An integrated multi-layered analysis of the metabolic networks of different tissues uncovers key genetic components of primary metabolism in maize

Prioritizing Metabolic Gene Regulators through Multi-Omic Network Integration in Maize

Elucidating gene regulatory networks (GRNs) 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. In this study, we integrated publicly available co-expression networks derived from more than 6,000 RNA-seq samples, 283 protein-DNA interaction assays, and 16 million of SNPs used to identify expression quantitative 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, protein-DNA interaction (PDI), trans-expression quantitative loci (trans-eQTL), and cis-eQTL combined with PDIs. To improve the functional annotation of TFs based on its target genes, we implemented three different strategies to integrate these four types of networks. We subsequently evaluated the effectiveness of our method through loss-of function mutant and random networks. The multi-network integration allowed us to identify transcriptional regulators of hormone-, metabolic- and development-related processes. Finally, using the topological properties of the fully integrated network, we identified potentially functional 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.

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.

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.

Opportunity and challenges of phenotyping plant salt tolerance

Salinity is a key factor limiting agricultural production worldwide. Recent advances in field phenotyping have enabled the recording of the environmental history and dynamic response of plants by considering both genotype × environment (G×E) interactions and envirotyping. However, only a few studies have focused on plant salt tolerance phenotyping. Therefore, we analyzed the potential opportunities and major challenges in improving plant salt tolerance using advanced field phenotyping technologies. RGB imaging and spectral and thermal sensors are the most useful and important sensing techniques for assessing key morphological and physiological traits of plant salt tolerance. However, field phenotyping faces challenges owing to its practical applications and high costs, limiting its use in early generation breeding and in developing countries.

Integrating multiomics data accelerates elucidation of plant primary and secondary metabolic pathways

Plants are the most important sources of food for humans, as well as supplying many ingredients that are of great importance for human health. Developing an understanding of the functional components of plant metabolism has attracted considerable attention. The rapid development of liquid chromatography and gas chromatography, coupled with mass spectrometry, has allowed the detection and characterization of many thousands of metabolites of plant origin. Nowadays, elucidating the detailed biosynthesis and degradation pathways of these metabolites represents a major bottleneck in our understanding. Recently, the decreased cost of genome and transcriptome sequencing rendered it possible to identify the genes involving in metabolic pathways. Here, we review the recent research which integrates metabolomic with different omics methods, to comprehensively identify structural and regulatory genes of the primary and secondary metabolic pathways. Finally, we discuss other novel methods that can accelerate the process of identification of metabolic pathways and, ultimately, identify metabolite function(s).

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.

Metabolome genome-wide association study provides biochemical and genetic insights into natural variation of primary metabolites in sesame

Plants' primary metabolites are of great importance from the survival and nutritional perspectives. However, the genetic bases underlying the profiles of primary metabolites in oilseed crops remain largely unclear. As one of the main oilseed crops, sesame (Sesamum indicum L.) is a potential model plant for investigating oil metabolism in plants. Therefore, the objective of this study is to disclose the genetic variants associated with variation in the content of primary metabolites in sesame. We performed a comprehensive metabolomics analysis of primary metabolites in 412 diverse sesame accessions using gas chromatography-mass spectrometry and identified a total of 45 metabolites, including fatty acids, monoacylglycerols (MAGs), and amino acids. Genome-wide association study unveiled 433 significant single-nucleotide polymorphism loci associated with variation in primary metabolite contents in sesame. By integrating diverse genomic analyses, we identified 10 key candidate causative genes of variation in MAG, fatty acid, asparagine, and sucrose contents. Among them, SiDSEL was significantly associated with multiple traits. SiCAC3 and SiKASI were strongly associated with variation in oleic acid and linoleic acid contents. Overexpression of SiCAC3, SiKASI, SiLTPI.25, and SiLTPI.26 in transgenic Arabidopsis and Saccharomyces cerevisiae revealed that SiCAC3 is a potential target gene for improvement of unsaturated fatty acid levels in crops. Furthermore, we found that it may be possible to breed several quality traits in sesame simultaneously. Our results provide valuable genetic resources for improving sesame seed quality and our understanding of oilseed crops' primary metabolism.

CRISPR/Cas-mediated editing of cis-regulatory elements for crop improvement

To improve future agricultural production, major technological advances are required to increase crop production and yield. Targeting the coding region of genes via the Clustered Regularly Interspaced Short Palindromic Repeats/CRISPR-associated Protein (CRISPR/Cas) system has been well established and has enabled the rapid generation of transgene-free plants, which can lead to crop improvement. The emergence of the CRISPR/Cas system has also enabled scientists to achieve cis-regulatory element (CRE) editing and, consequently, engineering endogenous critical CREs to modulate the expression of target genes. Recent genome-wide association studies have identified the domestication of natural CRE variants to regulate complex agronomic quantitative traits and have allowed for their engineering via the CRISPR/Cas system. Although engineering plant CREs can be advantageous to drive gene expression, there are still many limitations to its practical application. Here, we review the current progress in CRE editing and propose future strategies to effectively target CREs for transcriptional regulation for crop improvement.

A pan-Zea genome map for enhancing maize improvement

Background

Maize (Zea mays L.) is at the vanguard facing the upcoming breeding challenges. However, both a super pan-genome for the Zea genus and a comprehensive genetic variation map for maize breeding are still lacking.

Results

Here, we construct an approximately 6.71-Gb pan-Zea genome that contains around 4.57-Gb non-B73 reference sequences from fragmented de novo assemblies of 721 pan-Zea individuals. We annotate a total of 58,944 pan-Zea genes and find around 44.34% of them are dispensable in the pan-Zea population. Moreover, 255,821 common structural variations are identified and genotyped in a maize association mapping panel. Further analyses reveal gene presence/absence variants and their potential roles during domestication of maize. Combining genetic analyses with multi-omics data, we demonstrate how structural variants are associated with complex agronomic traits.

Conclusions

Our results highlight the underexplored role of the pan-Zea genome and structural variations to further understand domestication of maize and explore their potential utilization in crop improvement.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13059-022-02742-7.

Reverse genetic approaches for breeding nutrient-rich and climate-resilient cereal and food legume crops

In the last decade, advancements in genomics tools and techniques have led to the discovery of many genes. Most of these genes still need to be characterized for their associated function and therefore, such genes remain underutilized for breeding the next generation of improved crop varieties. The recent developments in different reverse genetic approaches have made it possible to identify the function of genes controlling nutritional, biochemical, and metabolic traits imparting drought, heat, cold, salinity tolerance as well as diseases and insect-pests. This article focuses on reviewing the current status and prospects of using reverse genetic approaches to breed nutrient-rich and climate resilient cereal and food legume crops.

Computational prediction of plant metabolic pathways

Uncovering genes encoding enzymes responsible for the biosynthesis of diverse plant metabolites is essential for metabolic engineering and production of plant metabolite-derived medicine. With the availability of multi-omics data for an ever-increasing number of plant species and the development of computational approaches, the metabolic pathways of many important plant compounds can be predicted, complementing a more traditional genetic and/or biochemical approach. Here, we summarize recent progress in predicting plant metabolic pathways using genome, transcriptome, proteome, interactome, and/or metabolome data, and the utility of integrating these data with machine learning to further improve metabolic pathway predictions.

Applications of Genomic Tools in Plant Breeding: Crop Biofortification

Crop breeding has mainly been focused on increasing productivity, either directly or by decreasing the losses caused by biotic and abiotic stresses (that is, incorporating resistance to diseases and enhancing tolerance to adverse conditions, respectively). Quite the opposite, little attention has been paid to improve the nutritional value of crops. It has not been until recently that crop biofortification has become an objective within breeding programs, through either conventional methods or genetic engineering. There are many steps along this long path, from the initial evaluation of germplasm for the content of nutrients and health-promoting compounds to the development of biofortified varieties, with the available and future genomic tools assisting scientists and breeders in reaching their objectives as well as speeding up the process. This review offers a compendium of the genomic technologies used to explore and create biodiversity, to associate the traits of interest to the genome, and to transfer the genomic regions responsible for the desirable characteristics into potential new varieties. Finally, a glimpse of future perspectives and challenges in this emerging area is offered by taking the present scenario and the slow progress of the regulatory framework as the starting point.

Metabolomic Analysis Reveals Nutritional Diversity among Three Staple Crops and Three Fruits

More than 2 billion people worldwide are under threat of nutritional deficiency. Thus, an in-depth comprehension of the nutritional composition of staple crops and popular fruits is essential for health. Herein, we performed LC-MS-based non-targeted and targeted metabolome analyses with crops (including wheat, rice, and corn) and fruits (including grape, banana, and mango). We detected a total of 2631 compounds by using non-targeted strategy and identified more than 260 nutrients. Our work discovered species-dependent accumulation of common present nutrients in crops and fruits. Although rice and wheat lack vitamins and amino acids, sweet corn was rich in most amino acids and vitamins. Among the three fruits, mango had more vitamins and amino acids than grape and banana. Grape and banana provided sufficient 5-methyltetrahydrofolate and vitamin B6, respectively. Moreover, rice and grape had a high content of flavonoids. In addition, the three crops contained more lipids than fruits. Furthermore, we also identified species-specific metabolites. The crops yielded 11 specific metabolites, including flavonoids, lipids, and others. Meanwhile, most fruit-specific nutrients were flavonoids. Our work discovered the complementary pattern of essential nutrients in crops and fruits, which provides metabolomic evidence for a healthy diet.

Biotransformation of Flavonoids Improves Antimicrobial and Anti-Breast Cancer Activities In Vitro

Coarse cereals are rich in flavonoids, which are bioactive substances with a wide range of functions. Biotransformation is considered an emerging approach to methylate flavonoids, displaying prominent regio- and stereoselectivity. In the current study, liquiritigenin, naringenin, and hesperidin flavonoids were biotransformed using O-methyltransferases that were heterologously expressed in Saccharomyces cerevisiae BJ5464-NpgA. Nuclear magnetic resonance (NMR) spectroscopy was used together with high-resolution mass spectroscopy analysis to determine the structures of the resulting methylated transformants, and their antimicrobial and antiproliferation activities were also characterized. Among the five methylated flavonoids obtained, 7-methoxy-liquiritigenin had the strongest inhibitory effect on Candida albicans SC5314 (C. albicans SC5314), Staphylococcus aureus ATCC6538 (S. aureus ATCC6538), and Escherichia coli ATCC25922 (E. coli ATCC25922), which increased 7.65-, 1.49-, and 0.54-fold in comparison to the values of their unmethylated counterparts at 200, 250, and 400 μM, respectively. The results suggest that 3′-methoxyhesperetin showed the best antiproliferative activity against MCF-7 cells with IC₅₀ values of 10.45 ± 0.45 µM, which was an increase of more than 14.35-fold compared to that of hesperetin. These results indicate that methylation enhances the antimicrobial activities and antiproliferative effects of flavonoids. The current study provides an experimental basis for further research on flavonoids as well as flavonoid-containing crops in the development of antimicrobial and anti-breast cancer drugs in addition to supplementary and health foods. The biotransformation method is ideal, as it represents a means for the sustainable production of bioactive flavonoids.

LYSINE KETOGLUTARATE REDUCTASE TRANS-SPLICING RELATED 1 is involved in temperature-dependent root growth in rice

Root length is an important root parameter directly related to the uptake of water and nutrients. However, the molecular mechanisms controlling root length are still not fully understood. Here, we isolated a short-root mutant of rice, dice2 (defective in cell elongation 2). The cell length and meristem size of the roots were decreased in dice2, but the root function in terms of mineral element uptake, root cell width, and root anatomy were hardly altered compared with wild-type (WT) rice. The root growth defect in dice2 could be partially rescued by high temperature. Map-based cloning combined with a complementation test revealed that the short-root phenotype was caused by a nonsense mutation in a gene which was annotated to encode Lysine Ketoglutarate Reductase Trans-Splicing related 1 (OsLKRT1). OsLKRT1, encoding a cytosol-localized protein, was expressed in all cells of the root tip and elongation region as well as the shoot. RNA-seq analysis showed that there was no difference between dice2 and the WT in the expression level of genes involved in root development identified so far. These results indicate that OsLKRT1 is involved in a novel pathway required for root cell elongation in rice, although its exact role remains to be further investigated.

Mining plant metabolomes: Methods, applications, and perspectives

Plants produce a variety of metabolites that are essential for plant growth and human health. To fully understand the diversity of metabolites in certain plants, lots of methods have been developed for metabolites detection and data processing. In the data-processing procedure, how to effectively reduce false-positive peaks, analyze large-scale metabolic data, and annotate plant metabolites remains challenging. In this review, we introduce and discuss some prominent methods that could be exploited to solve these problems, including a five-step filtering method for reducing false-positive signals in LC-MS analysis, QPMASS for analyzing ultra-large GC-MS data, and MetDNA for annotating metabolites. The main applications of plant metabolomics in species discrimination, metabolic pathway dissection, population genetic studies, and some other aspects are also highlighted. To further promote the development of plant metabolomics, more effective and integrated methods/platforms for metabolite detection and comprehensive databases for metabolite identification are highly needed. With the improvement of these technologies and the development of genomics and transcriptomics, plant metabolomics will be widely used in many fields.

Metabolomics and health: from nutritional crops and plant-based pharmaceuticals to profiling of human biofluids

During the past decade metabolomics has emerged as one of the fastest developing branches of “-omics” technologies. Metabolomics involves documentation, identification, and quantification of metabolites through modern analytical platforms in various biological systems. Advanced analytical tools, such as gas chromatography–mass spectrometry (GC/MS), liquid chromatography–mass spectroscopy (LC/MS), and non-destructive nuclear magnetic resonance (NMR) spectroscopy, have facilitated metabolite profiling of complex biological matrices. Metabolomics, along with transcriptomics, has an influential role in discovering connections between genetic regulation, metabolite phenotyping and biomarkers identification. Comprehensive metabolite profiling allows integration of the summarized data towards manipulation of biosynthetic pathways, determination of nutritional quality markers, improvement in crop yield, selection of desired metabolites/genes, and their heritability in modern breeding. Along with that, metabolomics is invaluable in predicting the biological activity of medicinal plants, assisting the bioactivity-guided fractionation process and bioactive leads discovery, as well as serving as a tool for quality control and authentication of commercial plant-derived natural products. Metabolomic analysis of human biofluids is implemented in clinical practice to discriminate between physiological and pathological state in humans, to aid early disease biomarker discovery and predict individual response to drug therapy. Thus, metabolomics could be utilized to preserve human health by improving the nutritional quality of crops and accelerating plant-derived bioactive leads discovery through disease diagnostics, or through increasing the therapeutic efficacy of drugs via more personalized approach. Here, we attempt to explore the potential value of metabolite profiling comprising the above-mentioned applications of metabolomics in crop improvement, medicinal plants utilization, and, in the prognosis, diagnosis and management of complex diseases.

The utility of metabolomics as a tool to inform maize biology

With the rise of high-throughput omics tools and the importance of maize and its products as food and bioethanol, maize metabolism has been extensively explored. Modern maize is still rich in genetic and phenotypic variation, yielding a wide range of structurally and functionally diverse metabolites. The maize metabolome is also incredibly dynamic in terms of topology and subcellular compartmentalization. In this review, we examine a broad range of studies that cover recent developments in maize metabolism. Particular attention is given to current methodologies and to the use of metabolomics as a tool to define biosynthetic pathways and address biological questions. We also touch upon the use of metabolomics to understand maize natural variation and evolution, with a special focus on research that has used metabolite-based genome-wide association studies (mGWASs).

Genome-wide association studies: assessing trait characteristics in model and crop plants

GWAS involves testing genetic variants across the genomes of many individuals of a population to identify genotype–phenotype association. It was initially developed and has proven highly successful in human disease genetics. In plants genome-wide association studies (GWAS) initially focused on single feature polymorphism and recombination and linkage disequilibrium but has now been embraced by a plethora of different disciplines with several thousand studies being published in model and crop species within the last decade or so. Here we will provide a comprehensive review of these studies providing cases studies on biotic resistance, abiotic tolerance, yield associated traits, and metabolic composition. We also detail current strategies of candidate gene validation as well as the functional study of haplotypes. Furthermore, we provide a critical evaluation of the GWAS strategy and its alternatives as well as future perspectives that are emerging with the emergence of pan-genomic datasets.

The genetic architecture of the dynamic changes in grain moisture in maize

Low grain moisture at harvest is crucial for safe production, transport and storage, but the genetic architecture of this trait in maize (Zea mays) remains elusive. Here, we measured the dynamic changes in grain moisture content in an association-mapping panel of 513 diverse maize inbred lines at five successive stages across five geographical environments. Genome-wide association study (GWAS) revealed 71 quantitative trait loci (QTLs) that influence grain moisture in maize. Epistatic effects play vital roles in the variability in moisture levels, even outperforming main-effect QTLs during the early dry-down stages. Distinct QTL-environment interactions influence the spatio-temporal variability of maize grain moisture, which is primarily triggered at specific times. By combining genetic population analysis, transcriptomic profiling and gene editing, we identified GRMZM5G805627 and GRMZM2G137211 as candidate genes underlying major QTLs for grain moisture in maize. Our results provide insights into the genetic architecture of dynamic changes in grain moisture, which should facilitate maize breeding.

Understanding Omics Driven Plant Improvement and de novo Crop Domestication: Some Examples

In the current era, one of biggest challenges is to shorten the breeding cycle for rapid generation of a new crop variety having high yield capacity, disease resistance, high nutrient content, etc. Advances in the "-omics" technology have revolutionized the discovery of genes and bio-molecules with remarkable precision, resulting in significant development of plant-focused metabolic databases and resources. Metabolomics has been widely used in several model plants and crop species to examine metabolic drift and changes in metabolic composition during various developmental stages and in response to stimuli. Over the last few decades, these efforts have resulted in a significantly improved understanding of the metabolic pathways of plants through identification of several unknown intermediates. This has assisted in developing several new metabolically engineered important crops with desirable agronomic traits, and has facilitated the de novo domestication of new crops for sustainable agriculture and food security. In this review, we discuss how "omics" technologies, particularly metabolomics, has enhanced our understanding of important traits and allowed speedy domestication of novel crop plants.

Dissection of the domestication-shaped genetic architecture of lettuce primary metabolism

Lettuce (Lactuca sativa L.) is an important vegetable crop species worldwide. The primary metabolism of this species is essential for its growth, development and reproduction as well as providing a considerable direct source of energy and nutrition for humans. Here, through investigating 77 primary metabolites in 189 accessions including all major horticultural types and wild lettuce L. serriola we showed that the metabolites in L. serriola were different from those in cultivated lettuce. The findings were consistent with the demographic model of lettuce and supported a single domestication event for this species. Selection signals among these metabolic traits were detected. Specifically, galactinol, malate, quinate and threonate were significantly affected by the domestication process and cultivar differentiation of lettuce. Galactinol and raffinose might have been selected during stem lettuce cultivation as an adaption to the local environments in China. Furthermore, we identified 154 loci significantly associated with the level of 51 primary metabolites. Three genes (LG8749721, LG8763094 and LG5482522) responsible for the levels of galactinol, raffinose, quinate and chlorogenic acid were further dissected, which may have been the target of domestication and/or affected by local adaptation. Additionally, our findings strongly suggest that human selection resulted in reduced quinate and chlorogenic acid levels in cultivated lettuce. Our study thus provides beneficial genetic resources for lettuce quality improvement and sheds light on the domestication and evolution of this important leafy green.

Identification of Genes Conferring Plant Salt Tolerance using GWAS: Current Success and Perspectives

An understanding of the molecular mechanisms that underlie plant salt tolerance is important for both economic and scientific interests. Genome-wide association study (GWAS) is a promising approach to pinpoint genes that confer plant salt tolerance. With the advancement of supporting technology and methodology, GWAS has enabled the discovery of genes that play central roles in regulating plant salt tolerance in the past decade. Here, I highlight recent successful GWAS work in unveiling the molecular factors underlying plant salt tolerance and discuss the concerns and opportunities in conducting such experiments. It is anticipated that GWAS will be increasingly successful in the identification of key genes that are useful for crop improvement.

The style and substance of plant flavonoid decoration; towards defining both structure and function

Over 8000 different flavonoids have been described and a considerable number of new flavonoid structures are being elucidated every year. The advent of metabolomics alongside the development of phytochemical genetics - wherein the genetic basis underlying the regulation of the levels of plant metabolites is determined - has provided a massive boost to such efforts. That said our understanding of the individual function(s) of the vast majority of the metabolites that constitute this important class of phytochemicals remains unknown. Here we review what is known concerning the major decorative modifications of flavonoids in plants, namely hydroxylation, glycosylation, methylation and acylation. Our major focus is with regard to the in planta function of these modified compounds, however, we also highlight the demonstrated bioactive roles which they possess. We additionally performed a comprehensive survey of the flavonoids listed in the KNApSAcK database in order to assess the frequency of occurrence of each type of flavonoid modification. We conclude that whilst considerable research has been carried out regarding the biological roles of flavonoids most studies to date have merely provided information on the compound class or sub-classes thereof as a whole with too little currently known on the specific role of individual metabolites. We, therefore, finally suggest a framework based on currently available tools by which the relative importance of the individual compounds can be assessed under various biological conditions in order to fill this knowledge-gap.

Parallel Metabolomic and Transcriptomic Analysis Reveals Key Factors for Quality Improvement of Tea Plants

As one of the most popular beverages globally, tea has enormous economic, cultural, and medicinal importance that necessitates a comprehensive metabolomics study of this species. In this study, a large-scale targeted metabolomics analysis on two types of leaf tissues of nine tea cultivars from five representative geographical origins within China was carried out using the liquid chromatography-mass spectrometry technique. RNA-seq-based transcriptomic analysis was in parallel conducted on the same samples, and gene expression and metabolic differentiation between tissues as well as between the multiple tea cultivars were investigated. The data obtained provide an accessible resource for further studies of naturally occurring metabolic variation of tea plants, which will aid in thoroughly interpreting the underlying genetic and molecular mechanisms of biosynthesis of specialized metabolites in this critical species. Candidate genes including a transcription factor (CsMYB5-like), which were highly correlated with both the content of flavonoids and the expression level of genes participating in the phenylpropanoid and flavonoid biosynthesis pathway, were identified as potential targets for quality improvement of tea.

Phenotyping: New Windows into the Plant for Breeders

Plant phenotyping enables noninvasive quantification of plant structure and function and interactions with environments. High-capacity phenotyping reaches hitherto inaccessible phenotypic characteristics. Diverse, challenging, and valuable applications of phenotyping have originated among scientists, prebreeders, and breeders as they study the phenotypic diversity of genetic resources and apply increasingly complex traits to crop improvement. Noninvasive technologies are used to analyze experimental and breeding populations. We cover the most recent research in controlled-environment and field phenotyping for seed, shoot, and root traits. Select field phenotyping technologies have become state of the art and show promise for speeding up the breeding process in early generations. We highlight the technologies behind the rapid advances in proximal and remote sensing of plants in fields. We conclude by discussing the new disciplines working with the phenotyping community: data science, to address the challenge of generating FAIR (findable, accessible, interoperable, and reusable) data, and robotics, to apply phenotyping directly on farms.

The Past, Present, and Future of Maize Improvement: Domestication, Genomics, and Functional Genomic Routes toward Crop Enhancement

After being domesticated from teosinte, cultivated maize (Zea mays ssp. mays) spread worldwide and now is one of the most important staple crops. Due to its tremendous phenotypic and genotypic diversity, maize also becomes to be one of the most widely used model plant species for fundamental research, with many important discoveries reported by maize researchers. Here, we provide an overview of the history of maize domestication and key genes controlling major domestication-related traits, review the currently available resources for functional genomics studies in maize, and discuss the functions of most of the maize genes that have been positionally cloned and can be used for crop improvement. Finally, we provide some perspectives on future directions regarding functional genomics research and the breeding of maize and other crops.

Large-scale metabolite quantitative trait locus analysis provides new insights for high-quality maize improvement

It is generally recognized that many favorable genes which were lost during domestication, including those related to both nutritional value and stress resistance, remain hidden in wild relatives. To uncover such genes in teosinte, an ancestor of maize, we conducted metabolite profiling in a BC₂ F₇ population generated from a cross between the maize wild relative (Zea mays ssp. mexicana) and maize inbred line Mo17. In total, 65 primary metabolites were quantified in four tissues (seedling-stage leaf, grouting-stage leaf, young kernel and mature kernel) with clear tissue-specific patterns emerging. Three hundred and fifty quantitative trait loci (QTLs) for these metabolites were obtained, which were distributed unevenly across the genome and included two QTL hotspots. Metabolite concentrations frequently increased in the presence of alleles from the teosinte genome while the opposite was observed for grain yield and shape trait QTLs. Combination of the multi-tissue transcriptome and metabolome data provided considerable insight into the metabolic variations between maize and its wild relatives. This study thus identifies favorable genes hidden in the wild relative which should allow us to balance high yield and quality in future modern crop breeding programs.

Exploring the Diversity of Plant Metabolism

Plants produce a huge array of metabolites, far more than those produced by most other organisms. Unraveling this diversity and its underlying genetic variation has attracted increasing research attention. Post-genomic profiling platforms have enabled the marriage and mining of the enormous amount of phenotypic and genetic diversity. We review here achievements to date and challenges remaining that are associated with plant metabolic research using multi-omic strategies. We focus mainly on strategies adopted in investigating the diversity of plant metabolism and its underlying features. Recent advances in linking metabotypes with phenotypic and genotypic traits are also discussed. Taken together, we conclude that exploring the diversity of metabolism could provide new insights into plant evolution and domestication.

The maize secondary metabolism glycosyltransferase UFGT2 modifies flavonols and contributes to plant acclimation to abiotic stresses

BACKGROUND AND AIMS

Nowadays, the plant family 1 glycosyltransferases (UGTs) are attracting more and more attention since members of this family can improve the properties of secondary metabolites and have significantly enriched the chemical species in plants. Over the past decade, most studies on UGTs have been conducted in Arabidopsis thaliana and they were proved to play diverse roles during the plant life cycle. The Zea mays (maize) GT1 family comprises a large number of UDP-glycosyltransferase (UGT) members. However, their enzyme activities and the biological functions are rarely revealed. In this study, a maize flavonol glycosyltransferase, UFGT2, is identified and its biological role is characterized in detail.

METHODS

The UFGT2 enzyme activity, the flavonol and glycoside levels in planta were examined by high- performance liquid chromatography (HPLC) and liquid chromatography-mass spectrometry (LC-MS). The functions of UFGT2 in modifying flavonols, mediating flavonol accumulation and improving stress tolerance were analysed using two ufgt2 mutants and transgenic arabidopsis plants.

KEY RESULTS

By in vitro enzyme assay, the maize UFGT2 was found to show strong activity towards two flavonols: kaemferol and quercetin. Two ufgt2 knockout mutants, Mu689 and Mu943, exhibited obvious sensitivity to salt and drought stresses. The endogenous quercetin and kaempferol glycosides, as well as the total flavonol levels were found to be substantially decreased in the two ufgt2 mutants, with declined H2O2-scavenging capacity. In contrast, ectopic expression of UFGT2 in arabidopsis led to increased flavonol contents and enhanced oxidative tolerance. Moreover, expression of typical stress-related genes in arabidopsis and maize were affected in UFGT2 overexpression plants or knockout mutants in response to abiotic stresses. UFGT2 was also transferred into the arabidopsis ugt78d2 mutant and it was found to recover the deficient flavonol glycoside pattern in the ugt78d2 mutant, which confirmed its catalysing activity in planta.

CONCLUSION

It is demonstrated in our study that a maize glycosyltransferase, UFGT2, involved in modifying flavonols, contributes to improving plant tolerance to abiotic stresses.

Crop metabolomics: from diagnostics to assisted breeding

BACKGROUND

Until recently, plant metabolomics have provided a deep understanding on the metabolic regulation in individual plants as experimental units. The application of these techniques to agricultural systems subjected to more complex interactions is a step towards the implementation of translational metabolomics in crop breeding.

AIM OF REVIEW

We present here a review paper discussing advances in the knowledge reached in the last years derived from the application of metabolomic techniques that evolved from biomarker discovery to improve crop yield and quality.

KEY SCIENTIFIC CONCEPTS OF REVIEW

Translational metabolomics applied to crop breeding programs.

Metabolomics 20 years on: what have we learned and what hurdles remain?

The term metabolome was coined in 1998, by analogy to genome, transcriptome and proteome. The first research papers using the terms metabolomics, metabonomics, metabolic profiling or metabolite profiling were published shortly thereafter. In this short review we reflect on the major achievements brought about by the use of these approaches, and document the knowledge and technology gaps that are currently constraining its further development. Finally, we detail why we think that the time is ripe to refocus our efforts on the understanding of metabolic function.