Chromosome-scale genome assembly and annotation of Xenocypris argentea.

IF 5.8 2区 综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES
Yidi Wu, Hang Sha, Hongwei Liang
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Abstract

Xenocypris argentea is a small to medium-sized freshwater cyprinid fish. It distributes widely in the rivers and lakes of China, and is often used as a tool fish for water quality improvement and optimizing aquaculture structures. In recent years, natural populations of X. argentea have decreased rapidly due to human activities, yet little is known about the genetics and genomics of this fish. In the present work, we reported a chromosome-level reference genome of X. argentea based on PacBio HiFi, Hi-C and Illumina paired-end sequencing technologies. The assembled genome was 984.96 Mb in length, with a contig N50 of 36.02 Mb. Using Hi-C interaction information, 99.47% of the contigs were anchored onto 24 chromosomes, and 18 of the chromosomes were gap-free. Further analysis identified 560.27 Mb of repeat sequences and 28,533 protein-coding genes in the genome, of which, 95.62% (27,284) genes were functionally annotated. This high-quality genome offers an invaluable resource for population genetics and phylogeny, comparative genomics, adaptive evolution and functional exploration of X. argentea.

凤尾Xenocypris染色体尺度的基因组组装与注释。
阿根廷xencypris是一种小型到中型淡水鲤科鱼类。它广泛分布在中国的河流和湖泊中,经常被用作改善水质和优化养殖结构的工具鱼。近年来,由于人类活动的影响,凤尾鱼的自然种群数量迅速减少,但人们对凤尾鱼的遗传和基因组学知之甚少。在本工作中,我们基于PacBio HiFi、Hi-C和Illumina配对端测序技术报道了阿根廷茶的染色体水平参考基因组。该基因组全长984.96 Mb, N50为36.02 Mb。利用Hi-C互作信息,99.47%的contigs被锚定在24条染色体上,其中18条染色体无间隙。进一步分析,共鉴定出560.27 Mb的重复序列和28533个蛋白质编码基因,其中95.62%(27284个)基因被功能注释。这一高质量的基因组为银杏的种群遗传学和系统发育、比较基因组学、适应进化和功能探索提供了宝贵的资源。
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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