Integration of metabolome and transcriptome reveals flavonoid accumulation in the intergeneric hybrid between Brassica rapa and Raphanus sativus

Brassicaceae Mustards: Phytochemical Constituents, Pharmacological Effects, and Mechanisms of Action against Human Disease

The Brassicaceae genus consists of many economically important mustards of value for food and medicinal purposes, namely Asian mustard (Brassica juncea), ball mustard (Neslia paniculata), black mustard (B. nigra), garlic mustard (Alliaria petiolata), hedge mustard (Sisymbrium officinale), Asian hedge mustard (S. orientale), oilseed rape (B. napus), rapeseed (B. rapa), treacle mustard (Erysimum repandum), smooth mustard (S. erysimoides), white ball mustard (Calepina irregularis), white mustard (Sinapis alba), and Canola. Some of these are commercially cultivated as oilseeds to meet the global demand for a healthy plant-derived oil, high in polyunsaturated fats, i.e., B. napus and B. juncea. Other species are foraged from the wild where they grow on roadsides and as a weed of arable land, i.e., E. repandum and S. erysimoides, and harvested for medicinal uses. These plants contain a diverse range of bioactive natural products including sulfur-containing glucosinolates and other potentially valuable compounds, namely omega-3-fatty acids, terpenoids, phenylpropanoids, flavonoids, tannins, S-methyl cysteine sulfoxide, and trace-elements. Various parts of these plants and many of the molecules that are produced throughout the plant have been used in traditional medicines and more recently in the mainstream pharmaceutical and food industries. This study relates the uses of mustards in traditional medicines with their bioactive molecules and possible mechanisms of action and provides an overview of the current knowledge of Brassicaceae oilseeds and mustards, their phytochemicals, and their biological activities.

Potential Regulatory Networks and Heterosis for Flavonoid and Terpenoid Contents in Pak Choi: Metabolomic and Transcriptome Analyses

Pak choi exhibits a diverse color range and serves as a rich source of flavonoids and terpenoids. However, the mechanisms underlying the heterosis and coordinated regulation of these compounds-particularly isorhamnetin-remain unclear. This study involved three hybrid combinations and the detection of 528 metabolites from all combinations, including 26 flavonoids and 88 terpenoids, through untargeted metabolomics. Analysis of differential metabolites indicated that the heterosis for the flavonoid and terpenoid contents was parent-dependent, and positive heterosis was observed for isorhamnetin in the two hybrid combinations (SZQ, 002 and HMG, ZMG). Moreover, there was a high transcription level of flavone 3'-O-methyltransferase, which is involved in isorhamnetin biosynthesis. The third group was considered the ideal hybrid combination for investigating the heterosis of flavonoid and terpenoid contents. Transcriptome analysis identified a total of 12,652 DEGs (TPM > 1) in various groups that were used for comparison, and DEGs encoding enzymes involved in various categories, including "carotenoid bio-synthesis" and "anthocyanin biosynthesis", were enriched in the hybrid combination (SZQ, 002). Moreover, the category of anthocyanin biosynthesis also was enriched in the hybrid combination (HMG, ZMG). The flavonoid pathway demonstrated more differential metabolites than the terpenoid pathway did. The WGCNA demonstrated notable positive correlations between the dark-green modules and many flavonoids and terpenoids. Moreover, there were 23 ERF genes in the co-expression network (r ≥ 0.90 and p < 0.05). Thus, ERF genes may play a significant role in regulating flavonoid and terpenoid biosynthesis. These findings enhance our understanding of the heterosis and coordinated regulation of flavonoid and terpenoid biosynthesis in pak choi, offering insights for genomics-based breeding improvements.

Transcript annotation of Chinese sturgeon (Acipenser sinensis) using Iso-seq and RNA-seq data

Chinese sturgeon (Acipenser sinensis) is a critically endangered fish inhabiting the Yangtze River and Chinese coastal waters. Numerous research projects and conservation efforts have focused on artificial propagation and release to restore this endangered species. However, genomic and full-length transcriptomic sequencing of Chinese sturgeon has rarely been reported. In this study, a total of 10 Chinese sturgeon tissues were used for PacBio Iso-seq and RNA-seq analyses. A total of 19,538 full-length transcripts were obtained with sizes from 51 bp to 7,033 bp. Moreover, cluster analysis of gene families and phylogenetic analysis of 14 species were performed. Furthermore, lncRNAs and coding sequence (CDS) were identified in all Chinese sturgeon tissues. Finally, gene expression profiles and differentially expressed genes (DEGs) were analyzed among 10 tissues in Chinese sturgeon. Taken together, full-length transcripts and the gene expression profile from Chinese sturgeon tissues will provide gene sequences and expression information for future functional genomic study and be very helpful for comprehensive understanding of the genetic mechanism of endangerment in Chinese sturgeon.

Metabolites and Plant Hormones Related to the Resistance Response to Feeding Stimulation and Leaf Clipping Control in Chinese Pine (Pinus tabuliformis Carr.)

This experiment was conducted to define changes in metabolic pathways in response to mandibulate insect feeding and to provide a reference for further investigation of the molecular mechanisms underlying the development of conifer resistance. Chinese pine (Pinus tabuliformis Carr.) in good growth status in natural condition was chosen for stimulation by 10 pine caterpillars (Dendrolimus tabulaefomis Tsai et Liu) as feeding stimulation (FS), leaf clipping control (LCC) as mechanical damage, and CK group (with no treatment) (recorded as 0 h). The metabolome and total flavonoid content were measured in the needles at 0, 2, and 8 h after treatment. Plant hormones were measured with needles at 0, 0.5, 1, 1.5, 2, 4, 6, and 8 h after different treatments. The results show that a total of 30.8% flavonoids are identified by metabolomics analysis. Compared with leaf clipping control, feeding stimulation of Chinese pine caterpillars significantly induced the upregulation of metabolites in the flavonoid pathway in Chinese pine, and the plant hormones JA and IAA showed expression trends consistent with those of the metabolome. According to the biological processes of the four plant hormones involved, JA and SA are mostly involved in resistance formation, and in this study, both of them also have fluctuating expressions influenced by feeding stimulation, while the expressions of the growth-related hormones IAA and ABA have no significant changes at other time points except for 1 h after treatment. Thus, the flavonoid pathway is one of the main pathways involved in resistance formation in conifers, and JA and IAA are involved in the formation of resistance.

Metabolomic and transcriptomic study to understand changes in metabolic and immune responses in steers under heat stress

Heat stress (HS) damages livestock by adversely affecting physiological and immunological functions. However, fundamental understanding of the metabolic and immunological mechanisms in animals under HS remains elusive, particularly in steers. To understand the changes on metabolic and immune responses in steers under HS condition, we performed RNA-sequencing and proton nuclear magnetic resonance spectroscopy-based metabolomics on HS-free (THI value: 64.92 ± 0.56) and HS-exposed (THI value: 79.13 ± 0.56) Jersey steer (n = 8, body weight: 559.67 ± 32.72 kg). This study clarifies the metabolic changes in 3 biofluids (rumen fluid, serum, and urine) and the immune responses observed in the peripheral blood mononuclear cells of HS-exposed steers. This integrated approach allowed the discovery of HS-sensitive metabolic and immunological pathways. The metabolomic analysis indicated that HS-exposed steers showed potential HS biomarkers such as isocitrate, formate, creatine, and riboflavin (P < 0.05). Among them, there were several integrative metabolic pathways between rumen fluid and serum. Furthermore, HS altered mRNA expression and immune-related signaling pathways. A meta-analysis revealed that HS decreased riboflavin metabolism and the expression of glyoxylate and dicarboxylate metabolism-related genes. Moreover, metabolic pathways, such as the hypoxia-inducible factor-1 signaling pathway, were downregulated in immune cells by HS (P < 0.05). These findings, along with the datasets of pathways and phenotypic differences as potential biomarkers in steers, can support more in-depth research to elucidate the inter-related metabolic and immunological pathways. This would help suggest new strategies to ameliorate the effects of HS, including disease susceptibility and metabolic disorders, in Jersey steers.

Cross-kingdom transcriptomic trends in the evolution of hybrid gene expression

Hybridization is a route to speciation that occurs widely across the eukaryote tree of life. The success of allopolyploids (hybrid species with increased ploidy) and homoploid hybrids (with unchanged ploidy) is well documented. However, their formation and establishment is not straightforward, with a suite of near‐instantaneous and longer term biological repercussions faced by the new species. Central to these challenges is the rewiring of gene regulatory networks following the merger of distinct genomes inherited from both parental species. Research on the evolution of hybrid gene expression has largely involved studies on a single hybrid species or a few gene families. Here, we present the first standardized transcriptome‐wide study exploring the fates of genes following hybridization across three kingdoms: animals, plants and fungi. Within each kingdom, we pair an allopolyploid system with a closely related homoploid hybrid to decouple the influence of increased ploidy from genome merger. Genome merger, not changes in ploidy, has the greatest effect on posthybridization expression patterns across all study systems. Strikingly, we find that differentially expressed genes in parent species preferentially switch to more similar expression in hybrids across all kingdoms, likely as a consequence of regulatory trans‐acting cross‐talk within the hybrid nucleus. We also highlight the prevalence of gene loss or silencing among extremely differentially expressed genes in hybrid species across all kingdoms. These shared patterns suggest that the evolutionary process of hybridization leads to common high‐level expression outcomes, regardless of the particular species or kingdom.

Integration of Metabolomics and Transcriptomics for Investigating the Tolerance of Foxtail Millet (Setaria italica) to Atrazine Stress

Foxtail millet (Setaria italica) is a monotypic species widely planted in China. However, residual atrazine, a commonly used maize herbicide, in soil, is a major abiotic stress to millet. Here, we investigated atrazine tolerance in millet based on the field experiments, then obtained an atrazine-resistant variety (Gongai2, GA2) and an atrazine-sensitive variety (Longgu31, LG31). To examine the effects of atrazine on genes and metabolites in millet plants, we compared the transcriptomic and metabolomic profiles between GA2 and LG31 seedling leaves. The results showed that 2,208 differentially expressed genes (DEGs; 501 upregulated, 1,707 downregulated) and 192 differentially expressed metabolites (DEMs; 82 upregulated, 110 downregulate) were identified in atrazine-treated GA2, while in atrazine-treated LG31, 1,773 DEGs (761 upregulated, 1,012 downregulated) and 215 DEMs (95 upregulated, 120 downregulated) were identified. The bioinformatics analysis of DEGs and DEMs showed that many biosynthetic metabolism pathways were significantly enriched in GA2 and LG31, such as glutathione metabolism (oxiglutatione, γ-glutamylcysteine; GSTU6, GSTU1, GSTF1), amino acid biosynthesis (L-cysteine, N-acetyl-L-glutamic acid; ArgB, GS, hisC, POX1), and phenylpropanoid biosynthesis [trans-5-o-(4-coumaroyl)shikimate; HST, C3'H]. Meanwhile, the co-expression analysis indicated that GA2 plants had enhanced atrazine tolerance owing to improved glutathione metabolism and proline biosynthesis, and the enrichment of scopoletin may help LG31 plants resist atrazine stress. Herein, we screened an atrazine-resistant millet variety and generated valuable information that may deepen our understanding of the complex molecular mechanism underlying the response to atrazine stress in millet.

Computational analyses of mechanism of action (MoA): data, methods and integration

The elucidation of a compound's Mechanism of Action (MoA) is a challenging task in the drug discovery process, but it is important in order to rationalise phenotypic findings and to anticipate potential side-effects. Bioinformatic approaches, advances in machine learning techniques and the increasing deposition of high-throughput data in public databases have significantly contributed to recent advances in the field, but it is not straightforward to decide which data and methods are most suitable to use in a given case. In this review, we focus on these methods and data and their applications in generating MoA hypotheses for subsequent experimental validation. We discuss compound-specific data such as -omics, cell morphology and bioactivity data, as well as commonly used supplementary prior knowledge such as network and pathway data, and provide information on databases where this data can be accessed. In terms of methodologies, we discuss both well-established methods (connectivity mapping, pathway enrichment) as well as more developing methods (neural networks and multi-omics integration). Finally, we review case studies where the MoA of a compound was successfully suggested from computational analysis by incorporating multiple data modalities and/or methodologies. Our aim for this review is to provide researchers with insights into the benefits and drawbacks of both the data and methods in terms of level of understanding, biases and interpretation - and to highlight future avenues of investigation which we foresee will improve the field of MoA elucidation, including greater public access to -omics data and methodologies which are capable of data integration.

INTEGRATE: Model-based multi-omics data integration to characterize multi-level metabolic regulation

Metabolism is directly and indirectly fine-tuned by a complex web of interacting regulatory mechanisms that fall into two major classes. On the one hand, the expression level of the catalyzing enzyme sets the maximal theoretical flux level (i.e., the net rate of the reaction) for each enzyme-controlled reaction. On the other hand, metabolic regulation controls the metabolic flux through the interactions of metabolites (substrates, cofactors, allosteric modulators) with the responsible enzyme. High-throughput data, such as metabolomics and transcriptomics data, if analyzed separately, do not accurately characterize the hierarchical regulation of metabolism outlined above. They must be integrated to disassemble the interdependence between different regulatory layers controlling metabolism. To this aim, we propose INTEGRATE, a computational pipeline that integrates metabolomics and transcriptomics data, using constraint-based stoichiometric metabolic models as a scaffold. We compute differential reaction expression from transcriptomics data and use constraint-based modeling to predict if the differential expression of metabolic enzymes directly originates differences in metabolic fluxes. In parallel, we use metabolomics to predict how differences in substrate availability translate into differences in metabolic fluxes. We discriminate fluxes regulated at the metabolic and/or gene expression level by intersecting these two output datasets. We demonstrate the pipeline using a set of immortalized normal and cancer breast cell lines. In a clinical setting, knowing the regulatory level at which a given metabolic reaction is controlled will be valuable to inform targeted, truly personalized therapies in cancer patients.

Genome-wide unbalanced expression bias and expression level dominance toward Brassica oleracea in artificially synthesized intergeneric hybrids of Raphanobrassica

Raphanobrassica (RrRrCrCr, 2n = 4x = 36), which is generated by distant hybridization between the maternal parent Raphanus sativus (RsRs, 2n = 2x = 18) and the paternal parent Brassica oleracea (C°C°, 2n = 2x = 18), displays intermediate silique phenotypes compared to diploid progenitors. However, the hybrid shares much more similarities in silique phenotypes with those of B. oleracea than those of R. sativus. Strikingly, the silique of Raphanobrassica is obviously split into two parts. To investigate the gene expression patterns behind these phenomena, transcriptome analysis was performed on the upper, middle, and lower sections of pods (RCsiu, RCsim, and RCsil), seeds in the upper and lower sections of siliques (RCseu and RCsel) from Raphanobrassica, whole pods (Rsi and Csi) and all seeds in the siliques (Rse and Cse) from R. sativus and B. oleracea. Transcriptome shock was observed in all five aforementioned tissues of Raphanobrassica. Genome-wide unbalanced biased expression and expression level dominance were also discovered, and both of them were toward B. oleracea in Raphanobrassica, which is consistent with the observed phenotypes. The present results reveal the global gene expression patterns of different sections of siliques of Raphanobrassica, pods, and seeds of B. oleracea and R. sativus, unraveling the tight correlation between global gene expression patterns and phenotypes of the hybrid and its parents.

Epigenetics and the success of invasive plants

Biological invasions impose ecological and economic problems on a global scale, but also provide extraordinary opportunities for studying contemporary evolution. It is critical to understand the evolutionary processes that underly invasion success in order to successfully manage existing invaders, and to prevent future invasions. As successful invasive species sometimes are suspected to rapidly adjust to their new environments in spite of very low genetic diversity, we are obliged to re-evaluate genomic-level processes that translate into phenotypic diversity. In this paper, we review work that supports the idea that trait variation, within and among invasive populations, can be created through epigenetic or other non-genetic processes, particularly in clonal invaders where somatic changes can persist indefinitely. We consider several processes that have been implicated as adaptive in invasion success, focusing on various forms of 'genomic shock' resulting from exposure to environmental stress, hybridization and whole-genome duplication (polyploidy), and leading to various patterns of gene expression re-programming and epigenetic changes that contribute to phenotypic variation or even novelty. These mechanisms can contribute to transgressive phenotypes, including hybrid vigour and novel traits, and may thus help to understand the huge successes of some plant invaders, especially those that are genetically impoverished. This article is part of the theme issue 'How does epigenetics influence the course of evolution?'