A chromosome-level genome assembly of Mylabris sibirica Fischer von Waldheim, 1823 (Coleoptera, Meloidae).

IF 6.9 2区综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES Scientific Data Pub Date : 2025-02-14 DOI:10.1038/s41597-025-04532-9

Chenhui Shen, Guofeng Yang, Min Tang, Xiaofei Li, Li Zhu, Wei Li, Lin Jin, Pan Deng, Huanhuan Zhang, Qing Zhai, Gang Wu, Xiaohong Yan

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Abstract

Mylabris sibirica is a hypermetamorphic insect that primarily feeds on oilseed rape during the adult stage. However, the limited availability of genomic resources hinders our understanding of the gene function, medical use, and ecological adaptation in M. sibirica. Here, a high-quality chromosome-level genome of M. sibirica was generated by PacBio, Illumina, and Hi-C technologies. Its genome size was 138.45 Mb, with a scaffold N50 of 13.84 Mb and 99.85% (138.25 Mb) of the assembly anchors onto 10 pseudo-chromosomes. BUSCO analysis showed this genome assembly had a high-level completeness of 100% (n = 1,367), containing 1,358 (99.4%) single-copy BUSCOs and 8 (0.6%) duplicated BUSCOs. In addition, a total of 11,687 protein-coding genes and 35.46% (49.10 Mb) repetitive elements were identified. The high-quality genome assembly offers valuable genomic resources for exploring gene function, medical use, and ecology.

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sibirica Fischer von Waldheim的染色体水平基因组组装，1823（鞘翅目，蝇科）。

西伯利亚大叶蝉是一种超变质昆虫，在成虫阶段主要以油菜为食。然而，有限的基因组资源阻碍了我们对西伯利亚支原体基因功能、医学用途和生态适应的理解。通过PacBio、Illumina和Hi-C技术，我们获得了西伯利亚支原体高质量的染色体水平基因组。其基因组大小为138.45 Mb，支架N50为13.84 Mb, 99.85% （138.25 Mb）的组装锚定在10条伪染色体上。BUSCO分析显示，该基因组组装具有100%的高完整性（n = 1,367），包含1,358个（99.4%）单拷贝BUSCO和8个（0.6%）重复BUSCO。此外，共鉴定出11,687个蛋白质编码基因和35.46% （49.10 Mb）的重复元件。高质量的基因组组装为探索基因功能、医学用途和生态学提供了宝贵的基因组资源。

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来源期刊

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.