There has been rapid growth in the use of transcriptomic analyses to study the interplay between gene expression and behavior. Experience can modify gene expression in the brain, leading to changes in internal state and behavioral displays, while gene expression variation between species is thought to specify many innate behavior differences. However, providing a causal association between a gene and a given behavior remains challenging as it is difficult to determine when and where a gene contributes to the function of a behaviorally-relevant neuronal population. Moreover, given that there are fewer genetic tools available for non-traditional model organisms, transcriptomic approaches have been largely limited to profiling of bulk tissue, which can obscure the contributions of subcortical brain regions implicated in multiple behaviors. Here, we discuss how emerging single cell technologies combined with methods offering additional spatial and connectivity information can give us insight about the genetic profile of specific cells involved in the neural circuit of target social behaviors. We also emphasize how these techniques are broadly adaptable to non-traditional model organisms. We propose that, ultimately, a combination of these approaches applied throughout development will be key to discerning how genes shape the formation of social behavior circuits.

使用转录组学分析来研究基因表达和行为之间的相互作用已经迅速增长。经验可以改变大脑中的基因表达，导致内部状态和行为表现的变化，而物种之间的基因表达差异被认为是许多先天行为差异的原因。然而，提供基因和给定行为之间的因果关系仍然具有挑战性，因为很难确定基因何时何地对行为相关的神经元群的功能做出贡献。此外，鉴于可用于非传统模式生物的遗传工具较少，转录组学方法在很大程度上仅限于大块组织的分析，这可能会掩盖与多种行为有关的皮层下大脑区域的贡献。这里，我们讨论了新兴的单细胞技术如何与提供额外空间和连接信息的方法相结合，可以让我们深入了解参与目标社会行为神经回路的特定细胞的遗传特征。我们还强调这些技术如何广泛适用于非传统模式生物。我们建议，最终，在整个开发过程中应用这些方法的组合将是辨别基因如何塑造社会行为回路形成的关键。我们还强调这些技术如何广泛适用于非传统模式生物。我们建议，最终，在整个开发过程中应用这些方法的组合将是辨别基因如何塑造社会行为回路形成的关键。我们还强调这些技术如何广泛适用于非传统模式生物。我们建议，最终，在整个开发过程中应用这些方法的组合将是辨别基因如何塑造社会行为回路形成的关键。