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Leaf blight is a fungal disease that mainly affects the growth and development of leaves in plants. To investigate the molecular mechanisms of leaf blight defense in poplar, we performed RNA-Seq and enzyme activity assays on the Populus simonii × Populus nigra leaves inoculated with Alternaria alternate fungus. Through weighted gene co-expression network analysis (WGCNA), we obtained co-expression gene modules significantly associated with SOD and POD activities, containing 183 and 275 genes, respectively. We then constructed a co-expression network of poplar genes related to leaf blight resistance based on weight values. Additionally, we identified hub transcription factors (TFs) and structural genes in the network. The network was dominated by 15 TFs, and four out of them, including ATWRKY75, ANAC062, ATMYB23 and ATEBP, had high connectivity in the network, which might play important functions in leaf blight defense. In addition, GO enrichment analysis revealed a total of 44 structural genes involved in biotic stress, resistance, cell wall and immune-related biological processes in the network. Among them, there were 16 highly linked structural genes in the central part, which may be directly involved in poplar resistance to leaf blight. The study explores key genes associated with leaf blight defense in poplar, which further gains an understanding of the molecular mechanisms of biotic stress response in plants.

Agropyron mongolicum (A. mongolicum) is an excellent gramineous forage with extreme drought tolerance, which lives in arid and semiarid desert areas. However, the mechanism that underlies the response of microRNAs (miRNAs) and their targets in A. mongolicum to drought stress is not well understood. In this study, we analyzed the transcriptome, small RNAome (specifically the miRNAome) and degradome to generate a comprehensive resource that focused on identifying key regulatory miRNA-target circuits under drought stress. The most extended transcript in each collection is known as the UniGene, and a total of 41,792 UniGenes and 1,104 miRNAs were identified, and 99 differentially expressed miRNAs negatively regulated 1,474 differentially expressed target genes. Among them, eight miRNAs were unique to A. mongolicum, and there were 36 target genes. A weighted gene co-expression network analysis identified five hub genes. The miRNAs of five hub genes were screened with an integration analysis of the degradome and sRNAs, such as osa-miR444a-3p.2-MADS47, bdi-miR408-5p_1ss19TA-CCX1, taemiR9774_ L-2R-1_1ss11GT-carC, ata-miR169a-3p-PAO2, and bdi-miR528-p3_2ss15TG20CA-HOX24. The functional annotations revealed that they were involved in mediating the brassinosteroid signal pathway, transporting and exchanging sodium and potassium ions and regulating the oxidation-reduction process, hydrolase activity, plant response to water deprivation, abscisic acid (ABA) and the ABA-activated signaling pathway to regulate drought stress. Five hub genes were discovered, which could play central roles in the regulation of drought-responsive genes. These results show that the combined analysis of miRNA, the transcriptome and degradation group provides a useful platform to investigate the molecular mechanism of drought resistance in A. mongolicum and could provide new insights into the genetic engineering of Poaceae crops in the future. [ABSTRACT FROM AUTHOR]

Platinum resistance is one of the major concerns in ovarian cancer treatment. Recent evidence shows the critical role of epithelial–mesenchymal transition (EMT) in this resistance. Epithelial‐like ovarian cancer cells show decreased sensitivity to cisplatin after cisplatin treatment. Our study prospected the association between epithelial phenotype and response to cisplatin in ovarian cancer. Microarray dataset GSE47856 was acquired from the GEO database. After identifying differentially expressed genes (DEGs) between epithelial‐like and mesenchymal‐like cells, the module identification analysis was performed using weighted gene co‐expression network analysis (WGCNA). The gene ontology (GO) and pathway analyses of the most considerable modules were performed. The protein–protein interaction network was also constructed. The hub genes were specified using Cytoscape plugins MCODE and cytoHubba, followed by the survival analysis and data validation. Finally, the co‐expression of miRNA‐lncRNA‐TF with the hub genes was reconstructed. The co‐expression network analysis suggests 20 modules relating to the Epithelial phenotype. The antiquewhite4, brown and darkmagenta modules are the most significant non‐preserved modules in the Epithelial phenotype and contain the most differentially expressed genes. GO, and KEGG pathway enrichment analyses on these modules divulge that these genes were primarily enriched in the focal adhesion, DNA replication pathways and stress response processes. ROC curve and overall survival rate analysis show that the co‐expression pattern of the brown module's hub genes could be a potential prognostic biomarker for ovarian cancer cisplatin resistance. [ABSTRACT FROM AUTHOR]

The Oliveria decumbens Vent. is a wild, rare, annual medicinal plant and endemic plant of Iran that has metabolites (mostly terpenes) which make it a precious plant in Persian Traditional Medicine and also a potential chemotherapeutic agent. The lack of genetic resources has slowed the discovery of genes involved in the terpenes biosynthesis pathway. It is a wild relative of Daucus carota. In this research, we performed the transcriptomic differences between two samples, flower and root of Oliveria decumbens, and also analyze the expression value of the genes involved in terpenoid biosynthesis by RNA-seq and its essential oil's phytochemicals analyzed by GC/MS. In total, 136,031,188 reads from two samples of flower and root have been produced. The result shows that the MEP pathway is mostly active in the flower and the MVA in the root. Three genes of GPP, FPPS, and GGPP that are the precursors in the synthesis of mono, di, and triterpenes are upregulated in root and 23 key genes were identified that are involved in the biosynthesis of terpenes. Three genes had the highest upregulation in the root including, and on the other hand, another three genes had the expression only in the flower. Meanwhile, 191 and 185 upregulated genes in the flower and root of the plant, respectively, were selected for the gene ontology analysis and reconstruction of co-expression networks. The current research is the first of its kind on Oliveria decumbens transcriptome and discussed 67 genes that have been deposited into the NCBI database. Collectively, the information obtained in this study unveils the new insights into characterizing the genetic blueprint of Oliveria decumbens Vent. which paved the way for medical/plant biotechnology and the pharmaceutical industry in the future. [ABSTRACT FROM AUTHOR]

Auxin receptor plays a significant role in the plant auxin signalling pathway in response to abiotic stress. Recently, we found that transgenic rice overexpressing ABP57 had higher drought tolerance than the wild-type cultivar, MR219, due to the fact of its enhanced leaf photosynthetic rate and yields under drought stress. We performed a microarray study on this line to investigate the underlying mechanisms contributing to the observed phenotype. After microarray data filtering, 3596 genes were subjected to modular gene co-expression network (mGCN) development using CEMiTool, an R package. We identified highly related genes in 12 modules that could act to specific responses towards drought or any of the abiotic stress types. Gene set enrichment and overrepresentation analyses for modules extracted two highly upregulated modules that are involved in drought-related biological processes such as transmembrane transport of metal ions and response to oxidative stress. Finally, 123 hub genes were identified in all modules after integrating co-expression information with physical interaction data. In addition, the interplay of significant pathways between the metabolism of chlorophyll and flavonoid and the signalling pathways of MAPK, IAA, and SA inferred the concurrent involvement of stress tolerance response. Collectively, our findings seek new future directions for breeding strategies in rice tolerant improvements. [ABSTRACT FROM AUTHOR]

Poplars have a strong response to light, and shade is one of the main environmental factors that limits the growth and development of poplars. Exploring the response mechanism of the developing xylem of poplar under shady conditions is of great reference significance for improving wood yields. In this study, three excellent hybrids of poplar (Populus euramericana 'Zhonglin46' (Pe), Populus deltoides '27-17' (Pd), Populus × 'Wq156' (Pw) were studied under shady conditions. Based on the phenotypic data and developing a xylem transcriptome analysis, the molecular mechanism of poplars' response to shade was preliminarily revealed, and the core regulatory genes responding to shade were identified by a weighted co-expression network analysis (WGCNA). The results showed that Pw growth was significantly affected by shade, while Pe growth was slightly affected by shade. An enrichment analysis of 13,675 differentially expressed genes (DEGs) found that shade affected the expression of genes related to the glutathione metabolic pathway. The WGCNA analysis identified two modules ("Brown" and "Purple") related to the shade response and discovered seven hub genes. These hub genes were related to xylem development, vascular cambium division, stomatal development, and phytochrome A signal transduction. These results provide important basic information for gaining insight into the molecular response to shade in different poplar hybrids. [ABSTRACT FROM AUTHOR]

Phosphorus (P) is an indispensable macronutrient for plant growth and development, and it is involved in various cellular biological activities in plants. Camellia oleifera is a unique high-quality woody oil plant that grows in the hills and mountains of southern China. However, the available P content is deficient in southern woodland soil. Until now, few studies focused on the regulatory functions of microRNAs (miRNAs) and their target genes under low inorganic phosphate (Pi) stress. In this study, we integrated small RNA, degradome, and transcriptome sequencing data to investigate the mechanism of low Pi adaptation in C. oleifera. We identified 40,689 unigenes and 386 miRNAs by the deep sequencing technology and divided the miRNAs into four different groups. We found 32 miRNAs which were differentially expressed under low Pi treatment. A total of 414 target genes of 108 miRNAs were verified by degradome sequencing. Gene ontology (GO) functional analysis of target genes found that they were related to the signal response to the stimulus and transporter activity, indicating that they may respond to low Pi stress. The integrated analysis revealed that 31 miRNA-target pairs had negatively correlated expression patterns. A co-expression regulatory network was established based on the profiles of differentially expressed genes. In total, three hub genes (ARF22, WRKY53, and SCL6), which were the targets of differentially expressed miRNAs, were discovered. Our results showed that integrated analyses of the small RNA, degradome, and transcriptome sequencing data provided a valuable basis for investigating low Pi in C. oleifera and offer new perspectives on the mechanism of low Pi tolerance in woody oil plants. [ABSTRACT FROM AUTHOR]

Background: Cold is one of the main abiotic stresses that severely affect plant growth and development, and crop productivity as well. Transcriptional changes during cold stress have already been intensively studied in various plant species. However, the gene networks involved in the regulation of differential cold tolerance between tobacco varieties with contrasting cold resistance are quite limited. Results: Here, we conducted multiple time-point transcriptomic analyses using Tai tobacco (TT, cold susceptibility) and Yan tobacco (YT, cold resistance) with contrasting cold responses. We identified similar DEGs in both cultivars after comparing with the corresponding control (without cold treatment), which were mainly involved in response to abiotic stimuli, metabolic processes, kinase activities. Through comparison of the two cultivars at each time point, in contrast to TT, YT had higher expression levels of the genes responsible for environmental stresses. By applying Weighted Gene Co-Expression Network Analysis (WGCNA), we identified two main modules: the pink module was similar while the brown module was distinct between the two cultivars. Moreover, we obtained 100 hub genes, including 11 important transcription factors (TFs) potentially involved in cold stress, 3 key TFs in the brown module and 8 key TFs in the pink module. More importantly, according to the genetic regulatory networks (GRNs) between TFs and other genes or TFs by using GENIE3, we identified 3 TFs (ABI3/VP1, ARR-B and WRKY) mainly functioning in differential cold responses between two cultivars, and 3 key TFs (GRAS, AP2-EREBP and C2H2) primarily involved in cold responses. Conclusion: Collectively, our study provides valuable resources for transcriptome- based gene network studies of cold responses in tobacco. It helps to reveal how key cold responsive TFs or other genes are regulated through network. It also helps to identify the potential key cold responsive genes for the genetic manipulation of tobacco cultivars with enhanced cold tolerance in the future. [ABSTRACT FROM AUTHOR]

Nasopharyngeal carcinoma is a type of head and neck cancer with a high incidence in men. In the past decades, the survival rate of NPC has remained around 70%, but it often leads to treatment failure due to its distant metastasis or recurrence. The lncRNA-mRNA regulatory network has not been fully elucidated. We downloaded the NPC-related gene expression datasets GSE53819 and GSE12452 from the Gene Expression Omnibus database; GSE53819 included 18 NPC tissues and 18 normal tissues, and GSE12452 included 31 NPC tissues and 10 normal tissues. Weighted gene coexpression network analysis was performed on mRNA and lncRNA to screen out modules that were highly correlated with tumor progression. The two datasets were subjected to differential analysis after removing batch effects, and then Venn diagrams were used to screen for overlapping genes in the module genes and differential genes. The lncRNA-mRNA co-expression network was then constructed, and key mRNAs were identified by MCODE analysis and expression analysis. GSEA analysis and qRT-PCR were performed on key mRNAs. Through a series of analyses, we speculated that BTK, CD72, PTPN6, and VAV1 may be independent predictors of the prognosis of NPC patients.Taken together, our study provides potential candidate biomarkers for NPC diagnosis, prognosis, or precise treatment. [ABSTRACT FROM AUTHOR]

Ionomics, the study of the composition of mineral nutrients and trace elements in organisms that represent the inorganic component of cells and tissues, has been widely studied to explore to unravel the molecular mechanism regulating the elemental composition of plants. However, the genetic factors of rice subspecies in the interaction between arsenic and functional ions have not yet been explained. Here, the correlation between As and eight essential ions in a rice core collection was analyzed, taking into account growing condition and genetic factors. The results demonstrated that the correlation between As and essential ions was affected by genetic factors and growing condition, but it was confirmed that the genetic factor was slightly larger with the heritability for arsenic content at 53%. In particular, the cluster coefficient of japonica (0.428) was larger than that of indica (0.414) in the co-expression network analysis for 23 arsenic genes, and it was confirmed that the distance between genes involved in As induction and detoxification of japonica was far than that of indica. These findings provide evidence that japonica populations could accumulate more As than indica populations. In addition, the cis-eQTLs of AIR2 (arsenic-induced RING finger protein) were isolated through transcriptome-wide association studies, and it was confirmed that AIR2 expression levels of indica were lower than those of japonica. This was consistent with the functional haplotype results for the genome sequence of AIR2, and finally, eight rice varieties with low AIR2 expression and arsenic content were selected. In addition, As-related QTLs were identified on chromosomes 5 and 6 under flooded and intermittently flooded conditions through genome-scale profiling. Taken together, these results might assist in developing markers and breeding plans to reduce toxic element content and breeding high-quality rice varieties in future. [ABSTRACT FROM AUTHOR]

MicroRNAs is one class of small non-coding RNAs that play important roles in plant growth and development. Though miRNAs and their target genes have been widely studied in many plant species, their functional roles in floral bud break and dormancy release in woody perennials is still unclear. In this study, we applied transcriptome and small RNA sequencing together to systematically explore the transcriptional and post-transcriptional regulation of floral bud break in P. mume. Through expression profiling, we identified a few candidate genes and miRNAs during different developmental stage transitions. In total, we characterized 1,553 DEGs associated with endodormancy release and 2,084 DEGs associated with bud flush. Additionally, we identified 48 known miRNAs and 53 novel miRNAs targeting genes enriched in biological processes such as floral organ morphogenesis and hormone signaling transudation. We further validated the regulatory relationship between differentially expressed miRNAs and their target genes combining computational prediction, degradome sequencing, and expression pattern analysis. Finally, we integrated weighted gene co-expression analysis and constructed miRNAmRNA regulatory networks mediating floral bud flushing competency. In general, our study revealed the miRNA-mediated networks in modulating floral bud break in P. mume. The findings will contribute to the comprehensive understanding of miRNA-mediated regulatory mechanism governing floral bud break and dormancy cycling in wood perennials. [ABSTRACT FROM AUTHOR]

Background: Mung bean is a short-duration and essential food crop owing to its cash prominence in Asia. Mung bean seeds are rich in protein, fiber, antioxidants, and phytonutrients. The NAC transcription factors (TFs) family is a large plant-specific family, participating in tissue development regulation and abiotic and biotic stresses. Results: In this study, we perform genome-wide comparisons of VrNAC with their homologs from Arabidopsis. We identified 81 NAC transcription factors (TFs) in mung bean genome and named as per their chromosome location. A phylogenetic analysis revealed that VrNACs are broadly distributed in nine groups. Moreover, we identified 20 conserved motifs across the VrNACs highlighting their roles in different biological process. Based on the gene structure of the putative VrNAC and segmental duplication events might be playing a vital role in the expansion of mung bean genome. A comparative phylogenetic analysis of mung bean NAC together with homologs from Arabidopsis allowed us to classify NAC genes into 13 groups, each containing several orthologs and paralogs. Gene ontology (GO) analysis categorized the VrNACs into biological process, cellular components and molecular functions, explaining the functions in different plant physiology processes. A gene co-expression network analysis identified 173 genes involved in the transcriptional network of putative VrNAC genes. We also investigated how miRNAs potentially target VrNACs and shape their interactions with proteins. VrNAC1.4 (Vradi01g03390.1) was targeted by the Vra-miR165 family, including 9 miRNAs. Vra-miR165 contributes to leaf development and drought tolerance. We also performed qRT-PCR on 22 randomly selected VrNAC genes to assess their expression patterns in the NM-98 genotype, widely known for being tolerant to drought and bacterial leaf spot disease. Conclusions: This genome-wide investigation of VrNACs provides a unique resource for further detailed investigations aimed at predicting orthologs functions and what role the play under abiotic and biotic stress, with the ultimate aim to improve mung bean production under diverse environmental conditions. [ABSTRACT FROM AUTHOR]

Background: According to clinical study results, immune checkpoint blockade (ICB) treatment enhances the survival outcome of patients with clear cell renal cell carcinoma (ccRCC). Previous research has divided ccRCC patients into immune subtypes with distinct ICB response rates. However, the study on the association between lncRNAs and ccRCC immune subtypes is lacking. Methods: Differentially expressed lncRNAs/mRNAs between two major immune subgroups were calculated. A weighted gene co-expression network analysis (WGCNA) was conducted to establish the lncRNA-mRNA co-expression network and select the key lncRNAs. Then, prognostic lncRNAs were selected from the network by the bioinformatics method. Next, the risk-score was estimated by lncRNA expression and their coefficients. Finally, a nomogram based on lncRNAs and clinical parameters was created to predict the prognosis of ccRCC. Results: LncRNAs and mRNAs associated with ccRCC immune subtypes were identified. The lncRNAs and mRNAs from a gene module closely linked to the immune subtype were used to construct a network. The KEGG pathways enriched in the network were related to immune system activation processes. These 8 lncRNAs (AL365361.1, LINC01934, AC090152.1, PCED1B-AS1, LINC00426, AC007728.2, AC243829.4, and LINC00158) were found to be positively correlated with immune cells of the tumor microenvironment. The C-index of the nomogram was 0.777, and the calibration curve data suggests that the nomogram has a high degree of discriminating capacity. Conclusion: In summary, we discovered core lncRNAs linked with immune subtypes and created corresponding lncRNA–mRNA networks. These lncRNAs are anticipated to have predictive significance for ccRCC and may provide insight into novel biomarkers for the disease. [ABSTRACT FROM AUTHOR]

Purpose: Through comprehensive bioinformatics analysis based on the immune microenvironment, this study aimed to identify immune-related RNA biomarkers that indicate aneurysmal subarachnoid hemorrhage (aSAH).Methods: The GSE73378 dataset was downloaded from the National Center for Biotechnology Information GEO database, providing blood from 107 normal controls and 103 patients with aSAH. The immune infiltration types in the aSAH blood samples were assessed and RNAs that were differentially expressed (DE) between 1) the aSAH and control groups and 2) the immune infiltration groups (high and low) were identified. The intersecting genes were subjected to weighted gene co-expression network analysis followed by co-expression network construction. The aSAH-related genes and pathways were identified from the Comparative Toxicogenomics Database: update 2019.Results: A total of three DE long non-coding RNAs (lncRNAs) and 301 DE mRNAs were identified. Of the 301 mRNAs, 91 were significantly enriched in three modules. Based on the 91 mRNAs and three lncRNAs, a co-expression network related to the disease pathway was constructed. This pathway consisted of 16 factors, including the 13 mRNAs (e.g., TNFSF13B, TNFSF10, MYD88, GNA12 and NSMAF) and three lncRNAs (FAM66A, LINC00954 and CELF2-AS2), as well as six pathways, including the NF-κB, toll-like receptor, and sphingolipid signalling pathways.Conclusion: TNFSF13B, MYD88, GNA12, NSMAF, FAM66A, LINC00954 and CELF2-AS2 may serve as biomarkers for aSAH. The NF-κB, toll-like receptor and sphingolipid signalling pathways may play critical roles in the progression of aSAH. [ABSTRACT FROM AUTHOR]

ObjectiveHypertrophic cardiomyopathy (HCM) is a complex heterogeneous heart disease. Recent reports found that long non-coding RNAs (lncRNAs) play an important role in the progression of cardiovascular diseases. The present study aimed to identify the novel lncRNAs and messenger RNAs (mRNAs) and determine the key pathways involved in HCM.MethodsThe lncRNA and mRNA sequencing datasets of GSE68316 and GSE130036 were downloaded from the Gene Expression Omnibus (GEO) database. An integrated co-expression network analysis was conducted to identify differentially expressed lncRNAs and differentially expressed mRNAs in patients with HCM. Then, gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were explored to identify the biological functions and signaling pathways of the co-expression network. Protein–protein interaction (PPI) and hub gene networks were constructed by using Cytoscape software. Plasma samples of patients with HCM and the GSE89714 dataset were used to validate the bioinformatics results.ResultsA total of 1,426 differentially expressed long non-coding RNAs (lncRNAs) and 1,715 differentially expressed mRNAs were obtained from GSE68316, of which 965 lncRNAs and 896 mRNAs were upregulated and 461 lncRNAs and 819 mRNAs were downregulated. A total of 469 differentially expressed lncRNAs and 2,407 differentially expressed mRNAs were screened from GSE130036, of which 183 lncRNAs and 1,283 mRNAs were upregulated and 286 lncRNAs and 1,124 mRNAs were downregulated. A co-expression network was constructed and contained 30 differentially expressed lncRNAs and 63 differentially expressed mRNAs, which were primarily involved in ‘G-protein beta/gamma-subunit complex binding,' ‘polyubiquitin modification-dependent protein binding,' ‘Apelin signaling pathway,' and ‘Wnt signaling pathway.' The 10 hub genes in the upregulated network [G Protein Subunit Alpha I2 (GNAI2), G Protein Subunit Alpha I1 (GNAI1), G Protein Subunit Alpha I3 (GNAI3), G Protein Subunit Gamma 2 (GNG2), G Protein Subunit Beta 1 (GNB1), G Protein Subunit Gamma 13 (GNG13), G Protein Subunit Gamma Transducin 1 (GNGT1), G Protein Subunit Gamma 12 (GNG12), AKT Serine/Threonine Kinase 1 (AKT1) and GNAS Complex Locus (GNAS)] and the 10 hub genes in the downregulated network [Nucleotide-Binding Oligomerization Domain Containing Protein 2 (NOD2), Receptor-Interacting Serine/Threonine Kinase 2 (RIPK2), Nucleotide-Binding Oligomerization Domain Containing Protein 1 (NOD1), Mitochondrial Antiviral Signaling Protein (MAVS), Autophagy Related 16-Like 1 (ATG16L1), Interferon Induced With Helicase C Domain 1 (IFIH1), Autophagy Related 5 (ATG5), TANK-Binding Kinase 1 (TBK1), Caspase Recruitment Domain Family Member 9 (CARD9), and von Willebrand factor (VWF)] were screened using cytoHubba. The expression of LA16c-312E8.2 and RP5-1160K1.3 in the plasma of patients with HCM was elevated, and the expression of the MIR22 host gene (MIR22HG) was decreased, which was consistent with our analysis, while the expression of LINC00324 and Small Nucleolar RNA Host Gene 12 (SNHG12) was not significantly different between the two groups. Verification analyses performed on GSE89714 showed the upregulated mRNAs of Chloride Voltage-Gated Channel 7 (CLCN7), N-Acetylglucosamine-1-Phosphate Transferase Subunit Gamma (GNPTG), Unk Like Zinc Finger (UNKL), Adenosine Monophosphate Deaminase 2 (AMPD2), GNAI3, WD Repeat Domain 81 (WDR81), and Serpin Family F Member 1 (SERPINF1) and downregulated mRNAs of TATA-Box Binding Protein Associated Factor 12 (TAF12) co-expressed with five crucial lncRNAs. Moreover, GNAI2, GNAI3, GNG12, and vWF were upregulated and GNAS was downregulated in the top 10 hub genes of upregulated and downregulated PPI networks.ConclusionThese findings from integrative biological analysis of lncRNA-mRNA co-expression networks explored the key genes and pathways and provide new insights into the understanding of the mechanism and discovering new therapeutic targets for HCM. Three differentially expressed pivotal lncRNAs (LA16c-312E8.2, RP5-1160K1.3, and MIR22HG) in the co-expression network may serve as biomarkers and intervention targets for the diagnosis and treatment of HCM.

The Oliveria decumbens Vent. is a wild, rare, annual medicinal plant and endemic plant of Iran that has metabolites (mostly terpenes) which make it a precious plant in Persian Traditional Medicine and also a potential chemotherapeutic agent. The lack of genetic resources has slowed the discovery of genes involved in the terpenes biosynthesis pathway. It is a wild relative of Daucus carota. In this research, we performed the transcriptomic differences between two samples, flower and root of Oliveria decumbens, and also analyze the expression value of the genes involved in terpenoid biosynthesis by RNA-seq and its essential oil’s phytochemicals analyzed by GC/MS. In total, 136,031,188 reads from two samples of flower and root have been produced. The result shows that the MEP pathway is mostly active in the flower and the MVA in the root. Three genes of GPP, FPPS, and GGPP that are the precursors in the synthesis of mono, di, and triterpenes are upregulated in root and 23 key genes were identified that are involved in the biosynthesis of terpenes. Three genes had the highest upregulation in the root including, and on the other hand, another three genes had the expression only in the flower. Meanwhile, 191 and 185 upregulated genes in the flower and root of the plant, respectively, were selected for the gene ontology analysis and reconstruction of co-expression networks. The current research is the first of its kind on Oliveria decumbens transcriptome and discussed 67 genes that have been deposited into the NCBI database. Collectively, the information obtained in this study unveils the new insights into characterizing the genetic blueprint of Oliveria decumbens Vent. which paved the way for medical/plant biotechnology and the pharmaceutical industry in the future.

BackgroundAccording to clinical study results, immune checkpoint blockade (ICB) treatment enhances the survival outcome of patients with clear cell renal cell carcinoma (ccRCC). Previous research has divided ccRCC patients into immune subtypes with distinct ICB response rates. However, the study on the association between lncRNAs and ccRCC immune subtypes is lacking.MethodsDifferentially expressed lncRNAs/mRNAs between two major immune subgroups were calculated. A weighted gene co-expression network analysis (WGCNA) was conducted to establish the lncRNA-mRNA co-expression network and select the key lncRNAs. Then, prognostic lncRNAs were selected from the network by the bioinformatics method. Next, the risk-score was estimated by lncRNA expression and their coefficients. Finally, a nomogram based on lncRNAs and clinical parameters was created to predict the prognosis of ccRCC.ResultsLncRNAs and mRNAs associated with ccRCC immune subtypes were identified. The lncRNAs and mRNAs from a gene module closely linked to the immune subtype were used to construct a network. The KEGG pathways enriched in the network were related to immune system activation processes. These 8 lncRNAs (AL365361.1, LINC01934, AC090152.1, PCED1B-AS1, LINC00426, AC007728.2, AC243829.4, and LINC00158) were found to be positively correlated with immune cells of the tumor microenvironment. The C-index of the nomogram was 0.777, and the calibration curve data suggests that the nomogram has a high degree of discriminating capacity.ConclusionIn summary, we discovered core lncRNAs linked with immune subtypes and created corresponding lncRNA–mRNA networks. These lncRNAs are anticipated to have predictive significance for ccRCC and may provide insight into novel biomarkers for the disease.

Abstract Background Gene fusion has epigenetic modification functions. The novel proteins encoded by gene fusion products play a role in cancer development. Therefore, a better understanding of the novel protein products may provide insights into the pathogenesis of tumors. However, the characteristics of chimeric genes are rarely studied. Here, we used weighted co-expression network analysis to investigate the biological roles and underlying mechanisms of chimeric genes. Methods Download the pig transcriptome data, we screened chimeric genes and parental genes from 688 sequences and 153 samples, predict their domains, and analyze their associations. We constructed a co-expression network of chimeric genes in pigs and conducted Gene Ontology enrichment and Kyoto Encyclopedia of Genes and Genomes pathway analysis on the generated modules using DAVID to identify key networks and modules related to chimeric genes. Results Our findings showed that most of the protein domains of chimeric genes were derived from fused pre-genes. Chimeric genes were enriched in modules involved in the negative regulation of cell proliferation and protein localization to centrosomes. In addition, the chimeric genes were related to the growth factor-β superfamily, which regulates cell growth and differentiation. Furthermore, in helper T cells, chimeric genes regulate the specific recognition of T cell receptors, implying that chimeric genes play a key role in the regulation pathway of T cells. Chimeric genes can produce new domains, and some chimeric genes are a key role involved in pathway-related function. Conclusions Most chimeric genes show binding activity. Domains of chimeric genes are derived from several combinations of parent genes. Chimeric genes play a key role in the regulation of several cellular pathways. Our findings may provide new directions to explore the roles of chimeric genes in tumors.

Abstract Background Network-based analysis of gene expression through co-expression networks can be used to investigate modular relationships occurring between genes performing different biological functions. An extended description of each of the network modules is therefore a critical step to understand the underlying processes contributing to a disease or a phenotype. Biological integration, topology study and conditions comparison (e.g. wild vs mutant) are the main methods to do so, but to date no tool combines them all into a single pipeline. Results Here we present GWENA, a new R package that integrates gene co-expression network construction and whole characterization of the detected modules through gene set enrichment, phenotypic association, hub genes detection, topological metric computation, and differential co-expression. To demonstrate its performance, we applied GWENA on two skeletal muscle datasets from young and old patients of GTEx study. Remarkably, we prioritized a gene whose involvement was unknown in the muscle development and growth. Moreover, new insights on the variations in patterns of co-expression were identified. The known phenomena of connectivity loss associated with aging was found coupled to a global reorganization of the relationships leading to expression of known aging related functions. Conclusion GWENA is an R package available through Bioconductor ( https://bioconductor.org/packages/release/bioc/html/GWENA.html ) that has been developed to perform extended analysis of gene co-expression networks. Thanks to biological and topological information as well as differential co-expression, the package helps to dissect the role of genes relationships in diseases conditions or targeted phenotypes. GWENA goes beyond existing packages that perform co-expression analysis by including new tools to fully characterize modules, such as differential co-expression, additional enrichment databases, and network visualization.

Abstract Background The hallmarks of cancer provide a highly cited and well-used conceptual framework for describing the processes involved in cancer cell development and tumourigenesis. However, methods for translating these high-level concepts into data-level associations between hallmarks and genes (for high throughput analysis), vary widely between studies. The examination of different strategies to associate and map cancer hallmarks reveals significant differences, but also consensus. Results Here we present the results of a comparative analysis of cancer hallmark mapping strategies, based on Gene Ontology and biological pathway annotation, from different studies. By analysing the semantic similarity between annotations, and the resulting gene set overlap, we identify emerging consensus knowledge. In addition, we analyse the differences between hallmark and gene set associations using Weighted Gene Co-expression Network Analysis and enrichment analysis. Conclusions Reaching a community-wide consensus on how to identify cancer hallmark activity from research data would enable more systematic data integration and comparison between studies. These results highlight the current state of the consensus and offer a starting point for further convergence. In addition, we show how a lack of consensus can lead to large differences in the biological interpretation of downstream analyses and discuss the challenges of annotating changing and accumulating biological data, using intermediate knowledge resources that are also changing over time.

Abstract Background Cottonseed is one of the major sources of vegetable oil. Analysis of the dynamic changes of fatty acid components and the genes regulating the composition of fatty acids of cottonseed oil is of great significance for understanding the biological processes underlying biosynthesis of fatty acids and for genetic improving the oil nutritional qualities. Results In this study, we investigated the dynamic relationship of 13 fatty acid components at 12 developmental time points of cottonseed (Gossypium hirsutum L.) and generated cottonseed transcriptome of the 12 time points. At 5–15 day post anthesis (DPA), the contents of polyunsaturated linolenic acid (C18:3n-3) and saturated stearic acid (C18:0) were higher, while linoleic acid (C18:2n-6) was mainly synthesized after 15 DPA. Using 5 DPA as a reference, 15,647 non-redundant differentially expressed genes were identified in 10–60 DPA cottonseed. Co-expression gene network analysis identified six modules containing 3275 genes significantly associated with middle-late seed developmental stages and enriched with genes related to the linoleic acid metabolic pathway and α-linolenic acid metabolism. Genes (Gh_D03G0588 and Gh_A02G1788) encoding stearoyl-ACP desaturase were identified as hub genes and significantly up-regulated at 25 DPA. They seemed to play a decisive role in determining the ratio of saturated fatty acids to unsaturated fatty acids. FAD2 genes (Gh_A13G1850 and Gh_D13G2238) were highly expressed at 25–50 DPA, eventually leading to the high content of C18:2n-6 in cottonseed. The content of C18:3n-3 was significantly decreased from 5 DPA (7.44%) to 25 DPA (0.11%) and correlated with the expression characteristics of Gh_A09G0848 and Gh_D09G0870. Conclusions These results contribute to our understanding on the relationship between the accumulation pattern of fatty acid components and the expression characteristics of key genes involved in fatty acid biosynthesis during the entire period of cottonseed development.

Abstract Background Night-break (NB) has been proven to repress flowering of short-day plants (SDPs). Long-noncoding RNAs (lncRNAs) play key roles in plant flowering. However, investigation of the relationship between lncRNAs and NB responses is still limited, especially in Chenopodium quinoa, an important short-day coarse cereal. Results In this study, we performed strand-specific RNA-seq of leaf samples collected from quinoa seedlings treated by SD and NB. A total of 4914 high-confidence lncRNAs were identified, out of which 91 lncRNAs showed specific responses to SD and NB. Based on the expression profiles, we identified 17 positive- and 7 negative-flowering lncRNAs. Co-expression network analysis indicated that 1653 mRNAs were the common targets of both types of flowering lncRNAs. By mapping these targets to the known flowering pathways in model plants, we found some pivotal flowering homologs, including 2 florigen encoding genes (FT (FLOWERING LOCUS T) and TSF (TWIN SISTER of FT) homologs), 3 circadian clock related genes (EARLY FLOWERING 3 (ELF3), LATE ELONGATED HYPOCOTYL (LHY) and ELONGATED HYPOCOTYL 5 (HY5) homologs), 2 photoreceptor genes (PHYTOCHROME A (PHYA) and CRYPTOCHROME1 (CRY1) homologs), 1 B-BOX type CONSTANS (CO) homolog and 1 RELATED TO ABI3/VP1 (RAV1) homolog, were specifically affected by NB and competed by the positive and negative-flowering lncRNAs. We speculated that these potential flowering lncRNAs may mediate quinoa NB responses by modifying the expression of the floral homologous genes. Conclusions Together, the findings in this study will deepen our understanding of the roles of lncRNAs in NB responses, and provide valuable information for functional characterization in future.

Ultraviolet-B (UV-B) radiation is a major abiotic stress that dragon trees are exposed to during their growth and development; however, it is also an environmental signal perceived by plants that affects the flavonoid pathway. Previous studies have demonstrated that amounts of flavonoids are contained in dragon tree resin, otherwise known as dragon’s blood. However, the traits and mechanism involved in the UV-B-mediated increase in flavonoids in dragon trees are still unknown. Here, we studied the response of Dracaena cambodiana under full solar UV-B radiation. The results showed that the contents of total flavonoids in D. cambodiana significantly increased after UV-B radiation exposure. Then, the transcriptome was used for determining the interactive mechanism of flavonoid accumulation and UV-B stress. Differential expression analyses identified 34 differentially expressed genes (DEGs) involved in flavonoid synthesis; specifically, 24 of the identified DEGs were significantly up-regulated after UV-B radiation exposure. In addition, 57 DEGs involved in Ca2+/kinase sensors, 58 DEGs involved in ROS scavenging and the plant hormone pathway, and 116 DEGs transcription factors in 5 families were further identified and analyzed. Finally, we deduced the potential mechanism of UV-B-promoting flavonoid formation to neutralize ROS damage derived from UV-B radiation in D. cambodiana based on the gene co-expression network and previous studies from other plants. Considering that wild dragon tree populations are currently highly threatened by anthropogenic and natural stressors, the interactive studies between D. cambodiana plants and UV-B radiation provide valuable information toward understanding the mechanism of dragon’s blood formation and help us reveal the evolution of D. cambodiana, with the eventual goal of aiding in the global conservation of this precious biological resource.

Eucommia ulmoides is a temperate gum source plant that produces trans-polyisoprene (TPI), also known as Eucommia rubber. The structural configuration and function of TPI offer a new material with important potential for industrial development. In this study, we detected the TPI content in the leaves of diploid and triploid E. ulmoides plants. The average TPI content in the leaves of triploid E. ulmoides was significantly higher than that of diploid. Transcriptome data and weighted gene co-expression network analyses identified a significant positive correlation between the EuFPS1 gene and TPI content. Overexpression of EuFPS1 increased the density of rubber particles and TPI content, indicating its crucial role in TPI biosynthesis. In addition, the expression of EuHDZ25 in E. ulmoides was significantly positively correlated with EuFPS1 expression. Yeast one-hybrid and dual-luciferase assays demonstrated that EuHDZ25 mainly promotes TPI biosynthesis through positive regulation of EuFPS1 expression. The significantly up-regulated expression of EuHDZ25 and its consequent upregulation of EuFPS1 during the biosynthesis of TPI may partially explain the increased TPI content of triploids. This study provides an important theoretical foundation for further exploring the molecular mechanism of secondary metabolites content variation in polyploids and can help to promote the development and utilization of rubber resources. [ABSTRACT FROM AUTHOR]

Aroma is a crucial attribute affecting the quality of pepper and its processed products, which has significant commercial value. However, little is known about the composition of volatile aroma compounds (VACs) in pepper fruits and their potential molecular regulatory mechanisms. In this study, HS-SPME-GC-MS combined with transcriptome sequencing is used to analyze the composition and formation mechanism of VACs in different kinds and development stages of pepper fruits. The results showed that 149 VACs, such as esters, alcohols, aldehydes, and terpenoids, were identified from 4 varieties and 3 development stages, and there were significant quantitative differences among different samples. Volatile esters were the most important aroma components in pepper fruits. PCA analysis showed that pepper fruits of different developmental stages had significantly different marker aroma compounds, which may be an important provider of pepper’s characteristic aroma. Transcriptome analysis showed that many differential genes (DEGs) were enriched in the metabolic pathways related to the synthesis of VACs, such as fatty acids, amino acids, MVA, and MEP in pepper fruits. In addition, we identified a large number of differential transcription factors (TFs) that may regulate the synthesis of VACs. Combined analysis of differential aroma metabolites and DEGs identified two co-expression network modules highly correlated with the relative content of VACs in pepper fruit. This study confirmed the basic information on the changes of VACs in the fruits of several Chinese spicy peppers at different stages of development, screened out the characteristic aroma components of different varieties, and revealed the molecular mechanism of aroma formation, providing a valuable reference for the quality breeding of pepper.

Drought is one of the most serious abiotic stressors in the environment, restricting agricultural production by reducing plant growth, development, and productivity. To investigate such a complex and multifaceted stressor and its effects on plants, a systems biology-based approach is necessitated, entailing the generation of co-expression networks, identification of high-priority transcription factors (TFs), dynamic mathematical modeling, and computational simulations. Here, we studied a high-resolution drought transcriptome of Arabidopsis. We identified distinct temporal transcriptional signatures and demonstrated the involvement of specific biological pathways. Generation of a large-scale co-expression network followed by network centrality analyses identified 117 TFs that possess critical properties of hubs, bottlenecks, and high clustering coefficient nodes. Dynamic transcriptional regulatory modeling of integrated TF targets and transcriptome datasets uncovered major transcriptional events during the course of drought stress. Mathematical transcriptional simulations allowed us to ascertain the activation status of major TFs, as well as the transcriptional intensity and amplitude of their target genes. Finally, we validated our predictions by providing experimental evidence of gene expression under drought stress for a set of four TFs and their major target genes using qRT-PCR. Taken together, we provided a systems-level perspective on the dynamic transcriptional regulation during drought stress in Arabidopsis and uncovered numerous novel TFs that could potentially be used in future genetic crop engineering programs.

Subtilases (SBTs), which belong to the serine peptidases, control plant development by regulating cell wall properties and the activity of extracellular signaling molecules, and affect all stages of the life cycle, such as seed development and germination, and responses to biotic and abiotic environments. In this study, 146 Gossypium hirsutum, 138 Gossypium barbadense, 89 Gossypium arboreum and 84 Gossypium raimondii SBTs were identified and divided into six subfamilies. Cotton SBTs are unevenly distributed on chromosomes. Synteny analysis showed that the members of SBT1 and SBT4 were expanded in cotton compared to Arabidopsis thaliana. Co-expression network analysis showed that six Gossypium arboreum SBT gene family members were in a network, among which five SBT1 genes and their Gossypium hirsutum and Arabidopsis thaliana direct homologues were down-regulated by salt treatment, indicating that the co-expression network might share conserved functions. Through co-expression network and annotation analysis, these SBTs may be involved in the biological processes of auxin transport, ABA signal transduction, cell wall repair and root tissue development. In summary, this study provides valuable information for the study of SBT genes in cotton and excavates SBT genes in response to salt stress, which provides ideas for cotton breeding for salinity resistance.

Salinity and alkalinity are among the important factors affecting the distribution, survival, growth and physiology of aquatic animals. Chinese sea bass (Lateolabrax maculatus) is an important aquaculture fish species in China that can widely adapt to diverse salinities from freshwater (FW) to seawater (SW) but moderately adapt to highly alkaline water (AW). In this study, juvenile L. maculatus were exposed to salinity change (SW to FW) and alkalinity stress (FW to AW). Coordinated transcriptomic responses in L. maculatus gills were investigated and based on the weighted gene co-expression network analysis (WGCNA), 8 and 11 stress-responsive modules (SRMs) were identified for salinity change and alkalinity stress, respectively, which revealed a cascade of cellular responses to oxidative and osmotic stress in L. maculatus gills. Specifically, four upregulated SRMs were enriched with induced differentially expressed genes (DEGs) for alkalinity stress, mainly corresponding to the functions of “extracellular matrix” and “anatomical structure”, indicating a strong cellular response to alkaline water. Both “antioxidative activity” and “immune response” functions were enriched in the downregulated alkaline SRMs, which comprised inhibited alkaline specific DEGs, revealing the severely disrupted immune and antioxidative functions under alkalinity stress. These alkaline-specific responses were not revealed in the salinity change groups with only moderately inhibited osmoregulation and induced antioxidative response in L. maculatus gills. Therefore, the results revealed the diverse and correlated regulation of the cellular process and stress response in saline-alkaline water, which may have arisen through the functional divergence and adaptive recruitment of the co-expression genes and will provide vital insights for the development of L. maculatus cultivation in alkaline water.

SUMMARY: Long non‐coding RNAs (lncRNAs) are emerging as versatile regulators in diverse biological processes. However, little is known about their cis‐ and trans‐regulatory contributions in gene expression under salt stress. Using 27 RNA‐seq data sets from Populus trichocarpa leaves, stems and roots, we identified 2988 high‐confidence lncRNAs, including 1183 salt‐induced differentially expressed lncRNAs. Among them, 301 lncRNAs have potential for positively affecting their neighboring genes, predominantly in a cis‐regulatory manner rather than by co‐transcription. Additionally, a co‐expression network identified six striking salt‐associated modules with a total of 5639 genes, including 426 lncRNAs, and in these lncRNA sequences, the DNA/RNA binding motifs are enriched. This suggests that lncRNAs might contribute to distant gene expression of the salt‐associated modules in a trans‐regulatory manner. Moreover, we found 30 lncRNAs that have potential to simultaneously cis‐ and trans‐regulate salt‐responsive homologous genes, and Ptlinc‐NAC72, significantly induced under long‐term salt stress, was selected for validating its regulation of the expression and functional roles of the homologs PtNAC72.A and PtNAC72.B (PtNAC72.A/B). The transient transformation of Ptlinc‐NAC72 and a dual‐luciferase assay of Ptlinc‐NAC72 and PtNAC72.A/B promoters confirmed that Ptlinc‐NAC72 can directly upregulate PtNAC72.A/B expression, and a presence/absence assay was further conducted to show that the regulation is probably mediated by Ptlinc‐NAC72 recognizing the tandem elements (GAAAAA) in the PtNAC72.A/B 5′ untranslated region (5′‐UTR). Finally, the overexpression of Ptlinc‐NAC72 produces a hypersensitive phenotype under salt stress. Altogether, our results shed light on the cis‐ and trans‐regulation of gene expression by lncRNAs in Populus and provides an example of long‐term salt‐induced Ptlinc‐NAC72 that could be used to mitigate growth costs by conferring plant resilience to salt stress. Significance Statement: Evidence of the cis‐ and trans‐regulation of gene expression by lncRNAs under salt stress is lacking. Here, we demonstrate the limits of cis‐regulation versus the limitless trans‐regulation of lncRNAs in potentially regulating gene expression under salt stress, and also demonstrate that Ptlinc‐NAC72 functions in delayed negative feedback under long‐term salt stress that could be exploited to maximize salt tolerance, thereby mitigating growth costs. [ABSTRACT FROM AUTHOR]

Background: Gene co-expression networks (GCNs) can be used to determine gene regulation and attribute gene function to biological processes. Different high throughput technologies, including one and two-channel microarrays and RNA-sequencing, allow evaluating thousands of gene expression data simultaneously, but these methodologies provide results that cannot be directly compared. Thus, it is complex to analyze co-expression relations between genes, especially when there are missing values arising for experimental reasons. Networks are a helpful tool for studying gene co-expression, where nodes represent genes and edges represent co-expression of pairs of genes. Results: In this paper, we establish a method for constructing a gene co-expression network for the Anopheles gambiae transcriptome from 257 unique studies obtained with different methodologies and experimental designs. We introduce the sliding threshold approach to select node pairs with high Pearson correlation coefficients. The resulting network, which we name AgGCN1.0, is robust to random removal of conditions and has similar characteristics to small-world and scale-free networks. Analysis of network sub-graphs revealed that the core is largely comprised of genes that encode components of the mitochondrial respiratory chain and the ribosome, while different communities are enriched for genes involved in distinct biological processes. Conclusion: Analysis of the network reveals that both the architecture of the core sub-network and the network communities are based on gene function, supporting the power of the proposed method for GCN construction. Application of network science methodology reveals that the overall network structure is driven to maximize the integration of essential cellular functions, possibly allowing the flexibility to add novel functions. [ABSTRACT FROM AUTHOR]

Salt stress negatively impacts crop production worldwide. Genetic diversity among barley (Hordeum vulgare) landraces adapted to adverse conditions should provide a valuable reservoir of tolerance genes for breeding programs. To identify molecular and biochemical differences between barley genotypes, transcriptomic and antioxidant enzyme profiles along with several morpho-physiological features were compared between salt-tolerant (Boulifa) and salt-sensitive (Testour) genotypes subjected to salt stress. Decreases in biomass, photosynthetic parameters, and relative water content were low in Boulifa compared to Testour. Boulifa had better antioxidant protection against salt stress than Testour, with greater antioxidant enzymes activities including catalase, superoxide dismutase, and guaiacol peroxidase. Transcriptome assembly for both genotypes revealed greater accumulation of differentially expressed transcripts in Testour compared to Boulifa, emphasizing the elevated transcriptional response in Testour following salt exposure. Various salt-responsive genes, including the antioxidant catalase 3, the osmoprotectant betaine aldehyde dehydrogenase 2, and the transcription factors MYB20 and MYB41, were induced only in Boulifa. By contrast, several genes associated with photosystems I and II, and light receptor chlorophylls A and B, were more repressed in Testour. Co-expression network analysis identified specific gene modules correlating with differences in genotypes and morpho-physiological traits. Overall, salinity-induced differential transcript accumulation underlies the differential morpho-physiological response in both genotypes and could be important for breeding salt tolerance in barley. [ABSTRACT FROM AUTHOR]

NAC (NAM, ATAF1/2, and CUC2) transcription factors (TFs) are one of the largest plant-specific TF families and play a pivotal role in adaptation to abiotic stresses. The genome-wide analysis of NAC TFs is still absent in Zanthoxylum bungeanum. Here, 109 ZbNAC proteins were identified from the Z. bungeanum genome and were classified into four groups with Arabidopsis NAC proteins. The 109 ZbNAC genes were unevenly distributed on 46 chromosomes and included 4 tandem duplication events and 17 segmental duplication events. Synteny analysis of six species pairs revealed the closely phylogenetic relationship between Z. bungeanum and C. sinensis. Twenty-four types of cis-elements were identified in the ZbNAC promoters and were classified into three types: abiotic stress, plant growth and development, and response to phytohormones. Co-expression network analysis of the ZbNACs revealed 10 hub genes, and their expression levels were validated by real-time quantitative polymerase chain reaction (qRT-PCR). Finally, ZbNAC007, ZbNAC018, ZbNAC047, ZbNAC072, and ZbNAC079 were considered the pivotal NAC genes for drought tolerance in Z. bungeanum. This study represented the first genome-wide analysis of the NAC family in Z. bungeanum, improving our understanding of NAC proteins and providing useful information for molecular breeding of Z. bungeanum. [ABSTRACT FROM AUTHOR]

Glycyrrhiza uralensis (Licorice), which belongs to Leguminosae, is famous for the function of pharmacologic action and natural sweetener with its dried roots and rhizomes. In recent years, the whole-genome sequence of G. uralensis has been completed, which will help to lay the foundation for the study of gene function. Here, we integrated the available genomic and transcriptomic data of G. uralensis and constructed the G. uralensis gene co-expression network. We then annotated gene functions of G. uralensis via aligning with public databases. Furthermore, gene families of G. uralensis were predicted by tools including iTAK (Plant Transcription factor and Protein kinase Identifier and Classifier), HMMER (hidden Markov models), InParanoid, and PfamScan. Finally, we constructed a platform for gene function analysis in G. uralensis (GURFAP, www.gzybioinfoormatics.cn/GURFAP). For analyzed and predicted gene function, we introduced various tools including BLAST (Basic local alignment search tool), GSEA (Gene set enrichment analysis), Motif, Heatmap, and JBrowse. Our analysis based on this platform indicated that the biosynthesis of glycyrrhizin might be regulated by MYB and bHLH. We also took CYP88D6 , CYP72A154, and bAS gene in the synthesis pathway of glycyrrhizin as examples to demonstrate the reliability and availability of our platform. Our platform GURFAP will provide convenience for researchers to mine the gene function of G. uralensis and thus discover more key genes involved in the biosynthetic pathway of active ingredients. [ABSTRACT FROM AUTHOR]

Long non-coding RNAs (lncRNAs) may play a role in psychiatric diseases including bipolar disorder (BD). We investigated mRNA-lncRNA co-expression patterns in neuronal-like cells treated with widely prescribed BD medications. The aim was to unveil insights into the complex mechanisms of BD medications and highlight potential targets for new drug development. Human neuronal-like (NT2-N) cells were treated with either lamotrigine, lithium, quetiapine, valproate or vehicle for 24 h. Genome-wide mRNA expression was quantified for weighted gene co-expression network analysis (WGCNA) to correlate the expression levels of mRNAs with lncRNAs. Functional enrichment analysis and hub lncRNA identification was conducted on key co-expressed modules associated with the drug response. We constructed lncRNA-mRNA co-expression networks and identified key modules underlying these treatments, as well as their enriched biological functions. Processes enriched in key modules included synaptic vesicle cycle, endoplasmic reticulum-related functions and neurodevelopment. Several lncRNAs such as GAS6-AS1 and MIR100HG were highlighted as driver genes of key modules. Our study demonstrates the key role of lncRNAs in the mechanism(s) of action of BD drugs. Several lncRNAs have been suggested as major regulators of medication effects and are worthy of further investigation as novel drug targets to treat BD. [ABSTRACT FROM AUTHOR]

We evaluated differential expression of genes in leaf and xylem tissues for three Eucalyptus clones in the field using Illumina sequencing, under four contrasting fertilization regimes: a control combining nitrogen (N), phosphorus (P), and potassium (K) and three regimes with N, K, and P deficiency. The field results showed significantly better performance with a control fertilizing regime for height and circumference at 14 months, but no differences between clones. The number of up and down regulated DEG (differentially expressed genes) in pairwise clone comparisons was around 5900 for leaf and 6900 for xylem at FDR < 0.01. With fertilization treatment comparisons, DEG were only observed for N deficiency versus control with 45 up and down-regulated DEG for leaf and 1022 for xylem. The number of DEGs between fertilizer deficiency treatment and control varied greatly within each clone showing important clone by fertilization interaction. Gene ontology analysis showed that a great number of genes were related to stress, transport, and transcription factors. The co-expression analysis showed some significant correlations between complex network gene expression and tree growth induced by fertilization regime. For example, the co-expression of a 54 DEG network showed a significant correlation with tree height (0.84, P value: 1e−04) and DBH (0.89, P value: 7e−06) in the case of N deficiency versus control. Our results suggest that gene expression levels between different fertilization treatments and clones can provide a basis for future research on gene function in Eucalyptus under nutrient stress with the perspective of new development in Eucalyptus breeding. [ABSTRACT FROM AUTHOR]

Background: A comprehensive analysis of gene expression profiling across tissues can provide necessary information for an in-depth understanding of their biological functions. We performed a large-scale gene expression analysis and generated a high-resolution atlas of the transcriptome in beef cattle. Results: Our transcriptome atlas was generated from 135 bovine tissues in adult beef cattle, covering 51 tissue types of major organ systems (e.g., muscular system, digestive system, immune system, reproductive system). Approximately 94.76% of sequencing reads were successfully mapped to the reference genome assembly ARS-UCD1.2. We detected a total of 60,488 transcripts, and 32% of them were not reported before. We identified 2654 housekeeping genes (HKGs) and 477 tissue-specific genes (TSGs) across tissues. Using weighted gene co-expression network analysis, we obtained 24 modules with 237 hub genes (HUBGs). Functional enrichment analysis showed that HKGs mainly maintain the basic biological activities of cells, while TSGs were involved in tissue differentiation and specific physiological processes. HKGs in bovine tissues were more conserved in terms of expression pattern as compared to TSGs and HUBGs among multiple species. Finally, we obtained a subset of tissue-specific differentially expressed genes (DEGs) between beef and dairy cattle and several functional pathways, which may be involved in production and health traits. Conclusions: We generated a large-scale gene expression atlas across the major tissues in beef cattle, providing valuable information for enhancing genome assembly and annotation. HKGs, TSGs, and HUBGs further contribute to better understanding the biology and evolution of multiple tissues in cattle. DEGs between beef and dairy cattle also fill in the knowledge gaps about differential transcriptome regulation of bovine tissues underlying economically important traits. [ABSTRACT FROM AUTHOR]

Potassium (K) is the essential element for plant growth. It is one of the critical factors that determine crop yield, quality, and especially leaf development in tobacco. However, the molecular mechanism of potassium use efficiency (KUE), especially non-coding RNA, is still unknown. In this study, tobacco seedlings were employed, and their hydro-cultivation with K treatments of low and sufficient concentrations was engaged. Physiological analysis showed that low potassium treatment could promote malondialdehyde (MDA) accumulation and antioxidant enzyme activities such as peroxidase (POD), ascorbate-peroxidase (APX). After transcriptomic analysis, a total of 10,585 LncRNA transcripts were identified, and 242 of them were significantly differently expressed under potassium starvation. Furthermore, co-expression networks were constructed and generated 78 potential regulation modules in which coding gene and LncRNAs are involved and functional jointly. By further module-trait analysis and module membership (MM) ranking, nine modules, including 616 coding RNAs and 146 LncRNAs, showed a high correlation with K treatments, and 20 hub K-responsive LncRNAs were finally predicted. Following gene ontology (GO) analysis, the results showed potassium starvation inducing the pathway of antioxidative stress which is consistent with the physiology result mentioned above. Simultaneously, a part of detected LncRNAs, such as MSTRG.6626.1 , MSTRG.11330.1 , and MSTRG.16041.1 , were co-relating with a bench of MYB, C3H, and NFYC transcript factors in response to the stress. Overall, this research provided a set of LncRNAs that respond to K concentration from starvation and sufficient supply. Simultaneously, the regulation network and potential co-functioning genes were listed as well. This massive dataset would serve as an outstanding clue for further study in tobacco and other plant species for nutrient physiology and molecular regulation mechanism. [ABSTRACT FROM AUTHOR]

Bioremediation has been considered as a promising method for recovering chemical polluted environments. Here Shewanella decolorationis strain Ni1-3 showed versatile abilities in bioremediation. To improve the bioremediation activity, RNA polymerase (RNAP) mutations of strain Ni1-3 were screened. Eleven mutants were obtained, of which mutant #40 showed enhanced Amaranth (AMR) degradation capacity, while mutant #21 showed defected capacity in AMR degradation but greatly enhanced capacity in cathodic metal leaching which is three to four times faster than that of the wild-type (WT) strain Ni1-3, suggesting that different pathways were involved in these two processes. Transcriptional profiling and gene co-expression networks between the mutants (i.e., #40 and #22) and the WT strain disclosed that the non-CymA-Mtr but cytochrome b - and flavin-oxidoreductase-dominated azo dye degradation pathways existed in S. decolorationis , which involved key proteins TorC, TorA, YceJ, YceI, Sye4, etc. Furthermore, the involvement of TorA was verified by trimethylamine N-oxide reduction and molybdenum enzyme inhibitory experiments. This study clearly demonstrates that RNAP mutations are effective to screen active microbial candidates in bioremediation. Meanwhile, by clarifying the novel gene co-expression network of extracellular electron transfer pathways, this study provides new insights in azo dye degradation and broadens the application of Shewanella spp. in bioremediation as well. [ABSTRACT FROM AUTHOR]

Simple Summary: Hepatocellular carcinoma (HCC) is the most common malignancy of liver cancer. However, treatment of HCC is still severely limited due to limitation of drug therapy. We aimed to screen more possible target genes and candidate drugs for HCC, exploring the possibility of drug treatments from systems biological perspective. We identified ten candidate target genes, which are hub genes in HCC co-expression networks, which also possess significant prognostic value in two independent HCC cohorts. The rationality of these target genes was well demonstrated through variety analyses of patient expression profiles. We then screened candidate drugs for target genes and finally identified withaferin-a and mitoxantrone as the candidate drug for HCC treatment. The drug effectiveness was validated in in vitro model and computational analysis, providing more evidence for our drug repositioning method and results. Hepatocellular carcinoma (HCC) is a malignant liver cancer that continues to increase deaths worldwide owing to limited therapies and treatments. Computational drug repurposing is a promising strategy to discover potential indications of existing drugs. In this study, we present a systematic drug repositioning method based on comprehensive integration of molecular signatures in liver cancer tissue and cell lines. First, we identify robust prognostic genes and two gene co-expression modules enriched in unfavorable prognostic genes based on two independent HCC cohorts, which showed great consistency in functional and network topology. Then, we screen 10 genes as potential target genes for HCC on the bias of network topology analysis in these two modules. Further, we perform a drug repositioning method by integrating the shRNA and drug perturbation of liver cancer cell lines and identifying potential drugs for every target gene. Finally, we evaluate the effects of the candidate drugs through an in vitro model and observe that two identified drugs inhibited the protein levels of their corresponding target genes and cell migration, also showing great binding affinity in protein docking analysis. Our study demonstrates the usefulness and efficiency of network-based drug repositioning approach to discover potential drugs for cancer treatment and precision medicine approach. [ABSTRACT FROM AUTHOR]

Sensorineural hearing loss (SNHL) is referred to as the most common type of hearing loss and typically occurs when the inner ear or the auditory nerve is damaged. Aging, noise exposure, and ototoxic drugs represent three main causes of SNHL, leading to substantial similarities in pathophysiological characteristics of cochlear degeneration. Although the common molecular mechanisms are widely assumed to underlie these similarities, its validity lacks systematic examination. To address this question, we generated three SNHL mouse models from aging, noise exposure, and cisplatin ototoxicity, respectively. Through constructing gene co-expression networks for the cochlear transcriptome data across different hearing-damaged stages, the three models are found to significantly correlate with each other in multiple gene co-expression modules that implicate distinct biological functions, including apoptosis, immune, inflammation, and ion transport. Bioinformatics analyses reveal several potential hub regulators, such as IL1B and CCL2 , both of which are verified to contribute to apoptosis accompanied by the increase of (ROS) in in vitro model system. Our findings disentangle the shared molecular circuits across different types of SNHL, providing potential targets for the broad effective therapeutic agents in SNHL. [ABSTRACT FROM AUTHOR]

Despite the important role the circadian clock plays in numerous critical physiological responses in plants, such as hypocotyl elongation, leaf movement, stomatal opening, flowering, and stress responses, there have been no investigations into the effect of the circadian clock on physiological and transcriptional networks under salt stress. Ulmus pumila L. has been reported to tolerate 100–150 mM NaCl treatment. We measured the diurnal variation in photosynthesis and chlorophyll fluorescence parameters and performed a time-course transcriptome analysis of 2-years-old U. pumila seedlings under salt treatment to dissect the physiological regulation and potential relationship between the circadian network and the salt stress response. Seedlings in 150 mM NaCl treatment exhibited salt-induced physiological enhancement compared to the control group. A total of 7009 differentially expressed unigenes (DEGs) were identified under salt stress, of which 16 DEGs were identified as circadian rhythm-related DEGs (crDEGs). Further analysis of dynamic expression changes revealed that DEGs involved in four crucial pathways—photosynthesis, thiamine metabolism, abscisic acid synthesis and metabolism, and the hormone-MAPK signal crosstalk pathway—are closely related to the circadian clock. Finally, we constructed a co-expression network between the circadian clock and these four crucial pathways. Our results help shed light on the molecular link between the circadian network and salt stress tolerance in U. pumila. [ABSTRACT FROM AUTHOR]

The inference of gene co-expression associations is one of the fundamental tasks for large-scale transcriptomic data analysis. Due to the high dimensionality and high noises in transcriptomic data, it is difficult to infer stable gene co-expression associations from single dataset. Meta-analysis of multisource data can effectively tackle this problem. We proposed Joint Embedding of multiple BIpartite Networks (JEBIN) to learn the low-dimensional consensus representation for genes by integrating multiple expression datasets. JEBIN infers gene co-expression associations in a nonlinear and global similarity manner and can integrate datasets with different distributions in linear time complexity with the gene and total sample size. The effectiveness and scalability of JEBIN were verified by simulation experiments, and its superiority over the commonly used integration methods was proved by three indexes on real biological datasets. Then, JEBIN was applied to study the gene co-expression patterns of hepatocellular carcinoma (HCC) based on multiple expression datasets of HCC and adjacent normal tissues, and further on latest HCC single-cell RNA-seq data. Results show that gene co-expressions are highly different between bulk and single-cell datasets. Finally, many differentially co-expressed ligand–receptor pairs were discovered by comparing HCC with adjacent normal data, providing candidate HCC targets for abnormal cell–cell communications. [ABSTRACT FROM AUTHOR]

Several species in Brassicaceae produce glucosinolates (GSLs) to protect themselves against pests. As demonstrated in A. thaliana, the reallocation of defence compounds, of which GSLs are a major part, is highly dependent on transport processes and serves to protect high-value tissues such as reproductive tissues. This study aimed to identify potential GSL-transporter proteins (TPs) using a network-biology approach. The known A. thaliana GSL genes were retrieved from the literature and pathway databases and searched against several co-expression databases to generate a gene network consisting of 1267 nodes and 14,308 edges. In addition, 1151 co-expressed genes were annotated, integrated, and visualised using relevant bioinformatic tools. Based on three criteria, 21 potential GSL genes encoding TPs were selected. The AST68 and ABCG40 potential GSL TPs were chosen for further investigation because their subcellular localisation is similar to that of known GSL TPs (SULTR1;1 and SULTR1;2) and ABCG36, respectively. However, AST68 was selected for a molecular-docking analysis using AutoDOCK Vina and AutoDOCK 4.2 with the generated 3D model, showing that both domains were well superimposed on the homologs. Both molecular-docking tools calculated good binding-energy values between the sulphate ion and Ser419 and Val172, with the formation of hydrogen bonds and van der Waals interactions, respectively, suggesting that AST68 was one of the sulphate transporters involved in GSL biosynthesis. This finding illustrates the ability to use computational analysis on gene co-expression data to screen and characterise plant TPs on a large scale to comprehensively elucidate GSL metabolism in A. thaliana. Most importantly, newly identified potential GSL transporters can serve as molecular tools in improving the nutritional value of crops. [ABSTRACT FROM AUTHOR]

SUMMARY: Plants cope with low phosphorus availability by adjusting growth and metabolism through transcriptomic and proteomic adaptations. We hypothesize that selected genotypes with distinct phosphorous (P) use efficiency covering the breeding history of European Flint heterotic pool provide a tool to reveal general and genotype‐specific molecular responses to P limitation. We reconstructed protein and gene co‐expression networks by weighted correlation network analysis and related these to phosphate deficiency‐induced traits. In roots, low phosphate supply resulted in a decreasing abundance of proteins in the oxidative pentose phosphate pathway and a negative correlation with root and shoot phosphate content. We observed an increase in abundance and positive correlation with root and shoot phosphate content for proteins in sucrose biosynthesis, lipid metabolism, respiration and RNA processing. Purple acid phosphatases, superoxide dismutase and phenylalanine ammonia lyase were identified as being upregulated under low phosphate in all genotypes. Overall, correlations between protein and mRNA abundance changes were limited, with ribosomal proteins and the ubiquitin protein degradation pathway exclusively responding with protein abundance changes. Carbohydrate, phospho‐ and sulfo‐lipid metabolism showed abundance changes at the protein and mRNA levels. These partially non‐overlapping proteomic and transcriptomic adjustments to low phosphate suggest sugar and lipid metabolism as metabolic processes associated with improved P use efficiency specifically in Founder Flint lines. We identified a mitogen‐activated protein kinase‐kinase as a potential genotype‐specific regulator of sucrose metabolism at low phosphate in Founder Flint line EP1. We conclude that, during breedingt of Elite Flint lines, regulation of primary metabolism has changed to result in a distinct low phosphate response in Founder lines. Significance Statement: We reconstructed protein and transcript co‐expression networks in Flint maize lines and related them to phosphate deficiency‐induced traits. Post‐translational regulation was found with protein synthesis and protein degradation, transcriptional and post‐transcriptional regulation was found with metabolic processes. MKK6 homolog was proposed as a genotype‐specific regulator for carbohydrate metabolism and protein synthesis processes. [ABSTRACT FROM AUTHOR]

Abstract Background Major depressive disorder (MDD) is a leading psychiatric disorder that involves complex abnormal biological functions and neural networks. This study aimed to compare the changes in the network connectivity of different brain tissues under different pathological conditions, analyzed the biological pathways and genes that are significantly related to disease progression, and further predicted the potential therapeutic drug targets. Methods Expression of differentially expressed genes (DEGs) were analyzed with postmortem cingulate cortex (ACC) and prefrontal cortex (PFC) mRNA expression profile datasets downloaded from the Gene Expression Omnibus (GEO) database, including 76 MDD patients and 76 healthy subjects in ACC and 63 MDD patients and 63 healthy subjects in PFC. The co-expression network construction was based on system network analysis. The function of the genes was annotated by Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. Human Protein Reference Database (HPRD, http://www.hprd.org/ ) was used for gene interaction relationship mapping. Results We filtered 586 DEGs in ACC and 616 DEGs in PFC for further analysis. By constructing the co-expression network, we found that the gene connectivity was significantly reduced under disease conditions (P = 0.04 in PFC and P = 1.227e−09 in ACC). Crosstalk analysis showed that CD19, PTDSS2 and NDST2 were significantly differentially expressed in ACC and PFC of MDD patients. Among them, CD19 and PTDSS2 have been targeted by several drugs in the Drugbank database. KEGG pathway analysis demonstrated that the function of CD19 and PTDSS2 were enriched with the pathway of Glycerophospholipid metabolism and T cell receptor signaling pathway. Conclusion Co-expression network and tissue comparing analysis can identify signaling pathways and cross talk genes related to MDD, which may provide novel insight for understanding the molecular mechanisms of MDD.

Abstract Background The sequencing and annotations of cotton genomes provide powerful theoretical support to unravel more physiological and functional information. Plant homeodomain (PHD) protein family has been reported to be involved in regulating various biological processes in plants. However, their functional studies have not yet been carried out in cotton. Results In this study, 108, 55, and 52 PHD genes were identified in G. hirsutum, G. raimondii, and G. arboreum, respectively. A total of 297 PHD genes from three cotton species, Arabidopsis, and rice were divided into five groups. We performed chromosomal location, phylogenetic relationship, gene structure, and conserved domain analysis for GhPHD genes. GhPHD genes were unevenly distributed on each chromosome. However, more GhPHD genes were distributed on At_05, Dt_05, and At_07 chromosomes. GhPHD proteins depicted conserved domains, and GhPHD genes exhibiting similar gene structure were clustered together. Further, whole genome duplication (WGD) analysis indicated that purification selection greatly contributed to the functional maintenance of GhPHD gene family. Expression pattern analysis based on RNA-seq data showed that most GhPHD genes showed clear tissue-specific spatiotemporal expression patterns elucidating the multiple functions of GhPHDs in plant growth and development. Moreover, analysis of cis-acting elements revealed that GhPHDs may respond to a variety of abiotic and phytohormonal stresses. In this regard, some GhPHD genes showed good response against abiotic and phytohormonal stresses. Additionally, co-expression network analysis indicated that GhPHDs are essential for plant growth and development, while GhPHD genes response against abiotic and phytohormonal stresses may help to improve plant tolerance in adverse environmental conditions. Conclusion This study will provide useful information to facilitate further research related to the vital roles of GhPHD gene family in plant growth and development.

Abstract Background Presently, there is no comprehensive analysis of the transcription regulation network in hematopoiesis. Comparison of networks arising from gene co-expression across species can facilitate an understanding of the conservation of functional gene modules in hematopoiesis. Results We used single-cell RNA sequencing to profile bone marrow from human and mouse, and inferred transcription regulatory networks in each species in order to characterize transcriptional programs governing hematopoietic stem cell differentiation. We designed an algorithm for network reconstruction to conduct comparative transcriptomic analysis of hematopoietic gene co-expression and transcription regulation in human and mouse bone marrow cells. Co-expression network connectivity of hematopoiesis-related genes was found to be well conserved between mouse and human. The co-expression network showed “small-world” and “scale-free” architecture. The gene regulatory network formed a hierarchical structure, and hematopoiesis transcription factors localized to the hierarchy’s middle level. Conclusions Transcriptional regulatory networks are well conserved between human and mouse. The hierarchical organization of transcription factors may provide insights into hematopoietic cell lineage commitment, and to signal processing, cell survival and disease initiation.

Summary: Background: The response rates of the clinical chemotherapies are still low in clear cell renal cell carcinoma (ccRCC). Computational drug repositioning is a promising strategy to discover new uses for existing drugs to treat patients who cannot get benefits from clinical drugs. Methods: We proposed a systematic approach which included the target prediction based on the co-expression network analysis of transcriptomics profiles of ccRCC patients and drug repositioning for cancer treatment based on the analysis of shRNA- and drug-perturbed signature profiles of human kidney cell line. Findings: First, based on the gene co-expression network analysis, we identified two types of gene modules in ccRCC, which significantly enriched with unfavorable and favorable signatures indicating poor and good survival outcomes of patients, respectively. Then, we selected four genes, BUB1B, RRM2, ASF1B and CCNB2, as the potential drug targets based on the topology analysis of modules. Further, we repurposed three most effective drugs for each target by applying the proposed drug repositioning approach. Finally, we evaluated the effects of repurposed drugs using an in vitro model and observed that these drugs inhibited the protein levels of their corresponding target genes and cell viability. Interpretation: These findings proved the usefulness and efficiency of our approach to improve the drug repositioning researches for cancer treatment and precision medicine. Funding: This study was funded by Knut and Alice Wallenberg Foundation and Bash Biotech Inc., San Diego, CA, USA.