WGCNA: an R package for weighted correlation network analysis

Single-cell profiling and clinical characteristics analysis of lung squamous carcinoma

Lung squamous carcinoma (LUSC) is a highly heterogeneous disease. However, the tumor microenvironment (TME) landscape and clinical characteristics for LUSC have not yet been elucidated. To map the TME and clinical characteristics of LUSC, we performed single-cell RNA sequencing for 504 LUSC samples on basis of TCGA and Gene Expression Omnibus. We introduced the computational algorithms "ESTIMATE" and "CIBERSORT" to analyze immune cell infiltration and immune-checkpoint-related gene signatures in various LUSC clusters. Weighted gene co-expression network analysis was used to explore the connections between molecular characteristics and clinical traits in LUSC. A prognostic model was constructed by performing multivariate COX. Two gene clusters exhibiting disparate immune and clinical characteristics were identified. Our findings indicate that patients in cluster 2, who have a more favorable prognosis, exhibit immune characteristics such as elevated levels of immunosuppression-associated M2 macrophages, resting memory CD4 T cells, resting dendritic cells (DC), and TNFRSF4, alongside reduced infiltration of activated DC and lower expression of TNFRSF18.Whereafter, the Risk Score model was built on basis of 3-DEGs signature consisted of cystatin C (CST3), transglutaminase type 2 (TGM2), JUN, which were proved by q-PCR and immunofluorescence. Besides, high-Risk Score may be responsible for poor prognosis in LUSC patients. Our study identified that tumor-infiltrating immune cell subtypes and the Risk Score model might shed light on the heterogeneity in LUSC patients. The TME, three DEGs and Risk Score can effectively serve as biomarkers to elucidate the immune landscape and predict prognosis in LUSC patients. They may provide insights to the investigations on therapeutic strategies for LUSC.

BIN1 inhibited tumor growth, metastasis and stemness by ALDH1/NOTCH pathway in bladder carcinoma

BACKGROUND

Bladder cancer (BLCA) represents one of the most prevalent urological malignancies worldwide. Bridging integrator 1 (BIN1), a well-characterized tumor suppressor that interacts with and inhibits oncogenic Myc transcription factors, has demonstrated crucial roles in various cancer types. However, its specific functions and underlying molecular mechanisms in BLCA development and progression remain poorly understood. This study aims to elucidate the role of BIN1 in regulating BLCA cell proliferation, metastasis, and cancer stem cell properties.

METHODS

Using urinary proteomics analysis, we identified BIN1 as a significantly dysregulated protein in BLCA. The clinical significance of BIN1 was further validated through comprehensive analyses of public databases. BIN1 expression levels defined distinct molecular and immunological subtypes of BLCA. Through proteomic profiling of BIN1-overexpressing UMUC3 cells and corresponding controls, we identified ALDH1 as a key downstream effector in the BIN1-regulated ALDH1/NOTCH signaling axis. We employed multiple experimental approaches, including Western blot analysis, quantitative RT-PCR, immunofluorescence staining, wound healing assays, transwell migration assays, colony formation assays, tumor sphere formation assays, flow cytometry, CCK8 proliferation assays, and cell transfection experiments.

RESULTS

We observed significant downregulation of BIN1 in both BLCA tissues and cell lines compared to normal adjacent tissues and SV-HUC-1 cells, respectively. BIN1 overexpression inhibited cancer cell proliferation by promoting apoptosis and suppressed epithelial-mesenchymal transition (EMT), thereby reducing local invasion and distant metastasis. Additionally, BIN1 regulated cancer stem cell properties through modulation of ALDH1 expression, with NOTCH2 acting as a crucial downstream mediator of ALDH1 signaling.

CONCLUSION

Our findings demonstrate that BIN1 functions as a tumor suppressor in BLCA and suggest its potential utility as both a diagnostic biomarker and therapeutic target for BLCA treatment.

The Monochoria genome provides insights into the molecular mechanisms underlying floral heteranthery

Heteranthery, the occurrence of functionally and structurally distinct stamens within a flower, represents a striking example of convergent evolution among diverse animal-pollinated lineages. Although the ecological basis of this somatic polymorphism is understood, the developmental and molecular mechanisms are largely unknown. To address this knowledge gap, we selected Monochoria elata (Pontederiaceae) as our study system due to its typical heterantherous floral structure. We constructed a chromosome-level genome assembly of M. elata, conducted transcriptomic analyses and target phytohormone metabolome analysis to explore gene networks and hormones associated with heteranthery. We focused on three key stamen characteristics-colour, spatial patterning, and filament elongation-selected for their significant roles in stamen differentiation and their relevance to the functional diversity observed in heterantherous species. Our analyses suggest that gene networks involving MelLEAFY3, MADS-box, and TCP genes regulate stamen identity, with anthocyanin influencing colour, and lignin contributing to filament elongation. Additionally, variation in jasmonic acid and abscisic acid concentration between feeding and pollinating anthers appears to contribute to their morphological divergence. Our findings highlight gene networks and hormones associated with intra-floral stamen differentiation and indicate that whole genome duplications have likely facilitated the evolution of heternathery during divergence from other Pontederiaceae without heteranthery.

Joint damage is more severe following a single bout than multiple bouts of high magnitude loading in mice

OBJECTIVE

While physiological loads maintain cartilage health, both joint overload and abnormal joint mechanical loading contribute to osteoarthritis (OA) development. Here, we examined the role of abnormal mechanical loading on joint health by comparing the severity of OA development following a single overload event and repetitive joint overloads.

METHOD

Cyclic tibial compression was applied to the left limbs of 26-week-old male mice at a peak load of 9N for either a single bout or daily bouts to initiate OA disease. Joint damage severity was morphologically examined using histology and microcomputed tomography at 6 weeks following the start of loading. Early-stage transcriptomic responses to loading were evaluated.

RESULTS

Joint damage was more severe at 6 weeks following a single bout of loading than after daily loading bouts. Severe cartilage damage, subchondral plate erosions, and soft tissue calcifications occurred following the single bout of loading. Daily loading bouts resulted in less severe cartilage damage and preserved subchondral plate integrity. A diverging transcriptomic response was identified in cartilage at 1 week with increased expression of fibrosis- and inflammation-related genes following a single bout of loading compared to daily loading.

CONCLUSIONS

Even applied at hyperphysiological load magnitudes known to initiate cartilage damage, repetitive loading may induce protective effects in the joint and attenuate OA progression over time relative to a single bout of loading. Our findings suggest the potential of mechanotherapies that use repetitive loading as disease-modifying treatments for OA disease.

Cellular Membrane Protein GRINA is Highly Expressed and Associated with Survival Outcomes in Liver Cancer Patients

OBJECTIVE

Hepatocellular carcinoma (HCC), a lethal cancer with high global mortality, may be targeted through ferroptosis, an iron-dependent form of cell death. Despite its potential, the prognostic value of ferroptosis in HCC is underexplored.

METHODS

Our study leveraged single-cell and bulk sequencing datasets to identify ferroptosis-related genes and developed a prognostic model via Cox and LASSO regression analyses. Survival and mutation analyses led to the creation of a nomogram for predicting patient prognosis. Furthermore, we investigated the role of GRINA, a ferroptosis-related gene, through functional assays, including cell proliferation, colony formation, and metastatic potential analyses. We also assessed mitochondrial abnormalities, intracellular iron, and ROS levels in GRINA-knockdown cells.

RESULTS

The developed ferroptosis-related model classified HCC patients into risk groups, revealing notable survival disparities. High-risk patients presented increased immune checkpoint gene expression. The nomogram revealed robust prognostic accuracy. Additionally, we found that GRINA suppression reduced HCC cell proliferation, colony formation, and metastatic potential. Cells with GRINA knockdown presented mitochondrial abnormalities and increased intracellular iron and ROS levels.

CONCLUSIONS

By analysing multiomics sequencing data, we established a connection between ferroptosis-related risk groups and the tumor immune microenvironment. These findings provide novel insights into the role of ferroptosis in HCC and suggest that GRINA inhibition is a potential therapeutic strategy, leading to mitochondrial damage and the induction of ferroptosis in HCC cell lines.

Topic modeling analysis of the Allen Human Brain Atlas

The human brain is a complex interconnected structure controlling all elementary and high-level cognitive tasks. It is composed of many regions that exhibit specific distributions of cell types and distinct patterns of functional connections. This complexity is rooted in differential transcription. The constituent cell types of different brain regions express distinctive combinations of genes as they develop and mature, ultimately shaping their functional state in adulthood. How precisely the genetic information of anatomical structures is connected to their underlying biological functions remains an open question in modern neuroscience. A major challenge is the identification of "universal patterns", which do not depend on the particular individual, but are instead basic structural properties shared by all brains. Despite the vast amount of gene expression data available at both the bulk and single-cell levels, this task remains challenging, mainly due to the lack of suitable data mining tools. In this paper, we propose an approach to address this issue based on a hierarchical version of Stochastic Block Modeling. Thanks to its specific choice of priors, the method is particularly effective in identifying these universal features. We use as a laboratory to test our algorithm a dataset obtained from six independent human brains from the Allen Human Brain Atlas. We show that the proposed method is indeed able to identify universal patterns much better than more traditional algorithms such as Latent Dirichlet Allocation or Weighted Correlation Network Analysis. The probabilistic association between genes and samples that we find well represents the known anatomical and functional brain organization. Moreover, leveraging the peculiar "fuzzy" structure of the gene sets obtained with our method, we identify examples of transcriptional and post-transcriptional pathways associated with specific brain regions, highlighting the potential of our approach.

Mapping and functional characterization of the golden fruit 1 (gf1) in melon (Cucumis melo L.)

KEY MESSAGE

A missense mutation that causes premature termination of the CmEGY1 protein leads to golden fruit in melon. Melon (Cucumis melo L.) is an economically important fruit crop that has been cultivated for thousands of years. Fruit color, a crucial trait influencing the appearance quality and economic value of melons, is primarily determined mainly by the type and concentration of pigments such as chlorophyll, carotenoids, and flavonoids. Identifying the genetic loci that govern melon fruit color contributes to breeding efforts aimed at enhancing melon rind coloration. This study reports an EMS-induced mutant, designated as gf1 (golden fruit 1), which produces fruit with both golden peel and flesh. Through MutMap and map-based cloning, we localized the gf1 locus to an 862 kb region containing 42 SNPs. Of these, a single SNP in the coding region caused a stop-gained mutation in the gene Cme13C08g017690, which exhibits the highest sequence similarity to Arabidopsis ETHYLENE-DEPENDENT GRAVITROPISM-DEFICIENT AND YELLOW-GREEN 1 (EGY1). Genome editing of CsEGY1, the cucumber homolog, confirmed its role in golden-fruit formation. Transcriptome and metabolome analyses revealed reduced flavonoid and carotenoid contents, accompanied by the downregulation of related biosynthetic genes. The identification and characterization of egy1 provide novel genetic insights and a valuable resource for improving melon appearance through breeding.

A multi-omics and cell type-specific characterization of the ventral striatum in human cocaine use disorder

Epigenome, transcriptome, and proteome analyses of postmortem brains have revealed initial molecular insights into cocaine use disorder (CUD). However, the inter-relationship between these omics and the contribution of individual cell types remains largely unknown. We present an in-depth analysis of molecular changes in the ventral striatum in CUD at multi-omics and single-cell resolution. Integrative multi-omics analyses of microRNA sequencing (microRNA-seq), RNA sequencing (RNA-seq), and proteomics datasets in 41 individuals and single-nuclei RNA-seq in a subset of 16 individuals revealed conserved deregulation of metabolic pathways, oxidative phosphorylation, and glutamatergic signaling. Cell type-specific analyses identified inverse metabolic pathway deregulation patterns in glial and neuronal cells, notably in astrocytes and medium-spiny neurons (MSNs). Characterizing astrocyte-neuron crosstalk revealed altered glutamatergic and cell-cell adhesion signaling in CUD. By applying a comprehensive multi-omics analytical framework, our study provides novel insights into CUD-associated molecular changes in the ventral striatum highlighting the perturbation of astrocytes, MSNs, and their crosstalk in CUD.

The Hao-Fountain syndrome protein USP7 regulates neuronal connectivity in the brain via a novel p53-independent ubiquitin signaling pathway

Mutation or deletion of the deubiquitinase USP7 causes Hao-Fountain syndrome (HAFOUS), which is characterized by speech delay, intellectual disability, and aggressive behavior and highlights important unknown roles of USP7 in the nervous system. Here, we conditionally delete USP7 in glutamatergic neurons in the mouse forebrain, triggering disease-relevant phenotypes, including sensorimotor deficits, impaired cognition, and aggressive behavior. Although USP7 deletion induces p53-dependent neuronal apoptosis, most behavioral abnormalities in USP7 conditional knockout mice persist following p53 loss. Strikingly, USP7 deletion perturbs the synaptic proteome and dendritic spinogenesis independent of p53. Integrated proteomics and biochemical analyses identify the RNA splicing factor Ppil4 as a key substrate of USP7. Ppil4 knockdown phenocopies the effect of USP7 loss on dendritic spines. Accordingly, USP7 loss disrupts splicing of synaptic genes. These findings reveal that USP7-Ppil4 signaling regulates neuronal connectivity in the developing brain with implications for our understanding of HAFOUS pathogenesis and other neurodevelopmental disorders.

Investigating biological nitrogen fixation via single-cell transcriptomics

The extensive use of nitrogen fertilizers has detrimental environmental consequences, and it is essential for society to explore sustainable alternatives. One promising avenue is engineering root nodule symbiosis, a naturally occurring process in certain plant species within the nitrogen-fixing clade, into non-leguminous crops. Advancements in single-cell transcriptomics provide unprecedented opportunities to dissect the molecular mechanisms underlying root nodule symbiosis at the cellular level. This review summarizes key findings from single-cell studies in Medicago truncatula, Lotus japonicus, and Glycine max. We highlight how these studies address fundamental questions about the development of root nodule symbiosis, including the following findings: (i) single-cell transcriptomics has revealed a conserved transcriptional program in root hair and cortical cells during rhizobial infection, suggesting a common infection pathway across legume species; (ii) characterization of determinate and indeterminate nodules using single-cell technologies supports the compartmentalization of nitrogen fixation, assimilation, and transport into distinct cell populations; (iii) single-cell transcriptomics data have enabled the identification of novel root nodule symbiosis genes and provided new approaches for prioritizing candidate genes for functional characterization; and (iv) trajectory inference and RNA velocity analyses of single-cell transcriptomics data have allowed the reconstruction of cellular lineages and dynamic transcriptional states during root nodule symbiosis.

Harnessing TAGAP to improve immunotherapy for lung squamous carcinoma treatment by targeting c-Rel in CD4+ T cells

Revealing the immunosenescence, particularly in CD4+ T cell function in lung squamous carcinoma (LUSC) assists in devising individual treatment strategies. This study identifies differentially expressed genes (DEGs) between ROS1 mutated (ROS1MUT) and wild-type (ROS1WT) LUSC samples from the TCGA database. Using WGCNA, immune-related DEGs (IRGs) were screened. Prognostic signatures derived from IRGs were used to compare immune infiltration, chemotherapy sensitivity, and immune-phenotyping score (IPS) between high- and low-risk subgroups. Hub gene abundance in different cell clusters was analyzed via Sc-seq. TAGAP overexpression or silencing was employed to assess its impact on cytokines production and differentiation of CD4+ T cells, downstream c-Rel expression, and tumor progression. High-risk subgroups exhibited decreased infiltration of natural killer, follicular helper T, and CD8+ T cells, but increased plasma, CD4+ memory resting T, and macrophage M2 cells. These subgroups were more sensitive to Sunitinib and CTLA4 blockade. TAGAP expression was significantly reduced in LUSC. Overexpressing TAGAP enhanced CD4+ T cells to produce cytokines, promoted differentiation into Th1/Th17 cells, inhibited Treg conversion, and suppressed LUSC cell phenotype in vitro. TAGAP overexpression in CD4+ T cells also inhibited LUSC tumor growth and boosted immune infiltration in vivo. TAGAP's effects on CD4+ T cells were partly reversed by c-Rel overexpression, highlighting TAGAP's role in rejuvenating CD4+ T cells and exerting anticancer effects by inhibiting c-Rel. This study elucidates the novel therapeutic potential of targeting TAGAP to modulate CD4+ T cell activity in immunotherapy for LUSC.

Identifying periphery biomarkers of first-episode drug-naïve patients with schizophrenia using machine-learning-based strategies

Schizophrenia is a complex mental disorder. Accurate diagnosis and classification of schizophrenia has always been a major challenge in clinic due to the lack of biomarkers. Therefore, identifying molecular biomarkers, particularly in the peripheral blood, is of great significance. This study aimed to identify immune-related molecular biomarkers of schizophrenia in peripheral blood. Eighty-four Peripheral blood leukocytes of first-episode drug-naïve (FEDN) patients with schizophrenia and 97 healthy controls were collected and examined using high-throughput RNA-sequencing. Differentially-expressed genes (DEGs) were analysed. Weighted correlation network analysis (WGCNA) was employed to identify schizophrenia-associated module genes. The CIBERSORT algorithm was adopted to analyse immune cell proportions. Then, machine-learning algorithms including random forest, LASSO, and SVM-RFE were employed to screen immune-related predictive genes of schizophrenia. The RNA-seq analyses revealed 734 DEGs. Further machine-learning-based bioinformatic analyses screened out three immune-related predictive genes of schizophrenia (FOSB, NUP43, and H3C1), all of which were correlated with neutrophils and natural killer cells resting. Lastly, external GEO datasets were used to verify the performance of the machine-learning models with these predictive genes. In conclusion, by analysing the peripheral mRNA expression profiles of FEDN patients with schizophrenia, this study identified three predictive genes that could be potential molecular biomarkers for schizophrenia.

Synchrony between midbrain gene transcription and dopamine terminal regulation is modulated by chronic alcohol drinking

Alcohol use disorder is marked by disrupted behavioral and emotional states which persist into abstinence. The enduring synaptic alterations that remain despite the absence of alcohol are of interest for interventions to prevent relapse. Here, 28 male rhesus macaques underwent over 20 months of alcohol drinking interspersed with three 30-day forced abstinence periods. After the last abstinence period, we paired direct sub-second dopamine monitoring via ex vivo voltammetry in nucleus accumbens core with RNA-sequencing of the ventral tegmental area. We found persistent augmentation of dopamine transporter function, kappa opioid receptor sensitivity, and putative dynorphin release - all inhibitory regulators which act to decrease extracellular dopamine. Surprisingly, though transcript expression was not altered, the relationship between gene expression and functional readouts of these encoded proteins was highly dynamic and altered by drinking history. These results outline the long-lasting synaptic impact of alcohol use and suggest that assessment of transcript-function relationships is critical for the rational design of precision therapeutics.

Edaravone mitigates TDP-43 mislocalization in human amyotrophic lateral sclerosis neurons with potential implication of the SIRT1-XBP1 pathway

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disorder characterized by progressive motor neuron loss along with pathological mislocalization of TAR DNA-binding protein 43 (TDP-43), a protein implicated in RNA metabolism. Although edaravone, a free-radical scavenger, has been approved for ALS treatment, its precise mechanism of action is not fully understood, particularly in relation to TDP-43 pathology. Here, we investigated the effects of edaravone on induced pluripotent stem cell (iPSC)-derived motor neurons in a patient with ALS harboring a TDP-43 mutation. Our results demonstrated that edaravone significantly attenuated neurodegeneration, as evidenced by neurite preservation, neuronal cell death reduction, and correction of aberrant cytoplasmic localization of TDP-43. These neuroprotective effects were not observed with vitamin C, indicating a unique mechanism of action for edaravone, distinct from its antioxidative properties. RNA sequencing revealed that edaravone rapidly modulated gene expression, including protein quality control pathway, such as the ubiquitin-proteasome system. Further analysis identified X-box binding protein (XBP1), a key regulator of the endoplasmic reticulum stress response, as a critical factor in the therapeutic effects of edaravone. This study suggests that edaravone may offer a multifaceted therapeutic approach for ALS by targeting oxidative stress and TDP-43 mislocalization through distinct molecular pathways.

Transcriptomic profiling reveals a regulatory network governing volatile compound biosynthesis in Shine Muscat grapes (Vitis labruscana Baily × V. vinifera L.)

MAIN CONCLUSION

Winter berries accumulated more free volatile compounds than summer berries, and C6 volatile compounds were the main contributors to free volatile compounds. The volatile composition of grapes and wines is important in viticulture, since their aroma is one of the most important determinants of grape fruit quality. The aroma and general quality of grape fruit are influenced by the production of volatile compounds primarily influenced by crop management. In this study, the free and bound volatile compounds were determined using gas chromatography-mass spectrometry (GC-MS), along with the transcriptomic analysis using Shine Muscat grape (Vitis labruscana Baily × V. vinifera L.) of summer and winter berries under two-crop-a-year cultivation in Guangxi. The findings demonstrated that phenols, terpenoids, and alcohols were the main bound volatile compounds in fruits from both seasons, whereas aldehydes, terpenoids, and alcohols were the leading free volatile compounds. Free volatile compound concentrations were substantially higher in winter than summer berries, but bound volatile compound concentrations were much lower. Specifically, the concentrations/constitution of free C6 volatile compounds showed a significant difference between the two seasons and highly correlated with the transcription of three genes involved in the lipoxygenase (LOX) pathway. Winter berries had a higher concentration of aldehydes, which might be ascribed to the higher expression of VvLOXA (VIT_06s0004g01510) and VvHPL1 (VIT_12s0059g01060) genes, while the higher concentration of alcohols in summer berries might be due to the higher expression of alcohol dehydrogenase (VvADH1, VIT_18s0001g15410). Furthermore, two VvBGLU genes (VIT_05s0077g01150, VIT_01s0011g00760) were supposed to regulate the enzymatic hydrolysis of glycoside-bound compounds in grapes. Three transcription factors including MYB60, MYBA1, and GATA16 were highly correlated with VvADH1, and they might play an important role in grape C6 alcohol biosynthesis. The findings may help to reveal a transcriptional regulation network of volatile compounds biosynthetic in grapes and to develop efficient cultivation practices.

Subfunctionalization and epigenetic regulation of a biosynthetic gene cluster in Solanaceae

Biosynthetic gene clusters (BGCs) are sets of often heterologous genes that are genetically and functionally linked. Among eukaryotes, BGCs are most common in plants and fungi and ensure the coexpression of the different enzymes coordinating the biosynthesis of specialized metabolites. Here, we report the identification of a withanolide BGC in Physalis grisea (ground-cherry), a member of the nightshade family (Solanaceae). A combination of transcriptomic, epigenomic, and metabolic analyses revealed that, following a duplication event, this BGC evolved two tissue-specifically expressed subclusters, containing several pairs of paralogs that contribute to related but distinct biochemical processes; this subfunctionalization is tightly associated with epigenetic features and the local chromatin environment. The two subclusters appear strictly isolated from each other at the structural chromatin level, each forming a highly self-interacting chromatin domain with tissue-dependent levels of condensation. This correlates with gene expression in either above- or below-ground tissue, thus spatially separating the production of different withanolide compounds. By comparative phylogenomics, we show that the withanolide BGC most likely evolved before the diversification of the Solanaceae family and underwent lineage-specific diversifications and losses. The tissue-specific subfunctionalization is common to species of the Physalideae tribe but distinct from other, independent duplication events outside of this clade. In sum, our study reports on an instance of an epigenetically modulated subfunctionalization within a BGC and sheds light on the biosynthesis of withanolides, a highly diverse group of steroidal triterpenoids important in plant defense and amenable to pharmaceutical applications due to their anti-inflammatory, antibiotic, and anticancer properties.

A spatial transcriptomic signature of 26 genes resolved at single-cell resolution characterizes high-risk gastric cancer precursors

Gastric cancer precursors demonstrate highly-variable rates of progression toward neoplasia. Certain high-risk precursors, such as gastric intestinal metaplasia with advanced histologic features, may be at up to 30-fold increased risk for progression compared to lower-risk intestinal metaplasia. The biological differences between high- and low-risk lesions have been incompletely explored. In this study, we use several clinical cohorts to characterize the microenvironment of advanced gastric cancer precursors relative to low-risk lesions using bulk, spatial, and single-cell gene expression assays. We identified a 26-gene panel which is associated with advanced lesions, localizes to metaplastic glands on histopathology, and is expressed in aberrant mature and immature intestinal cells not normally present in the healthy stomach. This gene expression signature suggests an important role of the immature intestinal lineages in promoting carcinogenesis in the metaplastic microenvironment. These findings may help to inform future biomarker development and strategies of gastric cancer prevention.

Mechanism of fatty acid synthesis metabolism during tuber swelling period of Chinese yam

Chinese yam is well-known for its nutritional value, specifically for its low fat content, which is rich in unsaturated fatty acids, thus providing high-quality and essential fats. This study used GC-MS analysis to identify 28 metabolites, predominantly composed of unsaturated fatty acids such as linoleic, linolenic, and oleic acids, which play a crucial role in maintaining membrane stability. Unsaturated fatty acids improve fluidity under low-temperature conditions, shield cells from oxidative stress, and maintain cell integrity. Through weighted gene co-expression network analysis, this study discovered 12 potential regulatory factors, including Acetyl CoA carboxylase, lipoxygenase, and fatty acid desaturase, that contribute to the synthesis of highly unsaturated fatty acids in Chinese yam. Additionally, variations in fatty acid biosynthesis pathway metabolite accumulation significantly affects the cold tolerance of different Chinese yam varieties. This study enhances our understanding of the regulatory network of fatty acid metabolites and offers new insights into the genetic enhancement of Chinese yam varieties, particularly in terms of low-temperature tolerance.

An Immunogenic Cell Death-Related Gene Signature Predicts the Prognosis and Immune Infiltration of Cervical Cancer

Objectives

Immunogenic cell death (ICD) has been demonstrated to play a critical role in the development and progression of malignant tumors by modulating the anti-tumor immune response. However, its function in cervical cancer (CC) remains largely unexplored. In this study, we aimed to construct an ICD-related gene signature to predict patient prognosis and immune cell infiltration in CC.

Methods

The gene expression profiles and clinical data of CC were downloaded from The Cancer Genome Alas (TCGA) and Gene Expression Omnibus (GEO) datasets, serving as the training and testing groups, respectively. An ICD-related gene signature was developed using the LASSO-Cox model. The expression levels of the associated ICD-related genes were evaluated using single-cell data, CC cell lines, and clinical samples in vitro.

Results

Two ICD-associated subtypes (cluster 1 and cluster 2) were identified through consensus clustering. Patients classified into cluster 2 demonstrated higher levels of immune cell infiltration and exhibited a more favorable prognosis. Subsequently, an ICD-related gene signature comprising 3 genes (IL1B, IFNG, and FOXP3) was established for CC. Based on the median risk score, patients in both training and testing cohorts were segregated into high-risk and low-risk groups. Further analyses indicated that the estimated risk score functioned as an independent prognostic factor for CC and influenced immune cell abundance within the tumor microenvironment. The up-regulation of the identified ICD-related genes was further validated in CC cell lines and collected clinical samples.

Conclusion

In summary, the stratification based on ICD-related genes demonstrated strong efficacy in predicting patient prognosis and immune cell infiltration, which also provides valuable new perspectives for the diagnosis and prognosis of CC.

Refined culture conditions with increased physiological relevance uncover oncogene-dependent metabolic signatures in Ewing sarcoma spheroids

Ewing sarcoma (EwS) cell line culture largely relies on standard techniques, which do not recapitulate physiological conditions. Here, we report on a feasible and cost-efficient EwS cell culture technique with increased physiological relevance employing an advanced medium composition, reduced fetal calf serum, and spheroidal growth. Improved reflection of the transcriptional activity related to proliferation, hypoxia, and differentiation in EwS patient tumors was detected in EwS cells grown in this refined in vitro condition. Moreover, transcriptional signatures associated with the oncogenic activity of the EwS-specific FET::ETS fusion transcription factors in the refined culture condition were shifted from proliferative toward metabolic gene signatures. The herein-presented EwS cell culture technique with increased physiological relevance provides a broadly applicable approach for enhanced in vitro modeling relevant to advancing EwS research and the validity of experimental results.

Gene module reconstruction identifies cellular differentiation processes and the regulatory logic of specialized secretion in zebrafish

During differentiation, cells become structurally and functionally specialized, but comprehensive views of the underlying remodeling processes are elusive. Here, we leverage single-cell RNA sequencing (scRNA-seq) developmental trajectories to reconstruct differentiation using two secretory tissues as models-the zebrafish notochord and hatching gland. First, we integrated expression and functional similarities to identify gene modules, revealing dozens of modules representing known and newly associated differentiation processes and their dynamics. Second, we focused on the unfolded protein response (UPR) transducer module to study how general versus cell-type-specific secretory functions are regulated. Profiling loss- and gain-of-function embryos identified that the UPR transcription factors creb3l1, creb3l2, and xbp1 are master regulators of a general secretion program. creb3l1/creb3l2 additionally activate an extracellular matrix secretion program, while xbp1 partners with bhlha15 to activate a gland-like secretion program. Our study presents module identification via multi-source integration for reconstructing differentiation (MIMIR) and illustrates how transcription factors confer general and specialized cellular functions.

Hirschsprung's disease may increase the incidence of inflammatory bowel disease through alterations in CA1

BACKGROUND

The role of Hirschsprung's disease (HSCR) for the development of inflammatory bowel disease (IBD) and the common pathogenesis of the diseases remains unclear. The objective is to investigate the relationship between HSCR and IBD.

METHODS

In our study, the Mendelian randomization approach was employed to analyze the causal relationships. A further search was conducted for differentially expressed genes (DEGs) between disease and control tissues in HSCR and IBD. Subsequently, the potential pathway mechanisms were subjected to an enrichment analysis. Furthermore, the molecular docking was employed to investigate the binding relationship between potential therapeutic targets and drugs.

RESULTS

The results show HSCR have an increased risk of developing IBD (IVW: OR = 1.048, P < 0.05; weighted median: OR = 1.065, P < 0.05). A total of 111 DEGs were identified in IBD, while 471 DEGs were observed in HSCR. CA1 was identified as core gene and exhibited lower expression levels in IBD (P < 0.05). Concomitantly, CA1 exhibited reduced expression levels in inflamed tissues. And the TNF and IL17 signaling pathway were found closely related to CA1 expression.

CONCLUSION

In total, our study shows HSCR promote the occurrence of IBD and reveals pathogenesis. Our results suggest CA1 may provide novel insight for the treatment of HSCR complicated with IBD.

IMPACT

Individuals with HSCR are at a higher risk of developing IBD (IVW: OR = 1.048, P < 0.05; Weighted median: OR = 1.065, P < 0.05). Patients with IBD exhibited lower expression levels of CA1 (P < 0.05). Furthermore, CA1 expression was found to be lower in inflamed tissues (P < 0.05). CA1 may provide novel insight for the treatment of HSCR complicated with IBD.

Arrayed CRISPR/Cas9 Loss-Of-Function Screen in a Neuronal Model of Adaptor Protein Complex 4 Deficiency Identifies Modulators of ATG9A Trafficking

Biallelic loss-of-function variants in the adaptor protein complex 4 (AP-4) disrupt trafficking of transmembrane proteins at the trans -Golgi network, including the autophagy-related protein 9A (ATG9A), leading to childhood-onset hereditary spastic paraplegia (AP-4-HSP). AP-4-HSP is characterized by features of both a neurodevelopmental and degenerative neurological disease. To investigate the molecular mechanisms underlying AP-4-HSP and identify potential therapeutic targets, we conducted an arrayed CRISPR/Cas9 loss-of-function screen of 8,478 genes, targeting the 'druggable genome', in a human neuronal model of AP-4 deficiency. Through this phenotypic screen and subsequent experiments, key modulators of ATG9A trafficking were identified, and complementary pathway analyses provided insights into the regulatory landscape of ATG9A transport. Knockdown of ANPEP and NPM1 enhanced ATG9A availability outside the trans -Golgi network, suggesting they regulate ATG9A localization. These findings deepen our understanding of ATG9A trafficking in the context of AP-4 deficiency and offer a framework for the development of targeted interventions for AP-4-HSP.

Identification of subtypes and biomarkers associated with disulfidptosis-related ferroptosis in ulcerative colitis

BACKGROUND

Disulfidptosis and ferroptosis are different programmed cell death modes, which are closely related to the development of a variety of diseases, but the relationship between them and ulcerative colitis (UC) is still unclear. Therefore, our study aimed to explore the molecular subtypes and biomarkers associated with disulfidptosis-related ferroptosis (DRF) in UC.

METHODS

We used Pearson analysis to identify DRF genes. Then, we classified 140 UC samples into different subtypes based on the DRF genes and explored the biological and clinical characteristics between them. Next, the hub genes were identified by differential analysis and WGCNA algorithms, and three machine learning algorithms were used to screen biomarkers for UC from hub genes. In addition, we analyzed the relationship between biomarkers of immune cells and transcription factors and predicted natural compounds that might be used to treat UC. Finally, we further verified the reliability of the markers by RT-qPCR experiments.

RESULTS

118 DRF genes were identified using Pearson analysis. Based on the expression level of the DRF genes, we classified UC patients into C1 and C2 subtypes, with significant differences in the abundance of immune infiltration and disease activity between the two subtypes. The machine learning algorithms identified three biomarkers, including XBP1, FH, and MAP3K5. Further analyses revealed that the three biomarkers were closely associated with a variety of immune cells and transcription factors. In addition, six natural compounds corresponding to the biomarkers were predicted, which may contribute to the effective treatment of UC. Finally, the expression trends of XBP1, FH, and MAP3K5 in animal experiments were consistent with the results of bioinformatics analysis.

CONCLUSION

In this study, we systematically elucidated the role of DRF genes in the development of UC, and identified three potential biomarkers, providing a new idea for the diagnosis and treatment of UC.

Network-based analysis of Alzheimer's Disease genes using multi-omics network integration with graph diffusion

Alzheimer's Disease (AD) is a complex neurodegenerative disorder affecting millions worldwide. Despite extensive research, the mechanisms behind AD remain elusive. Many studies suggest that disease-responsible genes often act as hub genes in biological networks. However, this assumption requires further investigation in the context of AD. To examine the network characteristics of known AD genes, it is crucial to construct a highly confident network, which is challenging to achieve using a single data source. This work integrates multi-omics networks inferred from microarray, single-cell RNA sequencing, and single-nuclei RNA sequencing expression data, weighted with protein interaction and gene ontology information. We generate a high-quality integrated network by utilizing various inference methods and combining them through a graph diffusion-based integration approach. This network is then analyzed to investigate the properties of known AD-specific genes. Our findings reveal that AD genes are not always high-degree or central hub nodes in the network. Instead, these genes are distributed across different quartiles of degree centrality while maintaining significant interconnections for effective regulation. Furthermore, our study highlights that peripheral genes, often overlooked, also play crucial roles by connecting to relevant disease nodes and hub genes. These findings challenge the conventional understanding that AD-responsible genes are primarily the hub genes in the network, offering new insights into the complex regulatory mechanisms of AD and suggesting novel directions for future research.

Identification of UBE2N as a biomarker of Alzheimer's disease by combining WGCNA with machine learning algorithms

Alzheimer's disease (AD) is the most common cause of dementia, emphasizing the critical need for the development of biomarkers that facilitate accurate and objective assessment of disease progression for early detection and intervention to delay its onset. In our study, three AD datasets from the Gene Expression Omnibus (GEO) database were integrated for differential expression analysis, followed by a weighted gene co-expression network analysis (WGCNA), and potential AD biomarkers were screened. Our study identified UBE2N as a promising biomarker for AD. Functional enrichment analysis revealed that UBE2N is associated with synaptic vesicle cycling and T cell/B cell receptor signaling pathways. Notably, UBE2N expression levels were found to be significantly reduced in the cortex and hippocampus of the TauP301S mice. Furthermore, analysis of single-cell data from AD patients demonstrated the association of UBE2N and T cell function. These findings underscore the potential of UBE2N as a valuable biomarker for AD, offering important insights for diagnosis and targeted therapeutic strategies.

Exogenous application of luteolin enhances wheat resistance to Puccinia striiformis f. sp. tritici

The accumulation of flavonoids facilitates plant resistance to biotic stress. However, few studies have explored the functions of flavonoids during the interaction between wheat and Puccinia striiformis Westendorp f. sp. tritici Eriksson (Pst). This study analyzed the expression profiles of flavonoids and their biosynthesis genes in the resistant accession Y0337 and the susceptible accession Y0402 infected with Pst. The results showed that flavonoid biosynthesis pathway (FBP) genes were induced during early Pst infection. Among these, 29 initial FBP DEGs exhibited higher expression during incompatible interaction. Further, the total levels of 12 identified flavonoids were higher during incompatible interaction; among these, apigenin, luteolin, cynaroside were accumulated and naringenin was decreased, they may play a crucial role in Pst resistance. Integrated analysis of the transcriptome and metabolome showed that 21 DEGs regulated four crucial flavonoids biosynthesis. The gene regulatory network suggested that the transcription factors EFRs, WRKYs, NACs, and bHLHs potentially regulated four flavonoids biosynthesis. Additionally, it was shown that luteolin inhibited spore germination and infection of Pstin vivo and in vitro. In summary, these results enhance our understanding of the flavonoids biosynthesis in wheat resistance to Pst and highlight the role of luteolin in this process.

Machine learning-based characterization of PANoptosis-related biomarkers and immune infiltration in ulcerative colitis: A comprehensive bioinformatics analysis and experimental validation

Ulcerative colitis (UC) is a heterogeneous autoimmune condition. PANoptosis, a new form of programmed cell death, plays a role in inflammatory diseases. This study aimed to identify differentially expressed PANoptosis-related genes (PRGs) involved in immune dysregulation in UC. Three key PRGs-BIRC3, MAGED1, and PSME2 were found using weighted gene co-expression network analysis (WGCNA) and machine learning. Immune infiltration analysis revealed that these key PRGs were associated with neutrophils, CD8+ T cells, activated CD4 T cells, and NK cells. Moreover, these key PRGs were significantly enriched in pathways related to inflammatory bowel disease, the IL-17 signaling pathway, and NOD-like receptor signaling pathway. The expression levels of the key PRGs were validated in various datasets, animal models, and UC intestinal tissue samples. Our findings confirmed the involvement of PANoptosis in UC and predict hub genes and immune characteristics, providing new insights for further investigations into UC pathogenic mechanisms and therapeutic strategies.

Predicting immunotherapy prognosis and targeted therapy sensitivity of colon cancer based on a CAF-related molecular signature

The role of cancer-associated fibroblasts (CAFs) in modulating the tumor microenvironment (TME) is gaining attention, yet their impact on prognosis and therapeutic response in colon cancer remains unclear. Here, we identified genes associated with CAF infiltration via weighted gene co-expression network analysis (WGCNA) utilizing data from The Cancer Genome Atlas (TCGA) and GSE39582 cohorts. Univariate Cox regression and least absolute shrinkage and selection operator (LASSO) regression analyses were used to construct CAF molecular signatures (CAFscore). Patients were categorized into high and low CAFscore groups to analyze clinicopathological traits, somatic mutations, immune evasion, and treatment responses. In this study, a total of 244 genes were correlated with CAF infiltration, with 11 linked to overall survival. Notably, FSTL3, CRIP2, and SLC2A3 were selected for the CAFscore. A higher CAFscore was associated with poorer prognoses, increased malignancy, and therapeutic resistance, particularly among patients with high tumor mutation burden and microsatellite instability. Furthermore, elevated FSTL3 expression was associated with reduced CD8+ T cell infiltration, indicating a suppressive TME. Mechanistically, CAFs may promote immune evasion via NAMPT ligand-receptor interactions based on single-cell RNA sequencing data. Thus, the CAFscore is crucial for personalizing treatment strategies and identifying patients who require more aggressive management.

Identification of crucial genes for polycystic ovary syndrome and atherosclerosis through comprehensive bioinformatics analysis and machine learning

OBJECTIVE

To identify potential biomarkers in patients with polycystic ovary syndrome (PCOS) and atherosclerosis, and to explore the common pathologic mechanisms between these two diseases in response to the increased risk of cardiovascular diseases in patients with PCOS.

METHODS

PCOS and atherosclerosis data sets were downloaded from the GEO database, and their differentially expressed genes were identified. Weighted gene co-expression network analysis was used to obtain intersection genes, and then protein-protein interaction and functional enrichment analysis were performed. Machine learning algorithms were used to select the key genes, which were then validated through external data sets. We constructed a nomogram to predict the risk of atherosclerosis in women with PCOS. Finally, the CIBERSORT algorithm was used to analyze the infiltration of immune cells in the atherosclerosis group.

RESULTS

We identified six hub genes (CD163, LAPTM5, TNFSF13B, MS4A4A, FGR, and IRF1) that exhibited excellent diagnostic value in validation data sets. Gene ontology terms and KEGG signaling pathway analysis revealed that key genes were associated with immune responses and inflammatory reactions. Abnormal immune cell infiltration was also found in the atherosclerosis group and was correlated with the six hub genes.

CONCLUSION

Common therapeutic targets of PCOS and atherosclerosis were preliminarily identified through bioinformatics analysis and machine learning techniques. These findings provide new treatment ideas for reducing the risk that PCOS will develop into atherosclerosis.

A 5-transcript signature for discriminating viral and bacterial etiology in pediatric pneumonia

Pneumonia stands as the primary cause of death among children under five, yet current diagnosis methods often result in inadequate or unnecessary treatments. Our research seeks to address this gap by identifying host transcriptomic biomarkers in the blood of children with definitive viral and bacterial pneumonia. We performed RNA sequencing on 192 prospectively collected whole blood samples, including 38 controls and 154 pneumonia cases, uncovering a 5-transcript signature (genes FAM20A, BAG3, TDRD9, MXRA7, and KLF14) that effectively distinguishes bacterial from viral pneumonia (area under the curve (AUC): 0.95 [0.88-1.00]). Initial validation using combined definitive and probable cases yielded an AUC of 0.87 [0.77-0.97], while full validation in a new prospective cohort of 32 patients achieved an AUC of 0.92 [0.83-1.00]. This robust signature holds significant potential to enhance diagnostics accuracy for pediatric pneumonia, reducing diagnostic delays and unnecessary treatments and potentially transforming clinical practice.

Noncoding variants and sulcal patterns in congenital heart disease: Machine learning to predict functional impact

Neurodevelopmental impairments associated with congenital heart disease (CHD) may arise from perturbations in brain developmental pathways, including the formation of sulcal patterns. While genetic factors contribute to sulcal features, the association of noncoding de novo variants (ncDNVs) with sulcal patterns in people with CHD remains poorly understood. Leveraging deep learning models, we examined the predicted impact of ncDNVs on gene regulatory signals. Predicted impact was compared between participants with CHD and a jointly called cohort without CHD. We then assessed the relationship of the predicted impact of ncDNVs with their sulcal folding patterns. ncDNVs predicted to increase H3K9me2 modification were associated with larger disruptions in right parietal sulcal patterns in the CHD cohort. Genes predicted to be regulated by these ncDNVs were enriched for functions related to neuronal development. This highlights the potential of deep learning models to generate hypotheses about the role of noncoding variants in brain development.

Peripheral blood mononuclear cell transcriptomic trajectories reveal dynamic regulation of inflammatory actors in delirium

Delirium is a neurologic syndrome characterized by inattention and cognitive impairment frequently encountered in the medically ill. Peripheral inflammation is a key trigger of delirium, but the patient-specific immune responses associated with delirium development and resolution are unknown. This retrospective cohort study of prospectively collected biospecimens examines RNA sequencing from peripheral blood mononuclear cells of adults hospitalized for COVID-19 to better understand patient-specific factors associated with delirium (n = 64). Longitudinal transcriptomic analyses highlight persistent immune dysregulation in delirium, marked by increasing expression trajectories of genes linked to innate immune pathways, including complement activation, cytokine production, and monocyte/macrophage recruitment. Genes involved adaptive immunity showed a declining trajectory over time in patients with delirium. Although corticosteroid treatment suppressed some aspects of immune hyperactivation, aberrant responses contributing to delirium were exacerbated. Delirium resolution was characterized by normalization of key transcripts such as CCL2 and innate immune markers. Novel associations with delirium were found in genes related to stress granule assembly and DUSP2 and KLF10 , which mediate T-cell responses. These findings provide insights into the peripheral immune responses accompanying delirium and their modulation by corticosteroids. Future trials targeting aberrant inflammatory responses may mitigate the severe outcomes associated with delirium due to COVID19.

Alterations in bile acid metabolites associated with pathogenicity and IVIG resistance in Kawasaki disease

Background

Kawasaki disease (KD) primarily affects children as an acute systemic vasculitis. Numerous studies indicated an elevated risk of cardiovascular disease due to metabolic disturbances. Despite this knowledge, the specific metabolic modes involved in KD remain unclear.

Methods

We examined the metabolome of individuals with 108 KD and 52 non-KD controls (KD vs. nKD) by ultraperformance liquid chromatography (UPLC) and tandem mass spectrometry (MS).

Results

Differential analysis uncovered the disturbed production of bile acids and lipids in KD. Furthermore, we investigated the impact of treatment, intravenous immunoglobulin (IVIG) resistance, and coronary artery (CA) occurrence on the metabolome. Our findings suggested that IVIG treatment alters the lipid and amino acid metabolism of KD patients. By orthogonal projections to latent structures discriminant analysis (OPLS-DA), there was no significant difference between the coronary injury groups and non-coronary injury groups, and IVIG resistance didn't appear to cause the metabolic change in KD patients.

Conclusions

Patients with KD exhibit metabolic abnormalities, particularly in bile acids and lipids. IVIG interventions may partially ameliorate these lipid abnormalities.

A system genetics analysis uncovers the regulatory variants controlling drought response in wheat

Plants activate a variable response to drought stress by modulating transcription of key genes. However, our knowledge of genetic variations governing gene expression in response to drought stress remains limited in natural germplasm. Here, we performed a comprehensive analysis of the transcriptional variability of 200 wheat accessions in response to drought stress by using a systems genetics approach integrating pan-transcriptome, co-expression networks, transcriptome-wide association study (TWAS), and expression quantitative trait loci (eQTLs) mapping. We identified 1621 genes and eight co-expression modules significantly correlated with wheat drought tolerance. We also defined 620 664 and 654 798 independent eQTLs associated with the expression of 17 429 and 18 080 eGenes under normal and drought stress conditions. Focusing on dynamic regulatory variants, we further identified 572 eQTL hotspots and constructed transcription factors governed drought-responsive network by the XGBoost model. Subsequently, by combining with genome-wide association study (GWAS), we uncovered a 369-bp insertion variant in the TaKCS3 promoter containing multiple cis-regulatory elements recognized by eQTL hotspot-associated transcription factors that enhance its transcription. Further functional analysis indicated that elevating TaKCS3 expression affects cuticular wax composition to reduce water loss during drought stress, and thereby increase drought tolerance. This study sheds light on the genome-wide genetic variants that influence dynamic transcriptional changes during drought stress and provides a valuable resource for the mining of drought-tolerant genes in the future.

Histone lactylation regulates PRKN-Mediated mitophagy to promote M2 Macrophage polarization in bladder cancer

BACKGROUND

Bladder cancer (BCa), particularly muscle-invasive bladder cancer (MIBC), is associated with poor prognosis, partly because of immune evasion driven by M2 tumor-associated macrophages (TAMs). Understanding the regulatory mechanisms of M2 macrophage polarization via PRKN-mediated mitophagy and histone lactylation (H3K18la) is crucial for improving treatment strategies.

METHODS

A single-cell atlas from 46 human BCa samples was constructed to identify macrophage subpopulations. Bioinformatics analysis and experimental validation, including ChIP-seq and lactylation modulation assays, were used to investigate the role of PRKN in M2 macrophage polarization and its regulation by H3K18la.

RESULTS

Single-cell analysis revealed distinct macrophage subpopulations, including M1 and M2 types. PRKN was identified as a critical regulator of mitophagy in M2 macrophages, supporting their immunosuppressive function. Bulk RNA-seq and gene intersection analysis revealed a set of mitophagy-related macrophage polarization genes (Mito_Macro_RGs) enriched in mitophagy and immune pathways. Pseudotime analysis revealed that PRKN was upregulated during the M1-to-M2 transition. siRNA-mediated PRKN knockdown impaired M2 polarization, reducing the expression of CD206 and ARG1. ChIP-seq and histone lactylation modulation confirmed that H3K18la enhanced PRKN expression, promoting mitophagy and M2 polarization and thereby facilitating immune suppression and tumor progression.

CONCLUSIONS

Histone lactylation regulated PRKN-mediated mitophagy, promoting M2 macrophage polarization and contributing to immune evasion in BCa.

Stress-responsive transcription factor families are key components of the core abiotic stress response in maize

Abiotic stresses, including drought, salt, heat, cold, flooding, and low nitrogen, have devastating impacts on agriculture and are increasing in frequency globally due to climate change. Plants can experience multiple abiotic stresses simultaneously or sequentially within a single growing season, and combinatorial stresses elicit shared or overlapping molecular and physiological responses. Here, we searched for core stress responsive genes in maize across diverse abiotic stressors through meta-analysis of public RNAseq data. Our analysis revealed significant heterogeneity in gene expression across datasets due to factors such as tissue type, genotype, and experimental conditions, which we mitigated through batch correction. Using nearly 1,900 RNAseq samples with both traditional set operations and a novel random forest machine learning approach, we identified a core set of 744 stress-responsive genes across the six stresses. These core genes are enriched in transcription factors, including stress-responsive families such as AP2/ERF-ERF, NAC, bZIP, HSF, and C2C2-CO-like. Co-expression network analysis demonstrated that these core TFs are co-expressed with stress-specific peripheral genes, supporting their role in regulating both generalized and stress-specific responses. Our results suggest that maize employs a conserved yet flexible transcriptional strategy to respond to abiotic stresses, with core TFs acting as potential regulators of both universal and stress-specific pathways. These findings provide a valuable resource for understanding stress tolerance mechanisms and for guiding future breeding and engineering efforts to enhance maize resilience under climate change.

Exploring the dynamic responses of group 3 innate lymphoid cells at different times in response to LPS challenge

Group 3 innate lymphoid cells (ILC3s) have clear roles in regulating mucosal immunity and tissue homeostasis in the intestine, though the immunological functions in lungs remain unclear. This study aimed to demonstrate the dynamic responses of ILC3s to acute inflammation upon LPS challenge. Microarray data and single-cell RNA sequencing (scRNA-seq) data obtained from the GEO database were combined to analyze the function of ILC3 subset, confirmed by flow cytometry assay and qRT-PCR. The gene enrichment analysis of intersected genes identified between microarray data in bacterial pneumonia and single-cell RNA sequencing of intestinal ILC3s were closely related to TNF-alpha effects on cytokine activity, cell motility and apoptosis pathway, indicating the possibility of intestinal ILC3s migration to the lung. Furthermore, the cellular landscapes of ILC3s in lung and intestine at different times after pulmonary infection exhibited varied ILC3 statuses. ILC3s in lung expanded a lot at 48 h while intestinal ILC3s decreased at 72 h response to LPS challenge, with higher expression of marked genes related to TNF-alpha effects on cytokine activity, cell motility and apoptosis pathway. The main findings in our study may serve as valuable resources for understanding the roles that ILC3s play upon LPS challenge, which may offer opportunities for translating ILC3s as therapeutic targets to regulate LPS-induced pulmonary inflammation.

Uridine Phosphorylase 1 as a Biomarker Associated with Glycolysis in Acute Lung Injury

The specific pathogenesis of acute lung injury (ALI) is complex and not yet clear, and the clinical treatment methods are relatively limited. It is of great clinical significance to explore its pathogenesis and effective molecular targets. Here, we identified an ALI biomarker (UPP1) associated with uridine metabolism by a systematic bioinformatics approach. It was also confirmed to be associated with the glycolytic pathway in the mouse ALI model. In addition, drug sensitivity analysis based on the CMAP database identified three UPP1-associated drugs (CAY10585, XL147 and IOX2) that may be useful in the treatment of ALI. Molecular docking and molecular dynamics simulations further confirmed the stability of the binding between UPP1 and the three drugs. In conclusion, this study confirms that the uridine metabolism gene UPP1 associated with glycolysis is a key biomarker of ALI and provides valuable insights into the potential application of CAY10585, XL147 and IOX2 in ALI.

Time-resolved oxidative signal convergence across the algae-embryophyte divide

The earliest land plants faced a significant challenge in adapting to environmental stressors. Stress on land is unique in its dynamics, entailing swift and drastic changes in light and temperature. While we know that land plants share with their closest streptophyte algal relatives key components of the genetic makeup for dynamic stress responses, their concerted action is little understood. Here, we combine time-course stress profiling using photophysiology, transcriptomics on 2.7 Tbp of data, and metabolite profiling analyses on 270 distinct samples, to study stress kinetics across three 600-million-year-divergent streptophytes. Through co-expression analysis and Granger causal inference we predict a gene regulatory network that retraces a web of ancient signal convergences at ethylene signaling components, osmosensors, and chains of major kinases. These kinase hubs already integrated diverse environmental inputs since before the dawn of plants on land.

Transgressive expression and dosage effect of A09 chromosome genes and their homoeologous genes influence the flowering time of resynthesized allopolyploid Brassica napus

BACKGROUND

The genomes of allopolyploids newly formed through hybridization and polyploidization exhibit substantial changes including those at genetic and epigenetic levels. These alterations may affect their gene expression patterns, leading to nonadditive gene expression. Currently, only a few reports are available on the impact of nonadditive gene expressions on traits.

RESULTS

Using six isogenic resynthesized Brassica napus lines across the first 10 generations, we studied the impact of gene expression patterns on flowering time. The expression levels of a group of genes, located on chromosome A09, were significantly positively correlated with flowering time. According to the expression analysis, the expression levels of the homologous pairs of 139 genes on chromosome A09 were lower in allopolyploids than in their diploid parents, which indicated a phenomenon of transgressive expression. Additionally, independent subgenomic analysis of homoeologous gene pairs on chromosome A09 of the allopolyploids demonstrated that the gene expression levels of B. napus subgenome A (BnA) and subgenome C (BnC) were similar. However, in two aneuploids carrying monosomic or trisomic A09 chromosome, the gene expression levels of BnA were lower or higher than those of BnC, and the corresponding flowering times of these two aneuploids were earlier and later, respectively.

CONCLUSIONS

These findings indicate that changes in gene dosage introduce biases in the expression of homoeologous genes. Moreover, upregulation or downregulation of homoeologous gene expression on a single chromosome partially alters the flowering time of the newly formed allopolyploid B. napus, which is of great significance for horticultural applications and future research on genetic mechanisms.

Pharmacogenomics-based subtype decoded implications for risk stratification and immunotherapy in pancreatic adenocarcinoma

BACKGROUND

With fatal malignant peculiarities and poor survival rate, outcomes of pancreatic adenocarcinoma (PAAD) were frustrated by non-response and even resistance to therapy due to heterogeneity across clinical patients. Nevertheless, pharmacogenomics has been developed for individualized-treatment and still maintains obscure in PAAD.

METHODS

A total of 964 samples from 10 independent multi-center cohorts were enrolled in our study. With drug response data from the profiling of relative inhibition simultaneously in mixtures (PRISM) and genomics of drug sensitivity in cancer (GDSC) databases, we established and validated multidimensionally three pharmacogenomics-classified subtypes using non-negative matrix factorization (NMF) and nearest template prediction (NTP) algorithms, separately. The heterogenous biological characteristics and precision medicine strategies among subtypes were further investigated.

RESULTS

Three pharmacogenomics-classified subtypes after stable and reproducible validation, distinguished in six aspects of prognosis, biological peculiarities, immune landscapes, genomic variations, immunotherapy and individualized management strategies. Subtype 2 was close to immunocompetent phenotype and projected to immunotherapy; Subtype 3 held most favorable outcomes and metabolic pathways distinctively, promising to be treated with first-line agents. Subtype 1 with worst prognosis, was anticipated to chromosome instability (CIN) phenotype and resistant to chemotherapeutic agents. In addition, ITGB6 contributed to subtype 1 resistance to 5-fluorouracil, and knockdown of ITGB6 enhanced sensitivity to 5-fluorouracil in in vitro experiments. Ultimately, appropriate clinical stratified treatments were assigned to corresponding subtypes according to pharmacogenomic transcripts. Some limitations were not taken into account, thus needs to be supported by more research.

CONCLUSION

A span-new molecular subtype exploited for PAAD uncovered an insight into precise medication on ground of pharmacogenomics, and highly refined multiple clinical management strategies for specific patients.

Integrated metabolomics and transcriptomics analyses reveal aluminum-activated malate transporter CsALMT14 contributing to fluoride tolerance in F-hyperaccumulator Camellia sinensis

Tea plants (Camellia sinensis) tend to accumulate excessive amounts of fluoride (F) compared to other plants. However, the specific mechanisms of F tolerance or detoxification in tea plants remain insufficiently understood. This study employed ultra-high performance liquid chromatography quadrupole time-of-flight mass spectrometry (UHPLC-Q-TOF/MS) to identify critical metabolites involved in F detoxification across two distinct tea plant cultivars with varying F accumulation capacities. Notably, malic acid and citric acid emerged as key metabolites that differentially accumulated under F-stressed conditions. Weighted gene co-expression network analysis indicated that C. sinensis aluminum (Al)-activated malate transporter genes CsALMT9 and CsALMT14 may be implicated in the response to F stress in C. sinensis. Further investigations revealed that CsALMT14 localized to the plasma membrane and exhibited significant transcriptional induction upon exposure to F toxicity. Moreover, heterologous expression of CsALMT14 enhanced F tolerance by mitigating F accumulation in transgenic yeast and Arabidopsis thaliana. Additionally, silencing of CsALMT14 by antisense oligodeoxynucleotide and virus-induced gene silencing reduced the content of malic acid but increased the accumulation of citric acid in tea plants, which might be attributed to the down-regulated expression of malic acid synthesis- and citric acid degradation-related genes. These findings suggest that CsALMT14 confers tolerance to F toxicity through F efflux and regulation of malic acid and citric acid metabolism-related gene expression, thereby providing a novel strategy for F detoxification in tea plants.

Cell type transcriptomics reveal shared genetic mechanisms in Alzheimer's and Parkinson's disease

Historically, Alzheimer's disease (AD) and Parkinson's disease (PD) have been investigated as two distinct disorders of the brain. However, a few similarities in neuropathology and clinical symptoms have been documented over the years. Traditional single gene-centric genetic studies, including GWAS and differential gene expression analyses, have struggled to unravel the molecular links between AD and PD. To address this, we tailor a pattern-learning framework to analyze synchronous gene co-expression at sub-cell-type resolution. Utilizing recently published single-nucleus AD (70,634 nuclei) and PD (340,902 nuclei) datasets from postmortem human brains, we systematically extract and juxtapose disease-critical gene modules. Our findings reveal extensive molecular similarities between AD and PD gene cliques. In neurons, disrupted cytoskeletal dynamics and mitochondrial stress highlight convergence in key processes; glial modules share roles in T-cell activation, myelin synthesis, and synapse pruning. This multi-module sub-cell-type approach offers insights into the molecular basis of shared neuropathology in AD and PD.

Gene expression atlas of the Colorado potato beetle (Leptinotarsa decemlineata)

The Colorado potato beetle (CPB) is a major pest of potato crops, known for its remarkable ability to develop resistance to more than 50 pesticides. For decades, CPB has served as a model species for studying insecticide resistance, insect physiology, diapause, reproduction, and evolution. However, research progress on CPB has been hindered by the lack of comprehensive genomic and transcriptomic resources. Here, leveraging a recently established chromosome-level genome assembly, we constructed a gene expression atlas of CPB using transcriptomic data from 61 samples representing major organs and developmental stages. By integrating short- and long-read sequencing technologies, we enhanced the genome annotation and identified 6,623 additional genes that were previously undetected. Furthermore, we developed a web portal to facilitate the search and visualization of the gene expression atlas, providing an accessible resource for the research community. The CPB gene expression atlas offers valuable tools and comprehensive data that will accelerate future research in pest control and insect biology.

Identification of core candidate genes responding to Verticillium wilt (Verticillium dahliae) in cotton via integrated methods

Cotton is a vital natural fiber and oil crop, yet it is severely affected by verticillium wilt (VW), known as the 'cancer' of cotton, hindering the industry's sustainable development. Upland cotton, which is widely cultivated, lacks effective resistance to VW, while most sea island cotton shows strong resistance. In this study, an F2:3 population was constructed by hybridizing the verticillium wilt-resistant island cotton variety 'Hai7124' with the susceptible variety 'Xinhai14'. Using Bulked Segregant Analysis (BSA-seq), we identified 10 genetic intervals significantly associated with resistance. Additionally, two pathogenic strains of Verticillium dahliae, Vd592 (a strong pathogenic type) and VdKT (a weak pathogenic type), were used to infect the 'Hai7124' and 'Xinhai14' for RNA-seq analysis, focusing on differentially expressed genes and signaling pathways in samples treated with different resistant and susceptible materials and infected with different pathogens. By integrating BSA-seq and RNA-seq association analyses, the candidate gene range was further refined. Five genes (GBMYB102, GBWRKY65, GBRDA2, GBSOT16, and GBCWINV1) were validated through virus-induced gene silencing (VIGS). The results revealed that reduced expression of these genes significantly decreases plant disease resistance and leads to a reduction in the activity of defense-related enzymes (such as SOD, CAT or PAL) and secondary metabolites (including lignin or flavonoids). Based on the preliminary functional analysis of these candidate genes, we speculate that redox metabolism and secondary metabolites play crucial roles in the resistance of island cotton to Verticillium wilt, and that the resistance of island cotton to verticillium wilt is the result of multiple genes working together.

Comprehensive molecular analysis of 26 newly established human pancreatic ductal adenocarcinoma cell lines reveals two clusters with variating drug sensitivities

BACKGROUND

Pancreatic ductal adenocarcinoma (PDAC) is a malignant form of cancer with the worst survival rate and an extremely low rate of response to treatments. The development and molecular characterization of pancreatic cancer cell lines (PCCLs) are essential for studying the biology of highly aggressive pancreatic adenocarcinoma.

METHODS

We applied whole exome sequencing (WES) and RNA-seq to identify molecular characteristics of 26 newly established PCCLs. Eighteen clinically relevant anti-cancer drugs were used to assess highly heterogeneous drug responses across the 26 cell lines.

RESULTS

We confirmed that common driver mutations of PDAC were well retained in our cell lines through WES analysis. Transcriptomic analysis identified two representative clusters that correlated with responses to certain drugs. By using Moffitt's classification method, the two clusters, C1 and C2, showed comparable expression patterns to "Basal-like" and "Classical" types, respectively. Drug screening results showed varying responses among different cell lines. In our cohort, C2 displayed greater sensitivity to anti-cancer drugs compared to C1. Furthermore, drugs targeting similar molecular pathways exhibited corresponding reactions among cell lines.

CONCLUSIONS

Our results underscored that transcriptomic features of pancreatic cancer correlate with drug sensitivity rather than with the effects of targeted drugs. Cell lines are useful in vitro model systems for studying the molecular mechanisms of PDAC.

Murine Model Insights: Identifying Dusp15 as a Novel Biomarker for Diabetic Cardiomyopathy Uncovered Through Integrated Omics Analysis and Experimental Validation

Background

Diabetic Cardiomyopathy (DCM) is a heart condition that arises specifically from diabetes mellitus, characterized by cardiac dysfunction in the absence of coronary artery disease or hypertension. The prevalence of DCM is rising in tandem with the global increase in diabetes, necessitating the development of early diagnostic markers and therapeutic targets. This study integrates bioinformatics analysis with experimental validation to identify potential biomarkers for DCM.

Methods

We performed gene expression data mining from the Gene Expression Omnibus (GEO) database. We employed Weighted Gene Co-expression Network Analysis (WGCNA) coupled with machine learning techniques to sift through hub differentially expressed genes (DEGs). Functional enrichment and protein-protein interaction (PPI) network analysis were also conducted to pinpoint key genes functions. Subsequent in vitro and in vivo experiments were performed to validate the findings.

Results

Our analysis revealed six core genes significantly associated with DCM. The expression of Dusp15 was notably downregulated and validated in both high-glucose cultured cardiomyocytes and DCM animal models, suggesting its potential role in DCM pathogenesis.

Conclusion

The integration of bioinformatics with experimental approaches has identified Dusp15 as a promising candidate for a DCM biomarker, offering valuable insights for early diagnosis and potential therapeutic development.

Comparative transcriptomic and hormone analyses reveal the molecular mechanisms regulating almond flowering stages

Almond (Prunus dulcis) is cultivated worldwide and is valued for its flavourful seeds, which have significant economic value. In China, domestically cultivated almonds are primarily found in Shache County, Kashgar, Xinjiang. However, in this region, the flowering stages generally begin too early, such that almond blooms are vulnerable to low spring temperatures, which can damage or kill flower organs and severely affect fruit yield. To date, there have been no studies on the regulatory mechanisms involved in almond flowering. Therefore, we conducted transcriptomic and hormone analyses on six flower developmental stages in two almond cultivars-the primary Chinese cultivar Wanfeng and the primary American cultivar Nonpareil-to determine the molecular mechanisms regulating flowering. In Shache County, Wanfeng almond completed its entire flowering stage in just 16 days, whereas Nonpareil required 43 days. The results of the GO and KEGG enrichment analyses of the differentially expressed genes revealed that Nonpareil almond requires more photosynthesis and more nutrients to complete the flowering process. The photoperiod pathway and time-ordered gene coexpression network revealed that four flowering time genes, CDFs, GA2ox8, IAA7, and WNK1, exhibited temporal expression patterns during the FP5 stage, which inhibited the development time needed for the two almond cultivars. Cytokinin-type hormones presented stronger differential accumulation patterns between the flowering stages of the two almond cultivars. We cloned a pair of PdSVP and PdAGL15 genes that interact in the nucleus and may regulate the developmental progress of the two cultivars during the bud stage. Finally, we integrated several key findings to construct a flowchart depicting the delayed flowering development of almond cultivars. Changes in environmental conditions significantly influence the delayed flowering of Nonpareil almond. This study employed multiomics strategies to reveal the complex differential molecular mechanisms of flowering development in two almond cultivars, providing a reference for the subsequent breeding of high-quality late-flowering almond cultivars in Xinjiang.

Comprehensive analysis of aging-related gene expression patterns and identification of potential intervention targets

PURPOSE

This study aims to understand the molecular mechanisms underlying the aging process and identify potential interventions to mitigate age-related decline and diseases.

METHODS

This study utilized the GSE168753 dataset to conduct comprehensive differential gene expression analysis and co-expression module analysis. Machine learning and Mendelian randomization analyses were employed to identify core aging-associated genes and potential drug targets. Molecular docking simulations and mediation analysis were also performed to explore potential compounds and mediators involved in the aging process.

RESULTS

The analysis identified 4164 differentially expressed genes, with 1893 upregulated and 2271 downregulated genes. Co-expression analysis revealed 21 modules, including both positively and negatively correlated modules between older age and younger age groups. Further exploration identified 509 aging-related genes with distinct biological functions. Machine learning and Mendelian randomization analyses identified eight core genes associated with aging, including DPP9, GNAZ, and RELL2. Molecular docking simulations suggested resveratrol, folic acid, and ethinyl estradiol as potential compounds capable of attenuating aging through modulation of RELL2 expression. Mediation analysis indicated that eosinophil counts and neutrophil count might act as mediators in the causal relationship between genes and aging-related indicators.

CONCLUSION

This comprehensive study provides valuable insights into the molecular mechanisms of aging and offers important implications for the development of anti-aging therapeutics. Key Messages What is already known on this topic - Prior research outlines aging's complexity, necessitating precise molecular targets for intervention. What this study adds - This study identifies novel aging-related genes, potential drug targets, and therapeutic compounds, advancing our understanding of aging mechanisms. How this study might affect research, practice, or policy - Findings may inform targeted therapies for age-related conditions, influencing future research and clinical practices.