Chromosome-level genome assembly of Sambus kanssuensis (Coleoptera: Buprestidae).

IF 5.8 2区综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES

Scientific Data Pub Date : 2025-05-28 DOI:10.1038/s41597-025-05271-7

Zhonghua Wei, Yunchun Li, Yingying Li, Jiuzhou Liu, Shuangmei Ding, Xulong Chen, Aimin Shi, Ding Yang

引用次数: 0

Abstract

Sambus kanssuensis Ganglbauer, 1890 (Coleoptera: Buprestidae), distributed in Gansu and Sichuan Provinces of China, is a phytophagous pest that feeds on the toxic plant Buddleja. However, the genomic resources of this beetle remain unknown, which impedes the understanding of its ecological adaptations. Consequently, this study presents a complete, well-assembled, and annotated genome of S. kanssuensis. The assembled results indicate a genome size of 312.42 Mb, comprising 206 scaffolds, with an N50 of 34.04 Mb; 98.68% of the assembly sequences were anchored to 11 chromosomes, including one sex chromosome. The genome contains 12,723 protein-coding genes, of which 11,977 have been annotated. BUSCO analysis revealed that the completeness of the chromosome-level genome is 97.9%. This chromosome-level genome provides valuable data for further investigations into detoxification mechanisms, ecological adaptations, population genetics, and the evolution of Buprestidae.

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甘肃野田鼠染色体水平的基因组组装（鞘翅目：野田鼠科）。

甘肃野蛾（Sambus kanssuensis Ganglbauer）， 1890（鞘翅目：野蛾科），分布于中国甘肃和四川两省，是一种以有毒植物野蛾为食的植食性害虫。然而，这种甲虫的基因组资源仍然未知，这阻碍了对其生态适应性的理解。因此，这项研究提出了一个完整的，良好的组装，并注释了南苏丹的基因组。结果表明，该基因全长312.42 Mb，包含206个支架，N50为34.04 Mb；98.68%的组装序列锚定在11条染色体上，其中包括1条性染色体。基因组包含12,723个蛋白质编码基因，其中11,977个已被注释。BUSCO分析显示，染色体水平基因组的完整性为97.9%。这个染色体水平的基因组为进一步研究解毒机制、生态适应、群体遗传学和bupresdae的进化提供了有价值的数据。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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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.