Chan Wan Wen Rochelle, Chang Jia Jin Marc, Tan Charles Zhiming, Ng Jie Xin, Ng Matthew Hui-Chieh, Jaafar Zeehan, Huang Danwei
Department of Biological Sciences, National University of Singapore, Singapore.
Lee Kong Chian Natural History Museum, National University of Singapore, Singapore.
J Fish Biol. 2024 Dec;105(6):1784-1799. doi: 10.1111/jfb.15920. Epub 2024 Sep 3.
Identification of fish larvae based on morphology is typically limited to higher taxonomic ranks (e.g., family or order), as larvae possess few morphological diagnostic characters for precise discrimination to species. When many samples are presented at any one time, the use of morphology to identify such specimens can be laborious and time-consuming. Using a reverse workflow for specimen sorting and identification leveraging high-throughput DNA sequencing, thousands of fish larvae can be DNA barcoded and sorted into molecular operational taxonomic units (mOTUs) in a single sequencing run with the nanopore sequencing technology (e.g., MinION). This process reduces the time and financial costs of morphology-based sorting and instead deploys experienced taxonomists for species taxonomic work where they are needed most. In this study, a total of 3022 fish larval specimens from plankton tows across four sites in Singapore were collected and sorted based on this workflow. Eye tissue from individual samples was used for DNA extraction and sequencing of cytochrome c oxidase subunit I. We generated a total of 2746 barcodes after quality filtering (90.9% barcoding success), identified 2067 DNA barcodes (75.3% identification success), and delimited 256 mOTUs (146 genera, 52 families). Our analyses identified specific challenges to species assignment, such as the potential misidentification of publicly available sequences used as reference barcodes. We highlighted how the conservative application and comparison of a local sequence database can help resolve identification conflicts. Overall, this proposed approach enables and expedites taxonomic identification of fish larvae, contributing to the enhancement of reference barcode databases and potentially better understanding of fish connectivity.
基于形态学识别鱼类幼体通常局限于较高的分类等级(如科或目),因为幼体具有的用于精确鉴别到物种的形态学诊断特征很少。当同时呈现许多样本时,利用形态学来识别这些标本可能既费力又耗时。通过采用反向工作流程,利用高通量DNA测序进行标本分类和识别,使用纳米孔测序技术(如MinION),在一次测序运行中可以对数千条鱼类幼体进行DNA条形码标记并分类到分子操作分类单元(mOTUs)中。这一过程减少了基于形态学分类的时间和财务成本,转而将经验丰富的分类学家部署到最需要他们进行物种分类工作的地方。在本研究中,根据这一工作流程,共收集并分类了来自新加坡四个地点浮游生物拖网的3022个鱼类幼体标本。从单个样本中提取眼睛组织用于DNA提取和细胞色素c氧化酶亚基I的测序。经过质量过滤后,我们共生成了2746个条形码(条形码成功率为90.9%),识别出2067个DNA条形码(识别成功率为75.3%),并划分出256个mOTUs(146个属,52个科)。我们的分析确定了物种鉴定面临的具体挑战,例如用作参考条形码的公开可用序列可能存在错误识别。我们强调了本地序列数据库的保守应用和比较如何有助于解决识别冲突。总体而言,这种提议的方法能够实现并加快鱼类幼体的分类鉴定,有助于增强参考条形码数据库,并可能更好地理解鱼类的连通性。