橄榄鲽(Paralichthys olivaceus)的全阶段基因组组装和基于图谱的遗传变异。

IF 5.8 2区 综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES
Julan Kim, Yoonsik Kim, Jeongwoen Shin, Yeong-Kuk Kim, Doo Ho Lee, Jong-Won Park, Dain Lee, Hyun-Chul Kim, Jeong-Ho Lee, Seung Hwan Lee, Jun Kim
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引用次数: 0

摘要

橄榄鲽(Paralichthys olivaceus),又称韩国比目鱼,是东亚国家一种具有重要经济价值的比目鱼。在这里,我们利用高保真长线程测序及其亲本短线程测序数据,提供了两个不同橄榄鲽个体的四个全相位基因组组装。我们获得了 42-44 Gb ~15-kb 和 ~Q30 高保真长读数,其组装质量值为 ~53。我们对每个基因组的 ~30 K 个基因、~170 MB 重复序列和 ~3 M 个 5-甲基胞嘧啶位置进行了注释,并建立了基于图谱的橄榄鲽泛基因组草案。我们发现了 500 万个单核苷酸变异和 100 K 个结构变异及其基因型信息,其中约 13% 的变异在两个韩国个体中可能是固定的。基于染色体水平的基因组组装,我们还探讨了早先报道的胸棘鲷家族的染色体进化。我们的高质量基因组资源将有助于未来的基因组选育,加快橄榄鲽的育种进程。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Fully phased genome assemblies and graph-based genetic variants of the olive flounder, Paralichthys olivaceus.

The olive flounder, Paralichthys olivaceus, also known as the Korean halibut, is an economically important flatfish in East Asian countries. Here, we provided four fully phased genome assemblies of two different olive flounder individuals using high-fidelity long-read sequencing and their parental short-read sequencing data. We obtained 42-44 Gb of ~15-kb and ~Q30 high-fidelity long reads, and their assembly quality values were ~53. We annotated ~30 K genes, ~170-Mb repetitive sequences, and ~3 M 5-methylcytosine positions for each genome assembly, and established a graph-based draft pan-genome of the olive flounder. We identified 5 M single-nucleotide variants and 100 K structural variants with their genotype information, where ~13% of the variants were possibly fixed in the two Korean individuals. Based on our chromosome-level genome assembly, we also explored chromosome evolution in the Pleuronectiformes family, as reported earlier. Our high-quality genomic resources will contribute to future genomic selection for accelerating the breeding process of the olive flounder.

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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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