High-resolution single-cell analyses reveal evolutionary constraints and evolvability of sexual circuits in <i>Drosophila</i>.

Abstract

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 <i>Drosophila</i> 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 <i>doublesex</i> (<i>dsx</i>) at high resolution, we delineated 84 molecularly distinct <i>dsx</i>+ cell types, each mapped to anatomically and functionally defined <i>dsx</i>+ neural populations. Our findings revealed a largely conserved cellular architecture, with minimal evolutionary gain or loss of cell types across four <i>Drosophila</i> species. A detailed comparison between <i>Drosophila melanogaster</i> (<i>D. melanogaster</i>) and <i>D. yakuba</i> uncovered pervasive heterogeneity in transcriptomic divergence among <i>dsx</i>+ cell types. While core cell type identities-defined by the sex determination gene <i>fruitless</i> (<i>fru</i>), 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 <i>dsx</i>+ 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.