美国加州大学圣迭戈分校任兵团队完成成年小鼠大脑染色质可及性的单细胞分析。相关论文于2023年12月13日在线发表在《自然》杂志上。

研究人员报告了一个成年小鼠大脑候选顺式调控DNA元件（cCRE）综合图谱，该图谱是通过分析来自117个解剖切片的230万个单个脑细胞的染色质可及性而生成的。该图谱包括约100万个cCRE及其在1482个不同脑细胞群中的染色质可及性，为小鼠基因组中最新的此类注释增加了44.6万个cCRE。小鼠大脑中的cCRE在人脑中具有中度保守性。小鼠特异性cCRE（特别是从大脑皮层兴奋神经元亚群中发现的cCRE）强烈富含转座元件，这表明转座元件在新调控程序的出现和神经元多样性中的潜在作用。

最后，研究人员推断了260多种亚类小鼠脑细胞的基因调控网络，并开发了深度学习模型，仅通过DNA序列就能预测不同脑细胞类型中基因调控元件的活动。这些研究成果为分析小鼠和人类大脑中细胞类型特异性基因调控程序提供了资源。

据介绍，单细胞技术的最新进展已发现了数千种脑细胞类型；然而，人们对这些细胞类型中基因调控程序的了解还远远不够。

附：英文原文

Title: Single-cell analysis of chromatin accessibility in the adult mouse brain

Author: Zu, Songpeng, Li, Yang Eric, Wang, Kangli, Armand, Ethan J., Mamde, Sainath, Amaral, Maria Luisa, Wang, Yuelai, Chu, Andre, Xie, Yang, Miller, Michael, Xu, Jie, Wang, Zhaoning, Zhang, Kai, Jia, Bojing, Hou, Xiaomeng, Lin, Lin, Yang, Qian, Lee, Seoyeon, Li, Bin, Kuan, Samantha, Liu, Hanqing, Zhou, Jingtian, Pinto-Duarte, Antonio, Lucero, Jacinta, Osteen, Julia, Nunn, Michael, Smith, Kimberly A., Tasic, Bosiljka, Yao, Zizhen, Zeng, Hongkui, Wang, Zihan, Shang, Jingbo, Behrens, M. Margarita, Ecker, Joseph R., Wang, Allen, Preissl, Sebastian, Ren, Bing

Issue&Volume: 2023-12-13

Abstract: Recent advances in single-cell technologies have led to the discovery of thousands of brain cell types; however, our understanding of the gene regulatory programs in these cell types is far from complete1,2,3,4. Here we report a comprehensive atlas of candidate cis-regulatory DNA elements (cCREs) in the adult mouse brain, generated by analysing chromatin accessibility in 2.3million individual brain cells from 117 anatomical dissections. The atlas includes approximately 1million cCREs and their chromatin accessibility across 1,482 distinct brain cell populations, adding over 446,000 cCREs to the most recent such annotation in the mouse genome. The mouse brain cCREs are moderately conserved in the human brain. The mouse-specific cCREs—specifically, those identified from a subset of cortical excitatory neurons—are strongly enriched for transposable elements, suggesting a potential role for transposable elements in the emergence of new regulatory programs and neuronal diversity. Finally, we infer the gene regulatory networks in over 260 subclasses of mouse brain cells and develop deep-learning models to predict the activities of gene regulatory elements in different brain cell types from the DNA sequence alone. Our results provide a resource for the analysis of cell-type-specific gene regulation programs in both mouse and human brains.

DOI: 10.1038/s41586-023-06824-9

Source: https://www.nature.com/articles/s41586-023-06824-9