Mining functional genes and characterizing cellular transcriptomic profiles in the single-cell atlas of adult Spodoptera litura ovary

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This study generated a single-cell transcriptomic atlas of the *Spodoptera litura* ovary, identified major cell populations, and validated key genes' roles in ovarian development and fecundity.

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The study generated a single-cell RNA sequencing atlas of the adult ovary in the lepidopteran pest Spodoptera litura, integrating cross-species comparisons with Drosophila melanogaster to identify major germline and somatic cell populations and to distinguish conserved versus species-specific ovarian features. The authors validated cell-type markers using in situ hybridization, then used RNA interference to test the roles of germline-enriched genes (Hsc70-4, Wech, Polo, Path) in ovarian development and fecundity. They also applied trajectory inference, SCENIC, and CellChat to infer transcriptional regulatory programs and predicted cell–cell communication during oogenesis. A key limitation is that the work is centered on insect ovarian biology as a molecular resource, rather than on mechanistic disease pathways. The paper does not explicitly discuss endometriosis or adenomyosis; it was included in the corpus via a keyword match in the upstream search index.

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Abstract

Understanding the reproductive biology of non-model organisms remains challenging due to the limited availability of high-resolution molecular resources. Here, we present a comprehensive single-cell transcriptomic atlas of the adult ovary of Spodoptera litura ( S. litura ), a highly polyphagous agricultural pest with a polytrophic meroistuc ovary. By integrating single-cell RNA sequencing with cross-species comparison to Drosophila melanogaster ( D. melanogaster ), we define major germline and somatic cell populations and delineate conserved and species-specific features of ovarian cell composition. To enhance the interpretability and reuse of this dataset, we combine transcriptomic profiling with in situ hybridization to validate cluster-specific molecular markers across ovarian cell types. We further apply RNA interference (RNAi) to assess the contributions of germline-enriched genes (Hsc70-4, Wech, Polo, Path) to ovarian development and fecundity. Trajectory inference, together with SCENIC and CellChat analyses, provides a system-level view of transcriptional regulatory programs and predicted intercellular communication pathways during oogenesis in S. litura . Collectively, this work establishes a valuable resource for studying lepidopteran insect oogenesis, offering a comparative framework for reproductive biology in non-model insects and highlighting potential targets for RNAi-based pest control strategies.
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Abstract Understanding the reproductive biology of non-model organisms remains challenging due to the limited availability of high-resolution molecular resources. Here, we present a comprehensive single-cell transcriptomic atlas of the adult ovary of Spodoptera litura (S. litura), a highly polyphagous agricultural pest with a polytrophic meroistuc ovary. By integrating single-cell RNA sequencing with cross-species comparison to Drosophila melanogaster (D. melanogaster), we define major germline and somatic cell populations and delineate conserved and species-specific features of ovarian cell composition. To enhance the interpretability and reuse of this dataset, we combine transcriptomic profiling with in situ hybridization to validate cluster-specific molecular markers across ovarian cell types. We further apply RNA interference (RNAi) to assess the contributions of germline-enriched genes (Hsc70-4, Wech, Polo, Path) to ovarian development and fecundity. Trajectory inference, together with SCENIC and CellChat analyses, provides a system-level view of transcriptional regulatory programs and predicted intercellular communication pathways during oogenesis in S. litura. Collectively, this work establishes a valuable resource for studying lepidopteran insect oogenesis, offering a comparative framework for reproductive biology in non-model insects and highlighting potential targets for RNAi-based pest control strategies. Competing Interest Statement The authors have declared no competing interest.

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europepmc
last seen: 2026-05-20T01:45:00.602351+00:00
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License: CC-BY-NC-4.0