小柯机器人

美国冷泉港实验室Anthony M. Zador研究组近日取得一项新成果。他们提出BRICseq桥接全脑区域间连接性到单只动物的神经活动和基因表达。该研究于2020年7月2日发表于《细胞》。

他们描述了BRICseq（全脑个体动物连接体测序），在几周内，它利用DNA条形码测序，低成本映射了单个个体的连接性。将BRICseq应用到小鼠新皮层，他们发现区域间连通性提供了一个转录组与活性相关的简单桥梁：少数基因的空间表达模式预测区域间连通性，以及连通性预测活性相关性。

他们还利用BRICseq绘制了缺少胼胝体突变的BTBR小鼠大脑图谱，并概括了其已知的结节病。BRICseq允许各个实验室比较年龄、性别、环境、遗传学和物种如何影响神经元连接，并将其与功能活动和基因表达整合在一起。

据了解，对神经网络的全面分析需要对大脑的连通性、活性和基因表达进行全脑测量。尽管高通量方法可用于绘制全脑活动和转录组图谱，但用于映射区域到区域连通性的可比较方法仍然缓慢且昂贵，因为它们需要在数百个大脑中求平均值。

附：英文原文

Title: BRICseq Bridges Brain-wide Interregional Connectivity to Neural Activity and Gene Expression in Single Animals

Author: Longwen Huang, Justus M. Kebschull, Daniel Fürth, Simon Musall, Matthew T. Kaufman, Anne K. Churchland, Anthony M. Zador

Issue&Volume: 2020-07-02

Abstract: Comprehensive analysis of neuronal networks requires brain-wide measurement of connectivity, activity, and gene expression. Although high-throughput methods are available for mapping brain-wide activity and transcriptomes, comparable methods for mapping region-to-region connectivity remain slow and expensive because they require averaging across hundreds of brains. Here we describe BRICseq (brain-wide individual animal connectome sequencing), which leverages DNA barcoding and sequencing to map connectivity from single individuals in a few weeks and at low cost. Applying BRICseq to the mouse neocortex, we find that region-to-region connectivity provides a simple bridge relating transcriptome to activity: the spatial expression patterns of a few genes predict region-to-region connectivity, and connectivity predicts activity correlations. We also exploited BRICseq to map the mutant BTBR mouse brain, which lacks a corpus callosum, and recapitulated its known connectopathies. BRICseq allows individual laboratories to compare how age, sex, environment, genetics, and species affect neuronal wiring and to integrate these with functional activity and gene expression.

DOI: 10.1016/j.cell.2020.05.029

Source: https://www.cell.com/cell/fulltext/S0092-8674(20)30624-3