Chromosome-level genome assembly of scalloped spiny lobster Panulirus homarus homarus.

IF 5.8 2区 综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES
Dongfang Sun, Jianjian Lv, Baoquan Gao, Shaoting Jia, Ping Liu, Jian Li, Jitao Li, Xianyun Ren
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引用次数: 0

Abstract

Lobsters, aquatic organisms of significant economic value, hold an important position in the global aquaculture and fisheries industries. However, due to overfishing and ecological change, the populations of certain lobster species have declined dramatically, prompting conservation efforts in various countries. However, limited genomics research has restricted our capacity to conserve and exploit lobster germplasm resources. Here, we present a chromosome-level reference genome for Panulirus homarus homarus constructed using PacBio long-read sequencing and Hi-C data. The genome assembly size was 2.61 Gb, with a contig N50 of 5.43 Mb, and a scaffold N50 of 36.69 Mb. The assembled sequences were anchored to 73 chromosomes, covering 96.05% of the total genome. A total of 25,580 protein-coding genes were predicted, and 99.98% of the genes were functionally annotated using various protein databases. The high-quality genome assembly provides a valuable resource for studying the biology and evolutionary history of P. h. homarus, and could facilitate sustainable resource management, aquaculture, and conservation of the species.

扇贝龙虾的染色体水平基因组组装。
龙虾是具有重要经济价值的水生生物,在全球水产养殖业和渔业中占有重要地位。然而,由于过度捕捞和生态变化,某些龙虾物种的数量急剧下降,促使各国采取保护措施。然而,有限的基因组学研究限制了我们保护和开发龙虾种质资源的能力。在此,我们利用PacBio长读测序和Hi-C数据构建了同源Panulirus homarus homarus的染色体水平参考基因组。基因组组装大小为2.61 Gb, contig N50为5.43 Mb, scaffold N50为36.69 Mb。组装的序列锚定在73条染色体上,覆盖了总基因组的96.05%。共预测了25580个蛋白质编码基因,99.98%的基因通过各种蛋白质数据库进行了功能注释。高质量的基因组图谱为研究homarus p.h.的生物学和进化历史提供了宝贵的资源,为资源的可持续管理、水产养殖和物种保护提供了依据。
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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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