单细胞分辨率下小鼠脑桥背侧的空间分辨转录图谱。

A spatially-resolved transcriptional atlas of the murine dorsal pons at single-cell resolution.

作者信息

Nardone Stefano, De Luca Roberto, Zito Antonino, Klymko Nataliya, Nicoloutsopoulos Dimitris, Amsalem Oren, Brannigan Cory, Resch Jon M, Jacobs Christopher L, Pant Deepti, Veregge Molly, Srinivasan Harini, Grippo Ryan M, Yang Zongfang, Zeidel Mark L, Andermann Mark L, Harris Kenneth D, Tsai Linus T, Arrigoni Elda, Verstegen Anne M J, Saper Clifford B, Lowell Bradford B

机构信息

Department of Medicine, Division of Endocrinology, Diabetes and Metabolism, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA.

Broad Institute of MIT and Harvard, Cambridge, MA, USA.

出版信息

bioRxiv. 2023 Nov 17:2023.09.18.558047. doi: 10.1101/2023.09.18.558047.

DOI:10.1101/2023.09.18.558047

PMID:38014113

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10680649/

Abstract

The "dorsal pons", or "dorsal pontine tegmentum" (dPnTg), is part of the brainstem. It is a complex, densely packed region whose nuclei are involved in regulating many vital functions. Notable among them are the parabrachial nucleus, the Kölliker Fuse, the Barrington nucleus, the locus coeruleus, and the dorsal, laterodorsal, and ventral tegmental nuclei. In this study, we applied single-nucleus RNA-seq (snRNA-seq) to resolve neuronal subtypes based on their unique transcriptional profiles and then used multiplexed error robust fluorescence in situ hybridization (MERFISH) to map them spatially. We sampled ~1 million cells across the dPnTg and defined the spatial distribution of over 120 neuronal subtypes. Our analysis identified an unpredicted high transcriptional diversity in this region and pinpointed many neuronal subtypes' unique marker genes. We also demonstrated that many neuronal subtypes are transcriptionally similar between humans and mice, enhancing this study's translational value. Finally, we developed a freely accessible, GPU and CPU-powered dashboard (http://harvard.heavy.ai:6273/) that combines interactive visual analytics and hardware-accelerated SQL into a data science framework to allow the scientific community to query and gain insights into the data.

摘要

“脑桥背侧”，即“脑桥背侧被盖”（dPnTg），是脑干的一部分。它是一个复杂且细胞密集的区域，其核团参与调节许多重要功能。其中值得注意的有臂旁核、 Kölliker Fuse核、巴林顿核、蓝斑以及背侧、外侧背侧和腹侧被盖核。在本研究中，我们应用单核RNA测序（snRNA-seq），根据神经元独特的转录谱来解析神经元亚型，然后使用多重误差稳健荧光原位杂交（MERFISH）对它们进行空间定位。我们在整个脑桥背侧被盖区域采集了约100万个细胞，并确定了120多种神经元亚型的空间分布。我们的分析确定了该区域存在意想不到的高转录多样性，并找出了许多神经元亚型的独特标记基因。我们还证明，许多神经元亚型在人类和小鼠之间转录相似，提高了本研究的转化价值。最后，我们开发了一个可免费访问的、由GPU和CPU驱动的仪表盘（http://harvard.heavy.ai:6273/），它将交互式视觉分析和硬件加速SQL结合到一个数据科学框架中，使科学界能够查询数据并从中获得见解。