived from ornithine, lysine, and nicotinic acid pathways were the most significantly (p < 0.05) enriched in Group 1_vs_Group 2, while flavone and flavonol as well as anthocyanins biosynthetic pathways were the most significantly (p < 0.05) enriched in Group 1_vs_Group 3. The results from this study provide a foundation for the manipulation of the onset and rate of leaf senescence and N remobilization in wheat.

Mapping of QTLs for morphophysiological and yield traits under water-deficit stress and well-watered conditions in maize

Maize productivity is significantly impacted by drought; therefore, improvement of drought tolerance is a critical goal in maize breeding. To achieve this, a better understanding of the genetic basis of drought tolerance is necessary. Our study aimed to identify genomic regions associated with drought tolerance-related traits by phenotyping a mapping population of recombinant inbred lines (RILs) for two seasons under well-watered (WW) and water-deficit (WD) conditions. We also used single nucleotide polymorphism (SNP) genotyping through genotyping-by-sequencing to map these regions and attempted to identify candidate genes responsible for the observed phenotypic variation. Phenotyping of the RILs population revealed significant variability in most of the traits, with normal frequency distributions, indicating their polygenic nature. We generated a linkage map using 1,241 polymorphic SNPs distributed over 10 chromosomes (chrs), covering a total genetic distance of 5,471.55 cM. We identified 27 quantitative trait loci (QTLs) associated with various morphophysiological and yield-related traits, with 13 QTLs identified under WW conditions and 12 under WD conditions. We found one common major QTL (qCW2-1) for cob weight and a minor QTL (qCH1-1) for cob height that were consistently identified under both water regimes. We also detected one major and one minor QTL for the Normalized Difference Vegetation Index (NDVI) trait under WD conditions on chr 2, bin 2.10. Furthermore, we identified one major QTL (qCH1-2) and one minor QTL (qCH1-1) on chr 1 that were located at different genomic positions to those identified in earlier studies. We found co-localized QTLs for stomatal conductance and grain yield on chr 6 (qg_s6-2 and qGY6-1), while co-localized QTLs for stomatal conductance and transpiration rate were identified on chr 7 (qg_s7-1 and qTR7-1). We also attempted to identify the candidate genes responsible for the observed phenotypic variation; our analysis revealed that the major candidate genes associated with QTLs detected under water deficit conditions were related to growth and development, senescence, abscisic acid (ABA) signaling, signal transduction, and transporter activity in stress tolerance. The QTL regions identified in this study may be useful in designing markers that can be utilized in marker-assisted selection breeding. In addition, the putative candidate genes can be isolated and functionally characterized so that their role in imparting drought tolerance can be more fully understood.

Genetic architecture of inter-specific and -generic grass hybrids by network analysis on multi-omics data

BACKGROUND

Understanding the mechanisms underlining forage production and its biomass nutritive quality at the omics level is crucial for boosting the output of high-quality dry matter per unit of land. Despite the advent of multiple omics integration for the study of biological systems in major crops, investigations on forage species are still scarce.

RESULTS

Our results identified substantial changes in gene co-expression and metabolite-metabolite network topologies as a result of genetic perturbation by hybridizing L. perenne with another species within the genus (L. multiflorum) relative to across genera (F. pratensis). However, conserved hub genes and hub metabolomic features were detected between pedigree classes, some of which were highly heritable and displayed one or more significant edges with agronomic traits in a weighted omics-phenotype network. In spite of tagging relevant biological molecules as, for example, the light-induced rice 1 (LIR1), hub features were not necessarily better explanatory variables for omics-assisted prediction than features stochastically sampled and all available regressors.

CONCLUSIONS

The utilization of computational techniques for the reconstruction of co-expression networks facilitates the identification of key omic features that serve as central nodes and demonstrate correlation with the manifestation of observed traits. Our results also indicate a robust association between early multi-omic traits measured in a greenhouse setting and phenotypic traits evaluated under field conditions.

Genetic architecture of seed glycerolipids in Asian cultivated rice

Glycerolipids are essential for rice development and grain quality but its genetic regulation remains unknown. Here we report its genetic base using metabolite-based genome-wide association study and metabolite-based quantitative traits locus (QTL) analyses based on lipidomic profiles of seeds from 587 Asian cultivated rice accessions and 103 chromosomal segment substitution lines, respectively. We found that two genes encoding phosphatidylcholine (PC):diacylglycerol cholinephosphotransferase (OsLP1) and granule-bound starch synthase I (Waxy) contribute to variations in saturated triacylglycerol (TAG) and lyso-PC contents, respectively. We demonstrated that allelic variation in OsLP1 sequence between indica and japonica results in different enzymatic preference for substrate PC-16:0/16:0 and different saturated TAG levels. Further evidence demonstrated that OsLP1 also affects heading date, and that co-selection of OsLP1 and a flooding-tolerant QTL in Aus results in the abundance of saturated TAGs associated with flooding tolerance. Moreover, we revealed that the sequence polymorphisms in Waxy has pleiotropic effects on lyso-PC and amylose content. We proposed that rice seed glycerolipids have been unintentionally shaped during natural and artificial selection for adaptive or import seed quality traits. Collectively, our findings provide valuable genetic resources for rice improvement and evolutionary insights into seed glycerolipid variations in rice.

A role for heritable transcriptomic variation in maize adaptation to temperate environments

Background

Transcription bridges genetic information and phenotypes. Here, we evaluated how changes in transcriptional regulation enable maize (Zea mays), a crop originally domesticated in the tropics, to adapt to temperate environments.

Result

We generated 572 unique RNA-seq datasets from the roots of 340 maize genotypes. Genes involved in core processes such as cell division, chromosome organization and cytoskeleton organization showed lower heritability of gene expression, while genes involved in anti-oxidation activity exhibited higher expression heritability. An expression genome-wide association study (eGWAS) identified 19,602 expression quantitative trait loci (eQTLs) associated with the expression of 11,444 genes. A GWAS for alternative splicing identified 49,897 splicing QTLs (sQTLs) for 7614 genes. Genes harboring both cis-eQTLs and cis-sQTLs in linkage disequilibrium were disproportionately likely to encode transcription factors or were annotated as responding to one or more stresses. Independent component analysis of gene expression data identified loci regulating co-expression modules involved in oxidation reduction, response to water deprivation, plastid biogenesis, protein biogenesis, and plant-pathogen interaction. Several genes involved in cell proliferation, flower development, DNA replication, and gene silencing showed lower gene expression variation explained by genetic factors between temperate and tropical maize lines. A GWAS of 27 previously published phenotypes identified several candidate genes overlapping with genomic intervals showing signatures of selection during adaptation to temperate environments.

Conclusion

Our results illustrate how maize transcriptional regulatory networks enable changes in transcriptional regulation to adapt to temperate regions.

Supplementary information

The online version contains supplementary material available at 10.1186/s13059-023-02891-3.

Genome-wide association study for the extractable phenolic profile and coat color of common bean seeds (Phaseolus vulgaris L.)

BACKGROUND

A large variation in seed coat colors and seed phenolic metabolites is present in common bean (Phaseolus vulgaris L.). The study of the relationships between seed coat color phenotype and the phenolic profile is an important step in the elucidation of the gene network involved in the phenylpropanoid biosynthetic pathway. However, this relationship is still poorly understood in this species.

RESULTS

A genome-wide association study (GWAS) was used to investigate the genomic regions associated with the synthesis of 10 flavonoids (5 anthocyanins and 5 flavonols) and with 10 seed coat color traits using a set of 308 common bean lines of the Spanish Diversity Panel (SDP) which have been genotyped with 11,763 SNP markers.. A total of 31 significant SNP-trait associations (QTNs) were identified, grouped in 20 chromosome regions: 6 for phenolic metabolites on chromosomes Pv01, Pv02, Pv04, Pv08, and Pv09, 13 for seed coat color on chromosomes Pv01, Pv02, Pv06, Pv07, and Pv10, and 1 including both types of traits located on chromosome Pv08. In all, 58 candidate genes underlying these regions have been proposed, 31 of them previously described in the phenylpropanoid pathway in common bean, and 27 of them newly proposed in this work based on the association study and their homology with Arabidopsis anthocyanin genes.

CONCLUSIONS

Chromosome Pv08 was identified as the main chromosome involved in the phenylpropanoid pathway and in consequence in the common bean seed pigmentation, with three independent chromosome regions identified, Phe/C_Pv08(2.7) (expanding from 2.71 to 4.04 Mbp), C_Pv08(5.8) (5.89-6.59 Mbp), and Phe_Pv08(62.5) (62.58 to 63.28 Mbp). Candidate genes previously proposed by other authors for the color genes V and P were validated in this GWAS. Candidate genes have been tentatively proposed from this study for color genes B and Rk on Pv02, Asp on Pv07, and complex C on Pv08. These results help to clarify the complex network of genes involved in the genetic control of phenolic compounds and seed color in common bean and provide the opportunity for future validation studies.

Visualization and metabolome for the migration and distribution behavior of pesticides residue in after-ripening of banana

Exploring the behavior of pesticide residues in fruits is important for effectively applying pesticides and minimizing the risk of pesticide exposure to humans. However, most studies do not consider in situ visual analysis of residues and migration patterns in fresh fruit samples. We investigated the migration patterns of thiram, propamocarb, imidacloprid and pyraclostrobin in fresh bananas based on ambient mass spectrometry imaging, metabolome and transcriptome analysis. The systemic pesticides entered via lateral penetration and vertical migration over time, which began to internally migrate to the inner core after 6 h. The non-systemic pesticide thiram did not enter the interior of the bananas, and remained only in the peel. The transportation rate of the pesticides increased with the decrease of water-octanol partition coefficient and the relative molecular mass. Moreover, the pesticide migrated fast with the increase of banana ripeness. The pesticides significantly enhanced pyruvate kinase, NADP-dependent malic enzyme, and malate synthase activities in the banana peels through carbohydrate metabolism. The banana pulp was also protected against the external toxicity of pesticides by the ascorbate-glutathione cycle. These results can provide guidelines for the appropriate application of pesticides and their safety evaluation.

Genome-wide association study identifies a gene conferring high physiological phosphorus use efficiency in rice

Phosphate (Pi) is indispensable for the growth and development of plant, and low-Pi stress is a major limitation for crop growth and yield worldwide. The tolerance to low-Pi stress varied among rice germplasm resources. However, the mechanisms underlying the tolerance of rice to low-Pi stress, as a complex quantitative trait, are not clear. We performed a genome-wide association study (GWAS) through a diverse worldwide collection of 191 rice accessions in the field under normal-Pi and low-Pi supply in two years. Twenty and three significant association loci were identified for biomass and grain yield per plant under low-Pi supply respectively. The expression level of OsAAD as a candidate gene from a associated locus was significantly up-regulated after low-Pi stress treatment for five days and tended to return to normal levels after Pi re-supply in shoots. Suppression of OsAAD expression could improve the physiological phosphorus use efficiency (PPUE) and grain yields through affecting the expression of several genes associated with GA biosynthesis and metabolism. OsAAD would be a promising gene for increasing PPUE and grain yield in rice under normal- and low-Pi supply via genome editing.

Watermelon domestication was shaped by stepwise selection and regulation of the metabolome

Although crop domestication has greatly aided human civilization, the sequential domestication and regulation of most quality traits remain poorly understood. Here, we report the stepwise selection and regulation of major fruit quality traits that occurred during watermelon evolution. The levels of fruit cucurbitacins and flavonoids were negatively selected during speciation, whereas sugar and carotenoid contents were positively selected during domestication. Interestingly, fruit malic acid and citric acid showed the opposite selection trends during the improvement. We identified a novel gene cluster (CGC1, cucurbitacin gene cluster on chromosome 1) containing both regulatory and structural genes involved in cucurbitacin biosynthesis, which revealed a cascade of transcriptional regulation operating mechanisms. In the CGC1, an allele caused a single nucleotide change in ClERF1 binding sites (GCC-box) in the promoter of ClBh1, which resulted in reduced expression of ClBh1 and inhibition of cucurbitacin synthesis in cultivated watermelon. Functional analysis revealed that a rare insertion of 244 amino acids, which arose in C. amarus and became fixed in sweet watermelon, in ClOSC (oxidosqualene cyclase) was critical for the negative selection of cucurbitacins during watermelon evolution. This research provides an important resource for metabolomics-assisted breeding in watermelon and for exploring metabolic pathway regulation mechanisms.

Integration of high-throughput phenotyping, GWAS, and predictive models reveals the genetic architecture of plant height in maize

Plant height (PH) is an essential trait in maize (Zea mays) that is tightly associated with planting density, biomass, lodging resistance, and grain yield in the field. Dissecting the dynamics of maize plant architecture will be beneficial for ideotype-based maize breeding and prediction, as the genetic basis controlling PH in maize remains largely unknown. In this study, we developed an automated high-throughput phenotyping platform (HTP) to systematically and noninvasively quantify 77 image-based traits (i-traits) and 20 field traits (f-traits) for 228 maize inbred lines across all developmental stages. Time-resolved i-traits with novel digital phenotypes and complex correlations with agronomic traits were characterized to reveal the dynamics of maize growth. An i-trait-based genome-wide association study identified 4945 trait-associated SNPs, 2603 genetic loci, and 1974 corresponding candidate genes. We found that rapid growth of maize plants occurs mainly at two developmental stages, stage 2 (S2) to S3 and S5 to S6, accounting for the final PH indicators. By integrating the PH-association network with the transcriptome profiles of specific internodes, we revealed 13 hub genes that may play vital roles during rapid growth. The candidate genes and novel i-traits identified at multiple growth stages may be used as potential indicators for final PH in maize. One candidate gene, ZmVATE, was functionally validated and shown to regulate PH-related traits in maize using genetic mutation. Furthermore, machine learning was used to build predictive models for final PH based on i-traits, and their performance was assessed across developmental stages. Moderate, strong, and very strong correlations between predictions and experimental datasets were achieved from the early S4 (tenth-leaf) stage. Colletively, our study provides a valuable tool for dissecting the spatiotemporal formation of specific internodes and the genetic architecture of PH, as well as resources and predictive models that are useful for molecular design breeding and predicting maize varieties with ideal plant architectures.

Metabolomics-centered mining of plant metabolic diversity and function: Past decade and future perspectives

Plants are natural experts in organic synthesis, being able to generate large numbers of specific metabolites with widely varying structures that help them adapt to variable survival challenges. Metabolomics is a research discipline that integrates the capabilities of several types of research including analytical chemistry, statistics, and biochemistry. Its ongoing development provides strategies for gaining a systematic understanding of quantitative changes in the levels of metabolites. Metabolomics is usually performed by targeting either a specific cell, a specific tissue, or the entire organism. Considerable advances in science and technology over the last three decades have propelled us into the era of multi-omics, in which metabolomics, despite at an earlier developmental stage than genomics, transcriptomics, and proteomics, offers the distinct advantage of studying the cellular entities that have the greatest influence on end phenotype. Here, we summarize the state of the art of metabolite detection and identification, and illustrate these techniques with four case study applications: (i) comparing metabolite composition within and between species, (ii) assessing spatio-temporal metabolic changes during plant development, (iii) mining characteristic metabolites of plants in different ecological environments and upon exposure to various stresses, and (iv) assessing the performance of metabolomics as a means of functional gene identification , metabolic pathway elucidation, and metabolomics-assisted breeding through analyzing plant populations with diverse genetic variations. In addition, we highlight the prominent contributions of joint analyses of plant metabolomics and other omics datasets, including those from genomics, transcriptomics, proteomics, epigenomics, phenomics, microbiomes, and ion-omics studies. Finally, we discuss future directions and challenges exploiting metabolomics-centered approaches in understanding plant metabolic diversity.

Rewiring of the seed metabolome during Tartary buckwheat domestication

Crop domestication usually leads to the narrowing genetic diversity. However, human selection mainly focuses on visible traits, such as yield and plant morphology, with most metabolic changes being invisible to the naked eye. Buckwheat accumulates abundant bioactive substances, making it a dual-purpose crop with excellent nutritional and medical value. Therefore, examining the wiring of these invisible metabolites during domestication is of major importance. The comprehensive profiling of 200 Tartary buckwheat accessions exhibits 540 metabolites modified as a consequence of human selection. Metabolic genome-wide association study illustrates 384 mGWAS signals for 336 metabolites are under selection. Further analysis showed that an R2R3-MYB transcription factor FtMYB43 positively regulates the synthesis of procyanidin. Glycoside hydrolase gene FtSAGH1 is characterized as responsible for the release of active salicylic acid, the precursor of aspirin and indispensably in plant defence. UDP-glucosyltransferase gene FtUGT74L2 is characterized as involved in the glycosylation of emodin, a major medicinal component specific in Polygonaceae. The lower expression of FtSAGH1 and FtUGT74L2 were associated with the reduction of salicylic acid and soluble EmG owing to domestication. This first large-scale metabolome profiling in Tartary buckwheat will facilitate genetic improvement of medicinal properties and disease resistance in Tartary buckwheat.

Genetic mapping of maize metabolites using high-throughput mass profiling

Plant metabolites are the basis of human nutrition and have biological relevance in ecology. Farmers selected plants with favorable characteristics since prehistoric times and improved the cultivars, but without knowledge of underlying mechanisms. Understanding the genetic basis of metabolite production can facilitate the successful breeding of plants with augmented nutritional value. To identify genetic factors related to the metabolic composition in maize, we generated mass profiles of 198 recombinant inbred lines (RILs) and their parents (B73 and Mo17) using direct-injection electrospray ionization mass spectrometry (DLI-ESI MS). Mass profiling allowed the correct clustering of samples according to genotype. We quantified 71 mass features from grains and 236 mass features from leaf extracts. For the corresponding ions, we identified tissue-specific metabolic 'Quantitative Trait Loci' (mQTLs) distributed across the maize genome. These genetic regions could regulate multiple metabolite biosynthesis pathways. Our findings demonstrate that DLI-ESI MS has sufficient analytical resolution to map mQTLs. These identified genetic loci will be helpful in metabolite-focused maize breeding. Mass profiling is a powerful tool for detecting mQTLs in maize and enables the high-throughput screening of loci responsible for metabolite biosynthesis.