5个常用环境DNA片段对长江鱼类的识别率

Species identification rates of commonly used Environmental DNA primers for Yangtze River fishes

  • 摘要:
    目的 为使水体中环境DNA (eDNA)在长江流域鱼类物种多样性研究中有更高的可参考性。
    方法 参考《长江鱼类名录》从公共数据库mitofish与NCBI中下载了320种长江鱼类DNA序列,从中截取了3种基因片段(12S RNA、16S RNA、COI)中的5种常用eDNA宏条形码(12S-AcDBM07、12S-Mifish-U、12S-Tele02、16S-Ac16s、COI-PS1)进行遗传距离计算,在不同种间差异阈值(0.03、0.02、0.01)下进行比对分析。得到不同种间差异阈值下常用eDNA宏条形码对长江鱼类的识别情况,探讨eDNA宏条形码在长江鱼类多样性研究中的应用条件。
    结果 在种间差异阈值为0.03、0.02、0.01时,分别有137、108、56种鱼类无法通过本研究中选择的5种常用eDNA宏条形码识别;其中蛋白质编码基因(COI-PS1)对鱼类的识别率最高,在不同种间差异阈值(0.03、0.02、0.01)下分别达到53.44%、60.63%、72.50%;12S-Tele02与12S-Mifish-U对长江鱼类识别种类上的重叠度最大,在不同种间差异阈值(0.03、0.02、0.01)下,重叠度分别达到98.54%、100%、91.11%。当选择2种eDNA宏条形码组合识别鱼类时,“12S-Tele02”&“COI-PS1”的组合在0.03、0.02和0.01的种间差异阈值下均识别了最多的种类,分别为180、206、257种,与同时使用5种eDNA宏条形码的组合相比分别相差3、6、7种。
    结论 将eDNA技术应用于长江鱼类多样性研究中需要充分考虑种间差异阈值的选择与近缘物种识别的关系,以防止OTU注释出现假阳性情况。在利用eDNA技术进行物种多样性监测时对于难以识别但保护价值较高的物种,可以有针对性地设计引物进行监测。本研究将为后期基于eDNA宏条形码技术的长江鱼类多样性调查以及相关研究提供基础参考资料。

     

    Abstract: Environmental DNA (eDNA) metabarcoding has emerged as a powerful approach for assessing aquatic biodiversity; however, it remains limited by uncertainties in OTU-clustering thresholds and taxonomic assignment. The Yangtze River, China’s longest river system, harbors over 4 300 aquatic species, with fish constituting a dominant group in freshwater ecosystems. Due to their sensitivity to water quality, fish serve as reliable ecological indicators for monitoring environmental change. To improve the reference value of eDNA in studying Yangtze River fish diversity, DNA sequences of 320 species were collected from Mitofish and NCBI databases. Five commonly used eDNA fragments (12S-AcDBM07, 12S-Mifish-U, 12S-Tele02, 16S-Ac16s, COI-PS1) were extracted from three genes (12S RNA, 16S RNA, COI) for genetic distance calculations under thresholds of 0.03, 0.02, and 0.01. This aimed to evaluate identification efficiency and explore applications in fish diversity studies. Results show that at thresholds of 0.03, 0.02, and 0.01, 137, 108, and 56 fish species could not be identified using the five fragments. Among them, the protein-coding gene COI-PS1 exhibited the highest identification rate, reaching 53.44%, 60.63%, and 72.50% respectively. Among the five fragments, 12S-Tele02 with 12S-Mifish-U had the greatest overlap in identified species, with 98.54%, 100%, and 91.11% consistency across thresholds. When selecting fragment combinations, “12S-Tele02” plus “COI-PS1” identified the most species under all thresholds (180, 206, and 257 species), differing only by 3, 6, and 7 species from the results of using all five fragments. In summary, this study highlights that the relationship between interspecies difference thresholds and species identification must be carefully considered in applying eDNA for Yangtze River fish diversity, to avoid false positives in OTU annotations. For species that are hard to distinguish but of high conservation value, targeted primer design can enhance monitoring efficiency. Moreover, combining eDNA technology with traditional netting can provide a more comprehensive assessment of local aquatic biodiversity.

     

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