Cell Landscapes for Zebrafish, Drosophila, and Earthworm

Cell landscapes constructed in Deep learning of cross-species single-cell landscapes identifies conserved regulatory programs underlying cell types.

In this study, we aimed to build cell landscapes for zebrafish, Drosophila, and earthworm using a whole-body single-cell RNA-seq (scRNA-seq) strategy that eliminates tissue specific batch effects.

Our analysis included dissociated 24 hours post fertilization (hpf), 72hpf, and 90-day zebrafish whole bodies (635,228 cells), 11- and 16-day Drosophila whole bodies (276,706 cells), and 6- and 8-mouth earthworm whole bodies (95,020 cells).

Jiaqi Li†, Jingjing Wang†*, Peijing Zhang†, Renying Wang†, Yuqing Mei, Zhongyi Sun, Lijiang Fei, Mengmeng Jiang, Lifeng Ma, Weigao E, Haide Chen, Xinru Wang, Yuting Fu, Hanyu Wu, Daiyuan Liu, Xueyi Wang, Jingyu Li, Qile Guo, Yuan Liao, Chengxuan Yu, Danmei Jia, Jian Wu, Shibo He, Huanju Liu, Jun Ma, Kai Lei, Jiming Chen, Xiaoping Han* and Guoji Guo*. Deep learning of cross-species single-cell landscapes identifies conserved regulatory programs underlying cell types. Nature Genetics, 2022. DOI: 10.1038/s41588-022-01197-7.