Preliminary construction and comparative analysis of environmental DNA metabarcoding reference database of freshwater fishes in Hainan Island
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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。Abstract: In order to determine the optimal reference database and target genes for environmental DNA study of freshwater fishes in Hainan Island, we compared the species coverage, annotation accuracy and threshold values of interspecific difference of COI, 12S and 16S between the self-built database and the public database. The results show that: 1) Seventy-two fish species were collected, among which 16 (COI), 20 (12S) and 22 (16S) species' reference sequences were provided for the first time. 2) Only 68.06% (COI), 66.67% (12S) and 69.44% (16S) of the fish had high similarity sequence in the public database. 3) The annotation accuracy based on the self-built database was significantly higher than that on the public database (COI: 100% vs 69.64%; 12S: 96.15% vs 67.30%; 16S: 96% vs 70%). 4) COI gene was the best target gene for identifying freshwater fishes in Hainan Island, followed by 16S gene. 5) The threshold values of interspecific difference based on K2P genetic distance were 0.006 9 (COI), 0.005 6 (12S) and 0.007 5 (16S), respectively, and the accuracy rates were 94.96% (COI), 89.05% (12S) and 92.70% (16S), respectively. This study reveals that the sequence annotation accuracy of the self-built database is significantly higher than that of the public database, and it is suggested that COI and 16S should be used as the environmental DNA metabarcoding genes of freshwater fishes in Hainan Island.
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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 databaseCOI 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 databaseCOI 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 *. 
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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 COI 12S 16S COI 12S 16S 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)
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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 databaseCOI 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 databaseCOI 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%.
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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 COI 12S 16S 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 鳊 Parabramis pekinensis、三角鲂 Megalobrama terminalis 0.008 87 — — 鳊 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 鳙 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.
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[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. -
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