Weighted Gene Co-expression Network Analysis (WGCNA) Reveals the Hub Role of Protein Ubiquitination in the Acquisition of Desiccation Tolerance in Boea hygrometrica

Recent advances in exploring transcriptional regulatory landscape of crops

Crop breeding entails developing and selecting plant varieties with improved agronomic traits. Modern molecular techniques, such as genome editing, enable more efficient manipulation of plant phenotype by altering the expression of particular regulatory or functional genes. Hence, it is essential to thoroughly comprehend the transcriptional regulatory mechanisms that underpin these traits. In the multi-omics era, a large amount of omics data has been generated for diverse crop species, including genomics, epigenomics, transcriptomics, proteomics, and single-cell omics. The abundant data resources and the emergence of advanced computational tools offer unprecedented opportunities for obtaining a holistic view and profound understanding of the regulatory processes linked to desirable traits. This review focuses on integrated network approaches that utilize multi-omics data to investigate gene expression regulation. Various types of regulatory networks and their inference methods are discussed, focusing on recent advancements in crop plants. The integration of multi-omics data has been proven to be crucial for the construction of high-confidence regulatory networks. With the refinement of these methodologies, they will significantly enhance crop breeding efforts and contribute to global food security.

CWGCNA: an R package to perform causal inference from the WGCNA framework

WGCNA (weighted gene co-expression network analysis) is a very useful tool for identifying co-expressed gene modules and detecting their correlations to phenotypic traits. Here, we explored more possibilities about it and developed the R package CWGCNA (causal WGCNA), which works from the traditional WGCNA pipeline but mines more information. It couples a mediation model with WGCNA, so the causal relationships among WGCNA modules, module features, and phenotypes can be found, demonstrating whether the module change causes the phenotype change or vice versa. After that, when annotating the module gene set functions, it uses a novel network-based method, considering the modules' topological structures and capturing their influence on the gene set functions. In addition to conducting these biological explorations, CWGCNA also contains a machine learning section to perform clustering and classification on multi-omics data, given the increasing popularity of this data type. Some basic functions, such as differential feature identification, are also available in our package. Its effectiveness is proved by the performance on three single or multi-omics datasets, showing better performance than existing methods. CWGCNA is available at: https://github.com/yuabrahamliu/CWGCNA.

Specific metabolic and cellular mechanisms of the vegetative desiccation tolerance in resurrection plants for adaptation to extreme dryness

MAIN CONCLUSION

Substantial advancements have been made in our comprehension of vegetative desiccation tolerance in resurrection plants, and further research is still warranted to elucidate the mechanisms governing distinct cellular adaptations. Resurrection plants are commonly referred to as a small group of extremophile vascular plants that exhibit vegetative desiccation tolerance (VDT), meaning that their vegetative tissues can survive extreme drought stress (> 90% water loss) and subsequently recover rapidly upon rehydration. In contrast to most vascular plants, which typically employ water-saving strategies to resist partial water loss and optimize water absorption and utilization to a limited extent under moderate drought stress, ultimately succumbing to cell death when confronted with severe and extreme drought conditions, resurrection plants have evolved unique mechanisms of VDT, enabling them to maintain viability even in the absence of water for extended periods, permitting them to rejuvenate without harm upon water contact. Understanding the mechanisms associated with VDT in resurrection plants holds the promise of expanding our understanding of how plants adapt to exceedingly arid environments, a phenomenon increasingly prevalent due to global warming. This review offers an updated and comprehensive overview of recent advances in VDT within resurrection plants, with particular emphasis on elucidating the metabolic and cellular adaptations during desiccation, including the intricate processes of cell wall folding and the prevention of cell death. Furthermore, this review highlights existing unanswered questions in the field, suggests potential avenues for further research to gain deeper insights into the remarkable VDT adaptations observed in resurrection plants, and highlights the potential application of VDT-derived techniques in crop breeding to enhance tolerance to extreme drought stress.

Comprehensive dissection of variation and accumulation of free amino acids in tea accessions

Free amino acids (FAAs) positively determine the tea quality, notably theanine (Thea), endowing umami taste of tea infusion, which is the profoundly prevalent research in albino tea genetic resources. Therefore, 339 tea accessions were collected to study FAAs level for deciphering its variation and accumulation mechanism. Interestingly, alanine (Ala) and Thea which had the highest diversity index (H') value among three varieties of Camellia sinensis (L.) O. Kuntze were significantly higher than wild relatives (P < 0.05). The intraspecific arginine (Arg) and glutamine (Gln) contents in C. sinensis var. assamica were significantly lower than sinensis and pubilimba varieties. Moreover, the importance of interdependencies operating across FAAs and chlorophyll levels were highlighted via the cell ultrastructure, metabolomics, and transcriptome analysis. We then determined that the association between phytochrome interacting factor 1 (CsPIF1) identified by weighted gene co-expression network analysis (WGCNA) and Thea content. Intriguingly, transient knock-down CsPIF1 expression increased Thea content in tea plant, and the function verification of CsPIF1 in Arabidopsis also indicated that CsPIF1 acts as a negative regulator of Thea content by mainly effecting the genes expression related to Thea biosynthesis, transport, and hydrolysis, especially glutamate synthase (CsGOGAT), which was validated to be associated with Thea content with a nonsynonymous SNP by Kompetitive Allele-Specific PCR (KASP). We also investigated the interspecific and geographical distribution of this SNP. Taken together, these results help us to understand and clarify the variation and profile of major FAAs in tea germplasms and promote efficient utilization in tea genetic improvement and breeding.

Identification of Key Modules and Candidate Genes for Powdery Mildew Resistance of Wheat-Agropyron cristatum Translocation Line WAT-2020-17-6 by WGCNA

As one of the serious diseases of wheat, powdery mildew (Blumeria graminis f. sp. tritici) is a long-term threat to wheat production. Therefore, it is of great significance to explore new powdery mildew-resistant genes for breeding. The wild relative species of wheat provide gene resources for resistance to powdery mildew breeding. Agropyron cristatum (2n = 4x = 28, genomes PPPP) is an important wild relative of wheat, carrying excellent genes for high yield, disease resistance, and stress resistance, which can be used for wheat improvement. To understand the molecular mechanism of powdery mildew resistance in the wheat-A. cristatum translocation line WAT2020-17-6, transcriptome sequencing was performed, and the resistance genes were analyzed by weighted gene co-expression network analysis (WGCNA). In the results, 42,845 differentially expressed genes were identified and divided into 18 modules, of which six modules were highly correlated with powdery mildew resistance. Gene ontology (GO) enrichment analysis showed that the six interested modules related to powdery mildew resistance were significantly enriched in N-methyltransferase activity, autophagy, mRNA splicing via spliceosome, chloroplast envelope, and AMP binding. The candidate hub genes of the interested modules were further identified, and their regulatory relationships were analyzed based on co-expression data. The temporal expression pattern of the 12 hub genes was verified within 96 h after powdery mildew inoculation by RT-PCR assay. In this study, we preliminarily explained the resistance mechanism of the wheat-A. cristatum translocation lines and obtained the hub candidate genes, which laid a foundation in the exploration of resistance genes in A. cristatum for powdery mildew-resistant breeding in wheat.

Myco-Synergism Boosts Herbivory-Induced Maize Defense by Triggering Antioxidants and Phytohormone Signaling

BACKGROUND

Biocontrol strategies are the best possible and eco-friendly solution to develop resistance against O furnacalis and improve the maize yield. However, the knowledge about underlying molecular mechanisms, metabolic shifts, and hormonal signaling is limited.

METHODS

Here, we used an axenic and a consortium of entomopathogenic Beauveria bassiana OFDH1-5 and a pathogen-antagonistic Trichoderma asperellum GDFS1009 in maize and observed that consortium applications resulted in higher chlorophyll contents and antioxidants activities [superoxide dismutase (SOD), peroxidase (POD), proline, protease, and polyphenol oxidase (PPO)] with a decrease in O. furnacalis survival. We performed a comprehensive transcriptome and an untargeted metabolome profiling for the first time at a vegetative stage in fungal inoculated maize leaves at 0-, 12-, 24-, 48-, and 72-h post insect infestation.

RESULTS

The consortium of B. bassiana and T. asperellum leads to 80-95% of O. furnacalis mortality. A total of 13,156 differentially expressed genes were used for weighted gene coexpression network analysis. We identified the six significant modules containing thirteen candidate genes [protein kinase (GRMZM2G025459), acyl-CoA dehydrogenase (GRMZM5G864319), thioredoxin gene (GRMZM2G091481), glutathione S-transferase (GRMZM2G116273), patatin-like phospholipase gene (GRMZM2G154523), cytochrome P450 (GRMZM2G139874), protease inhibitor (GRMZM2G004466), (AC233926.1_FG002), chitinase (GRMZM2G453805), defensin (GRMZM2G392863), peroxidase (GRMZM2G144153), GDSL- like lipase (AC212068.4_FG005), and Beta-glucosidase (GRMZM2G031660)], which are not previously reported that are highly correlated with Jasmonic acid - Ethylene (JA-ET) signaling pathway and antioxidants. We detected a total of 130 negative and 491 positive metabolomic features using a ultrahigh-performance liquid chromatography ion trap time-of-flight mass spectrometry (UHPLC-QTOF-MS). Intramodular significance and real time-quantitative polymerase chain reaction (RT-qPCR) expressions showed that these genes are the true candidate genes. Consortium treated maize had higher jasmonic acid (JA), salicylic acid (SA), and ethylene (ET) levels.

CONCLUSION

Our results provide insights into the genetics, biochemicals, and metabolic diversity and are useful for future biocontrol strategies against ACB attacks.

MeWRKY IIas, Subfamily Genes of WRKY Transcription Factors From Cassava, Play an Important Role in Disease Resistance

Cassava (Manihot esculenta Crantz) is an important tropical crop for food, fodder, and energy. Cassava bacterial blight (CBB) caused by Xanthomonas axonopodis pv. manihotis (Xam) occurs in all cassava growing regions and threatens global cassava production. WRKY transcription factor family plays the essential roles during plant growth, development, and abiotic or biotic stress. Particularly, previous studies have revealed the important role of the group IIa WRKY genes in plant disease resistance. However, a comprehensive analysis of group IIa subfamily in cassava is still missing. Here, we identified 102 WRKY members, which were classified into three groups, I, II, and III. Transient expression showed that six MeWRKY IIas were localized in the nucleus. MeWRKY IIas transcripts accumulated significantly in response to SA, JA, and Xam. Overexpression of MeWRKY27 and MeWRKY33 in Arabidopsis enhanced its resistance to Pst DC3000. In contrast, silencing of MeWRKY27 and MeWRKY33 in cassava enhanced its susceptibility to Xam. Co-expression network analysis showed that different downstream genes are regulated by different MeWRKY IIa members. The functional analysis of downstream genes will provide clues for clarifying molecular mechanism of cassava disease resistance. Collectively, our results suggest that MeWRKY IIas are regulated by SA, JA signaling, and coordinate response to Xam infection.

Comparative analysis of physiological, agronomic and transcriptional responses to drought stress in wheat local varieties from Mongolia and Northern China

Drought is one of the major abiotic stresses that threaten wheat production worldwide, especially in the Mongolian Plateau and adjacent regions. This study aims to find local wheat varieties with high yields and drought resistance at various developmental stages based on agronomic traits and drought resistance indices analysis and explore the underlining molecular mechanisms by transcriptome analysis. Our results revealed that drought stress started at the seedling stage has a greater impact on crop yields. Four types of drought responses were found among the tested varieties. Type 1 and type 2 show low tolerance to drought stress despite high or low yield in control condition, type 3 exhibits high yield under control condition but dropped significantly after drought, and type 4 displays relatively high and stable yields under control and drought conditions. Transcriptome analysis performed with the representative varieties of the four types revealed GO terms and KEGG pathways enriched among drought-triggered differential expressed genes (DEGs). A network containing 18 modules was constructed using weighted gene co-expression analysis (WGCNA). Ten modules were significantly correlated to yield by module-trait correlation, and 3 modules showed Darkhan 144 specific gene expression patterns. C2H2 zinc finger factor-recognized motifs were identified from the promoters of genes in these modules. qRT-PCR confirmed several key DEGs with specific expression patterns and physiological measurements validated the relatively low oxidative damage and high antioxidant capacity in the drought tolerant variety Dankhan 144. These findings provide an important basis for local agriculture and breeding of drought-tolerant high yield wheat varieties.

Crops for dry environments

Climate change necessitates increased stress resilience of food crops. We describe four potential solutions, with emphasis on a relatively novel approach aiming at true tolerance of drought rather than improved water-holding capacity of crops, which is a common approach in current breeding and genome editing efforts. Some Angiosperms are known to tolerate loss of 95% of their cellular water, without dying, not dissimilar to seeds. The molecular mechanisms and their regulation underlying this remarkable ability are potentially useful to design tolerant crops. Since most crops produce desiccation tolerant seeds, genomic information for this attribute is present but inactive in vegetative parts of the plant. Based on recent evidence from both seeds and desiccation tolerant Angiosperms we address possible routes to 'flipping the switch' to vegetative desiccation tolerance in major crops.

From gene to biomolecular networks: a review of evidences for understanding complex biological function in plants

Although at the infancy stage, biomolecular network biology is a comprehensive approach to understand complex biological function in plants. Recent advancements in the accumulation of multi-omics data coupled with computational approach have accelerated our current understanding of the complexities of gene function at the system level. Biomolecular networks such as protein-protein interaction, co-expression and gene regulatory networks have extensively been used to decipher the intricacies of transcriptional reprogramming of hundreds of genes and their regulatory interaction in response to various environmental perturbations mainly in the model plant Arabidopsis. This review describes recent applications of network-based approaches to understand the biological functions in plants and focuses on the challenges and opportunities to harness the full potential of the approach.

A Label-Free Proteomic and Complementary Metabolomic Analysis of Leaves of the Resurrection Plant Xerophytaschlechteri during Dehydration

Vegetative desiccation tolerance, or the ability to survive the loss of ~95% relative water content (RWC), is rare in angiosperms, with these being commonly called resurrection plants. It is a complex multigenic and multi-factorial trait, with its understanding requiring a comprehensive systems biology approach. The aim of the current study was to conduct a label-free proteomic analysis of leaves of the resurrection plant Xerophyta schlechteri in response to desiccation. A targeted metabolomics approach was validated and correlated to the proteomics, contributing the missing link in studies on this species. Three physiological stages were identified: an early response to drying, during which the leaf tissues declined from full turgor to a RWC of ~80–70%, a mid-response in which the RWC declined to 40% and a late response where the tissues declined to 10% RWC. We identified 517 distinct proteins that were differentially expressed, of which 253 proteins were upregulated and 264 were downregulated in response to the three drying stages. Metabolomics analyses, which included monitoring the levels of a selection of phytohormones, amino acids, sugars, sugar alcohols, fatty acids and organic acids in response to dehydration, correlated with some of the proteomic differences, giving insight into the biological processes apparently involved in desiccation tolerance in this species.

Optimizing weighted gene co-expression network analysis with a multi-threaded calculation of the topological overlap matrix

Biomolecular networks are often assumed to be scale-free hierarchical networks. The weighted gene co-expression network analysis (WGCNA) treats gene co-expression networks as undirected scale-free hierarchical weighted networks. The WGCNA R software package uses an Adjacency Matrix to store a network, next calculates the topological overlap matrix (TOM), and then identifies the modules (sub-networks), where each module is assumed to be associated with a certain biological function. The most time-consuming step of WGCNA is to calculate TOM from the Adjacency Matrix in a single thread. In this paper, the single-threaded algorithm of the TOM has been changed into a multi-threaded algorithm (the parameters are the default values of WGCNA). In the multi-threaded algorithm, Rcpp was used to make R call a C++ function, and then C++ used OpenMP to start multiple threads to calculate TOM from the Adjacency Matrix. On shared-memory MultiProcessor systems, the calculation time decreases as the number of CPU cores increases. The algorithm of this paper can promote the application of WGCNA on large data sets, and help other research fields to identify sub-networks in undirected scale-free hierarchical weighted networks. The source codes and usage are available at https://github.com/do-somethings-haha/multi-threaded_calculate_unsigned_TOM_from_unsigned_or_signed_Adjacency_Matrix_of_WGCNA.

Systems biology for crop improvement

In recent years, generation of large-scale data from genome, transcriptome, proteome, metabolome, epigenome, and others, has become routine in several plant species. Most of these datasets in different crop species, however, were studied independently and as a result, full insight could not be gained on the molecular basis of complex traits and biological networks. A systems biology approach involving integration of multiple omics data, modeling, and prediction of the cellular functions is required to understand the flow of biological information that underlies complex traits. In this context, systems biology with multiomics data integration is crucial and allows a holistic understanding of the dynamic system with the different levels of biological organization interacting with external environment for a phenotypic expression. Here, we present recent progress made in the area of various omics studies-integrative and systems biology approaches with a special focus on application to crop improvement. We have also discussed the challenges and opportunities in multiomics data integration, modeling, and understanding of the biology of complex traits underpinning yield and stress tolerance in major cereals and legumes.

DNA methylation-mediated modulation of rapid desiccation tolerance acquisition and dehydration stress memory in the resurrection plant Boea hygrometrica

Pre-exposure of plants to various abiotic conditions confers improved tolerance to subsequent stress. Mild drought acclimation induces acquired rapid desiccation tolerance (RDT) in the resurrection plant Boea hygrometrica, but the mechanisms underlying the priming and memory processes remain unclear. In this study, we demonstrated that drought acclimation-induced RDT can be maintained for at least four weeks but was completely erased after 18 weeks based on a combination of the phenotypic and physiological parameters. Global transcriptome analysis identified several RDT-specific rapid dehydration-responsive genes related to cytokinin and phospholipid biosynthesis, nitrogen and carbon metabolism, and epidermal morphogenesis, most of which were pre-induced by drought acclimation. Comparison of whole-genome DNA methylation revealed dehydration stress-responsive hypomethylation in the CG, CHG, and CHH contexts and acclimation-induced hypermethylation in the CHH context of the B. hygrometrica genome, consistent with the transcriptional changes in methylation pathway genes. As expected, the global promoter and gene body methylation levels were negatively correlated with gene expression levels in both acclimated and dehydrated plants but showed no association with transcriptional divergence during the procedure. Nevertheless, the promoter methylation variations in the CG and CHG contexts were significantly associated with the differential expression of genes required for fundamental genetic processes of DNA conformation, RNA splicing, translation, and post-translational protein modification during acclimation, growth, and rapid dehydration stress response. It was also associated with the dehydration stress-induced upregulation of memory genes, including pre-mRNA-splicing factor 38A, vacuolar amino acid transporter 1-like, and UDP-sugar pyrophosphorylase, which may contribute directly or indirectly to the improvement of dehydration tolerance in B. hygrometrica plants. Altogether, our findings demonstrate the potential implications of DNA methylation in dehydration stress memory and, therefore, provide a molecular basis for enhanced dehydration tolerance in plants induced by drought acclimation.

Drought is a major adverse environmental condition affecting plant growth and productivity. Although plants can be trained to improved tolerance to the subsequent drought stress, most land plants are unable to recover from severe dehydration when the relative water content in their vegetative tissues drops below 20–30%. However, a small group of angiosperms, termed resurrection plants, can survive extreme water deficiency of their vegetative tissues to an air-dried state and recovered upon rehydration. Understanding the biochemical and molecular basis of desiccation tolerance is valuable for extending our knowledge of the maximum ability of plants to deal with extreme water loss. Boea hygrometrica is a well-characterized resurrection plant that can not only tolerate slow dehydration but also extend its ability to survive rapid dehydration after a priming process of slow dehydration and rehydration. The rapid desiccation tolerance in primed plants can be maintained for at least four weeks. Here, we utilized this system of drought acclimation-induced RDT acquisition, maintenance, and erasing to explore plant phenotypic, physiological, and transcriptional changes, as well as DNA methylation dynamics. The analyses of the effect of DNA methylation on gene expression and promoter methylation changes with differential gene expression revealed the putative epigenetic control of dehydration stress memory in plants.

Expression dynamics of dehydration tolerance in the tropical plant Marchantia inflexa

Tolerance to prolonged water deficit occurs along a continuum in plants, with dehydration tolerance (DhT) and desiccation tolerance (DT) representing some of the most extreme adaptations to water scarcity. Although DhT and DT presumably vary among individuals of a single species, this variability remains largely unstudied. Here, we characterized expression dynamics throughout a dehydration-rehydration time-course in six diverse genotypes of the dioecious liverwort Marchantia inflexa. We identified classical signatures of stress response in M. inflexa, including major changes in transcripts related to metabolism, expression of LEA and ELIP genes, and evidence of cell wall remodeling. However, we detected very little temporal synchronization of these responses across different genotypes of M. inflexa, which may be related to genotypic variation among samples, constitutive expression of dehydration-associated transcripts, the sequestration of mRNAs in ribonucleoprotein partials prior to drying, or the lower tolerance of M. inflexa relative to most bryophytes studied to date. Our characterization of intraspecific variation in expression dynamics suggests that differences in the timing of transcriptional adjustments contribute to variation among genotypes, and that developmental differences impact the relative tolerance of meristematic and differentiated tissues. This work highlights the complexity and variability of water stress tolerance, and underscores the need for comparative studies that seek to characterize variation in DT and DhT.

Gene co-expression network analysis to identify critical modules and candidate genes of drought-resistance in wheat

AIM

To establish a gene co-expression network for identifying principal modules and hub genes that are associated with drought resistance mechanisms, analyzing their mechanisms, and exploring candidate genes.

METHODS AND FINDINGS

42 data sets including PRJNA380841 and PRJNA369686 were used to construct the co-expression network through weighted gene co-expression network analysis (WGCNA). A total of 1,896,897,901 (284.30 Gb) clean reads and 35,021 differentially expressed genes (DEGs) were obtained from 42 samples. Functional enrichment analysis indicated that photosynthesis, DNA replication, glycolysis/gluconeogenesis, starch and sucrose metabolism, arginine and proline metabolism, and cell cycle were significantly influenced by drought stress. Furthermore, the DEGs with similar expression patterns, detected by K-means clustering, were grouped into 29 clusters. Genes involved in the modules, such as dark turquoise, yellow, and brown, were found to be appreciably linked with drought resistance. Twelve central, greatly correlated genes in stage-specific modules were subsequently confirmed and validated at the transcription levels, including TraesCS7D01G417600.1 (PP2C), TraesCS5B01G565300.1 (ERF), TraesCS4A01G068200.1 (HSP), TraesCS2D01G033200.1 (HSP90), TraesCS6B01G425300.1 (RBD), TraesCS7A01G499200.1 (P450), TraesCS4A01G118400.1 (MYB), TraesCS2B01G415500.1 (STK), TraesCS1A01G129300.1 (MYB), TraesCS2D01G326900.1 (ALDH), TraesCS3D01G227400.1 (WRKY), and TraesCS3B01G144800.1 (GT).

CONCLUSIONS

Analyzing the response of wheat to drought stress during different growth stages, we have detected three modules and 12 hub genes that are associated with drought resistance mechanisms, and five of those genes are newly identified for drought resistance. The references provided by these modules will promote the understanding of the drought-resistance mechanism. In addition, the candidate genes can be used as a basis of transgenic or molecular marker-assisted selection for improving the drought resistance and increasing the yields of wheat.

Decoding Gene Networks Modules That Explain the Recovery of Hymenoglossum cruentum Cav. After Extreme Desiccation

Hymenoglossum cruentum (Hymenophyllaceae) is a poikilohydric, homoiochlorophyllous desiccation-tolerant (DT) epiphyte fern. It can undergo fast and frequent dehydration-rehydration cycles. This fern is highly abundant at high-humidity/low-light microenvironments within the canopy, although rapid changes in humidity and light intensity are frequent. The objective of this research is to identify genes associated to desiccation-rehydration cycle in the transcriptome of H. cruentum to better understand the genetic dynamics behind its desiccation tolerance mechanism. H. cruentum plants were subjected to a 7 days long desiccation-rehydration process and then used to identify key expressed genes associated to its capacity to dehydrate and rehydrate. The relative water content (RWC) and maximum quantum efficiency (F v/F m) of H. cruentum fronds decayed to 6% and 0.04, respectively, at the end of the desiccation stage. After re-watering, the fern showed a rapid recovery of RWC and F v/F m (ca. 73% and 0.8, respectively). Based on clustering and network analysis, our results reveal key genes, such as UBA/TS-N, DYNLL, and LHC, orchestrating intracellular motility and photosynthetic metabolism; strong balance between avoiding cell death and defense (CAT3, AP2/ERF) when dehydrated, and detoxifying pathways and stabilization of photosystems (GST, CAB2, and ELIP9) during rehydration. Here we provide novel insights into the genetic dynamics behind the desiccation tolerance mechanism of H. cruentum.