Chromosome-level genome assembly for the ecologically and economically important alga Saccharina japonica.

IF 6.9 2区 综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES Scientific Data Pub Date : 2025-02-18 DOI:10.1038/s41597-025-04620-w
Xiaodong Li, Yu-Long Li, Chenhui Zhong, Jing Li, Li Su, Jin-Xian Liu, Shaojun Pang
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Abstract

Saccharina japonica is a major kelp species of brown algae with the highest production among aquaculture seaweeds and holds important ecological and economic value. Despite advancements in domestication, a high-quality chromosome-level genome assembly is needed to assist its genetic improvement. Previous genome assemblies of S. japonica were either on a draft-level or highly fragmented. Here, we generated a high-quality chromosome-level genome for the female sporophyte using PacBio sequencing and Hi-C. The genome is 516.11 Mb, with contig N50 length of 491.30 Kb and scaffold N50 length of 16.24 Mb, anchored into 32 pseudo-chromosomes. Repetitive elements constituted 45.07% of the genome, and 17,739 protein-coding genes were predicted, of which 82% were functionally annotated. This genome provides a crucial resource for biotechnological advances in S. japonica breeding and offers insights into the ecology and evolution of brown algae.

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具有重要生态和经济意义的海藻糖藻的染色体水平基因组组装。
糖藻(Saccharina japonica)是养殖海藻中产量最高的褐藻主要海带种,具有重要的生态和经济价值。尽管在驯化方面取得了进展,但需要高质量的染色体水平基因组组装来辅助其遗传改进。先前的粳稻基因组组合要么处于草稿水平,要么高度碎片化。在这里,我们使用PacBio测序和Hi-C为雌性孢子体生成了高质量的染色体水平基因组。基因组全长516.11 Mb, contig N50长度491.30 Kb, scaffold N50长度16.24 Mb,锚定在32条伪染色体上。重复元件占基因组的45.07%,预测了17739个蛋白质编码基因,其中82%被功能注释。该基因组为粳稻育种的生物技术进步提供了重要资源,并为褐藻的生态学和进化提供了见解。
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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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