伪装石斑鱼(Epinephelus polyphekadion)染色体水平基因组组装与注释。

IF 6.9 2区 综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES
Haoyi Li, Yiqun Liu, Mingguang Mao, Yunxiang Mao
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引用次数: 0

摘要

伪装石斑鱼(Epinephelus polyphhekadion)是一种广泛分布于印度太平洋的经济食肉鱼类。然而,由于缺乏有效的参考基因组,严重阻碍了多角棘球绦虫生物学和基因组育种的进一步研究。在这里,我们利用PacBio测序和Hi-C技术提出了高质量的E. polyhekadia染色体水平基因组组装。染色体水平基因组全长1.1 Gb,序列N50为40.8 Mb。大约99.4%的组装长度固定在24条假染色体上。共预测蛋白编码基因25165个,其中功能注释基因24634个,占97.9%。使用BUSCO估计装配的完整性为99.1%。综上所述,本研究获得的首个参考基因组不仅为石斑鱼生物学和进化研究提供了关键的遗传资源,而且有利于石斑鱼人工产业基因组杂交育种的发展。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Chromosome-level genome assembly and annotation of the camouflage grouper (Epinephelus polyphekadion).

Chromosome-level genome assembly and annotation of the camouflage grouper (Epinephelus polyphekadion).

Chromosome-level genome assembly and annotation of the camouflage grouper (Epinephelus polyphekadion).

The camouflage grouper (Epinephelus polyphekadion) is an economically carnivorous fish widely distributed in the Indo-Pacific. However, no valid reference genome of E. polyphekadion severely hinders further research on biology and genomic breeding programs. Here, we presented a high-quality chromosome-level genome assembly of E. polyphekadion using PacBio sequencing and Hi-C technologies. The chromosome-level genome has a total length of 1.1 Gb with a contig N50 of 40.8 Mb. Approximately 99.4% of the assembly lengths were anchored to 24 pseudochromosomes. In total, 25,165 protein-coding genes were predicted, among which 24,634 genes (97.9%) were functionally annotated. The completeness of the assembly was estimated to be 99.1% using BUSCO. In summary, the first reference genome of E. polyphekadion in this study will not only provide pivotal genetic resources for further biological and evolutionary studies of groupers, but also benefit the development of genomic hybridization breeding in the artificial grouper industry.

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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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