WGCNA: an R package for weighted correlation network analysis

Genome-wide identification of Ankyrin (ANK) repeat gene families in three Dendrobium species and the expression of ANK genes in D. officinale under gibberellin and abscisic acid treatments

BACKGROUND

Dendrobium Sw. represents one of the most expansive genera within the Orchidaceae family, renowned for its species' high medicinal and ornamental value. In higher plants, the ankyrin (ANK) repeat protein family is characterized by a unique ANK repeat domain, integral to a plethora of biological functions and biochemical activities. The ANK gene family plays a pivotal role in various plant physiological processes, including stress responses, hormone signaling, and growth. Hence, investigating the ANK gene family and identifying disease-resistance genes in Dendrobium is of paramount importance.

RESULTS

This research identified 78 ANK genes in Dendrobium officinale Kimura et Migo, 77 in Dendrobium nobile Lindl., and 58 in Dendrobium chrysotoxum Lindl. Subsequently, we conducted comprehensive bioinformatics analyses on these ANK gene families, encompassing gene classification, chromosomal localization, phylogenetic relationships, gene structure and motif characterization, cis-acting regulatory element identification, collinearity assessment, protein-protein interaction network construction, and gene expression profiling. Concurrently, three DoANK genes (DoANK14, DoANK19, and DoANK47) in D. officinale were discerned to indirectly activate the NPR1 transcription factor in the ETI system via SA, thereby modulating the expression of the antibacterial PR gene. Hormonal treatments with GA3 and ABA revealed that 17 and 8 genes were significantly up-regulated, while 4 and 8 genes were significantly down-regulated, respectively. DoANK32 was found to localize to the ArfGAP gene in the endocytosis pathway, impacting vesicle transport and the polar movement of auxin.

CONCLUSION

Our findings provide a robust framework for the taxonomic classification, evolutionary analysis, and functional prediction of Dendrobium ANK genes. The three highlighted ANK genes (DoANK14, DoANK19, and DoANK47) from D. officinale may prove valuable in disease resistance and stress response research. DoANK32 is implicated in the morphogenesis and development of D. officinale through its role in vesicular transport and auxin polarity, with subcellular localization studies confirming its presence in the nucleus and cell membrane. ANK genes displaying significant expression changes in response to hormonal treatments could play a crucial role in the hormonal response of D. officinale, potentially inhibiting its growth and development through the modulation of plant hormones such as GA3 and ABA.

GPR65 contributes to constructing immunosuppressive microenvironment in glioma

Glioma, especially glioblastoma patients, present highly heterogeneous and immunosuppressive microenvironment, leading to their poor response to treatment and survival. Targeting the tumor microenvironment is considered a promising therapeutic strategy. M2 macrophages are highly infiltrated in glioma tissue, even up to 50% of the total number of bulk tissue cells. Here, we identified GPR65 as the hub gene of the M2 macrophage-related module in glioma through WGCNA analysis. The expression and prognosis analysis suggested that GPR65 was positively correlated with the malignancy and poor prognosis of glioma, and the heterogeneity analysis found that GPR65 was highly expressed in the vascular proliferation area of glioma, which matched the spatial expression characteristics of M2 macrophages. We further verified that GPR65 was highly expressed in macrophages but not tumor cells in the glioma microenvironment by single-cell data analysis and immunofluorescence. Most importantly, we found that inhibition of GPR65 was sufficient to reduce macrophages' polarization response to glioma cell and break the malignant cooperation with glioma cells. Our study reports the expression characteristics and malignant behavior of GPR65 in the glioma microenvironment, which provides a new alternative target of treatment to glioma microenvironment.

The Molecular Landscape of Premature Aging Diseases Defined by Multilayer Network Exploration

Premature Aging (PA) diseases are rare genetic disorders that mimic some aspects of physiological aging at an early age. Various causative genes of PA diseases have been identified in recent years, providing insights into some dysfunctional cellular processes. However, the identification of PA genes also revealed significant genetic heterogeneity and highlighted the gaps in this understanding of PA-associated molecular mechanisms. Furthermore, many patients remain undiagnosed. Overall, the current lack of knowledge about PA diseases hinders the development of effective diagnosis and therapies and poses significant challenges to improving patient care. Here, a network-based approach to systematically unravel the cellular functions disrupted in PA diseases is presented. Leveraging a network community identification algorithm, it is delved into a vast multilayer network of biological interactions to extract the communities of 67 PA diseases from their 132 associated genes. It is found that these communities can be grouped into six distinct clusters, each reflecting specific cellular functions: DNA repair, cell cycle, transcription regulation, inflammation, cell communication, and vesicle-mediated transport. That these clusters collectively represent the landscape of the molecular mechanisms that are perturbed in PA diseases, providing a framework for better understanding their pathogenesis is proposed. Intriguingly, most clusters also exhibited a significant enrichment in genes associated with physiological aging, suggesting a potential overlap between the molecular underpinnings of PA diseases and natural aging.

RNA-seq reveals the gene expression in patterns in Populus × euramericana 'Neva' plantation under different precision water and fertilizer-intensive management

BACKGROUND

Populus spp. is a crucial fast-growing and productive tree species extensively cultivated in the mid-latitude plains of the world. However, the impact of intensive cultivation management on gene expression in plantation remains largely unexplored.

RESULTS

Precision water and fertilizer-intensive management substantially increased key enzyme activities of nitrogen transport, assimilation, and photosynthesis (1.12-2.63 times than CK) in Populus × euramericana 'Neva' plantation. Meanwhile, this management approach had a significant regulatory effect on the gene expression of poplar plantations. 1554 differential expression genes (DEGs)were identified in drip irrigation (ND) compared with conventional irrigation. Relative to ND, 2761-4116 DEGs, predominantly up-regulated, were identified under three drip fertilization combinations, among which 202 DEGs were mainly regulated by fertilization. Moreover, drip irrigation reduced the expression of cell wall synthesis-related genes to reduce unnecessary water transport. Precision drip and fertilizer-intensive management promotes the synergistic regulation of carbon and nitrogen metabolism and up-regulates the expression of major genes in nitrogen transport and assimilation processes (5 DEGs), photosynthesis (15 DEGs), and plant hormone signal transduction (11 DEGs). The incorporation of trace elements further enhanced the up-regulation of secondary metabolic process genes. In addition, the co-expression network identified nine hub genes regulated by precision water and fertilizer-intensive management, suggesting a pivotal role in regulating the growth of poplar.

CONCLUSION

Precision water and fertilizer-intensive management demonstrated the ability to regulate the expression of key genes and transcription factor genes involved in carbon and nitrogen metabolism pathways, plant hormone signal transduction, and enhance the activity of key enzymes involved in related processes. This regulation facilitated nitrogen absorption and utilization, and photosynthetic abilities such as light capture, light transport, and electron transport, which faintly synergistically regulate the growth of poplar plantations. These results provide a reference for proposing highly efficient precision intensive management to optimize the expression of target genes.

Epigenetic heterogeneity shapes the transcriptional landscape of regional microglia

Microglia, the innate immune cells in the central nervous system, exhibit distinct transcriptional profiles across brain regions that are important for facilitating their specialized function. There has been recent interest in identifying the epigenetic modifications associated with these distinct transcriptional profiles, as these may improve our understanding of the underlying mechanisms governing the functional specialization of microglia. One obstacle to achieving this goal is the large number of microglia required to obtain a genome-wide profile for a single histone modification. Given the cellular and regional heterogeneity of the brain, this would require pooling many samples which would impede biological applications that are limited by numbers of available animals. To overcome this obstacle, we have adapted a method of chromatin profiling known as Cleavage Under Targets and Tagmentation (CUT&Tag-Direct) to profile histone modifications associated with regional differences in gene expression throughout the brain reward system. Consistent with previous studies, we find that transcriptional profiles of microglia vary by brain region. However, here we report that these regional differences also exhibit transcriptional network signatures specific to each region. Additionally, we find that these region-dependent network signatures are associated with differential deposition of H3K27ac and H3K7me3, and while the H3K27me3 landscape is remarkably stable across brain regions, the H3K27ac landscape is most consistent with the anatomical location of microglia which explain their distinct transcriptional profiles. Altogether, these findings underscore the established role of H3K27me3 in cell fate determination and support the active role of H3K27ac in the dynamic regulation of microglial gene expression. In this study, we report a molecular and computational framework that can be applied to improve our understanding of the role of epigenetic regulation in microglia in both health and disease, using as few as 2,500 cells per histone mark.

Identification of novel cattle (Bos taurus) genes and biological insights of their function in pre-implantation embryo development

BACKGROUND

Appropriate regulation of genes expressed in oocytes and embryos is essential for acquisition of developmental competence in mammals. Here, we hypothesized that several genes expressed in oocytes and pre-implantation embryos remain unknown. Our goal was to reconstruct the transcriptome of oocytes (germinal vesicle and metaphase II) and pre-implantation cattle embryos (blastocysts) using short-read and long-read sequences to identify putative new genes.

RESULTS

We identified 274,342 transcript sequences and 3,033 of those loci do not match a gene present in official annotations and thus are potential new genes. Notably, 63.67% (1,931/3,033) of potential novel genes exhibited coding potential. Also noteworthy, 97.92% of the putative novel genes overlapped annotation with transposable elements. Comparative analysis of transcript abundance identified that 1,840 novel genes (recently added to the annotation) or potential new genes were differentially expressed between developmental stages (FDR < 0.01). We also determined that 522 novel or potential new genes (448 and 34, respectively) were upregulated at eight-cell embryos compared to oocytes (FDR < 0.01). In eight-cell embryos, 102 novel or putative new genes were co-expressed (|r|> 0.85, P < 1 × 10-8) with several genes annotated with gene ontology biological processes related to pluripotency maintenance and embryo development. CRISPR-Cas9 genome editing confirmed that the disruption of one of the novel genes highly expressed in eight-cell embryos reduced blastocyst development (ENSBTAG00000068261, P = 1.55 × 10-7).

CONCLUSIONS

Our results revealed several putative new genes that need careful annotation. Many of the putative new genes have dynamic regulation during pre-implantation development and are important components of gene regulatory networks involved in pluripotency and blastocyst formation.

Transcriptome analysis unravels key pathways and hub genes related to immature fruit abscission in Camellia oleifera

Immature fruit abscission of Camellia oleifera (C. oleifera) is a common problem limiting yield increases. However, the regulatory mechanisms underlying immature fruit abscission in C. oleifera are unclear. In this study, we systematically investigated changes in the morphological, physiological, and gene expression of fruit abscission zones (FAZs) of soon-to-abscise fruits (M2). We found that fruit abscission before ripening mainly occurs during the August abscission stage of 'Huashuo'. At the beginning of this stage, the FAZs of M2 have a marked dent, and the separation layer structures are preliminarily formed. Phytohormone analysis showed that the contents of indole-3-acetic acid (IAA) and jasmonic acid (JA) in the FAZs of M2 were significantly decreased compared with the non-abscised fruits, while the content of trans-zeatin (TZR) was increased. Transcriptome analysis identified differentially expressed genes (DEGs) mainly involved in phytohormone metabolism, including ethylene, auxin, JA, and the cis-zeatin signal transduction pathway. There were also many DEGs involved in cell wall catabolism. Weighted gene co-expression network analysis (WGCNA) further suggested that the transcription factors NAC100 and ERF114 participate in the immature fruit abscission of C. oleifera. This study provides insights into the fruit abscission mechanism of C. oleifera.

Shirebi granules ameliorate acute gouty arthritis by inhibiting NETs-induced imbalance between immunity and inflammation

BACKGROUND

Acute gouty arthritis (AGA) is classified as 'arthritis' in traditional Chinese medicine (TCM) theory. Shirebi granules (SGs), derived from the classic prescription SiMiaoWan, exerts satisfying therapeutic efficacy in ameliorating AGA clinically. However, the underlying mechanisms of SGs against AGA remain unclarified.

METHODS

AGA-related biological processes, signal pathways and biomarker genes were mined from the GEO database through bioinformatics. SGs components were systematically recognized using the UPLC-Q-TOF-MS/MS. A correlation network was established based on the biomarker genes and the chemical components, from which the signal pathway used for further study was selected. Finally, we established an AGA model using SD rats injected with monosodium urate (MSU) in the ankle joint for experimental validation. A combination of behavioral tests, H&E, safranin O- fast green, western blotting, and immunofluorescence were employed to reveal the mechanism of action of SGs on AGA.

RESULTS

The deterioration of AGA was significantly related to the imbalance between immunity and inflammation, neutrophil chemotaxis and inflammatory factor activation. HDAC5, PRKCB, NFκB1, MPO, PRKCA, PIK3CA were identified to be the candidate targets of SGs against AGA, associated with neutrophil extracellular traps (NETs) signal pathway. Animal experiments demonstrated that SGs effectively repaired cartilage damage, blocked TLR4 activation, and inhibited the expression of NETs indicators and inflammatory factors. In addition, SGs prominently alleviated joint redness and swelling, improved joint dysfunction, inhibited inflammatory infiltration of AGA rats.

CONCLUSION

Our data reveal that SGs may effectively alleviate the disease severity of AGA by suppressing NETs-promoted imbalance between immunity and inflammation.

Cardiac Molecular Analysis Reveals Aging-Associated Metabolic Alterations Promoting Glycosaminoglycans Accumulation via Hexosamine Biosynthetic Pathway

Age is a prominent risk factor for cardiometabolic disease, often leading to heart structural and functional changes. However, precise molecular mechanisms underlying cardiac remodeling and dysfunction exclusively resulting from physiological aging remain elusive. Previous research demonstrated age-related functional alterations in baboons, analogous to humans. The goal of this study is to identify early cardiac molecular alterations preceding functional adaptations, shedding light on the regulation of age-associated changes. Unbiased transcriptomics of left ventricle samples are performed from female baboons aged 7.5-22.1 years (human equivalent ≈30-88 years). Weighted-gene correlation network and pathway enrichment analyses are performed, with histological validation. Modules of transcripts negatively correlated with age implicated declined metabolism-oxidative phosphorylation, tricarboxylic acid cycle, glycolysis, and fatty-acid β-oxidation. Transcripts positively correlated with age suggested a metabolic shift toward glucose-dependent anabolic pathways, including hexosamine biosynthetic pathway (HBP). This shift is associated with increased glycosaminoglycan synthesis, modification, precursor synthesis via HBP, and extracellular matrix accumulation, verified histologically. Upregulated extracellular matrix-induced signaling coincided with glycosaminoglycan accumulation, followed by cardiac hypertrophy-related pathways. Overall, these findings revealed a transcriptional shift in metabolism favoring glycosaminoglycan accumulation through HBP before cardiac hypertrophy. Unveiling this metabolic shift provides potential targets for age-related cardiac diseases, offering novel insights into early age-related mechanisms.

Consensus clustering and development of a risk signature based on trajectory differential genes of cancer-associated fibroblast subpopulations in colorectal cancer

BACKGROUND

Cancer-associated fibroblasts (CAFs) play a crucial role in the progression of colorectal cancer (CRC). However, the impact of CAF subpopulation trajectory differentiation on CRC remains unclear.

METHODS

In this study, we first explored the trajectory differences of CAFs subpopulations using bulk and integrated single-cell sequencing data, and then performed consensus clustering of CRC samples based on the trajectory differential genes of CAFs subpopulations. Subsequently, we analyzed the heterogeneity of CRC subtypes using bioinformatics. Finally, we constructed relevant prognostic signature using machine learning and validated them using spatial transcriptomic data.

RESULTS

Based on the differential genes of CAFs subpopulation trajectory differentiation, we identified two CRC subtypes (C1 and C2) in this study. Compared to C1, C2 exhibited worse prognosis, higher immune evasion microenvironment and high CAF characteristics. C1 was primarily associated with metabolism, while C2 was primarily associated with cell metastasis and immune regulation. By combining 101 combinations of 10 machine learning algorithms, we developed a High-CAF risk signatures (HCAFRS) based on the C2 characteristic gene. HCAFRS was an independent prognostic factor for CRC and, when combined with clinical parameters, significantly predicted the overall survival of CRC patients. HCAFRS was closely associated with epithelial-mesenchymal transition, angiogenesis, and hypoxia. Furthermore, the risk score of HCAFRS was mainly derived from CAFs and was validated in the spatial transcriptomic data.

CONCLUSION

In conclusion, HCAFRS has the potential to serve as a promising prognostic indicator for CRC, improving the quality of life for CRC patients.

PTBP1-mediated repression of neuron-specific CDC42 splicing constitutes a genomic alteration-independent, developmentally conserved vulnerability in IDH-wildtype glioblastoma

Gene co-expression networks may encode hitherto inadequately recognized vulnerabilities for adult gliomas. By identifying evolutionally conserved gene co-expression modules around EGFR (EM) or PDGFRA (PM), we recently proposed an EM/PM classification scheme, which assigns IDH-wildtype glioblastomas (GBM) into the EM subtype committed in neural stem cell compartment, IDH-mutant astrocytomas and oligodendrogliomas into the PM subtype committed in early oligodendrocyte lineage. Here, we report the identification of EM/PM subtype-specific gene co-expression networks and the characterization of hub gene polypyrimidine tract-binding protein 1 (PTBP1) as a genomic alteration-independent vulnerability in IDH-wildtype GBM. Supervised by the EM/PM classification scheme, we applied weighted gene co-expression network analysis to identify subtype-specific global gene co-expression modules. These gene co-expression modules were characterized for their clinical relevance, cellular origin and conserved expression pattern during brain development. Using lentiviral vector-mediated constitutive or inducible knockdown, we characterized the effects of PTBP1 on the survival of IDH-wildtype GBM cells, which was complemented with the analysis of PTBP1-depedent splicing pattern and overexpression of splicing target neuron-specific CDC42 (CDC42-N) isoform.  Transcriptomes of adult gliomas can be robustly assigned into 4 large gene co-expression modules that are prognostically relevant and are derived from either malignant cells of the EM/PM subtypes or tumor microenvironment. The EM subtype is associated with a malignant cell-intrinsic gene module involved in pre-mRNA splicing, DNA replication and damage response, and chromosome segregation, and a microenvironment-derived gene module predominantly involved in extracellular matrix organization and infiltrating immune cells. The PM subtype is associated with two malignant cell-intrinsic gene modules predominantly involved in transcriptional regulation and mRNA translation, respectively. Expression levels of these gene modules are independent prognostic factors and malignant cell-intrinsic gene modules are conserved during brain development. Focusing on the EM subtype, we identified PTBP1 as the most significant hub for the malignant cell-intrinsic gene module. PTBP1 is not altered in most glioma genomes. PTBP1 represses the conserved splicing of CDC42-N. PTBP1 knockdown or CDC42-N overexpression disrupts actin cytoskeleton dynamics, causing accumulation of reactive oxygen species and cell apoptosis. PTBP1-mediated repression of CDC42-N splicing represents a potential genomic alteration-independent, developmentally conserved vulnerability in IDH-wildtype GBM.

A twin analysis to estimate genetic and environmental factors contributing to variation in weighted gene co-expression network module eigengenes

Multivariate network-based analytic methods such as weighted gene co-expression network analysis are frequently applied to human and animal gene-expression data to estimate the first principal component of a module, or module eigengene (ME). MEs are interpreted as multivariate summaries of correlated gene-expression patterns and network connectivity across genes within a module. As such, they have the potential to elucidate the mechanisms by which molecular genomic variation contributes to individual differences in complex traits. Although increasingly used to test for associations between modules and complex traits, the genetic and environmental etiology of MEs has not been empirically established. It is unclear if, and to what degree, individual differences in blood-derived MEs reflect random variation versus familial aggregation arising from heritable or shared environmental influences. We used biometrical genetic analyses to estimate the contribution of genetic and environmental influences on MEs derived from blood lymphocytes collected on a sample of N = 661 older male twins from the Vietnam Era Twin Study of Aging (VETSA) whose mean age at assessment was 67.7 years (SD = 2.6 years, range = 62-74 years). Of the 26 detected MEs, 14 (56%) had statistically significant additive genetic variation with an average heritability of 44% (SD = 0.08, range = 35%-64%). Despite the relatively small sample size, this demonstration of significant family aggregation including estimates of heritability in 14 of the 26 MEs suggests that blood-based MEs are reliable and merit further exploration in terms of their associations with complex traits and diseases.

Sustained mucosal colonization and fecal metabolic dysfunction by Bacteroides associates with fecal microbial transplant failure in ulcerative colitis patients

Fecal microbial transplantation (FMT) offers promise for treating ulcerative colitis (UC), though the mechanisms underlying treatment failure are unknown. This study harnessed longitudinally collected colonic biopsies (n = 38) and fecal samples (n = 179) from 19 adults with mild-to-moderate UC undergoing serial FMT in which antimicrobial pre-treatment and delivery mode (capsules versus enema) were assessed for clinical response (≥ 3 points decrease from the pre-treatment Mayo score). Colonic biopsies underwent dual RNA-Seq; fecal samples underwent parallel 16S rRNA and shotgun metagenomic sequencing as well as untargeted metabolomic analyses. Pre-FMT, the colonic mucosa of non-responsive (NR) patients harbored an increased burden of bacteria, including Bacteroides, that expressed more antimicrobial resistance genes compared to responsive (R) patients. NR patients also exhibited muted mucosal expression of innate immune antimicrobial response genes. Post-FMT, NR and R fecal microbiomes and metabolomes exhibited significant divergence. NR metabolomes had elevated concentrations of immunostimulatory compounds including sphingomyelins, lysophospholipids and taurine. NR fecal microbiomes were enriched for Bacteroides fragilis and Bacteroides salyersiae strains that encoded genes capable of taurine production. These findings suggest that both effective mucosal microbial clearance and reintroduction of bacteria that reshape luminal metabolism associate with FMT success and that persistent mucosal and fecal colonization by antimicrobial-resistant Bacteroides species may contribute to FMT failure.

The multi-tissue gene expression and physiological responses of water deprived Peromyscus eremicus

The harsh and dry conditions of desert environments have resulted in genomic adaptations, allowing for desert organisms to withstand prolonged drought, extreme temperatures, and limited food resources. Here, we present a comprehensive exploration of gene expression across five tissues (kidney, liver, lung, gastrointestinal tract, and hypothalamus) and 19 phenotypic measurements to explore the whole-organism physiological and genomic response to water deprivation in the desert-adapted cactus mouse (Peromyscus eremicus). The findings encompass the identification of differentially expressed genes and correlative analysis between phenotypes and gene expression patterns across multiple tissues. Specifically, we found robust activation of the vasopressin renin-angiotensin-aldosterone system (RAAS) pathways, whose primary function is to manage water and solute balance. Animals reduced food intake during water deprivation, and upregulation of PCK1 highlights the adaptive response to reduced oral intake via its actions aimed at maintained serum glucose levels. Even with such responses to maintain water balance, hemoconcentration still occurred, prompting a protective downregulation of genes responsible for the production of clotting factors while simultaneously enhancing angiogenesis which is thought to maintain tissue perfusion. In this study, we elucidate the complex mechanisms involved in water balance in the desert-adapted cactus mouse, P. eremicus. By prioritizing a comprehensive analysis of whole-organism physiology and multi-tissue gene expression in a simulated desert environment, we describe the complex response of regulatory processes.

Identification and experimental verification of a biomarker by combining the unfolded protein response with the immune cells in colon cancer

BACKGROUND

The unfolded protein response (UPR) is associated with immune cells that regulate the biological behavior of tumors. This article aims to combine UPR-associated genes with immune cells to find a prognostic marker and to verify its connection to the UPR.

METHODS

Univariate cox analysis was used to screen prognostically relevant UPRs and further screened for key UPRs among them by machine learning. ssGSEA was used to calculate immune cell abundance. Univariate cox analysis was used to screen for prognostically relevant immune cells. Multivariate cox analysis was used to calculate UPR_score and Tumor Immune Microenvironment score (TIME_score). WGCNA was used to screen UPR-Immune-related (UI-related) genes. Consensus clustering analysis was used to classify patients into molecular subtype. Based on the UI-related genes, we classified colon adenocarcinoma (COAD) samples by cluster analysis. Single-cell analysis was used to analyze the role of UI-related genes. We detected the function of TIMP1 by cell counting and transwell. Immunoblotting was used to detect whether TIMP1 was regulated by key UPR genes.

RESULTS

Combined UPR-related genes and immune cells can determine the prognosis of COAD patients. Cluster analysis showed that UI-related genes were associated with clinical features of COAD. Single-cell analysis revealed that UI-related genes may act through stromal cells. We defined three key UI-related genes by machine learning algorithms. Finally, we found that TIMP1, regulated by key genes of UPR, promoted colon cancer proliferation and metastasis.

CONCLUSIONS

We found that TIMP1 was a prognostic marker and experimentally confirmed that TIMP1 was regulated by key genes of UPR.

Potential impact of epithelial splicing regulatory protein 1 (ESRP1) associated with tumor immunity in pancreatic adenocarcinoma

Pancreatic adenocarcinoma (PAAD) is a prevalent and highly malignant gastrointestinal tumor. Therefore, exploring the mechanisms of drug resistance and immune pathways in PAAD is crucial for clinical treatment. In this study, a total of 497 differentially expressed genes (DEGs) were identified between normal and PAAD samples, and which were enriched to 117 GO terms and 7 functional pathways. Subsequently, 5 overall survival-related DEGs (ESRP1, KRT6A, H2BC11, H2BC4 and KLK) was generated using Cox hazards regression analysis in TCGA dataset. Furthermore, the weighted gene co-expression network analysis revealed a strong association between ESRP1 and PAAD among 5 survival-related DEGs. Patients were divided into two clusters based on ESRP1 expression levels, and low ESRP1 expression existed stronger immune infiltration and higher expression of immunomodulatory targets than high ESRP1 expression by single-sample gene set enrichment analysis, which indicated that low ESRP1 expression was associated with longer survival compared to high ESRP1 expression. Finally, our study also found that immune cells distribution and immunomodulatory targets gene expression in the GEO dataset were similar to the TCGA cohort. Overall, our findings suggest that ESRP1 may play a role in influencing immune contexture and regulating immune function of PAAD patients by integrating data from various databases. SIGNIFICANCE: Utilizing TCGA and GEO datasets, this study uncovers the significant impact of epithelial splicing regulatory protein 1 (ESRP1) on PAAD. ESRP1 emerges as a key regulator of immune function, influencing tumor microenvironment and immune cell infiltration. Cluster analysis shows that low ESRP1 expression correlates with enhanced immune activity, predicting better prognosis. This discovery suggests that ESRP1 can serve as a potential biomarker for the prognosis of PAAD, offering new insights into personalized immunotherapy by influencing immune regulation and tumor progression.

Multi-omic analysis of Huntington's disease reveals a compensatory astrocyte state

The mechanisms underlying the selective regional vulnerability to neurodegeneration in Huntington's disease (HD) have not been fully defined. To explore the role of astrocytes in this phenomenon, we used single-nucleus and bulk RNAseq, lipidomics, HTT gene CAG repeat-length measurements, and multiplexed immunofluorescence on HD and control post-mortem brains. We identified genes that correlated with CAG repeat length, which were enriched in astrocyte genes, and lipidomic signatures that implicated poly-unsaturated fatty acids in sensitizing neurons to cell death. Because astrocytes play essential roles in lipid metabolism, we explored the heterogeneity of astrocytic states in both protoplasmic and fibrous-like (CD44+) astrocytes. Significantly, one protoplasmic astrocyte state showed high levels of metallothioneins and was correlated with the selective vulnerability of distinct striatal neuronal populations. When modeled in vitro, this state improved the viability of HD-patient-derived spiny projection neurons. Our findings uncover key roles of astrocytic states in protecting against neurodegeneration in HD.

Comparative phenotypic and transcriptomic analysis reveals genotypic differences in nitrogen use efficiency in sorghum

Sorghum (Sorghumbicolor L.), a model for C4 grass and an emerging biofuel crop, is known for its robust tolerance to low input field. However, the focus on enhancing nitrogen use efficiency (NUE) in sorghum under low nitrogen (N) conditions has been limited. This study conducted hydroponic experiments and field trials with two sorghum inbred lines, contrasting in their N efficiency: the N-efficient (398B) and the N-inefficient (CS3541) inbred lines. The aim was to analyze the key factors influencing NUE by integrating phenotypic, physiological, and multi-omics approaches under N deficiency conditions. The field experiments revealed that 398B displayed superior NUE and yield performance compared to CS3541. In hydroponic experiments, the growth of 398B outperformed CS3541 following N deficiency, attributing to its higher photosynthetic and sustaining activity of N metabolism-related enzymes. Genomic and transcriptomic integration highlighted fewer genomic diversities and alterations in global gene expression in 398B, which were likely contributor to its high NUE. Additionally, co-expression network analysis suggested the involvement of key genes which impact N uptake efficiency (NUpE) and N utilization efficiency (NUtE) in both lines, such as an N transporter, Sobic.003G371000.v3.2leaf(NPF5.10) and a transcription factor, Sobic.002G202800.v3.2leaf(WRKY) in bolstering NUE under low-N stress. The findings collectively suggested that 398B achieved higher NUpE and NUtE, effectively coordinating photosynthesis and N metabolism to enhance NUE. The candidate genes regulating N uptake and utilization efficiencies could provide valuable insights for developing sorghum breeds with improved NUE, contributing to sustainable agricultural practices and bioenergy crop development.

Widespread changes in gene expression accompany body size evolution in nematodes

Body size is a fundamental trait that drives multiple evolutionary and ecological patterns. Caenorhabditis inopinata is a fig-associated nematode that is exceptionally large relative to other members of the genus, including Caenorhabditis elegans. We previously showed that C. inopinata is large primarily due to postembryonic cell size expansion that occurs during the larval-to-adult transition. Here, we describe gene expression patterns in C. elegans and C. inopinata throughout this developmental period to understand the transcriptional basis of body size change. We performed RNA-seq in both species across the L3, L4, and adult stages. Most genes are differentially expressed across all developmental stages, consistent with C. inopinata's divergent ecology and morphology. We also used a model comparison approach to identify orthologues with divergent dynamics across this developmental period between the 2 species. This included genes connected to neurons, behavior, stress response, developmental timing, and small RNA/chromatin regulation. Multiple hypodermal collagens were also observed to harbor divergent developmental dynamics across this period, and genes important for molting and body morphology were also detected. Genes associated with transforming growth factor β signaling revealed idiosyncratic and unexpected transcriptional patterns given their role in body size regulation in C. elegans. This widespread transcriptional divergence between these species is unexpected and maybe a signature of the ecological and morphological divergence of C. inopinata. Alternatively, transcriptional turnover may be the rule in the Caenorhabditis genus, indicative of widespread developmental system drift among species. This work lays the foundation for future functional genetic studies interrogating the bases of body size evolution in this group.

Transcriptome Profiling and Weighted Gene Correlation Network Analysis Reveal Hub Genes and Pathways Involved in the Response to Polyethylene-Glycol-Induced Drought Stress of Two Citrus Rootstocks

Agriculture faces the dual challenge of increasing food production and safeguarding the environment. Climate change exacerbates this challenge, reducing crop yield and biomass due to drought stress, especially in semi-arid regions where Citrus plants are cultivated. Understanding the molecular mechanisms underlying drought tolerance in Citrus is crucial for developing adaptive strategies. Plants of two citrus rootstocks, Carrizo Citrange and Bitters (C22), were grown in aerated half-strength Hoagland's nutrient solution. Post-acclimation, the plants were exposed to a solution containing 0% (control) or 15% PEG-8000 for 10 days. Leaf malonyl dialdehyde (MDA) and hydrogen peroxide (H2O2) content were measured to assess the reached oxidative stress level. Total RNA was extracted, sequenced, and de novo-assembled. Weighted Gene Correlation Network Analysis (WGCNA) was conducted to examine the relationship between gene expression patterns and the levels of MDA and H2O2 used as oxidative stress indicators. Plant visual inspection and MDA and H2O2 contents clearly indicate that Bitters is more tolerant than Carrizo towards PEG-induced drought stress. RNA-Seq analysis revealed a significantly higher number of differentially expressed genes (DEGs) in Carrizo (6092) than in Bitters (320), with most being associated with drought sensing, ROS scavenging, osmolyte biosynthesis, and cell wall metabolism. Moreover, the WGCNA identified transcription factors significantly correlated with MDA and H2O2 levels, thus providing insights into drought-coping strategies and offering candidate genes for enhancing citrus drought tolerance.

Canine hyper-sociability structural variants associated with altered three-dimensional chromatin state

Strong selection on complex traits can lead to skewed trait means and reduced trait variability in populations. An example of this phenomenon can be evidenced in allele frequency changes and skewed trait distributions driven by persistent human-directed selective pressures in domesticated species. Dog domestication is linked to several genomic variants; however, the functional impacts of these variants may not always be straightforward when found in non-coding regions of the genome. Four polymorphic transposable elements (TE) found within non-coding sites along a 5 Mb region on canine CFA6 have evolved due to directional selection associated with heightened human-directed hyper-sociability in domesticated dogs. We found that the polymorphic TE in intron 17 of the canine GTF2I gene, which was previously reported to be negatively correlated with canid human-directed hyper-sociability, is associated with altered chromatin looping and hence distinct cis-regulatory landscapes. We reported supporting evidence of an E2F1-DNA binding peak concordant with the altered loop and higher expression of GTF2I exon 18, indicative of alternative splicing. Globally, we discovered differences in pathways regulating the extra-cellular matrix with respect to TE copy number. Overall, we reported evidence suggesting an intriguing molecular convergence between the emergence of hypersocial behaviors in dogs and the same genes that, when hemizygous, produce human Williams Beuren Syndrome characterized by cranio-facial defects and heightened social behaviors. Our results additionally emphasize the often-overlooked potential role of chromatin architecture in social evolution.

Effects of yeast culture supplementation on milk yield, rumen fermentation, metabolism, and bacterial composition in dairy goats

The effects of yeast culture (YC) on dairy goat milk yield and potential effects of rumen microbial population changes on rumen fermentation are poorly understood. This study aimed to evaluate the effects of YC on milk yield and rumen fermentation in dairy goats and explore the potential microbial mechanisms. Forty Laoshan dairy goats with a weight of 51.23 ± 2.23 kg and daily milk yield of 1.41 ± 0.26 kg were randomly divided into 4 groups: control (no YC), YC1 (10 g/day per goat), YC2 (25 g/day per goat), and YC3 (40 g/day per goat). The pre-feeding period was 15 days, and the official period was 60 days. Laoshan dairy goats were milked twice daily, and the individual milk yield was recorded. On the last day of the official period, rumen fluid was collected to measure rumen fermentation, perform quantitative polymerase chain reaction (PCR), and detect metabolites. Compared to the control group, the YC group had greater milk yield; higher acetic acid, butyric acid, and total volatile fatty acid contents; and lower ammonia-N (NH3-N) content in the rumen (p < 0.05). YC increased the abundance of Clostridia_UCG-014 and Paraprevotella (p < 0.05). Differential metabolites L-leucine and aspartic acid were screened. This study revealed the microbial mechanisms linking the relative abundance of Paraprevotella and Clostridia_UCG-014 to L-leucine and aspartic acid utilization. These results describe the potential benefits of supplementing 10 g/day per goat YC in the diets of Laoshan dairy goats for improving the rumen environment and milk yield.

Construction of a prognostic model via WGCNA combined with the LASSO algorithm for stomach adenocarcinoma patients

Objective

This study aimed to identify prognostic signatures to predict the prognosis of patients with stomach adenocarcinoma (STAD), which is necessary to improve poor prognosis and offer possible treatment strategies for STAD patients.

Methods

The overlapping genes between the key model genes that were screened by the weighted gene co-expression network analysis (WGCNA) and differentially expressed genes (DEGs) whose expression was different with significance between normal and tumor tissues were extracted to serve as co-expression genes. Then, enrichment analysis was performed on these genes. Furthermore, the least absolute shrinkage and selection operator (LASSO) regression was performed to screen the hub genes among overlapping genes. Finally, we constructed a model to explore the influence of polygenic risk scores on the survival probability of patients with STAD, and interaction effect and mediating analyses were also performed.

Results

DEGs included 2,899 upregulated genes and 2,896 downregulated genes. After crossing the DEGs and light-yellow module genes that were obtained by WGCNA, a total of 39 overlapping genes were extracted. The gene enrichment analysis revealed that these genes were enriched in the prion diseases, biosynthesis of unsaturated fatty acids, RNA metabolic process, hydrolase activity, etc. PIP5K1P1, PTTG3P, and SNORD15B were determined by LASSO-Cox. The prognostic prediction of the three-gene model was established. The Cox regression analysis showed that the comprehensive risk score for three genes was an independent prognosis factor.

Conclusion

PIP5K1P1, PTTG3P, and SNORD15B are related to the prognosis and overall survival of patients. The three-gene risk model constructed has independent prognosis predictive ability for STAD.

TFEB controls sensitivity to chemotherapy and immuno-killing in non-small cell lung cancer

BACKGROUND

In non-small cell lung cancer (NSCLC) the efficacy of chemo-immunotherapy is affected by the high expression of drug efflux transporters as ABCC1 and by the low expression of ABCA1, mediating the isopentenyl pyrophosphate (IPP)-dependent anti-tumor activation of Vγ9Vδ2 T-lymphocytes. In endothelial cells ABCA1 is a predicted target of the transcription factor EB (TFEB), but no data exists on the correlation between TFEB and ABC transporters involved in the chemo-immuno-resistance in NSCLC.

METHODS

The impact of TFEB/ABCC1/ABCA1 expression on NSCLC patients' survival was analyzed in the TCGA-LUAD cohort and in a retrospective cohort of our institution. Human NSCLC cells silenced for TFEB (shTFEB) were analyzed for ABC transporter expression, chemosensitivity and immuno-killing. The chemo-immuno-sensitizing effects of nanoparticles encapsulating zoledronic acid (NZ) on shTFEB tumors and on tumor immune-microenvironment were evaluated in Hu-CD34+ mice by single-cell RNA-sequencing.

RESULTS

TFEBlowABCA1lowABCC1high and TFEBhighABCA1highABCC1low NSCLC patients had the worst and the best prognosis, respectively, in the TCGA-LUAD cohort and in a retrospective cohort of patients receiving platinum-based chemotherapy or immunotherapy as first-line treatment. By silencing shTFEB in NSCLC cells, we demonstrated that TFEB was a transcriptional inducer of ABCA1 and a repressor of ABCC1. shTFEB cells had also a decreased activity of ERK1/2/SREBP2 axis, implying reduced synthesis and efflux via ABCA1 of cholesterol and its intermediate IPP. Moreover, TFEB silencing reduced cholesterol incorporation in mitochondria: this event increased the efficiency of OXPHOS and the fueling of ABCC1 by mitochondrial ATP. Accordingly, shTFEB cells were less immuno-killed by the Vγ9Vδ2 T-lymphocytes activated by IPP and more resistant to cisplatin. NZ, which increased IPP efflux but not OXPHOS and ATP production, sensitized shTFEB immuno-xenografts, by reducing intratumor proliferation and increasing apoptosis in response to cisplatin, and by increasing the variety of anti-tumor infiltrating cells (Vγ9Vδ2 T-lymphocytes, CD8+T-lymphocytes, NK cells).

CONCLUSIONS

This work suggests that TFEB is a gatekeeper of the sensitivity to chemotherapy and immuno-killing in NSCLC, and that the TFEBlowABCA1lowABCC1high phenotype can be predictive of poor response to chemotherapy and immunotherapy. By reshaping both cancer metabolism and tumor immune-microenvironment, zoledronic acid can re-sensitize TFEBlow NSCLCs, highly resistant to chemo- and immunotherapy.

Whole-genome sequencing identifies novel genes for autism in Chinese trios

Autism spectrum disorder (ASD) is a neurodevelopmental disorder with high genetic heritability but heterogeneity. Fully understanding its genetics requires whole-genome sequencing (WGS), but the ASD studies utilizing WGS data in Chinese population are limited. In this study, we present a WGS study for 334 individuals, including 112 ASD patients and their non-ASD parents. We identified 146 de novo variants in coding regions in 85 cases and 60 inherited variants in coding regions. By integrating these variants with an association model, we identified 33 potential risk genes (P<0.001) enriched in neuron and regulation related biological process. Besides the well-known ASD genes (SCN2A, NF1, SHANK3, CHD8 etc.), several high confidence genes were highlighted by a series of functional analyses, including CTNND1, DGKZ, LRP1, DDN, ZNF483, NR4A2, SMAD6, INTS1, and MRPL12, with more supported evidence from GO enrichment, expression and network analysis. We also integrated RNA-seq data to analyze the effect of the variants on the gene expression and found 12 genes in the individuals with the related variants had relatively biased expression. We further presented the clinical phenotypes of the proband carrying the risk genes in both our samples and Caucasian samples to show the effect of the risk genes on phenotype. Regarding variants in non-coding regions, a total of 74 de novo variants and 30 inherited variants were predicted as pathogenic with high confidence, which were mapped to specific genes or regulatory features. The number of de novo variants found in patient was significantly associated with the parents' ages at the birth of the child, and gender with trend. We also identified small de novo structural variants in ASD trios. The results in this study provided important evidence for understanding the genetic mechanism of ASD.

Hub genes identification and validation of ferroptosis in SARS-CoV-2 induced ARDS: perspective from transcriptome analysis

Introduction

Acute Respiratory Distress Syndrome (ARDS) poses a significant health challenge due to its high incidence and mortality rates. The emergence of SARS-CoV-2 has added complexity, with evidence suggesting a correlation between COVID-19 induced ARDS and post-COVID symptoms. Understanding the underlying mechanisms of ARDS in COVID-19 patients is crucial for effective clinical treatment.

Method

To investigate the potential role of ferroptosis in SARS-CoV-2 induced ARDS, we conducted a comprehensive analysis using bioinformatics methods. Datasets from the Gene Expression Omnibus (GEO) were utilized, focusing on COVID-19 patients with varying ARDS severity. We employed weighted gene co-expression network analysis (WGCNA), differential gene expression analysis, and single-cell sequencing to identify key genes associated with ferroptosis in ARDS. Hub genes were validated using additional GEO datasets and cell experiment.

Result

The analysis discerned 916 differentially expressed genes in moderate/severe ARDS patients compared to non-critical individuals. Weighted Gene Co-expression Network Analysis (WGCNA) unveiled two modules that exhibited a positive correlation with ARDS, subsequently leading to the identification of 15 hub genes associated with ferroptosis. Among the noteworthy hub genes were MTF1, SAT1, and TXN. Protein-protein interaction analysis, and pathway analysis further elucidated their roles. Immune infiltrating analysis highlighted associations between hub genes and immune cells. Validation in additional datasets confirmed the upregulation of MTF1, SAT1, and TXN in SARS-CoV-2-induced ARDS. This was also demonstrated by qRT-PCR results in the BEAS-2B cells vitro model, suggesting their potential as diagnostic indicators.

Discussion

This study identifies MTF1, SAT1, and TXN as hub genes associated with ferroptosis in SARS-CoV-2-induced ARDS. These findings provide novel insights into the molecular mechanisms underlying ARDS in COVID-19 patients and offer potential targets for immune therapy and targeted treatment. Further experimental validation is warranted to solidify these findings and explore therapeutic interventions for ARDS in the context of COVID-19.

Integrative multi-omic analysis reveals conserved cell-projection deficits in human Down syndrome brains

Down syndrome (DS) is the most common genetic cause of cognitive disability. However, it is largely unclear how triplication of a small gene subset may impinge on diverse aspects of DS brain physiopathology. Here, we took a multi-omic approach and simultaneously analyzed by RNA-seq and proteomics the expression signatures of two diverse regions of human postmortem DS brains. We found that the overexpression of triplicated genes triggered global expression dysregulation, differentially affecting transcripts, miRNAs, and proteins involved in both known and novel biological candidate pathways. Among the latter, we observed an alteration in RNA splicing, specifically modulating the expression of genes involved in cytoskeleton and axonal dynamics in DS brains. Accordingly, we found an alteration in axonal polarization in neurons from DS human iPSCs and mice. Thus, our study provides an integrated multilayer expression database capable of identifying new potential targets to aid in designing future clinical interventions for DS.

Evaluating the significance of ECSCR in the diagnosis of ulcerative colitis and drug efficacy assessment

Background

The main challenge in diagnosing and treating ulcerative colitis (UC) has prompted this study to discover useful biomarkers and understand the underlying molecular mechanisms.

Methods

In this study, transcriptomic data from intestinal mucosal biopsies underwent Robust Rank Aggregation (RRA) analysis to identify differential genes. These genes intersected with UC key genes from Weighted Gene Co-expression Network Analysis (WGCNA). Machine learning identified UC signature genes, aiding predictive model development. Validation involved external data for diagnostic, progression, and drug efficacy assessment, along with ELISA testing of clinical serum samples.

Results

RRA integrative analysis identified 251 up-regulated and 211 down-regulated DEGs intersecting with key UC genes in WGCNA, yielding 212 key DEGs. Subsequently, five UC signature biomarkers were identified by machine learning based on the key DEGs-THY1, SLC6A14, ECSCR, FAP, and GPR109B. A logistic regression model incorporating these five genes was constructed. The AUC values for the model set and internal validation data were 0.995 and 0.959, respectively. Mechanistically, activation of the IL-17 signaling pathway, TNF signaling pathway, PI3K-Akt signaling pathway in UC was indicated by KEGG and GSVA analyses, which were positively correlated with the signature biomarkers. Additionally, the expression of the signature biomarkers was strongly correlated with various UC types and drug efficacy in different datasets. Notably, ECSCR was found to be upregulated in UC serum and exhibited a positive correlation with neutrophil levels in UC patients.

Conclusions

THY1, SLC6A14, ECSCR, FAP, and GPR109B can serve as potential biomarkers of UC and are closely related to signaling pathways associated with UC progression. The discovery of these markers provides valuable information for understanding the molecular mechanisms of UC.

MDK promotes M2 macrophage polarization to remodel the tumour microenvironment in clear cell renal cell carcinoma

The efficacy of immunotherapy for clear cell renal cell carcinoma (ccRCC), especially advanced ccRCC, is limited, presenting a clinical challenge. This limitation is closely tied to the immune regulation network. Understanding the heterogeneity of the tumour microenvironment (TME) is crucial for developing advanced ccRCC therapies. Using publicly available ccRCC data (scRNA-seq, bulk RNA-seq, and somatic mutation data), a multiomics study was performed to explore TME heterogeneity. Three distinct ccRCC immune subtypes were identified through combined scRNA-seq and bulk RNA-seq analysis. A prognostic model based on unique cell signalling molecules in immunosuppressive tumour subtype was validated in the TCGA and CheckMate cohorts. MDK emerged as a critical regulatory gene in the immunosuppressive subtype, predicting a poor ccRCC prognosis and a poor immunotherapy response. MDK promotes M2 macrophage polarization via the MDK-LRP1 interaction, and the inhibition of MDK suppressed M2 polarization. This study revealed the heterogeneity of the ccRCC TME and a reliable prognostic model, shedding light on the vital role of MDK in the immunosuppressive TME and paving the way for optimized ccRCC immunotherapy.

The clinical significance of endoplasmic reticulum stress related genes in non-small cell lung cancer and analysis of single nucleotide polymorphism for CAV1

In recent years, protein homeostasis imbalance caused by endoplasmic reticulum stress has become a major hallmark of cancer. Studies have shown that endoplasmic reticulum stress is closely related to the occurrence, development, and drug resistance of non-small cell lung cancer, however, the role of various endoplasmic reticulum stress-related genes in non-small cell lung cancer is still unclear. In this study, we established an endoplasmic reticulum stress scores based on the Cancer Genome Atlas for non-small cell lung cancer to reflect patient features and predict prognosis. Survival analysis showed significant differences in overall survival among non-small cell lung cancer patients with different endoplasmic reticulum stress scores. In addition, endoplasmic reticulum stress scores was significantly correlated with the clinical features of non-small cell lung cancer patients, and can be served as an independent prognostic indicator. A nomogram based on endoplasmic reticulum stress scores indicated a certain clinical net benefit, while ssGSEA analysis demonstrated that there was a certain immunosuppressive microenvironment in high endoplasmic reticulum stress scores. Gene Set Enrichment Analysis showed that scores was associated with cancer pathways and metabolism. Finally, weighted gene co-expression network analysis displayed that CAV1 was closely related to the occurrence of non-small cell lung cancer. Therefore, in order to further analyze the role of this gene, Chinese non-smoking females were selected as the research subjects to investigate the relationship between CAV1 rs3779514 and susceptibility and prognosis of non-small cell lung cancer. The results showed that the mutation of rs3779514 significantly reduced the risk of non-small cell lung cancer in Chinese non-smoking females, but no prognostic effect was found. In summary, we proposed an endoplasmic reticulum stress scores, which was an independent prognostic factor and indicated immune characteristics in the microenvironment of non-small cell lung cancer. We also validated the relationship between single nucleotide polymorphism locus of core genes and susceptibility to non-small cell lung cancer.

Transcriptomic and physiological responses of Quercus acutissima and Quercus palustris to drought stress and rewatering

Establishment of oak seedlings, which is an important factor in forest restoration, is affected by drought that hampers the survival, growth, and development of seedlings. Therefore, it is necessary to understand how seedlings respond to and recover from water-shortage stress. We subjected seedlings of two oak species, Quercus acutissima and Quercus palustris, to drought stress for one month and then rewatered them for six days to observe physiological and genetic expression changes. Phenotypically, the growth of Q. acutissima was reduced and severe wilting and recovery failure were observed in Q. palustris after an increase in plant temperature. The two species differed in several physiological parameters during drought stress and recovery. Although the photosynthesis-related indicators did not change in Q. acutissima, they were decreased in Q. palustris. Moreover, during drought, content of soluble sugars was significantly increased in both species, but it recovered to original levels only in Q. acutissima. Malondialdehyde content increased in both the species during drought, but it did not recover in Q. palustris after rewatering. Among the antioxidant enzymes, only superoxide dismutase activity increased in Q. acutissima during drought, whereas activities of ascorbate peroxidase, catalase, and glutathione reductase increased in Q. palustris. Abscisic acid levels were increased and then maintained in Q. acutissima, but recovered to previous levels after rewatering in Q. palustris. RNA samples from the control, drought, recovery day 1, and recovery day 6 treatment groups were compared using transcriptome analysis. Q. acutissima exhibited 832 and 1076 differentially expressed genes (DEGs) related to drought response and recovery, respectively, whereas Q. palustris exhibited 3947 and 1587 DEGs, respectively under these conditions. Gene ontology enrichment of DEGs revealed "response to water," "apoplast," and "Protein self-association" to be common to both the species. However, in the heatmap analysis of genes related to sucrose and starch synthesis, glycolysis, antioxidants, and hormones, the two species exhibited very different transcriptome responses. Nevertheless, the levels of most DEGs returned to their pre-drought levels after rewatering. These results provide a basic foundation for understanding the physiological and genetic expression responses of oak seedlings to drought stress and recovery.

Network proteomics of the Lewy body dementia brain reveals presynaptic signatures distinct from Alzheimer's disease

Lewy body dementia (LBD), a class of disorders comprising Parkinson's disease dementia (PDD) and dementia with Lewy bodies (DLB), features substantial clinical and pathological overlap with Alzheimer's disease (AD). The identification of biomarkers unique to LBD pathophysiology could meaningfully advance its diagnosis, monitoring, and treatment. Using quantitative mass spectrometry (MS), we measured over 9,000 proteins across 138 dorsolateral prefrontal cortex (DLPFC) tissues from a University of Pennsylvania autopsy collection comprising control, Parkinson's disease (PD), PDD, and DLB diagnoses. We then analyzed co-expression network protein alterations in those with LBD, validated these disease signatures in two independent LBD datasets, and compared these findings to those observed in network analyses of AD cases. The LBD network revealed numerous groups or "modules" of co-expressed proteins significantly altered in PDD and DLB, representing synaptic, metabolic, and inflammatory pathophysiology. A comparison of validated LBD signatures to those of AD identified distinct differences between the two diseases. Notably, synuclein-associated presynaptic modules were elevated in LBD but decreased in AD relative to controls. We also found that glial-associated matrisome signatures consistently elevated in AD were more variably altered in LBD, ultimately stratifying those LBD cases with low versus high burdens of concurrent beta-amyloid deposition. In conclusion, unbiased network proteomic analysis revealed diverse pathophysiological changes in the LBD frontal cortex distinct from alterations in AD. These results highlight the LBD brain network proteome as a promising source of biomarkers that could enhance clinical recognition and management.

Dynamic patterns of gene expressional and regulatory variations in cotton heterosis

Purpose

Although the application of heterosis has significantly increased crop yield over the past century, the mechanisms underlying this phenomenon still remain obscure. Here, we applied transcriptome sequencing to unravel the impacts of parental expression differences and transcriptomic reprogramming in cotton heterosis.

Methods

A high-quality transcriptomic atlas covering 15 developmental stages and tissues was constructed for XZM2, an elite hybrid of upland cotton (Gossypium hirsutum L.), and its parental lines, CRI12 and J8891. This atlas allowed us to identify gene expression differences between the parents and to characterize the transcriptomic reprogramming that occurs in the hybrid.

Results

Our analysis revealed abundant gene expression differences between the parents, with pronounced tissue specificity; a total of 1,112 genes exhibited single-parent expression in at least one tissue. It also illuminated transcriptomic reprogramming in the hybrid XZM2, which included both additive and non-additive expression patterns. Coexpression networks between parents and hybrid constructed via weighted gene coexpression network analysis identified modules closely associated with fiber development. In particular, key regulatory hub genes involved in fiber development showed high-parent dominant or over dominant patterns in the hybrid, potentially driving the emergence of heterosis. Finally, high-depth resequencing data was generated and allele-specific expression patterns examined in the hybrid, enabling the dissection of cis- and trans-regulation contributions to the observed expression differences.

Conclusion

Parental transcriptional differences and transcriptomic reprogramming in the hybrid, especially the non-additive upregulation of key genes, play an important role in shaping heterosis. Collectively, these findings provide new insights into the molecular basis of heterosis in cotton.

LcINH1 as an inhibitor of cell wall invertase LcCWIN5 regulates early seed development in Litchi chinensis Sonn

Sugar signal mediated by Cell wall invertase (CWIN) plays a central role in seed development. In higher plants, invertase inhibitors (INHs) suppress CWIN activities at a post-translational level. In Litchi chinensis cultivar 'Nuomici', impaired CWIN expression is associated with seed abortion. Here, the expression of LcINH1 was significantly higher in the funicle of seed-aborting cultivar 'Nuomici' than big-seeded cultivar 'Heiye'. Promoter analyses found LcINH1 contained a 404 bp repeat fragment with an endosperm regulatory element of Skn-1_motif. LcINH1 and LcCWIN2/5 were located in plasma membrane. LcINH1 was able to interact with LcCWIN5, but not with LcCWIN2. In vitro enzyme activity assay demonstrated that LcINH1 could inhibit CWIN activity. Silencing LcINH1 in 'Nuomici' resulted in normal seed development, paralleled increased CWIN activities and glucose levels. Transcriptome analysis identified 1079 differentially expressed genes (DEGs) in LcINH1-silenced fruits. KEGG analysis showed significant enrichment of DEGs in pathways related to transporters and plant hormone signal transduction. Weighted gene co-expression network analysis indicated that the turquoise module was highly correlated with fructose content, and LcSWEET3b was closely associated with early seed development. These findings suggest that LcINH1 regulate LcCWIN5 activity at the post-translational level to alter sucrose metabolism, thereby affecting early seed development in litchi.

Integrated Single-Cell Multiomic Profiling of Caudate Nucleus Suggests Key Mechanisms in Alcohol Use Disorder

Alcohol use disorder (AUD) is likely associated with complex transcriptional alterations in addiction-relevant brain regions. We characterize AUD-associated differences in cell type-specific gene expression and chromatin accessibility in the caudate nucleus by conducting a single-nucleus RNA-seq assay and a single-nucleus RNA-seq + ATAC-seq (multiome) assay on caudate tissue from 143 human postmortem brains (74 with AUD). We identified 17 cell types. AUD was associated with a higher proportion of microglia in an activated state and more astrocytes in a reactive state. There was widespread evidence for differentially expressed genes across cell types with the most identified in oligodendrocytes and astrocytes, including genes involved in immune response and synaptic regulation, many of which appeared to be regulated in part by JUND and OLIG2. Microglia-astrocyte communication via interleukin-1 beta, and microglia-astrocyte-oligodendrocyte interaction via transforming growth factor beta 1 were increased in individuals with AUD. Expression quantitative trait loci analysis revealed potential driver genes of AUD, including ADAL, that may protect against AUD in medium spiny neurons and interneurons. This work provides a thorough profile of the effects of AUD in the human brain and identifies several promising genes for further study.

A python library for the fast and scalable computation of biologically meaningful individual specific networks

Individual Specific Networks (ISNs) are a tool used in computational biology to infer Individual Specific relationships between biological entities from omics data. ISNs provide insights into how the interactions among these entities affect their respective functions. To address the scarcity of solutions for efficiently computing ISNs on large biological datasets, we present ISN-tractor, a data-agnostic, highly optimized Python library to build and analyse ISNs. ISN-tractor demonstrates superior scalability and efficiency in generating Individual Specific Networks (ISNs) when compared to existing methods such as LionessR, both in terms of time and memory usage, allowing ISNs to be used on large datasets. We show how ISN-tractor can be applied to real-life datasets, including The Cancer Genome Atlas (TCGA) and HapMap, showcasing its versatility. ISN-tractor can be used to build ISNs from various -omics data types, including transcriptomics, proteomics, and genotype arrays, and can detect distinct patterns of gene interactions within and across cancer types. We also show how Filtration Curves provided valuable insights into ISN characteristics, revealing topological distinctions among individuals with different clinical outcomes. Additionally, ISN-tractor can effectively cluster populations based on genetic relationships, as demonstrated with Principal Component Analysis on HapMap data.

Identification of potential diagnostic genes for atherosclerosis in women with polycystic ovary syndrome

Polycystic ovary syndrome (PCOS), which is the most prevalent endocrine disorder among women in their reproductive years, is linked to a higher occurrence and severity of atherosclerosis (AS). Nevertheless, the precise manner in which PCOS impacts the cardiovascular well-being of women remains ambiguous. The Gene Expression Omnibus database provided four PCOS datasets and two AS datasets for this study. Through the examination of genes originating from differentially expressed (DEGs) and critical modules utilizing functional enrichment analyses, weighted gene co-expression network (WGCNA), and machine learning algorithm, the research attempted to discover potential diagnostic genes. Additionally, the study investigated immune infiltration and conducted gene set enrichment analysis (GSEA) to examine the potential mechanism of the simultaneous occurrence of PCOS and AS. Two verification datasets and cell experiments were performed to assess biomarkers' reliability. The PCOS group identified 53 genes and AS group identified 175 genes by intersecting DEGs and key modules of WGCNA. Then, 18 genes from two groups were analyzed by machine learning algorithm. Death Associated Protein Kinase 1 (DAPK1) was recognized as an essential gene. Immune infiltration and single-gene GSEA results suggest that DAPK1 is associated with T cell-mediated immune responses. The mRNA expression of DAPK1 was upregulated in ox-LDL stimulated RAW264.7 cells and in granulosa cells. Our research discovered the close association between AS and PCOS, and identified DAPK1 as a crucial diagnostic biomarker for AS in PCOS.

Chemosynthetic alphaproteobacterial diazotrophs reside in deep-sea cold-seep bottom waters

Nitrogen (N)-fixing organisms, also known as diazotrophs, play a crucial role in N-limited ecosystems by controlling the production of bioavailable N. The carbon-dominated cold-seep ecosystems are inherently N-limited, making them hotspots of N fixation. However, the knowledge of diazotrophs in cold-seep ecosystems is limited compared to other marine ecosystems. In this study, we used multi-omics to investigate the diversity and catabolism of diazotrophs in deep-sea cold-seep bottom waters. Our findings showed that the relative abundance of diazotrophs in the bacterial community reached its highest level in the cold-seep bottom waters compared to the cold-seep upper waters and non-seep bottom waters. Remarkably, more than 98% of metatranscriptomic reads aligned on diazotrophs in cold-seep bottom waters belonged to the genus Sagittula, an alphaproteobacterium. Its metagenome-assembled genome, named Seep-BW-D1, contained catalytic genes (nifHDK) for nitrogen fixation, and the nifH gene was actively transcribed in situ. Seep-BW-D1 also exhibited chemosynthetic capability to oxidize C1 compounds (methanol, formaldehyde, and formate) and thiosulfate (S2O32-). In addition, we observed abundant transcripts mapped to genes involved in the transport systems for acetate, spermidine/putrescine, and pectin oligomers, suggesting that Seep-BW-D1 can utilize organics from the intermediates synthesized by methane-oxidizing microorganisms, decaying tissues from cold-seep benthic animals, and refractory pectin derived from upper photosynthetic ecosystems. Overall, our study corroborates that carbon-dominated cold-seep bottom waters select for diazotrophs and reveals the catabolism of a novel chemosynthetic alphaproteobacterial diazotroph in cold-seep bottom waters.

IMPORTANCE

Bioavailable nitrogen (N) is a crucial element for cellular growth and division, and its production is controlled by diazotrophs. Marine diazotrophs contribute to nearly half of the global fixed N and perform N fixation in various marine ecosystems. While previous studies mainly focused on diazotrophs in the sunlit ocean and oxygen minimum zones, recent research has recognized cold-seep ecosystems as overlooked N-fixing hotspots because the seeping fluids in cold-seep ecosystems introduce abundant bioavailable carbon but little bioavailable N, making most cold seeps inherently N-limited. With thousands of cold-seep ecosystems detected at continental margins worldwide in the past decades, the significant role of cold seeps in marine N biogeochemical cycling is emphasized. However, the diazotrophs in cold-seep bottom waters remain poorly understood. Through multi-omics, this study identified a novel alphaproteobacterial chemoheterotroph belonging to Sagittula as one of the most active diazotrophs residing in cold-seep bottom waters and revealed its catabolism.

Comparing time-series transcriptomes between chilling-resistant and -susceptible rice reveals potential transcription factors responding to chilling stress

Low temperature is one of the most important environmental factors that inhibits rice growth and grain yield. Transcription factors (TFs) play crucial roles in chilling acclimation by regulating gene expression. However, transcriptional dynamics and key regulators responding to low temperature remain largely unclear in rice. In this study, a transcriptome-based comparative analysis was performed to explore genome-wide gene expression profiles between a chilling-resistant cultivar DC90 and a chilling-susceptible cultivar 9311 at a series of time points under low temperature treatment and recovery condition. A total of 3,590 differentially expressed genes (DEGs) between two cultivars were determined and divided into 12 co-expression modules. Meanwhile, several biological processes participating in the chilling response such as abscisic acid (ABA) responses, water deprivation, protein metabolic processes, and transcription regulator activities were revealed. Through weighted gene co-expression network analysis (WGCNA), 15 hub TFs involved in chilling conditions were identified. Further, we used the gene regulatory network (GRN) to evaluate the top 50 TFs, which might have potential roles responding to chilling stress. Finally, five TFs, including a C-repeat binding factor (OsCBF3), a zinc finger-homeodomain protein (OsZHD8), a tandem zinc finger protein (OsTZF1), carbon starved anther (CSA), and indeterminate gametophyte1 (OsIG1) were identified as crucial candidates responsible for chilling resistance in rice. This study deepens our understanding in the gene regulation networks of chilling stress in rice and offers potential gene resources for breeding climate-resilient crops.

Reference genome sequence and population genomic analysis of peas provide insights into the genetic basis of Mendelian and other agronomic traits

Peas are essential for human nutrition and played a crucial role in the discovery of Mendelian laws of inheritance. In this study, we assembled the genome of the elite vegetable pea cultivar 'Zhewan No. 1' at the chromosome level and analyzed resequencing data from 314 accessions, creating a comprehensive map of genetic variation in peas. We identified 235 candidate loci associated with 57 important agronomic traits through genome-wide association studies. Notably, we pinpointed the causal gene haplotypes responsible for four Mendelian traits: stem length (Le/le), flower color (A/a), cotyledon color (I/i) and seed shape (R/r). Additionally, we discovered the genes controlling pod form (Mendelian P/p) and hilum color. Our study also involved constructing a gene expression atlas across 22 tissues, highlighting key gene modules related to pod and seed development. These findings provide valuable pea genomic information and will facilitate the future genome-informed improvement of pea crops.

Identifying polyamine related biomarkers in diagnosis and treatment of ulcerative colitis by integrating bulk and single-cell sequencing data

Ulcerative colitis (UC) is a chronic inflammatory disorder of the colon, and its pathogenesis remains unclear. Polyamine metabolic enzymes play a crucial role in UC. In this study, we aimed to identify pivotal polyamine-related genes (PRGs) and explore the underlying mechanism between PRGs and the disease status and therapeutic response of UC. We analyzed mRNA-sequencing data and clinical information of UC patients from the GEO database and identified NNMT, PTGS2, TRIM22, TGM2, and PPARG as key PRGs associated with active UC using differential expression analysis and weighted gene co-expression network analysis (WCGNA). Receiver operator characteristic curve (ROC) analysis confirmed the accuracy of these key genes in UC and colitis-associated colon cancer (CAC) diagnosis, and we validated their relationship with therapeutic response in external verification sets. Additionally, single-cell analysis revealed that the key PRGs were specific to certain immune cell types, emphasizing the vital role of intestinal tissue stem cells in active UC. The results were validated in vitro and in vivo experiments, including the colitis mice model and CAC mice model. In conclusion, these key PRGs effectively predict the progression of UC patients and could serve as new pharmacological biomarkers for the therapeutic response of UC.

Developmental toxicity of the neonicotinoid pesticide clothianidin to the larvae of the crustacean Decapoda, Penaeus vannamei

The developmental toxicity effects of neonicotinoid pesticides such as clothianidin have not been fully explored in agricultural applications. This is particularly noteworthy because such pesticides significantly impact the survival rates of invertebrates, with arthropod larvae being particularly vulnerable. This study aimed to address this research gap by specifically investigating the toxicological effects of clothianidin on the developmental stages of the larvae of the economically important aquaculture species Penaeus vannamei. In these experiments, shrimp eggs were exposed to seawater containing different concentrations of clothianidin beginning at N1, and each phase was observed and analyzed to determine its toxic impact on larval development. These results revealed that clothianidin induces an increase in deformity rates and triggers abnormal cell apoptosis. It also significantly reduced survival rates and markedly decreased body length and heart rate in the later stages of larval development (P3). Transcriptomic analysis revealed disruptions in larval DNA integrity, protein synthesis, and signal transduction caused by clothianidin. To survive prolonged exposure, larvae may attempt to maintain their viability by repairing cell structures and enhancing signal transduction mechanisms. This study offers the first empirical evidence of the toxicity of clothianidin to arthropod larvae, underscoring the impact of environmental pollution on aquatic health.

Evolution of the biosynthetic pathways of terpene scent compounds in roses

It is unknown why roses are terpene-rich, what the terpene biosynthetic pathways in roses are, and why only a few rose species produce the major components of rose essential oil. Here, we assembled two high-quality chromosome-level genomes for Rosa rugosa and Rosa multiflora. We also re-sequenced 132 individuals from the F1 progeny of Rosa chinensis and Rosa wichuraiana and 36 of their related species. Comparative genomics revealed that expansions of the 3-hydroxy-3-methylglutaryl-coenzyme A reductase (HMGR) and terpene synthases (TPSs) gene families led to the enrichment of terpenes in rose scent components. We constructed a terpene biosynthesis network and discovered a TPS-independent citronellol biosynthetic pathway in roses through gene functional identification, genome-wide association studies (GWASs), and multi-omic analysis. Heterologous co-expression of rose citronellol biosynthetic genes in Nicotiana benthamiana led to citronellol production. Our genomic and metabolomic analyses suggested that the copy number of NUDX1-1a determines the citronellol content in different rose species. Our findings not only provide additional genome and gene resources and reveal the evolution of the terpene biosynthetic pathways but also present a nearly complete scenario for terpenoid metabolism that will facilitate the breeding of fragrant roses and the production of rose oil.

Resources modulate developmental shifts but not infection tolerance upon coinfection in an insect system

Energetic resources fuel immune responses and parasite growth within organisms, but it is unclear whether energy allocation is sufficient to explain changes in infection outcomes under the threat of multiple parasites. We manipulated diet in flour beetles (Tribolium confusum) infected with two natural parasites to investigate the role of resources in shifting metabolic and immune responses after single and co-infection. Our results suggest that gregarine parasites alter the within-host energetic environment, and by extension juvenile development time, in a diet-dependent manner. Gregarines do not affect host resistance to acute bacterial infection but do stimulate the expression of an alternative set of immune genes and promote damage to the gut, ultimately contributing to reduced survival regardless of diet. Thus, energy allocation is not sufficient to explain the immunological contribution to coinfection outcomes, emphasizing the importance of mechanistic insight for predicting the impact of coinfection across levels of biological organization.

The influence of CLEC5A on early macrophage-mediated inflammation in COPD progression

Chronic obstructive pulmonary disease (COPD) is a complex syndrome with poorly understood mechanisms driving its early progression (GOLD stages 1-2). Elucidating the genetic factors that influence early-stage COPD, particularly those related to airway inflammation and remodeling, is crucial. This study analyzed lung tissue sequencing data from patients with early-stage COPD (GSE47460) and smoke-exposed mice. We employed Weighted Gene Co-Expression Network Analysis (WGCNA) and machine learning to identify potentially pathogenic genes. Further analyses included single-cell sequencing from both mice and COPD patients to pinpoint gene expression in specific cell types. Cell-cell communication and pseudotemporal analyses were conducted, with findings validated in smoke-exposed mice. Additionally, Mendelian randomization (MR) was used to confirm the association between candidate genes and lung function/COPD. Finally, functional validation was performed in vitro using cell cultures. Machine learning analysis of 30 differentially expressed genes identified 8 key genes, with CLEC5A emerging as a potential pathogenic factor in early-stage COPD. Bioinformatics analyses suggested a role for CLEC5A in macrophage-mediated inflammation during COPD. Two-sample Mendelian randomization linked CLEC5A single nucleotide polymorphisms (SNPs) with Forced Expiratory Volume in One Second (FEV1), FEV1/Forced Vital Capacity (FVC) and early/later on COPD. In vitro, the knockdown of CLEC5A led to a reduction in inflammatory markers within macrophages. Our study identifies CLEC5A as a critical gene in early-stage COPD, contributing to its pathogenesis through pro-inflammatory mechanisms. This discovery offers valuable insights for developing early diagnosis and treatment strategies for COPD and highlights CLEC5A as a promising target for further investigation.

Transcriptomics and weighted protein network analyses of the LRRK2 protein interactome reveal distinct molecular signatures for sporadic and LRRK2 Parkinson's Disease

Mutations in the LRRK2 gene are the most common genetic cause of familial Parkinson's Disease (LRRK2-PD) and an important risk factor for sporadic PD (sPD). Multiple clinical trials are ongoing to evaluate the benefits associated with the therapeutical reduction of LRRK2 kinase activity. In this study, we described the changes of transcriptomic profiles (whole blood mRNA levels) of LRRK2 protein interactors in sPD and LRRK2-PD cases as compared to healthy controls with the aim of comparing the two PD conditions. We went on to model the protein-protein interaction (PPI) network centred on LRRK2, which was weighted to reflect the transcriptomic changes on expression and co-expression levels of LRRK2 protein interactors. Our results showed that LRRK2 interactors present both similar and distinct alterations in expression levels and co-expression behaviours in the sPD and LRRK2-PD cases; suggesting that, albeit being classified as the same disease based on clinical features, LRRK2-PD and sPD display significant differences from a molecular perspective. Interestingly, the similar changes across the two PD conditions result in decreased connectivity within a topological cluster of the LRRK2 PPI network associated with protein metabolism/biosynthesis and ribosomal metabolism suggesting protein homoeostasis and ribosomal dynamics might be affected in both sporadic and familial PD in comparison with controls.

Comparative transcriptome provides new insights into the molecular regulation of olive trees to chilling stress

Olive (Olea europaea L.), an economically important oil-producing crop, is sensitive to low temperature, which severely limits its productivity and geographical distribution. However, the underlying mechanism of cold tolerance in olive remains elusive. In this study, a chilling experiment (4 °C) on the living saplings of two olive cultivars revealed that O. europaea cv. Arbequina showed stronger cold tolerance with greater photosynthetic activity compared with O. europaea cv. Leccino. Transcriptome analyses revealed that early light-inducible protein 1 (ELIP1), the main regulator for chlorophyll synthesis, is dramatically induced to protect the photosynthesis at low temperatures. Furthermore, weighted gene co-expression network analysis, yeast one-hybrid and luciferase assays demonstrated that transcription factor bHLH66 serves as an important regulator of ELIP1 transcription by binding to the G-box motif in the promoter. Taken together, our research revealed a novel transcriptional module consisting of bHLH66-ELIP1 in the adaptation of olive trees to cold stress.

Identification of TFRC as a biomarker for pulmonary arterial hypertension based on bioinformatics and experimental verification

BACKGROUND

Pulmonary arterial hypertension (PAH) is a life-threatening chronic cardiopulmonary disease. However, there is a paucity of studies that reflect the available biomarkers from separate gene expression profiles in PAH.

METHODS

The GSE131793 and GSE113439 datasets were combined for subsequent analyses, and batch effects were removed. Bioinformatic analysis was then performed to identify differentially expressed genes (DEGs). Weighted gene co-expression network analysis (WGCNA) and a protein-protein interaction (PPI) network analysis were then used to further filter the hub genes. Functional enrichment analysis of the intersection genes was performed using Gene Ontology (GO), Disease Ontology (DO), Kyoto encyclopedia of genes and genomes (KEGG) and gene set enrichment analysis (GSEA). The expression level and diagnostic value of hub gene expression in pulmonary arterial hypertension (PAH) patients were also analyzed in the validation datasets GSE53408 and GSE22356. In addition, target gene expression was validated in the lungs of a monocrotaline (MCT)-induced pulmonary hypertension (PH) rat model and in the serum of PAH patients.

RESULTS

A total of 914 differentially expressed genes (DEGs) were identified, with 722 upregulated and 192 downregulated genes. The key module relevant to PAH was selected using WGCNA. By combining the DEGs and the key module of WGCNA, 807 genes were selected. Furthermore, protein-protein interaction (PPI) network analysis identified HSP90AA1, CD8A, HIF1A, CXCL8, EPRS1, POLR2B, TFRC, and PTGS2 as hub genes. The GSE53408 and GSE22356 datasets were used to evaluate the expression of TFRC, which also showed robust diagnostic value. According to GSEA enrichment analysis, PAH-relevant biological functions and pathways were enriched in patients with high TFRC levels. Furthermore, TFRC expression was found to be upregulated in the lung tissues of our experimental PH rat model compared to those of the controls, and the same conclusion was reached in the serum of the PAH patients.

CONCLUSIONS

According to our bioinformatics analysis, the observed increase of TFRC in the lung tissue of human PAH patients, as indicated by transcriptomic data, is consistent with the alterations observed in PAH patients and rodent models. These data suggest that TFRC may serve as a potential biomarker for PAH.

Integrated metabolomic and transcriptomic analysis reveals biosynthesis mechanism of flavone and caffeoylquinic acid in chrysanthemum

BACKGROUND

Chrysanthemum morifolium 'HangBaiJu', a popular medicinal and edible plant, exerts its biological activities primarily through the presence of flavones and caffeoylquinic acids (CQAs). However, the regulatory mechanism of flavone and CQA biosynthesis in the chrysanthemum capitulum remains unclear.

RESULTS

In this study, the content of flavones and CQAs during the development of chrysanthemum capitulum was determined by HPLC, revealing an accumulation pattern with higher levels at S1 and S2 and a gradual decrease at S3 to S5. Transcriptomic analysis revealed that CmPAL1/2, CmCHS1/2, CmFNS, CmHQT, and CmHCT were key structural genes in flavones and CQAs biosynthesis. Furthermore, weighted gene co-expression correlation network analysis (WGCNA), k-means clustering, correlation analysis and protein interaction prediction were carried out in this study to identify transcription factors (TFs) associated with flavone and CQA biosynthesis, including MYB, bHLH, AP2/ERF, and MADS-box families. The TFs CmERF/PTI6 and CmCMD77 were proposed to act as upstream regulators of CmMYB3 and CmbHLH143, while CmMYB3 and CmbHLH143 might form a complex to directly regulate the structural genes CmPAL1/2, CmCHS1/2, CmFNS, CmHQT, and CmHCT, thereby controlling flavone and CQA biosynthesis.

CONCLUSIONS

Overall, these findings provide initial insights into the TF regulatory network underlying flavones and CQAs accumulation in the chrysanthemum capitulum, which laid a theoretical foundation for the quality improvement of C. morifolium 'HangBaiJu' and the high-quality development of the industry.

Interactive molecular causal networks of hypertension using a fast machine learning algorithm MRdualPC

BACKGROUND

Understanding the complex interactions between genes and their causal effects on diseases is crucial for developing targeted treatments and gaining insight into biological mechanisms. However, the analysis of molecular networks, especially in the context of high-dimensional data, presents significant challenges.

METHODS

This study introduces MRdualPC, a computationally tractable algorithm based on the MRPC approach, to infer large-scale causal molecular networks. We apply MRdualPC to investigate the upstream causal transcriptomics influencing hypertension using a comprehensive dataset of kidney genome and transcriptome data.

RESULTS

Our algorithm proves to be 100 times faster than MRPC on average in identifying transcriptomics drivers of hypertension. Through clustering, we identify 63 modules with causal driver genes, including 17 modules with extensive causal networks. Notably, we find that genes within one of the causal networks are associated with the electron transport chain and oxidative phosphorylation, previously linked to hypertension. Moreover, the identified causal ancestor genes show an over-representation of blood pressure-related genes.

CONCLUSIONS

MRdualPC has the potential for broader applications beyond gene expression data, including multi-omics integration. While there are limitations, such as the need for clustering in large gene expression datasets, our study represents a significant advancement in building causal molecular networks, offering researchers a valuable tool for analyzing big data and investigating complex diseases.