留言板

尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

姓名
邮箱
手机号码
标题
留言内容
验证码

海南岛淡水鱼类环境DNA宏条形码参考数据库的初步构建及比较分析

陈治 蔡杏伟 张清凤 李高俊 马春来 申志新

陈治, 蔡杏伟, 张清凤, 李高俊, 马春来, 申志新. 海南岛淡水鱼类环境DNA宏条形码参考数据库的初步构建及比较分析[J]. 南方水产科学, 2022, 18(3): 1-12. doi: 10.12131/20210339
引用本文: 陈治, 蔡杏伟, 张清凤, 李高俊, 马春来, 申志新. 海南岛淡水鱼类环境DNA宏条形码参考数据库的初步构建及比较分析[J]. 南方水产科学, 2022, 18(3): 1-12. doi: 10.12131/20210339
CHEN Zhi, CAI Xingwei, ZHANG Qingfeng, LI Gaojun, MA Chunlai, SHEN Zhixin. Preliminary construction and comparative analysis of environmental DNA metabarcoding reference database of freshwater fishes in Hainan Island[J]. South China Fisheries Science, 2022, 18(3): 1-12. doi: 10.12131/20210339
Citation: CHEN Zhi, CAI Xingwei, ZHANG Qingfeng, LI Gaojun, MA Chunlai, SHEN Zhixin. Preliminary construction and comparative analysis of environmental DNA metabarcoding reference database of freshwater fishes in Hainan Island[J]. South China Fisheries Science, 2022, 18(3): 1-12. doi: 10.12131/20210339

海南岛淡水鱼类环境DNA宏条形码参考数据库的初步构建及比较分析

doi: 10.12131/20210339
基金项目: 国家自然科学基金项目 (32002389);海南省自然科学基金项目(422RC717, 320RC748);海南热带海洋学院引进人才科研启动资助项目 (RHDRC201907)
详细信息
    作者简介:

    陈治:陈 治 (1990—),男,讲师,博士,从事水生濒危动物保护研究。E-mail: change@139.com

    通讯作者:

    蔡杏伟 (1989—),男, 副研究员,博士,从事鱼类生态学研究。E-mail: caixw618@163.com

    申志新 (1964—),男,研究员,从事渔业生态学研究。E-mail: shen_266@msn.com

  • 中图分类号: S 931.2

Preliminary construction and comparative analysis of environmental DNA metabarcoding reference database of freshwater fishes in Hainan Island

  • 摘要: 为确定海南岛淡水鱼类环境DNA研究的最优参考数据库及最优目标基因,比较了自建数据库与公共数据库在COI、12S、16S 3个条形码片段上的物种覆盖度、注释准确率及种间差异阈值。结果表明:1) 实地采集鱼类72种,其中有16 (COI)、20 (12S) 和22 (16S) 种鱼类的参考序列为该研究首次提供;2) 仅有68.06% (COI)、66.67% (12S) 和69.44% (16S) 的鱼类在公共数据库比对到高相似度序列;3) 自建数据库对两个数据库共有鱼类的物种注释准确率显著高于公共数据库 (COI: 100% vs 69.64%; 12S: 96.15% vs 67.30%; 16S: 96% vs 70%);4) COI基因是判别海南岛淡水鱼类的最优目标基因,16S次之;5) 基于K2P遗传距离确定的种间差异阈值分别为0.006 9 (COI)、0.005 6 (12S) 和0.007 5 (16S),其物种判别准确率为94.96% (COI)、89.05% (12S)和92.70% (16S)。结果表明自建数据库优于公共数据库,建议使用COI、16S作为海南岛淡水鱼类环境DNA宏条形码基因。
  • 图  1  本研究中自建数据库及公共数据库的鱼类种数

    Figure  1.  Number of fish species in self-built database and public database in this study

    图  2  可注释到种的鱼类的候选物种数 (序列相似度≥99%)

    Figure  2.  Number of candidate species of fish that can be annotated at species level (with≥99% sequence similarity)

    图  3  基于152条线粒体COI序列构建的NJ系统发育树

    Figure  3.  NJ phylogenetic tree constructed based on 152 mitochondrial COI sequences

    图  5  基于150条线粒体16S序列构建的NJ系统发育树

    Figure  5.  NJ phylogenetic tree constructed based on 150 mitochondrial 16S sequences

    图  4  基于150条线粒体12S序列构建的NJ系统发育树

    Figure  4.  NJ phylogenetic tree constructed based on 150 mitochondrial 12S sequences

    表  1  公共数据库和自建数据库参考序列简介

    Table  1.   Summary of metabarcoding reference sequence in public database and self-built database

    数据来源
    Data source
    目标基因
    Target gene
    鱼类总数Total number
    of fish
    序列总数
    Total number of sequences
    标注采样地点的序列总数Total number of sequences with sampling location information标注样品采集于海南的序列总数*
    Total number of sequences collected from Hainan
    标注样品采集于海南的鱼类种数*
    Total number of fish collected from Hainan
    公共数据库
    Public database
    COI 123 2 704 181 8 3
    12S 117 648 75 2 1
    16S 115 736 59 0 0
    自建数据库
    Self-built database
    COI 72 85 85 85 72
    12S 72 85 85 85 72
    16S 72 85 85 85 72
    注:凡是没有明确标注采样地点的序列 (包括海南特有种) 一律不纳入*统计范围。Note: The sequences without sampling location information (including endemic species in Hainan) will not be included in the statistical scope of *.
    下载: 导出CSV

    表  2  可注释到种的序列在不同阈值范围内的候选物种数 ($\overline {\boldsymbol X}{\bf {\pm} } {\bf{SD}} $)

    Table  2.   Number of candidate species of sequence that can be annotated at species level within different threshold values

    序列相似度
    Sequence similarity
    候选物种数 Number of candidate species
    基于公共数据库 Based on public database基于自建数据库 Based on self-built database
    COI12S16SCOI12S16S
    100% 0~9 (1.43±1.64) 0~9 (1.01±1.51) 0~9 (1.00±1.46) 1~2 (1.03±0.18) 1~2 (1.08±.028) 1~2 (1.07±.025)
    100%>X≥99% 0~15 (1.04±1.88) 0~7 (0.53±0.98) 0~7 (0.85±1.22) 0~1 (0.13±0.34) 0~1 (0.03±0.18) 0~1 (0.03±0.18)
    99%>X≥98% 0~10 (1.07±1.74) 0~11 (0.85±1.42) 0~11 (1.03±1.67) 0~3 (0.19±0.63) 0~3 (0.13±0.37) 0~2 (0.10±0.29)
    100%≥X≥99% 0~21 (2.47±3.06) 0~16 (1.53±2.06) 0~15 (1.85±2.27) 1~3 (1.14±0.47) 1~2 (1.10±0.30) 1~2 (1.09±0.28)
    100%≥X≥98% 0~31 (3.53±4.31) 0~27 (2.38±2.99) 0~23 (2.88±3.24) 1~4 (1.31±0.98) 1~4 (1.20±0.65) 1~3 (1.16±0.45)
    下载: 导出CSV

    表  3  两种数据库共有物种的注释结果

    Table  3.   Annotation results of common fish species in two databases

    参考数据库
    Reference database
    目标基因
    Target gene
    共有物种数
    Number of shared species
    低相似度物种数
    Number of species with low sequence similarity
    不确定物种数或错误注释物种数Number of uncertain species or incorrectly annotated species正确注释物种数
    Number of correctly annotated species
    注释准确率
    Annotation accuracy/%
    公共数据库
    Public database
    COI 56 14 3 39 69.64
    12S 52 12 5 35 67.30
    16S 50 11 4 35 70
    自建数据库
    Self-built database
    COI 56 0 0 56 100
    12S 52 0 2 50 96.15
    16S 50 0 2 48 96
    注:不确定物种是注释到的多个候选物种序列完全相同 (序列相似度=100%),且皆有历史分布记录,难以排除错误物种;低相似度物种指序列相似度<98%。Note: Uncertain species refer to multiple candidate species whose sequences are identical (sequence similarity=100%) and all of them have historical distribution records in Hainan, so it is difficult to exclude the wrong species. Low similarity species refer to the species whose sequence similarity<98%.
    下载: 导出CSV

    表  4  两两序列的遗传距离 (K2P)

    Table  4.   Pairwise distance of genetic divergences (K2P) within various sequences

    物种 Species遗传距离 Pairwise distance
    COI12S16S
    南方波鱼 Rasbora steineri (A, B) 0 0 0.007 66
    海南马口鱼 Opsariichthys hainanensis、南方马口鱼 O. bidens (A) 0.008 43
    蒙古鲌 Culter mongolicus mongolicus、鳊 Parabramis pekinensis 0.006 94
    海南鲌 C. recurviceps (A, B) 0 0 0
    海南鲌 C. recurviceps (A, B)、红鳍鲌 Chanodichthys erythropterus 0.006 95 0.005 64
    红鳍鲌 C. erythropterus、海南似鱎 Toxabramis houdemeri 0.009 44
    海南拟䱗 Pseudohemiculter hainanensis、䱗 Hemiculter leucisculus 0.006 94 0.007 54
    Parabramis pekinensis、三角鲂 Megalobrama terminalis 0.008 87
    P. pekinensis、斯氏鲂 (疑似) M. skolkovii (Suspected) 0.008 87
    三角鲂 M. terminalis、斯氏鲂 (疑似) M. skolkovii (Suspected) 0
    黄尾鲴 Xenocypris davidi、银鲴 X. macrolepis 0 0
    疏斑小鲃 Puntius paucimaculatus、条纹小鲃 P. semifasciolatus 0.006 95 0
    细尾白甲鱼 Onychostoma lepturum (A, B) 0 0 0
    厚唇光唇鱼 Acrossocheilus paradoxus (A, B) 0 0 0
    间䱻 Hemibarbus medius (A, B) 0 0 0
    尖鳍鲤 Cyprinus acutidorsalis、鲤 C. carpio 0 0 0.007 54
    Hypophthalmichthys nobilis、鲢 H. molitrix 0.006 94
    美丽小条鳅 Micronemacheilus pulcher、齐氏小条鳅 M. zispi 0.006 94 0.005 74
    泥鳅 Misgurnus anguillicaudatus、大鳞副泥鳅 Paramisgurnus dabryanus 0.008 03 0 0
    越南隐鳍鲇 Pterocryptis cochinchinensis (A, B) 0.006 94 0
    中间黄颡鱼 Pelteobagrus intermedius (A, B) 0 0 0.004 46
    黑首阿胡虾虎鱼 Awaous melanocephalus (A, B) 0 0.008 04 0
    黑首阿胡虾虎鱼 A. melanocephalus (A, C) 0 0.001 01 0
    黑首阿胡虾虎鱼 A. melanocephalus (B, C) 0 0.009 05 0
    子陵吻虾虎鱼 Rhinogobius giurinus、吻虾虎鱼sp. 3 Rhinogobius sp. 3 0 0
    陵水吻虾虎鱼 R. linshuiensis (A, B) 0 0 0
    陵水吻虾虎鱼 R. linshuiensis、吻虾虎鱼sp. 2 Rhinogobius sp. 2 0.006 94 0 0
    攀鲈 Anabas testudineus (A, B) 0.006 94 0 0
    黑体塘鳢 Eleotris melanosoma (A, B) 0 0 0
    南方马口鱼 O. bidens (A, B) 0.006 94 0.006 28
    注:遗传距离在0.01以上的物种均能正确鉴定,故本表只展示遗传距离在0.01以下的物种。—. 遗传距离≥0.01;A、B、C. 种内不同个体。Note: All species with a genetic distance above 0.01 can be correctly identified, so only the results with a genetic distance below 0.01 are shown. —. Genetic distance ≥0.01; A, B, C. Intraspecific samples.
    下载: 导出CSV
  • [1] 程馨雨, 陶捐, 武瑞东, 等. 淡水鱼类功能生态学研究进展[J]. 生态学报, 2019, 39(3): 810-822.
    [2] THOMSEN P F, WILLERSLEV E. Environmental DNA: an emerging tool in conservation for monitoring past and present biodiversity[J]. Biol Conserv, 2015, 183(1): 4-18.
    [3] 陈炼, 吴琳, 刘燕, 等. 环境DNA metabarcoding及其在生态学研究中的应用[J]. 生态学报, 2016, 36(15): 4573-4582.
    [4] 姜维, 赵虎, 邓捷, 等. 环境DNA分析技术——一种水生生物调查新方法[J]. 水生态学杂志, 2016, 37(5): 1-7.
    [5] BALASINGHAM K D, WALTER R P, MANDRAK N E, et al. Environmental DNA detection of rare and invasive fish species in two Great Lakes tributaries[J]. Mol Ecol, 2018, 27(1): 112-127. doi: 10.1111/mec.14395
    [6] THOMSEN P F, KIELGAST J, IVERSEN L L, et al. Monitoring endangered freshwater biodiversity using environmental DNA[J]. Mol Ecol, 2012, 21(11): 2565-2573. doi: 10.1111/j.1365-294X.2011.05418.x
    [7] SCHENEKAR T, SCHLETTERER M, LECAUDEY L A, et al. Reference databases, primer choice, and assay sensitivity for environmental metabarcoding: lessons learnt from a re-evaluation of an eDNA fish assessment in the Volga headwaters[J]. River Res Appl, 2020, 36(7): 1004-1013. doi: 10.1002/rra.3610
    [8] VALENTINI A, TABERLET P, MIAUD C, et al. Next-generation monitoring of aquatic biodiversity using environmental DNA metabarcoding[J]. Mol Ecol, 2016, 25(4): 929-942. doi: 10.1111/mec.13428
    [9] 李晗溪, 黄雪娜, 李世国, 等. 基于环境DNA-宏条形码技术的水生生态系统入侵生物的早期监测与预警[J]. 生物多样性, 2019, 27(5): 491-504.
    [10] JI Y, ASHTON L, PEDLEY S M, et al. Reliable, verifiable and efficient monitoring of biodiversity via metabarcoding[J]. Ecol Lett, 2013, 16(10): 1245-1257. doi: 10.1111/ele.12162
    [11] SATO Y, MIYA M, FUKUNAGA T, et al. MitoFish and MiFish pipeline: a mitochondrial genome database of fish with an analysis pipeline for environmental DNA metabarcoding[J]. Mol Biol Evol, 2018, 35(6): 1553-1555. doi: 10.1093/molbev/msy074
    [12] 徐念, 常剑波. 长江中下游干流环境DNA样品鱼类物种检测的初步研究[J]. 水生态学杂志, 2016, 27(5): 49-55.
    [13] LI Y, EVANS N T, RENSHAW M A, et al. Estimating fish alpha-and beta-diversity along a small stream with environmental DNA metabarcoding[J]. MBMG, 2018, 2(1): e24262.
    [14] SHAW J L A, CLARKE L J, WEDDERBURN S D, et al. Comparison of environmental DNA metabarcoding and conventional fish survey methods in a river system[J]. Biol Conserv, 2016, 197(4): 131-138.
    [15] SHU L, LUDWIG A, PENG Z G. Environmental DNA metabarcoding primers for freshwater fish detection and quantification: in silico and in tanks[J]. Ecol Evol, 2021, 11(3): 8281-8294.
    [16] ZHANG S, ZHAO J, YAO M. A comprehensive and comparative evaluation of primers for metabarcoding eDNA from fish[J]. Methods Ecol Evol, 2020, 11(12): 1609-1625. doi: 10.1111/2041-210X.13485
    [17] MIYA M, SATO Y, FUKUNAGA T, et al. MiFish, a set of universal PCR primers for metabarcoding environmental DNA from fishes: detection of more than 230 subtropical marine species[J]. Roy Soc Open Sci, 2015, 2(7): 150088. doi: 10.1098/rsos.150088
    [18] MILAN D T, MENDES I S, DAMASCENO J S, et al. New 12S metabarcoding primers for enhanced neotropical freshwater fish biodiversity assessment[J]. Sci Rep-UK, 2020, 10(1): 17966. doi: 10.1038/s41598-020-74902-3
    [19] 邢巧, 史建康, 林彰文, 等. 海南省生物多样性保护战略与行动计划[M]. 北京: 科学出版社, 2015: 7-8.
    [20] 申志新, 李高俊, 蔡杏伟, 等. 海南省淡水野生鱼类多样性演变及保护建议[J]. 中国水产, 2018(11): 56-60.
    [21] 李高俊, 顾党恩, 蔡杏伟, 等. 海南岛“两江一河” 淡水土著鱼类的种类组成与分布现状[J]. 淡水渔业, 2020, 50(6): 15-22. doi: 10.3969/j.issn.1000-6907.2020.06.003
    [22] 中国水产科学研究院珠江水产研究所, 上海水产大学, 中国水产科学研究院东海水产研究所, 等. 海南岛淡水及河口鱼类志 [M]. 广州: 广东科技出版社, 1986: 1-372.
    [23] 中国水产科学研究院珠江水产研究所, 华南师范大学, 暨南大学, 等. 广东淡水鱼类志 [M]. 广州: 广东科技出版社, 1991: 1-561.
    [24] VENCES M, LYRA M L, PERL R G B, et al. Freshwater vertebrate metabarcoding on Illumina platforms using double-indexed primers of the mitochondrial 16S rRNA gene[J]. Conserv Genet Resour, 2016, 8(3): 323-327. doi: 10.1007/s12686-016-0550-y
    [25] 吴娜. 南海鱼类凭证标本采集及DNA条形码库构建与应用 [D]. 上海: 上海海洋大学, 2017: 13-16.
    [26] 梁日深, 唐丰寿, 何浩斌, 等. 西太平洋沿海石斑鱼属鱼类DNA条形码及分子系统进化研究[J]. 水生生物学报, 2021, 45(4): 851-860. doi: 10.7541/2021.2020.080
    [27] 郜星晨, 姜伟. 三峡库区常见鱼类DNA条形码本地BLAST数据库的构建和应用 [J]. 基因组学与应用生物学, 2021, 40(5/6): 1952-1960.
    [28] JERDE C L, MAHON A R, CAMPBELL T, et al. Are genetic reference libraries sufficient for environmental DNA metabarcoding of Mekong River basin fish?[J]. Water-SUI, 2021, 13(13): 01767.
    [29] LIM N K M, TAY Y C, SRIVATHSAN A, et al. Next-generation freshwater bioassessment: eDNA metabarcoding with a conserved metazoan primer reveals species-rich and reservoir-specific communities[J]. Roy Soc Open Sci, 2016, 3(11): 160635. doi: 10.1098/rsos.160635
    [30] GILLET B, COTTET M, DESTANQUE T, et al. Direct fishing and eDNA metabarcoding for biomonitoring during a 3-year survey significantly improves number of fish detected around a South East Asian reservoir[J]. PLOS ONE, 2018, 13(12): e0208592. doi: 10.1371/journal.pone.0208592
    [31] ALAM M J, KIM N K, ANDRIYONO S, et al. Assessment of fish biodiversity in four Korean rivers using environmental DNA metabarcoding[J]. PeerJ, 2020, 8(2): e9508.
    [32] MIYA M, GOTOH R O, SADO T. MiFish metabarcoding: a high-throughput approach for simultaneous detection of multiple fish species from environmental DNA and other samples[J]. Fish Sci, 2020, 86(6): 939-970. doi: 10.1007/s12562-020-01461-x
    [33] HEBERT P D N, CYWINSKA A, BALL S L, et al. Biological identifications through DNA barcodes[J]. Proc Royal Soc London B, 2003, 270(1512): 313-321. doi: 10.1098/rspb.2002.2218
    [34] EVANS N T, LAMBERTI G A. Freshwater fisheries assessment using environmental DNA: a primer on the method, its potential, and shortcomings as a conservation tool[J]. Fish Res, 2018, 197(4): 60-66.
    [35] MACHER J N, VIVANCOS A, PIGGOTT J J, et al. Comparison of environmental DNA and bulk-sample metabarcoding using highly degenerate cytochrome c oxidase I primers[J]. Mol Ecol Resour, 2018, 18(6): 1456-1468. doi: 10.1111/1755-0998.12940
    [36] GANTNER S, ANDERSSON A F, LAURA A S, et al. Novel primers for 16S rRNA-based archaeal community analyses in environmental samples[J]. J Microbiol Meth, 2011, 84(1): 12-18. doi: 10.1016/j.mimet.2010.10.001
    [37] MATHESON H. Review of methods of selective primer-dimer reduction in vitro[J]. Meth Biomol Res, 2009, 31(7): 476-488.
    [38] IVANOVA N V, ZEMLAK T S, HANNER R H, et al. Universal primer cocktails for fish DNA barcoding[J]. Mol Ecol Notes, 2007, 7(4): 544-548. doi: 10.1111/j.1471-8286.2007.01748.x
    [39] COLLINS R A, BAKKER J, WANGENSTEEN O S, et al. Non-specific amplification compromises environmental DNA metabarcoding with COI[J]. Methods Ecol Evol, 2019, 10(11): 1985-2001. doi: 10.1111/2041-210X.13276
    [40] MENNING D, SIMMONS T, TALBOT S. Using redundant primer sets to detect multiple native Alaskan fish species from environmental DNA[J]. Conserv Genet Resour, 2020, 12(1): 109-123. doi: 10.1007/s12686-018-1071-7
    [41] JENNINGS W B, RUSCHI P A, FERRARO G, et al. Barcoding the Neotropical freshwater fish fauna using a new pair of universal COI primers with a discussion of primer dimers and M13 primer tails[J]. Genome, 2019, 62(2): 77-83. doi: 10.1139/gen-2018-0145
    [42] SULTANA S, ALI M E, HOSSAIN M A M, et al. Universal mini COI barcode for the identification of fish species in processed products[J]. Food Res Int, 2018, 105: 19-28.
    [43] YAMAMOTO S, MASUDA R, SATO Y, et al. Environmental DNA metabarcoding reveals local fish communities in a species-rich coastal sea[J]. Sci Rep-UK, 2017, 7(1): 40368. doi: 10.1038/srep40368
    [44] BYLEMANS J, GLEESON D M, HARDY C M, et al. Toward an ecoregion scale evaluation of eDNA metabarcoding primers: a case study for the freshwater fish biodiversity of the Murray-Darling Basin (Australia)[J]. Ecol Evol, 2018, 8(17): 8697-8712. doi: 10.1002/ece3.4387
    [45] 陈治. 浙江近海鱼类多样性eDNA调查方法的建立与应用 [D]. 青岛: 中国海洋大学, 2019: 149-152.
  • 20210339附录A.pdf
  • 加载中
图(5) / 表(4)
计量
  • 文章访问数:  322
  • HTML全文浏览量:  83
  • PDF下载量:  68
  • 被引次数: 0
出版历程
  • 收稿日期:  2021-11-10
  • 修回日期:  2021-12-26
  • 录用日期:  2022-02-05
  • 网络出版日期:  2022-02-21
  • 刊出日期:  2022-06-02

目录

    /

    返回文章
    返回