Department of Aquatic Bioscience, Graduate School of Agricultural and Life Sciences, The University of Tokyo, 1-1-1 Yayoi, Bunkyo-ku, 113-8657, Tokyo, Japan.
Tokyo Sea Life Park, 6-2-3 Rinkai-cho, Edogawa-ku, 134-8587, Tokyo, Japan.
Funct Integr Genomics. 2023 Mar 22;23(2):96. doi: 10.1007/s10142-023-01013-3.
Many studies have investigated the ability of environmental DNA (eDNA) to identify the species. However, when individual species are to be identified, accurate estimation of their abundance using traditional eDNA analyses is still difficult. We previously developed a novel analytical method called HaCeD-Seq (haplotype count from eDNA by sequencing), which focuses on the mitochondrial D-loop sequence for eels and tuna. In this study, universal D-loop primers were designed to enable the comprehensive detection of multiple fish species by a single sequence. To sequence the full-length D-loop with high accuracy, we performed nanopore sequencing with unique molecular identifiers (UMI). In addition, to determine the D-loop reference sequence, whole genome sequencing was performed with thin coverage, and complete mitochondrial genomes were determined. We developed a UMI-based Nanopore D-loop sequencing analysis pipeline and released it as open-source software. We detected 5 out of 15 species (33%) and 10 haplotypes out of 35 individuals (29%) among the detected species. This study demonstrates the possibility of comprehensively obtaining information related to population size from eDNA. In the future, this method can be used to improve the accuracy of fish resource estimation, which is currently highly dependent on fishing catches.
许多研究都调查了环境 DNA(eDNA)识别物种的能力。然而,当需要鉴定个别物种时,使用传统的 eDNA 分析准确估计它们的丰度仍然很困难。我们之前开发了一种称为 HaCeD-Seq(通过测序计算 eDNA 中的单倍型数量)的新型分析方法,该方法专注于鳗鱼和金枪鱼的线粒体 D 环序列。在这项研究中,设计了通用的 D 环引物,使通过单个序列能够全面检测多种鱼类。为了以高精度对全长 D 环进行测序,我们使用具有独特分子标识符(UMI)的纳米孔测序进行测序。此外,为了确定 D 环参考序列,我们进行了薄覆盖的全基因组测序,并确定了完整的线粒体基因组。我们开发了基于 UMI 的纳米孔 D 环测序分析管道,并将其作为开源软件发布。在检测到的物种中,我们检测到了 15 个物种中的 5 个(33%)和 35 个个体中的 10 个单倍型(29%)。本研究表明从 eDNA 中全面获取与种群规模相关信息的可能性。在未来,该方法可用于提高目前高度依赖捕捞量的鱼类资源估计的准确性。