A single-cell multi-omics atlas of mouse retina

The mouse retina, a well-established model for studying neural development and-sensory function, exhibits high-cellular heterogeneity that necessitates high-resolution-multi-omics analysis. scCAT-seq serves as a key tool for this purpose, as it enables thesimultaneous detection of two molecular signals within individual cells. However,experimental -conditions-including cell freshness, nuclear isolation methods, and-freezing treatment-have-severely compromised the quality of single-cell-scCAT-seq:data from the mouse retina. Additionally, the scarcity of datasets that systematically-compare these conditions has created gaps in data standardization and utility. Herein,we generated a comprehensive- single-cell multi-omics dataset of the mouse retina,comprising HT-scCAT-seq -libraries across three experimental- conditions: fresh-cells(n=6), fresh cell-nuclei (n=8), and frozen-cell nuclei (n=8). Following rigorous qualitycontrol, we obtained 78,771 high-quality cells. Using this dataset, we identified 7 major-retinal-cell types and-constructed a dual-omics atlas. This resource not only facilitates-in-depth understanding ofhow experimental conditions impact scCAT-seq data but also-advances future-research-on retinal-cell function-and regulation.e