Genetic Determinants of the Network of Primary Metabolism and Their Relationships to Plant Performance in a Maize Recombinant Inbred Line Population

Metabolome guided treasure hunt - learning from metabolic diversity

Metabolomics is a rapidly evolving field focused on the comprehensive identification and quantification of small molecules in biological systems. As the final layer of the biological hierarchy following of the genome, transcriptome and proteome, it presents a dynamic snapshot of phenotype, influenced by genetic, environmental and physiological factors. Whilst the metabolome sits downstream of genes and proteins, there are multiple higher levels-tissues, organs, the entire organism, and interactions with other organisms, which need to be considered in order to fully comprehend organismal biology. Advances in metabolomics continue to expand its applications in plant biology, biotechnology, and natural product discovery unlocking many of nature's most beneficial colors, tastes, nutrients and medicines. Flavonoids and other specialized metabolites are essential for plant defense against oxidative stress and function as key phytonutrients for human health. Recent advancements in gene-editing and metabolic engineering have significantly improved the nutritional value and flavor of crop plants. Here we highlight how advanced metabolic analysis is driving improvements in crops uncovering genes that influence nutrient and flavor profile and plant derived compounds with medicinal potential.

The homeostasis of β-alanine is key for Arabidopsis reproductive growth and development

β-Alanine, an abundant non-proteinogenic amino acid, acts as a precursor for coenzyme A and plays a role in various stress responses. However, a comprehensive understanding of its metabolism in plants remains incomplete. Previous metabolic genome-wide association studies (mGWAS) identified ALANINE:GLYOXYLATE AMINOTRANSFERASE2 (AGT2, AT4G39660) linked to β-alanine levels in Arabidopsis under normal conditions. In this study, we aimed to deepen our insights into β-alanine regulation by conducting mGWAS under two contrasting environmental conditions: control (12 h photoperiod, 21°C, 150 μmol m-2 sec-1) and stress (harvested after 1820 min at 32°C and darkness). We identified two highly significant quantitative trait loci (QTL) for β-alanine, including the AGT2 locus associated in both environments and ALDEHYDE DEHYDROGENASE6B2 (ALDH6B2, AT2G14170) associated only under stress conditions. A coexpression-correlation network revealed that the regulatory pathway involving β-alanine levels, AGT2, and ALDH6B2 connects the branched chained amino acid (BCAA) degradation through the propionate pathway. Metabolic profiles of AGT2 overexpression (OE) and knock-out (KO) lines (agt2) across various organs and developmental stages established the critical role of AGT2 in β-alanine metabolism. This work underscores the importance of β-alanine homeostasis for proper growth and development in Arabidopsis.

Novel candidate genes and genetic basis analysis of kernel starch content in tropical maize

BACKGROUND

Starch is the most abundant carbohydrate in maize grains, serving as a primary energy source for both humans and animals, and playing a crucial role in various industrial applications. Increasing the starch content of maize grains is beneficial for improving the grain yield and quality. To gain insight into the genetic basis of starch content in maize kernels, a multiparent population (MPP) was constructed and evaluated for starch content in three different environments.

RESULTS

The integration of QTL mapping and genome-wide association analysis (GWAS) identified two SNPs, 8_166371888 and 8_178656036, which overlapped the QTL interval of qSC8-1, identified in the tropical maize line YML46. The phenotypic variance explained (PVE) by the QTL qSC8-1 was12.17%, while the SNPs 8_166371888 and 8_178656036 explained 10.19% and 5.72% of the phenotypic variance. Combined GWAS and QTL analyses led to the identification of two candidate genes, Zm00001d012005 and Zm00001d012687 located on chromosome 8.

CONCLUSIONS

The candidate gene Zm00001d012005 encodes histidine kinase, which is known to play a role in starch accumulation in rice spikes. Related histidine kinases, such as AHK1, are involved in endosperm transfer cell development in barley, which affects grain quality. Zm00001d012687 encodes triacylglycerol lipase, which reduces seed oil content. Since oil content in cereal kernels is negatively correlated with starch content, this gene is likely involved in regulating the starch content in maize kernels. These findings provide insights into the genetic mechanisms underlying kernel starch content and establish a theoretical basis for breeding maize varieties with high starch content.

Exploring genetics and genomics trends to understand the link between secondary metabolic genes and agronomic traits in cereals under stress

The plant metabolome is considered an important interface between the genome and its phenome, where it plays a significant role in regulating plant growth in response to various environmental cues. A wide array of specialized metabolites is produced by plants, which are essential for mediating environmental interactions and their adaptation. Notably, enhanced accumulation of these specialized metabolites, particularly plant secondary metabolites (PSMs), is a part of the chemical defense response that is directly linked to improved stress tolerance. Therefore, exploring the genetic diversity underlying the immense variation of the secondary metabolite pool could unravel the adaptation mechanisms in plants against different environmental stresses. The post-genomic profiling platforms have enabled the exploration of the link between metabolic diversity and important agronomic traits. The current review focuses on the major achievements and future challenges associated with plant secondary metabolite (PSM) research in graminaceous crops using advanced omics approaches. Given this, we briefly summarize different strategies adopted to explore the genetic diversity and evolution of PSMs in cereal crops. Further, we have discussed the recent technological advancements to integrate multi-omics approaches linking the metabolome diversity with the genome, transcriptome, and proteome of these crops under stress. Combining these data with phenomics (the omics of phenotypes) provides a holistic view of how plants respond to stress. Next, we outlined the genetic manipulation studies performed so far in cereals to engineer secondary metabolic pathways for enhanced stress tolerance. In summary, our review provides new insight into developing genetic and genomic trends in exploring the secondary metabolite diversity in graminaceous crops and discusses how this information can be utilized in designing strategies to generate future stress-resilient crops.

Comprehensive multi-layered analyses of genotype-dependent proteo-metabolic networks reveal organellar crosstalk and biochemical pathways regulating aroma formation in rice

Molecular basis of rice aroma formation is sparsely known and developmental programs driving biochemical pathways towards aroma is in infancy. Here, discovery and targeted proteo-metabolome of non-aromatic and aromatic rice seeds across developmental stages identified a total of 442 aroma-responsive proteins (ARPs) and 824 aroma-responsive metabolites (ARMs) involved in metabolism, calcium and G-protein signaling. Biochemical examination revealed ARM/Ps were linked to 2-acetylpyrrolidine, γ-aminobutyrate, anthocyanin, tannins, flavonoids and related enzymes. Pairwise correlation and clustering showed positive correlation among ARM/Ps. Consistent with aroma-related QTLs, ARPs were mapped on chromosomes 3,4,5,8 and were mainly compartmentalized in cytoplasm and mitochondria. ARM/P-correlation network identified associations related to metabolism and signaling. Multiple reaction monitoring (MRM) confirmed role of catechins, quinic acid and quercetin in aroma formation. Pathway enrichment, multivariate analysis and qRT-PCR validated that calcium and G-protein signaling, aromatic/branched-chain aminoacid, 2-acetylpyrrolidine, oxylipin, melvonate and prenylpyrophosphate pathways, indole, phenylacetate, flavonoid, cinnamoic ester govern aroma formation in rice.

Proteo-metabolomic Dissection of Extracellular Matrix Reveals Alterations in Cell Wall Integrity and Calcium Signaling Governs Wall-Associated Susceptibility during Stem Rot Disease in Jute

The plant surveillance system confers specificity to disease and immune states by activating distinct molecular pathways linked to cellular functionality. The extracellular matrix (ECM), a preformed passive barrier, is dynamically remodeled at sites of interaction with pathogenic microbes. Stem rot, caused by Macrophomina phaseolina, adversely affects fiber production in jute. However, how wall related susceptibility affects the ECM proteome and metabolome remains undetermined in bast fiber crops. Here, stem rot responsive quantitative temporal ECM proteome and metabolome were developed in jute upon M. phaseolina infection. Morpho-histological examination revealed that leaf shredding was accompanied by reactive oxygen species production in patho-stressed jute. Electron microscopy showed disease progression and ECM architecture remodeling due to necrosis in the later phase of fungal attack. Using isobaric tags for relative and absolute quantitative proteomics and liquid chromatography-tandem mass spectrometry, we identified 415 disease-responsive proteins involved in wall integrity, acidification, proteostasis, hydration, and redox homeostasis. The disease-related correlation network identified functional hubs centered on α-galactosidase, pectinesterase, and thaumatin. Gas chromatography-mass spectrometry analysis pointed toward enrichment of disease-responsive metabolites associated with the glutathione pathway, TCA cycle, and cutin, suberin, and wax metabolism. Data demonstrated that wall-degrading enzymes, structural carbohydrates, and calcium signaling govern rot responsive wall-susceptibility. Proteomics data were deposited in Pride (PXD046937; PXD046939).

The evolution of morphological castes under decoupled control

Eusociality, where units that previously reproduced independently function as one entity, is of major interest in evolutionary biology. Obligate eusociality is characterized by morphologically differentiated castes and reduced conflict. We explore conditions under which morphological castes may arise in the Hymenoptera and factors constraining their evolution. Control over offspring morphology and behaviour seems likely to be decoupled. Provisioners (queens and workers) can influence offspring morphology directly through the nutrition they provide, while adult offspring control their own behaviour. Provisioners may, however, influence worker behaviour indirectly if offspring modify their behaviour in response to their morphology. If manipulation underlies helping, we should not see helping evolve before specialized worker morphology, yet empirical observations suggest that behavioural castes precede morphological castes. We use evolutionary invasion analyses to show how the evolution of a morphologically differentiated worker caste depends on the prior presence of a behavioural caste: specialist worker morphology will be mismatched with behaviour unless some offspring already choose to work. A mother's certainty about her offspring's behaviour is also critical-less certainty results in greater mismatch. We show how baseline worker productivity can affect the likelihood of a morphological trait being favoured by natural selection. We then show how under a decoupled control scenario, morphologically differentiated castes should be less and less likely to be lost as they become more specialized. We also suggest that for eusociality to be evolutionarily irreversible, workers must be unable to functionally replace reproductives and reproductives must be unable to reproduce without help from workers.

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.

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.

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.

Multi-omics assists genomic prediction of maize yield with machine learning approaches

With the improvement of high-throughput technologies in recent years, large multi-dimensional plant omics data have been produced, and big-data-driven yield prediction research has received increasing attention. Machine learning offers promising computational and analytical solutions to interpret the biological meaning of large amounts of data in crops. In this study, we utilized multi-omics datasets from 156 maize recombinant inbred lines, containing 2496 single nucleotide polymorphisms (SNPs), 46 image traits (i-traits) from 16 developmental stages obtained through an automatic phenotyping platform, and 133 primary metabolites. Based on benchmark tests with different types of prediction models, some machine learning methods, such as Partial Least Squares (PLS), Random Forest (RF), and Gaussian process with Radial basis function kernel (GaussprRadial), achieved better prediction for maize yield, albeit slight difference for method preferences among i-traits, genomic, and metabolic data. We found that better yield prediction may be caused by various capabilities in ranking and filtering data features, which is found to be linked with biological meaning such as photosynthesis-related or kernel development-related regulations. Finally, by integrating multiple omics data with the RF machine learning approach, we can further improve the prediction accuracy of grain yield from 0.32 to 0.43. Our research provides new ideas for the application of plant omics data and artificial intelligence approaches to facilitate crop genetic improvements.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-024-01454-z.

Metabolic GWAS-based dissection of genetic basis underlying nutrient quality variation and domestication of cassava storage root

BACKGROUND

Metabolites play critical roles in regulating nutritional qualities of plants, thereby influencing their consumption and human health. However, the genetic basis underlying the metabolite-based nutrient quality and domestication of root and tuber crops remain largely unknown.

RESULTS

We report a comprehensive study combining metabolic and phenotypic genome-wide association studies to dissect the genetic basis of metabolites in the storage root (SR) of cassava. We quantify 2,980 metabolic features in 299 cultivated cassava accessions. We detect 18,218 significant marker-metabolite associations via metabolic genome-wide association mapping and identify 12 candidate genes responsible for the levels of metabolites that are of potential nutritional importance. Me3GT, MeMYB4, and UGT85K4/UGT85K5, which are involved in flavone, anthocyanin, and cyanogenic glucoside metabolism, respectively, are functionally validated through in vitro enzyme assays and in vivo gene silencing analyses. We identify a cluster of cyanogenic glucoside biosynthesis genes, among which CYP79D1, CYP71E7b, and UGT85K5 are highly co-expressed and their allelic combination contributes to low linamarin content. We find MeMYB4 is responsible for variations in cyanidin 3-O-glucoside and delphinidin 3-O-rutinoside contents, thus controlling SR endothelium color. We find human selection affects quercetin 3-O-glucoside content and SR weight per plant. The candidate gene MeFLS1 is subject to selection during cassava domestication, leading to decreased quercetin 3-O-glucoside content and thus increased SR weight per plant.

CONCLUSIONS

These findings reveal the genetic basis of cassava SR metabolome variation, establish a linkage between metabolites and agronomic traits, and offer useful resources for genetically improving the nutrition of cassava and other root crops.

Plant Metabolomics: Current Initiatives and Future Prospects

Plant metabolomics is a rapidly advancing field of plant sciences and systems biology. It involves comprehensive analyses of small molecules (metabolites) in plant tissues and cells. These metabolites include a wide range of compounds, such as sugars, amino acids, organic acids, secondary metabolites (e.g., alkaloids and flavonoids), lipids, and more. Metabolomics allows an understanding of the functional roles of specific metabolites in plants' physiology, development, and responses to biotic and abiotic stresses. It can lead to the identification of metabolites linked with specific traits or functions. Plant metabolic networks and pathways can be better understood with the help of metabolomics. Researchers can determine how plants react to environmental cues or genetic modifications by examining how metabolite profiles change under various crop stages. Metabolomics plays a major role in crop improvement and biotechnology. Integrating metabolomics data with other omics data (genomics, transcriptomics, and proteomics) provides a more comprehensive perspective of plant biology. This systems biology approach enables researchers to understand the complex interactions within organisms.

Quantifying the impact of dynamic plant-environment interactions on metabolic regulation

A plant's genome encodes enzymes, transporters and many other proteins which constitute metabolism. Interactions of plants with their environment shape their growth, development and resilience towards adverse conditions. Although genome sequencing technologies and applications have experienced triumphantly rapid development during the last decades, enabling nowadays a fast and cheap sequencing of full genomes, prediction of metabolic phenotypes from genotype × environment interactions remains, at best, very incomplete. The main reasons are a lack of understanding of how different levels of molecular organisation depend on each other, and how they are constituted and expressed within a setup of growth conditions. Phenotypic plasticity, e.g., of the genetic model plant Arabidopsis thaliana, has provided important insights into plant-environment interactions and the resulting genotype x phenotype relationships. Here, we summarize previous and current findings about plant development in a changing environment and how this might be shaped and reflected in metabolism and its regulation. We identify current challenges in the study of plant development and metabolic regulation and provide an outlook of how methodological workflows might support the application of findings made in model systems to crops and their cultivation.

Non-targeted metabolomics analysis of metabolite changes in two quinoa genotypes under drought stress

BACKGROUND

Quinoa is an important economic crop, drought is one of the key factors affecting quinoa yield. Clarifying the adaptation strategy of quinoa to drought is conducive to cultivating drought-tolerant varieties. At present, the study of quinoa on drought stress-related metabolism and the identification of related metabolites are still unknown. As a direct feature of biochemical functions, metabolites can reveal the biochemical pathways involved in drought response.

RESULT

Here, we studied the physiological and metabolic responses of drought-tolerant genotype L1 and sensitive genotype HZ1. Under drought conditions, L1 had higher osmotic adjustment ability and stronger root activity than HZ1, and the relative water content of L1 was also higher than that of HZ1. In addition, the barrier-to- sea ratio of L1 is significantly higher than that of HZ1. Using untargeted metabolic analysis, a total of 523, 406, 301 and 272 differential metabolites were identified in L1 and HZ1 on day 3 and day 9 of drought stress. The key metabolites (amino acids, nucleotides, peptides, organic acids, lipids and carbohydrates) accumulated differently in quinoa leaves. and HZ1 had the most DEMs in Glycerophospholipid metabolism (ko00564) and ABC transporters (ko02010) pathways.

CONCLUSION

These results provide a reference for characterizing the response mechanism of quinoa to drought and improving the drought tolerance of quinoa.

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.

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.

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.

Natural variation of respiration-related traits in plants

Plant respiration is one of the greatest global metabolic fluxes, but rates of respiration vary massively both within different cell types as well as between different individuals and different species. Whilst this is well known, few studies have detailed population-level variation of respiration until recently. The last 20 years have seen a renaissance in studies of natural variance. In this review, we describe how experimental breeding populations and collections of large populations of accessions can be used to determine the genetic architecture of plant traits. We further detail how these approaches have been used to study the rate of respiration per se as well as traits that are intimately associated with respiration. The review highlights specific breakthroughs in these areas but also concludes that the approach should be more widely adopted in the study of respiration per se as opposed to the more frequently studied respiration-related traits.

QTL analysis of important agronomic traits and metabolites in foxtail millet (Setaria italica) by RIL population and widely targeted metabolome

As a bridge between genome and phenotype, metabolome is closely related to plant growth and development. However, the research on the combination of genome, metabolome and multiple agronomic traits in foxtail millet (Setaria italica) is insufficient. Here, based on the linkage analysis of 3,452 metabolites via with high-quality genetic linkage maps, we detected a total of 1,049 metabolic quantitative trait loci (mQTLs) distributed in 11 hotspots, and 28 metabolite-related candidate genes were mined from 14 mQTLs. In addition, 136 single-environment phenotypic QTL (pQTLs) related to 63 phenotypes were identified by linkage analysis, and there were 12 hotspots on these pQTLs. We futher dissected 39 candidate genes related to agronomic traits through metabolite-phenotype correlation and gene function analysis, including Sd1 semidwarf gene, which can affect plant height by regulating GA synthesis. Combined correlation network and QTL analysis, we found that flavonoid-lignin pathway maybe closely related to plant architecture and yield in foxtail millet. For example, the correlation coefficient between apigenin 7-rutinoside and stem diameter reached 0.98, and they were co-located at 41.33-44.15 Mb of chromosome 5, further gene function analysis revealed that 5 flavonoid pathway genes, as well as Sd1, were located in this interval . Therefore, the correlation and co-localization between flavonoid-lignins and plant architecture may be due to the close linkage of their regulatory genes in millet. Besides, we also found that a combination of genomic and metabolomic for BLUP analysis can better predict plant agronomic traits than genomic or metabolomic data, independently. In conclusion, the combined analysis of mQTL and pQTL in millet have linked genetic, metabolic and agronomic traits, and is of great significance for metabolite-related molecular assisted breeding.

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.

Metabolism of crown tissue is crucial for drought tolerance and recovery after stress cessation in Lolium/Festuca forage grasses

A process of plant recovery after drought cessation is a complex trait which has not been fully recognized. The most important organ associated with this phenomenon in monocots, including forage grasses, is the crown tissue located between shoots and roots. The crown tissue is a meristematic crossroads for metabolites and other compounds between these two plant organs. Here, for the first time, we present a metabolomic and lipidomic study focused on the crown tissue under drought and recovery in forage grasses, important for agriculture in European temperate regions. The plant materials involve high (HDT) and low drought-tolerant (LDT) genotypes of Festuca arundinacea, and Lolium multiflorum/F. arundinacea introgression forms. The obtained results clearly demonstrated that remodeling patterns of the primary metabolome and lipidome in the crown under drought and recovery were different between HDT and LDT plants. Furthermore, HDT plants accumulated higher contents of primary metabolites under drought in the crown tissue, especially carbohydrates which could function as osmoprotectants and storage materials. On the other hand, LDT plants characterized by higher membranes damage under drought, simultaneously accumulated membrane phospholipids in the crown and possessed the capacity to recover their metabolic functions after stress cessation to the levels observed in HDT plants.

Foliar Pathogen Infection Manipulates Soil Health through Root Exudate-Modified Rhizosphere Microbiome

Negative plant-soil feedback (NPSF) due to the buildup of soilborne pathogens in soil is a major obstacle in sustainable agricultural systems. Beneficial rhizosphere microfloras are recruited by plants, and mediating this has become a strategic priority to manipulate plant health. Here, we found that foliar infection of Panax notoginseng by Alternaria panax changed plant-soil feedback from negative to positive. Foliar infection modified the rhizosphere soil microbial community and reversed the direction of the buildup of the soilborne pathogen Ilyonectria destructans and beneficial microbes, including Trichoderma, Bacillus, and Streptomyces, in rhizosphere soil. These beneficial microbes not only showed antagonistic ability against the pathogen I. destructans but also enhanced the resistance of plants to A. panax. Foliar infection enhanced the exudation of short- and long-chain organic acids, sugars, and amino acids from roots. In vitro and in vivo experiments validated that short- and long-chain organic acids and sugars play dual roles in simultaneously suppressing pathogens but enriching beneficial microbes. In summary, foliar infection could change root secretion to drive shifts in the rhizosphere microbial community to enhance soil health, providing a new strategy to alleviate belowground disease in plants through aboveground inducement. IMPORTANCE Belowground soilborne disease is the main factor limiting sustainable agricultural production and is difficult to manage due to the complexity of the soil environment. Here, we found that aboveground parts of plants infected by foliar pathogens could enhance the secretion of organic acids, sugars, and amino acids in root exudates to suppress soilborne pathogens and enrich beneficial microbes, eventually changing the plant and soil feedback from negative to positive and alleviating belowground soilborne disease. This is an exciting strategy by which to achieve belowground soilborne disease management by manipulating the aboveground state through aboveground stimulation.

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.

Lipidomics-Assisted GWAS (lGWAS) Approach for Improving High-Temperature Stress Tolerance of Crops

High-temperature stress (HT) over crop productivity is an important environmental factor demanding more attention as recent global warming trends are alarming and pose a potential threat to crop production. According to the Sixth IPCC report, future years will have longer warm seasons and frequent heat waves. Thus, the need arises to develop HT-tolerant genotypes that can be used to breed high-yielding crops. Several physiological, biochemical, and molecular alterations are orchestrated in providing HT tolerance to a genotype. One mechanism to counter HT is overcoming high-temperature-induced membrane superfluidity and structural disorganizations. Several HT lipidomic studies on different genotypes have indicated the potential involvement of membrane lipid remodelling in providing HT tolerance. Advances in high-throughput analytical techniques such as tandem mass spectrometry have paved the way for large-scale identification and quantification of the enormously diverse lipid molecules in a single run. Physiological trait-based breeding has been employed so far to identify and select HT tolerant genotypes but has several disadvantages, such as the genotype-phenotype gap affecting the efficiency of identifying the underlying genetic association. Tolerant genotypes maintain a high photosynthetic rate, stable membranes, and membrane-associated mechanisms. In this context, studying the HT-induced membrane lipid remodelling, resultant of several up-/down-regulations of genes and post-translational modifications, will aid in identifying potential lipid biomarkers for HT tolerance/susceptibility. The identified lipid biomarkers (LIPIDOTYPE) can thus be considered an intermediate phenotype, bridging the gap between genotype–phenotype (genotype–LIPIDOTYPE–phenotype). Recent works integrating metabolomics with quantitative genetic studies such as GWAS (mGWAS) have provided close associations between genotype, metabolites, and stress-tolerant phenotypes. This review has been sculpted to provide a potential workflow that combines MS-based lipidomics and the robust GWAS (lipidomics assisted GWAS-lGWAS) to identify membrane lipid remodelling related genes and associations which can be used to develop HS tolerant genotypes with enhanced membrane thermostability (MTS) and heat stable photosynthesis (HP).

Comparative Tolerance Levels of Maize Landraces and a Hybrid to Natural Infestation of Fall Armyworm

Simple Summary

Exploiting the tolerance of plants against herbivorous insects is a viable pest management alternative, especially where conventional controls are ineffective. For example, due to the inefficacy of currently adopted practices, new strategies and methods are needed for Spodoptera frugiperda management in maize. This study evaluated the tolerance levels of maize landraces and a conventional hybrid under natural infestation of S. frugiperda. We found promising sources of tolerance among the landraces, evident as tolerance indices that varied across the landraces and hybrid we evaluated.

Abstract

Insect pests such as Spodoptera frugiperda cause significant losses to maize (Zea mays mays). Control of S. frugiperda is difficult, but the use of insect resistant cultivars, including tolerant cultivars, is a promising alternative, and landraces are a potential source of insect resistance. This study investigated tolerance to S. frugiperda in five Brazilian landraces, Amarelão, Aztequinha, Branco Antigo, Palha Roxa, and São Pedro, in relation to one conventional (non-Bt) hybrid, BM207, under field conditions. We assessed tolerance as the ratio of insecticide-free to insecticide-protected plants for plant height, stem diameter, and leaf chlorophyll content at two plant stages. Tolerance ratios varied across the maize genotypes, but inconsistently across plant variables, and cluster analysis revealed three groups based on tolerance ratios. A first group contained genotypes similarly tolerant to S. frugiperda, BM207, Palha Roxa, São Pedro, and Aztequinha, while the second and third groups each contained single genotypes, Amarelão, and Branco Antigo, which were considered not tolerant. Overall, the landraces Palha Roxa, São Pedro, and Aztequinha compared favorably to BM207 in terms of tolerance, and therefore may be valuable for management of this pest, and as germplasm sources to improve tolerance in other cultivars.

'Omics' approaches in developing combined drought and heat tolerance in food crops

Global climate change will significantly increase the intensity and frequency of hot, dry days. The simultaneous occurrence of drought and heat stress is also likely to increase, influencing various agronomic characteristics, such as biomass and other growth traits, phenology, and yield-contributing traits, of various crops. At the same time, vital physiological traits will be seriously disrupted, including leaf water content, canopy temperature depression, membrane stability, photosynthesis, and related attributes such as chlorophyll content, stomatal conductance, and chlorophyll fluorescence. Several metabolic processes contributing to general growth and development will be restricted, along with the production of reactive oxygen species (ROS) that negatively affect cellular homeostasis. Plants have adaptive defense strategies, such as ROS-scavenging mechanisms, osmolyte production, secondary metabolite modulation, and different phytohormones, which can help distinguish tolerant crop genotypes. Understanding plant responses to combined drought/heat stress at various organizational levels is vital for developing stress-resilient crops. Elucidating the genomic, proteomic, and metabolic responses of various crops, particularly tolerant genotypes, to identify tolerance mechanisms will markedly enhance the continuing efforts to introduce combined drought/heat stress tolerance. Besides agronomic management, genetic engineering and molecular breeding approaches have great potential in this direction.

Metabolomics and Molecular Approaches Reveal Drought Stress Tolerance in Plants

Metabolic regulation is the key mechanism implicated in plants maintaining cell osmotic potential under drought stress. Understanding drought stress tolerance in plants will have a significant impact on food security in the face of increasingly harsh climatic conditions. Plant primary and secondary metabolites and metabolic genes are key factors in drought tolerance through their involvement in diverse metabolic pathways. Physio-biochemical and molecular strategies involved in plant tolerance mechanisms could be exploited to increase plant survival under drought stress. This review summarizes the most updated findings on primary and secondary metabolites involved in drought stress. We also examine the application of useful metabolic genes and their molecular responses to drought tolerance in plants and discuss possible strategies to help plants to counteract unfavorable drought periods.

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.

An integrated transcriptome and metabolome approach reveals the accumulation of taste-related metabolites and gene regulatory networks during watermelon fruit development

Accumulation patterns and gene regulatory networks of sugars and cucurbitacins and related primary and secondary metabolites during cultivated watermelon 'Cheng Lan' and wild watermelon 'PI 632,751' fruit development were identified. Metabolites are the end products of cellular regulatory processes and play important roles in fruit taste formation. However, comprehensive studies on the accumulation patterns of watermelon fruit metabolites and transcriptional regulatory networks are still scarce. In this study, 451 annotated metabolites were identified at four key fruit developmental stages in wild watermelon 'PI 632,751' and modern cultivated watermelon 'Cheng Lan'. Interestingly, 11 sugars and 25 major primary metabolites were mainly accumulated in 'Cheng Lan' during fruit development, which are considered to be the potential metabolites beneficial to the formation of watermelon taste. Cucurbitacins and the main flavonoids were mainly specifically accumulated in 'PI 632,751', not being considered to be responsible for the taste. Moreover, forty-seven genes involved in carbohydrate metabolism, glycolysis, and TCA cycle were highly expressed in 'Cheng Lan', which was positively correlated with the accumulation of major primary metabolites. Alternatively, seven UDP-glycosyltransferase genes are closely related to the glycosylation of cucurbitacins through co-expression analysis. Our findings established a global map of metabolite accumulation and gene regulation during fruit development in wild and cultivated watermelons and provided valuable information on taste formation in watermelon fruit.

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).

Genetic Improvement in Sunflower Breeding—Integrated Omics Approach

Foresight in climate change and the challenges ahead requires a systematic approach to sunflower breeding that will encompass all available technologies. There is a great scarcity of desirable genetic variation, which is in fact undiscovered because it has not been sufficiently researched as detection and designing favorable genetic variation largely depends on thorough genome sequencing through broad and deep resequencing. Basic exploration of genomes is insufficient to find insight about important physiological and molecular mechanisms unique to crops. That is why integrating information from genomics, epigenomics, transcriptomics, proteomics, metabolomics and phenomics enables a comprehensive understanding of the molecular mechanisms in the background of architecture of many important quantitative traits. Omics technologies offer novel possibilities for deciphering the complex pathways and molecular profiling through the level of systems biology and can provide important answers that can be utilized for more efficient breeding of sunflower. In this review, we present omics profiling approaches in order to address their possibilities and usefulness as a potential breeding tools in sunflower genetic improvement.

Comparative Metabolite Profile, Biological Activity and Overall Quality of Three Lettuce (Lactuca sativa L., Asteraceae) Cultivars in Response to Sulfur Nutrition

The main objective of the present study was to assess the effects of sulfur (S) nutrition on plant growth, overall quality, secondary metabolites, and antibacterial and radical scavenging activities of hydroponically grown lettuce cultivars. Three lettuce cultivars, namely, Pazmanea RZ (green butterhead, V1), Hawking RZ (green multi-leaf lettuce, V2), and Barlach RZ (red multi-leaf, V3) were subjected to two S-treatments in the form of magnesium sulfate (+S) or magnesium chloride (-S). Significant differences were observed under -S treatments, especially among V1 and V2 lettuce cultivars. These responses were reflected in the yield, levels of macro- and micro-nutrients, water-soluble sugars, and free inorganic anions. In comparison with the green cultivars (V1 and V2), the red-V3 cultivar revealed a greater acclimation to S starvation, as evidenced by relative higher plant growth. In contrast, the green cultivars showed higher capabilities in production and superior quality attributes under +S condition. As for secondary metabolites, sixteen compounds (e.g., sesquiterpene lactones, caffeoyl derivatives, caffeic acid hexose, 5-caffeoylquinic acid (5-OCQA), quercetin and luteolin glucoside derivatives) were annotated in all three cultivars with the aid of HPLC-DAD-MS-based untargeted metabolomics. Sesquiterpene lactone lactucin and anthocyanin cyanidin 3-O-galactoside were only detected in V1 and V3 cultivars, respectively. Based on the analyses, the V3 cultivar was the most potent radical scavenger, while V1 and V2 cultivars exhibited antibacterial activity against Staphylococcus aureus in response to S provision. Our study emphasizes the critical role of S nutrition in plant growth, acclimation, and nutritional quality. The judicious-S application can be adopted as a promising antimicrobial prototype for medical applications.

Metabolic profiling for dissection of late leaf spot disease resistance mechanism in groundnut

Late leaf spot (LLS) caused by fungi Passalora personata is generally more destructive and difficult to control than early leaf spot. The aim of this study was to decipher biochemical defense mechanism in groundnut genotypes against P. personata by identifying resistance specific biomarkers and metabolic pathways induced during host-pathogen interaction. Metabolomics of non-infected and infected leaves of moderately resistant (GPBD4 and ICGV86590), resistant (KDG128 and RHRG06083) and susceptible (GG20, JL24 and TMV2) genotypes was carried out at 5 days after infection (65 days after sowing). Non-targeted metabolite analysis using GC-MS revealed total 77 metabolites including carbohydrates, sugar alcohols, amino acids, fatty acids, polyamines, phenolics, terpenes and sterols. Variable importance in projection (VIP) measure of partial least squares-discriminant analysis (PLS-DA) showed that resistant and moderately resistant genotypes possessed higher intensities of ribonic acid, cinnamic acid, malic acid, squalene, xylulose, galactose, fructose, glucose, β-amyrin and hydroquinone while susceptible genotypes had higher amount of gluconic acid 2-methoxime, ribo-hexose-3-ulose and gluconic acid. Heat map analysis showed that resistant genotypes had higher intensities of β-amyrin, hydroquinone in non-infected and malic acid, squalene, putrescine and 2,3,4-trihydroxybutyric acid in infected leaves. Dendrogram analysis further separated resistant genotypes in the same cluster along with infected moderately resistant genotypes. The most significant pathways identified are: linoleic acid metabolism, flavone and flavonol biosynthesis, cutin, suberin and wax biosynthesis, pentose and glucuronate interconversions, starch and sucrose metabolism, stilbenoid biosynthesis and ascorbate and aldarate metabolism. Targeted metabolite analysis further confirmed that resistant genotypes possessed higher content of primary metabolites sucrose, glucose, fructose, malic acid and citric acid. Moreover, resistant genotypes possessed higher content of salicylic, coumaric, ferulic, cinnamic, gallic acid (phenolic acids) and kaempferol, quercetin and catechin (flavonols). Thus metabolites having higher accumulation in resistant genotypes can be used as biomarkers for screening of LSS resistant germplasm. These results unravel that higher amount of primary metabolites leads to stimulate the accumulation of more amounts of secondary metabolites such as phenolic acid, flavanols, stilbenes and terpenoids (squalene and β-amyrin) biosynthesis which are ultimately involved in defense mechanism against LLS pathogen.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s12298-021-00985-5.

Delineation of mechanistic approaches employed by plant growth promoting microorganisms for improving drought stress tolerance in plants

Drought stress is expected to increase in intensity, frequency, and duration in many parts of the world, with potential negative impacts on plant growth and productivity. The plants have evolved complex physiological and biochemical mechanisms to respond and adjust to water-deficient environments. The physiological and biochemical mechanisms associated with water-stress tolerance and water-use efficiency have been extensively studied. Besides these adaptive and mitigating strategies, the plant growth-promoting rhizobacteria (PGPR) play a significant role in alleviating plant drought stress. These beneficial microorganisms colonize the endo-rhizosphere/rhizosphere of plants and enhance drought tolerance. The common mechanism by which these microorganisms improve drought tolerance included the production of volatile compounds, phytohormones, siderophores, exopolysaccharides, 1-aminocyclopropane-1-carboxylate deaminase (ACC deaminase), accumulation of antioxidant, stress-induced metabolites such as osmotic solutes proline, alternation in leaf and root morphology and regulation of the stress-responsive genes. The PGPR is an easy and efficient alternative approach to genetic manipulation and crop enhancement practices because plant breeding and genetic modification are time-consuming and expensive processes for obtaining stress-tolerant varieties. In this review, we will elaborate on PGPR's mechanistic approaches in enhancing the plant stress tolerance to cope with the drought stress.

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.

Comparison of Metabolic Profiling of Arabidopsis Inflorescences Between Landsberg erecta and Columbia, and Meiosis-Defective Mutants by 1H-NMR Spectroscopy

With the rapid development of omics technologies during the last several decades, genomics, transcriptomics, and proteomics have been extensively used to characterize gene or protein functions in many organisms at the cell or tissue level. However, metabolomics has not been conducted in reproductive organs, with a focus on meiosis in plants. In this study, we adopted a nuclear magnetic resonance (NMR)-based metabolomics approach to reveal the metabolic profile of inflorescences from two Arabidopsis accessions, Columbia (Col) and Landsberg erecta (Ler), and several sterile mutants caused by meiosis defects. We identified 68 dominant metabolites in the samples. Col and Ler displayed distinct metabolite profiles. Interestingly, mutants with similar meiotic defects, such as Atrad51-3, Atrfc1-2, and Atpol2a-2, exhibited similar alterations in metabolites, including upregulation of energy metabolites and promotion of compounds related to maintenance of genomic stability, cytoplasmic homeostasis, and membrane integrity. The collective data reveal distinct changes in metabolites in Arabidopsis inflorescences between the Col and Ler wild type accessions. NMR-based metabolomics could be an effective tool for molecular phenotyping in studies of aspects of plant reproductive development such as meiosis.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s43657-021-00012-3.

Ancestral sequence reconstruction - An underused approach to understand the evolution of gene function in plants?

Whilst substantial research effort has been placed on understanding the interactions of plant proteins with their molecular partners, relatively few studies in plants - by contrast to work in other organisms - address how these interactions evolve. It is thought that ancestral proteins were more promiscuous than modern proteins and that specificity often evolved following gene duplication and subsequent functional refining. However, ancestral protein resurrection studies have found that some modern proteins have evolved de novo from ancestors lacking those functions. Intriguingly, the new interactions evolved as a consequence of just a few mutations and, as such, acquisition of new functions appears to be neither difficult nor rare, however, only a few of them are incorporated into biological processes before they are lost to subsequent mutations. Here, we detail the approach of ancestral sequence reconstruction (ASR), providing a primer to reconstruct the sequence of an ancestral gene. We will present case studies from a range of different eukaryotes before discussing the few instances where ancestral reconstructions have been used in plants. As ASR is used to dig into the remote evolutionary past, we will also present some alternative genetic approaches to investigate molecular evolution on shorter timescales. We argue that the study of plant secondary metabolism is particularly well suited for ancestral reconstruction studies. Indeed, its ancient evolutionary roots and highly diverse landscape provide an ideal context in which to address the focal issue around the emergence of evolutionary novelties and how this affects the chemical diversification of plant metabolism.

Metabolomics Intervention Towards Better Understanding of Plant Traits

The majority of the most economically important plant and crop species are enriched with the availability of high-quality reference genome sequences forming the basis of gene discovery which control the important biochemical pathways. The transcriptomics and proteomics resources have also been made available for many of these plant species that intensify the understanding at expression levels. However, still we lack integrated studies spanning genomics–transcriptomics–proteomics, connected to metabolomics, the most complicated phase in phenotype expression. Nevertheless, for the past few decades, emphasis has been more on metabolome which plays a crucial role in defining the phenotype (trait) during crop improvement. The emergence of modern high throughput metabolome analyzing platforms have accelerated the discovery of a wide variety of biochemical types of metabolites and new pathways, also helped in improving the understanding of known existing pathways. Pinpointing the causal gene(s) and elucidation of metabolic pathways are very important for development of improved lines with high precision in crop breeding. Along with other-omics sciences, metabolomics studies have helped in characterization and annotation of a new gene(s) function. Hereby, we summarize several areas in the field of crop development where metabolomics studies have made its remarkable impact. We also assess the recent research on metabolomics, together with other omics, contributing toward genetic engineering to target traits and key pathway(s).

Genetic analysis of maize shank length by QTL mapping in three recombinant inbred line populations

In maize, the shank is a unique tissue linking the stem to the ear. Shank length (SL) mainly affects the transport of photosynthetic products to the ear and the dehydration of kernels via regulated husk morphology. The limited studies on SL revealed it is a highly heritable quantitative trait controlled by significant additive and additive-dominance effects. However, the genetic basis of SL remains unclear. In this study, we analyzed three maize recombinant inbred line (RIL) populations to elucidate the molecular mechanism underlying the SL. The data indicated the SL varied among the three RIL populations and was highly heritable. Additionally, the SL was positively correlated with the husk length (HL), husk number (HN), ear length (EL), and ear weight (EW) in the BY815/K22 (BYK) and CI7/K22 (CIK) RIL populations, but was negatively correlated with the husk width (HW) in the BYK RIL population. Moreover, 10 quantitative trait loci (QTL) for SL were identified in the three RIL populations, five of which were large-effect QTL. The percentage of the total phenotypic variation explained by the QTL for SL was 13.67 %, 20.45 %, and 30.81 % in the BY815/DE3 (BYD), BYK, and CIK RIL populations, respectively. Further analyses uncovered some genetic overlap between SL and EL, SL and ear row number (ERN), SL and cob weight (CW), and SL and HN. Unlike the large-effect QTL qSL BYK-2-2, which spanned the centromere, the other four large-effect QTL were delimited to a single peak bin via bin map. Furthermore, 2, 5, 6, and 12 genes associated with SL were identified for qSL BYK-2-1, qSL CIK-2-1, qSL CIK-9-1, and qSL CIK-9-2, respectively. Five of the candidate genes for SL may contribute to the hormone metabolism and sphingolipid biosynthesis regulating cell elongation, division, differentiation, and expansion. These results may be relevant for future studies on the genetic basis of SL and for the molecular breeding of maize based on marker-assisted selection to develop new varieties with an ideal SL.

Comparative Metabolomic Profiling of Citrullus spp. Fruits Provides Evidence for Metabolomic Divergence during Domestication

Watermelon (Citrullus lanatus) is one of the most nutritional fruits that is widely distributed in the whole world. The nutritional compositions are mainly influenced by the genotype and environment. However, the metabolomics of different domestication status and different flesh colors watermelon types is not fully understood. In this study, we reported an extensive assessment of metabolomic divergence in the fruit flesh among Citrullus sp. and within Citrullus sp. We demonstrate that metabolic profiling was significantly different between the wild and cultivated watermelons, the apigenin 6-C-glucoside, luteolin 6-C-glucoside, chrysoeriol C-hexoside, naringenin C-hexoside, C-pentosyl-chrysoeriol O-hexoside, and sucrose are the main divergent metabolites. Correlation analysis results revealed that flavonoids were present in one tight metabolite cluster. The main divergent metabolites in different flesh-colored cultivated watermelon fruits are p-coumaric acid, 2,3-dihydroflavone, catechin, N-(3-indolylacetyl)-l-alanine, 3,4-dihydroxycinnamic acid, and pelargonidin o-hexoside. A total of 431 differentially accumulated metabolites were identified from pairwise comparative analyses. C. lanatus edible-seed watermelon (cultivars) and C. mucosospermus (wild) have similar fruit metabolic profiles and phenotypic traits, indicating that edible-seed watermelon may be a relative of wild species and a relatively primitive differentiation type of cultivated watermelon. Our data provide extensive knowledge for metabolomics-based watermelon improvement of Citrullus fruits meet their enhanced nutritive properties or upgraded germplasm utility values.

Metabolomic Analysis of Natural Variation in Arabidopsis

Methodological advances in coupled-mass spectrometry (gas chromatography and liquid chromatography; GC-MS and LC-MS) have rendered the profiling of highly complex plant extracts relatively facile and allowed that their high-throughput use aids the investigation of a range of biological questions. Among these is the elucidation of the genetic factors underlying metabolite abundance. For this purpose genome-wide association studies (GWAS) are being widely adopted in Arabidopsis with the resultant quantitative trait loci being subjected to cross-validation by the use of recombinant inbred lines, introgression lines, and T-DNA insertional knockout lines.

Using Metabolomics to Assist Plant Breeding

Recent methodological advances in both gas chromatography-mass spectrometry (GC-MS) and liquid chromatography-mass spectrometry (LC-MS) have provided a deep understanding of metabolic regulation occurring in plant cells. The application of these techniques to agricultural systems is, however, subject to more complex interactions. Here we summarize a step-by-step modern metabolomics methodology that generates metabolome data toward the implementation of metabolomics in crop breeding. We describe a metabolic workflow, and provide guidelines for handling large sample numbers for the specific purpose of metabolic quantitative trait loci approaches.

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.

Genetic Variance of Metabolomic Features and Their Relationship With Malting Quality Traits in Spring Barley

Barley is the most common source for malt to be used in brewing beer and other alcoholic beverages. This involves converting the starch of barley into fermentable sugars a process that involves malting, that is germinating of the grains, and mashing, which is an enzymatic process. Numerous metabolic processes are involved in germination, where distinct and time-dependent alterations at the metabolite levels happen. In this study, 2,628 plots of 565 spring malting barley lines from Nordic Seed A/S were investigated. Phenotypic records were available for six malting quality (MQ) traits: filtering speed (FS), wort clearness (WCL), extract yield (EY), wort color (WCO), beta glucan (BG), and wort viscosity (WV). Each line had a set of dense genomic markers. In addition, 24,018 metabolomic features (MFs) were obtained for each sample from nuclear magnetic resonance (NMR) spectra for wort samples produced from each experimental plot. The genetic variation in the MFs was investigated using a univariate model, and the relationship between MFs and the MQ traits was studied using a bivariate model. Results showed that a total of 8,604 MFs had heritability estimates significantly larger than 0 and for all MQ traits, there were genetic correlations with up to 86.77% and phenotypic correlations with up to 90.07% of the significant heritable MFs. In conclusion, around one third of all MFs were significantly heritable, among which a considerable proportion had significant additive genetic and/or phenotypic correlations with the MQ traits (WCO, WV, and BG) in spring barley. The results from this study indicate that many of the MFs are heritable and MFs have great potential to be used in breeding barley for high MQ.

Microalgae as Potential Anti-Inflammatory Natural Product Against Human Inflammatory Skin Diseases

The skin is the first line of defense against pathogen and other environmental pollutant. The body is constantly exposed to reactive oxygen species (ROS) that stimulates inflammatory process in the skin. Many studies have linked ROS to various inflammatory skin diseases. Patients with skin diseases face various challenges with inefficient and inappropriate treatment in managing skin diseases. Overproduction of ROS in the body will result in oxidative stress which will lead to various cellular damage and alter normal cell function. Multiple signaling pathways are seen to have significant effects during ROS-mediated oxidative stress. In this review, microalgae have been selected as a source of natural-derived antioxidant to combat inflammatory skin diseases that are prominent in today’s society. Several studies have demonstrated that bioactive compounds isolated from microalgae have anti-inflammation and anti-oxidative properties that can help remedy various skin diseases. These compounds are able to inhibit production of pro-inflammatory cytokines and reduce the expression of inflammatory genes. Bioactive compounds from microalgae work in action by altering enzyme activities, regulating cellular activities, targeting major signaling pathways related to inflammation.

Three-dimensional genetic networks among seed oil-related traits, metabolites and genes reveal the genetic foundations of oil synthesis in soybean

Although the biochemical and genetic basis of lipid metabolism is clear in Arabidopsis, there is limited information concerning the relevant genes in Glycine max (soybean). To address this issue, we constructed three-dimensional genetic networks using six seed oil-related traits, 52 lipid metabolism-related metabolites and 54 294 SNPs in 286 soybean accessions in total. As a result, 284 and 279 candidate genes were found to be significantly associated with seed oil-related traits and metabolites by phenotypic and metabolic genome-wide association studies and multi-omics analyses, respectively. Using minimax concave penalty (MCP) and smoothly clipped absolute deviation (SCAD) analyses, six seed oil-related traits were found to be significantly related to 31 metabolites. Among the above candidate genes, 36 genes were found to be associated with oil synthesis (27 genes), amino acid synthesis (four genes) and the tricarboxylic acid (TCA) cycle (five genes), and four genes (GmFATB1a, GmPDAT, GmPLDα1 and GmDAGAT1) are already known to be related to oil synthesis. Using this information, 133 three-dimensional genetic networks were constructed, 24 of which are known, e.g. pyruvate-GmPDAT-GmFATA2-oil content. Using these networks, GmPDAT, GmAGT and GmACP4 reveal the genetic relationships between pyruvate and the three major nutrients, and GmPDAT, GmZF351 and GmPgs1 reveal the genetic relationships between amino acids and seed oil content. In addition, GmCds1, along with average temperature in July and the rainfall from June to September, influence seed oil content across years. This study provides a new approach for the construction of three-dimensional genetic networks and reveals new information for soybean seed oil improvement and the identification of gene function.

Metabolomics analysis reveals differences in evolution between maize and rice

Metabolites are the intermediate and final products of metabolism, which play essential roles in plant growth, evolution and adaptation to changing climates. However, it is unclear how evolution contributes to metabolic variation in plants. Here, we investigated the metabolomics data from leaf and seed tissues in maize and rice. Using principal components analysis based on leaf metabolites but not seed metabolites, metabolomics data could be clearly separated for rice Indica and Japonica accessions, while two maize subgroups, temperate and tropical, showed more visible admixture. Rice and maize seed exhibited significant interspecific differences in metabolic variation, while within rice, leaf and seed displayed similar metabolic variations. Among 10 metabolic categories, flavonoids had higher variation in maize than rice, indicating flavonoids are a key constituent of interspecific metabolic divergence. Interestingly, metabolic regulation was also found to be reshaped dramatically from positive to negative correlations, indicative of the differential evolutionary processes in maize and rice. Moreover, perhaps due to this divergence significantly more metabolic interactions were identified in rice than maize. Furthermore, in rice, the leaf was found to harbor much more intense metabolic interactions than the seed. Our result suggests that metabolomes are valuable for tracking evolutionary history, thereby complementing and extending genomic insights concerning which features are responsible for interspecific differentiation in maize and rice.