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跨物种单细胞图谱揭示遗传性视网膜疾病的致病基因特征

Cross-species single-cell landscapes identify the pathogenic gene characteristics of inherited retinal diseases.

作者信息

Hu Hualei, Liu Fei, Gao Pan, Huang Yuwen, Jia Danna, Reilly Jamas, Chen Xiang, Han Yunqiao, Sun Kui, Luo Jiong, Li Pei, Zhang Zuxiao, Wang Qing, Lu Qunwei, Luo Daji, Shu Xinhua, Tang Zhaohui, Liu Mugen, Ren Xiang

机构信息

Key Laboratory of Molecular Biophysics of Ministry of Education, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, China.

State Key Laboratory of Freshwater Ecology and Biotechnology, Institute of Hydrobiology, The Innovative Academy of Seed Design, Hubei Hongshan Laboratory, Chinese Academy of Sciences, Wuhan, China.

出版信息

Front Genet. 2024 Jul 11;15:1409016. doi: 10.3389/fgene.2024.1409016. eCollection 2024.

Abstract

INTRODUCTION

Inherited retinal diseases (IRDs) affect ∼4.5 million people worldwide. Elusive pathogenic variants in over 280 genes are associated with one or more clinical forms of IRDs. It is necessary to understand the complex interaction among retinal cell types and pathogenic genes by constructing a regulatory network. In this study, we attempt to establish a panoramic expression view of the cooperative work in retinal cells to understand the clinical manifestations and pathogenic bases underlying IRDs.

METHODS

Single-cell RNA sequencing (scRNA-seq) data on the retinas from 35 retina samples of 3 species (human, mouse, and zebrafish) including 259,087 cells were adopted to perform a comparative analysis across species. Bioinformatic tools were used to conduct weighted gene co-expression network analysis (WGCNA), single-cell regulatory network analysis, cell-cell communication analysis, and trajectory inference analysis.

RESULTS

The cross-species comparison revealed shared or species-specific gene expression patterns at single-cell resolution, such as the stathmin family genes, which were highly expressed specifically in zebrafish Müller glias (MGs). Thirteen gene modules were identified, of which nine were associated with retinal cell types, and Gene Ontology (GO) enrichment of module genes was consistent with cell-specific highly expressed genes. Many IRD genes were identified as hub genes and cell-specific regulons. Most IRDs, especially the retinitis pigmentosa (RP) genes, were enriched in rod-specific regulons. Integrated expression and transcription regulatory network genes, such as congenital stationary night blindness (CSNB) genes , , and , showed cell-specific expression and transcription characteristics in either rods or bipolar cells (BCs). IRD genes showed evolutionary conservation (, , and ) and divergence (, , and ) along the trajectory of photoreceptors (PRs) among species. In particular, the Leber congenital amaurosis (LCA) gene showed high expression at the beginning of the trajectory of both PRs and BCs.

CONCLUSION

We identified molecular pathways and cell types closely connected with IRDs, bridging the gap between gene expression, genetics, and pathogenesis. The IRD genes enriched in cell-specific modules and regulons suggest that these diseases share common etiological bases. Overall, mining of interspecies transcriptome data reveals conserved transcriptomic features of retinas across species and promising applications in both normal retina anatomy and retina pathology.

摘要

引言

遗传性视网膜疾病(IRD)在全球约影响450万人。超过280个基因中难以捉摸的致病变异与一种或多种IRD临床形式相关。有必要通过构建调控网络来了解视网膜细胞类型与致病基因之间的复杂相互作用。在本研究中,我们试图建立视网膜细胞协同工作的全景表达视图,以了解IRD的临床表现和致病基础。

方法

采用来自3个物种(人类、小鼠和斑马鱼)的35个视网膜样本(包括259,087个细胞)的视网膜单细胞RNA测序(scRNA-seq)数据进行跨物种比较分析。使用生物信息学工具进行加权基因共表达网络分析(WGCNA)、单细胞调控网络分析、细胞间通讯分析和轨迹推断分析。

结果

跨物种比较揭示了单细胞分辨率下共享或物种特异性的基因表达模式,例如stathmin家族基因,其在斑马鱼穆勒胶质细胞(MG)中特异性高表达。鉴定出13个基因模块,其中9个与视网膜细胞类型相关,模块基因的基因本体(GO)富集与细胞特异性高表达基因一致。许多IRD基因被鉴定为枢纽基因和细胞特异性调控子。大多数IRD,尤其是视网膜色素变性(RP)基因,在视杆细胞特异性调控子中富集。整合表达和转录调控网络基因,如先天性静止性夜盲(CSNB)基因 、 和 ,在视杆细胞或双极细胞(BC)中表现出细胞特异性表达和转录特征。IRD基因在物种间光感受器(PR)轨迹上表现出进化保守性( 、 和 )和分歧性( 、 和 )。特别是,莱伯先天性黑蒙(LCA)基因 在PR和BC轨迹开始时均高表达。

结论

我们确定了与IRD密切相关的分子途径和细胞类型,弥合了基因表达、遗传学和发病机制之间的差距。富集在细胞特异性模块和调控子中的IRD基因表明这些疾病具有共同的病因基础。总体而言,跨物种转录组数据挖掘揭示了跨物种视网膜保守的转录组特征以及在正常视网膜解剖学和视网膜病理学中的潜在应用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7cd0/11269129/37cd02cccca6/fgene-15-1409016-g001.jpg

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