Haplotype resolved chromosome-level genome assembly of the gold barb (Barbodes semifasciolatus).

IF 5.8 2区 综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES
Weitao Chen, Chao Li, Rong Yang, Yuefei Li, Baosheng Wu, Jie Li
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引用次数: 0

Abstract

The gold barb (Barbodes semifasciolatus), a member of the Cyprinidae family, exhibits remarkable adaptability to highly acidic environments, making it an ideal model for studying extreme environmental adaptation. However, its genome has not been previously characterized. To address this, we assembled a high-quality chromosome-scale genome for B. semifasciolatus using High-Fidelity (HiFi) sequencing and Hi-C technology. The resulting haplotype-resolved assemblies, spanning 776 Mb and 779 Mb across 25 chromosomes, achieved genome coverages of 99.5% and 99.7%, respectively, and included four gap-free chromosomes. Genome quality assessment using BUSCO indicated a high completeness score of 98.2% for haplotype1 and 98.3% for haplotype2, further validated by strong synteny with the zebrafish (Danio rerio), confirming the assembly's integrity and continuity. Through integration of full-length transcriptome data, RNA sequencing, and homology-based annotation, we identified 26,057 protein-coding genes with 2,087 pseudogenes in haplotype 2, and 25,622 protein-coding genes with 2,101 pseudogenes in haplotype 1. This high-resolution genome assembly is a crucial resource for advancing research in the Cyprinidae, particularly for understanding adaptive evolution in extreme environments.

金倒钩(Barbodes semifasciolatus)染色体水平基因组组装的单倍型解析。
金倒钩(Barbodes semifasciolatus)是鲤科的一员,对高酸性环境具有显著的适应性,是研究极端环境适应性的理想模型。然而,它的基因组以前没有被描述过。为了解决这个问题,我们使用高保真(High-Fidelity, HiFi)测序和Hi-C技术组装了高质量的半带库双鱼染色体尺度基因组。由此产生的单倍型分解组装,横跨25条染色体,长度分别为776 Mb和779 Mb,基因组覆盖率分别为99.5%和99.7%,包括4条无间隙染色体。利用BUSCO进行的基因组质量评估显示,haplotype1和haplotype2的完整性得分分别为98.2%和98.3%,与斑马鱼(Danio rerio)的强同一性进一步验证了该序列的完整性和连续性。通过整合全长转录组数据、RNA测序和基于同源性的注释,我们在单倍型2中鉴定出26,057个蛋白质编码基因和2,087个假基因,在单倍型1中鉴定出25,622个蛋白质编码基因和2,101个假基因。这种高分辨率的基因组组装是推进鲤科研究的重要资源,特别是对于理解极端环境下的适应性进化。
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
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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