Shoenhard Hannah, Granato Michael
Department of Cell and Developmental Biology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.
PLoS One. 2023 Feb 14;18(2):e0281609. doi: 10.1371/journal.pone.0281609. eCollection 2023.
Behavioral screens in model organisms have greatly facilitated the identification of genes and genetic pathways that regulate defined behaviors. Identifying the neural circuitry via which specific genes function to modify behavior remains a significant challenge in the field. Tissue- and cell type-specific knockout, knockdown, and rescue experiments serve this purpose, yet in zebrafish screening through dozens of candidate cell-type-specific and brain-region specific driver lines for their ability to rescue a mutant phenotype remains a bottleneck. Here we report on an alternative strategy that takes advantage of the variegation often present in Gal4-driven UAS lines to express a rescue construct in a neuronal tissue-specific and variegated manner. We developed and validated a computational pipeline that identifies specific brain regions where expression levels of the variegated rescue construct correlate with rescue of a mutant phenotype, indicating that gene expression levels in these regions may causally influence behavior. We termed this unbiased correlative approach Multivariate Analysis of Variegated Expression in Neurons (MAVEN). The MAVEN strategy advances the user's capacity to quickly identify candidate brain regions where gene function may be relevant to a behavioral phenotype. This allows the user to skip or greatly reduce screening for rescue and proceed to experimental validation of candidate brain regions via genetically targeted approaches. MAVEN thus facilitates identification of brain regions in which specific genes function to regulate larval zebrafish behavior.
模式生物中的行为筛选极大地促进了对调控特定行为的基因和遗传通路的识别。确定特定基因通过何种神经回路发挥作用来改变行为仍是该领域的一项重大挑战。组织和细胞类型特异性敲除、敲低及拯救实验可实现这一目的,但在斑马鱼中,通过数十种候选细胞类型特异性和脑区特异性驱动系筛选其拯救突变表型的能力仍是一个瓶颈。在此,我们报告一种替代策略,该策略利用Gal4驱动的UAS系中常出现的斑驳现象,以神经元组织特异性和斑驳的方式表达拯救构建体。我们开发并验证了一种计算流程,该流程可识别斑驳拯救构建体的表达水平与突变表型拯救相关的特定脑区,这表明这些区域的基因表达水平可能因果性地影响行为。我们将这种无偏相关方法称为神经元斑驳表达多变量分析(MAVEN)。MAVEN策略提高了用户快速识别基因功能可能与行为表型相关的候选脑区的能力。这允许用户跳过或大幅减少拯救筛选,并通过基因靶向方法对候选脑区进行实验验证。因此,MAVEN有助于识别特定基因在其中发挥作用以调控斑马鱼幼体行为的脑区。