Simultaneous profiling of RNA isoforms and chromatin accessibility of single cells of human retinal organoids

被引:0
|
作者
Zhang, Shuyao [1 ]
Xiao, Yuhua [1 ]
Mo, Xinzhi [1 ]
Chen, Xu [1 ]
Zhong, Jiawei [1 ]
Chen, Zheyao [1 ]
Liu, Xu [1 ]
Qiu, Yuanhui [1 ]
Dai, Wangxuan [1 ]
Chen, Jia [1 ]
Jin, Xishan [1 ]
Fan, Guoping [2 ,3 ]
Hu, Youjin [1 ,4 ]
机构
[1] Sun Yat Sen Univ, Zhongshan Ophthalm Ctr, State Key Lab Ophthalmol, Guangzhou, Peoples R China
[2] UCLA, David Geffen Sch Med, Dept Human Genet, Los Angeles, CA USA
[3] Scintillon Res Inst, 6868 Nancy Ridge Dr, San Diego, CA 92121 USA
[4] Guangdong Prov Key Lab Ophthalmol & Visual Sci, Guangzhou, Peoples R China
基金
中国国家自然科学基金; 国家重点研发计划;
关键词
REVEALS; SEQ;
D O I
10.1038/s41467-024-52335-0
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Single-cell multi-omics sequencing is a powerful approach to analyze complex mechanisms underlying neuronal development and regeneration. However, current methods lack the ability to simultaneously profile RNA alternative splicing and chromatin accessibility at the single-cell level. We develop a technique, single-cell RNA isoform and chromatin accessibility sequencing (scRICA-seq), which demonstrates higher sensitivity and cost-effectiveness compared to existing methods. scRICA-seq can profile both isoforms and chromatin accessibility for up to 10,000 single cells in a single run. Applying this method to human retinal organoids, we construct a multi-omic cell atlas and reveal associations between chromatin accessibility, isoform expression of fate-determining factors, and alternative splicing events in their binding sites. This study provides insights into integrating epigenetics, transcription, and RNA splicing to elucidate the mechanisms underlying retinal neuronal development and fate determination. Here, the authors present scRICA-seq, which is capable of profiling isoforms and chromatin accessibility for up to 10,000 single cells in a single run. By applying this method to human retinal organoids, they construct a multi-omic cell atlas.
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页数:13
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