可进化性
生物
进化生物学
生物神经网络
电池类型
基因
计算生物学
基因调控网络
人类进化遗传学
编码
神经元回路
转录组
神经科学
性别选择
遗传学
进化动力学
功能分歧
猕猴
自然选择
系统生物学
神经网络
作者
Justin T. Walsh,Ian P. Junker,Yu-Chieh David Chen,Yen-Chung Chen,Helena Gifford,Dawn S. Chen,Yun Ding
标识
DOI:10.1073/pnas.2516083122
摘要
Understanding how the cellular and molecular composition of neural circuits evolves to generate species-specific behaviors remains a major challenge in evolutionary biology and neuroscience. The remarkable diversity of male sexual behaviors among Drosophila species, despite their recent divergence, offers an excellent model for addressing this question. Here, by harnessing single-cell transcriptomics of the sexual circuits labeled by the sex determination gene doublesex ( dsx ) at high resolution, we delineated 84 molecularly distinct dsx + cell types, each mapped to anatomically and functionally defined dsx + neural populations. Our findings revealed a largely conserved cellular architecture, with minimal evolutionary gain or loss of cell types across four Drosophila species. A detailed comparison between Drosophila melanogaster ( D. melanogaster ) and D. yakuba uncovered pervasive heterogeneity in transcriptomic divergence among dsx + cell types. While core cell type identities—defined by the sex determination gene fruitless ( fru ), neurotransmitters, monoamines, and transcription factors—remain highly conserved, we observed striking evolutionary turnover in neuropeptide signaling pathways in a highly cell-type-specific manner, underscoring the role of functional reconfiguration of conserved circuits in behavioral evolution. Further investigation of sex differences in dsx + neurons revealed that male-specific cell types are not more evolutionarily divergent than sex-unbiased ones. Finally, we developed an interactive web resource for data access and characterized marker gene combinations enabling cell-type-specific labeling. Overall, our study provides insights into how neural circuits evolve to encode behavioral diversity and establishes a high-resolution framework for understanding the cellular basis of behavioral adaptation.
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