热带紫海胆(Heliocidaris crassispina)染色体水平基因组组装。

IF 6.9 2区 综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES
Yang Liu, Ting Chen, Bo Ma, Jiayue Yin, Chunhua Ren, Xiao Jiang, Yanhong Wang, Wenjie Pan, Jiasheng Huang, Suzhong Yu, Peng Luo
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引用次数: 0

摘要

禾草海胆是一种具有生态价值和经济价值的热带海胆,是理想的实验动物。本研究首先采用PacBio HiFi和Hi-C测序数据的组合来呈现高质量的、染色体水平的草蚜基因组组装。该基因组全长709.77 Mb,序列N50长度为4.98 Mb,支架N50长度为33.23 Mb。该组装固定在21条假染色体上,覆盖了基因组的98.32%。共鉴定出18665个蛋白质编码基因,BUSCO分析显示完整性评分为97.1%。此外,对非编码rna (ncrna)进行了注释,包括mirna、RNAs、trna和snrna,提供了对基因组更完整的功能理解。高质量的参考基因组将丰富现有棘皮动物基因组资源,为今后的资源调查、基因组育种和海洋牧场管理等研究提供坚实的基础。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A chromosome-level genome assembly of tropical purple sea urchin Heliocidaris crassispina.

Heliocidaris crassispina is a tropical sea urchin that holds both ecological and economic value and serves as an ideal experimental animal. This study first employed a combination of PacBio HiFi and Hi-C sequencing data to present a high-quality, chromosome-level assembly of H. crassispina genome. This assembled genome spanned 709.77 Mb, with a contig N50 length of 4.98 Mb and a scaffold N50 length of 33.23 Mb. The assembly was anchored on 21 pseudo-chromosomes, covering 98.32% of the genome. A total of 18,665 protein-coding genes were identified, and BUSCO analysis revealed a completeness score of 97.1%. Additionally, non-coding RNAs (ncRNAs) were annotated, including miRNAs, rRNAs, tRNAs and snRNAs, providing a more complete functional understanding of the genome. The high-quality reference genome will enrich the current echinoderm genomic resources and provide a solid foundation for future studies on H. crassispina, including resource surveys, genomic breeding, and marine ranch management.

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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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