波罗的海欧洲鲽(P. flesus)基因组指导下的器官特异性转录组组装。

IF 5.8 2区 综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES Scientific Data Pub Date : 2024-10-30 DOI:10.1038/s41597-024-04004-6
Konrad Pomianowski, Ewa Kulczykowska, Artur Burzyński
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引用次数: 0

摘要

尽管欧洲鲽经常被用于研究并具有重要的经济价值,但该物种仍然缺乏全面的转录组数据。在本研究中,我们展示了栖息在格但斯克湾(波罗的海南部)咸水中的欧洲鲽雌鱼十个选定器官的 RNA-Seq 数据。利用高通量下一代测序技术 NovaSeq 6000 生成了 500 M 个测序读数。这些读数与欧洲比目鱼参考基因组进行了映射,并将映射中提取的读数进行组装,产生了 61k 个可靠的等位组。根据PFAM、PANTHER、UniProt和InterPro蛋白质数据库的搜索结果,将基因本体论(GO)术语分配给大多数注释等位基因/单基因。真核生物、元古宙、脊椎动物和翼手目数据库的 BUSCOs 统计数据表明,报告的转录组具有很高的完整性。该数据集可成功用作生物学、水产养殖和毒理学等多个研究领域的实验设计工具。
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Genome guided, organ-specific transcriptome assembly of the European flounder (P. flesus) from the Baltic Sea.

Although the European flounder is frequently used in research and has economic importance, there is still lack of comprehensive transcriptome data for this species. In the present research we show RNA-Seq data from ten selected organs of P. flesus female inhabiting brackish waters of the Gulf of Gdańsk (southern Baltic Sea). High throughput Next Generation Sequencing technology NovaSeq 6000 was used to generate 500 M sequencing reads. These were mapped against European flounder reference genome and reads extracted from the mapping were assembled producing 61k reliable contigs. Gene ontology (GO) terms were assigned to the majority of annotated contigs/unigenes based on the results of PFAM, PANTHER, UniProt and InterPro protein databases searches. BUSCOs statistics for eukaryota, metazoa, vertebrata and actinopterygii databases showed that the reported transcriptome represents a high level of completeness. The data set can be successfully used as a tool in design of experiments from various research fields including biology, aquaculture and toxicology.

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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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