Temporal network analysis identifies early physiological and transcriptomic indicators of mild drought in Brassica rapa

Streamlined spatial and environmental expression signatures characterize the minimalist duckweed Wolffia australiana

Single-cell genomics permits a new resolution in the examination of molecular and cellular dynamics, allowing global, parallel assessments of cell types and cellular behaviors through development and in response to environmental circumstances, such as interaction with water and the light-dark cycle of the Earth. Here, we leverage the smallest, and possibly most structurally reduced, plant, the semiaquatic Wolffia australiana, to understand dynamics of cell expression in these contexts at the whole-plant level. We examined single-cell-resolution RNA-sequencing data and found Wolffia cells divide into four principal clusters representing the above- and below-water-situated parenchyma and epidermis. Although these tissues share transcriptomic similarity with model plants, they display distinct adaptations that Wolffia has made for the aquatic environment. Within this broad classification, discrete subspecializations are evident, with select cells showing unique transcriptomic signatures associated with developmental maturation and specialized physiologies. Assessing this simplified biological system temporally at two key time-of-day (TOD) transitions, we identify additional TOD-responsive genes previously overlooked in whole-plant transcriptomic approaches and demonstrate that the core circadian clock machinery and its downstream responses can vary in cell-specific manners, even in this simplified system. Distinctions between cell types and their responses to submergence and/or TOD are driven by expression changes of unexpectedly few genes, characterizing Wolffia as a highly streamlined organism with the majority of genes dedicated to fundamental cellular processes. Wolffia provides a unique opportunity to apply reductionist biology to elucidate signaling functions at the organismal level, for which this work provides a powerful resource.

Developing the 'omic toolkit of comparative physiologists

Typical 'omic analyses reduce complex biological systems to simple lists of supposedly independent variables, failing to account for changes in the wider transcriptional landscape. In this commentary, we discuss the utility of network approaches for incorporating this wider context into the study of physiological phenomena. We highlight opportunities to build on traditional network tools by utilising cutting-edge techniques to account for higher order interactions (i.e. beyond pairwise associations) within datasets, allowing for more accurate models of complex 'omic systems. Finally, we show examples of previous works utilising network approaches to gain additional insight into their organisms of interest. As 'omics grow in both their popularity and breadth of application, so does the requirement for flexible analytical tools capable of interpreting and synthesising complex datasets.

Impact of translational regulation on diel expression revealed by time-series ribosome profiling in Arabidopsis

Plants have developed the ability to adjust to the day/night cycle through the expression of diel genes, which allow them to effectively respond to environmental changes and optimise their growth and development. Diel oscillations also have substantial implications in many physiological processes, including photosynthesis, floral development, and environmental stress responses. The expression of diel genes is regulated by a combination of the circadian clock and responses to environmental cues, such as light and temperature. A great deal of information is available on the transcriptional regulation of diel gene expression. However, the extent to which translational regulation is involved in controlling diel changes in expression is not yet clear. To investigate the impact of translational regulation on diel expression, we conducted Ribo-seq and RNA-seq analyses on a time-series sample of Arabidopsis shoots cultivated under a 12 h light/dark cycle. Our results showed that translational regulation is involved in about 71% of the genes exhibiting diel changes in mRNA abundance or translational activity, including clock genes, many of which are subject to both translational and transcriptional control. They also revealed that the diel expression of glycosylation and ion-transporter-related genes is mainly established through translational regulation. The expression of several diel genes likely subject to translational regulation through upstream open-reading frames was also determined.

Metabolite-mediated adaptation of crops to drought and the acquisition of tolerance

Drought is one of the major and growing threats to agriculture productivity and food security. Metabolites are involved in the regulation of plant responses to various environmental stresses, including drought stress. The complex drought tolerance can be ascribed to several simple metabolic traits. These traits could then be used for detecting the genetic architecture of drought tolerance. Plant metabolomes show dynamic differences when drought occurs during different developmental stages or upon different levels of drought stress. Here, we reviewed the major and most recent findings regarding the metabolite-mediated plant drought response. Recent progress in the development of drought-tolerant agents is also discussed. We provide an updated schematic overview of metabolome-driven solutions for increasing crop drought tolerance and thereby addressing an impending agricultural challenge.

Combining PSII photochemistry and hydraulics improves predictions of photosynthesis and water use from mild to lethal drought

Rising temperatures and increases in drought negatively impact the efficiency and sustainability of both agricultural and forest ecosystems. Although hydraulic limitations on photosynthesis have been extensively studied, a solid understanding of the links between whole plant hydraulics and photosynthetic processes at the cellular level under changing environmental conditions is still missing, hampering our predictive power for plant mortality. Here, we examined plant hydraulic traits and CO2 assimilation rate under progressive water limitation by implementing Photosystem II (PSII) dynamics with a whole plant process model (TREES). The photosynthetic responses to plant water status were parameterized based on measurements of chlorophyll a fluorescence, gas exchange and water potential for Brassica rapa (R500) grown in a greenhouse under fully watered to lethal drought conditions. The updated model significantly improved predictions of photosynthesis, stomatal conductance and leaf water potential. TREES with PSII knowledge predicted a larger hydraulic safety margin and a decrease in percent loss of conductivity. TREES predicted a slower decrease in leaf water potential, which agreed with measurements. Our results highlight the pressing need for incorporating PSII drought photochemistry into current process models to capture cross-scale plant water dynamics from cell to whole plant level.

Integrated Analysis of miRNA and mRNA Regulation Network in Hypertension

Hypertension is the most common chronic disease. Early diagnosis is helpful for early medical intervention. The miRNAs and the messenger RNAs (mRNAs) network may be valuable disease diagnosis markers. We aimed to explore the diagnostic value of the miRNA-mRNA network for hypertension patients. Data of miRNAs and mRNAs expression were obtained from the Gene Expression Omnibus database. The weighted gene co-expression network analysis was performed to screen hypertension-related gene modules, and these genes undergone functional enrichment analysis using "clusterProfiler" package. Differential expression analysis was applied on miRNAs expression profiles using "limma" package. TargetScanHuman and miRDB databases were used to select target mRNAs. Cytoscape software was used to visualize the miRNA-mRNA regulation network. P value < 0.05 was considered statistically significant after t test. There were 123 screened mRNAs which were enriched in 161 Gene ontology (GO) terms and 14 Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. Thirty-five differentially expressed miRNAs (DEMs) are found in the GSE75670. Totally 36 miRNA-mRNA pairs were obtained after the integrated analysis, and three mRNAs and the hsa-miRNA-5589-5p were identified as key joints. Hub genes, KIAA0513, ARID3A and LRPAP1, and key hsa-miRNA-5589-5p are potential diagnostic biomarkers for hypertension. Our findings are promising in the clinical application, conducive to early detection and prompt intervention of hypertension.

A Dual Transcriptomic Approach Reveals Contrasting Patterns of Differential Gene Expression During Drought in Arbuscular Mycorrhizal Fungus and Carrot

While arbuscular mycorrhizal (AM) fungi are known for providing host plants with improved drought tolerance, we know very little about the fungal response to drought in the context of the fungal-plant relationship. In this study, we evaluated the drought responses of the host and symbiont, using the fungus Rhizophagus irregularis with carrot (Daucus carota) as a plant model. Carrots inoculated with spores of R. irregularis DAOM 197198 were grown in a greenhouse. During taproot development, carrots were exposed to a 10-day water restriction. Compared with well-watered conditions, drought caused diminished photosynthetic activity and reduced plant growth in carrot with and without AM fungi. Droughted carrots had lower root colonization. For R. irregularis, 93% of 826 differentially expressed genes (DEGs) were upregulated during drought, including phosphate transporters, several predicted transport proteins of potassium, and the aquaporin RiAQPF2. In contrast, 78% of 2,486 DEGs in AM carrot were downregulated during drought, including the symbiosis-specific genes FatM, RAM2, and STR, which are implicated in lipid transfer from the host to the fungus and were upregulated exclusively in AM carrot during well-watered conditions. Overall, this study provides insight into the drought response of an AM fungus in relation to its host; the expression of genes related to symbiosis and nutrient exchange were downregulated in carrot but upregulated in the fungus. This study reveals that carrot and R. irregularis exhibit contrast in their regulation of gene expression during drought, with carrot reducing its apparent investment in symbiosis and the fungus increasing its apparent symbiotic efforts. [Formula: see text] Copyright © 2023 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.

Diurnal oscillations of epigenetic modifications are associated with variation in rhythmic expression of homoeologous genes in Brassica napus

BACKGROUND

Epigenetic modifications that exhibit circadian oscillations also promote circadian oscillations of gene expression. Brassica napus is a heterozygous polyploid species that has undergone distant hybridization and genome doubling events and has a young and distinct species origin. Studies incorporating circadian rhythm analysis of epigenetic modifications can offer new insights into differences in diurnal oscillation behavior among subgenomes and the regulation of diverse expressions of homologous gene rhythms in biological clocks.

RESULTS

In this study, we created a high-resolution and multioscillatory gene expression dataset, active histone modification (H3K4me3, H3K9ac), and RNAPII recruitment in Brassica napus. We also conducted the pioneering characterization of the diurnal rhythm of transcription and epigenetic modifications in an allopolyploid species. We compared the evolution of diurnal rhythms between subgenomes and observed that the Cn subgenome had higher diurnal oscillation activity in both transcription and active histone modifications than the An subgenome. Compared to the A subgenome in Brassica rapa, the An subgenome of Brassica napus displayed significant changes in diurnal oscillation characteristics of transcription. Homologous gene pairs exhibited a higher proportion of diurnal oscillation in transcription than subgenome-specific genes, attributed to higher chromatin accessibility and abundance of active epigenetic modification types. We found that the diurnal expression of homologous genes displayed diversity, and the redundancy of the circadian system resulted in extensive changes in the diurnal rhythm characteristics of clock genes after distant hybridization and genome duplication events. Epigenetic modifications influenced the differences in the diurnal rhythm of homologous gene expression, and the diurnal oscillation of homologous gene expression was affected by the combination of multiple histone modifications.

CONCLUSIONS

Herein, we presented, for the first time, a characterization of the diurnal rhythm characteristics of gene expression and its epigenetic modifications in an allopolyploid species. Our discoveries shed light on the epigenetic factors responsible for the diurnal oscillation activity imbalance between subgenomes and homologous genes' rhythmic expression differences. The comprehensive time-series dataset we generated for gene expression and epigenetic modifications provides a valuable resource for future investigations into the regulatory mechanisms of protein-coding genes in Brassica napus.

Transcriptome analysis reveals that PbMYB61 and PbMYB308 are involved in the regulation of lignin biosynthesis in pear fruit stone cells

Pear fruit stone cells have thick walls and are formed by the secondary deposition of lignin in the primary cell wall of thin-walled cells. Their content and size seriously affect fruit characteristics related to edibility. To reveal the regulatory mechanism underlying stone cell formation during pear fruit development and to identify hub genes, we examined the stone cell and lignin contents of 30 'Shannongsu' pear flesh samples and analyzed the transcriptomes of 15 pear flesh samples collected at five developmental stages. On the basis of the RNA-seq data, 35 874 differentially expressed genes were detected. Additionally, two stone cell-related modules were identified according to a WGCNA. A total of 42 lignin-related structural genes were subsequently obtained. Furthermore, nine hub structural genes were identified in the lignin regulatory network. We also identified PbMYB61 and PbMYB308 as candidate transcriptional regulators of stone cell formation after analyzing co-expression networks and phylogenetic relationships. Finally, we experimentally validated and characterized the candidate transcription factors and revealed that PbMYB61 regulates stone cell lignin formation by binding to the AC element in the PbLAC1 promoter to upregulate expression. However, PbMYB308 negatively regulates stone cell lignin synthesis by binding to PbMYB61 to form a dimer that cannot activate PbLAC1 expression. In this study, we explored the lignin synthesis-related functions of MYB family members. The results presented herein are useful for elucidating the complex mechanisms underlying lignin biosynthesis during pear fruit stone cell development.

Identification of genes associated with abiotic stress tolerance in sweetpotato using weighted gene co-expression network analysis

Sweetpotato, Ipomoea batatas (L.), a key food security crop, is negatively impacted by heat, drought, and salinity stress. The orange-fleshed sweetpotato cultivar "Beauregard" was exposed to heat, salt, and drought treatments for 24 and 48 h to identify genes responding to each stress condition in leaves. Analysis revealed both common (35 up regulated, 259 down regulated genes in the three stress conditions) and unique sets of up regulated (1337 genes by drought, 516 genes by heat, and 97 genes by salt stress) and down regulated (2445 genes by drought, 678 genes by heat, and 204 genes by salt stress) differentially expressed genes (DEGs) suggesting common, yet stress-specific transcriptional responses to these three abiotic stressors. Gene Ontology analysis of down regulated DEGs common to both heat and salt stress revealed enrichment of terms associated with "cell population proliferation" suggestive of an impact on the cell cycle by the two stress conditions. To identify shared and unique gene co-expression networks under multiple abiotic stress conditions, weighted gene co-expression network analysis was performed using gene expression profiles from heat, salt, and drought stress treated 'Beauregard' leaves yielding 18 co-expression modules. One module was enriched for "response to water deprivation," "response to abscisic acid," and "nitrate transport" indicating synergetic crosstalk between nitrogen, water, and phytohormones with genes encoding osmotin, cell expansion, and cell wall modification proteins present as key hub genes in this drought-associated module. This research lays the groundwork for exploring to a further degree, mechanisms for abiotic stress tolerance in sweetpotato.

Hub Gene Mining and Co-Expression Network Construction of Low-Temperature Response in Maize of Seedling by WGCNA

Weighted gene co-expression network analysis (WGCNA) is a research method in systematic biology. It is widely used to identify gene modules related to target traits in multi-sample transcriptome data. In order to further explore the molecular mechanism of maize response to low-temperature stress at the seedling stage, B144 (cold stress tolerant) and Q319 (cold stress sensitive) provided by the Maize Research Institute of Heilongjiang Academy of Agricultural Sciences were used as experimental materials, and both inbred lines were treated with 5 °C for 0 h, 12 h, and 24 h, with the untreated material as a control. Eighteen leaf samples were used for transcriptome sequencing, with three biological replicates. Based on the above transcriptome data, co-expression networks of weighted genes associated with low-temperature-tolerance traits were constructed by WGCNA. Twelve gene modules significantly related to low-temperature tolerance at the seedling stage were obtained, and a number of hub genes involved in low-temperature stress regulation pathways were discovered from the four modules with the highest correlation with target traits. These results provide clues for further study on the molecular genetic mechanisms of low-temperature tolerance in maize at the seedling stage.

Gene co-expression network analysis for the selection of candidate early warning indicators of heat and nutrient stress in Posidonia oceanica

The continuous worldwide seagrasses decline calls for immediate actions in order to preserve this precious marine ecosystem. The main stressors that have been linked with decline in seagrasses are 1) the increasing ocean temperature due to climate change and 2) the continuous inputs of nutrients (eutrophication) associated with coastal human activities. To avoid the loss of seagrass populations, an "early warning" system is needed. We used Weighed Gene Co-expression Network Analysis (WGCNA), a systems biology approach, to identify potential candidate genes that can provide an early warning signal of stress in the Mediterranean iconic seagrass Posidonia oceanica, anticipating plant mortality. Plants were collected from both eutrophic (EU) and oligotrophic (OL) environments and were exposed to thermal and nutrient stress in a dedicated mesocosm. By correlating the whole-genome gene expression after 2-weeks exposure with the shoot survival percentage after 5-weeks exposure to stressors, we were able to identify several transcripts that indicated an early activation of several biological processes (BP) including: protein metabolic process, RNA metabolic process, organonitrogen compound biosynthetic process, catabolic process and response to stimulus, which were shared among OL and EU plants and among leaf and shoot apical meristem (SAM), in response to excessive heat and nutrients. Our results suggest a more dynamic and specific response of the SAM compared to the leaf, especially the SAM from plants coming from a stressful environment appeared more dynamic than the SAM from a pristine environment. A vast list of potential molecular markers is also provided that can be used as targets to assess field samples.

An intrinsically disordered region-containing protein mitigates the drought-growth trade-off to boost yields

Drought stress poses a serious threat to global agricultural productivity and food security. Plant resistance to drought is typically accompanied by a growth deficit and yield penalty. Herein, we report a previously uncharacterized, dicotyledon-specific gene, Stress and Growth Interconnector (SGI), that promotes growth during drought in the oil crop rapeseed (Brassica napus) and the model plant Arabidopsis (Arabidopsis thaliana). Overexpression of SGI conferred enhanced biomass and yield under water-deficient conditions, whereas corresponding CRISPR SGI mutants exhibited the opposite effects. These attributes were achieved by mediating reactive oxygen species (ROS) homeostasis while maintaining photosynthetic efficiency to increase plant fitness under water-limiting environments. Further spatial-temporal transcriptome profiling revealed dynamic reprogramming of pathways for photosynthesis and stress responses during drought and the subsequent recovery. Mechanistically, SGI represents an intrinsically disordered region-containing protein that interacts with itself, catalase isoforms, dehydrins, and other drought-responsive positive factors, restraining ROS generation. These multifaceted interactions stabilize catalases in response to drought and facilitate their ROS-scavenging activities. Taken altogether, these findings provide insights into currently underexplored mechanisms to circumvent trade-offs between plant growth and stress tolerance that will inform strategies to breed climate-resilient, higher yielding crops for sustainable agriculture.

Light, rather than circadian rhythm, regulates gas exchange in ferns and lycophytes

Circadian regulation plays a vital role in optimizing plant responses to the environment. However, while circadian regulation has been extensively studied in angiosperms, very little is known for lycophytes and ferns, leaving a gap in our understanding of the evolution of circadian rhythms across the plant kingdom. Here, we investigated circadian regulation in gas exchange through stomatal conductance and photosynthetic efficiency in a phylogenetically broad panel of 21 species of lycophytes and ferns over a 46 h period under constant light and a selected few under more natural conditions with day-night cycles. No rhythm was detected under constant light for either lycophytes or ferns, except for two semi-aquatic species of the family Marsileaceae (Marsilea azorica and Regnellidium diphyllum), which showed rhythms in stomatal conductance. Furthermore, these results indicated the presence of a light-driven stomatal control for ferns and lycophytes, with a possible passive fine-tuning through leaf water status adjustments. These findings support previous evidence for the fundamentally different regulation of gas exchange in lycophytes and ferns compared to angiosperms, and they suggest the presence of alternative stomatal regulations in Marsileaceae, an aquatic family already well known for numerous other distinctive physiological traits. Overall, our study provides evidence for heterogeneous circadian regulation across plant lineages, highlighting the importance of broad taxonomic scope in comparative plant physiology studies.

Local diversity of drought resistance and resilience in Populus tomentosa correlates with the variation of DNA methylation

Little information is known about DNA methylation variation in shaping environment-specific drought resistance and resilience for tree adaptation. In this study, we leveraged RNA sequencing and whole-genome bisulfite sequencing data to dissect the distinction of epigenetic regulation under drought stress and rewater condition of Populus tomentosa accessions from three geographical regions. We demonstrated low resistance and high resilience for accessions from South. Non-CG methylation levels in promoter regions of Southern accessions were lower than accessions from higher latitudes and negatively regulated gene expression. CHH context methylation was more sensitive to drought stress, and the geographical-specific differentially methylated regions were scarcely changed by environmental fluctuation. We identified 60 conserved hub genes within the co-expression networks that correlate with photosynthetic and stomatal morphological traits. Epigenome-wide association studies and genome-wide association studies of these 60 hub genes revealed the interdependency between genetic and epigenetic variation in GATA9 and LECRK-VIII.2, which was associated with stomatal morphology and chlorophyll content. The natural epigenetic variation in GATA9 was also faithfully transmitted to progenies in two family-based F1 populations. This study indicates a functional relationship of DNA methylation diversity with drought resistance and resilience which offers new insights into plants' local adaptation to a stressful environment.

Transcriptomic and metabolic regulatory network characterization of drought responses in tobacco

Drought stress usually causes huge economic losses for tobacco industries. Drought stress exhibits multifaceted impacts on tobacco systems through inducing changes at different levels, such as physiological and chemical changes, changes of gene transcription and metabolic changes. Understanding how plants respond and adapt to drought stress helps generate engineered plants with enhanced drought resistance. In this study, we conducted multiple time point-related physiological, biochemical,transcriptomic and metabolic assays using K326 and its derived mutant 28 (M28) with contrasting drought tolerance. Through integrative analyses of transcriptome and metabolome,we observed dramatic changes of gene expression and metabolic profiles between M28 and K326 before and after drought treatment. we found that some of DEGs function as key enzymes responsible for ABA biosynthesis and metabolic pathway, thereby mitigating impairment of drought stress through ABA signaling dependent pathways. Four DEGs were involved in nitrogen metabolism, leading to synthesis of glutamate (Glu) starting from NO-3 /NO-2 that serves as an indicator for stress responses. Importantly, through regulatory network analyses, we detected several drought induced TFs that regulate expression of genes responsible for ABA biosynthesis through network, indicating direct and indirect involvement of TFs in drought responses in tobacco. Thus, our study sheds some mechanistic insights into how plant responding to drought stress through transcriptomic and metabolic changes in tobacco. It also provides some key TF or non-TF gene candidates for engineering manipulation for breeding new tobacco varieties with enhanced drought tolerance.

Coexpression Network Construction and Visualization from Transcriptomes Underlying ER Stress Responses

Dynamic gene expression changes are primary cellular reactions in response to most stresses and developmental cues in all organisms, including plants. With the ever-decreasing cost and increasing access, high-throughput transcriptome analyses have become a significant research tool to understand a wide spectrum of complex gene regulatory mechanisms. However, it is still challenging to understand the complete picture of gene responses because of the interactive and dynamic nature of gene expression in biological networks. Coexpression network analyses followed by network mapping are being increasingly applied to overcome this challenge. In this chapter, we will introduce detailed instructions for performing a weighted coexpression network analysis (WGCNA) and network visualization using a transcriptome dataset obtained during recovery from endoplasmic reticulum (ER) stress in Arabidopsis thaliana. The streamlined workflow described here allows biologists to identify and visualize coexpression interactions among genes, accessing a comprehensive landscape of dynamic gene expression changes for further downstream analyses using their datasets.

Identification of genes for seed isoflavones based on bulk segregant analysis sequencing in soybean natural population

We identified four hub genes for isoflavone biosynthesis based on BSA-seq and WGCNA methods and validated that GmIE3-1 positively contribute to isoflavone accumulation in soybean. Soybean isoflavones are secondary metabolites of great interest owing to their beneficial impact on human health. Herein, we profiled the seed isoflavone content by HPLC in 1551 soybean accessions grown in two locations for two years and constructed two extreme pools with high (4065.1 µg g^-1) and low (1427.23 µg g^-1) isoflavone contents to identify candidate genes involved in isoflavone biosynthesis pathways using bulk segregant analysis sequencing (BSA-seq) approach. The results showed that the average sequencing depths were 50.3× and 65.7× in high and low pools, respectively. A total of 23,626 polymorphic SNPs and 5299 InDels were detected between both pools and 1492 genes with different variations were identified. Based on differential genes in BSA-seq and weighted gene co-expression network analysis (WGCNA), four hub genes, Glyma.06G290400 (designated as GmIE3-1), Glyma.01G239200, Glyma.01G241500, Glyma.13G256100 were identified, encoding E3 ubiquitin-protein ligase, arm repeat protein interacting with ABF2, zinc metallopeptidase EGY3, and dynamin-related protein 3A, respectively. The allelic variation in GmIE3-1 showed a significant influence on isoflavone accumulation. The virus-induced gene silencing (VIGS) and RNAi hairy root transformation of GmIE3-1 revealed partial suppression of this gene could cause a significant decrease (P < 0.0001) of total isoflavone content, suggesting GmIE3-1 is a positive regulator for isoflavones. The present study demonstrated that the BSA-seq approach combined with WGCNA, VIGS and hairy root transformation can efficiently identify isoflavone candidate genes in soybean natural population.

Comparative transcriptome and WGCNA reveal key genes involved in lignocellulose degradation in Sarcomyxa edulis

The developmental transcriptomes of Sarcomyxa edulis were assessed to explore the molecular mechanisms underlying lignocellulose degradation. Six stages were analyzed, spanning the entire developmental process: growth of mycelium until occupying half the bag (B1), mycelium under low-temperature stimulation after occupying the entire bag (B2), appearance of mycelium in primordia (B3), primordia (B4), mycelium at the harvest stage (B5), and mature fruiting body (B6). Samples from all six developmental stages were used for transcriptome sequencing, with three biological replicates for all experiments. A co-expression network of weighted genes associated with extracellular enzyme physiological traits was constructed using weighted gene co-expression network analysis (WGCNA). We obtained 19 gene co-expression modules significantly associated with lignocellulose degradation. In addition, 12 key genes and 8 kinds of TF families involved in lignocellulose degradation pathways were discovered from the four modules that exhibited the highest correlation with the target traits. These results provide new insights that advance our understanding of the molecular genetic mechanisms of lignocellulose degradation in S. edulis to facilitate its utilization by the edible mushroom industry.

Response of Rice with Overlapping Growth Stages to Water Stress by Assimilates Accumulation and Transport and Starch Synthesis of Superior and Inferior Grains

Drought stress at jointing–booting directly affects plant growth and productivity in rice. Limited by natural factors, the jointing and booting stages of short-growth-period rice varieties are highly overlapped in high-latitude areas, which are more sensitive to water deficit. However, little is known about the dry matter translocation in rice and the strategies of starch synthesis and filling of superior and inferior grains under different drought stress was unclear. In this study, the rice plants were subjected to three degrees of drought stress (−10 kPa, −25 kPa, −40 kPa) for 15 days during the jointing–booting stage; we investigated dry matter accumulation and translocation, grain filling and enzyme activities to starch synthesis of superior and inferior grains in rice with overlapping growth stages from 2016 to 2017. The results showed that drought stress significantly reduced dry matter accumulation in the stems and leaves. Mild and moderate drought increased dry matter translocation efficiency. However, severe drought stress largely limited the dry matter accumulation and translocation. A large amount of dry matter remains in vegetative organs under severe drought stress. The high content in NSC in stem and sheath plays a key role in resisting drought stress. The drought stress at jointing–booting directly caused a change in the grain filling strategy. Under moderate and severe drought, the grain-filling active period of the superior grains was shortened to complete the necessary reproductive growth. The grain-filling active period of the inferior grains was significantly prolonged to avoid a decrease in grain yield. The significant decrease in the grain-filling rate of the superior and inferior grains caused a reduction in the thousand-grain weight. In particular, the influence of the grain-filling rate of inferior grains on the thousand-grain weight was more significant. Drought stress changed the starch synthesis strategies of the superior and inferior grains. Soluble starch synthase and starch branching enzyme activities of inferior grains increased significantly under drought stress. GBSS activity was not sensitive to drought stress. Therefore, amylose content was decreased and amylopectin synthesis was enhanced under drought stress, especially in inferior grains.

WGCNA Identifies a Comprehensive and Dynamic Gene Co-Expression Network That Associates with Smut Resistance in Sugarcane

Sugarcane smut is a major fungal disease caused by Sporisorium scitamineum, which seriously reduces the yield and quality of sugarcane. In this study, 36 transcriptome data were collected from two sugarcane genotypes, YT93-159 (resistant) and ROC22 (susceptible) upon S. scitamineum infection. Data analysis revealed 20,273 (12,659 up-regulated and 7614 down-regulated) and 11,897 (7806 up-regulated and 4091 down-regulated) differentially expressed genes (DEGs) in YT93-159 and ROC22, respectively. A co-expression network was then constructed by weighted gene co-expression network analysis (WGCNA), which identified 5010 DEGs in 15 co-expressed gene modules. Four of the 15 modules, namely, Skyblue, Salmon, Darkorange, and Grey60, were significantly associated with smut resistance. The GO and KEGG enrichment analyses indicated that the DEGs involving in these four modules could be enriched in stress-related metabolic pathways, such as MAPK and hormone signal transduction, plant-pathogen interaction, amino acid metabolism, glutathione metabolism, and flavonoid, and phenylpropanoid biosynthesis. In total, 38 hub genes, including six from the Skyblue module, four from the Salmon module, 12 from the Darkorange module, and 16 from the Grey60 module, were screened as candidate hub genes by calculating gene connectivity in the corresponding network. Only 30 hub genes were amplifiable with RT-qPCR, of which 27 were up-regulated upon S. scitamineum infection. The results were consistent with the trend of gene expression in RNA-Seq, suggesting their positive roles in smut resistance. Interestingly, the expression levels of AOX, Cyb5, and LAC were higher in ROC22 than in YT93-159, indicating these three genes may act as negative regulators in response to S. scitamineum infection. This study revealed the transcriptome dynamics in sugarcane challenged by S. scitamineum infection and provided gene targets for smut resistance breeding in sugarcane.

Integration of rhythmic metabolome and transcriptome provides insights into the transmission of rhythmic fluctuations and temporal diversity of metabolism in rice

Various aspects of the organisms adapt to cyclically changing environmental conditions via transcriptional regulation. However, the role of rhythmicity in altering the global aspects of metabolism is poorly characterized. Here, we subjected four rice (Oryza sativa) varieties to a range of metabolic profiles and RNA-seq to investigate the temporal relationships of rhythm between transcription and metabolism. More than 40% of the rhythmic genes and a quarter of metabolites conservatively oscillated across four rice accessions. Compared with the metabolome, the transcriptome was more strongly regulated by rhythm; however, the rhythm of metabolites had an obvious opposite trend between day and night. Through association analysis, the time delay of rhythmic transmission from the transcript to the metabolite level was ∼4 h under long-day conditions, although the transmission was nearly synchronous for carbohydrate and nucleotide metabolism. The rhythmic accumulation of metabolites maintained highly coordinated temporal relationships in the metabolic network, whereas the correlation of some rhythmic metabolites, such as branched-chain amino acids (BCAAs), was significantly different intervariety. We further demonstrated that the cumulative diversity of BCAAs was due to the differential expression of branched-chain aminotransferase 2 at dawn. Our research reveals the flexible pattern of rice metabolic rhythm existing with conservation and diversity.

Investigation of Brassica and its relative genomes in the post-genomics era

The Brassicaceae family includes many economically important crop species, as well as cosmopolitan agricultural weed species. In addition, Arabidopsis thaliana, a member of this family, is used as a molecular model plant species. The genus Brassica is mesopolyploid, and the genus comprises comparatively recently originated tetrapolyploid species. With these characteristics, Brassicas have achieved the commonly accepted status of model organisms for genomic studies. This paper reviews the rapid research progress in the Brassicaceae family from diverse omics studies, including genomics, transcriptomics, epigenomics, and three-dimensional (3D) genomics, with a focus on cultivated crops. The morphological plasticity of Brassicaceae crops is largely due to their highly variable genomes. The origin of several important Brassicaceae crops has been established. Genes or loci domesticated or contributing to important traits are summarized. Epigenetic alterations and 3D structures have been found to play roles in subgenome dominance, either in tetraploid Brassica species or their diploid ancestors. Based on this progress, we propose future directions and prospects for the genomic investigation of Brassicaceae crops.

Transcriptome-guided annotation and functional classification of long non-coding RNAs in Arabidopsis thaliana

Long non-coding RNAs (lncRNAs) are a prominent class of eukaryotic regulatory genes. Despite the numerous available transcriptomic datasets, the annotation of plant lncRNAs remains based on dated annotations that have been historically carried over. We present a substantially improved annotation of Arabidopsis thaliana lncRNAs, generated by integrating 224 transcriptomes in multiple tissues, conditions, and developmental stages. We annotate 6764 lncRNA genes, including 3772 that are novel. We characterize their tissue expression patterns and find 1425 lncRNAs are co-expressed with coding genes, with enriched functional categories such as chloroplast organization, photosynthesis, RNA regulation, transcription, and root development. This improved transcription-guided annotation constitutes a valuable resource for studying lncRNAs and the biological processes they may regulate.

The spatiotemporal regulations of epicatechin biosynthesis under normal flowering and the continuous inflorescence removal treatment in Fagopyrum dibotrys

BACKGROUND

Flowering is a critical physiological change that interferes with not only biomass yield but also secondary metabolism, such as the biosynthesis of flavonoids, in rhizome/root plants. The continuous inflorescence removal (CIR) treatment is frequently conducted to weaken this effect. Fagopyrum dibotrys (D.Don) H.Hara (Golden buckwheat) is a kind of rhizome medicinal plant rich in flavonoids and is widely used for the treatment of lung diseases. The CIR treatment is usually conducted in F. dibotrys because of its excessive reproductive growth. To uncover the molecular mechanisms, comprehensive analysis was performed using metabolome and transcriptome data obtained from normally bloomed and the CIR treated plants.

RESULTS

Metabolome results demonstrated that in the rhizomes of F. dibotrys, its bioactive compound called epicatechin has higher amount than most of the detected precursors. Compared with the normally bloomed plants, the level of epicatechin in the rhizomes of the CIR group increased by 25% at the withering stage. Based on 96 samples of the control and the CIR groups at 4 flowering stages for 4 tissues, RNA-Seq results revealed a 3 ~ 5 times upregulations of all the key enzyme genes involved in the biosynthesis of epicatechin in both time (from the bud stage to the withering stage) and spatial dimensions (from the top of branch to rhizome) under the CIR treatment compared to normal flowering. Integrated analysis of LC-MS/MS and transcriptome revealed the key roles of several key enzyme genes besides anthocyanidin reductase (ANR). A total of 93 transcription factors were identified to co-expressed with the genes in epicatechin biosynthetic pathway. The flowering activator SQUAMOSA promoter-binding protein like (SPLs) exhibited opposite spatiotemporal expression patterns to that of the epicatechin pathway genes; SPL3 could significantly co-express with all the key enzyme genes rather than the flowering repressor DELLA. Weighted gene co-expression network analysis (WGCNA) further confirmed the correlations among chalcone synthases (CHSs), chalcone isomerases (CHIs), ANRs, SPLs and other transcription factors.

CONCLUSIONS

SPL3 might dominantly mediate the effect of normal flowering and the CIR treatment on the biosynthesis of epicatechin in rhizomes mainly through the negative regulations of its key enzyme genes including CHS, CHI and ANR.

Integrating spatial transcriptomics with single-cell transcriptomics reveals a spatiotemporal gene landscape of the human developing kidney

BACKGROUND

Research on spatiotemporal gene landscape can provide insights into the spatial characteristics of human kidney development and facilitate kidney organoid cultivation. Here, we profiled the spatiotemporal gene programs of the human embryonic kidneys at 9 and 18 post-conception weeks (PCW) by integrating the application of microarray-based spatial transcriptomics and single-cell transcriptomics.

RESULTS

We mapped transcriptomic signatures of scRNA-seq cell types upon the 9 and 18 PCW kidney sections based on cell-type deconvolution and multimodal intersection analyses, depicting a spatial landscape of developing cell subpopulations. We established the gene characteristics in the medullary regions and revealed a strong mitochondrial oxidative phosphorylation and glycolysis activity in the deeper medullary region. We also built a regulatory network centered on GDNF-ETV4 for nephrogenic niche development based on the weighted gene co-expression network analysis and highlighted the key roles of Wnt, FGF, and JAG1-Notch2 signaling in maintaining renal branching morphogenesis.

CONCLUSIONS

Our findings obtained by this spatiotemporal gene program are expected to improve the current understanding of kidney development.

Transcriptome Analysis of Pennisetum glaucum (L.) R. Br. Provides Insight Into Heat Stress Responses

Pennisetum glaucum (L.) R. Br., being widely grown in dry and hot weather, frequently encounters heat stress at various stages of growth. The crop, due to its inherent capacity, efficiently overcomes such stress during vegetative stages. However, the same is not always the case with the terminal (flowering through grain filling) stages of growth, where recovery from stress is more challenging. However, certain pearl millet genotypes such as 841-B are known to overcome heat stress even at the terminal growth stages. Therefore, we performed RNA sequencing of two contrasting genotypes of pearl millet (841-B and PPMI-69) subjected to heat stress (42°C for 6 h) at flowering stages. Over 274 million high quality reads with an average length of 150 nt were generated, which were assembled into 47,310 unigenes having an average length of 1,254 nucleotides, N50 length of 1853 nucleotides, and GC content of 53.11%. Blastx resulted in the annotation of 35,628 unigenes, and functional classification showed 15,950 unigenes designated to 51 Gene Ontology terms. A total of 13,786 unigenes were allocated to 23 Clusters of Orthologous Groups, and 4,255 unigenes were distributed to 132 functional Kyoto Encyclopedia of Genes and Genomes database pathways. A total of 12,976 simple sequence repeats and 305,759 SNPs were identified in the transcriptome data. Out of 2,301 differentially expressed genes, 10 potential candidate genes were selected based on log2 fold change and adjusted p value parameters for their differential gene expression by qRT-PCR. We were able to identify differentially expressed genes unique to either of the two genotypes, and also, some DEGs common to both the genotypes were enriched. The differential expression patterns suggested that 841-B 6 h has better ability to maintain homeostasis during heat stress as compared to PPMI-69 6 h. The sequencing data generated in this study, like the SSRs and SNPs, shall serve as an important resource for the development of genetic markers, and the differentially expressed heat responsive genes shall be used for the development of transgenic crops.

Gene Co-expression Network and Regression Analysis Identify the Transcriptomic, Physiological, and Biochemical Indicators of the Response of Alpine Woody Plant Rhododendron rex to Drought Stress

Increasing severity of drought stress due to global change and extreme weather has been affecting the biodiversity, function, and stability of forest ecosystems. However, despite being an important component in the alpine and subalpine vegetation in forest ecosystems, Rhododendron species have been paid rare attention in the study of molecular mechanism of tolerance or response to drought. Herein, we investigated the correlation of transcriptomic changes with the physiological and biochemical indicators of Rhododendron rex under drought stress by using the co-expression network approach and regression analysis. Compared with the control treatment, the number of significantly differentially expressed unigenes (DEGs) increased with the degree of drought stress. The DEGs were mainly enriched in the cell wall metabolic process, signaling pathways, sugar metabolism, and nitrogen metabolism. Coupled analysis of the transcriptome, physiological, and biochemical parameters indicated that the metabolic pathways were highly correlated with the physiological and biochemical indicators under drought stress, especially the chlorophyll fluorescence parameters, such as the actual photosynthetic efficiency of photosystem II, electron transport rate, photochemical quenching coefficient, and the maximum quantum efficiency of photosystem II photochemistry. The majority of the response genes related to the metabolic pathways, including photosynthesis, sugar metabolism, and phytohormone signal pathway, were highly expressed under drought stress. In addition, genes associated with cell wall, pectin, and galacturonan metabolism also played crucial roles in the response of R. rex to drought stress. The results provided novel insight into the molecular response of the alpine woody species under drought stress and may improve the understanding of the response of forest ecosystems to the global climate change.

Photosynthetic Carbon Fixation and Sucrose Metabolism Supplemented by Weighted Gene Co-expression Network Analysis in Response to Water Stress in Rice With Overlapping Growth Stages

Drought stress at jointing and booting phases of plant development directly affects plant growth and productivity in rice. Limited by natural factors, the jointing and booting stages in rice varieties are known to overlap in high-latitude areas that are more sensitive to water deficit. However, the regulation of photosynthetic carbon fixation and sucrose metabolism in rice leaves under different degrees of drought stress remains unclear. In this study, rice plants were subjected to three degrees of drought stress (-10, -25, -and 40 kPa) for 15 days during the jointing-booting stage, we investigated photosynthetic carbon sequestration and sucrose metabolism pathways in rice leaves and analyzed key genes and regulatory networks using transcriptome sequencing in 2016. And we investigated the effects of drought stress on the growth periods of rice with overlapping growth periods in 2016 and 2017. The results showed that short-term drought stress promoted photosynthetic carbon fixation. However, ribulose-1,5-bisphosphate carboxylase/oxygenase (RuBisCO) activity significantly decreased, resulting in a significant decrease in photosynthetic rate. Drought stress increased the maximum activity of fructose-1,6-bisphosphate aldolase (FBA). FBA maintains the necessary photosynthetic rate during drought stress and provides a material base after the resumption of irrigation in the form of controlling the content of its reaction product triose phosphate. Drought stress significantly affected the activities of sucrose synthase (SuSase) and sucrose phosphate synthase (SPS). Vacuoles invertase (VIN) activity increased significantly, and the more severe the drought, the higher the VIN activity. Severe drought stress at the jointing-booting stage severely restricted the growth process of rice with overlapping growth stages and significantly delayed heading and anthesis stages. Transcriptome analysis showed that the number of differentially expressed genes was highest at 6-9 days after drought stress. Two invertase and four β-amylase genes with time-specific expression were involved in sucrose-starch metabolism in rice under drought stress. Combined with weighted gene co-expression network analysis, VIN and β-amylase genes up-regulated throughout drought stress were regulated by OsbZIP04 and OsWRKY62 transcription factors under drought stress. This study showed that any water deficit at the jointing-booting stage would have a serious effect on sucrose metabolism in leaves of rice with overlapping growth stages.

Nanotoxicological effects and transcriptome mechanisms of wheat (Triticum aestivum L.) under stress of polystyrene nanoplastics

At present, the uptake and accumulation of nanoplastics by plants have raised particular concerns. However, molecular mechanisms underlying nanoplastic phytotoxicity are still vague and insufficient. To address this scientific gap, we analyzed the transcriptome response of hydroponically grown wheat (Triticum aestivum L.) to polystyrene nanoplastics (PSNPs) (100 nm) by integrating the differentially expressed gene analysis (DEGA) and the weighted gene correlation network analysis (WGCNA). PSNPs could significantly shape the gene expression patterns of wheat in a tissue-specific manner. Four candidate modules and corresponding hub genes associated with plant traits were identified using WGCNA. PSNPs significantly altered carbon metabolism, amino acid biosynthesis, mitogen-activated protein kinase (MAPK) signaling pathway-plant, plant hormone signal transduction, and plant-pathogen interaction Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. In addition, some Gene Ontology (GO) terms associated with the metal ion transport were further screened. These findings shed new light on the phytotoxic mechanism and environmental implication behind the interaction of nanoplastics and crop plants, and advance our understanding of the potential adverse effect induced by the presence of nanoplastics in agricultural systems.

The biology of time: dynamic responses of cell types to developmental, circadian and environmental cues

As sessile organisms, plants are finely tuned to respond dynamically to developmental, circadian and environmental cues. Genome-wide studies investigating these types of cues have uncovered the intrinsically different ways they can impact gene expression over time. Recent advances in single-cell sequencing and time-based bioinformatic algorithms are now beginning to reveal the dynamics of these time-based responses within individual cells and plant tissues. Here, we review what these techniques have revealed about the spatiotemporal nature of gene regulation, paying particular attention to the three distinct ways in which plant tissues are time sensitive. (i) First, we discuss how studying plant cell identity can reveal developmental trajectories hidden in pseudotime. (ii) Next, we present evidence that indicates that plant cell types keep their own local time through tissue-specific regulation of the circadian clock. (iii) Finally, we review what determines the speed of environmental signaling responses, and how they can be contingent on developmental and circadian time. By these means, this review sheds light on how these different scales of time-based responses can act with tissue and cell-type specificity to elicit changes in whole plant systems.

Diversity in nonlinear responses to soil moisture shapes evolutionary constraints in Brachypodium

Water availability is perhaps the greatest environmental determinant of plant yield and fitness. However, our understanding of plant-water relations is limited because-like many studies of organism-environment interaction-it is primarily informed by experiments considering performance at two discrete levels-wet and dry-rather than as a continuously varying environmental gradient. Here, we used experimental and statistical methods based on function-valued traits to explore genetic variation in responses to a continuous soil moisture gradient in physiological and morphological traits among 10 genotypes across two species of the model grass genus Brachypodium. We find that most traits exhibit significant genetic variation and nonlinear responses to soil moisture variability. We also observe differences in the shape of these nonlinear responses between traits and genotypes. Emergent phenomena arise from this variation including changes in trait correlations and evolutionary constraints as a function of soil moisture. Our results point to the importance of considering diversity in nonlinear organism-environment relationships to understand plastic and evolutionary responses to changing climates.

Transcriptomic Analysis Reveals Regulatory Networks for Osmotic Water Stress and Rewatering Response in the Leaves of Ginkgo biloba

To elucidate the transcriptomic regulation mechanisms that underlie the response of Ginkgo biloba to dehydration and rehydration, we used ginkgo saplings exposed to osmotically driven water stress and subsequent rewatering. When compared with a control group, 137, 1453, 1148, and 679 genes were differentially expressed in ginkgo leaves responding to 2, 6, 12, and 24 h of water deficit, and 796 and 1530 genes were differentially expressed responding to 24 and 48 h of rewatering. Upregulated genes participated in the biosynthesis of abscisic acid, eliminating reactive oxygen species (ROS), and biosynthesis of flavonoids and bilobalide, and downregulated genes were involved in water transport and cell wall enlargement in water stress-treated ginkgo leaves. Under rehydration conditions, the genes associated with water transport and cell wall enlargement were upregulated, and the genes that participated in eliminating ROS and the biosynthesis of flavonoids and bilobalide were downregulated in the leaves of G. biloba. Furthermore, the weighted gene coexpression networks were established and correlated with distinct water stress and rewatering time-point samples. Hub genes that act as key players in the networks were identified. Overall, these results indicate that the gene coexpression networks play essential roles in the transcriptional reconfiguration of ginkgo leaves in response to water stress and rewatering.

Circadian coordination of cellular processes and abiotic stress responses

Diel changes in the environment are perceived by the circadian clock which transmits temporal information throughout the plant cell to synchronize daily and seasonal environmental signals with internal biological processes. Dynamic modulations of diverse levels of clock gene regulation within the plant cell are impacted by stress. Recent insights into circadian control of cellular processes such as alternative splicing, polyadenylation, and noncoding RNAs are discussed. We highlight studies on the circadian regulation of reactive oxygen species, calcium signaling, and gating of temperature stress responses. Finally, we briefly summarize recent work on the translation-specific rhythmicity of cell cycle genes and the control of subcellular localization and relocalization of oscillator components. Together, this mini-review highlights these cellular events in the context of clock gene regulation and stress responses in Arabidopsis.

A ten-genes-based diagnostic signature for atherosclerosis

BACKGROUND

Atherosclerosis is the leading cause of cardiovascular disease with a high mortality worldwide. Understanding the atherosclerosis pathogenesis and identification of efficient diagnostic signatures remain major problems of modern medicine. This study aims to screen the potential diagnostic genes for atherosclerosis.

METHODS

We downloaded the gene chip data of 135 peripheral blood samples, including 57 samples with atherosclerosis and 78 healthy subjects from GEO database (Accession Number: GSE20129). The weighted gene co-expression network analysis was applied to identify atherosclerosis-related genes. Functional enrichment analysis was conducted by using the clusterProfiler R package. The interaction pairs of proteins encoded by atherosclerosis-related genes were screened using STRING database, and the interaction network was further optimized with the cytoHubba plug-in of Cytoscape software.

RESULTS

The logistic regression diagnostic model was constructed to predict normal and atherosclerosis samples. A gene module which included 532 genes related to the occurrence of atherosclerosis were screened. Functional enrichment analysis basing on the 532 genes identified 235 significantly enriched GO terms and 44 significantly enriched KEGG pathways. The top 50 hub genes of the protein-protein interaction network were identified. The final logistic regression diagnostic model was established by the optimal 10 key genes, which could distinguish atherosclerosis samples from normal samples.

CONCLUSIONS

A predictive model based on 10 potential atherosclerosis-related genes was obtained, which should shed light on the diagnostic research of atherosclerosis.

Analysis of Shared Genetic Regulatory Networks for Alzheimer's Disease and Epilepsy

Alzheimer's disease (AD) and epilepsy are neurological disorders that affect a large cohort of people worldwide. Although both of the two diseases could be influenced by genetic factors, the shared genetic mechanism underlying the pathogenesis of them is still unclear. In this study, we aimed to identify the shared genetic networks and corresponding hub genes for AD and epilepsy. Firstly, the gene coexpression modules (GCMs) were constructed by weighted gene coexpression network analysis (WGCNA), and 16 GCMs were identified. Through further integration of GCMs, genome-wide association studies (GWASs), and expression quantitative trait loci (eQTLs), 4 shared GCMs of AD and epilepsy were identified. Functional enrichment analysis was performed to analyze the shared biological processes of these GCMs and explore the functional overlaps between these two diseases. The results showed that the genes in shared GCMs were significantly enriched in nervous system-related pathways, such as Alzheimer's disease and neuroactive ligand-receptor interaction pathways. Furthermore, the hub genes of AD- and epilepsy-associated GCMs were captured by weighted key driver analysis (wKDA), including TRPC1, C2ORF40, NR3C1, KIAA0368, MMT00043109, STEAP1, MSX1, KL, and CLIC6. The shared GCMs and hub genes might provide novel therapeutic targets for AD and epilepsy.

Gene-Metabolite Network Analysis Revealed Tissue-Specific Accumulation of Therapeutic Metabolites in Mallotus japonicus

Mallotus japonicus is a valuable traditional medicinal plant in East Asia for applications as a gastrointestinal drug. However, the molecular components involved in the biosynthesis of bioactive metabolites have not yet been explored, primarily due to a lack of omics resources. In this study, we established metabolome and transcriptome resources for M. japonicus to capture the diverse metabolite constituents and active transcripts involved in its biosynthesis and regulation. A combination of untargeted metabolite profiling with data-dependent metabolite fragmentation and metabolite annotation through manual curation and feature-based molecular networking established an overall metabospace of M. japonicus represented by 2129 metabolite features. M. japonicus de novo transcriptome assembly showed 96.9% transcriptome completeness, representing 226,250 active transcripts across seven tissues. We identified specialized metabolites biosynthesis in a tissue-specific manner, with a strong correlation between transcripts expression and metabolite accumulations in M. japonicus. The correlation- and network-based integration of metabolome and transcriptome datasets identified candidate genes involved in the biosynthesis of key specialized metabolites of M. japonicus. We further used phylogenetic analysis to identify 13 C-glycosyltransferases and 11 methyltransferases coding candidate genes involved in the biosynthesis of medicinally important bergenin. This study provides comprehensive, high-quality multi-omics resources to further investigate biological properties of specialized metabolites biosynthesis in M. japonicus.

Transcriptome, degradome and physiological analysis provide new insights into the mechanism of inhibition of litchi fruit senescence by melatonin

Litchi fruit has high commercial value on the international market, but senesces rapidly after harvest. We used weighted gene co-expression network analysis (WGCNA) and degradome technology to investigate the molecular mechanisms of melatonin-mediated delay of litchi fruit senescence through application of exogenous melatonin and p-chlorophenylalanine (p-CPA, an inhibitor of melatonin biosynthesis) treatments. Results demonstrated that exogenous melatonin treatment delayed litchi fruit senescence while p-CPA accelerated senescence. Coupled analyses of transcriptome and physiological parameters of litchi fruit provided the correlation of network modules with dynamic changes in browning index during storage. Additionally, we found that microRNAs (miR858 and miR160a) and their targets were actively involved in melatonin-mediated delay of litchi fruit senescence. Melatonin treatment decreased abscisic acid (ABA) content but increased PP2C and F-box expression levels, suggesting the involvement of ABA signaling in melatonin-mediated antisenescence. The transcriptions of ZAT, NAC and DREB1 were activated by melatonin treatment. Moreover, the major functional genes involved in histone methylation, γ-aminobutyric acid (GABA) metabolism, energy production, reactive oxygen species (ROS) accumulation and cell death were identified in the melatonin-inhibited litchi pericarp browning. Taken together, we first constructed the global map of the important regulators and pathways to delay litchi senescence and pericarp browning mediated by melatonin.

What is quantitative plant biology?

Quantitative plant biology is an interdisciplinary field that builds on a long history of biomathematics and biophysics. Today, thanks to high spatiotemporal resolution tools and computational modelling, it sets a new standard in plant science. Acquired data, whether molecular, geometric or mechanical, are quantified, statistically assessed and integrated at multiple scales and across fields. They feed testable predictions that, in turn, guide further experimental tests. Quantitative features such as variability, noise, robustness, delays or feedback loops are included to account for the inner dynamics of plants and their interactions with the environment. Here, we present the main features of this ongoing revolution, through new questions around signalling networks, tissue topology, shape plasticity, biomechanics, bioenergetics, ecology and engineering. In the end, quantitative plant biology allows us to question and better understand our interactions with plants. In turn, this field opens the door to transdisciplinary projects with the society, notably through citizen science.

Soil Microsite Outweighs Cultivar Genotype Contribution to Brassica Rhizobacterial Community Structure

Microorganisms residing on root surfaces play a central role in plant development and performance and may promote growth in agricultural settings. Studies have started to uncover the environmental parameters and host interactions governing their assembly. However, soil microbial communities are extremely diverse and heterogeneous, showing strong variations over short spatial scales. Here, we quantify the relative effect of meter-scale variation in soil bacterial community composition among adjacent field microsites, to better understand how microbial communities vary by host plant genotype as well as soil microsite heterogeneity. We used bacterial 16S rDNA amplicon sequencing to compare rhizosphere communities from four Brassica rapa cultivars grown in three contiguous field plots (blocks) and evaluated the relative contribution of resident soil communities and host genotypes in determining rhizosphere community structure. We characterize concomitant meter-scale variation in bacterial community structure among soils and rhizospheres and show that this block-scale variability surpasses the influence of host genotype in shaping rhizosphere communities. We identified biomarker amplicon sequence variants (ASVs) associated with bulk soil and rhizosphere habitats, each block, and three of four cultivars. Numbers and percent abundances of block-specific biomarkers in rhizosphere communities far surpassed those from bulk soils. These results highlight the importance of fine-scale variation in the pool of colonizing microorganisms during rhizosphere assembly and demonstrate that microsite variation may constitute a confounding effect while testing biotic and abiotic factors governing rhizosphere community structure.

Machine learning analysis of gene expression profile reveals a novel diagnostic signature for osteoporosis

Background

Osteoporosis (OP) is increasingly prevalent with the aging of the world population. It is urgent to identify efficient diagnostic signatures for the clinical application.

Method

We downloaded the mRNA profile of 90 peripheral blood samples with or without OP from GEO database (Number: GSE152073). Weighted gene co-expression network analysis (WGCNA) was used to reveal the correlation among genes in all samples. GO term and KEGG pathway enrichment analysis was performed via the clusterProfiler R package. STRING database was applied to screen the interaction pairs among proteins. Protein–protein interaction (PPI) network was visualized based on Cytoscape, and the key genes were screened using the cytoHubba plug-in. The diagnostic model based on these key genes was constructed, and 5-fold cross validation method was applied to evaluate its reliability.

Results

A gene module consisted of 176 genes predicted to be associated with the occurrence of OP was identified. A total of 16 significantly enriched GO terms and 1 significantly enriched KEGG pathway were obtained based on the 176 genes. The top 50 key genes in the PPI network were identified. Then 22 genes were screened based on stepwise regression analysis from the 50 key genes. Of which, 9 genes were further screened out by multivariate regression analysis with the significant threshold of P value < 0.01. The diagnostic model was established based on the optimal 9 key genes, which efficiently separated the normal samples and OP samples.

Conclusion

A diagnostic model established based on nine key genes could reliably separate OP patients from healthy subjects, which provided novel lightings on the diagnostic research of OP.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13018-021-02329-1.

Circadian Clock Components Offer Targets for Crop Domestication and Improvement

During plant domestication and improvement, farmers select for alleles present in wild species that improve performance in new selective environments associated with cultivation and use. The selected alleles become enriched and other alleles depleted in elite cultivars. One important aspect of crop improvement is expansion of the geographic area suitable for cultivation; this frequently includes growth at higher or lower latitudes, requiring the plant to adapt to novel photoperiodic environments. Many crops exhibit photoperiodic control of flowering and altered photoperiodic sensitivity is commonly required for optimal performance at novel latitudes. Alleles of a number of circadian clock genes have been selected for their effects on photoperiodic flowering in multiple crops. The circadian clock coordinates many additional aspects of plant growth, metabolism and physiology, including responses to abiotic and biotic stresses. Many of these clock-regulated processes contribute to plant performance. Examples of selection for altered clock function in tomato demonstrate that with domestication, the phasing of the clock is delayed with respect to the light–dark cycle and the period is lengthened; this modified clock is associated with increased chlorophyll content in long days. These and other data suggest the circadian clock is an attractive target during breeding for crop improvement.

A four-genes based diagnostic signature for osteoarthritis

Osteoarthritis (OA) is a primary leading cause of pain and disability. However, some cases are diagnosed at the later stage which delayed the timely treatment. This study aims to identify effective diagnostic signature for OA. The mRNA profile GSE48566 including 106 blood samples of OA patients and 33 blood samples of healthy individuals was downloaded from Gene Expression Omnibus (GEO) database. The potential OA-related genes were screened by weighted gene co-expression network analysis (WGCNA). Gene ontology (GO) term and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed to reveal the functions or pathways of OA-related genes using the clusterProfiler function package of R software. Key genes significantly involved in OA progression were further screened by protein-protein interaction (PPI) network. The logistic regression model and the random forest model were conducted by bringing into optimal genes selected by stepwise regression analysis, and fivefold cross validation method was used to determine their reliability. A total of 146 genes, existed in three modules and might be associated with the occurrence of OA, were screened. 15 genes were screened from the PPI network and four genes, including CCR6, CLEC7A, IL18 and SRSF2, were further optimized. Finally, a logistic regression model and a random forest model were conducted by bringing into four optimal genes, and could reliably separate OA patients from healthy subjects. Our study established two effective diagnostic models based on CCR6, CLEC7A, IL18 and SRSF2, which could reliably separate OA patients from healthy subjects.

Dynamic changes of transcriptome of fifth-instar spodoptera litura larvae in response to insecticide

Spodoptera litura is a major insect with a cosmopolitan distribution and strong resistance to multiple insecticides. Determining the molecular basis and key candidate genes of the insecticide resistance of S. litura may help in managing this insect. In this study, fifth-instar S. litura larvae were subjected to transcriptome analysis at 6, 12, 24, 48, and 72 h after feeding on an LC20 dose of avermectin. The result showed that genes responding to avermectin changed dynamically with different gene counts and resistance mechanisms at the fifth instar based on a metabolic pathway map. These responses included degrading the insecticide by a series of P450 and glutathione-S-transferase enzymes starting at the 12 h time point, with subsequent increases in the number of genes involved and shifts to TOLL and immune deficiency (IMD) pathways at 48 h after feeding the insecticide. Weighted correlation network analysis (WGCNA) determined a co-expression module related to the avermectin response at 12 and 24 h (r = 0.403, p = 0.0371; r = 0.436, p = 0.023), in which a hub gene (LOC111358940) related to metalloproteinase activity was identified. In addition, Analysis of the genes in the co-expression module further revealed that eight genes encoding UDP-glucuronosyltransferases were directly associated with insecticide response in S. litura. These results provide better understanding of the avermectin response mechanism of S. litura and may be useful in developing improved control strategies for this species.

SUPPLEMENTARY INFORMATION

The online version of this article (10.1007/s13205-021-02651-9) contains supplementary material, which is available to authorized users.

Weighted gene coexpression network analysis-based identification of key modules and hub genes associated with drought sensitivity in rice

BACKGROUND

Drought stress is an adverse factor with deleterious effects on several aspects of rice growth. However, the mechanism underlying drought resistance in rice remains unclear. To understand the molecular mechanism of the drought response in rice, drought-sensitive CSSL (Chromosome Single-substitution Segment Line) PY6 was used to map QTLs of sensitive phenotypes and to reveal the impact of the QTLs on transcriptional profiling.

RESULTS

The QTL dss-1 was mapped onto the short arm of chromosome 1 of rice. According to transcriptomic analysis, the identified differentially expressed genes (DEGs) exhibited a downregulated pattern and were mainly enriched in photosynthesis-related GO terms, indicating that photosynthesis was greatly inhibited under drought. Further, according to weighted gene coexpression network analysis (WGCNA), specific gene modules (designating a group of genes with a similar expression pattern) were strongly correlated with H₂O₂ (4 modules) and MDA (3 modules), respectively. Likewise, GO analysis revealed that the photosynthesis-related GO terms were consistently overrepresented in H₂O₂-correlated modules. Functional annotation of the differentially expressed hub genes (DEHGs) in the H₂O₂ and MDA-correlated modules revealed cross-talk between abiotic and biotic stress responses for these genes, which were annotated as encoding WRKYs and PR family proteins, were notably differentially expressed between PY6 and PR403.

CONCLUSIONS

We speculated that drought-induced photosynthetic inhibition leads to H₂O₂ and MDA accumulation, which can then trigger the reprogramming of the rice transcriptome, including the hub genes involved in ROS scavenging, to prevent oxidative stress damage. Our results shed light on and provide deep insight into the drought resistance mechanism in rice.

Network-based approaches for understanding gene regulation and function in plants

Expression reprogramming directed by transcription factors is a primary gene regulation underlying most aspects of the biology of any organism. Our views of how gene regulation is coordinated are dramatically changing thanks to the advent and constant improvement of high-throughput profiling and transcriptional network inference methods: from activities of individual genes to functional interactions across genes. These technical and analytical advances can reveal the topology of transcriptional networks in which hundreds of genes are hierarchically regulated by multiple transcription factors at systems level. Here we review the state of the art of experimental and computational methods used in plant biology research to obtain large-scale datasets and model transcriptional networks. Examples of direct use of these network models and perspectives on their limitations and future directions are also discussed.

Expansion of the circadian transcriptome in Brassica rapa and genome-wide diversification of paralog expression patterns

An important challenge of crop improvement strategies is assigning function to paralogs in polyploid crops. Here we describe the circadian transcriptome in the polyploid crop Brassica rapa. Strikingly, almost three-quarters of the expressed genes exhibited circadian rhythmicity. Genetic redundancy resulting from whole genome duplication is thought to facilitate evolutionary change through sub- and neo-functionalization among paralogous gene pairs. We observed genome-wide expansion of the circadian expression phase among retained paralogous pairs. Using gene regulatory network models, we compared transcription factor targets between B. rapa and Arabidopsis circadian networks to reveal evidence for divergence between B. rapa paralogs that may be driven in part by variation in conserved non-coding sequences (CNS). Additionally, differential drought response among retained paralogous pairs suggests further functional diversification. These findings support the rapid expansion and divergence of the transcriptional network in a polyploid crop and offer a new approach for assessing paralog activity at the transcript level.

Effects of circadian clock and light on melatonin concentration in Hypericum perforatum L. (St. John's Wort)

BACKGROUND

Melatonin acts as a signaling hormone and entraining agent in many organisms. We studied the spatiotemporal regulation and influence of light (photoperiods, intensities, and spectral qualities) on melatonin concentration in the medicinal herb Hypericum perforatum L. Furthermore, melatonin concentrations in the leaves of eight species of the Hypericum genus were compared and analyzed using high-performance liquid chromatography.

RESULTS

Melatonin concentration was found to be the highest in its flowers and leaves. The leaves exhibited a rhythmic variation in melatonin concentration of approximately 24 h under both light-dark entrained (Zeitgeber time) and constant light [circadian time (CT)] conditions, with melatonin concentration peaking at approximately CT6 in the middle of the subjective day. Melatonin concentration was influenced significantly by not only photoperiods but also applied light's wavelength and intensity. It was approximately six times higher under long-day conditions (18-h light:6-h dark) than under short-day photoperiods (10-h light:14-h dark) and was the highest (131 μg/g fresh weight [FW]) under treatment with blue light at an intensity of 45 µmol·m2/s of photons. The melatonin concentration of the two examined Hypericum spp., namely H. kouytchense Lev. and H. coris L., were approximately twice that of H. perforatum L.

CONCLUSION

Our findings provide first insights on melatonin-related functions and mechanisms in the circadian system of H. perforatum and useful resources for further melatonin-oriented research and possible applications in agriculture and pharmaceutical industries.

Tripartite mutualisms as models for understanding plant-microbial interactions

All plants host diverse microbial assemblages that shape plant health, productivity, and function. While some microbial effects are attributable to particular symbionts, interactions among plant-associated microbes can nonadditively affect plant fitness and traits in ways that cannot be predicted from pairwise interactions. Recent research into tripartite plant-microbe mutualisms has provided crucial insight into this nonadditivity and the mechanisms underlying plant interactions with multiple microbes. Here, we discuss how interactions among microbial mutualists affect plant performance, highlight consequences of biotic and abiotic context-dependency for nonadditive outcomes, and summarize burgeoning efforts to determine the molecular bases of how plants regulate establishment, resource exchange, and maintenance of tripartite interactions. We conclude with four goals for future tripartite studies that will advance our overall understanding of complex plant-microbial interactions.