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Single-cell multimodal sequencing parallelly captures multiple modalities of the same cell, providing unparalleled insights into cell heterogeneity and cell dynamics. For example, joint profiling of chromatin accessibility and transcriptome from the same single cell (scATAC + RNA) identified new cell subsets within the well-defined clusters. However, lack of single-cell multimodal omics (scMMO) database has led to data fragmentation, seriously hindering access, utilization and mining of scMMO data. Here, we constructed a scMMO atlas by collecting and integrating various scMMO data, then constructed scMMO database and portal called scMMO-atlas (https://www.biosino.org/scMMO-atlas/). scMMO-atlas includes scATAC + RNA (ISSAAS-seq, SNARE-seq, paired-seq, sci-CAR, scCARE-seq, 10X Multiome and so on), scRNA + protein, scATAC + protein and scTri-modal omics data, with 3 168 824 cells from 27 cell tissues/organs. scMMO-atlas offered an interactive portal for visualization and featured analysis for each modality and the integrated data. Integrated analysis of scATAC + RNA data of mouse cerebral cortex in scMMO-atlas identified more cell subsets compared with unimodal omics data. Among these new cell subsets, there is an early astrocyte subset highly expressed Grm3, called Astro-Grm3. Furthermore, we identified Ex-L6-Tle4-Nrf1, a progenitor of Ex-L6-Tle4, indicating the statistical power provided by the big data in scMMO-atlas. In summary, scMMO-atlas offers cell atlas, database and portal to facilitate data utilization and biological insight.
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http://dx.doi.org/10.1093/nar/gkae821 | DOI Listing |
Clin Epigenetics
September 2025
Department of Psychiatry and Psychotherapy, Philipps University Marburg, Marburg, Germany.
Background: Work-related stress is a well-established contributor to mental health decline, particularly in the context of burnout, a state of prolonged exhaustion. Epigenetic clocks, which estimate biological age based on DNA methylation (DNAm) patterns, have been proposed as potential biomarkers of chronic stress and its impact on biological aging and health. However, their role in mediating the relationship between work-related stress, physiological stress markers, and burnout remains unclear.
View Article and Find Full Text PDFAlzheimers Res Ther
September 2025
Department of Neurology, Saarland University, Kirrberger Straße, 66421, Homburg/Saar, Germany.
Background: Alzheimer's disease (AD) patients and animal models exhibit an altered gut microbiome that is associated with pathological changes in the brain. Intestinal miRNA enters bacteria and regulates bacterial metabolism and proliferation. This study aimed to investigate whether the manipulation of miRNA could alter the gut microbiome and AD pathologies.
View Article and Find Full Text PDFActa Neuropathol Commun
September 2025
Department of Stem Cell and Regenerative Biotechnology, School of Advanced Biotechnology, Molecular & Cellular Reprogramming Center, Institute of Advanced Regenerative Science, and Institute of Health, Aging & Society, Konkuk University, Seoul, 05029, Republic of Korea.
Diagn Pathol
September 2025
Department of Gastrointestinal Medical Oncology, Fudan University Shanghai Cancer Center, Shanghai, 200032, China.
Background: Gastric cancer is one of the most common cancers worldwide, with its prognosis influenced by factors such as tumor clinical stage, histological type, and the patient's overall health. Recent studies highlight the critical role of lymphatic endothelial cells (LECs) in the tumor microenvironment. Perturbations in LEC function in gastric cancer, marked by aberrant activation or damage, disrupt lymphatic fluid dynamics and impede immune cell infiltration, thereby modulating tumor progression and patient prognosis.
View Article and Find Full Text PDFGenome Biol
September 2025
Department of Evolutionary Genetics, Max-Planck Institute for Evolutionary Biology, Plön, Germany.
Background: Most RNA-seq datasets harbor genes with extreme expression levels in some samples. Such extreme outliers are usually treated as technical errors and are removed from the data before further statistical analysis. Here we focus on the patterns of such outlier gene expression to investigate whether they provide insights into the underlying biology.
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