Ciliopathies are life-threatening human diseases caused by defective cilia. They can often be traced back to mutations of genes encoding transition zone (TZ) proteins demonstrating that the understanding of TZ organisation is of paramount importance. The TZ consists of multimeric protein modules that are subject to a stringent assembly hierarchy. Previous reports place Rpgrip1l at the top of the TZ assembly hierarchy in By performing quantitative immunofluorescence studies in RPGRIP1L mouse embryos and human embryonic cells, we recognise a different situation in vertebrates in which Rpgrip1l deficiency affects TZ assembly in a cell type-specific manner. In cell types in which the loss of Rpgrip1l alone does not affect all modules, additional truncation or removal of vertebrate-specific Rpgrip1 results in an impairment of all modules. Consequently, Rpgrip1l and Rpgrip1 synergistically ensure the TZ composition in several vertebrate cell types, revealing a higher complexity of TZ assembly in vertebrates than in invertebrates.
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http://dx.doi.org/10.15252/embj.201797791 | DOI Listing |
CNS Neurosci Ther
January 2025
Beijing Key Laboratory of Hypoxia Translational Medicine, Xuanwu Hospital, Center of Stroke, Beijing Institute of Brain Disorder, Capital Medical University, Beijing, China.
Objective: Ischemia-reperfusion of the abdominal aorta often results in damage to distant organs, such as the heart and brain. This cellular heterogeneity within affected tissues complicates the roles of specific cell subsets in abdominal aorta occlusion model (AAO) injury. However, cell type-specific molecular pathology in the hippocampus after ischemia is poorly understood.
View Article and Find Full Text PDFMol Neurodegener
January 2025
The Jackson Laboratory, Bar Harbor, ME, 04609, USA.
Background: Age is the principal risk factor for neurodegeneration in both the retina and brain. The retina and brain share many biological properties; thus, insights into retinal aging and degeneration may shed light onto similar processes in the brain. Genetic makeup strongly influences susceptibility to age-related retinal disease.
View Article and Find Full Text PDFGenome Med
January 2025
Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, 181 Longwood Avenue, Boston, MA, 02115, USA.
Background: Large-scale pharmacogenomic resources, such as the Connectivity Map (CMap), have greatly assisted computational drug discovery. However, despite their widespread use, CMap-based methods have thus far been agnostic to the biological activity of drugs as well as to the genomic effects of drugs in multiple disease contexts. Here, we present a network-based statistical approach, Pathopticon, that uses CMap to build cell type-specific gene-drug perturbation networks and integrates these networks with cheminformatic data and diverse disease phenotypes to prioritize drugs in a cell type-dependent manner.
View Article and Find Full Text PDFJ Headache Pain
January 2025
Clinical Systems Biology Laboratories, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
Background: Migraine is a complex neurological disorder characterized by recurrent episodes of severe headaches. Although genetic factors have been implicated, the precise molecular mechanisms, particularly gene expression patterns in migraine-associated brain regions, remain unclear. This study applies machine learning techniques to explore region-specific gene expression profiles and identify critical gene programs and transcription factors linked to migraine pathogenesis.
View Article and Find Full Text PDFBackground: Analyzing disease-linked genetic variants via expression quantitative trait loci (eQTLs) is important for identifying potential disease-causing genes. Previous research prioritized genes by integrating Genome-Wide Association Study (GWAS) results with tissue- level eQTLs. Recent studies have explored brain cell type-specific eQTLs, but they lack a systematic analysis across various Alzheimer's disease (AD) GWAS datasets, nor did they compare effects between tissue and cell type levels or across different cell type-specific eQTL datasets.
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