A comprehensive cell atlas of fall armyworm (Spodoptera frugiperda) larval gut and fat body via snRNA-Seq.

IF 5.8 2区 综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES Scientific Data Pub Date : 2025-02-12 DOI:10.1038/s41597-025-04520-z
Chao Sun, Yongqi Shao, Junaid Iqbal
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Abstract

The midgut and fat body of insects control key physiological processes, including growth, digestion, metabolism, and stress response. Single-nucleus RNA sequencing (snRNA-seq) is a promising way to reveal organ complexity at the cellular level, yet data for lepidopteran insects are lacking. We utilized snRNA-seq to assess cellular diversity in the midgut and fat body of Spodoptera frugiperda. Our study identified 20 distinct clusters in the midgut, including enterocytes, enteroendocrine, stem-like cells, and muscle cells, and 27 clusters in the fat body, including adipocytes, hemocytes, and epithelial cells. This dataset, containing all identified cell types in midgut and fat body, is valuable for characterizing the cellular composition of these organs and uncovering new cell-specific biomarkers. This cellular atlas enhances our understanding of cellular heterogeneity of fat and midgut, serving as a basis for future functional and comparative analyses. As the first snRNA-seq study on the midgut and fat body of S. frugiperda, it will also support future research, contribute to lepidopteran studies, and aid in developing targeted pest control strategies.

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昆虫的中肠和脂肪体控制着关键的生理过程,包括生长、消化、新陈代谢和应激反应。单核 RNA 测序(snRNA-seq)是在细胞水平揭示器官复杂性的一种很有前途的方法,但目前还缺乏鳞翅目昆虫的相关数据。我们利用 snRNA-seq 评估了蛙翅蝶中肠和脂肪体的细胞多样性。我们的研究在中肠中发现了 20 个不同的细胞群,包括肠细胞、肠内分泌细胞、干样细胞和肌肉细胞;在脂肪体中发现了 27 个细胞群,包括脂肪细胞、血细胞和上皮细胞。这个数据集包含了中肠和脂肪体中所有已识别的细胞类型,对于描述这些器官的细胞组成和发现新的细胞特异性生物标记物非常有价值。该细胞图谱增强了我们对脂肪和中肠细胞异质性的了解,为未来的功能和比较分析奠定了基础。作为第一项关于节肢动物中肠和脂肪体的 snRNA-seq 研究,它还将支持未来的研究,为鳞翅目昆虫研究做出贡献,并有助于制定有针对性的害虫控制策略。
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来源期刊
Scientific Data
Scientific Data Social Sciences-Education
CiteScore
11.20
自引率
4.10%
发文量
689
审稿时长
16 weeks
期刊介绍: Scientific Data is an open-access journal focused on data, publishing descriptions of research datasets and articles on data sharing across natural sciences, medicine, engineering, and social sciences. Its goal is to enhance the sharing and reuse of scientific data, encourage broader data sharing, and acknowledge those who share their data. The journal primarily publishes Data Descriptors, which offer detailed descriptions of research datasets, including data collection methods and technical analyses validating data quality. These descriptors aim to facilitate data reuse rather than testing hypotheses or presenting new interpretations, methods, or in-depth analyses.
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