Pan-cancer scRNA-seq analysis reveals immunological and diagnostic significance of the peripheral blood mononuclear cells.

Peripheral blood mononuclear cells (PBMCs) reflect systemic immune response during cancer progression. However, a comprehensive understanding of the composition and function of PBMCs in cancer patients is lacking, and the potential of these features to assist cancer diagnosis is also unclear. Here, the compositional and status differences between cancer patients and healthy donors in PBMCs were investigated by single-cell RNA sequencing (scRNA-seq), involving 262,025 PBMCs from 68 cancer samples and 14 healthy samples. We observed an enhanced activation and differentiation of most immune subsets in cancer patients, along with reduction of naïve T cells, expansion of macrophages, impairment of NK cells and myeloid cells, as well as tumor promotion and immunosuppression. Based on characteristics including differential cell type abundances and/or hub genes identified from weight gene co-expression network analysis (WGCNA) modules of each major cell type, we applied logistic regression to construct cancer diagnosis models. Furthermore, we found that the above models can distinguish cancer patients and healthy donors with high sensitivity. Our study provided new insights into using the features of PBMCs in non-invasive cancer diagnosis.

PbGBF3 enhances salt response in pear by upregulating PbAPL2 and PbSDH1 and reducing ABA-mediated salt sensitivity.

Pear is a widely cultivated fruit crop, but its distribution and sustainable production are significantly limited by salt stress. This study used RNA-Seq time-course analysis, WGCNA, and functional enrichment analysis to uncover the molecular mechanisms underlying salt stress tolerance in Pyrus ussuriensis. We identified an ABA-related regulatory module, PbGBF3-PbAPL2-PbSDH1, as crucial in this response. PbGBF3, a bZIP transcription factor, enhances salt tolerance by upregulating PbAPL2 and PbSDH1. Overexpression of PbGBF3 improved salt tolerance in Pyrus communis calli and Arabidopsis, while silencing it reduced tolerance in Pyrus betulifolia. Functional assays showed that PbGBF3 binds to the promoters of PbAPL2 and PbSDH1, increasing their expression. PbAPL2 and PbSDH1, key enzymes in starch synthesis and the sorbitol pathway, respectively, enhance salt tolerance by increasing AGPase activity, soluble sugar content, and SDH activity, improving ROS scavenging and ion balance. Our findings suggest that the PbGBF3-PbAPL2 and PbGBF3-PbSDH1 modules positively regulate salt tolerance by enhancing ABA signaling and reducing ABA-mediated growth inhibition. These insights provide a foundation for developing salt-tolerant pear cultivars.

Ancient secretory pathways contributed to the evolutionary origin of an ecologically impactful bioluminescence system.

Evolutionary innovations in chemical secretion - such as the production of secondary metabolites, pheromones, and toxins - profoundly impact ecological interactions across a broad diversity of life. These secretory innovations may involve a "legacy-plus-innovation" mode of evolution, whereby new biochemical pathways are integrated with conserved secretory processes to create novel products. Among secretory innovations, bioluminescence is important because it evolved convergently many times to influence predator-prey interactions, while often producing courtship signals linked to increased rates of speciation. However, whether or not deeply conserved secretory genes are used in secretory bioluminescence remains unexplored. Here, we show that in the ostracod Vargula tsujii, the evolutionary novel c-luciferase gene is co-expressed with many conserved genes, including those related to toxin production and high-output protein secretion. Our results demonstrate that the legacy-plus-innovation mode of secretory evolution, previously applied to sensory modalities of olfaction, gustation, and nociception, also encompasses light-producing signals generated by bioluminescent secretions. This extension broadens the paradigm of secretory diversification to include not only chemical signals but also bioluminescent light as an important medium of ecological interaction and evolutionary innovation.

Distinct transcriptional alterations distinguish Lewy body disease from Alzheimer's disease.

Lewy body dementia and Alzheimer's disease (AD) are leading causes of cognitive impairment, characterized by distinct but overlapping neuropathological hallmarks. Lewy body disease (LBD) is characterized by alpha-synuclein aggregates in the form of Lewy bodies as well as the deposition of extracellular amyloid plaques, with many cases also exhibiting neurofibrillary tangle (NFT) pathology. In contrast, Alzheimer's disease is characterized by amyloid plaques and neurofibrillary tangles. Both conditions often co-occur with additional neuropathological changes, such as vascular disease and TDP-43 pathology. To elucidate shared and distinct molecular signatures underlying these mixed neuropathologies, we extensively analyzed transcriptional changes in the anterior cingulate cortex, a brain region critically involved in cognitive processes. We performed bulk tissue RNAseq from the anterior cingulate cortex and determined differentially expressed genes (q-value < 0.05) in control (n = 81), Lewy body disease (n = 436), Alzheimer's disease (n = 53), and pathological amyloid cases consisting of amyloid pathology with minimal or no tau pathology (n = 39). We used gene set enrichment and weighted gene correlation network analysis (WGCNA) to understand the pathways associated with each neuropathologically defined group. Lewy body disease cases had strong up-regulation of inflammatory pathways and down-regulation of metabolic pathways. The Lewy body disease cases were further subdivided into either high Thal amyloid, Braak NFT, or low pathological burden cohorts. Compared to the control cases, the Lewy body disease cohorts consistently showed up-regulation for genes involved in protein folding and cytokine immune response, as well as down-regulation of fatty acid metabolism. Surprisingly, concomitant tau pathology within the Lewy body disease cases resulted in no additional changes. Some core inflammatory pathways were shared between Alzheimer's disease and Lewy body disease but with numerous disease-specific changes. Direct comparison of Lewy body disease cohorts versus Alzheimer's disease cases revealed strong enrichment of synaptic signaling, behavior, and neuronal system pathways. Females had a stronger response overall in both Lewy body and Alzheimer's disease, with several sex-specific changes. Overall, the results identify genes commonly and uniquely dysregulated in neuropathologically defined Lewy body disease and Alzheimer's disease cases, shedding light on shared and distinct molecular pathways. Additionally, the study underscores the importance of considering sex-specific changes in understanding the complex transcriptional landscape of these neurodegenerative diseases.

Deciphering Nucleic Acid Binding Proteome of Mouse Immune Organs Reveals Hub Proteins for Aging.

Profiling the nucleic acid-binding proteins (NABPs) during aging process is critical to elucidate its roles in biological systems as well as transcriptional and translational regulation. Here, we developed a comprehensive strategy to survey the NABPs of mouse immune organs by using single cell preparation and selective capture technology-based proteomics. Our approach provided a global view of tissue NABPs from different organs under normal physiological conditions with extraction specificity of 70 to 90%. Through quantitative proteomics analysis of mouse spleen and thymus at 1, 4, 12, 24, 48, and 72 weeks, we investigated the molecular features of aging-related NABPs. A total of 2674 proteins were quantified in all six stages, demonstrating distinct and time-specific expression pattern of NABPs. Thymus and spleen exhibited unique aging signatures, and differential proteins and pathways were enriched across the mouse lifespan. Three core modules and 16 hub proteins associated with aging were revealed through weighted gene correlation network analysis. Significant candidates were screened for immunoassay verification, and six hub proteins were confirmed. The integrated strategy pertains the capability to decipher the dynamic functions of NABPs in aging physiology and benefit further mechanism research.

Identification and validation of CRLF1 and NRG1 as immune-related signatures in hypertrophic scar.

BACKGROUND: Hypertrophic scar (HTS) is a prevalent chronic inflammatory skin disorder characterized by abnormal proliferation and extracellular matrix deposition and the precise mechanisms underlying HTS remain elusive. This study aimed to identify and validate potential immune-related genes associated with hypertrophic scar formation. METHODS: Skin samples from normal (n = 12) and hypertrophic scar tissues (n = 12) were subjected to RNA-seq analysis. Differentially expressed genes (DEGs) and significant modular genes in Weighted gene Co-expression Network Analysis (WGCNA) were identified. Subsequently, functional enrichment analysis was performed on the intersecting genes. Additionally, eight immune-related genes were matched from the ImmPort database. Validation of NRG1 and CRLF1 was carried out using an external cohort (GSE136906). Furthermore, the association between these two genes and immune cells was assessed by Spearman correlation analysis. Finally, RNA was extracted from normal and hypertrophic scar samples, and RT-qPCR, Immunohistochemistry staining and Western Blot were employed to validate the expression of characteristic genes. RESULTS: A total of 940 DEGs were identified between HTS and normal samples, and 288 key module genes were uncovered via WGCNA. Enrichment analysis in key module revealed involvement in many immune-related pathways, such as Th17 cell differentiation, antigen processing and presentation and B cell receptor signaling pathway. The eight immune-related genes (IFI30, NR2F2, NRG1, ESM1, NFATC2, CRLF1, COLEC12 and IL6) were identified by matching from the ImmPort database. Notably, we observed that activated mast cell positively correlated with CRLF1 expression, while CD8 T cells exhibited a positive correlation with NRG1. The expression of NRG1 and CRLF1 was further validated in clinical samples. CONCLUSION: In this study, two key immune-related genes (CRLF1 and NRG1) were identified as characteristic genes associated with HTS. These findings provide valuable insights into the immune-related mechanisms underlying hypertrophic scar formation.

SGCP: a spectral self-learning method for clustering genes in co-expression networks.

BACKGROUND: A widely used approach for extracting information from gene expression data employs the construction of a gene co-expression network and the subsequent computational detection of gene clusters, called modules. WGCNA and related methods are the de facto standard for module detection. The purpose of this work is to investigate the applicability of more sophisticated algorithms toward the design of an alternative method with enhanced potential for extracting biologically meaningful modules. RESULTS: We present self-learning gene clustering pipeline (SGCP), a spectral method for detecting modules in gene co-expression networks. SGCP incorporates multiple features that differentiate it from previous work, including a novel step that leverages gene ontology (GO) information in a self-leaning step. Compared with widely used existing frameworks on 12 real gene expression datasets, we show that SGCP yields modules with higher GO enrichment. Moreover, SGCP assigns highest statistical importance to GO terms that are mostly different from those reported by the baselines. CONCLUSION: Existing frameworks for discovering clusters of genes in gene co-expression networks are based on relatively simple algorithmic components. SGCP relies on newer algorithmic techniques that enable the computation of highly enriched modules with distinctive characteristics, thus contributing a novel alternative tool for gene co-expression analysis.

Mining cholesterol genes from thousands of mouse livers identifies aldolase C as a regulator of cholesterol biosynthesis.

The availability of genome-wide transcriptomic and proteomic datasets is ever-increasing and often not used beyond initial publication. Here, we applied module-based coexpression network analysis to a comprehensive catalog of 35 mouse genome-wide liver expression datasets (encompassing more than 3800 mice) with the goal of identifying and validating unknown genes involved in cholesterol metabolism. From these 35 datasets, we identified a conserved module of genes enriched with cholesterol biosynthetic genes. Using a systematic approach across the 35 datasets, we identified three genes (Rdh11, Echdc1, and Aldoc) with no known role in cholesterol metabolism. We then performed functional validation studies and show that each gene is capable of regulating cholesterol metabolism. For the glycolytic gene, Aldoc, we demonstrate that it contributes to de novo cholesterol biosynthesis and regulates cholesterol and triglyceride levels in mice. As Aldoc is located within a genome-wide significant genome-wide association studies locus for human plasma cholesterol levels, our studies establish Aldoc as a causal gene within this locus. Through our work, we develop a framework for leveraging mouse genome-wide liver datasets for identifying and validating genes involved in cholesterol metabolism.

Integrated analysis of bulk and single-cell RNA-seq data reveals cell differentiation-related subtypes and a scoring system in bladder cancer.

Bladder cancer (BLCA) exhibits notable molecular heterogeneity, influencing diverse clinical outcomes. However, the molecular subtypes associated with cell differentiation-related genes (CDR) and their prognostic implications remain unexplored. Analysing two GEO single-cell datasets, we identified genes linked to cell differentiation. Utilizing these genes, we explored distinct molecular subtypes. WGCNA analysis further identified CDR-associated genes, and the CDR score system, constructed using Lasso and Cox regression, was developed. Clinical prognosis and variations in immune-related factors among patient groups were assessed. Core genes were selected and confirmed through in vitro experiments. Two BLCA subtypes related to cell differentiation were identified: Subtype B demonstrated a favourable prognosis, while Subtype A exhibited significant immune cell infiltration. The CDR score system of nine genes revealed a positive correlation between higher scores and a poorer prognosis. The comprehensive analysis uncovered a positive association between CDR genes and M2 macrophages and unresponsiveness to immune therapy. Functional experiments validated that ANXA5 downregulation influences tumour cell migration without affecting proliferation. Our study reveals distinct cell differentiation-related molecular subtypes and introduces the CDR scoring system in BLCA. ANXA5 emerges as a potential therapeutic target, offering promising avenues for personalized treatment strategies.

Unveiling the role of copper metabolism and STEAP2 in idiopathic pulmonary fibrosis molecular landscape.

Idiopathic pulmonary fibrosis (IPF) is a debilitating interstitial lung disease characterized by progressive fibrosis and poor prognosis. Despite advancements in treatment, the pathophysiological mechanisms of IPF remain elusive. Herein, we conducted an integrated bioinformatics analysis combining clinical data and carried out experimental validations to unveil the intricate molecular mechanism of IPF. Leveraging three IPF datasets, we identified 817 upregulated and 560 downregulated differentially expressed genes (DEGs). Of these, 14 DEGs associated with copper metabolism were identified, shedding light on the potential involvement of disrupted copper metabolism in IPF progression. Immune infiltration analysis revealed dysregulated immune cell infiltration in IPF, with a notable correlation between copper metabolism-related genes and immune cells. Weighted gene co-expression network analysis (WGCNA) identified a central module correlated with IPF-associated genes, among which STEAP2 emerged as a key hub gene. Subsequent in vivo and in vitro studies confirmed the upregulation of STEAP2 in IPF model. Knockdown of STEAP2 using siRNA alleviated fibrosis in vitro, suggesting potential pathway related to copper metabolism in the pathophysiological progression of IPF. Our study established a novel link between immune cell infiltration and dysregulated copper metabolism. The revelation of intracellular copper overload and upregulated STEAP2 unravelled a potential therapeutic option. These findings offer valuable insights for future research and therapeutic interventions targeting STEAP2 and associated pathways in IPF.

Identification of two key biomarkers CD93 and FGL2 associated with survival of acute myeloid leukaemia by weighted gene co-expression network analysis.

Acute myeloid leukaemia (AML) is a biologically heterogeneous haematological malignancy. This study was performed to identify the potential biomarkers for the prognosis and treatment of AML. We applied weighted gene co-expression network analysis to identify key modules and hub genes related to the prognosis of AML using data from The Cancer Genome Atlas (TCGA). In total, 1581 differentially expressed genes (1096 upregulated and 485 downregulated) were identified between AML patients and healthy controls, with the blue module being the most significant among 14 modules associated with AML morphology. Through functional enrichment analysis, we identified 217 genes in the blue module significantly enriched in 'neutrophil degranulation' and 'neutrophil activation involved in immune response' pathways. The survival analysis revealed six genes (S100A9, S100A8, HK3, CD93, CXCR2 and FGL2) located in the significantly enriched pathway that were notably related to AML survival. We validated the expression of these six genes at gene and single-cell levels and identified methylation loci of each gene, except for S100A8. Finally, in vitro experiments were performed to demonstrate whether the identified hub genes were associated with AML survival. After knockdown of CD93 and FGL2, cell proliferation was significantly reduced in U937 cell line over 5 days. In summary, we identified CD93 and FGL2 as key hub genes related to AML survival, with FGL2 being a novel biomarker for the prognosis and treatment of AML.

Exploration of shared gene signatures and molecular mechanisms between type 2 diabetes and osteoporosis.

Type 2 diabetes mellitus (T2D) and osteoporosis (OP) are systemic metabolic diseases and often coexist. The mechanism underlying this interrelationship remains unclear. We downloaded microarray data for T2D and OP from the Gene Expression Omnibus (GEO) database. Using weighted gene co-expression network analysis (WGCNA), we identified co-expression modules linked to both T2D and OP. To further investigate the functional implications of these associated genes, we evaluated enrichment using ClueGO software. Additionally, we performed a biological process analysis of the genes unique in T2D and OP. We constructed a comprehensive miRNA-mRNA network by incorporating target genes and overlapping genes from the shared pool. Through the implementation of WGCNA, we successfully identified four modules that propose a plausible model that elucidates the disease pathway based on the associated and distinct gene profiles of T2D and OP. The miRNA-mRNA network analysis revealed co-expression of PDIA6 and SLC16A1; their expression was upregulated in patients with T2D and islet ß-cell lines. Remarkably, PDIA6 and SLC16A1 were observed to inhibit the proliferation of pancreatic ß cells and promote apoptosis in vitro, while downregulation of PDIA6 and SLC16A1 expression led to enhanced insulin secretion. This is the first study to reveal the significant roles of PDIA6 and SLC16A1 in the pathogenesis of T2D and OP, thereby identifying additional genes that hold potential as indicators or targets for therapy.

Integrative analysis of single-cell embryo data reveals transcriptome signatures for the human pre-implantation inner cell mass.

As the source of embryonic stem cells (ESCs), inner cell mass (ICM) can form all tissues of the embryo proper, however, its role in early human lineage specification remains controversial. Although a stepwise differentiation model has been proposed suggesting the existence of ICM as a distinct developmental stage, the underlying molecular mechanism remains unclear. In the present study, we perform an integrated analysis on the public human preimplantation embryonic single-cell transcriptomic data and apply a trajectory inference algorithm to measure the cell plasticity. In our results, ICM population can be clearly discriminated on the dimension-reduced graph and confirmed by compelling evidences, thus validating the two-step hypothesis of lineage commitment. According to the branch probabilities and differentiation potential, we determine the precise time points for two lineage segregations. Further analysis on gene expression dynamics and regulatory network indicates that transcription factors including GSC, PRDM1, and SPIC may underlie the decisions of ICM fate. In addition, new human ICM marker genes, such as EPHA4 and CCR8 are discovered and validated by immunofluorescence. Given the potential clinical applications of ESCs, our analysis provides a further understanding of human ICM cells and facilitates the exploration of more unique characteristics in early human development.

Transcriptome analysis reveals that PbMYB61 and PbMYB308 are involved in the regulation of lignin biosynthesis in pear fruit stone cells.

Pear fruit stone cells have thick walls and are formed by the secondary deposition of lignin in the primary cell wall of thin-walled cells. Their content and size seriously affect fruit characteristics related to edibility. To reveal the regulatory mechanism underlying stone cell formation during pear fruit development and to identify hub genes, we examined the stone cell and lignin contents of 30 'Shannongsu' pear flesh samples and analyzed the transcriptomes of 15 pear flesh samples collected at five developmental stages. On the basis of the RNA-seq data, 35 874 differentially expressed genes were detected. Additionally, two stone cell-related modules were identified according to a WGCNA. A total of 42 lignin-related structural genes were subsequently obtained. Furthermore, nine hub structural genes were identified in the lignin regulatory network. We also identified PbMYB61 and PbMYB308 as candidate transcriptional regulators of stone cell formation after analyzing co-expression networks and phylogenetic relationships. Finally, we experimentally validated and characterized the candidate transcription factors and revealed that PbMYB61 regulates stone cell lignin formation by binding to the AC element in the PbLAC1 promoter to upregulate expression. However, PbMYB308 negatively regulates stone cell lignin synthesis by binding to PbMYB61 to form a dimer that cannot activate PbLAC1 expression. In this study, we explored the lignin synthesis-related functions of MYB family members. The results presented herein are useful for elucidating the complex mechanisms underlying lignin biosynthesis during pear fruit stone cell development.

Identification and core gene-mining of Weighted Gene Co-expression Network Analysis-based co-expression modules related to flood resistance in quinoa seedlings.

BACKGROUND: As an emerging food crop with high nutritional value, quinoa has been favored by consumers in recent years; however, flooding, as an abiotic stress, seriously affects its growth and development. Currently, reports on the molecular mechanisms related to quinoa waterlogging stress responses are lacking; accordingly, the core genes related to these processes were explored via Weighted Gene Co-expression Network Analysis (WGCNA). RESULTS: Based on the transcriptome data, WGCNA was used to construct a co-expression network of weighted genes associated with flooding resistance-associated physiological traits and metabolites. Here, 16 closely related co-expression modules were obtained, and 10 core genes with the highest association with the target traits were mined from the two modules. Functional annotations revealed the biological processes and metabolic pathways involved in waterlogging stress, and four candidates related to flooding resistance, specifically AP2/ERF, MYB, bHLH, and WRKY-family TFs, were also identified. CONCLUSIONS: These results provide clues to the identification of core genes for quinoa underlying quinoa waterlogging stress responses. This could ultimately provide a theoretical foundation for breeding new quinoa varieties with flooding tolerance.

Transcriptome and weighted gene co-expression network analyses reveal key genes and pathways involved in early fruit ripening in Citrus sinensis.

BACKGROUND: The fruit ripening period is an important target trait in fruit tree crop breeding programs. Thus, citrus tree breeders seek to develop extreme early ripening cultivars that allow optimization of citrus maturation periods. In this study, we explored the regulatory network involved in fruit ripening in Citrus sinensis using the 'Newhall' navel orange variety and its early-ripening mutant, 'Gannanzao'. This research will provide a basis for further research on important signaling pathways, gene functions and variety breeding of Citrus sinensis related to fruit ripening period. RESULTS: Physiological analyses suggested that early fruit ripening in 'Gannanzao' is regulated by early accumulation of abscisic acid (ABA), persistently high levels of jasmonic acid (JA), and higher sucrose content in the pericarp. Pericarp samples from 'Gannanzao' and 'Newhall' navel oranges were sampled for RNA sequencing analysis at 180, 200, and 220 days after flowering; 1430 differentially expressed genes (DEGs) were identified. Functional enrichment analysis indicated that these DEGs were mainly enriched in the plant hormone signal transduction and sugar metabolism pathways, as well as other pathways related to fruit ripening. Important DEGs associated with fruit ripening in 'Gannanzao' included genes involved in ABA and JA metabolism and signal transduction, as well as sugar metabolism. Weighted gene co-expression network analysis showed that the deep pink module had the strongest correlations with ABA content, JA content, and early ripening. Based on gene functionality and gene expression analyses of 37 genes in this module, two candidate hub genes and two ethylene response factor 13 (ERF13) genes (Cs_ont_5g000690 and Cs_ont_5g000700) were identified as key genes regulated by ABA and JA signaling. These findings will help to clarify the mechanisms that underlie early citrus fruit ripening and will lead to the development of excellent genetic resources for further breeding of extreme early-ripening varieties. CONCLUSIONS: Through analyses of the 'Newhall' navel orange cultivar and its early-ripening mutant 'Gannanzao', we identified genes involved in ABA and JA metabolism, signal transduction, and sugar metabolism that were related to fruit ripening. Among these, two ERF13 genes were inferred to be key genes in the regulation of fruit ripening. These findings provide insights into the genetic architecture related to early fruit ripening in C. sinensis.

Characterization of lncRNA and mRNA profiles in the process of repairing peripheral nerve defects with cell-matrixed nerve grafts.

BACKGROUND: Decellularized extracellular matrix (dECM) is an intriguing natural biomaterial that has garnered significant attention due to its remarkable biological properties. In our study, we employed a cell-matrixed nerve graft for the repair of sciatic nerve defects in rats. The efficacy of this approach was assessed, and concurrently, the underlying molecular regulatory mechanisms were explored to elucidate how such grafts facilitate nerve regeneration. Long noncoding RNAs (lncRNAs) regulate mRNA expression via multiple mechanisms, including post-transcriptional regulation, transcription factor effects, and competitive binding with miRNAs. These interactions between lncRNAs and mRNAs facilitate precise control of gene expression, allowing organisms to adapt to varying biological environments and physiological states. By investigating the expression profiles and interaction dynamics of mRNAs and lncRNAs, we can enhance our understanding of the molecular mechanisms through which cell-matrixed nerve grafts influence neural repair. Such studies are pivotal in uncovering the intricate networks of gene regulation that underpin this process. RESULTS: Weighted gene co-expression network analysis (WGCNA) utilizes clustering algorithms, such as hierarchical clustering, to aggregate genes with similar expression profiles into modules. These modules, which potentially correspond to distinct biological functions or processes, can subsequently be analyzed for their association with external sample traits. By correlating gene modules with specific conditions, such as disease states or responses to treatments, WGCNA enables a deeper understanding of the genetic architecture underlying various phenotypic traits and their functional implications. We identified seven mRNA modules and five lncRNA modules that exhibited associations with treatment or time-related events by WGCNA. We found the blue (mRNAs) module which displayed a remarkable enrichment in "axonal guidance" and "metabolic pathways", exhibited strong co-expression with multiple lncRNA modules, including blue (related to "GnRH secretion" and "pyrimidine metabolism"), green (related to "arginine and proline metabolism"), black (related to "nitrogen metabolism"), grey60 (related to "PPAR signaling pathway"), and greenyellow (related to "steroid hormone biosynthesis"). All of the top 50 mRNAs and lncRNAs exhibiting the strongest correlation were derived from the blue module. Validation of key molecules were performed using immunohistochemistry and qRT-PCR. CONCLUSION: Revealing the principles and molecular regulatory mechanisms of the interaction between materials and biological entities, such as cells and tissues, is a direction for the development of biomimetic tissue engineering technologies and clinically effective products.

Combined metabolome and transcriptome analysis reveal the mechanism of water stress in Ophiocordyceps sinensis.

BACKGROUND: Ophiocordyceps sinensis (O. sinensis) is the dominant bacterium in the asexual stage of Chinese cordyceps, and its growth usually suffers from water stress. Thus, simulating its ecological growth environment is crucial for artificial cultivation. This study aimed to reveal the mechanism underlying the water stress tolerance of Ophiocordyceps sinensis (O. sinensis) by combining metabolomic and transcriptome analyses to identify crucial pathways related to differentially expressed genes (DEGs) and metabolites (DEMs) involved in the response to water stress. RESULTS: Gene coexpression analysis revealed that many genes related to 'betalain biosynthesis', 'tyrosine metabolism', 'linoleic acid metabolism', 'fructose and mannose metabolism', and 'starch and sucrose metabolism' were highly upregulated after 20d-water stress. Metabolomic analysis revealed that many metabolites regulated by these genes in these metabolic pathways were markedly decreased. On the one hand, we surmised that carbohydrate metabolism and the ß-oxidation pathway worked cooperatively to generate enough acyl-CoA and then entered the TCA cycle to provide energy when exposed to water stress. On the other hand, the betalain biosynthesis and tyrosine metabolism pathway might play crucial roles in response to water stress in O. sinensis by enhancing cell osmotic potential and producing osmoregulatory substances (betaine) and antioxidant pigments (eumelanin). CONCLUSIONS: Overall, our findings provide important information for further exploration of the mechanism underlying the water stress tolerance of O. sinensis for the industrialization of artificial cultivation of Chinese cordyceps.

RNA sequencing identifies key genes involved in intramuscular fat deposition in chickens at different developmental stages.

BACKGROUND: Intramuscular fat (IMF) is an important factor in meat quality, and triglyceride (TG) and Phospholipids (PLIP), as the main components of IMF, are of great significance to the improvement of meat quality. RESULTS: In this study, we used 30 RNA sequences generated from the transcriptome of chicken breast muscle tissues at different developmental stages to construct a gene expression matrix to map RNA sequence reads to the chicken genome and identify the transcript of origin. We used weighted gene co-expression network analysis (WGCNA) and identified 27 co-expression modules, 10 of which were related to TG and PLIP. We identified 150 highly-connected hub genes related to TG and PLIP, respectively, which were found to be mainly enriched in the adipocytokine signaling pathway, MAPK signaling pathway, mTOR signaling pathway, FoxO signaling pathway, and TGF-beta signaling pathway. Additionally, using the BioMart database, we identified 134 and 145 candidate genes related to fat development in the TG-related module and PLIP-related module, respectively. Among them, RPS6KB1, BRCA1, CDK1, RPS3, PPARGC1A, ACSL1, NDUFAB1, NDUFA9, ATP5B and PRKAG2 were identified as candidate genes related to fat development and highly-connected hub genes in the module, suggesting that these ten genes may be important candidate genes affecting IMF deposition. CONCLUSIONS: RPS6KB1, BRCA1, CDK1, RPS3, PPARGC1A, ACSL1, NDUFAB1, NDUFA9, ATP5B and PRKAG2 may be important candidate genes affecting IMF deposition. The purpose of this study was to identify the co-expressed gene modules related to chicken IMF deposition using WGCNA and determine key genes related to IMF deposition, so as to lay a foundation for further research on the molecular regulation mechanism underlying chicken fat deposition.

Transcriptomic profiling and discovery of key transcription factors involved in adventitious roots formation from root cuttings of mulberry.

ARs plays a crucial role in plant morphogenesis and development. The limited and inefficient rooting of scions poses a significant challenge to the efficiency and quality of clonal propagation of forest trees in silvicultural practices. Building on previous research conducted by our team, we found that applying IBA at a concentration of 1000 mg/L significantly enhanced mulberry rooting. This study aims to uncover the molecular mechanisms underlying this effect by analyzing RNA sequencing data from mulberry phloem before and after treatment with IBA over time intervals of 10, 20, 30, and 40 days. We identified 5226 DEGs, which were then classified into GO terms and KEGG pathways, showing significant enrichment in hormone signaling processes. Using WGCNA, we identified eight co-expression modules, two of which were significantly correlated with the IBA treatment. Additionally, 18 transcription factors that potentially facilitate ARs formation in mulberry were identified, and an exploratory analysis on the cis-regulatory elements associated with these transcription factors was conducted. The findings of this study provide a comprehensive understanding of the mechanisms of ARs in mulberry and offer theoretical support for the discovery and utilization of exceptional genetic resources within the species.