WGCNA Analysis of Salt-Responsive Core Transcriptome Identifies Novel Hub Genes in Rice

Comprehensive Transcriptome and Proteome Analyses Reveal the Drought Responsive Gene Network in Potato Roots

The root system plays a decisive role in the growth and development of plants. The water requirement of a root system depends strongly on the plant species. Potatoes are an important food and vegetable crop grown worldwide, especially under irrigation in arid and semi-arid regions. However, the expected impact of global warming on potato yields calls for an investigation of genes related to root development and drought resistance signaling pathways in potatoes. In this study, we investigated the molecular mechanisms of different drought-tolerant potato root systems in response to drought stress under controlled water conditions, using potato as a model. We analyzed the transcriptome and proteome of the drought-sensitive potato cultivar Atlantic (Atl) and the drought-tolerant cultivar Qingshu 9 (Q9) under normal irrigation (CK) and weekly drought stress (D). The results showed that a total of 14,113 differentially expressed genes (DEGs) and 5596 differentially expressed proteins (DEPs) were identified in the cultivars. A heat map analysis of DEGs and DEPs showed that the same genes and proteins in Atl and Q9 exhibited different expression patterns under drought stress. Weighted gene correlation network analysis (WGCNA) showed that in Atl, Gene Ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG)-enriched pathways were related to pyruvate metabolism and glycolysis, as well as cellular signaling and ion transmembrane transporter protein activity. However, GO terms and KEGG-enriched pathways related to phytohormone signaling and the tricarboxylic acid cycle were predominantly enriched in Q9. The present study provides a unique genetic resource to effectively explore the functional genes and uncover the molecular regulatory mechanism of the potato root system in response to drought stress.

Weighted gene co-expression network analysis reveals hub genes regulating response to salt stress in peanut

Peanut (Arachis hypogaea L.) is an important oilseed crop worldwide. However, soil salinization becomes one of the main limiting factors of peanut production. Therefore, developing salt-tolerant varieties and understanding the molecular mechanisms of salt tolerance is important to protect peanut yield in saline areas. In this study, we selected four peanut varieties with contrasting response to salt challenges with T1 and T2 being tolerance and S1 and S2 being susceptible. High-throughput RNA sequencing resulted in more than 314.63 Gb of clean data from 48 samples. We identified 12,057 new genes, 7,971of which have functional annotations. KEGG pathway enrichment analysis of uniquely expressed genes in salt-tolerant peanut revealed that upregulated genes in the root are involved in the MAPK signaling pathway, fatty acid degradation, glycolysis/gluconeogenesis, and upregulated genes in the shoot were involved in plant hormone signal transduction and the MAPK signaling pathway. Na+ content, K+ content, K+/ Na+, and dry mass were measured in root and shoot tissues, and two gene co-expression networks were constructed based on weighted gene co-expression network analysis (WGCNA) in root and shoot. In this study, four key modules that are highly related to peanut salt tolerance in root and shoot were identified, plant hormone signal transduction, phenylpropanoid biosynthesis, starch and sucrose metabolism, flavonoid biosynthesis, carbon metabolism were identified as the key biological processes and metabolic pathways for improving peanut salt tolerance. The hub genes include genes encoding ion transport (such as HAK8, CNGCs, NHX, NCL1) protein, aquaporin protein, CIPK11 (CBL-interacting serine/threonine-protein kinase 11), LEA5 (late embryogenesis abundant protein), POD3 (peroxidase 3), transcription factor, and MAPKKK3. There were some new salt-tolerant genes identified in peanut, including cytochrome P450, vinorine synthase, sugar transport protein 13, NPF 4.5, IAA14, zinc finger CCCH domain-containing protein 62, beta-amylase, fatty acyl-CoA reductase 3, MLO-like protein 6, G-type lectin S-receptor-like serine/threonine-protein kinase, and kinesin-like protein KIN-7B. The identification of key modules, biological pathways, and hub genes in this study enhances our understanding of the molecular mechanisms underlying salt tolerance in peanuts. This knowledge lays a theoretical foundation for improving and innovating salt-tolerant peanut germplasm.

Analysis of huanglongbing-associated RNA-seq data reveals disturbances in biological processes within Citrus spp. triggered by Candidatus Liberibacter asiaticus infection

Introduction

Huanglongbing (HLB), a disease that's ubiquitous worldwide, wreaks havoc on the citrus industry. The primary culprit of HLB is the gram-negative bacterium Candidatus Liberibacter asiaticus (CLas) that infects the phloem, but its damaging mechanism is yet to be fully understood.

Methods and results

In this study, a multitude of tools including weighted correlation network analysis (WGCNA), protein-protein interaction (PPI) network analysis and gene expression profiling are employed to unravel the intricacies of its pathogenesis. The investigation pinpoints various central genes, such as the ethylene-responsive transcription factor 9 (ERF9) and thioredoxin reductase 1 (TrxR1), that are associated with CLas invasion and resultant disturbances in numerous biological operations. Additionally, the study uncovers a range of responses through the detection of differential expressed genes (DEGs) across different experiments. The discovery of core DEGs leads to the identification of pivotal genes such as the sieve element occlusion (SEO) and the wall-associated receptor kinase-like 15 (WAKL15). PPI network analysis highlights potential vital proteins, while GO and KEGG pathway enrichment analysis illustrate a significant impact on multiple defensive and metabolic pathways. Gene set enrichment analysis (GSEA) indicates significant alterations in biological processes such as leaf senescence and response to biotic stimuli.

Discussion

This all-encompassing approach extends valuable understanding into the pathogenesis of CLas, potentially aiding future research and therapeutic strategies for HLB.

Mining key circRNA-associated-ceRNA networks for milk fat metabolism in cows with varying milk fat percentages

BACKGROUND

Cow milk fat is an essential indicator for evaluating and measuring milk quality and cow performance. Growing research has identified the molecular functions of circular RNAs (circRNAs) necessary for mammary gland development and lactation in mammals.

METHOD

The present study analyzed circRNA expression profiling data in mammary epithelial cells (MECs) from cows with highly variable milk fat percentage (MFP) using differential expression analysis and weighted gene co-expression network analysis (WGCNA).

RESULTS

A total of 309 differentially expressed circRNAs (DE-circRNAs) were identified in the high and low MFP groups. WGCNA analysis revealed that the pink module was significantly associated with MFP (r = - 0.85, P = 0.007). Parental genes of circRNAs in this module were enriched mainly in lipid metabolism-related signaling pathways, such as focal adhesion, ECM-receptor interaction, adherens junction and AMPK. Finally, six DE-circRNAs were screened from the pink module: circ_0010571, circ_0007797, circ_0002746, circ_0003052, circ_0004319, and circ_0012840. Among them, circ_0002746, circ_0003052, circ_0004319, and circ_0012840 had circular structures and were highly expressed in mammary tissues. Subcellular localization revealed that these four DE-circRNAs may play a regulatory role in the mammary glands of dairy cows, mainly as competitive endogenous RNAs (ceRNAs). Seven hub target genes (GNB1, GNG2, PLCB1, PLCG1, ATP6V0C, NDUFS4, and PIGH) were obtained by constructing the regulatory network of their ceRNAs and then analyzed by CytoHubba and MCODE plugins in Cytoscape. Functional enrichment analysis revealed that these genes are crucial and most probable ceRNA regulators in milk fat metabolism.

CONCLUSIONS

Our study identified several vital circRNAs and ceRNAs affecting milk fat synthesis, providing new research ideas and a theoretical basis for cow lactation, milk quality, and breed improvement.

Comparison of Transcriptome Differences between Two Rice Cultivars Differing in Cadmium Translocation from Spike-Neck to Grain

At present, the mechanism of varietal differences in cadmium (Cd) accumulation in rice is not well understood. Two rice cultivars, ZZY (high translocation-high grain Cd) and SJ18 (low translocation-low grain Cd), were used to analyze transcriptome differences in the spike-neck tissue in field trials. The results showed that, compared with ZZY, 22,367 differentially expressed genes (DEGs) were identified in SJ18, including 2941 upregulated and 19,426 downregulated genes. GO analysis enriched 59 downregulated terms, concerning 24 terms enriched for more than 1000 DEGs, including cellular and metabolic processes, biological regulation, localization, catalytic activity, transporter activity, signaling, etc. KEGG enrichment identified 21 significant downregulated pathways, regarding the ribosome, metabolic pathways, biosynthesis of secondary metabolism, signaling transduction, cell membrane and cytoskeleton synthesis, genetic information transfer, amino acid synthesis, etc. Weighted gene co-expression network analysis (WGCNA) revealed that these DEGs could be clustered into five modules. Among them, the yellow module was significantly related to SJ18 with hub genes related to OsHMA and OsActin, whereas the brown module was significantly related to ZZY with hub genes related to mitogen-activated protein kinase (MAPK), CBS, and glutaredoxin. This suggests that different mechanisms are involved in the process of spike-neck-grain Cd translocation among varieties. This study provides new insights into the mechanisms underlying differences in Cd transport among rice varieties.

A meta-analysis highlights the cross-resistance of plants to drought and salt stresses from physiological, biochemical, and growth levels

In nature, drought and salt stresses often occur simultaneously and affect plant growth at multiple levels. However, the mechanisms underlying plant responses to drought and salt stresses and their interactions are still not fully understood. We performed a meta-analysis to compare the effects of drought, salt, and combined stresses on plant physiological, biochemical, morphological and growth traits, analyze the different responses of C3 and C4 plants, as well as halophytes and non-halophytes, and identify the interactive effects on plants. There were numerous similarities in plant responses to drought, salt, and combined stresses. C4 plants had a more effective antioxidant defense system, and could better maintain above-ground growth. Halophytes could better maintain photosynthetic rate (Pn) and relative water content (RWC), and reduce growth as an adaptation strategy. The responses of most traits (Pn, RWC, chlorophyll content, soluble sugar content, H2O2 content, plant dry weight, etc.) to combined stress were less-than-additive, indicating cross-resistance rather than cross-sensitivity of plants to drought and salt stresses. These results are important to improve our understanding of drought and salt cross-resistance mechanisms and further induce resistance or screen-resistant varieties under stress combination.

Study on changing disciplinarian of beak colors in ducks and the regulation network based on transcriptome sequencing

Beak color in ducks is a primary characteristic of local breeds and genetic resources. Among them, black beaks, a rare packaging trait of high-quality duck products, have attracted much attention. In this study, Runzhou White Created ducks (black beak) and white-feathered Putian black ducks (yellow beak) were used to construct the F2 generation resource population to study the changing discipline of beak color combined with the beak color statistics of gray-beaked ducklings of Runzhou White Created ducks. Subsequently, transcriptome sequencing was performed to identify genetic markers related to beak color. To explore the rules of beak color change and its regulatory network, trends, and trend analysis and weighted gene co-expression network analysis（WGCNA）were performed. The screening results were verified by real-time quantitative polymerase chain reaction. A large difference was observed between the beak colors of birds from the F1 generation at 0 and 42 d of age. The F2 generation results show that nearly half of the black-beaked ducklings become green-beaked; the proportion of black spots for gray- and patterned-beaked ducklings increases with age, with most becoming green-beaked. Moreover, the beak color darkened from the first day, and the gray color value decreased significantly from the second day. Transcriptome sequencing indicated that TYR was differentially expressed between black and yellow beaks at 4 to 6 wk of age, and trend and WGCNA analyses showed that EDNRB signaling pathway genes and MITF were highly expressed in the first week, and TYR, TYRP1, and DCT were highly expressed at 4 to 6 wk of age. Therefore, there is melanin synthesis and deposition after hatching for gray- and patterned-beaked ducklings, while the yellow pigment might be deposited in the epidermis of beaks for black-beaked ducklings. The EDNRB signaling pathway is probably involved in early melanosome maturation and melanin formation in duck beaks, and genes such as TYR can maintain the black-beak phenotype.

RNA-Seq-Based WGCNA and Association Analysis Reveal the Key Regulatory Module and Genes Responding to Salt Stress in Wheat Roots

Soil salinization is the main abiotic stressor faced by crops. An improved understanding of the transcriptional response to salt stress in roots, the organ directly exposed to a high salinity environment, can inform breeding strategies to enhance tolerance and increase crop yield. Here, RNA-sequencing was performed on the roots of salt-tolerant wheat breeding line CH7034 at 0, 1, 6, 24, and 48 h after NaCl treatment. Based on transcriptome data, a weighted gene co-expression network analysis (WGCNA) was constructed, and five gene co-expression modules were obtained, of which the blue module was correlated with the time course of salt stress at 1 and 48 h. Two GO terms containing 249 differentially expressed genes (DEGs) related to osmotic stress response and salt-stress response were enriched in the blue module. These DEGs were subsequently used for association analysis with a set of wheat germplasm resources, and the results showed that four genes, namely a Walls Are Thin 1-related gene (TaWAT), an aquaporin gene (TaAQP), a glutathione S-transfer gene (TaGST), and a zinc finger gene (TaZFP), were associated with the root salt-tolerance phenotype. Using the four candidate genes as hub genes, a co-expression network was constructed with another 20 DEGs with edge weights greater than 0.6. The network showed that TaWAT and TaAQP were mainly co-expressed with fifteen interacting DEGs 1 h after salt treatment, while TaGST and TaZFP were mainly co-expressed with five interacting DEGs 48 h after salt treatment. This study provides key modules and candidate genes for understanding the salt-stress response mechanism in wheat roots.

Differential expression of the genes encoding immune system components in response to Pseudomonas syringae and Pseudomonas aeruginosa in Arabidopsis thaliana

In innate immunity, the first layer of defense against any microbial infection is triggered by the perception of pathogen-associated molecular patterns by highly specific pattern recognition receptors. The Pseudomonas syringae pv. tomato and Pseudomonas aeruginosa are plant-pathogenic bacterial species that include pathogenic strains in a wide range of different plant species. In the current study, extensive analysis including gene expression of 12 hub genes, gene ontology, protein-protein interaction, and cis-element prediction to dissect the Arabidopsis response to above-mentioned bacteria were performed. Further, we evaluated weighted co-expression network analysis (WGCNA) in the wild-type plants and coi-1 mutant line and determined changes in responsive genes at two time-points (4 and 8 h) of post-treatment with P. syringae and P. aeruginosa. Compared to the wild-type plants, coi-1 mutant showed significant expression in most of the genes involved, indicating that their protein products have important role in innate immunity and RNA silencing pathways. Our findings showed that 12 hub genes were co-expressed in response to P. syringae and P. aeruginosa infections. Based on the network analysis, transcription factors, receptors, protein kinase, and pathogenesis-related protein (PR1) were involved in the immunity system. Gene ontology related to each module was involved in defense response, protein serine kinase activity, and primary miRNA processing. Based on the cis-elements prediction, MYB, MYC, WRE3, W-box, STRE, and ARE contained the most number of cis-elements in co-expressed network genes. Also, in coi-1 mutant, most responsive genes against theses pathogens were up-regulated. The knowledge gained in the gene expression analysis in response to P. syringae and P. aeruginosa in the model plant, i.e., Arabidopsis, is essential to allow us to gain more insight about the innate immunity in other crops.

Weighted Gene Co-Expression Network Analysis Based on Stimulation by Lipopolysaccharides and Polyinosinic:polycytidylic Acid Provides a Core Set of Genes for Understanding Hemolymph Immune Response Mechanisms of Amphioctopus fangsiao

The primary influencer of aquaculture quality in Amphioctopus fangsiao is pathogen infection. Both lipopolysaccharides (LPS) and polyinosinic:polycytidylic acid (Poly I:C) are recognized by the pattern recognition receptor (PRR) within immune cells, a system that frequently serves to emulate pathogen invasion. Hemolymph, which functions as a transport mechanism for immune cells, offers vital transcriptome information when A. fangsiao is exposed to pathogens, thereby contributing to our comprehension of the species' immune biological mechanisms. In this study, we conducted analyses of transcript profiles under the influence of LPS and Poly I:C within a 24 h period. Concurrently, we developed a Weighted Gene Co-expression Network Analysis (WGCNA) to identify key modules and genes. Further, we carried out Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses to investigate the primary modular functions. Co-expression network analyses unveiled a series of immune response processes following pathogen stress, identifying several key modules and hub genes, including PKMYT1 and NAMPT. The invaluable genetic resources provided by our results aid our understanding of the immune response in A. fangsiao hemolymph and will further our exploration of the molecular mechanisms of pathogen infection in mollusks.

Joint QTL Mapping and Transcriptome Sequencing Analysis Reveal Candidate Genes for Salinity Tolerance in Oryza sativa L. ssp. Japonica Seedlings

Salinity stress is one of the major abiotic stresses affecting crop growth and production. Rice is an important food crop in the world, but also a salt-sensitive crop, and the rice seedling stage is the most sensitive to salt stress, which directly affects the final yield formation. In this study, two RIL populations derived from the crosses of CD (salt-sensitive)/WD (salt-tolerant) and KY131 (salt-sensitive)/XBJZ (salt-tolerant) were used as experimental materials, and the score of salinity toxicity (SST), the relative shoot length (RSL), the relative shoot fresh weight (RSFW), and the relative shoot dry weight (RSDW) were used for evaluating the degree of tolerance under salt stress in different lines. The genetic linkage map containing 978 and 527 bin markers were constructed in two RIL populations. A total of 14 QTLs were detected on chromosomes 1, 2, 3, 4, 7, 9, 10, 11, and 12. Among them, qSST12-1, qSST12-2, and qRSL12 were co-localized in a 140-kb overlap interval on chromosome 12, which containing 16 candidate genes. Furthermore, transcriptome sequencing and qRT-PCR were analyzed in CD and WD under normal and 120 mM NaCl stress. LOC_Os12g29330, LOC_Os12g29350, LOC_Os12g29390, and LOC_Os12g29400 were significantly induced by salt stress in both CD and WD. Sequence analysis showed that LOC_Os12g29400 in the salt-sensitive parents CD and KY131 was consistent with the reference sequence (Nipponbare), whereas the salt-tolerant parents WD and XBJZ differed significantly from the reference sequence both in the promoter and exon regions. The salt-tolerant phenotype was identified by using two T3 homozygous mutant plants of LOC_Os12g29400; the results showed that the score of salinity toxicity (SST) of the mutant plants (CR-3 and CR-5) was significantly lower than that of the wild type, and the seedling survival rate (SSR) was significantly higher than that of the wild type, which indicated that LOC_Os12g29400 could negatively regulate the salinity tolerance of rice at the seedling stage. The results lay a foundation for the analysis of the molecular mechanism of rice salinity tolerance and the cultivation of new rice varieties.

Phenomic and transcriptomic analyses reveal the sequential synthesis of Fe3O4 nanoparticles in Acidithiobacillus ferrooxidans BYM

IMPORTANCE

As the most important non-magnetotactic magnetosome-producing bacteria, Acidithiobacillus ferrooxidans only requires very mild conditions to produce Fe3O4 nanoparticles, thus conferring greater flexibility and potential application in biomagnetic nanoparticle production. However, the available information cannot explain the mechanism of Fe3O4 nanoparticle formation in A. ferrooxidans. In this study, we applied phenomic and transcriptomic analyses to reveal this mechanism. We found that different treatment condition factors notably affect the phenomic data of Fe3O4 nanoparticle in A. ferrooxidans. Using transcriptomic analyses, the gene network controlling/regulating Fe3O4 nanoparticle biogenesis in A. ferrooxidans was proposed, excavating the candidate hub genes for Fe3O4 nanoparticle formation in A. ferrooxidans. Based on this information, a sequential model for Fe3O4 nanoparticle synthesis in A. ferrooxidans was hypothesized. It lays the groundwork for further clarifying the feature of Fe3O4 nanoparticle synthesis.

Transcriptome Analysis and QTL Mapping Identify Candidate Genes and Regulatory Mechanisms Related to Low-Temperature Germination Ability in Maize

Low-temperature germination ability (LTGA) is an important characteristic for spring sowing maize. However, few maize genes related to LTGA were confirmed, and the regulatory mechanism is less clear. Here, maize-inbred lines Ye478 and Q1 with different LTGA were used to perform transcriptome analysis at multiple low-temperature germination stages, and a co-expression network was constructed by weighted gene co-expression network analysis (WGCNA). Data analysis showed that 7964 up- and 5010 down-regulated differentially expressed genes (DEGs) of Ye478 were identified at low-temperature germination stages, while 6060 up- and 2653 down-regulated DEGs of Q1 were identified. Gene ontology (GO) enrichment analysis revealed that ribosome synthesis and hydrogen peroxide metabolism were enhanced and mRNA metabolism was weakened under low-temperature stress for Ye478, while hydrogen peroxide metabolism was enhanced and mRNA metabolism was weakened for Q1. DEGs pairwise comparisons between the two genotypes found that Ye478 performed more ribosome synthesis at low temperatures compared with Q1. WGCNA analysis based on 24 transcriptomes identified 16 co-expressed modules. Of these, the MEbrown module was highly correlated with Ye478 at low-temperature stages and catalase and superoxide dismutase activity, and the MEred, MEgreen, and MEblack modules were highly correlated with Ye478 across low-temperature stages, which revealed a significant association between LTGA and these modules. GO enrichment analysis showed the MEbrown and MEred modules mainly functioned in ribosome synthesis and cell cycle, respectively. In addition, we conducted quantitative trait loci (QTL) analysis based on a doubled haploid (DH) population constructed by Ye478 and Q1 and identified a major QTL explanting 20.6% of phenotype variance on chromosome 1. In this QTL interval, we found three, four, and three hub genes in the MEbrown, MEred, and MEgreen modules, of which two hub genes (Zm00001d031951, Zm00001d031953) related to glutathione metabolism and one hub gene (Zm00001d031617) related to oxidoreductase activity could be the candidate genes for LTGA. These biological functions and candidate genes will be helpful in understanding the regulatory mechanism of LTGA and the directional improvement of maize varieties for LTGA.

Comparative transcriptome analysis reveals key genes and coordinated mechanisms in two rice cultivars differing in cadmium accumulation

Although Cd accumulation varies among rice varieties is recognized, the underlying mechanisms are not well clarified. In this study, comparative transcriptome analysis were performed by hydroponic culture system with two rice varieties, Y1540 (high Cd accumulator) and Y15 (low Cd accumulator) under 20 μM Cd stress. Results revealed 17,320 differentially expressed genes (DEGs) in roots of Y15 (7,655 upregulated and 9,665 downregulated) and 17,386 DEGs in roots of Y1540 (8,823 upregulated and 8,563 downregulated) expose to 20 μM Cd stress. Gene ontology (GO) analysis enriched 24 and 26 terms in Y15 and Y1540 respectively, including 23 common terms. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment showed 27 and 28 significant pathways in Y15 and Y1540 respectively, with 19 common pathways. Different responses to Cd stress between cultivars were not only reflected in differently enriched GO terms and KEGG pathways but also in different DEGs of 23 common GO terms and significant sequences represented by p-values of 19 common KEGG pathways. Both cultivars resist Cd through common processes with different weights; hence glutathione metabolism, mineral absorption, biosynthesis of secondary metabolites, and degradation of aromatic compounds could be playing a more important role in Y1540, whereas ribosome biogenesis in eukaryotes, mismatch repair, aminoacyl-tRNA biosynthesis, and the cell cycle maybe playing a more important role in Y15. Weighted gene co-expression network analysis (WGCNA) showed that five and three modules were clustered in Y15 and Y1540, respectively, with yellow and brown modules in Y15 and brown modules in Y1540 being significantly related to Cd stress. Further analysis showed that most of hub genes in Y15 were related to signal transduction or transcription factors, while most of hub genes in Y1540 were related to binding, metabolic, and secondary metabolic processes, which demonstrated their different response patterns at transcriptomic level to Cd stress.

Gene Co-Expression Analysis Reveals the Transcriptome Changes and Hub Genes of Fructan Metabolism in Garlic under Drought Stress

Drought has become a serious environmental factor that affects the growth and yield of plants. Fructan, as an important storage compound in garlic, plays an important role in drought tolerance. Genomic changes in plants under drought stress clarify the molecular mechanism of plants' responses to stress. Therefore, we used RNA-seq to determine the transcriptomic changes in garlic under drought stress and identified the key module related to fructan metabolism by weighted gene co-expression network analysis. We conducted a comprehensive analysis of the garlic transcriptome under drought stress over a time course (0, 3, 6, 9, 12, 15 d). Drought significantly induces changes in gene expression. The number of specifically expressed genes were 1430 (3 d), 399 (6 d), 313 (9 d), 351 (12 d), and 1882 (15 d), and only 114 genes responded at each time point. The number of upregulated DEGs was higher than the number of downregulated DEGs. Gene ontology and a Kyoto Encyclopedia of Genes and Genomes analysis showed that garlic was more likely to cause changes in carbohydrate metabolism pathways under drought stress. Fructan content measurements showed that drought stress significantly induced fructan accumulation in garlic. To determine whether there were modules involved in the transcriptional regulation of fructan content in garlic, we further analyzed the genes related to fructan metabolism using WGCNA. They were enriched in two modules, with F-box protein and GADPH as hub genes, which are involved in garlic fructan metabolism in response to drought stress. These results provide important insights for the future research and cultivation of drought-tolerant garlic varieties.

Comprehensive Evaluation and Transcriptome Analysis Reveal the Salt Tolerance Mechanism in Semi-Wild Cotton (Gossypium purpurascens)

Elevated salinity significantly threatens cotton growth, particularly during the germination and seedling stages. The utilization of primitive species of Gossypium hirsutum, specifically Gossypium purpurascens, has the potential to facilitate the restoration of genetic diversity that has been depleted due to selective breeding in modern cultivars. This investigation evaluated 45 G. purpurascens varieties and a salt-tolerant cotton variety based on 34 morphological, physiological, and biochemical indicators and comprehensive salt tolerance index values. This study effectively identified a total of 19 salt-tolerant and two salt-resistant varieties. Furthermore, transcriptome sequencing of a salt-tolerant genotype (Nayanmian-2; NY2) and a salt-sensitive genotype (Sanshagaopao-2; GP2) revealed 2776, 6680, 4660, and 4174 differentially expressed genes (DEGs) under 0.5, 3, 12, and 24 h of salt stress. Gene ontology enrichment analysis indicated that the DEGs exhibited significant enrichment in biological processes like metabolic (GO:0008152) and cellular (GO:0009987) processes. MAPK signaling, plant-pathogen interaction, starch and sucrose metabolism, plant hormone signaling, photosynthesis, and fatty acid metabolism were identified as key KEGG pathways involved in salinity stress. Among the DEGs, including NAC, MYB, WRKY, ERF, bHLH, and bZIP, transcription factors, receptor-like kinases, and carbohydrate-active enzymes were crucial in salinity tolerance. Weighted gene co-expression network analysis (WGCNA) unveiled associations of salt-tolerant genotypes with flavonoid metabolism, carbon metabolism, and MAPK signaling pathways. Identifying nine hub genes (MYB4, MYB105, MYB36, bZIP19, bZIP43, FRS2 SMARCAL1, BBX21, F-box) across various intervals offered insights into the transcriptional regulation mechanism of salt tolerance in G. purpurascens. This study lays the groundwork for understanding the important pathways and gene networks in response to salt stress, thereby providing a foundation for enhancing salt tolerance in upland cotton.

Identification of core genes associated with different phosphorus levels in quinoa seedlings by weighted gene co-expression network analysis

BACKGROUND

Quinoa is a highly nutritious and novel crop that is resistant to various abiotic stresses. However, its growth and development is restricted due to its limited utilization of soil phosphorus. Studies on the levels of phosphorus in quinoa seedlings are limited; therefore, we analyzed transcriptome data from quinoa seedlings treated with different concentrations of phosphorus.

RESULTS

To identify core genes involved in responding to various phosphorus levels, the weighted gene co-expression network analysis method was applied. From the 12,085 expressed genes, an analysis of the gene co-expression network was done. dividing the expressed genes into a total of twenty-five different modules out of which two modules were strongly correlated with phosphorus levels. Subsequently we identified five core genes that correlated strongly either positively or negatively with the phosphorus levels. Gene ontology and assessments of the Kyoto Encyclopedia of Genes and Genomes have uncovered important biological processes and metabolic pathways that are involved in the phosphorus level response.

CONCLUSIONS

We discovered crucial new core genes that encode proteins from various transcription factor families, such as MYB, WRKY, and ERF, which are crucial for abiotic stress resistance. This new library of candidate genes associated with the phosphorus level responses in quinoa seedlings will help in breeding varieties that are tolerant to phosphorus levels.

Comparative Transcriptome Analysis Reveals the Effect of Lignin on Storage Roots Formation in Two Sweetpotato (Ipomoea batatas (L.) Lam.) Cultivars

Sweet potato (Ipomoea batatas (L.) Lam.) is one of the most important crops with high storage roots yield. The formation and expansion rate of storage root (SR) plays a crucial role in the production of sweet potato. Lignin affects the SR formation; however, the molecular mechanisms of lignin in SR development have been lacking. To reveal the problem, we performed transcriptome sequencing of SR harvested at 32, 46, and 67 days after planting (DAP) to analyze two sweet potato lines, Jishu25 and Jishu29, in which SR expansion of Jishu29 was early and had a higher yield. A total of 52,137 transcripts and 21,148 unigenes were obtained after corrected with Hiseq2500 sequencing. Through the comparative analysis, 9577 unigenes were found to be differently expressed in the different stages in two cultivars. In addition, phenotypic analysis of two cultivars, combined with analysis of GO, KEGG, and WGCNA showed the regulation of lignin synthesis and related transcription factors play a crucial role in the early expansion of SR. The four key genes swbp1, swpa7, IbERF061, and IbERF109 were proved as potential candidates for regulating lignin synthesis and SR expansion in sweet potato. The data from this study provides new insights into the molecular mechanisms underlying the impact of lignin synthesis on the formation and expansion of SR in sweet potatoes and proposes several candidate genes that may affect sweet potato yield.

Weighted gene co-expression network analysis of nitrogen (N)-responsive genes and the putative role of G-quadruplexes in N use efficiency (NUE) in rice

Rice is an important target to improve crop nitrogen (N) use efficiency (NUE), and the identification and shortlisting of the candidate genes are still in progress. We analyzed data from 16 published N-responsive transcriptomes/microarrays to identify, eight datasets that contained the maximum number of 3020 common genes, referred to as N-responsive genes. These include different classes of transcription factors, transporters, miRNA targets, kinases and events of post-translational modifications. A Weighted gene co-expression network analysis (WGCNA) with all the 3020 N-responsive genes revealed 15 co-expression modules and their annotated biological roles. Protein-protein interaction network analysis of the main module revealed the hub genes and their functional annotation revealed their involvement in the ubiquitin process. Further, the occurrences of G-quadruplex sequences were examined, which are known to play important roles in epigenetic regulation but are hitherto unknown in N-response/NUE. Out of the 3020 N-responsive genes studied, 2298 contained G-quadruplex sequences. We compared these N-responsive genes containing G-quadruplex sequences with the 3601 genes we previously identified as NUE-related (for being both N-responsive and yield-associated). This analysis revealed 389 (17%) NUE-related genes containing G-quadruplex sequences. These genes may be involved in the epigenetic regulation of NUE, while the rest of the 83% (1811) genes may regulate NUE through genetic mechanisms and/or other epigenetic means besides G-quadruplexes. A few potentially important genes/processes identified as associated with NUE were experimentally validated in a pair of rice genotypes contrasting for NUE. The results from the WGCNA and G4 sequence analysis of N-responsive genes helped identify and shortlist six genes as candidates to improve NUE. Further, the hitherto unavailable segregation of genetic and epigenetic gene targets could aid in informed interventions through genetic and epigenetic means of crop improvement.

Mining genes regulating root system architecture in maize based on data integration analysis

KEY MESSAGE

A new strategy that integrated multiple public data resources was established to construct root gene co-expression network and mine genes regulating root system architecture in maize. A root gene co-expression network, containing 13,874 genes, was constructed. A total of 53 root hub genes and 16 priority root candidate genes were identified. One priority root candidate was further functionally verified using overexpression transgenic maize lines. Root system architecture (RSA) is crucial for crops productivity and stress tolerance. In maize, few RSA genes are functionally cloned, and effective discovery of RSA genes remains a great of challenge. In this work, we established a strategy to mine maize RSA genes by integrating functionally characterized root genes, root transcriptome, weighted gene co-expression network analysis (WGCNA) and genome-wide association analysis (GWAS) of RSA traits based on public data resources. A total of 589 maize root genes were collected by searching well-characterized root genes in maize or homologous genes of other species. We performed WGCNA to construct a maize root gene co-expression network containing 13874 genes based on public available root transcriptome data, and further discovered the 53 hub genes related to root traits. In addition, by the prediction function of obtained root gene co-expression network, a total of 1082 new root candidate genes were explored. By further overlapping the obtained new root candidate gene with the root-related GWAS of RSA candidate genes, 16 priority root candidate genes were identified. Finally, a priority root candidate gene, Zm00001d023379 (encodes pyruvate kinase 2), was validated to modulate root open angle and shoot-borne roots number using its overexpression transgenic lines. Our results develop an integration analysis method for effectively exploring regulatory genes of RSA in maize and open a new avenue to mine the candidate genes underlying complex traits.

Gene Coexpression Analysis Identifies Genes Associated with Chlorophyll Content and Relative Water Content in Pearl Millet

Pearl millet is a significant crop that is tolerant to abiotic stresses and is a staple food of arid regions. However, its underlying mechanisms of stress tolerance are not fully understood. Plant survival is regulated by the ability to perceive a stress signal and induce appropriate physiological changes. Here, we screened for genes regulating physiological changes such as chlorophyll content (CC) and relative water content (RWC) in response to abiotic stress by using "weighted gene coexpression network analysis" (WGCNA) and clustering changes in physiological traits, i.e., CC and RWC associated with gene expression. Genes' correlations with traits were defined in the form of modules, and different color names were used to denote a particular module. Modules are groups of genes with similar patterns of expression, which also tend to be functionally related and co-regulated. In WGCNA, the dark green module (7082 genes) showed a significant positive correlation with CC, and the black (1393 genes) module was negatively correlated with CC and RWC. Analysis of the module positively correlated with CC highlighted ribosome synthesis and plant hormone signaling as the most significant pathways. Potassium transporter 8 and monothiol glutaredoxin were reported as the topmost hub genes in the dark green module. In Clust analysis, 2987 genes were found to display a correlation with increasing CC and RWC. Furthermore, the pathway analysis of these clusters identified the ribosome and thermogenesis as positive regulators of RWC and CC, respectively. Our study provides novel insights into the molecular mechanisms regulating CC and RWC in pearl millet.

Physiological, transcriptome and co-expression network analysis of chlorophyll-deficient mutants in flue-cured tobacco

BACKGROUND

Photosynthetic pigments in higher plants, including chlorophyll (Chl) and carotenoids, are crucial for photosynthesis and photoprotection. Chl-deficient tobacco seedlings generally have a lower photosynthesis rate and higher nitrate-nitrogen (NO₃-N) content, which causes a profound influence on tobacco yield and quality. In this study, a stable albino leaf mutant (Al) and slight-green leaf mutant (SG) obtained from the common flue-cured tobacco (Nicotiana tabacum L.) cultivar 'Zhongyan 100' (ZY100) by mutagenesis with ethyl methanesulfonate (EMS) were used as materials. The differences between the Chl-deficient mutants and the wild-type (WT) were analyzed in terms of biomass, photosynthetic fluorescence parameters, and carbon- and nitrogen-related physiological parameters. RNA sequencing (RNA-seq) and weighted gene co-expression network analysis (WGCNA) were used to explore the key pathways and candidate genes regulating differentiated chlorophyll and nitrate content.

RESULTS

The results showed that, when compared to the WT, the Chl content and biomass of mutant plants were considerably lower while the NO₃-N content was substantially elevated. The net photosynthetic rate, photosynthetic fluorescence parameters, carbohydrate, soluble protein, and carbon- and nitrogen-related enzyme activities all decreased in leaves of mutants and the development of chloroplasts was abnormal. Applying more nitrogen improved the growth and development of mutants, whereas NO₃-N content distinctively increased compared with that of the WT. Through transcriptome sequencing, the downregulated genes in mutants were enriched in plant hormone signal transduction and nitrogen metabolism, which are involved in pigment biosynthesis and the carbon fixation pathway. In addition, two hub genes and seven transcription factors identified from the blue module through WGCNA were likely to be key candidate factors involved in chlorophyll synthesis and nitrate accumulation.

CONCLUSION

Our results demonstrated that differences in chlorophyll and nitrate content were caused by the combined effects of chloroplast development, photosynthesis, as well as related biological activity. In addition, transcriptome results provide a bioinformatics resource for further functional identification of key pathways and genes responsible for differences in chlorophyll and nitrate content in tobacco plants.

Transcriptome and Co-Expression Network Analysis Reveals the Molecular Mechanism of Rice Root Systems in Response to Low-Nitrogen Conditions

Nitrogen is an important nutrient for plant growth and essential metabolic processes. Roots integrally obtain nutrients from soil and are closely related to the growth and development of plants. In this study, the morphological analysis of rice root tissues collected at different time points under low-nitrogen and normal nitrogen conditions demonstrated that, compared with normal nitrogen treatment, the root growth and nitrogen use efficiency (NUE) of rice under low-nitrogen treatment were significantly improved. To better understand the molecular mechanisms of the rice root system’s response to low-nitrogen conditions, a comprehensive transcriptome analysis of rice seedling roots under low-nitrogen and control conditions was conducted in this study. As a result, 3171 differentially expressed genes (DEGs) were identified. Rice seedling roots enhance NUE and promote root development by regulating the genes related to nitrogen absorption and utilization, carbon metabolism, root growth and development, and phytohormones, thereby adapting to low-nitrogen conditions. A total of 25,377 genes were divided into 14 modules using weighted gene co-expression network analysis (WGCNA). Two modules were significantly associated with nitrogen absorption and utilization. A total of 8 core genes and 43 co-expression candidates related to nitrogen absorption and utilization were obtained in these two modules. Further studies on these genes will contribute to the understanding of low-nitrogen adaptation and nitrogen utilization mechanisms in rice.

Weighted gene co-expression network analysis revealed the key pathways and hub genes of potassium regulating cotton root adaptation to salt stress

Soil salinization is one of the main abiotic stresses affecting cotton yield and planting area. Potassium application has been proven to be an important strategy to reduce salt damage in agricultural production. However, the mechanism of potassium regulating the salt adaptability of cotton has not been fully elucidated. In the present research, the appropriate potassium application rate for alleviating salt damage of cotton based on different K⁺/Na⁺ ratios we screened, and a gene co-expression network based on weighted gene co-expression network analysis (WGCNA) using the transcriptome data sets treated with CK (0 mM NaCl), S (150 mM NaCl), and SK8 (150 mM NaCl + 9.38 mM K₂SO₄) was constructed. In this study, four key modules that are highly related to potassium regulation of cotton salt tolerance were identified, and the mitogen-activated protein kinase (MAPK) signaling pathway, tricarboxylic acid (TCA) cycle and glutathione metabolism pathway were identified as the key biological processes and metabolic pathways for potassium to improve cotton root salt adaptability. In addition, 21 hub genes and 120 key candidate genes were identified in this study, suggesting that they may play an important role in the enhancement of salt adaptability of cotton by potassium. The key modules, key biological pathways and hub genes discovered in this study will provide a new understanding of the molecular mechanism of potassium enhancing salinity adaptability in cotton, and lay a theoretical foundation for the improvement and innovation of high-quality cotton germplasm.

Combined genome-wide association study and gene co-expression network analysis identified ZmAKINβγ1 involved in lead tolerance and accumulation in maize seedlings

Lead (Pb) contamination has become an important abiotic stress that negatively influences crop biomass and yield, threatening human health via food chains. The excavation of causal genes for Pb tolerance in maize will contribute to the breeding of Pb-tolerant maize germplasms. This study aimed to demonstrate the effects of AKINbetagamma-1 protein kinase (ZmAKINβγ1) on maize tolerance to Pb and reveal its molecular mechanisms underlying Pb tolerance. ZmAKINβγ1 was identified using genome-wide association study and weighted gene co-expression network analysis for shoot dry weight (SDW) and root dry weight (RDW) under Pb treatment. The OE and RNAi experiments showed that ZmAKINβγ1 negatively regulated maize tolerance to Pb by reducing SDW and RDW and increasing Pb accumulation in maize. Comparative transcriptome analysis between the OE/RNAi and wild-type lines revealed that ZmAKINβγ1 participated in the pectin metabolism process and nitrogen compound response. Gene-based association analyses revealed that three variants located in ZmAKINβγ1 promoter induced changes in its expression and Pb tolerance among maize lines. The dual-luciferase reporter system verified that the two genotypes (AAT and CGG) of ZmAKINβγ1 promoter had contrasting transcriptional activities. Collectively, ZmAKINβγ1-mediated Pb tolerance provided new insights into the cultivation of Pb-tolerant maize varieties and phytoremediation of Pb-polluted soils.

Transcriptome analysis of two pepper genotypes infected with pepper mild mottle virus

Pepper mild mottle virus (PMMoV) poses a significant threat to pepper production because it is highly contagious and extremely persistent in soil. Despite this threat, little is known about the molecular processes that underlie plant responses to pepper mild mottle virus. Here, we performed RNA sequencing of tolerant ("17-p63") and susceptible ("16-217") pepper genotypes after pepper mild mottle virus or mock inoculation. Viral accumulation in systemic leaves was lower in the pepper mild mottle virus-resistant 17-p63 genotype than in the pepper mild mottle virus-sensitive 16-217 genotype, and infection symptoms were more apparent in systemic leaves of 16-217 than in those of 17-p63 at the same timepoints during the infection process. We identified 2,959 and 2,159 differentially expressed genes (DEGs) in systemic leaves of infected 16-217 and 17-p63, respectively. Through Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis of differentially expressed genes from both genotypes revealed significant enrichment of the MAPK signaling pathway, plant-pathogen interaction, and flavonoid biosynthesis. A number of differentially expressed genes showed opposite trends in relation to stress resistance and disease defense in the two genotypes. We also performed weighted gene co-expression network analysis (WGCNA) of all samples and identified modules associated with resistance to pepper mild mottle virus, as well as seven hub genes. These results identify candidate virus resistance genes and provide insight into pepper defense mechanisms against pepper mild mottle virus.

Transcriptome analysis of pika heart tissue reveals mechanisms underlying the adaptation of a keystone species on the roof of the world

High-altitude environments impose intense stresses on living organisms and drive striking phenotypic and genetic adaptations, such as hypoxia resistance, cold tolerance, and increases in metabolic capacity and body mass. As one of the most successful and dominant mammals on the Qinghai-Tibetan Plateau (QHTP), the plateau pika (Ochotona curzoniae) has adapted to the extreme environments of the highest altitudes of this region and exhibits tolerance to cold and hypoxia, in contrast to closely related species that inhabit the peripheral alpine bush or forests. To explore the potential genetic mechanisms underlying the adaptation of O. curzoniae to a high-altitude environment, we sequenced the heart tissue transcriptomes of adult plateau pikas (comparing specimens from sites at two different altitudes) and Gansu pikas (O. cansus). Differential expression analysis and weighted gene co-expression network analysis (WGCNA) were used to identify differentially expressed genes (DEGs) and their primary functions. Key genes and pathways related to high-altitude adaptation were identified. In addition to the biological processes of signal transduction, energy metabolism and material transport, the identified plateau pika genes were mainly enriched in biological pathways such as the negative regulation of smooth muscle cell proliferation, the apoptosis signalling pathway, the cellular response to DNA damage stimulus, and ossification involved in bone maturation and heart development. Our results showed that the plateau pika has adapted to the extreme environments of the QHTP via protection against cardiomyopathy, tissue structure alterations and improvements in the blood circulation system and energy metabolism. These adaptations shed light on how pikas thrive on the roof of the world.

A Pan-Transcriptome Analysis Indicates Efficient Downregulation of the FIB Genes Plays a Critical Role in the Response of Alfalfa to Cold Stress

Alfalfa (Medicago sativa L.) is a perennial forage legume that is widely distributed throughout the world, and cold stress is an important environmental factor limiting the growth and production of alfalfa in cold regions. However, little is known of the molecular mechanisms regarding cold tolerance in alfalfa. Here, we conducted physiological metabolism assays and pan-transcriptome sequencing on eight cultivars of alfalfa under cold stress conditions. The results of the RNA-seq analysis showed that the genes are "oxidoreductase activity" and "transcription regulator activity", suggesting that genes with such functions are more likely to play important roles in the response to cold stress by alfalfa. In addition, to identify specific gene modules and hub genes in response to alfalfa cold stress, we applied weighted gene co-expression network (WGCNA) analyses to the RNA-seq data. Our results indicate that the modules of genes that focus on the ATPase complex, ribosome biogenesis, are more likely to be involved in the alfalfa response to cold stress. It is important to note that we identified two fibronectin (FIB) genes as hub genes in alfalfa in response to cold stress and that they negatively regulate alfalfa response to chilling stress, and it is possible that dormant alfalfa is more effective at down-regulating FIB expression and therefore more resistant to cold stress.

WGCNA Analysis Revealed the Hub Genes Related to Soil Cadmium Stress in Maize Kernel (Zea mays L.)

Soil contamination by heavy metals has become a prevalent topic due to their widespread release from industry, agriculture, and other human activities. Great progress has been made in elucidating the uptake and translocation of cadmium (Cd) accumulation in rice. However, there is still little known about corresponding progress in maize. In the current study, we performed a comparative RNA-Seq-based approach to identify differentially expressed genes (DEGs) of maize immature kernel related to Cd stress. In total, 55, 92, 22, and 542 DEGs responsive to high cadmium concentration soil were identified between XNY22-CHS-8 vs. XNY22-YA-8, XNY22-CHS-24 vs. XNY22-YA-24, XNY27-CHS-8 vs. XNY27-YA-8, and XNY27-CHS-24 vs. XNY27-YA-24, respectively. The weighted gene co-expression network analysis (WGCNA) categorized the 9599 Cd stress-responsive hub genes into 37 different gene network modules. Combining the hub genes and DEGs, we obtained 71 candidate genes. Gene Ontology (GO) enrichment analysis of genes in the greenyellow module in XNY27-YA-24 and connectivity genes of these 71 candidate hub genes showed that the responses to metal ion, inorganic substance, abiotic stimulus, hydrogen peroxide, oxidative stress, stimulus, and other processes were enrichment. Moreover, five candidate genes that were responsive to Cd stress in maize kernel were detected. These results provided the putative key genes and pathways to response to Cd stress in maize kernel, and a useful dataset for unraveling the underlying mechanism of Cd accumulation in maize kernel.

LncRNA-mediated ceRNA regulatory network provides new insight into chlorogenic acid synthesis in sweet potato

Sweet potato (Ipomoea batatas L.) is considered a highly nutritional and economical crop due to its high contents of bioactive substances, such as anthocyanin and chlorogenic acid (CGA), especially in leaves and stems. The roles of noncoding RNAs (ncRNA), including long noncoding RNA (lncRNA) and microRNA (miRNA), in CGA synthesis, are still unknown. In this study, the differentially expressed (DE) mRNAs, miRNAs, and lncRNAs in two leafy vegetable genotypes "FS7-6-14-7" (high CGA content) and "FS7-6" (low CGA content) were identified. The cis-regulation between lncRNA and mRNA was analyzed. Then, the CGA synthesis-related modules MEBlue and MEYellow were identified to detect trans-regulation mRNA-lncRNA pairs. The GO and KEGG annotations suggested that mRNA in these two modules was significantly enriched in the secondary metabolite synthesis biosynthesis category. A competing endogenous RNAs (ceRNA) network, including 8730 miRNA-mRNA and 444 miRNA-lncRNA pairs, was constructed by DEmiRNA target prediction. Then, a CGA synthesis-related ceRNA network was obtained with lncRNA and mRNA from MEBlue and MEYellow. Finally, one relational pair, MSTRG.47662.1/mes-miR398/itb04g00990, was selected for functional validation. Overexpression of lncRNA MSTRG.47662.1 and mRNA itb04g00990 increased CGA content in both tobacco and sweet potato callus, while overexpression of miRNA mes-miR398 decreased CGA content. Meanwhile, regression analysis of the expression patterns demonstrated that MSTRG.47662.1, acting as a ceRNA, promoted itb04g00990 expression by competitively binding mes-miR398 in CGA synthesis in sweet potato. Our results provide insights into how ncRNA-mediated ceRNA regulatory networks likely contribute to CGA synthesis in leafy sweet potato.

Transcriptome analysis reveals the proline metabolic pathway and its potential regulation TF-hub genes in salt-stressed potato

Potato (Solanum tuberosum) is currently the third most important food crop in the world. However, the production of potato is seriously threatened by salt stress, which often occurs in the facility cultivation environment, and the mining of salt tolerance genes in potato remains to be further studied. In this study, test-tube plantlets of DM potato were treated with 200-mM NaCl to simulate salt stress, and 15 cDNA libraries were constructed for RNA-seq analysis. A total of 8383 DEGs were identified, of which 3961 DEGs were shared among all the salt treatments, and 264 (7.15%) TF-coding genes were identified from these shared DEGs. KEGG enrichment analysis showed that most DEGs identified from the "arginine and proline metabolism" (ko00330) were enriched in the proline metabolic pathway, and their functions almost covered the whole proline metabolic process. Further analysis showed that expression levels of all the 13 structural DEGs in the pathway were significantly up-regulated and proline accumulation was also significantly increased under salt stress, and 13 TF-hub genes were discovered by WGCNA in the lightcyan and tan modules which were highly positively correlated with the proline contents. Correlation analysis revealed that the four TF-hub genes of the lightcyan module and seven structural DEGs of the proline metabolic pathway might be the potential candidate genes, especially the potential and novel regulatory gene StGLK014720. Furthermore, the dual-luciferase reporter assay confirmed that the key protein StGLK014720 could activate the promoters of both structural genes StAST021010 and StAST017480. In conclusion, these results lay the foundation for further study on the salt tolerance mechanism of potato, and provide a theoretical basis and new genetic resources for salt tolerance breeding of potato.

Transcriptome analysis and mining of genes related to shade tolerance in foxtail millet (Setaria italica (L.) P. Beauv.)

A stereo interplanting system with foxtail millet beneath chestnut trees is an effective planting method to raise the utilization of land in chestnut orchards, increase yields and improve quality of chestnut nuts. Consequently, exploration of genes involved in shade tolerance response in foxtail millet and breeding shade-tolerant varieties have become urgent issues. In this study, RNA-seq of leaf samples from two shade-tolerant varieties and three shade-intolerant varieties of foxtail millet at the booting stage was performed. Comparisons between the varieties revealed that 70 genes were commonly differentially expressed. Moreover, the ratio of net photosynthetic rate under shaded environment to that under light environment could be used as an indicator of shade tolerance. Subsequently, weighted gene co-expression network analysis was employed to construct a co-expression network and modules were correlated with this ratio. A total of 375 genes were identified as potentially relevant to shade tolerance, among which nine genes were also present in the 70 differentially expressed genes, which implied that they were good candidates for genes involved in shade tolerance. Our results provide valuable resources for elucidation of the molecular mechanisms underlying shade tolerance and will contribute to breeding of shade-tolerant foxtail millet that are adapted to the shaded environment under chestnut trees.

Comparative physiological and coexpression network analyses reveal the potential drought tolerance mechanism of peanut

BACKGROUND

Drought stress has negative effects on plant growth and productivity. In this study, a comprehensive analysis of physiological responses and gene expression was performed. The responses and expressions were compared between drought-tolerant (DT) and drought-sensitive (DS) peanut varieties to investigate the regulatory mechanisms and hub genes involved in the impact of drought stress on culture.

RESULTS

The drought-tolerant variety had robust antioxidative capacities with higher total antioxidant capacity and flavonoid contents, and it enhanced osmotic adjustment substance accumulation to adapt to drought conditions. KEGG analysis of differentially expressed genes demonstrated that photosynthesis was strongly affected by drought stress, especially in the drought-sensitive variety, which was consistent with the more severe suppression of photosynthesis. The hub genes in the key modules related to the drought response, including genes encoding protein kinase, E3 ubiquitin-protein ligase, potassium transporter, pentatricopeptide repeat-containing protein, and aspartic proteinase, were identified through a comprehensive combined analysis of genes and physiological traits using weighted gene co-expression network analysis. There were notably differentially expressed genes between the two varieties, suggesting the positive roles of these genes in peanut drought tolerance.

CONCLUSION

A comprehensive analysis of physiological traits and relevant genes was conducted on peanuts with different drought tolerances. The findings revealed diverse drought-response mechanisms and identified candidate genes for further research.

Root and shoot biology of Arabidopsis halleri dissected by WGCNA: an insight into the organ pivotal pathways and genes of an hyperaccumulator

Arabidopsis halleri is a hyperaccumulating pseudo-metallophyte and an emerging model to explore molecular basis of metal tolerance and hyperaccumulation. In this regard, understanding of interacting genes can be a crucial aspect as these interactions regulate several biological functions at molecular level in response to multiple signals. In this current study, we applied a weighted gene co-expression network analysis (WGCNA) on root and shoot RNA-seq data of A. halleri to predict the related scale-free organ specific co-expression networks, for the first time. A total of 19,653 genes of root and 18,081 genes of shoot were grouped into 14 modules and subjected to GO and KEGG enrichment analysis. "Photosynthesis" and "photosynthesis-antenna proteins" were identified as the most enriched and common pathway to both root and shoot. Whereas "glucosinolate biosynthesis," "autophagy," and "SNARE interactions in vesicular transport" were specific to root, and "circadian rhythm" was found to be enriched only in shoot. Later, hub and bottleneck genes were identified in each module by using cytoHubba plugin based on Cytoscape and scoring the relevance of each gene to the topology of the network. The modules with the most significant differential expression pattern across control and treatment (Cd-Zn treatment) were selected and their hub and bottleneck genes were screened to validate their possible involvement in heavy metal stress. Moreover, we combined the analysis of co-expression modules together with protein-protein interactions (PPIs), confirming some genes as potential candidates in plant heavy metal stress and as biomarkers. The results from this analysis shed the light on the pivotal functions to the hyperaccumulative trait of A. halleri, giving perspective to new paths for future research on this species.

Transcriptome and Metabolome Analyses Revealed the Response Mechanism of Sugar Beet to Salt Stress of Different Durations

Salinity is one of the most serious threats to agriculture worldwide. Sugar beet is an important sugar-yielding crop and has a certain tolerance to salt; however, the genome-wide dynamic response to salt stress remains largely unknown in sugar beet. In the present study, physiological and transcriptome analyses of sugar beet leaves and roots were compared under salt stress at five time points. The results showed that different salt stresses influenced phenotypic characteristics, leaf relative water content and root activity in sugar beet. The contents of chlorophyll, malondialdehyde (MDA), the activities of peroxidase (POD), superoxide dismutase (SOD), and catalase (CAT) were also affected by different salt stresses. Compared with control plants, there were 7391 and 8729 differentially expressed genes (DEGs) in leaves and roots under salt stress, respectively. A total of 41 hub genes related to salt stress were identified by weighted gene co-expression network analysis (WGCNA) from DEGs, and a transcriptional regulatory network based on these genes was constructed. The expression pattern of hub genes under salt stress was confirmed by qRT-PCR. In addition, the metabolite of sugar beet was compared under salt stress for 24 h. A total of 157 and 157 differentially accumulated metabolites (DAMs) were identified in leaves and roots, respectively. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis further indicated that DEGs and DAMs act on the starch and sucrose metabolism, alpha-linolenic acid metabolism, phenylpropanoid biosynthesis and plant hormone signal transduction pathway. In this study, RNA-seq, WGCNA analysis and untargeted metabolomics were combined to investigate the transcriptional and metabolic changes of sugar beet during salt stress. The results provided new insights into the molecular mechanism of sugar beet response to salt stress, and also provided candidate genes for sugar beet improvement.

Weighted Gene Correlation Network Analysis (WGCNA) of Arabidopsis Somatic Embryogenesis (SE) and Identification of Key Gene Modules to Uncover SE-Associated Hub Genes

Somatic embryogenesis (SE), which occurs naturally in many plant species, serves as a model to elucidate cellular and molecular mechanisms of embryo patterning in plants. Decoding the regulatory landscape of SE is essential for its further application. Hence, the present study was aimed at employing Weighted Gene Correlation Network Analysis (WGCNA) to construct a gene coexpression network (GCN) for Arabidopsis SE and then identifying highly correlated gene modules to uncover the hub genes associated with SE that may serve as potential molecular targets. A total of 17,059 genes were filtered from a microarray dataset comprising four stages of SE, i.e., stage I (zygotic embryos), stage II (proliferating tissues at 7 days of induction), stage III (proliferating tissues at 14 days of induction), and stage IV (mature somatic embryos). This included 1,711 transcription factors and 445 EMBRYO DEFECTIVE genes. GCN analysis identified a total of 26 gene modules with the module size ranging from 35 to 3,418 genes using a dynamic cut tree algorithm. The module-trait analysis revealed that four, four, seven, and four modules were associated with stages I, II, III, and IV, respectively. Further, we identified a total of 260 hub genes based on the degree of intramodular connectivity. Validation of the hub genes using publicly available expression datasets demonstrated that at least 78 hub genes are potentially associated with embryogenesis; of these, many genes remain functionally uncharacterized thus far. In silico promoter analysis of these genes revealed the presence of cis-acting regulatory elements, “soybean embryo factor 4 (SEF4) binding site,” and “E-box” of the napA storage-protein gene of Brassica napus; this suggests that these genes may play important roles in plant embryo development. The present study successfully applied WGCNA to construct a GCN for SE in Arabidopsis and identified hub genes involved in the development of somatic embryos. These hub genes could be used as molecular targets to further elucidate the molecular mechanisms underlying SE in plants.

Identification of stress-related genes by co-expression network analysis based on the improved turbot genome

Turbot (Scophthalmus maximus), commercially important flatfish species, is widely cultivated in Europe and China. With the continuous expansion of the intensive breeding scale, turbot is exposed to various stresses, which greatly impedes the healthy development of turbot industry. Here, we present an improved high-quality chromosome-scale genome assembly of turbot using a combination of PacBio long-read and Illumina short-read sequencing technologies. The genome assembly spans 538.22 Mb comprising 27 contigs with a contig N50 size of 25.76 Mb. Annotation of the genome assembly identified 104.45 Mb repetitive sequences, 22,442 protein-coding genes and 3,345 ncRNAs. Moreover, a total of 345 stress responsive candidate genes were identified by gene co-expression network analysis based on 14 published stress-related RNA-seq datasets consisting of 165 samples. Significantly improved genome assembly and stress-related candidate gene pool will provide valuable resources for further research on turbot functional genome and stress response mechanism, as well as theoretical support for the development of molecular breeding technology for resistant turbot varieties.

Measurement(s)	whole genome sequencing
Technology Type(s)	PacBio long-read and Illumina short-read sequencing technologies

Identification of major candidate genes for multiple abiotic stress tolerance at seedling stage by network analysis and their validation by expression profiling in rice (Oryza sativa L.)

A wealth of microarray and RNA-seq data for studying abiotic stress tolerance in rice exists but only limited studies have been carried out on multiple stress-tolerance responses and mechanisms. In this study, we identified 6657 abiotic stress-responsive genes pertaining to drought, salinity and heat stresses from the seedling stage microarray data of 83 samples and used them to perform unweighted network analysis and to identify key hub genes or master regulators for multiple abiotic stress tolerance. Of the total 55 modules identified from the analysis, the top 10 modules with 8-61 nodes comprised 239 genes. From these 10 modules, 10 genes common to all the three stresses were selected. Further, based on the centrality properties and highly dense interactions, we identified 7 intra-modular hub genes leading to a total of 17 potential candidate genes. Out of these 17 genes, 15 were validated by expression analysis using a panel of 4 test genotypes and a pair of standard check genotypes for each abiotic stress response. Interestingly, all the 15 genes showed upregulation under all stresses and in all the genotypes, suggesting that they could be representing some of the core abiotic stress-responsive genes. More pertinently, eight of the genes were found to be co-localized with the stress-tolerance QTL regions. Thus, in conclusion, our study not only provided an effective approach for studying abiotic stress tolerance in rice, but also identified major candidate genes which could be further validated by functional genomics for abiotic stress tolerance.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13205-022-03182-7.

Gene co-expression network analysis reveals the positive impact of endocytosis and mitochondria-related genes over nitrogen metabolism in Saccharomyces cerevisiae

Nitrogen metabolism is essential for most cellular activities. Therefore, a deep understanding of its regulatory mechanisms is necessary for the efficient utilization of nitrogen sources for Saccharomyces cerevisiae. In this study, a gene co-expression network was constructed for S. cerevisiae S288C with different nitrogen sources. From this, a key gene co-expression module related to nitrogen source preference utilization was obtained, and 10 hub genes centrally located in the co-expression network were identified. Functional studies verified that the endocytosis-related genes CAP1 and END3 significantly increased the utilization of multiple non-preferred amino acids and reduced the accumulation of the harmful nitrogen metabolite precursor urea by regulating amino acid transporters and TOR pathway. The mitochondria-related gene ATP12, MRPL22, MRP1 and NAM9 significantly increased the utilization of multiple non-preferred amino acids and reduced accumulation of the urea by coordinately regulating nitrogen catabolism repression, Ssy1p-Ptr3p-Ssy5p signaling sensor system, amino acid transporters, TOR pathway and urea metabolism-related pathways. Furthermore, these data revealed the potential positive effects of endocytosis and mitochondrial ribosomes protein translation on nitrogen source preference. This study provides new analytical perspectives for complex regulatory networks involving nitrogen metabolism in S. cerevisiae.

Universal gene co-expression network reveals receptor-like protein genes involved in broad-spectrum resistance in pepper (Capsicum annuum L.)

Receptor-like proteins (RLPs) on plant cells have been implicated in immune responses and developmental processes. Although hundreds of RLP genes have been identified in plants, only a few RLPs have been functionally characterized in a limited number of plant species. Here, we identified RLPs in the pepper (Capsicum annuum) genome and performed comparative transcriptomics coupled with the analysis of conserved gene co-expression networks (GCNs) to reveal the role of core RLP regulators in pepper-pathogen interactions. A total of 102 RNA-seq datasets of pepper plants infected with four pathogens were used to construct CaRLP-targeted GCNs (CaRLP-GCNs). Resistance-responsive CaRLP-GCNs were merged to construct a universal GCN. Fourteen hub CaRLPs, tightly connected with defense-related gene clusters, were identified in eight modules. Based on the CaRLP-GCNs, we evaluated whether hub CaRLPs in the universal GCN are involved in the biotic stress response. Of the nine hub CaRLPs tested by virus-induced gene silencing, three genes (CaRLP264, CaRLP277, and CaRLP351) showed defense suppression with less hypersensitive response-like cell death in race-specific and non-host resistance response to viruses and bacteria, respectively, and consistently enhanced susceptibility to Ralstonia solanacearum and/or Phytophthora capsici. These data suggest that key CaRLPs are involved in the defense response to multiple biotic stresses and can be used to engineer a plant with broad-spectrum resistance. Together, our data show that generating a universal GCN using comprehensive transcriptome datasets can provide important clues to uncover genes involved in various biological processes.

Integration of Transcriptome and Metabolome Provides New Insights to Flavonoids Biosynthesis in Dendrobium huoshanense

Dendrobium huoshanense is both a traditional herbal medicine and a plant of high ornamental and medicinal value. We used transcriptomics and metabolomics to investigate the effects of growth year on the secondary metabolites of D. huoshanense stems obtained from four different years of cultivation. In this study, a total of 428 differentially accumulated metabolites (DAMs) and 1802 differentially expressed genes (DEGs) were identified. The KEGG enrichment analysis of DEGs and DAMs revealed significant differences in "Flavonoid biosynthesis", "Phenylpropanoid biosynthesis" and "Flavone and flavonol biosynthesis". We summarize the biosynthesis pathway of flavonoids in D. huoshanense, providing new insights into the biosynthesis and regulation mechanisms of flavonoids in D. huoshanense. Additionally, we identified two candidate genes, FLS (LOC110107557) and F3'H (LOC110095936), which are highly involved in flavonoid biosynthesis pathway, by WGCNA analysis. The aim of this study is to investigate the effects of growth year on secondarily metabolites in the plant and provide a theoretical basis for determining a reasonable harvesting period for D. huoshanense.

Weighted Gene Co-Expression Analysis Network-Based Analysis on the Candidate Pathways and Hub Genes in Eggplant Bacterial Wilt-Resistance: A Plant Research Study

Solanum melongena L. (eggplant) bacterial wilt is a severe soil borne disease. Here, this study aimed to explore the regulation mechanism of eggplant bacterial wilt-resistance by transcriptomics with weighted gene co-expression analysis network (WGCNA). The different expression genes (DEGs) of roots and stems were divided into 21 modules. The module of interest (root: indianred4, stem: coral3) with the highest correlation with the target traits was selected to elucidate resistance genes and pathways. The selected module of roots and stems co-enriched the pathways of MAPK signalling pathway, plant pathogen interaction, and glutathione metabolism. Each top 30 hub genes of the roots and stems co-enriched a large number of receptor kinase genes. A total of 14 interesting resistance-related genes were selected and verified with quantitative polymerase chain reaction (qPCR). The qPCR results were consistent with those of WGCNA. The hub gene of EGP00814 (namely SmRPP13L4) was further functionally verified; SmRPP13L4 positively regulated the resistance of eggplant to bacterial wilt by qPCR and virus-induced gene silencing (VIGS). Our study provides a reference for the interaction between eggplants and bacterial wilt and the breeding of broad-spectrum and specific eggplant varieties that are bacterial wilt-resistant.

Transcriptome and metabolome analyses of response of Synechocystis sp. PCC 6803 to methyl viologen

The toxicity of methyl viologen (MV) to organisms is mainly due to the oxidative stress caused by reactive oxygen species produced from cell response. This study mainly investigated the response of Synechocystis sp. PCC 6803 to MV by combining transcriptomic and metabolomic analyses. Through transcriptome sequencing, we found many genes responding to MV stress, and analyzed them by weighted gene co-expression network analysis (WGCNA). Meanwhile, many metabolites were also found by metabolomic analysis to be regulated post MV treatment. Based on the analysis results of Kyoto encyclopedia of genes and genomes (KEGG) of the differentially expressed genes (DEGs) in the transcriptome and the differential metabolites in the metabolome, the dynamic changes of genes and metabolites involved in ten metabolic pathways in response to MV were analyzed. The results indicated that although the oxidative stress caused by MV was the strongest at 6 h, the proportion of the upregulated genes and metabolites involved in these ten metabolic pathways was the highest. Photosynthesis positively regulated the response to MV-induced oxidative stress, and the regulation of environmental information processing was inhibited by MV. Other metabolic pathways played different roles at different times and interacted with each other to respond to MV. This study comprehensively analyzed the response of Synechocystis sp. PCC 6803 to oxidative stress caused by MV from a multi-omics perspective, with providing key data and important information for in-depth analysis of the response of organisms to MV, especially photosynthetic organisms. KEY POINTS: • Methyl viologen (MV) treatment caused regulatory changes in genes and metabolites. • Proportion of upregulated genes and metabolites was the highest at 6-h MV treatment. • Photosynthesis and environmental information processing involved in MV response.

Identification of a Four-Gene Signature With Prognostic Significance in Endometrial Cancer Using Weighted-Gene Correlation Network Analysis

Endometrial hyperplasia (EH) is a precursor for endometrial cancer (EC). However, biomarkers for the progression from EH to EC and standard prognostic biomarkers for EC have not been identified. In this study, we aimed to identify key genes with prognostic significance for the progression from EH to EC. Weighted-gene correlation network analysis (WGCNA) was used to identify hub genes utilizing microarray data (GSE106191) downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) were identified from the Uterine Corpus Endometrial Carcinoma (UCEC) dataset of The Cancer Genome Atlas database. The Limma-Voom R package was applied to detect differentially expressed genes (DEGs; mRNAs) between cancer and normal samples. Genes with |log2 (fold change [FC])| > 1.0 and p < 0.05 were considered as DEGs. Univariate and multivariate Cox regression and survival analyses were performed to identify potential prognostic genes using hub genes overlapping in the two datasets. All analyses were conducted using R Bioconductor and related packages. Through WGCNA and overlapping genes in hub modules with DEGs in the UCEC dataset, we identified 42 hub genes. The results of the univariate and multivariate Cox regression analyses revealed that four hub genes, BUB1B, NDC80, TPX2, and TTK, were independently associated with the prognosis of EC (Hazard ratio [95% confidence interval]: 0.591 [0.382–0.912], p = 0.017; 0.605 [0.371–0.986], p = 0.044; 1.678 [1.132–2.488], p = 0.01; 2.428 [1.372–4.29], p = 0.02, respectively). A nomogram was established with a risk score calculated using the four genes’ coefficients in the multivariate analysis, and tumor grade and stage had a favorable predictive value for the prognosis of EC. The survival analysis showed that the high-risk group had an unfavorable prognosis compared with the low-risk group (p < 0.0001). The receiver operating characteristic curves also indicated that the risk model had a potential predictive value of prognosis with area under the curve 0.807 at 2 years, 0.783 at 3 years, and 0.786 at 5 years. We established a four-gene signature with prognostic significance in EC using WGCNA and established a nomogram to predict the prognosis of EC.

Identification of Key Transcription Factors Related to Bacterial Spot Resistance in Pepper through Regulatory Network Analyses

Bacterial spot (BS), caused by Xanthomonas campestris pv. Vesicatoria (Xcv), severely affects the quality and yield of pepper. Thus, breeding new pepper cultivars with enhanced resistance to BS can improve economic benefits for pepper production. Identification of BS resistance genes is an essential step to achieve this goal. However, very few BS resistance genes have been well characterized in pepper so far. In this study, we reanalyzed public multiple time points related to RNA-seq data sets from two pepper cultivars, the Xcv-susceptible cultivar ECW and the Xcv-resistant cultivar VI037601, post Xcv infection. We identified a total of 3568 differentially expressed genes (DEGs) between two cultivars post Xcv infection, which were mainly involved in some biological processes, such as Gene Ontology (GO) terms related to defense response to bacterium, immune system process, and regulation of defense response, etc. Through weighted gene co-expression network analysis (WGCNA), we identified 15 hub (Hub) transcription factor (TF) candidates in response to Xcv infection. We further selected 20 TFs from the gene regulatory network (GRN) potentially involved in Xcv resistance response. Finally, we predicted 4 TFs, C3H (p-coumarate 3-hydroxylase), ERF (ethylene-responsive element binding factor), TALE (three-amino-acid-loop-extension), and HSF (heat shock transcription factor), as key factors responsible for BS disease resistance in pepper. In conclusion, our study provides valuable resources for dissecting the underlying molecular mechanism responsible for Xcv resistance in pepper. Additionally, it also provides valuable references for mining transcriptomic data to identify key candidates for disease resistance in horticulture crops.

Identification of Chlorophyll Metabolism- and Photosynthesis-Related Genes Regulating Green Flower Color in Chrysanthemum by Integrative Transcriptome and Weighted Correlation Network Analyses

Green chrysanthemums are difficult to breed but have high commercial value. The molecular basis for the green petal color in chrysanthemum is not fully understood. This was investigated in the present study by RNA sequencing analysis of white and green ray florets collected at three stages of flower development from the F₁ progeny of the cross between Chrysanthemum × morifolium “Lüdingdang” with green-petaled flowers and Chrysanthemum vistitum with white-petaled flowers. The chlorophyll content was higher and chloroplast degradation was slower in green pools than in white pools at each developmental stage. Transcriptome analysis revealed that genes that were differentially expressed between the two pools were enriched in pathways related to chlorophyll metabolism and photosynthesis. We identified the transcription factor genes CmCOLa, CmCOLb, CmERF, and CmbHLH as regulators of the green flower color in chrysanthemum by differential expression analysis and weighted gene co-expression network analysis. These findings can guide future efforts to improve the color palette of chrysanthemum flowers through genetic engineering.

Transcriptome-based approaches for clarification of nutritional responses and improvement of crop production

Genome-wide transcriptome profiling is a powerful tool for identifying key genes and pathways involved in plant development and physiological processes. This review summarizes studies that have used transcriptome profiling mainly in rice to focus on responses to macronutrients such as nitrogen, phosphorus and potassium, and spatio-temporal root profiling in relation to the regulation of root system architecture as well as nutrient uptake and transport. We also discuss strategies based on meta- and co-expression analyses with different attributed transcriptome data, which can be used for investigating the regulatory mechanisms and dynamics of nutritional responses and adaptation, and speculate on further advances in transcriptome profiling that could have potential application to crop breeding and cultivation.

Weighted gene co-expression network analysis of the salt-responsive transcriptomes reveals novel hub genes in green halophytic microalgae Dunaliella salina

Despite responses to salinity stress in Dunaliella salina, a unicellular halotolerant green alga, being subject to extensive study, but the underlying molecular mechanism remains unknown. Here, Empirical Bayes method was applied to identify the common differentially expressed genes (DEGs) between hypersaline and normal conditions. Then, using weighted gene co-expression network analysis (WGCNA), which takes advantage of a graph theoretical approach, highly correlated genes were clustered as a module. Subsequently, connectivity patterns of the identified modules in two conditions were surveyed to define preserved and non-preserved modules by combining the Zsummary and medianRank measures. Finally, common and specific hub genes in non-preserved modules were determined using Eigengene-based module connectivity or module membership (k_ME) measures and validation was performed by using leave-one-out cross-validation (LOOCV). In this study, the power of beta = 12 (scale-free R2 = 0.8) was selected as the soft-thresholding to ensure a scale-free network, which led to the identification of 15 co-expression modules. Results also indicate that green, blue, brown, and yellow modules are non-preserved in salinity stress conditions. Examples of enriched Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways in non-preserved modules are Sulfur metabolism, Oxidative phosphorylation, Porphyrin and chlorophyll metabolism, Vitamin B6 metabolism. Moreover, the systems biology approach was applied here, proposed some salinity specific hub genes, such as radical-induced cell death1 protein (RCD1), mitogen-activated protein kinase kinase kinase 13 (MAP3K13), long-chain acyl-CoA synthetase (ACSL), acetyl-CoA carboxylase, biotin carboxylase subunit (AccC), and fructose-bisphosphate aldolase (ALDO), for the development of metabolites accumulating strains in D. salina.

Alternative Splicing Enhances the Transcriptome Complexity of Liriodendron chinense

Alternative splicing (AS) plays pivotal roles in regulating plant growth and development, flowering, biological rhythms, signal transduction, and stress responses. However, no studies on AS have been performed in Liriodendron chinense, a deciduous tree species that has high economic and ecological value. In this study, we used multiple tools and algorithms to analyze transcriptome data derived from seven tissues via hybrid sequencing. Although only 17.56% (8,503/48,408) of genes in L. chinense were alternatively spliced, these AS genes occurred in 37,844 AS events. Among these events, intron retention was the most frequent AS event, producing 1,656 PTC-containing and 3,310 non-PTC-containing transcripts. Moreover, 183 long noncoding RNAs (lncRNAs) also underwent AS events. Furthermore, weighted gene coexpression network analysis (WGCNA) revealed that there were great differences in the activities of transcription and post-transcriptional regulation between pistils and leaves, and AS had an impact on many physiological and biochemical processes in L. chinense, such as photosynthesis, sphingolipid metabolism, fatty acid biosynthesis and metabolism. Moreover, our analysis showed that the features of genes may affect AS, as AS genes and non-AS genes had differences in the exon/intron length, transcript length, and number of exons/introns. In addition, the structure of AS genes may impact the frequencies and types of AS because AS genes with more exons or introns tended to exhibit more AS events, and shorter introns tended to be retained, whereas shorter exons tended to be skipped. Furthermore, eight AS genes were verified, and the results were consistent with our analysis. Overall, this study reveals that AS and gene interaction are mutual-on one hand, AS can affect gene expression and translation, while on the other hand, the structural characteristics of the gene can also affect AS. This work is the first to comprehensively report on AS in L. chinense, and it can provide a reference for further research on AS in L. chinense.