Chromosome-scale genome assembly of the tropical abalone (Haliotis asinina).

IF 5.8 2区 综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES
Roy Barkan, Ira Cooke, Sue-Ann Watson, Sally C Y Lau, Jan M Strugnell
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引用次数: 0

Abstract

Abalone (family Haliotidae) are an ecologically and economically significant group of marine gastropods that can be found in tropical and temperate waters. To date, only a few Haliotis genomes are available, all belonging to temperate species. Here, we provide the first chromosome-scale abalone genome assembly and the first reference genome of the tropical abalone Haliotis asinina. The combination of PacBio long-read HiFi sequencing and Dovetail's Omni-C sequencing allowed the chromosome-level assembly of this genome, while PacBio Isoform sequencing across five tissue types enabled the construction of high-quality gene models. This assembly resulted in 16 pseudo-chromosomes spanning over 1.12 Gb (98.1% of total scaffolds length), N50 of 67.09 Mb, the longest scaffold length of 105.96 Mb, and a BUSCO completeness score of 97.6%. This study identified 25,422 protein-coding genes and 61,149 transcripts. In an era of climate change and ocean warming, this genome of a heat-tolerant species can be used for comparative genomics with a focus on thermal resistance. This high-quality reference genome of H. asinina is a valuable resource for aquaculture, fisheries, and ecological studies.

热带鲍鱼(Haliotis asinina)染色体级基因组组装。
鲍鱼(鲍鱼科)是一类具有重要生态和经济价值的海洋腹足类动物,分布于热带和温带水域。迄今为止,只有少数鲍鱼基因组可用,而且都属于温带物种。在这里,我们提供了第一个染色体级鲍鱼基因组组装和热带鲍鱼 Haliotis asinina 的第一个参考基因组。结合使用 PacBio 长读程 HiFi 测序和 Dovetail 的 Omni-C 测序,我们完成了染色体级的基因组组装,同时通过对五种组织类型进行 PacBio Isoform 测序,我们构建了高质量的基因模型。这次组装得到了 16 个伪染色体,跨度超过 1.12 Gb(占支架总长度的 98.1%),N50 为 67.09 Mb,最长支架长度为 105.96 Mb,BUSCO 完整性得分为 97.6%。这项研究发现了 25,422 个蛋白质编码基因和 61,149 个转录本。在气候变化和海洋变暖的时代,这个耐热物种的基因组可用于以耐热性为重点的比较基因组学研究。这一高质量的H. asinina参考基因组是水产养殖、渔业和生态研究的宝贵资源。
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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