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Multi-omic profiling reveals epithelial remodeling in necrotizing enterocolitis

GSE278973 Mus musculus Expression profiling by high throughput sequencing; Genome binding/occupancy profiling by high throughput sequencing 4 samples Submitted 2026/04/15 Platform GPL24247
Summary
Necrotizing enterocolitis (NEC) is a devastating gastrointestinal disease predominantly affecting premature infants, characterized by severe intestinal inflammation and tissue necrosis. Despite advances in neonatal care, NEC remains a significant clinical challenge with high mortality and morbidity rates. Understanding the molecular and cellular mechanisms underlying NEC pathogenesis is crucial for developing targeted therapies and improving clinical outcomes. In this study, we utilized a mouse model of NEC induced by hypoxia, formula feeding, and lipopolysaccharide administration to investigate the molecular changes at single-cell resolution. We performed bulk RNA sequencing, single-nucleus RNA sequencing (snRNA-seq), single-nucleus assay for transposase-accessible chromatin sequencing (snATAC-seq) and multiplexed error-robust fluorescence in situ hybridization (MERFISH) spatial transcriptomics on intestinal tissues collected from control and NEC groups at postnatal day 9. Data were analyzed to identify cell populations, epigenetic profiles, and regulatory pathways associated with NEC progression.
Published in
Molecular and Chromatin Accessibility Programs Underlying Epithelial Injury and Impaired Regeneration in Neonatal Necrotizing Enterocolitis
Xiong Y, Zito A, Liang H et al. · Cellular and molecular gastroenterology and hepatology 2026 · PMID 41571092 · doi:10.1016/j.jcmgh.2026.101730
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Direct links to NCBI, no account and no request form: the whole study as GSE278973_RAW.tar, processed values as the series matrix, the supplementary file directory, and per-sample supplementary files for any of the 4 samples. Raw sequencing reads are also available from ENA.

Also filed as BioProject PRJNA1169867 and SRA study SRP537163. Searching any of these in the dataset finder brings you back here.

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