Evidence map›Paper›PMID 40042873›Full record

ArticleInvestigative ophthalmology & visual science2025

Single-Cell Multiomics Analysis of Early Wound Response Programs in the Mouse Corneal Epithelium.

Zhao-Jing Lu, Jin-Guo Ye, Jing-Ni Li, Jiang-Bo Liang, Ming Zhou, Qiu-Ling Hu, Qi-Kai Zhang, Yu-Heng Lin, Ying-Feng Zheng

Abstract read
In one paragraph

Article in Investigative ophthalmology & visual science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Zhao-Jing LuState Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-Sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, China.
Jin-Guo YeState Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-Sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, China.
Jing-Ni LiState Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-Sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, China.
Jiang-Bo LiangState Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-Sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, China.
Ming ZhouState Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-Sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, China.
Qiu-Ling HuState Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-Sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, China.
Qi-Kai ZhangState Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-Sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, China.
Yu-Heng LinState Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-Sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, China.
Ying-Feng ZhengState Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-Sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: Wound healing is crucial for restoring homeostasis in living organisms. Although wound response mechanisms have been studied extensively, the gene regulatory programs involved remain to be elucidated. Here, we used single-cell RNA sequencing (RNA-seq) and ATAC sequencing (ATAC-seq) analysis to profile the regulatory landscape of mouse corneal epithelium in early wound response. Methods: We used our previously published single-cell data sets of homeostatic adult mouse corneal epithelium as the unwounded group. The wounded group data sets were obtained by sequencing the epithelium after an annular epithelial wound. Following the integration of the relevant data sets, the Seurat and ArchR packages were employed for single-cell RNA-seq and single-cell ATAC-seq data processing and downstream analysis, respectively. The Monocle 2 was used for pseudo-time analysis, CellChat for intercellular communication analysis, and pySCENIC for analyzing transcription factors. The expression of key genes was validated via immunofluorescence staining and quantitative real-time PCR. Results: Our data show that the number of cell type-specific genes decreases and the number of common transcriptional responses increases in early wound response. Concurrently, we find that the chromatin accessibility landscape undergoes significant changes across all epithelial cell types and that the wound-induced open regions are similarly distributed across the genome. Motif enrichment analysis shows that Fosl1/AP-1 binding site is highly enriched among the opened regions. However, by assessing the correlation between changes in chromatin accessibility and gene expression, we observe that only a small subset of wound-induced genes shows a high correlation with the accessibility of nearby chromatin. Conclusions: Our study provides a detailed single-cell landscape for transcriptomic and epigenetic changes in mouse corneal epithelium during early wound response, which improved our understanding of the mechanisms of wound healing.

Indexed as

Corneal InjuriesEpithelium, CornealGene Expression RegulationSingle-Cell AnalysisWound HealingAnimalsDisease Models, AnimalGene Expression ProfilingMiceMice, Inbred C57BLMultiomicsReal-Time Polymerase Chain ReactionSequence Analysis, RNA

Identifiers

PMID40042873
PMCPMC11892537

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.