A novel taxonomic database for eukaryotic mitochondrial cytochrome oxidase subunit I gene (eKOI), with a focus on protists diversity.

IF 3.6 4区 生物学 Q1 MATHEMATICAL & COMPUTATIONAL BIOLOGY
Rubén González-Miguéns, Àlex Gàlvez-Morante, Margarita Skamnelou, Meritxell Antó, Elena Casacuberta, Daniel J Richter, Enrique Lara, Daniel Vaulot, Javier Del Campo, Iñaki Ruiz-Trillo
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引用次数: 0

Abstract

Metabarcoding has emerged as a robust method for assessing biodiversity patterns by retrieving environmental DNA directly from ecosystems. While the 18S rRNA gene is the primary genetic marker used for broad eukaryotic metabarcoding, it has limitations in resolving lower taxonomic levels. A potential alternative is the mitochondrial cytochrome oxidase subunit I (COI) gene because it offers resolution at the species level. However, the COI gene lacks a comprehensive, curated taxonomically informed database including protists. To address this gap, we introduce eKOI, a novel, curated COI gene database designed to enhance the taxonomic annotation for protists that can be used for COI-based metabarcoding. eKOI integrates data from GenBank and mitochondrial genomes, followed by extensive manual curation to eliminate redundancies and contaminants, recovering 15 947 sequences within 80 eukaryotic phyla. We validated the use of eKOI by reannotating several COI metabarcoding datasets, revealing previously unidentified protist biodiversity and demonstrating the database utility for community-level analyses.

一个新的真核线粒体细胞色素氧化酶亚基I基因(eKOI)的分类数据库,重点关注原生生物的多样性。
元条形码已经成为一种通过直接从生态系统中检索环境DNA来评估生物多样性模式的强大方法。虽然18S rRNA基因是用于广泛真核生物元条形码编码的主要遗传标记,但它在解决较低分类水平方面存在局限性。一个潜在的替代方案是线粒体细胞色素氧化酶亚基I (COI)基因,因为它在物种水平上提供了解决方案。然而,COI基因缺乏一个包括原生生物在内的全面的、精心策划的分类信息数据库。为了解决这一差距,我们引入了eKOI,这是一个新的COI基因数据库,旨在增强原生生物的分类注释,可用于基于COI的元条形码。eKOI整合了来自GenBank和线粒体基因组的数据,随后进行了大量的人工管理,以消除冗余和污染物,在80个真核生物门中恢复了15947个序列。我们通过重新标注几个COI元条形码数据集来验证eKOI的使用,揭示了以前未识别的原生生物多样性,并展示了数据库在社区层面分析的实用性。
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来源期刊
Database: The Journal of Biological Databases and Curation
Database: The Journal of Biological Databases and Curation MATHEMATICAL & COMPUTATIONAL BIOLOGY-
CiteScore
9.00
自引率
3.40%
发文量
100
审稿时长
>12 weeks
期刊介绍: Huge volumes of primary data are archived in numerous open-access databases, and with new generation technologies becoming more common in laboratories, large datasets will become even more prevalent. The archiving, curation, analysis and interpretation of all of these data are a challenge. Database development and biocuration are at the forefront of the endeavor to make sense of this mounting deluge of data. Database: The Journal of Biological Databases and Curation provides an open access platform for the presentation of novel ideas in database research and biocuration, and aims to help strengthen the bridge between database developers, curators, and users.
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