Transcriptomic alterations in cortical astrocytes following the development of post-traumatic epilepsy.

Post-traumatic epilepsy (PTE) stands as one of the numerous debilitating consequences that follow traumatic brain injury (TBI). Despite its impact on many individuals, the current landscape offers only a limited array of reliable treatment options, and our understanding of the underlying mechanisms and susceptibility factors remains incomplete. Among the potential contributors to epileptogenesis, astrocytes, a type of glial cell, have garnered substantial attention as they are believed to promote hyperexcitability and the development of seizures in the brain following TBI. The current study evaluated the transcriptomic changes in cortical astrocytes derived from animals that developed seizures as a result of severe focal TBI. Using RNA-Seq and ingenuity pathway analysis (IPA), we unveil a distinct gene expression profile in astrocytes, including alterations in genes supporting inflammation, early response modifiers, and neuropeptide-amidating enzymes. The findings underscore the complex molecular dynamics in astrocytes during PTE development, offering insights into therapeutic targets and avenues for further exploration.

Cold-stress induced metabolomic and transcriptomic changes in leaves of three mango varieties with different cold tolerance.

BACKGROUND: Mango (Mangifera indica L.) is grown in Hainan, Guangdong, Yunnan, Sichuan, and Fujian provinces and Guanxi autonomous region of China. However, trees growing in these areas suffer severe cold stress during winter, which affects the yield. To this regard, data on global metabolome and transcriptome profiles of leaves are limited. Here, we used combined metabolome and transcriptome analyses of leaves of three mango cultivars with different cold stress tolerance, i.e. Jinhuang (J)-tolerant, Tainung (T) and Guiremang No. 82 (G)-susceptible, after 24 (LF), 48 (MF) and 72 (HF) hours of cold. RESULTS: A total of 1,323 metabolites belonging to 12 compound classes were detected. Of these, amino acids and derivatives, nucleotides and derivatives, and lipids accumulated in higher quantities after cold stress exposure in the three cultivars. Notably, Jinhuang leaves showed increasing accumulation trends of flavonoids, terpenoids, lignans and coumarins, and alkaloids with exposure time. Among the phytohormones, jasmonic acid and abscisic acid levels decreased, while N6-isopentenyladenine increased with cold stress time. Transcriptome analysis led to the identification of 22,526 differentially expressed genes. Many genes enriched in photosynthesis, antenna proteins, flavonoid, terpenoid (di- and sesquiterpenoids) and alkaloid biosynthesis pathways were upregulated in Jihuang leaves. Moreover, expression changes related to phytohormones, MAPK (including calcium and H2O2), and the ICE-CBF-COR signalling cascade indicate involvement of these pathways in cold stress responses. CONCLUSION: Cold stress tolerance in mango leaves is associated with regulation of primary and secondary metabolite biosynthesis pathways. Jasmonic acid, abscisic acid, and cytokinins are potential regulators of cold stress responses in mango leaves.

Distinct actions of testicular endocrine and lumicrine signaling on the proximal epididymal transcriptome.

The epididymal function and gene expression in mammals are under the control of the testis. Sex steroids are secreted from the testis and act on the epididymis in an endocrine manner. There is another, non-sex steroidal secreted signaling, named lumicrine signaling, in which testis-derived secreted proteins go through the male reproductive tract and act on the epididymis. The effects of such multiple regulations on the epididymis by the testis have been investigated for many genes. The recent development of high-throughput next-generation sequencing now enables us a further comparative survey of endocrine and lumicrine action-dependent gene expression. In the present study, testis-derived endocrine and lumicrine actions on epididymal gene expression were comparatively investigated by RNA-seq transcriptomic analyses. This investigation utilized experimental animal models in which testis-derived endocrine and/or lumicrine actions were interfered with, such as unilateral or bilateral orchidectomy. By bilateral orchidectomy, which interferes with both endocrine and lumicrine actions, 431 genes were downregulated. By unilateral orchidectomy, which also interferes with endocrine and lumicrine actions by the unilateral testis, but the endocrine action was compensated by the contralateral testis, 283 genes were downregulated. The content of such genes downregulated by unilateral orchidectomy was like those of lumicrine action-interfered efferent duct-ligation, W/Wv, and Nell2-/- mice. When genes affected by unilateral and bilateral orchidectomy were compared, 154 genes were commonly downregulated, whereas 217 genes were specifically downregulated only by bilateral orchidectomy, indicating the distinction between endocrine and lumicrine actions on the proximal epididymal transcriptome. Comparative transcriptome analyses also showed that the expressions of genes emerging since Amniota were notably impacted by bilateral orchidectomy, unilateral orchidectomy, and lumicrine action-interfering treatments; the degree of influence from these treatments varied based on the evolutionary stage beyond Amniota. These findings unveil an evolutional transition of regulated gene expression in the proximal epididymis by two different testis-derived signaling mechanisms.

Unveiling the role of HIST2H2AC in stroke through single-cell and transcriptome analysis.

Stroke is a leading cause of death and disability, and genetic risk factors play a significant role in its development. Unfortunately, effective therapies for stroke are currently limited. Early detection and diagnosis are critical for improving outcomes and developing new treatment strategies. In this study, we aimed to identify potential biomarkers and effective prevention and treatment strategies for stroke by conducting transcriptome and single-cell analyses. Our analysis included screening for biomarkers, functional enrichment analysis, immune infiltration, cell-cell communication, and single-cell metabolism. Through differential expression analysis, enrichment analysis, and protein-protein interaction (PPI) network construction, we identified HIST2H2AC as a potential biomarker for stroke. Our study also highlighted the diagnostic role of HIST2H2AC in stroke, its relationship with immune cells in the stroke environment, and our improved understanding of metabolic pathways after stroke. Overall, our research provided important insights into the pathogenesis of stroke, including potential biomarkers and treatment strategies that can be explored further to improve outcomes for stroke patients.

Transcriptomic Data Analysis Using the Galaxy Platform: Coffee (Coffea arabica L.) Flowers as Example.

Coffee, an important agricultural product for tropical producing countries, is facing challenges due to climate change, including periods of drought, irregular rain distribution, and high temperatures. These changes result in plant water stress, leading to significant losses in coffee productivity and quality. Understanding the processes that affect coffee flowering is crucial for improving productivity and quality. In this chapter, we describe a protocol for transcriptome analysis using available Internet software, mainly in the Galaxy Platform, using RNA-Seq data from flowers collected from different parts of the coffee tree. The methods presented in this chapter provide a comprehensive protocol for transcriptome analysis of differentially expressed genes from flowers of coffee plant. This knowledge can be utilized in coffee genetic improvement programs, particularly in the selection of cultivars that are tolerant to water deficit.

Detecting early-warning biomarkers associated with heart-exosome genetic-signature for acute myocardial infarction: A source-tracking study of exosome.

The genetic information of plasma total-exosomes originating from tissues have already proven useful to assess the severity of coronary artery diseases (CAD). However, plasma total-exosomes include multiple sub-populations secreted by various tissues. Only analysing the genetic information of plasma total-exosomes is perturbed by exosomes derived from other organs except the heart. We aim to detect early-warning biomarkers associated with heart-exosome genetic-signatures for acute myocardial infarction (AMI) by a source-tracking analysis of plasma exosome. The source-tracking of AMI plasma total-exosomes was implemented by deconvolution algorithm. The final early-warning biomarkers associated with heart-exosome genetic-signatures for AMI was identified by integration with single-cell sequencing, weighted gene correction network and machine learning analyses. The correlation between biomarkers and clinical indicators was validated in impatient cohort. A nomogram was generated using early-warning biomarkers for predicting the CAD progression. The molecular subtypes landscape of AMI was detected by consensus clustering. A higher fraction of exosomes derived from spleen and blood cells was revealed in plasma exosomes, while a lower fraction of heart-exosomes was detected. The gene ontology revealed that heart-exosomes genetic-signatures was associated with the heart development, cardiac function and cardiac response to stress. We ultimately identified three genes associated with heart-exosomes defining early-warning biomarkers for AMI. The early-warning biomarkers mediated molecular clusters presented heterogeneous metabolism preference in AMI. Our study introduced three early-warning biomarkers associated with heart-exosome genetic-signatures, which reflected the genetic information of heart-exosomes carrying AMI signals and provided new insights for exosomes research in CAD progression and prevention.

Anti-inflammatory and immunoregulatory effects of colistin sulphate on human PBMCs.

In previous studies, CST has been identified as having an immunostimulatory effect on Caenorhabditis elegans and macrophage of rats. Here, we further investigated its immunomodulatory effects on human peripheral blood mononuclear cells (PBMCs). LPS-stimulated PBMCs inflammatory model was established. Flow cytometry was applied to measure phagocytosis of PBMCs. Cytokine mRNA and protein expression levels of LPS-stimulated PBMCs with or without CST were measured by qRT-PCR and ELISA. The transcriptomic profile of CST-treated PBMCs was investigated by RNA-sequencing. Gene Ontology (GO) and Kyoto Encylopedia of Genes and Genomes (KEGG) were applied to find potential signalling pathways. PBMCs showed a significant increase in phagocytic activity at 6 h after being incubated with CST at the concentration of 10 µg/mL. In the presence of LPS, CST maintained and promoted the expression of TNF-α and chemokine CCL24. The content of pro-inflammatory cytokines, such as IL-1ß, IL-6 and IFN-γ, which were released from LPS-stimulated PBMCs, was reduced by CST at 6 h. Anti-inflammatory cytokines, such as IL-4, IL-13 and TGF-ß1, were significantly increased by CST at 24 h. A total of 277 differentially expressed immune-related genes (DEIRGs) were detected and cytokine-cytokine receptor interaction was highly enriched. CST presented obvious anti-inflammatory and immunoregulatory effects in LPS-induced PBMCs inflammatory model not only by improving the ability of PBMCs to clear pathogens but also by decreasing pro-inflammatory cytokines and increasing anti-inflammatory cytokines. And the mechanism may be related to cytokine-cytokine receptor interaction.

Unveiling unique alternative splicing responses to low temperature in Zoysia japonica through ZjRTD1.0, a high-quality reference transcript dataset.

Inadequate reference databases in RNA-seq analysis can hinder data utilization and interpretation. In this study, we have successfully constructed a high-quality reference transcript dataset, ZjRTD1.0, for Zoysia japonica, a widely-used turfgrass with exceptional tolerance to various abiotic stress, including low temperatures and salinity. This dataset comprises 113,089 transcripts from 57,143 genes. BUSCO analysis demonstrates exceptional completeness (92.4%) in ZjRTD1.0, with reduced proportions of fragmented (3.3%) and missing (4.3%) orthologs compared to prior datasets. ZjRTD1.0 enables more precise analyses, including transcript quantification and alternative splicing assessments using public datasets, which identified a substantial number of differentially expressed transcripts (DETs) and differential alternative splicing (DAS) events, leading to several novel findings on Z. japonica's responses to abiotic stresses. First, spliceosome gene expression influenced alternative splicing significantly under abiotic stress, with a greater impact observed during low-temperature stress. Then, a significant positive correlation was found between the number of differentially expressed genes (DEGs) encoding protein kinases and the frequency of DAS events, suggesting the role of protein phosphorylation in regulating alternative splicing. Additionally, our results suggest possible involvement of serine/arginine-rich (SR) proteins and heterogeneous nuclear ribonucleoproteins (hnRNPs) in generating inclusion/exclusion isoforms under low-temperature stress. Furthermore, our investigation revealed a significantly enhanced overlap between DEGs and differentially alternatively spliced genes (DASGs) in response to low-temperature stress, suggesting a unique co-regulatory mechanism governing transcription and splicing in the context of low-temperature response. In conclusion, we have proven that ZjRTD1.0 will serve as a reliable and useful resource for future transcriptomic analyses in Z. japonica.

Differentially expressed genes of esophageal tissue in male acute and chronic sleep deprivation mice.

Gastroesophageal reflux disease (GERD) is associated with sleep disturbances. However, mechanisms underlying these interactions remain unclear. Male acute and chronic sleep deprivation (SD) mice were used for this study. Mice in the chronic SD group exhibited anxiety- and depression-like behaviors. We further performed high-throughput genome sequencing and bioinformatics analysis to screen for featured differentially expressed genes (DEGs) in the esophageal tissue. The acute SD group, comprised 25 DEGs including 14 downregulated and 11 upregulated genes. Compared with the acute SD group, more DEGs were present in the chronic SD group, with a total of 169 DEGs, including 88 downregulated and 81 upregulated genes. Some DEGs that were closely related to GERD and associated esophageal diseases were significantly different in the chronic SD group. Quantitative real-time polymerase chain reaction verified the downregulation of Krt4, Krt13, Krt15 and Calml3 and upregulation of Baxl1 and Per3. Notably, these DEGs are involved in biological processes, which might be the pathways of the neuroregulatory mechanisms of DEGs expression.

Cross-modality mapping using image varifolds to align tissue-scale atlases to molecular-scale measures with application to 2D brain sections.

This paper explicates a solution to building correspondences between molecular-scale transcriptomics and tissue-scale atlases. This problem arises in atlas construction and cross-specimen/technology alignment where specimens per emerging technology remain sparse and conventional image representations cannot efficiently model the high dimensions from subcellular detection of thousands of genes. We address these challenges by representing spatial transcriptomics data as generalized functions encoding position and high-dimensional feature (gene, cell type) identity. We map onto low-dimensional atlas ontologies by modeling regions as homogeneous random fields with unknown transcriptomic feature distribution. We solve simultaneously for the minimizing geodesic diffeomorphism of coordinates through LDDMM and for these latent feature densities. We map tissue-scale mouse brain atlases to gene-based and cell-based transcriptomics data from MERFISH and BARseq technologies and to histopathology and cross-species atlases to illustrate integration of diverse molecular and cellular datasets into a single coordinate system as a means of comparison and further atlas construction.

Full-length transcriptome analysis of a bloom-forming dinoflagellate Prorocentrum shikokuense (Dinophyceae).

Prorocentrum shikokuense (formerly P. donghaiense) is a pivotal dinoflagellate species associating with the HABs in the East China Sea. The complexity of its large nuclear genome hindered us from understanding its genomic characteristics. Full-length transcriptome sequencing offers a practical solution to decipher the physiological mechanisms of a species without the reference genome. In this study, we employed single-molecule real-time (SMRT) sequencing technology to sequence the full-length transcriptome of Prorocentrum shikokuense. We successfully generated 41.73 Gb of clean SMRT sequencing reads and isolated 105,249 non-redundant full-length non-chimeric reads. Our trial has led to the identification of 11,917 long non-coding RNA transcripts, 514 alternative splicing events, 437 putative transcription factor genes from 17 TF gene families, and 34,723 simple sequence repeats. Additionally, a total of 78,265 open reading frames were identified, of them 15,501 were the protein coding sequences. This dataset is valuable for annotating P. shikokuense genome, and will contribute significantly to the in-depth studies on the molecular mechanisms underlining the dinoflagellate bloom formation.

Joint Bayesian estimation of cell dependence and gene associations in spatially resolved transcriptomic data.

Recent technologies such as spatial transcriptomics, enable the measurement of gene expressions at the single-cell level along with the spatial locations of these cells in the tissue. Spatial clustering of the cells provides valuable insights into the understanding of the functional organization of the tissue. However, most such clustering methods involve some dimension reduction that leads to a loss of the inherent dependency structure among genes at any spatial location in the tissue. This destroys valuable insights of gene co-expression patterns apart from possibly impacting spatial clustering performance. In spatial transcriptomics, the matrix-variate gene expression data, along with spatial coordinates of the single cells, provides information on both gene expression dependencies and cell spatial dependencies through its row and column covariances. In this work, we propose a joint Bayesian approach to simultaneously estimate these gene and spatial cell correlations. These estimates provide data summaries for downstream analyses. We illustrate our method with simulations and analysis of several real spatial transcriptomic datasets. Our work elucidates gene co-expression networks as well as clear spatial clustering patterns of the cells. Furthermore, our analysis reveals that downstream spatial-differential analysis may aid in the discovery of unknown cell types from known marker genes.

Integrated metabolome and transcriptome analyses reveal the role of BoGSTF12 in anthocyanin accumulation in Chinese kale (Brassica oleracea var. alboglabra).

BACKGROUND: The vivid red, purple, and blue hues that are observed in a variety of plant fruits, flowers, and leaves are produced by anthocyanins, which are naturally occurring pigments produced by a series of biochemical processes occurring inside the plant cells. The purple-stalked Chinese kale, a popular vegetable that contains anthocyanins, has many health benefits but needs to be investigated further to identify the genes involved in the anthocyanin biosynthesis and translocation in this vegetable. RESULTS: In this study, the purple- and green-stalked Chinese kale were examined using integrative transcriptome and metabolome analyses. The content of anthocyanins such as cyanidin-3-O-(6″-O-feruloyl) sophoroside-5-O-glucoside, cyanidin-3,5-O-diglucoside (cyanin), and cyanidin-3-O-(6″-O-p-hydroxybenzoyl) sophoroside-5-O-glucoside were considerably higher in purple-stalked Chinese kale than in its green-stalked relative. RNA-seq analysis indicated that 23 important anthocyanin biosynthesis genes, including 3 PAL, 2 C4H, 3 4CL, 3 CHS, 1 CHI, 1 F3H, 2 FLS, 2 F3'H, 1 DFR, 3 ANS, and 2 UFGT, along with the transcription factor BoMYB114, were significantly differentially expressed between the purple- and green-stalked varieties. Results of analyzing the expression levels of 11 genes involved in anthocyanin production using qRT-PCR further supported our findings. Association analysis between genes and metabolites revealed a strong correlation between BoGSTF12 and anthocyanin. We overexpressed BoGSTF12 in Arabidopsis thaliana tt19, an anthocyanin transport mutant, and this rescued the anthocyanin-loss phenotype in the stem and rosette leaves, indicating BoGSTF12 encodes an anthocyanin transporter that affects the accumulation of anthocyanins. CONCLUSION: This work represents a key step forward in our understanding of the molecular processes underlying anthocyanin production in Chinese kale. Our comprehensive metabolomic and transcriptome analyses provide important insights into the regulatory system that controls anthocyanin production and transport, while providing a foundation for further research to elucidate the physiological importance of the metabolites found in this nutritionally significant vegetable.

Effect of metabolically divergent pig breeds and tissues on mesenchymal stem cell expression patterns during adipogenesis.

BACKGROUND: Unraveling the intricate and tightly regulated process of adipogenesis, involving coordinated activation of transcription factors and signaling pathways, is essential for addressing obesity and related metabolic disorders. The molecular pathways recruited by mesenchymal stem cells (MSCs) during adipogenesis are also dependent on the different sources of the cells and genetic backgrounds of donors, which contribute to the functional heterogeneity of the stem cells and consequently affect the developmental features and fate of the cells. METHODS: In this study, the alteration of transcripts during differentiation of synovial mesenchymal stem cells (SMSCs) derived from fibrous synovium (FS) and adipose synovial tissue (FP) of two pig breeds differing in growth performance (German Landrace (DL)) and fat deposition (Angeln Saddleback (AS)) was investigated. SMSCs from both tissues and breeds were stimulated to differentiate into adipocytes in vitro and sampled at four time points (day 1, day 4, day 7 and day 14) to obtain transcriptomic data. RESULTS: We observed numerous signaling pathways related to the cell cycle, cell division, cell migration, or cell proliferation during early stages of adipogenesis. As the differentiation process progresses, cells begin to accumulate intracellular lipid droplets and changes in gene expression patterns in particular of adipocyte-specific markers occur. PI3K-Akt signaling and metabolic pathways changed most during adipogenesis, while p53 signaling and ferroptosis were affected late in adipogenesis. When comparing MSCs from FS and FP, only a limited number of differentially expressed genes (DEGs) and enriched signaling pathways were identified. Metabolic pathways, including fat, energy or amino acid metabolism, were highly enriched in the AS breed SMSCs compared to those of the DL breed, especially at day 7 of adipogenesis, suggesting retention of the characteristic metabolic features of their original source, demonstrating donor memory in culture. In contrast, the DL SMSCs were more enriched in immune signaling pathways. CONCLUSIONS: Our study has provided important insights into the dynamics of adipogenesis and revealed metabolic shifts in SMSCs associated with different cell sources and genetic backgrounds of donors. This emphasises the critical role of metabolic and genetic factors as important indications and criteria for donor stem cell selection.

Comparative transcriptome revealed the molecular responses of Aconitum carmichaelii Debx. to downy mildew at different stages of disease development.

BACKGROUND: Aconitum carmichaelii Debx. has been widely used as a traditional medicinal herb for a long history in China. It is highly susceptible to various dangerous diseases during the cultivation process. Downy mildew is the most serious leaf disease of A. carmichaelii, affecting plant growth and ultimately leading to a reduction in yield. To better understand the response mechanism of A. carmichaelii leaves subjected to downy mildew, the contents of endogenous plant hormones as well as transcriptome sequencing were analyzed at five different infected stages. RESULTS: The content of 3-indoleacetic acid, abscisic acid, salicylic acid and jasmonic acid has changed significantly in A. carmichaelii leaves with the development of downy mildew, and related synthetic genes such as 9-cis-epoxycarotenoid dioxygenase and phenylalanine ammonia lyase were also significant for disease responses. The transcriptomic data indicated that the differentially expressed genes were primarily associated with plant hormone signal transduction, plant-pathogen interaction, the mitogen-activated protein kinase signaling pathway in plants, and phenylpropanoid biosynthesis. Many of these genes also showed potential functions for resisting downy mildew. Through weighted gene co-expression network analysis, the hub genes and genes that have high connectivity to them were identified, which could participate in plant immune responses. CONCLUSIONS: In this study, we elucidated the response and potential genes of A. carmichaelii to downy mildew, and observed the changes of endogenous hormones content at different infection stages, so as to contribute to the further screening and identification of genes involved in the defense of downy mildew.

xWAS analysis in neuropsychiatric disorders by integrating multi-molecular phenotype quantitative trait loci and GWAS summary data.

BACKGROUND: Integrating quantitative trait loci (QTL) data related to molecular phenotypes with genome-wide association study (GWAS) data is an important post-GWAS strategic approach employed to identify disease-associated molecular features. Various types of molecular phenotypes have been investigated in neuropsychiatric disorders. However, these findings pertaining to distinct molecular features are often independent of each other, posing challenges for having an overview of the mapped genes. METHODS: In this study, we comprehensively summarized published analyses focusing on four types of risk-related molecular features (gene expression, splicing transcriptome, protein abundance, and DNA methylation) across five common neuropsychiatric disorders. Subsequently, we conducted supplementary analyses with the latest GWAS dataset and corresponding deficient molecular phenotypes using Functional Summary-based Imputation (FUSION) and summary data-based Mendelian randomization (SMR). Based on the curated and supplemented results, novel reliable genes and their functions were explored. RESULTS: Our findings revealed that eQTL exhibited superior ability in prioritizing risk genes compared to the other QTL, followed by sQTL. Approximately half of the genes associated with splicing transcriptome, protein abundance, and DNA methylation were successfully replicated by eQTL-associated genes across all five disorders. Furthermore, we identified 436 novel reliable genes, which enriched in pathways related with neurotransmitter transportation such as synaptic, dendrite, vesicles, axon along with correlations with other neuropsychiatric disorders. Finally, we identified ten multiple molecular involved regulation patterns (MMRP), which may provide valuable insights into understanding the contribution of molecular regulation network targeting these disease-associated genes. CONCLUSIONS: The analyses prioritized novel and reliable gene sets related with five molecular features based on published and supplementary results for five common neuropsychiatric disorders, which were missed in the original GWAS analysis. Besides, the involved MMRP behind these genes could be given priority for further investigation to elucidate the pathogenic molecular mechanisms underlying neuropsychiatric disorders in future studies.

Single-cell insights: pioneering an integrated atlas of chromatin accessibility and transcriptomic landscapes in diabetic cardiomyopathy.

BACKGROUND: Diabetic cardiomyopathy (DCM) poses a growing health threat, elevating heart failure risk in diabetic individuals. Understanding DCM is crucial, with fibroblasts and endothelial cells playing pivotal roles in driving myocardial fibrosis and contributing to cardiac dysfunction. Advances in Multimodal single-cell profiling, such as scRNA-seq and scATAC-seq, provide deeper insights into DCM's unique cell states and molecular landscape for targeted therapeutic interventions. METHODS: Single-cell RNA and ATAC data from 10x Multiome libraries were processed using Cell Ranger ARC v2.0.1. Gene expression and ATAC data underwent Seurat and Signac filtration. Differential gene expression and accessible chromatin regions were identified. Transcription factor activity was estimated with chromVAR, and Cis-coaccessibility networks were calculated using Cicero. Coaccessibility connections were compared to the GeneHancer database. Gene Ontology analysis, biological process scoring, cell-cell communication analysis, and gene-motif correlation was performed to reveal intricate molecular changes. Immunofluorescent staining utilized various antibodies on paraffin-embedded tissues to verify the findings. RESULTS: This study integrated scRNA-seq and scATAC-seq data obtained from hearts of WT and DCM mice, elucidating molecular changes at the single-cell level throughout the diabetic cardiomyopathy progression. Robust and accurate clustering analysis of the integrated data revealed altered cell proportions, showcasing decreased endothelial cells and macrophages, coupled with increased fibroblasts and myocardial cells in the DCM group, indicating enhanced fibrosis and endothelial damage. Chromatin accessibility analysis unveiled unique patterns in cell types, with heightened transcriptional activity in myocardial cells. Subpopulation analysis highlighted distinct changes in cardiomyocytes and fibroblasts, emphasizing pathways related to fatty acid metabolism and cardiac contraction. Fibroblast-centered communication analysis identified interactions with endothelial cells, implicating VEGF receptors. Endothelial cell subpopulations exhibited altered gene expressions, emphasizing contraction and growth-related pathways. Candidate regulators, including Tcf21, Arnt, Stat5a, and Stat5b, were identified, suggesting their pivotal roles in DCM development. Immunofluorescence staining validated marker genes of cell subpopulations, confirming PDK4, PPARγ and Tpm1 as markers for metabolic pattern-altered cardiomyocytes, activated fibroblasts and endothelial cells with compromised proliferation. CONCLUSION: Our integrated scRNA-seq and scATAC-seq analysis unveils intricate cell states and molecular alterations in diabetic cardiomyopathy. Identified cell type-specific changes, transcription factors, and marker genes offer valuable insights. The study sheds light on potential therapeutic targets for DCM.

Treating sex and gender differences as a continuous variable can improve precision cancer treatments.

BACKGROUND: The significant sex and gender differences that exist in cancer mechanisms, incidence, and survival, have yet to impact clinical practice. One barrier to translation is that cancer phenotypes cannot be segregated into distinct male versus female categories. Instead, within this convenient but contrived dichotomy, male and female cancer phenotypes are highly overlapping and vary between female- and male- skewed extremes. Thus, sex and gender-specific treatments are unrealistic, and our translational goal should be adaptation of treatment to the variable effects of sex and gender on targetable pathways. METHODS: To overcome this obstacle, we profiled the similarities in 8370 transcriptomes of 26 different adult and 4 different pediatric cancer types. We calculated the posterior probabilities of predicting patient sex and gender based on the observed sexes of similar samples in this map of transcriptome similarity. RESULTS: Transcriptomic index (TI) values were derived from posterior probabilities and allowed us to identify poles with local enrichments for male or female transcriptomes. TI supported deconvolution of transcriptomes into measures of patient-specific activity in sex and gender-biased, targetable pathways. It identified sex and gender-skewed extremes in mechanistic phenotypes like cell cycle signaling and immunity, and precisely positioned each patient's whole transcriptome on an axis of continuously varying sex and gender phenotypes. CONCLUSIONS: Cancer type, patient sex and gender, and TI value provides a novel and patient- specific mechanistic identifier that can be used for realistic sex and gender-adaptations of precision cancer treatment planning.

Some efforts to improve cancer therapy involve the idea of personalizing treatments to who a patient is and how their cancer operates. Personalizing treatment can involve straighforward features like a patient's age, family cancer history, personal disease and surgical histories, as well as more complex features like analysis of their specific cancer's mechanisms of growth and spread throughout the body. One glaring omission in common personalization schemes is the sex and gender of the patient. While patient sex and gender is known to substantially affect cancer rates and response to treatment, we do not yet use this information in treatment planning. There are multiple reasons for this but among them is that we tend to think about sex and gender as an either/or categorization. You are either a male/man or a female/woman. This is not accurate as there are many variables that contribute to who an individual is as a male/man or female/woman. This variability is a challenge to incorporating these features into personalized treatment planning. Here, we have developed a method to address this challenge. It is our great hope that this will enable the use of this critically important element of personalization in cancer treatment planning and improve survival rates for all patients.

Single-cell transcriptomics unveil profiles and interplay of immune subsets in rare autoimmune childhood Sjögren's disease.

Childhood Sjögren's disease represents critically unmet medical needs due to a complete lack of immunological and molecular characterizations. This study presents key immune cell subsets and their interactions in the periphery in childhood Sjögren's disease. Here we show that single-cell RNA sequencing identifies the subsets of IFN gene-enriched monocytes, CD4+ T effector memory, and XCL1+ NK cells as potential key players in childhood Sjögren's disease, and especially in those with recurrent parotitis, which is the chief symptom prompting clinical visits from young children. A unique cluster of monocytes with type I and II IFN-related genes is identified in childhood Sjögren's disease, compared to the age-matched control. In vitro regulatory T cell functional assay demonstrates intact functionality in childhood Sjögren's disease in contrast to reduced suppression in adult Sjögren's disease. Mapping this transcriptomic landscape and interplay of immune cell subsets will expedite the understanding of childhood Sjögren's disease pathogenesis and set the foundation for precision medicine.

Abundant transcriptomic alterations in the human cerebellum of patients with a C9orf72 repeat expansion.

The most prominent genetic cause of both amyotrophic lateral sclerosis (ALS) and frontotemporal lobar degeneration (FTLD) is a repeat expansion in the gene C9orf72. Importantly, the transcriptomic consequences of the C9orf72 repeat expansion remain largely unclear. Here, we used short-read RNA sequencing (RNAseq) to profile the cerebellar transcriptome, detecting alterations in patients with a C9orf72 repeat expansion. We focused on the cerebellum, since key C9orf72-related pathologies are abundant in this neuroanatomical region, yet TDP-43 pathology and neuronal loss are minimal. Consistent with previous work, we showed a reduction in the expression of the C9orf72 gene and an elevation in homeobox genes, when comparing patients with the expansion to both patients without the C9orf72 repeat expansion and control subjects. Interestingly, we identified more than 1000 alternative splicing events, including 4 in genes previously associated with ALS and/or FTLD. We also found an increase of cryptic splicing in C9orf72 patients compared to patients without the expansion and controls. Furthermore, we demonstrated that the expression level of select RNA-binding proteins is associated with cryptic splice junction inclusion. Overall, this study explores the presence of widespread transcriptomic changes in the cerebellum, a region not confounded by severe neurodegeneration, in post-mortem tissue from C9orf72 patients.