Previous studies on enhancers and their target genes were largely based on bulk samples that represent 'average' regulatory activities from a large population of millions of cells, masking the heterogeneity and important effects from the sub-populations. In recent years, single-cell sequencing technology has enabled the profiling of open chromatin accessibility at the single-cell level (scATAC-seq), which can be used to annotate the enhancers and promoters in specific cell types. A comprehensive resource is highly desirable for exploring how the enhancers regulate the target genes at the single-cell level. Hence, we designed a single-cell database scEnhancer (http://enhanceratlas.net/scenhancer/), covering 14 527 776 enhancers and 63 658 600 enhancer-gene interactions from 1 196 906 single cells across 775 tissue/cell types in three species. An unsupervised learning method was employed to sort and combine tens or hundreds of single cells in each tissue/cell type to obtain the consensus enhancers. In addition, we utilized a cis-regulatory network algorithm to identify the enhancer-gene connections. Finally, we provided a user-friendly platform with seven useful modules to search, visualize, and browse the enhancers/genes. This database will facilitate the research community towards a functional analysis of enhancers at the single-cell level.
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http://dx.doi.org/10.1093/nar/gkab1032 | DOI Listing |
Mol Hum Reprod
January 2025
Follicle Biology Laboratory, Research Group Genetics, Reproduction and Development, Vrije Universiteit Brussel (VUB), Brussels, Belgium.
Biphasic in vitro oocyte maturation (IVM) can be offered as a patient-friendly alternative to conventional ovarian stimulation in in vitro fertilization (IVF) patients predicted to be hyper-responsive to ovarian stimulation. However, cumulative live birth rates after IVM per cycle are lower than after conventional ovarian stimulation for IVF. In different animal species, supplementation of IVM media with oocyte-secreted factors (OSFs) improves oocyte developmental competence through the expression of pro-ovulatory genes in cumulus cells.
View Article and Find Full Text PDFDiscov Oncol
January 2025
Second Department of Oncology, The Second Hospital of Hebei Medical University, Shijiazhuang, 050000, Hebei, China.
Introduction: We conducted a panoramic analysis of GBN5 expression and prognosis in 33 cancers, aiming to deepen the systematic understanding of GBN5 in cancer.
Materials And Methods: We employed a multi-omics approach, including transcriptomic, genomic, proteomic, single-cell cytomic, spatial transcriptomic, and genomic data, to explore the prognostic value and potential oncogenic mechanisms of GBN5 across pan-cancers from multiple perspectives.
Results: We found that GBN5 was differentially expressed in multiple tumors and showed early diagnostic value.
Nutrients
January 2025
Department of Physiology, University of Louisville School of Medicine, Louisville, KY 40202, USA.
Background/objectives: Chronic gut dysbiosis due to a high-fat diet (HFD) instigates cardiac remodeling and heart failure with preserved ejection fraction (HFpEF), in particular, kidney/volume-dependent HFpEF. Studies report that although mitochondrial ATP citrate lyase (ACLY) supports cardiac function, it decreases more in human HFpEF than HFrEF. Interestingly, ACLY synthesizes lipids and creates hyperlipidemia.
View Article and Find Full Text PDFInt J Mol Sci
January 2025
School of Chemistry and Life Science, Suzhou University of Science and Technology, Suzhou 215011, China.
Colorectal cancer (CRC) is one of the most common malignant tumors, characterized by a high incidence and mortality rate. Macrophages, as a key immune cell type within the tumor microenvironment (TME), play a key role in tumor immune evasion and the progression of CRC. Therefore, identifying macrophage biomarkers is of great significance for predicting the prognosis of CRC patients.
View Article and Find Full Text PDFInt J Mol Sci
January 2025
School of Environmental Science and Engineering, Hainan University, Haikou 570228, China.
Hepatocellular carcinoma (HCC), a leading liver tumor globally, is influenced by diverse risk factors. Cellular senescence, marked by permanent cell cycle arrest, plays a crucial role in cancer biology, but its markers and roles in the HCC immune microenvironment remain unclear. Three machine learning methods, namely k nearest neighbor (KNN), support vector machine (SVM), and random forest (RF), are utilized to identify eight key HCC cell senescence markers (HCC-CSMs).
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