Chromosome-level genome assembly and annotation of the sharpsnout seabream (Diplodus puntazzo).

IF 5.8 2区 综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES
Cinta Pegueroles, Carles Galià-Camps, Marta Pascual, Marta Bassitta, Didac González, Carola Greve, Enrique Macpherson, Núria Raventós, Tilman Schell, Héctor Torrado, Carlos Carreras
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Abstract

Diplodus puntazzo is a demersal fish inhabiting the Mediterranean Sea and the eastern Atlantic and plays an important ecological role in coastal areas. Here, we present the first nuclear genome assembly and annotation of this species and genus. We used a combination of PacBio CLR long reads, Illumina short reads and chromatin capture reads (Omni-C) to generate a chromosome-level assembly. The nuclear genome assembly has a total span of 788 Mb, containing 24 chromosome-scale scaffolds (98.76% of the total length), coinciding with its known karyotype. By using RNA-Seq data from D. puntazzo and gene models from closely related species, we also generated a high-quality nuclear annotation. We predicted a total of 87,572 transcripts from the nuclear genome, 26,838 coding, and 60,734 non-coding that included lncRNA, snoRNA, and tRNAs. We also assembled and annotated the mitochondrial genome, circularized in 16,642 bp comprising 13 protein-coding genes, 2 rRNA, and 22 tRNA. This high-quality reference genome will enrich the current genomic resources available to the large fish scientific community.

尖吻鲷(Diplodus puntazzo)染色体级基因组组装与注释。
puntazzo梁龙是一种生活在地中海和东大西洋的底栖鱼类,在沿海地区起着重要的生态作用。在这里,我们提出了该种和属的第一个核基因组组装和注释。我们使用PacBio CLR长读取,Illumina短读取和染色质捕获读取(Omni-C)的组合来生成染色体水平的组装。核基因组的总长度为788 Mb,包含24个染色体尺度的支架(占总长度的98.76%),与已知的核型一致。通过使用D. puntazzo的RNA-Seq数据和来自近缘物种的基因模型,我们还生成了高质量的核注释。我们预测了来自核基因组的总共87,572个转录本,26,838个编码转录本和60,734个非编码转录本,包括lncRNA, snoRNA和trna。我们还组装并注释了线粒体基因组,该基因组长16,642 bp,包含13个蛋白质编码基因,2个rRNA和22个tRNA。这种高质量的参考基因组将丰富目前可供大型鱼类科学界使用的基因组资源。
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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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