Chromosome-level genome assembly of the cave leech Sinospelaeobdella cavatuses (Hirudinea: Haemadipsidae).

IF 5.8 2区综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES

Scientific Data Pub Date : 2024-11-13 DOI:10.1038/s41597-024-04007-3

Binbin Yao, Delong Guan, Lulu Yang, Tao Jiang, Lu Zhao, Muhammad Salabat Khan, Sheng-Quan Xu

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Abstract

Leeches are famous for their high medical value and wide environmental adaptability. Among them, cave leeches are a very fascinating and rare group, which is an important component in the study of adaptive evolution of leeches. However, no study has yet reported a reference genome for this group. In this study, we assembled a high-quality chromosome-level genome of the cave terrestrial leech Sinospelaeobdella cavatuses, through Illumina and PacBio sequencing, alongside chromosome conformation capture techniques. The resulting genome spans 153.67 Mb across 9 pseudochromosomes(range: 11.33 to 23.53 Mb), with a mounting rate of up to 95.37% and features an N50 length of 17.15 Mb. This genome is composed of 35.16% repetitive elements and contains 21180 predicted protein-coding genes. Decoding the S. cavatuses genome not only promotes future studies on study of its phylogeny, evolution, and behavior, but also provides valuable resources for in-depth investigation on adaptive evolution of leech.

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洞穴水蛭（Sinospelaeobdella cavatuses）（蛭科：Haemadipsidae）染色体组水平的基因组组装。

水蛭以其极高的医疗价值和广泛的环境适应性而闻名于世。其中，穴居水蛭是一个非常迷人和罕见的群体，是研究水蛭适应性进化的重要组成部分。然而，目前还没有关于该类水蛭参考基因组的研究报告。在这项研究中，我们通过Illumina和PacBio测序技术以及染色体构象捕获技术，组装了洞穴陆生水蛭Sinospelaeobdella cavatuses的高质量染色体组基因组。测序结果显示，9个假染色体的基因组跨度为153.67 Mb（范围：11.33至23.53 Mb），安装率高达95.37%，N50长度为17.15 Mb。该基因组由 35.16% 的重复元件组成，包含 21180 个预测的蛋白质编码基因。水蛭基因组的解码不仅有助于今后对其系统发育、进化和行为的研究，也为深入研究水蛭的适应性进化提供了宝贵的资源。

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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.