A chromosome-level genome assembly of the mud carp (Cirrhinus molitorella).

IF 5.8 2区综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES

Scientific Data Pub Date : 2025-02-17 DOI:10.1038/s41597-025-04615-7

Guangxian Tu, Zhuyue Yan, Long Zhang, Ziwei Liu, Yanrong Lv, Zhengyuan Li, Jian He, Shaoping Weng, Jianguo He, Muhua Wang

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Abstract

Algal blooms, which have become increasingly prevalent worldwide over the past decade, significantly impact on water quality and aquatic organisms. Filter-feeding fish are used to control phytoplankton and improve the ecological quality of water bodies. Mud carp (Cirrhinus molitorella) is a freshwater cyprinid species that predominantly consumes algae. Here, we generated a high-quality chromosome-level assembly of C. molitorella by integrating PacBio and Hi-C sequencing strategies. The genome assembly is 1.05 Gb, with a contig N50 of 24.13 Mb and a scaffold N50 of 39.38 Mb. The Benchmarking Universal Single-Copy Orthologs (BUSCO) (v4.0.5) benchmark of genome assembly reached 97.4% (95.8% single-copy). The consensus quality value (QV) and k-mer completeness of the C. molitorella assembly evaluated by Merqury software were 30.35 and 92.16%, respectively. The construction of the C. molitorella genome provides a valuable genetic resource that will facilitate the investigation of the digestion mechanism of filter-feeding fish.

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藻华在过去十年中在全球范围内日益盛行，对水质和水生生物造成了严重影响。滤食性鱼类被用来控制浮游植物，改善水体的生态质量。鲮鱼（Cirrhinus molitorella）是一种淡水鲤科鱼类，主要食用藻类。在这里，我们通过整合 PacBio 和 Hi-C 测序策略，生成了高质量的鲮鱼染色体组。该基因组组装为 1.05 Gb，等位基因 N50 为 24.13 Mb，支架 N50 为 39.38 Mb。基因组组装的通用单拷贝同源物基准（BUSCO）（v4.0.5）达到了 97.4%（单拷贝 95.8%）。Merqury软件对C. molitorella基因组组装的共识质量值（QV）和k-mer完整性的评估分别为30.35%和92.16%。C. molitorella基因组的构建为研究滤食性鱼类的消化机制提供了宝贵的遗传资源。

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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.