Weighted Gene Co-expression Analysis Research Articles

Transcriptome analysis highlights the influence of temperature on hydrolase and traps in nematode-trapping fungi

Pine wilt disease caused by Bursaphelenchus xylophilus poses a serious threat to the economic and ecological value of forestry. Nematode trapping fungi trap and kill nematodes using specialized trapping devices, which are highly efficient and non-toxic to the environment, and are very promising for use as biological control agents. In this study, we isolated several nematode-trapping fungi from various regions and screened three for their high nematocidal efficiency. However, the effectiveness of these fungi as nematicides is notably influenced by temperature and exhibits different morphologies in response to temperature fluctuations, which are categorized as “NA,” “thin,” “dense,” and “sparse.” The trend of trap formation with temperature was consistent with the trend of nematocidal efficiency with temperature. Both of which initially increased and then decreased with increasing temperature. Among them, Arthrobotrys cladodes exhibited the highest level of nematocidal activity and trap formation among the tested species. Transcriptome data were collected from A. cladodes with various trap morphologies. Hydrolase activity was significantly enriched according to GO and KEGG enrichment analyses. Eight genes related to hydrolases were found to be consistent with the trend of trap morphology with temperature. Weighted gene co-expression analysis and the Cytoscape network revealed that these 8 genes are associated with either mitosis or autophagy. This suggests that they contribute to the formation of “dense” structures in nematode-trapping fungi. One of these genes is the serine protein hydrolase gene involved in autophagy. This study reveals a potentially critical role for hydrolases in trap formation and nematocidal efficiency. And presents a model where temperature affects trap formation and nematocidal efficiency by influencing the serine protease prb1 involved in the autophagy process.

Early life adversity is associated with differential gene expression in immune cells: A cluster-based analysis across an acute psychosocial stressor

Elucidating mechanisms by which early-life adversity (ELA) contributes to increased disease risk is important for mitigating adverse health outcomes. Prior work has found differences in immune cell gene expression related to inflammation and mitochondrial activity. Using a within-person between-group experimental design, we investigated differences in gene expression clusters across acute psychosocial stress and no-stress conditions. Participants were young adults (N = 29, aged 18 – 25 years, 62 % female, 47 % with a history of ELA). Gene expression was assessed in peripheral blood mononuclear cells collected at 8 blood draws spanning two 5-hour sessions (stress vs. no-stress) separated by a week, 4 across each session (number of observations = 221). We applied two unsupervised gene clustering methods – latent profile analysis (LPA) and weighted gene co-expression analysis (WGCNA) – to cluster genes with similar expression patterns across participants. LPA identified 11 clusters, 7 of which were significantly associated with ELA-status. WGCNA identified 5 clusters, 3 of which were significantly associated with ELA-status. LPA- and WGCNA-identified clusters were correlated, and all clusters were highly preserved across sessions and time. There was no significant effect of acute stress on cluster gene expression, but there was a significant effect of time, and significant differences by ELA-status. ELA-associated clusters related to RNA splicing/processing, inflammation, leukocyte differentiation and division, and mitochondrial activity were differentially expressed across time: ELA-exposed individuals showed decreased expression of these clusters at 90-minutes while controls showed increased expression. Our findings replicate previous work in this area and highlight additional mechanisms by which ELA may contribute to disease risk.

Unraveling the Heterogeneity of CD8+ T-Cell Subsets in Liver Cirrhosis: Implications for Disease Progression.

: Liver cirrhosis involves chronic inflammation and progressive fibrosis. Among various immune cells, CD8+ T cells are considered a major contributor to hepatic inflammation and fibrosis. However, the exact molecular pathways governing CD8+ T-cell-mediated effects in cirrhosis remain unclear. : This study analyzed transcriptomic and single-cell sequencing data to elucidate CD8+ T-cell heterogeneity and implications in cirrhosis. : Weighted gene co-expression analysis of bulk RNA-seq data revealed an association between cirrhosis severity and activated T-cell markers like HLA and chemokine genes. Furthermore, single-cell profiling uncovered eight CD8+ T-cell subtypes, notably, effector memory (Tem) and exhausted (Tex) T cells. Tex cells, defined by PDCD1, LAG3, and CXCL13 expression, were increased in cirrhosis, while Tem cells were decreased. Lineage tracing and differential analysis highlighted CXCL13+ Tex cells as a terminal, exhausted subtype of cells with roles in PD-1 signaling, glycolysis, and T-cell regulation. CXCL13+ Tex cells displayed T-cell exhaustion markers like PDCD1, HAVCR2, TIGIT, and TNFRSF9. Functional analysis implicated potential roles of these cells in immunosuppression. Finally, a CXCL13+ Tex-cell gene signature was found that correlated with cirrhosis severity and poorer prognosis of liver cancer. : In summary, this comprehensive study defines specialized CD8+ T-cell subpopulations in cirrhosis, with CXCL13+ Tex cells displaying an exhausted phenotype associated with immune dysregulation and advanced disease. Key genes and pathways regulating these cells present potential therapeutic targets.

Accumulation mechanism of metabolite markers identified by machine learning between Qingyuan and Xiushui counties in Polygonatum cyrtonema Hua

Polygonatum cyrtonema Hua is a traditional Chinese medicinal plant acclaimed for its therapeutic potential in diabetes and various chronic diseases. Its rhizomes are the main functional parts rich in secondary metabolites, such as flavonoids and saponins. But their quality varies by region, posing challenges for industrial and medicinal application of P. cyrtonema. In this study, 482 metabolites were identified in P. cyrtonema rhizome from Qingyuan and Xiushui counties. Cluster analysis showed that samples between these two regions had distinct secondary metabolite profiles. Machine learning methods, specifically support vector machine-recursive feature elimination and random forest, were utilized to further identify metabolite markers including flavonoids, phenolic acids, and lignans. Comparative transcriptomics and weighted gene co-expression analysis were performed to uncover potential candidate genes including CHI, UGT1, and PcOMT10/11/12/13 associated with these compounds. Functional assays using tobacco transient expression system revealed that PcOMT10/11/12/13 indeed impacted metabolic fluxes of the phenylpropanoid pathway and phenylpropanoid-related metabolites such as chrysoeriol-6,8-di-C-glucoside, syringaresinol-4'-O-glucopyranosid, and 1-O-Sinapoyl-D-glucose. These findings identified metabolite markers between these two regions and provided valuable genetic insights for engineering the biosynthesis of these compounds.

Lysosome-related biomarkers in preeclampsia and cancers: Machine learning and bioinformatics analysis

BackgroundLysosomes serve as regulatory hubs, and play a pivotal role in human diseases. However, the precise functions and mechanisms of action of lysosome-related genes remain unclear in preeclampsia and cancers. This study aimed to identify lysosome-related biomarkers in preeclampsia, and further explore the biomarkers shared between preeclampsia and cancers. Materials and methodsWe obtained GSE60438 and GSE75010 datasets from the Gene Expression Omnibus database, pre-procesed them and merged them into a training cohort. The limma package in R was used to identify the differentially expressed mRNAs between the preeclampsia and normal control groups. Differentially expressed lysosome-related genes were identified by intersecting the differentially expressed mRNAs and lysosome-related genes obtained from Gene Ontology and GSEA databases. Gene Ontology annotations and Kyoto Encyclopedia of Genes and Genomes enrichment analysis were performed using the DAVID database. The CIBERSORT method was used to analyze immune cell infiltration. Weighted gene co-expression analyses and three machine learning algorithm were used to identify lysosome-related diagnostic biomarkers. Lysosome-related diagnostic biomarkers were further validated in the testing cohort GSE25906. Nomogram diagnostic models for preeclampsia were constructed. In addition, pan-cancer analysis of lysosome-related diagnostic biomarkers were identified by was performed using the TIMER, Sangebox and TISIDB databases. Finally, the Drug-Gene Interaction, TheMarker and DSigDB Databases were used for drug-gene interactions analysis. ResultsA total of 11 differentially expressed lysosome-related genes were identified between the preeclampsia and control groups. Three molecular clusters connected to lysosome were identified, and enrichment analysis demonstrated their strong relevance to the development and progression of preeclampsia. Immune infiltration analysis revealed significant immunity heterogeneity among different clusters. GBA, OCRL, TLR7 and HEXB were identified as lysosome-related diagnostic biomarkers with high AUC values, and validated in the testing cohort GSE25906. Nomogram, calibration curve, and decision curve analysis confirmed the accuracy of predicting the occurrence of preeclampsia based on OCRL and HEXB. Pan-cancer analysis showed that GBA, OCRL, TLR7 and HEXB were associated with the prognosis of patients with various tumors and tumor immune cell infiltration. Twelve drugs were identified as potential drugs for the treatment of preeclampsia and cancers. ConclusionThis study identified GBA, OCRL, TLR7 and HEXB as potential lysosome-related diagnostic biomarkers shared between preeclampsia and cancers.

Spatiotemporal transcriptomic plasticity in barley roots: unravelling water deficit responses in distinct root zones

BackgroundDrought poses a major threat to agricultural production and thus food security. Understanding the processes shaping plant responses to water deficit is essential for global food safety. Though many studies examined the effect of water deficit on the whole-root level, the distinct functions of each root zone and their specific stress responses remain masked by this approach.ResultsIn this study, we investigated the effect of water deficit on root development of the spring barley (Hordeum vulgare L.) cultivar Morex and examined transcriptomic responses at the level of longitudinal root zones. Water deficit significantly reduced root growth rates after two days of treatment. RNA-sequencing revealed root zone and temporal gene expression changes depending on the duration of water deficit treatment. The majority of water deficit-regulated genes were unique for their respective root zone-by-treatment combination, though they were associated with commonly enriched gene ontology terms. Among these, we found terms associated with transport, detoxification, or cell wall formation affected by water deficit. Integration of weighted gene co-expression analyses identified differential hub genes, that highlighted the importance of modulating energy and protein metabolism and stress response.ConclusionOur findings provide new insights into the highly dynamic and spatiotemporal response cascade triggered by water deficit and the underlying genetic regulations on the level of root zones in the barley cultivar Morex, providing potential targets to enhance plant resilience against environmental constraints. This study further emphasizes the importance of considering spatial and temporal resolution when examining stress responses.

Triosephosphate isomerase 1 may be a risk predictor in laryngeal squamous cell carcinoma: a multi-centered study integrating bulk RNA, single-cell RNA, and protein immunohistochemistry

BackgroundAlthough great progress has been made in anti-cancer therapy, the prognosis of laryngeal squamous cell carcinoma (LSCC) patients remains unsatisfied. Quantities of studies demonstrate that glycolytic reprograming is essential for the progression of cancers, where triosephosphate isomerase 1 (TPI1) serves as a catalytic enzyme. However, the clinicopathological significance and potential biological functions of TPI1 underlying LSCC remains obscure.MethodsWe collected in-house 82 LSCC tissue specimens and 56 non-tumor tissue specimens. Tissue microarrays (TMA) and immunohistochemical (IHC) experiments were performed. External LSCC microarrays and bulk RNA sequencing data were integrated to evaluate the expression of TPI1. We used a log-rank test and the CIBERSORT algorithm to assess the prognostic value of TPI1 and its association with the LSCC microenvironment. Malignant laryngeal epithelial cells and immune-stromal cells were identified using inferCNV and CellTypist. We conducted a comprehensive analysis to elucidate the molecular functions of TPI1 in LSCC tissue and single cells using Pearson correlation analysis, high dimensional weighted gene co-expression analysis, gene set enrichment analysis, and clustered regularly interspaced short palindromic repeats (CRISPR) screen. We explored intercellular communication patterns between LSCC single cells and immune-stromal cells and predicted several therapeutic agents targeting TPI1.ResultsBased on the in-house TMA and IHC analysis, TPI1 protein was found to have a strong positive expression in the nucleus of LSCC cells but only weakly positive activity in the cytoplasm of normal laryngeal cells (p < 0.0001). Further confirmation of elevated TPI1 mRNA expression was obtained from external datasets, comparing 251 LSCC tissue samples to 136 non-LSCC tissue samples (standardized mean difference = 1.06). The upregulated TPI1 mRNA demonstrated a high discriminative ability between LSCC and non-LSCC tissue (area under the curve = 0.91; sensitivity = 0.87; specificity = 0.79), suggesting its potential as a predictive marker for poor prognosis (p = 0.037). Lower infiltration abundance was found for plasma cells, naïve B cells, monocytes, and neutrophils in TPI-high expression LSCC tissue. Glycolysis and cell cycle were significantly enriched pathways for both LSCC tissue and single cells, where heat shock protein family B member 1, TPI1, and enolase 1 occupied a central position. Four outgoing communication patterns and two incoming communication patterns were identified from the intercellular communication networks. TPI1 was predicted as an oncogene in LSCC, with CRISPR scores less than -1 across 71.43% of the LSCC cell lines. TPI1 was positively correlated with the half maximal inhibitory concentration of gemcitabine and cladribine.ConclusionsTPI1 is dramatically overexpressed in LSCC than in normal tissue, and the high expression of TPI1 may promote LSCC deterioration through its metabolic and non-metabolic functions. This study contributes to advancing our knowledge of LSCC pathogenesis and may have implications for the development of targeted therapies in the future.

Co-Expression Network Analysis of the Transcriptome Identified Hub Genes and Pathways Responding to Saline–Alkaline Stress in Sorghum bicolor L.

Soil salinization, an intractable problem, is becoming increasingly serious and threatening fragile natural ecosystems and even the security of human food supplies. Sorghum (Sorghum bicolor L.) is one of the main crops growing in salinized soil. However, the tolerance mechanisms of sorghum to saline–alkaline soil are still ambiguous. In this study, RNA sequencing was carried out to explore the gene expression profiles of sorghum treated with sodium bicarbonate (150 mM, pH = 8.0, treated for 0, 6, 12 and 24 h). The results show that 6045, 5122, 6804, 7978, 8080 and 12,899 differentially expressed genes (DEGs) were detected in shoots and roots after 6, 12 and 24 h treatments, respectively. GO, KEGG and weighted gene co-expression analyses indicate that the DEGs generated by saline–alkaline stress were primarily enriched in plant hormone signal transduction, the MAPK signaling pathway, starch and sucrose metabolism, glutathione metabolism and phenylpropanoid biosynthesis. Key pathway and hub genes (TPP1, WRKY61, YSL1 and NHX7) are mainly related to intracellular ion transport and lignin synthesis. The molecular and physiological regulation processes of saline–alkali-tolerant sorghum are shown by these results, which also provide useful knowledge for improving sorghum yield and quality under saline–alkaline conditions.

Exploring the role of the disulfidptosis-related gene SLC7A11 in adrenocortical carcinoma: implications for prognosis, immune infiltration, and therapeutic strategies

BackgroundDisulfidptosis and the disulfidptosis-related gene SLC7A11 have recently attracted significant attention for their role in tumorigenesis and tumour management. However, its association with adrenocortical carcinoma (ACC) is rarely discussed.MethodsDifferential analysis, Cox regression analysis, and survival analysis were used to screen for the hub gene SLC7A11 in the TCGA and GTEx databases and disulfidptosis-related gene sets. Then, we performed an association analysis between SLC7A11 and clinically relevant factors in ACC patients. Univariate and multivariate Cox regression analyses were performed to evaluate the prognostic value of SLC7A11 and clinically relevant factors. Weighted gene coexpression analysis was used to find genes associated with SLC7A11. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses and the LinkedOmics database were used to analyse the functions of SLC7A11-associated genes. The CIBERSORT and Xcell algorithms were used to analyse the relationship between SLC7A11 and immune cell infiltration in ACC. The TISIDB database was applied to search for the correlation between SLC7A11 expression and immune chemokines. In addition, we performed a correlation analysis for SLC7A11 expression and tumour mutational burden and immune checkpoint-related genes and assessed drug sensitivity based on SLC7A11 expression. Immunohistochemistry and RT‒qPCR were used to validate the upregulation of SLC7A11 in the ACC.ResultsSLC7A11 is highly expressed in multiple urological tumours, including ACC. SLC7A11 expression is strongly associated with clinically relevant factors (M-stage and MYL6 expression) in ACC. SLC7A11 and the constructed nomogram can accurately predict ACC patient outcomes. The functions of SLC7A11 and its closely related genes are tightly associated with the occurrence of disulfidptosis in ACC. SLC7A11 expression was tightly associated with various immune cell infiltration disorders in the ACC tumour microenvironment (TME). It was positively correlated with the expression of immune chemokines (CXCL8, CXCL3, and CCL20) and negatively correlated with the expression of immune chemokines (CXCL17 and CCL14). SLC7A11 expression was positively associated with the expression of immune checkpoint genes (NRP1, TNFSF4, TNFRSF9, and CD276) and tumour mutation burden. The expression level of SLC7A11 in ACC patients is closely associated withcthe drug sensitivity.ConclusionIn ACC, high expression of SLC7A11 is associated with migration, invasion, drug sensitivity, immune infiltration disorders, and poor prognosis, and its induction of disulfidptosis is a promising target for the treatment of ACC.

Metabolome and Transcriptome Analyses Provide Insights into Glucosinolate Accumulation in the Novel Vegetable Crop Cardamine violifolia

Cardamine violifolia, a species belonging to the Brassicaceae family, is a novel vegetable crop that is rich in glucosinolates. However, the specific glucosinolate profiles in this species remain unknown. In the present study, four parts of C. violifolia were collected including central leaves (CLs), outer leaves (OLs), petiole (P), and root (R). The highest level of total glucosinolate was observed in the R. A total of 19 glucosinolates were found in C. violifolia. The predominant glucosinolate compounds were 3-methylbutyl glucosinolate, 6-methylsulfinylhexyl glucosinolate, Indol-3-ylmethyl glucosinolate, 4-methoxyglucobrassicin, and neoglucobrassicin. A transcriptome analysis showed that 16 genes, including BCAT1, BCAT3-6, CYP79A2, CYP79B2-3, CYP83A1, CYP83B1, and SOT17-18, and nine metabolites, such as valine, tryptophan, and 1-methylpropyl glucosinolate, were enriched in the glucosinolate biosynthesis pathway. These genes may be involved in the regulation of glucosinolate accumulation among the four parts. A weighted gene co-expression analysis showed that five genes were predicted to regulate glucosinolate accumulation, including ABC transporter G family member 19, 3-ketoacyl-CoA synthase 19, and pyruvate decarboxylase 1. This study deepens our understanding of the nutrient quality of C. violifolia and provides insights into the regulatory mechanism of glucosinolate accumulation in C. violifolia.

Epigenetic responses to rhinovirus exposure in airway epithelial cells are correlated with key transcriptional pathways in chronic rhinosinusitis.

Viruses may drive immune mechanisms responsible for chronic rhinosinusitis with nasal polyposis (CRSwNP), but little is known about the underlying molecular mechanisms. To identify epigenetic and transcriptional responses to a common upper respiratory pathogen, rhinovirus (RV), that are specific to patients with CRSwNP using a primary sinonasal epithelial cell culture model. Airway epithelial cells were collected at surgery from patients with CRSwNP (cases) and from controls without sinus disease, cultured, and then exposed to RV or vehicle for 48 h. Differential gene expression and DNA methylation (DNAm) between cases and controls in response to RV were determined using linear mixed models. Weighted gene co-expression analysis (WGCNA) was used to identify (a) co-regulated gene expression and DNAm signatures, and (b) genes, pathways, and regulatory mechanisms specific to CRSwNP. We identified 5585 differential transcriptional and 261 DNAm responses (FDR <0.10) to RV between CRSwNP cases and controls. These differential responses formed three co-expression/co-methylation modules that were related to CRSwNP and three that were related to RV (Bonferroni corrected p < .01). Most (95%) of the differentially methylated CpGs (DMCs) were in modules related to CRSwNP, whereas the differentially expressed genes (DEGs) were more equally distributed between the CRSwNP- and RV-related modules. Genes in the CRSwNP-related modules were enriched in known CRS and/or viral response immune pathways. RV activates specific epigenetic programs and correlated transcriptional networks in the sinonasal epithelium of individuals with CRSwNP. These novel observations suggest epigenetic signatures specific to patients with CRSwNP modulate response to viral pathogens at the mucosal environmental interface. Determining how viral response pathways are involved in epithelial inflammation in CRSwNP could lead to therapeutic targets for this burdensome airway disorder.

Reprogramming astrocytic NDRG2/NF-κB/C3 signaling restores the diabetes-associated cognitive dysfunction.

Dementia is a serious complication in patients with diabetes-associated cognitive dysfunction (DACD). In this study, we aim to explore the protective effect of exercise on DACD in diabetic mice, and the role of NDRG2 as a potential guarder for reversing the pathological structure of neuronal synapses. Seven weeks of standardized exercise at moderate intensity was carried out using an animal treadmill in the vehicle+Run and STZ+Run groups. Based on quantitative transcriptome and tandem mass tag (TMT) proteome sequencing, weighted gene co-expression analysis (WGCNA) and gene set enrichment analysis (GSEA) were used to investigate the activation of complement cascades to injury neuronal synaptic plasticity. Golgi staining, Western blotting, immunofluorescence staining, and electrophysiology were used to verify the reliability of sequencing data. The role of NDRG2 was assessed by overexpressing or inhibiting the NDRG2 gene invivo. Moreover, we estimated the cognitive function in diabetic or normal patients using DSST scores. Exercise reversed the injury of neuronal synaptic plasticity and the downregulation of astrocytic NDRG2 in diabetic mice, which succeeded in attenuating DACD. The deficiency of NDRG2 aggravated the activation of complement C3 by accelerating the phosphorylation of NF-κB, ultimately leading to synaptic injury and cognitive dysfunction. Conversely, the overexpression of NDRG2 promoted astrocytic remodeling by inhibiting complement C3, thus attenuating synaptic injury and cognitive dysfunction. Meanwhile, C3aR blockade rescued dendritic spines loss and cognitive deficits in diabetic mice. Moreover, the average DSST score of diabetic patients was significantly lower than that of non-diabetic peers. Levels of complement C3 in human serum were elevated in diabetic patients compared to those in non-diabetic patients. Our findings illustrate the effectiveness and integrative mechanism of NDRG2-induced improvement of cognition from a multi-omics perspective. Additionally, they confirm that the expression of NDRG2 is closely related to cognitive function in diabetic mice and the activation of complement cascades accelerated impairment of neuronal synaptic plasticity. NDRG2 acts as a regulator of astrocytic-neuronal interaction via NF-κB/C3/C3aR signaling to restore synaptic function in diabetic mice. This study was supported by the National Natural Science Foundation of China (No. 81974540, 81801899, 81971290), the Key Research and Development Program of Shaanxi (Program No. 2022ZDLSF02-09) and Fundamental Research Funds for the Central Universities (Grant No. xzy022019020).

Identification of molecular subgroups in osteomyelitis induced by staphylococcus aureus infection through gene expression profiles

BackgroundStaphylococcus aureus (S. aureus) infection-induced osteomyelitis (OM) is an inflammatory bone disease accompanied by persistent bone destruction, and the treatment is challenging because of its tendency to recur. Present study was aimed to explore the molecular subgroups of S. aureus infection-induced OM and to deepen the mechanistic understanding for molecularly targeted treatment of OM.MethodsIntegration of 164 OM samples and 60 healthy samples from three datasets of the Gene Expression Omnibus (GEO) database. OM patients were classified into different molecular subgroups based on unsupervised algorithms and correlations of clinical characteristics between subgroups were analyzed. Next, The CIBERSORT algorithm was used to evaluate the proportion of immune cell infiltration in different OM subgroups. Weighted gene co-expression analysis (WGCNA) was used to identify different gene modules and explore the relationship with clinical characteristics, and further annotated OM subgroups and gene modules by the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis.ResultsTwo subgroups with excellent consistency were identified in this study, subgroup and hospital length of stay were independent predictors of OM. Compared with subgroup I, OM patients in subgroup II had longer hospital length of stay and more severe disease. Meanwhile, the infiltration proportions of monocytes and macrophages M0 were higher in patients of OM subgroup II. Finally, combined with the characteristics of the KEGG enrichment modules, the expression of osteoclast differentiation-related genes such as CTSK was upregulated in OM subgroup II, which may be closely associated with more severe OM patients.ConclusionThe current study showed that OM subgroup II had longer hospital length of stay and more severe disease, the osteoclast differentiation pathway and the main target CTSK contribute to our deeper understanding for the molecular mechanisms associated with S. aureus infection-induced OM, and the construction of molecular subgroups suggested the necessity for different subgroups of patients to receive individualized treatment.

Identification of the Key Transcription Factors Regulating the Expression of the Genes Associated with Barley Malt Quality during Malting

Barley malt is produced through a malting process; it begins with steeping followed by germination and kilning, in which dramatic changes happen for a large number of physiological and biochemical traits in barley seeds. The objectives of this study were to comprehensively investigate the phenotypic changes during malting, and identify the key regulators that modulate the expression of genes associated with malt quality traits. The results showed that there was a significant positive correlation between gibberellic acid (GA) content and the activities of some hydrolytic enzymes, including α-amylases, β-amylases, and limit dextrinase (LD), and a significant negative correlation between GA and β-glucan content. Starch content had little change, but starch granules were pitted severely during malting. Weighted gene coexpression analysis (WGCNA) identified the genes associated with the greatest changes of the examined malt traits during malting. The correlation analysis and protein-protein interaction (PPI) analysis detected several key transcriptional factor (TF) regulating genes associated with malt quality. These genes and TFs regulating malting traits are potentially useful in barley breeding for malt quality improvement.

Identification of immune-related genes in acute myocardial infarction based on integrated bioinformatical methods and experimental verification.

Acute myocardial infarction (AMI) is one of the leading causes of death worldwide. The etiology of AMI is complex and has not been fully defined. In recent years, the role of immune response in the development, progression and prognosis of AMI has received increasing attention. The aim of this study was to identify key genes associated with the immune response in AMI and to analyze their immune infiltration. The study included a total of two GEO databases, containing 83 patients with AMI and 54 healthy individuals. We used the linear model of microarray data (limma) package to find the differentially expressed genes associated with AMI, performing weighted gene co-expression analysis (WGCNA) to further identify the genes associated with inflammatory response to AMI. We found the final hub genes through the protein-protein interaction (PPI) network and least absolute shrinkage and selection operator (LASSO) regression model. To verify the above conclusions, we constructed mice AMI model, extracting myocardial tissue to perform qRT-PCR. Furthermore, the CIBERSORT tool for immune cells infiltration analysis was also carried out. A total of 5,425 significant up-regulated and 2,126 down-regulated genes were found in GSE66360 and GSE24519. A total of 116 immune-related genes in close association with AMI were screened by WGCNA analysis. These genes were mostly clustered in the immune response on the basis of GO and KEGG enrichment. With construction of PPI network and LASSO regression analysis, this research found three hub genes (SOCS2, FFAR2, MYO10) among these differentially expressed genes. The immune cell infiltration results revealed that significant differences could be found on T cells CD4 memory activated, Tregs (regulatory T cells), macrophages M2, neutrophils, T cells CD8, T cells CD4 naive, eosinophils between controls and AMI patients.

LncRNA analysis of mAb producing CHO clones reveals marker and engineering potential

Long non-coding RNAs (lncRNAs) are a potential new cell line engineering tool for improvement of yield and stability of CHO cells. In this study, we performed RNA sequencing of mAb producer CHO clones to study the lncRNA and protein coding transcriptome in relation to productivity. First, a robust linear model was used to identify genes correlating to productivity. To unravel specific patterns in expression of these genes, we employed weighted gene coexpression analysis (WGCNA) to find coexpressed modules, looking both for lncRNAs and coding genes. There was little overlap in the genes associated with productivity between the two products studied, possibly due to the difference in absolute range of productivity between the two mAbs. Therefore, we focused on the product with higher productivity and stronger candidate lncRNAs. To evaluate their potential as engineering targets, these candidate lncRNAs were transiently overexpressed or deleted by stable CRISPR Cas9 knock out both in a high and a low productivity subclone. We found that the thus achieved expression level of the identified lncRNAs, as confirmed by qPCR, does correlate well to productivity, so that they represent good markers that may be used for early clone selection. Additionally, we found that the deletion of one tested lncRNA region decreased viable cell density (VCD), prolonged culture time and increased cell size, final titer and specific productivity per cell. These results demonstrate the feasibility and usefulness of engineering lncRNA expression in production cell lines.

Priming grapevine with lipopolysaccharide confers systemic resistance to Pierce's disease and identifies a peroxidase linked to defense priming.

Priming is an adaptive mechanism that fortifies plant defense by enhancing activation of induced defense responses following pathogen challenge. Microorganisms have signature microbe-associated molecular patterns (MAMPs) that induce the primed state. The lipopolysaccharide (LPS) MAMP isolated from the xylem-limited pathogenic bacterium, Xylella fastidiosa, acts as a priming stimulus in Vitis vinifera grapevines. Grapevines primed with LPS developed significantly less internal tyloses and external disease symptoms than naive vines. Differential gene expression analysis indicated major transcriptomic reprogramming during the priming and postpathogen challenge phases. Furthermore, the number of differentially expressed genes increased temporally and spatially in primed vines, but not in naive vines during the postpathogen challenge phase. Using a weighted gene co-expression analysis, we determined that primed vines have more genes that are co-expressed in both local and systemic petioles than naive vines indicating an inherent synchronicity that underlies the systemic response to this vascular pathogen specific to primed plants. We identified a cationic peroxidase, VviCP1, that was upregulated during the priming and postpathogen challenge phases in an LPS-dependent manner. Transgenic expression of VviCP1 conferred significant disease resistance, thus, demonstrating that grapevine is a robust model for mining and expressing genes linked to defense priming and disease resistance.

WGCNA based identification of hub genes associated with cold response and development in Apis mellifera metamorphic pupae.

Honeybee is a crucial pollinator in nature, and plays an indispensable role in both agricultural production and scientific research. In recent decades, honeybee was challenged with health problems by biotic and abiotic stresses. As a key ecological factor, temperature has been proved to have an impact on the survival and production efficiency of honeybees. Previous studies have demonstrated that low temperature stress can affect honeybee pupation and shorten adult longevity. However, the molecular mechanism underlying the effects of low temperatures on honeybee growth and development during their developmental period remain poorly understood. In this paper, the weighted gene co-expression analysis (WGCNA) was employed to explore the molecular mechanisms underpinnings of honeybees' respond to low temperatures (20°C) during four distinct developmental stages: large-larvae, prepupae, early-pupae and mid-pupae. Through an extensive transcriptome analysis, thirteen gene co-expression modules were identified and analyzed in relation to honeybee development and stress responses. The darkorange module was found to be associated with low temperature stress, with its genes primarily involved in autophagy-animal, endocytosis and MAPK signaling pathways. Four hub genes were identified within this module, namely, loc726497, loc409791, loc410923, and loc550857, which may contribute to honeybee resistance to low temperature and provide insight into the underlying mechanism. The gene expression patterns of grey60 and black modules were found to correspond to the developmental stages of prepupae and early-pupae, respectively, with the hub genes loc409494, loc725756, loc552457, loc726158, Ip3k and Lcch3 in grey60 module likely involved in brain development, and the hub genes loc410555 in black module potentially related to exoskeleton development. The brown module genes exhibited a distinct pattern of overexpression in mid-pupae specimens, with genes primarily enriched in oxidative phosphorylation, citrate cycle and other pathways, which may be related to the formation of bee flying muscle. No related gene expression module was found for mature larvae stage. These findings provide valuable insights into the developmental process of honeybees at molecular level during the capped brood stage.

Integrative analysis of metabolite and transcriptome reveals biosynthetic pathway and candidate genes for eupatilin and jaceosidin biosynthesis in Artemisia argyi.

Artemisia argyi (A. argyi) is a medicinal plant belonging to the Asteraceae family and Artemisia genus. Flavonoids abundant in A. argyi are associated with anti-inflammatory, anticancer, and antioxidative effects. Eupatilin and jaceosidin are representative polymethoxy flavonoids with medicinal properties significant enough to warrant the development of drugs using their components. However, the biosynthetic pathways and related genes of these compounds have not been fully explored in A. argyi. This study comprehensively analyzed the transcriptome data and flavonoids contents from four different tissues of A. argyi (young leaves, old leaves, trichomes collected from stems, and stems without trichomes) for the first time. We obtained 41,398 unigenes through the de-novo assembly of transcriptome data and mined promising candidate genes involved in the biosynthesis of eupatilin and jaceosidin using differentially expressed genes, hierarchical clustering, phylogenetic tree, and weighted gene co-expression analysis. Our analysis led to the identification of a total of 7,265 DEGs, among which 153 genes were annotated as flavonoid-related genes. In particular, we were able to identify eight putative flavone-6-hydroxylase (F6H) genes, which were responsible for providing a methyl group acceptor into flavone basic skeleton. Furthermore, five O-methyltransferases (OMTs) gene were identified, which were required for the site-specific O-methylation during the biosynthesis of eupatilin and jaceosidin. Although further validation would be necessary, our findings pave the way for the modification and mass-production of pharmacologically important polymethoxy flavonoids through genetic engineering and synthetic biological approaches.

Repurposing Approved Drugs for Sarcopenia Based on Transcriptomics Data in Humans.

Sarcopenia, characterized by age-related loss of muscle mass, strength, and decreased physical performance, is a growing public health challenge amid the rapidly ageing population. As there are no approved drugs that target sarcopenia, it has become increasingly urgent to identify promising pharmacological interventions. In this study, we conducted an integrative drug repurposing analysis utilizing three distinct approaches. Firstly, we analyzed skeletal muscle transcriptomic sequencing data in humans and mice using gene differential expression analysis, weighted gene co-expression analysis, and gene set enrichment analysis. Subsequently, we employed gene expression profile similarity assessment, hub gene expression reversal, and disease-related pathway enrichment to identify and repurpose candidate drugs, followed by the integration of findings with rank aggregation algorithms. Vorinostat, the top-ranking drug, was also validated in an in vitro study, which demonstrated its efficacy in promoting muscle fiber formation. Although still requiring further validation in animal models and human clinical trials, these results suggest a promising drug repurposing prospect in the treatment and prevention of sarcopenia.