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. 2018 Jun 13;8(14):6932–6951. doi: 10.1002/ece3.4210

DNA barcoding of economically important freshwater fish species from north‐central Nigeria uncovers cryptic diversity

Oluyinka A Iyiola 1,†, Lotanna M Nneji 2,3,4,†, Moshood K Mustapha 1, Chioma G Nzeh 1, Segun O Oladipo 5, Ifeanyi C Nneji 6, Agboola O Okeyoyin 7, Christopher D Nwani 8, Obih A Ugwumba 9, Adiaha A A Ugwumba 9, Emmanuel O Faturoti 10, Yun‐yu Wang 2, Jing Chen 11, Wen‐Zhi Wang 2,3,11,✉, Adeniyi C Adeola 2,3,✉
PMCID: PMC6065348  PMID: 30073057

Abstract

This study examines the utility of morphology and DNA barcoding in species identification of freshwater fishes from north‐central Nigeria. We compared molecular data (mitochondrial cytochrome c oxidase subunit I (COI) sequences) of 136 de novo samples from 53 morphologically identified species alongside others in GenBank and BOLD databases. Using DNA sequence similarity‐based (≥97% cutoff) identification technique, 50 (94.30%) and 24 (45.30%) species were identified to species level using GenBank and BOLD databases, respectively. Furthermore, we identified cases of taxonomic problems in 26 (49.00%) morphologically identified species. There were also four (7.10%) cases of mismatch in DNA barcoding in which our query sequence in GenBank and BOLD showed a sequence match with different species names. Using DNA barcode reference data, we also identified four unknown fish samples collected from fishermen to species level. Our Neighbor‐joining (NJ) tree analysis recovers several intraspecific species clusters with strong bootstrap support (≥95%). Analysis uncovers two well‐supported lineages within Schilbe intermedius. The Bayesian phylogenetic analyses of Nigerian S. intermedius with others from GenBank recover four lineages. Evidence of genetic structuring is consistent with geographic regions of sub‐Saharan Africa. Thus, cryptic lineage diversity may illustrate species’ adaptive responses to local environmental conditions. Finally, our study underscores the importance of incorporating morphology and DNA barcoding in species identification. Although developing a complete DNA barcode reference library for Nigerian ichthyofauna will facilitate species identification and diversity studies, taxonomic revisions of DNA sequences submitted in databases alongside voucher specimens are necessary for a reliable taxonomic and diversity inventory.

Keywords: Biodiversity, conservation policy, geographic variation, integrative taxonomy, mitochondrial DNA, population divergence

1. INTRODUCTION

Nigerian freshwater bodies include reservoirs, lakes, rivers, ponds, and perennial swamps which constitute about 12% of Nigeria’s total surface area (Ita, Sado, Balogun, Pandogori, & Ibitoye, 1985). They are richly endowed with fishery resources of more than 268 species of freshwater fishes (Froese & Pauly, 2017; Olaosebikan & Bankole, 2005; Olaosebikan & Raji, 1998). These serve enormous socio‐economic importance as sources of animal protein, income etc. However, over the years, reports have shown decline in the number of fish caught from most Nigerian inland waters (Oguntade, Oketoki, Ukenye, Usman, & Adeleke, 2014). This could be attributed to inadequate management of fisheries, climate change, pollution, and degradation of water bodies (Odo, Nwani, & Eyo, 2009). The impact of environmental pollution and other human activities on fish diversity cannot be overestimated. Hence, improved management plans and conservation approaches will aid in preventing loss of Nigerian fish diversity.

Accurate identification of species is a pivotal component in conservation efforts. The use of traditional methods (morphological characters) in species identification is common in Nigeria. In fact, about 48% of Nigerian freshwater fish species have been characterized using this method (Nwani et al., 2011). Although the use of morphological approach can be incorrect (Ward, Hanner, & Hebert, 2009), its accuracy has not yet been tested for Nigerian fishes. The challenges of the use of morphology lie in the discrimination of closely related organisms (Rasmussen, Morrissey, & Hebert, 2009). This has paved way for the development of improved molecular approaches for identification of fish species (Abdullah & Rehbein, 2017; Nazarov et al., 2012; Nwani, Eyo, & Udoh, 2016; Ratnasingham & Hebert, 2007).

Different DNA‐based methods, particularly DNA barcoding, have been evaluated for identification of fish species in Africa including Nigeria (Nwakanna, Ude, & Unachukwu, 2015; Nwani et al., 2011). DNA barcoding is a species identification tool, the information from which may be used as a conservation tool or potentially as part of the evidence to delimit species (Crawford, Alonso, Jaramillo, Sucre, & Ibáñez, 2011; Crawford et al., 2012; Gehring, Ratsoavina, & Vences, 2010; Nazarov et al., 2012; Vargas, Araújo, & Santos, 2009). It involves the use of 5′ region of the mitochondrial cytochrome c oxidase subunit I (COI) as a target gene (Hebert, Cywinska, Ball, & deWaard, 2003). DNA barcoding has been proven effective in facilitating rapid species identification when compared with morphological taxonomic approach (Hebert et al., 2003). For instances, in several studies, more than 98% of the analyzed species were clearly identified using DNA barcoding approach (Costa et al., 2012; deWaard, Hebert, & Humble, 2011; Liu & Zhang, 2018; Steinke, Zemlak, & Hebert, 2009; Valdez‐Moreno, Ivanova, Elías‐Gutiérrez, Contreras‐Balderas, & Hebert, 2009; Ward, Zemlak, Innes, Last, & Hebert, 2005; Zhang & Hanner, 2011). Studies have also documented the usefulness of DNA barcoding approach in unraveling cryptic lineages within many species of fish (Benzaquem, Oliveira, da Silva Batista, Zuanon, & Porto, 2015; Mat Jaafar, Taylor, Mohd Nor, de Bruyn, & Carvalho, 2012; Mohammed, Manal, Rasha, & Magdy, 2016). Thus, DNA barcoding could be an effective genetic tool that would assist Nigerian conservation managers in identifying species accurately and uncover hidden diversity.

To date, there are no studies on the DNA barcoding of freshwater fishes in north‐central region of Nigeria. Herein, we explored the use of DNA barcoding as reliable molecular tool for identification of fish species obtained from the north‐central Nigeria. We evaluated and compared GenBank and BOLD databases for use in species identification. Furthermore, we compared the taxonomic reliability of morphological method against DNA barcodes. Finally, we examined the usefulness of DNA barcode reference data in uncovering cryptic lineage diversity in fish species from north‐central Nigeria.

2. MATERIALS AND METHODS

2.1. Sample collection

We collected one hundred thirty‐six (136) freshwater fish samples belonging to 53 species between 2016 and 2017 (Table 1). Our sampling covered nine (9) inland water bodies (Oyun and Asa Reservoirs, Rivers Asa, Moro, Awon, Apodu‐Malete, Asa‐Laduba and Niger; and, Jebba Hydroelectric Power Dam Basin) in north‐central Nigeria. Specimens were caught using gill and cast nets. Fish specimens were identified from monographs, description checklist and standard taxonomic guides. Species identification and nomenclature followed fish identification guide of Olaosebikan and Raji (1998), Idodo‐Umeh (2003) and Fish Base databases (Froese & Pauly, 2017). Additional species identification and verification were sought from two trained taxonomists at the Department of Zoology, University of Ilorin, Nigeria. After each specimen was identified, tail fin and white muscle tissue were taken and preserved in 95% ethanol. The voucher specimens were fixed with 4% formalin and kept in 70% ethanol. Representative voucher specimens were imaged by digital scanning and later deposited in Museums of Department of Bioscience and Biotechnology, Kwara State University, Malete, Nigeria and the rest in the Department of Zoology, University of Ilorin, Nigeria. Furthermore, to verify the reliability of DNA barcode reference data in identification of unknown fish specimens, four muscle tissue samples of unknown fish species were collected from fishermen in River Niger, Niger State, Nigeria (Table 1). Morphological identification using fish guide could not be achieved due to unavailability of whole fish specimens. We preserved tissues in 95% ethanol and subsequently stored under −80°C.

Table 1.

List of species including voucher’s specimen number, species name, locality information and GenBank accession number

S/No Specimen voucher Organism Locality GenBank accession no.
1 YLMC112 Alestes baremoze Nigeria: Niger State, Jebba HEP Upstream MG824552
2 YLMC145 A. baremoze Nigeria: Kwara State, Jebba HEP Downstream MG824553
3 YLMC165 Auchenoglanis biscutatus Nigeria: Niger State, Jebba HEP Upstream MG824554
4 YLMC153 Auchenoglanis occidentalis Nigeria: Niger State, Jebba HEP Upstream MG824555
5 YLMC025 A. occidentalis Nigeria: Kwara State, Moro River MG824556
6 YLMC042 A. occidentalis Nigeria: Kwara State, Moro River MG824557
7 YLMC281 A. occidentalis Nigeria: Kwara State, Moro River –
8 YLMC274 Bagrus bajad Nigeria: Kwara State, Jebba HEP Downstream MG824559
9 YLMC061 B. bajad Nigeria: Kwara State, Jebba HEP Downstream MG824560
10 YLMC210 Bagrus docmac Nigeria: Niger State, Jebba HEP Upstream MG824561
11 YLMC051 B. docmac Nigeria: Niger State, Jebba HEP Upstream MG824562
12 YLMC149 Brienomyrus niger Nigeria: Niger State, Jebba HEP Upstream MG824563
13 YLMC022 B. niger Nigeria: Kwara State, Moro River MG824564
14 YLMC233 Brycinus nurse Nigeria: Kwara State, Jebba HEP Downstream MG824565
15 YLMC097 B. nurse Nigeria: Kwara State, Jebba HEP Downstream MG824566
16 YLMC312 Brycinus sp. Nigeria: Niger State, Jebba HEP Upstream MG824567
17 YLMC213 Chrysichthys cf auratus Nigeria: Niger State, Jebba HEP Upstream MG824568
18 YLMC062 C. cf auratus Nigeria: Niger State, Jebba HEP Upstream MG824569
19 YLMC295 Chrysichthys nigrodigitatus Nigeria: Niger State, Jebba HEP Upstream MG824570
20 YLMC315 C. nigrodigitatus Nigeria: Niger State, Jebba HEP Upstream MG824571
21 YLMC002 Chrysichthys sp. Nigeria: Kwara State, Oyun Reservoir MG824572
22 YLMC006 Chrysichthys sp. Nigeria: Kwara State, Oyun Reservoir MG824573
23 YLMC461 Chrysichthys sp. Nigeria: Niger State, Jebba HEP Upstream MG824574
24 YLMC081 C. citharus Nigeria: Niger State, Jebba HEP Upstream MG824575
25 YLMC076 C. citharus Nigeria: Niger State, Jebba HEP Upstream MG824576
26 YLMC079 C. citharus Nigeria: Niger State, Jebba HEP Upstream MG824577
27 YLMC092 C. citharus Nigeria: Niger State, Jebba HEP Upstream MG824578
28 YLMC463 Clarias gabonensis Nigeria: Niger State, Jebba HEP Upstream MG824579
29 YLMC209 C. gariepinus Nigeria: Niger State, Jebba HEP Upstream MG824580
30 YLMC240 C. gariepinus Nigeria: Kwara State, Apodu‐Malete MG824581
31 YLMC273 C. gariepinus Nigeria: Kwara State, Apodu‐Malete MG824582
32 YLMC084 C. gariepinus Nigeria: Niger State, Jebba HEP Upstream MG824583
33 YLMC115 C. laticeps Nigeria: Niger State, Jebba HEP Upstream MG824584
34 YLMC154 C. laticeps Nigeria: Niger State, Jebba HEP Upstream MG824585
35 YLMC197 C. laticeps Nigeria: Niger State, Jebba HEP Upstream MG824586
36 YLMC300 Distichodius engycephalus Nigeria: Kwara State, Jebba HEP Downstream MG824587
37 YLMC134 D. rostratus Nigeria: Niger State, Jebba HEP Upstream MG824588
38 YLMC301 D. rostratus Nigeria: Niger State, Jebba HEP Upstream MG824589
39 YLMC098 D. rostratus Nigeria: Niger State, Jebba HEP Upstream MG824590
40 YLMC318 Gymnarchus niloticus Nigeria: Niger State, Jebba HEP Upstream MG824591
41 YLMC333 G. niloticus Nigeria: Niger State, Jebba HEP Upstream MG824592
42 YLMC013 Hemichromis bimaculatus Nigeria: Kwara State, Asa River MG824593
43 YLMC021 H. bimaculatus Nigeria: Kwara State, Asa River MG824594
44 YLMC010 Heterotis niloticus Nigeria: Kwara State, Asa River MG824595
45 YLMC284 H. niloticus Nigeria: Kwara State, Asa River –
46 YLMC180 Hydrocynus vittatus Nigeria: Niger State, Jebba HEP Upstream MG824597
47 YLMC083 H. vittatus Nigeria: Niger State, Jebba HEP Upstream MG824598
48 YLMC222 Hyperopisus bebe Nigeria: Niger State, Jebba HEP Upstream MG824599
49 YLMC033 H. bebe Nigeria: Kwara State, Awon River MG824600
50 YLMC090 Labeo coubie Nigeria: Kwara State, Jebba HEP Downstream MG824601
51 YLMC121 L.coubie Nigeria: Niger State, Jebba HEP Upstream MG824602
52 YLMC127 L.coubie Nigeria: Niger State, Jebba HEP Upstream MG824603
53 YLMC031 L. parvus Nigeria: Kwara State, Awon River MG824604
54 YLMC032 L. parvus Nigeria: Kwara State, Awon River MG824605
55 YLMC100 L. senegalensis Nigeria: Kwara State, Jebba HEP Downstream MG824606
56 YLMC035 L. senegalensis Nigeria: Niger State, River Niger MG824607
57 YLMC054 L. senegalensis Nigeria: Kwara State, Jebba HEP Downstream MG824608
58 YLMC138 L. niloticus Nigeria: Niger State, Jebba HEP Upstream MG824609
59 YLMC193 L. niloticus Nigeria: Niger State, Jebba HEP Upstream MG824610
60 YLMC082 L. niloticus Nigeria: Niger State, Jebba HEP Upstream MG824611
61 YLMC244 Malapterurus sp. Nigeria: Kwara State, Jebba HEP Downstream MG824612
62 YLMC225 Marcusenius senegalensis Nigeria: Kwara State, Jebba HEP Downstream MG824613
63 YLMC335 M. senegalensis Nigeria: Kwara State, Jebba HEP Downstream MG824614
64 YLMC454 M. senegalensis Nigeria: Kwara State, Jebba HEP Downstream MG824615
65 YLMC455 M. senegalensis Nigeria: Kwara State, Jebba HEP Downstream MG824616
66 YLMC053 M. senegalensis Nigeria: Kwara State, Jebba HEP Downstream MG824617
67 YLMC036 Mormyrops anguilloides Nigeria: Niger State, River Niger MG824618
68 YLMC024 M. anguilloides Nigeria: Kwara State, Moro River MG824619
69 YLMC269 M. anguilloides Nigeria: Niger State, Jebba HEP Upstream MG824620
70 YLMC289 M. anguilloides Nigeria: Niger State, Jebba HEP Upstream –
71 YLMC046 Mormyrus hasselquistii Nigeria: Niger State, River Niger MG824622
72 YLMC381 Mormyrus macrophthalmus Nigeria: Kwara State, Jebba HEP Downstream MG824623
73 YLMC091 M. macrophthalmus Nigeria: Kwara State, Jebba HEP Downstream MG824624
74 YLMC039 Mormyrus tapirus Nigeria: Niger State, River Niger MG824625
75 YLMC217 M. tapirus Nigeria: Kwara State, Jebba HEP Downstream MG824626
76 YLMC172 Oreochromis aureus Nigeria: Kwara State, Jebba HEP Downstream MG824627
77 YLMC206 O. aureus Nigeria: Kwara State, Jebba HEP Downstream MG824628
78 YLMC218 O. aureus Nigeria: Kwara State, Jebba HEP Downstream MG824629
79 YLMC008 Oreochromis sp. Nigeria: Kwara State, Asa River MG824630
80 YLMC126 Oreochromis sp. Nigeria: Kwara State, Jebba HEP Downstream MG824631
81 YLMC096 Oreochromis sp. Nigeria: Kwara State, Jebba HEP Downstream MG824632
82 YLMC004 Parachanna insignis Nigeria: Kwara State, Oyun Reservoir MG824633
83 YLMC453 P. insignis Nigeria: Kwara State, Kwara State, Asa‐Laduba MG824634
84 YLMC005 Parachanna obscura Nigeria: Kwara State, Oyun Reservoir MG824635
85 YLMC045 P. obscura Nigeria: Kwara State, Kwara State, Asa‐Laduba MG824636
86 YLMC317 Protopterus sp. Nigeria: Kwara State, Jebba HEP Downstream MG824637
87 YLMC001 Sarotherodon galilaeus Nigeria: Kwara State, Oyun Reservoir MG824638
88 YLMC446 S. galilaeus Nigeria: Kwara State, Apodu‐Malete MG824639
89 YLMC007 Schilbe intermedius Nigeria: Kwara State, Oyun Reservoir MG824640
90 YLMC009* S. intermedius Nigeria: Kwara State, Asa reservoir MG824641
91 YLMC016* S. intermedius Nigeria: Kwara State, Asa reservoir MG824642
92 YLMC017* S. intermedius Nigeria: Kwara State, Asa reservoir MG824643
93 YLMC271* S. intermedius Nigeria: Kwara State, Jebba HEP Downstream MG824644
94 YLMC285* S. intermedius Nigeria: Niger State, Jebba HEP Upstream MG824645
95 YLMC034* S. intermedius Nigeria: Kwara State, Kwara State, Awon River MG824646
96 YLMC450* S. intermedius Nigeria: Kwara State, Kwara State, Asa‐Laduba MG824647
97 YLMC451* S. intermedius Nigeria: Kwara State, Kwara State, Asa‐Laduba MG824648
98 YLMC277* S. intermedius Nigeria: Kwara State, Kwara State, Asa‐Laduba –
99 YLMC139* Schilbe mystus Nigeria: Kwara State, Jebba HEP Downstream MG824650
100 YLMC216* S. mystus Nigeria: Kwara State, Jebba HEP Downstream MG824651
101 YLMC248* Schilbe sp. Nigeria: Kwara State, Jebba HEP Downstream MG824652
102 YLMC123 Synodontis aff. bastiani Nigeria: Kwara State, Jebba HEP Downstream MG824653
103 YLMC063 S. aff. bastiani Nigeria: Kwara State, Jebba HEP Downstream MG824654
104 YLMC152 S. aff. bastiani Nigeria: Kwara State, Jebba HEP Downstream MG824655
105 YLMC299 S. aff. bastiani Nigeria: Kwara State, Jebba HEP Downstream MG824656
106 YLMC099 S. aff. bastiani Nigeria: Kwara State, Jebba HEP Downstream MG824657
107 YLMC029 Synodontis aff. haugi Nigeria: Kwara State, Awon River MG824658
108 YLMC030 S. aff. haugi Nigeria: Kwara State, Awon River MG824659
109 YLMC125 Synodontis batesonda Nigeria: Kwara State, Jebba HEP Downstream MG824660
110 YLMC103 Synodontis clarias Nigeria: Kwara State, Jebba HEP Downstream MG824661
111 YLMC293 S. clarias Nigeria: Kwara State, Jebba HEP Downstream MG824662
112 YLMC040 S. clarias Nigeria: Niger State, River Niger MG824663
113 YLMC041 S. clarias Nigeria: Niger State, River Niger MG824664
114 YLMC106 Synodontis membranacea Nigeria: Kwara State, Jebba HEP Downstream MG824665
115 YLMC247 S. membranacea Nigeria: Kwara State, Jebba HEP Downstream MG824666
116 YLMC064 S. membranacea Nigeria: Kwara State, Jebba HEP Downstream MG824667
117 YLMC184 Synodontis nigrita Nigeria: Niger State, Jebba HEP Upstream MG824668
118 YLMC292 S. nigrita Nigeria: Niger State, Jebba HEP Upstream MG824669
119 YLMC108 Synodontis obesus Nigeria: Kwara State, Jebba HEP Downstream MG824670
120 YLMC069 S. obesus Nigeria: Kwara State, Jebba HEP Downstream MG824671
121 YLMC306 Synodontis ocellifer Nigeria: Kwara State, Jebba HEP Downstream MG824672
122 YLMC205 Synodontis sp. Nigeria: Kwara State, Jebba HEP Downstream MG824673
123 YLMC014 Synodontis violacea Nigeria: Kwara State, Asa river MG824674
124 YLMC027 S. violacea Nigeria: Kwara State, Asa river MG824675
125 YLMC028 S. violacea Nigeria: Kwara State, Asa river MG824676
126 YLMC437 S. violacea Nigeria: Niger State, Jebba HEP Upstream MG824677
127 YLMC057 S. violacea Nigeria: Niger State, Jebba HEP Upstream MG824678
128 YLMC161 Tetraodon lineatus Nigeria: Niger State, Jebba HEP Upstream MG824679
129 YLMC268 T. lineatus Nigeria: Kwara State, Jebba HEP Downstream MG824680
130 YLMC070 Tetraodon lineatus Nigeria: Niger State, Jebba HEP Upstream MG824681
131 YLMC011 Tilapia zillii Nigeria: Kwara State, Asa reservoir MG824682
132 YLMC020 T. zillii Nigeria: Kwara State, Asa reservoir MG824683
133 YLMC263 T. zillii Nigeria: Kwara State, Jebba HEP Downstream MG824684
134 YLMC068 T. zillii Nigeria: Kwara State, Jebba HEP Downstream MG824685
135 YLMC272 T. zillii Nigeria: Kwara State, Jebba HEP Downstream –
136 YLMC354 T. zillii Nigeria: Kwara State, Jebba HEP Downstream –
Sample 1 YLMC050a A. occidentalis Collected from a fisherman beside River Niger, Nigeria MG824558
Sample 2 YLMC047a H. niloticus Collected from a fisherman beside River Niger, Nigeria MG824596
Sample 3 YLMC048a M. anguilloides Collected from a fisherman beside River Niger, Nigeria MG824621
Sample 4 YLMC049a S. intermedius Collected from a fisherman beside River Niger, Nigeria MG824649
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HEP: hydroelectric plant; −: samples for which PCR amplification failed.

Vouchers with asterisks represent samples deposited in the Museums of Department of Bioscience and Biotechnology, Kwara State University, Malete, Nigeria.

a

Unknown tissue samples from collected from a fisherman River Niger, Nigeria.

2.2. DNA extraction, polymerase chain reaction (PCR), amplification and sequencing

We used proteinase K to digest the ethanol‐preserved tissues and followed the standard phenol‐chloroform extraction procedure to extract the total genomic DNA (Sambrook & Russell, 2001). The concentration of the extracted DNA estimated using a UV spectrophotometer ranged from 91.2 to 6905.8 ng/μl. For the preparation of genomic working DNA, we diluted the DNA extracts with sterile water to obtain genomic working DNA with concentration ranging from 30.0 to 80.0 ng/μl. After, we amplified the mitochondrial DNA Cytochrome c Oxidase I (COI) gene of the newly acquired specimens in a volume reaction of 25 μl that contained 1.5 μl of genomic working DNA, 18.5 μl of PCR water, 2.5 μl of Taq polymerase buffer, 2 μl of dNTP, 1 μl of each of the forward and reverse primers (10 pm/μl) and 0.30 μl of rTaq polymerase. The primers used for the amplification were designed by Ward et al. (2005): FishF1 – 5′TCAACCAACCACAAAGACATTGGCAC3′ and FishR1‐5′TAGACTTCTGGGTGGCCAAAGAATCA3′. The PCR cycle profiles were as follow: 5 min initial denaturation at 94°C, followed by 35 cycles of 1 min at 94°C, annealing for 45 s at 55°C, extension for 1 min at 72°C; final extension for 10 min at 72°C. Purified PCR products were directly sequenced in both forward and reverse directions with an automated DNA sequencer (ABI 3730) following manufacturer’s instruction.

2.3. Sequence assembly and data analyses

The nucleotide sequences were viewed and confirmed by eye using SeqManTMII (DNASTAR Lasergene 7). They were aligned in MEGA 7.0 using ClustalW (Kumar, Stecher, & Tamura, 2016) with default parameters. The aligned sequences were translated into amino acids to check for premature stop codons and to confirm that the open reading frame was maintained in the protein‐coding loci. To confirm the identity of the amplified sequences, we conducted BLAST searches by inputting the FASTA sequences in the nucleotide collection database (under option “other”) for each specimen using the Megablast search for highly similar sequences on GenBank (https://blast.ncbi.nlm.nih.gov/Blast.cgi). Additionally, FASTA sequences of each of COI sequences were inputted into the BOLD Identification Request tool (http://www.boldsystems.org/index.php/IDS_OpenIdEngine). Sequences were submitted for species level identification under option “Species Level Barcode Record.” Following Hebert et al. (2003), a similarity cutoff of ≥97% was used for species level identification for sequences submitted to both GenBank and BOLD databases. The submitted sequence was matched to a species with the highest similarity score. We further compared species names assigned using morphology, GenBank and BOLD databases. Using BOLD database, we estimated the Barcode Index Number (BIN), average and maximum intraspecific distance, average genetic distance to the nearest neighbor and the nearest neighbor member for each species.

We used MEGA v. 7.0 to create a neighbor‐joining (NJ) tree based on the Kimura 2 parameter distance (K2P) (Kimura, 1980) and estimated the intergeneric, inter‐ and intraspecific sequence divergences. For the NJ tree, we considered bootstrap values of 95% and above as strongly supported. Following Decru, Van Ginneken, Verheyen, and Snoeks (2016), identification is considered successful if the sequence and the match are conspecific and failed if they are allospecific.

Upon discovery of deeply divergent lineages within species, further genetic analysis was carried out to investigate possibility of cryptic lineage diversity. To infer this, we downloaded additional related sequences of such species from the GenBank (Table S1). The Bayesian Inference (BI) analysis was rooted with a closely related species as out‐group taxon. We partitioned the COI gene into codon position 1, 2 and 3. Evolutionary model testing for each of the partitioned codon was performed using JMODELTEST (Posada, 2008). Furthermore, models were selected: GTR + G for the first and third codon positions; and F81 for the second codon position. Phylogenetic relationships were evaluated using a Bayesian framework as implemented in BEAST v1.6.1 (Drummond & Rambaut, 2007). Analysis was run for 20 million generations with sampling every 1,000th generation. Two independent runs with four Markov chain Monte Carlo Chains (MCMC) were performed. We excluded the first 25% of the tree as burn‐in before the log‐likelihood scores stabilized. A 50% majority rule consensus of the sampled trees was constructed and visualized using FigTree v1.4.2 (Rambaut, 2012). We considered bootstrap values of Bayesian Posterior Probabilities (PP) ≥0.95 as being strongly supported (Hillis & Huelsenbeck, 1992).

3. RESULTS

3.1. Morphology‐based species identification

Of the 136 specimens collected, all specimens (100%) were identified to consist of 53 species belonging to 28 genera and 18 families based on morphology (Table 2). This included 46 (86.80%) species identified to species level and seven (13.20%) species that could not be assigned species level and thus referred to genus.

Table 2.

Species identification using morphological and DNA barcode approaches. Species identification cutoff of 97% was used for GenBank and BOLD databases

S/No. Morphological ID GenBank identificationSpecies name (accession no) Similarity (%) BOLD identificationSpecies name Similarity (%)
1 Alestes baremoze A. baremoze (JF800979) 97 A. baremoze 100
2 Auchenoglanis biscutatus Auchenoglanis biscutatus (JF510501) 100 Auchenoglanis biscutatus 100
3 Auchenoglanis occidentalis A. occidentalis (HM882801) 100 A. occidentalis 100
4 Bagrus bajad B. bajad (HM882795) 100 B. bajad 100
5 Bagrus docmac Bagrus docmac (EU490857) 99 Bagrus docmac 99.20
6 Hyperopisus bebe Brienomyrus niger (JF510502) 99 B. niger 1 99.80
7 Brycinus nurse Brycinus nurse (HM882786) 99 Brycinus nurse 100
8 Brycinus sp. Brycinus sp. (JF510504) 99 Brycinus sp. 99.26
9 Chrysichthys cf. auratus Chrysichthys cf. auratus (HG803482) 100 N/A N/A
10 Chrysichthys nigrodigitatus Chrysichthys nigrodigitatus (HG803416) 100 Chrysichthys auratus 100
11 Chrysichthys sp. Chrysichthys sp. (HG803490) 99 Chrysichthys sp.2 99.60
12 Citharinus citharus Citharinus citharus citharus (HM882705) 100 Citharinus citharus 3 100
13 Clarias gabonensis Clarias gabonensis (HM882836) 100 Clarias gabonensis 4 100
14 Clarias gariepinus Clarias gariepinus (HM882821) 100 Clarias gariepinus 5 100
15 Clarotes laticeps Clarotes laticeps (HG803491) 100 Clarotes laticeps 100
16 Distichodius engycephalus Distichodius engycephalus (HM882993) 99 Distichodius engycephalus 99.80
17 Distichodius rostratus Distichodius rostratus (HM882994) 100 Distichodius rostratus 100
18 Gymnarchus niloticus G. niloticus (AP009610) 100 G. niloticus 100
19 Hemichromis bimaculatus Hemichromis bimaculatus (HM882913) 99 Hemichromis bimaculatus 6 99.80
20 Hydrocynus vittatus Hydrocynus vittatus (HM882886) 100 Hydrocynus vittatus 100
21 Heterotis niloticus H. niloticus (FJ890318) 100 H. niloticus 100
22 H. bebe H. bebe (JF510502) 99 B. niger 7 99.80
23 Labeo coubie Labeo sp. (HM882842) 100 Labeo sp.8 100
24 Labeo parvus Labeo parvus (AP013339) 100 Labeo parvus 9 100
25 Labeo senegalensis Labeo horie (JX074211) 100 Labeo horie 10 100
26 Lates niloticus L. niloticus (KJ443710) 99 L. niloticus 99.80
27 Malapterurus sp. Malapterurus melanochir (KT193322) 93 N/A N/A
28 Marcusenius senegalensis Marcusenius senegalensis (HM882721) 99 Marcusenius senegalensis 99.80
29 Mormyrops anguilloides M. anguilloides (AP011576) 99 M. anguilloides 99.60
30 Mormyrus rume Mormyrus hasselquistii (HM882746) 100 Mormyrus hasselquistii 11 100
31 Mormyrus macrophthalmus Mormyrus macrophthalmus (HM882759) 100 Mormyrus macrophthalmus 100
32 Mormyrus rume Mormyrus tapirus (HM882745) 99 Mormyrus longirostris 12 100
33 Oreochromis aureus Sarotherodon galilaeus (HM882887) 100 Sarotherodon galilaeus 13 100
34 Oreochromis sp. Oreochromis sp. (KX781822) 100 Oreochromis aureus 14 100
35 Parachanna insignis Parachanna obscura (MF496976) 100 Parachanna obscura 15 100
36 Parachanna obscura Parachanna obscura (MF496976) 100 Parachanna obscura 16 100
37 Protopterus sp. Protopterus sp. (JF510519) 99 Protopterus sp. 99.10
38 Oreochromis niloticus Sarotherodon galilaeus (KM438546) 99 Sarotherodon galilaeus 17 100
39 Schilbe intermedius S. intermedius (HM882935) 100 S. intermedius 100
40 Schilbe sp. S. intermedius (KT193441) 95 S. intermedius 98.90
41 Synodontis eupterus Synodontis aff. bastiani (HF565861) 99 Synodontis aff. bastiani 18 100
42 Synodontis schall Synodontis aff. haugi (HF565896) 100 Synodontis aff. haugi 19 100
43 Synodontis batensoda Synodontis batensoda (HF565863) 100 Synodontis batensoda 20 100
44 Synodontis clarias Synodontis clarias (HF565870) 99 Synodontis clarias 99.80
45 Synodontis membranacea Synodontis membranacea (HF565908) 100 Synodontis membranacea 21 100
46 Schilbe mystus Schilbe mystus (HM882942) 99 Schilbe mystus 100
47 Synodontis nigrita Synodontis nigrita (HF565916) 100 Synodontis nigrita 100
48 Synodontis obesus Synodontis obesus (HF565926) 99 Synodontis obesus 22 99.30
49 Synodontis ocellifer Synodontis sp. (HM882967) 100 Synodontis sp.23 100
50 Synodontis sp. Synodontis batensoda (HF565863) 96 N/A N/A
51 Synodontis violacea Synodontis violacea (HF565985) 99 Synodontis sp.24 100
52 Tetraodon lineatus Tetraodon lineatus (KT715694) 100 Tetraodon lineatus 25 100
53 Tilapia guineensis Coptodon zillii (KJ938220) 100 Tilapia zillii 26 100
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N/A, Sequences for the specimen are not available in BOLD; Individuals with superscript before species name represent specimens for which a species level match could not be made, but the queried species is likely to be one of the following: 1 B. niger or H. bebe; 2 Chrysichthys sp. or C. nigrodigitatus; 3 Citharinus citharus or C. citharus citharus; 4 Clarias gabonensis, Clarias sp. or C. agboyiensis; 5 C. gariepinus or Clarias sp.; 6 Hemichromis bimaculatus or H. fasciatus; 7 B. niger or H. bebe; 8 Labeo sp. or L. coubie; 9 L. parvus, L. cf. parvus, L. cylindricus, L. victorianus, Labeobarbus altianalis or L. molybdinus; 10 L. horie or L. senegalensis; 11 Mormyrus hasselquistii or Mormyrus sp.; 12 M. longirostris, M. tapirus or M. rume; 13 Sarotherodon galilaeus, Sarotherodon sp., Oreochromis mossambicus, O. niloticus, Oreochromis sp., O. aureus, O. aureus × O. niloticus, Oreochromis sp. TP or Tilapia zillii; 14 Oreochromis mossambicus, O. niloticus, Oreochromis sp., O. aureus, O. aureus × O. niloticus, Oreochromis sp. TP or Tilapia zillii; 15 Parachanna obscura or P. insignis; 16 P. obscura or P. insignis; 17 S. galilaeus, O. mossambicus, Sarotherodon sp., O. leucostictus, O. niloticus, Oreochromis sp., O. aureus, O. aureus × O. niloticus, Oreochromis sp. TP or S. galilaeus boulengeri; 18 Synodontis aff. bastiani, S. schall, S. aff. schall, S. aff. haugi or S. ouemeensis; 19 S. aff. haugi, S. aff. schall, S. aff. bastiani, S. schall or S. ouemeensis; 20 S. batensoda, S. resupinatus, S. membranacea, Brachysynodontis batensoda or S. aff. schall; 21 S. membranacea, B. batensoda, S. aff. schall, S. batensoda or S. resupinatus; 22 S. obesus, S. cf. obesus or S. rebeli; 23 Synodontis sp. or S. ocellifer; 24 Synodontis sp. or S. violaceus; 25 Tetraodon lineatus or T. pustulatus; 26 T. zillii, O. mossambicus, Coptodon zillii, Coptodon sp., C. rendalli or T. guineensis.

3.2. Amplification success and sequence statistics

We obtained 130 sequences (all >500 bp) belonging to 53 morphologically identified species (Table 1). This accounts for 95.60% amplification success rate (Table 1). Even with repeated attempts, sequences of six samples did not amplify probably due to some technical problems. However, we did not perform multiple temperature gradients or used alternative primers for PCR amplification for failed samples, as this would increase laboratory cost, time and resources. After trimming ambiguous bases, overall consensus length of 537 nucleotide base pairs (bp) was used in the analyses. The sequences contained 287 conserved sites, 260 variable sites and 250 phylogenetically informative sites. Overall base contents were as follows: A = 25.90%, C = 28.90%, G = 17.00% and T = 28.20%. No insertion, deletions and stop codon were observed; hence, all the amplified sequences represent functional mitochondrial COI sequences. Novel sequences generated were deposited in GenBank (Table 1) under Accession Nos. MG824552–MG824685. The COI sequences and related information for each specimen were also made publicly accessible via the BOLD systems website within “Diversity studies and DNA barcoding of Nigerian freshwater and marine fishes” project as part of the international fish barcode of life project.

3.3. DNA sequence similarity‐based species identification

All the 130 successfully amplified sequences were crossreferenced to GenBank and BOLD databases. One hundred twenty‐seven sequences (97.70%) belonging to 50 (94.30%) species showed species sequence similarity of ≥97% when crossreferenced in the GenBank. However, individuals morphologically identified as Malapterurus sp., Schilbe sp. and Synodontis sp. could not be identified to species level (DNA similarity sequences of ≤97%) using GenBank database. Using BOLD, 63 sequences (48.50%) belonging to 24 species (45.30%) could be matched to species level. Result shows that nearest neighbor values of the sequences were higher than the maximum intraspecific distance, pointing to the presence of a barcoding gap (Table 3). On the other hand, species level match for remaining 63 (48.50%) sequences obtained from 26 morphologically identified species (49.00%) could not be made, as queried specimens showed sequence similarity of ≥97% for more than one species. Attempt to estimate the BIN for these sequences failed, indicating possible taxonomic problems (Table 3). Furthermore, four sequences (3.00%) of three species (5.70%) morphologically identified as Chrysichthys cf. auratus, Malapterurus sp. and Synodontis sp. were unable to match to any records in BOLD database.

Table 3.

Barcode Index Number details of freshwater fishes from north‐central Nigeria

Morphological ID BOLD identificationSpecies name N BIN details Nearest neighbor
BIN AvD MxD DNN
Alestidae
Alestes baremoze A. baremoze 2 BOLD: AAJ3269 0.23 0.46 4.18 Alestes dentex
Brycinus nurse Brycinus nurse 2 BOLD: AAI8453 0.47 1.08 11.4 Brachyalestes bimaculatus
Brycinus sp. Brycinus sp. 1 BOLD: AAL6091 4.72 Brycinus cf. macrolepidotus
Hydrocynus vittatus Hydrocynus vittatus 2 BOLD: AAE1861 0.61 0.16 5.14 Hydrocynus forskahlii
Arapaimidae
Heterotis niloticus H. niloticus 1 BOLD: AAL6307 0.00 0.00 16.85 Monopterus albus
Bagridae
Bagrus bajad B. bajad 2 BOLD: AAL7132 0.31 0.31 2.57 Bagrus filamentosus
Bagrus docmac Bagrus docmac 2 BOLD: AAE1929 0.00 0.00 3.64 B. bajad
Channidae
Parachanna insignis Parachanna obscura 2 C/A
Parachanna obscura Parachanna obscura 2 C/A
Cichlidae
Hemichromis bimaculatus Hemichromis bimaculatus 2 C/A
Oreochromis aureus Sarotherodon galilaeus 3 C/A
Oreochromis sp. Oreochromis sp. 3 C/A
Oreochromis niloticus Sarotherodon galilaeus 2 C/A
Tilapia guineensis Tilapia zillii 4 C/A
Citharinidae
Citharinus citharus Citharinus citharus 4 C/A
Clariidae
Clarias gabonensis Clarias gabonensis 1 C/A
Clarias gariepinus Clarias gariepinus 4 C/A
Claroteidae
Auchenoglanis biscutatus Auchenoglanis biscutatus 1 BOLD: AAJ9618 0.00 0.00 8.03 Auchenoglanis occidentalis
A.occidentalis A. occidentalis 3 BOLD: AAL5844 0.09 0.15 5.78 A. occidentalis
Chrysichthys cf. auratus N/A 2 N/A
Chrysichthys nigrodigitatus Chrysichthys auratus 2 BOLD: AAL6568 0.08 0.16 3.37 Chrysichthys nigrodigitatus
Chrysichthys sp. Chrysichthys sp. 3 C/A
Clarotes laticeps Clarotes laticeps 3 BOLD: AAK5763 0.28 0.80 13.80 Chrysichthys nigrodigitatus
Cyprinidae
Labeo coubie Labeo sp. 3 C/A
Labeo parvus Labeo parvus 2 C/A
Labeo senegalensis Labeo horie 3 C/A
Distochodontidae
Distichodius engycephalus Distichodius engycephalus 1 BOLD: AAL6656 4.65% Distichodus petersii
Distichodius rostratus Distichodius rostratus 3 BOLD: AAL6019 0.23 0.61 5.14 Distichodus engycephalus
Gymnarchidae
Gymnarchus niloticus G. niloticus 2 BOLD: AAI6415 0.10 0.15 15.73 Mastomys
Latidae
Lates niloticus L. niloticus 3 BOLD: AAA2960 0.27 0.68 4.49
Malapteruridae
Malapterurus sp. N/A 1
Mochokidae
Synodontis eupterus Synodontis aff. bastiani 5 C/A
Synodontis schall Synodontis aff. haugi 2 C/A
Synodontis batensoda Synodontis batensoda 1 C/A
Synodontis clarias Synodontis clarias 4 BOLD: ACH9809 0.32 0.65 4.43 Synodontis sorex
Synodontis membranacea Synodontis membranacea 3 C/A
Synodontis nigrita Synodontis nigrita 2 BOLD: AAL5812 0.29 1.08 3.53 Synodontis
Synodontis obesus Synodontis obesus 2 C/A
Synodontis ocellifer Synodontis sp. 1 C/A
Synodontis sp. N/A 1
Synodontis violacea Synodontis sp. 5 C/A
Morymidae
Hyperopisus bebe sp1 Brevimyrus niger 2 C/A
H.bebe sp2 B. niger 2 C/A
Marcusenius senegalensis Marcusenius senegalensis 5 BOLD: AAL6601 0.68 1.23 3.21 Marcusenius macrolepidotus
Mormyrops anguilloides M. anguilloides 3 BOLD: ACR9609 0.34 0.34 4.33 Mormyrops masuianus
Mormyrus rume Mormyrus hasselquistii 1 C/A
Mormyrus macrophthalmus Mormyrus macrophthalmus 2 BOLD: AAM0703 8.83 Mormyrus caballus
Mormyrus rume Mormyrus tapirus 2 C/A
Protopteridae
Protopterus sp. Protopterus sp. 1 BOLD: AAL6244 0.51 0.77 2.56 Protopterus sp.
Schilbeidae
Schilbe intermedius S. intermedius 9 BOLD: AAL5704 0.44 0.77 6.1 S. intermedius
Schilbe sp. S. intermedius 1 BOLD: AAD0083 0.17 0.17 5.08 S. intermedius
Schilbe mystus Schilbe mystus 2 BOLD: AAM0039 N/A N/A 4.82 Schilbe grenfelli
Tetraodontidae
Tetraodon lineatus Tetraodon lineatus 3 C/A
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AvD: average intraspecific distance; BIN: Barcode Index Number, an identification number for barcoding clusters recognized by BOLD within the species; C/A: individuals for which a species level match could not be made; DNN: average genetic distance to the nearest neighbor; MxD: maximum intraspecific distance; N: number of barcode sequences; N/A: sequences for the specimen are not available in BOLD.

3.4. Mismatch in taxonomy

Of the 53 morphologically identified species, 34 (64.20%) matched with species names assigned using morphological approach and GenBank database. Using BOLD database, only 19 (35.80%) were in accordance with species names assigned using both morphological and BOLD database (Table 2). We observed cases of mismatch in names assigned to species using morphology and DNA barcoding approach. While species level assignments of 21 species (39.60%) were in accordance with species level identification made using morphology and DNA barcoding approach, our result revealed mismatch in species names assigned to 27 species (50.90%) using morphology and DNA barcoding. Comparing GenBank and BOLD databases, we encountered four (7.50%) cases of mismatches in which our query sequence for GenBank and BOLD showed a sequence match with different species names within 97% similarity cutoff (Table 2).

3.5. Tree‐based identification

We used HM883007 (Pellonula leonensis); and AP009231 (Pellonula vorax) as the out‐group taxa to root the NJ tree (NJ) for the pooled COI sequences of freshwater fishes from north‐central Nigeria (Figure 1). From our NJ tree analyses, most individuals of same species (92.50%) clustered together. Most of the species clusters in the NJ tree were strongly supported (bootstrap values ≥95%) except for Alestes baremoze (bootstrap values = 57%). Furthermore, undescribed species (Chrysichythys sp., Malapterurus sp., Protopterus sp., Synodotis sp., and Schilbe sp.) formed strongly supported lineages in the NJ tree and were clearly separated from their sister species (Figure 1). Thus, the NJ tree revealed that species identification based on morphological evidence and molecular methods are broadly consistent in most cases.

Figure 1.

Figure 1

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Neighbor‐Joining tree of Cytochrome c oxidase I gene sequences derived from 53 freshwater fish species from north‐central Nigeria. Values above branches are bootstrap values >50% and values below 50% are not shown

The K2P intergeneric COI sequence divergence values ranged from 0.30% to 31.40% (Table 4). The smallest intergenera genetic divergence values were observed between Hyperopisus and Brienomyrus (0.30%); while the highest pairwise comparison was between Protopterus and Lates (31.40%) and between Parachanna and Malapterurus (31.30%). We obtained interspecific divergence in the range of 0.30%–32.40% (Table S2). The least divergence (0.30%) was observed between Hyperopisus bebe and Brienomyrus niger; while highest interspecific divergence (32.40%) was between Bagrus bajad and Protopterus sp. (Table S2). Intraspecific genetic distances range from 0.00% and 16.39% (Table S3). We observed the highest intraspecific divergence in A. baremoze (16.39%) and Schilbe intermedius (4.14%) (Table S3).

Table 4.

Intergeneric pairwise genetic distance (%) of COI sequence data of freshwater fishes from north‐central Nigeria using Kimura‐2‐parameter

S/NO Genus 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27
1 Alestes
2 Auchenoglanis 28.40
3 Bagrus 26.70 18.60
4 Brienomyrus 27.80 28.10 28.70
5 Brycinus 17.90 23.70 24.60 24.40
6 Chrysichthys 25.90 19.80 18.90 28.40 24.20
7 Citharinus 24.70 23.00 26.50 28.00 22.70 23.70
8 Clarias 25.60 22.90 19.90 24.30 24.30 22.40 26.30
9 Clarotes 24.60 21.30 20.00 27.90 24.10 17.60 23.50 21.00
10 Distichodius 27.30 27.80 24.70 27.90 24.50 27.80 20.60 23.50 26.00
11 Gymnarchus 28.10 27.00 25.60 26.30 27.90 27.90 30.20 22.40 26.30 26.90
12 Hemichromis 26.40 25.60 26.80 28.00 25.30 24.20 24.60 26.90 24.20 27.30 28.40
13 Heterotis 28.70 27.00 26.30 25.50 27.80 30.10 27.00 27.90 25.90 26.20 24.80 24.30
14 Hydrocynus 17.20 25.00 25.60 26.10 19.10 25.00 24.80 22.20 26.20 26.00 27.10 25.10 27.50
15 Hyperopisus 27.60 27.80 28.40 0.30 24.20 28.40 27.90 24.20 27.60 27.60 26.30 27.70 25.30 25.90
16 Labeo 28.50 27.40 25.20 24.60 26.70 25.30 25.00 23.30 23.70 24.20 24.10 26.40 25.20 27.70 24.60
17 Lates 28.20 27.90 27.60 25.30 26.10 27.90 27.20 27.80 28.70 24.20 27.40 28.60 24.60 27.20 25.00 27.90
18 Malapterurus 26.90 20.30 21.40 25.70 23.80 22.80 24.00 21.60 19.70 22.60 27.30 28.70 24.00 28.00 25.60 24.90 27.00
19 Marcusenius 27.80 26.70 27.50 12.70 24.50 28.10 28.20 23.10 26.40 26.10 25.50 27.70 27.50 26.00 12.70 25.30 25.50 24.40
20 Mormyrops 30.20 26.90 29.60 17.30 27.60 27.70 27.60 28.00 28.30 29.80 26.40 27.40 27.70 28.10 17.30 27.00 29.90 27.00 18.50
21 Oreochromis 25.40 24.70 25.10 27.60 26.10 21.60 22.70 25.40 23.30 25.90 27.80 18.30 24.60 23.40 27.30 24.60 25.90 27.50 27.70 25.20
22 Parachanna 30.00 25.90 28.70 29.70 25.80 29.10 25.10 31.20 28.10 27.40 28.90 25.90 28.50 27.00 29.60 26.90 27.70 31.30 30.50 28.80 24.80
23 Protopterus 31.00 28.60 31.00 29.20 29.10 29.80 29.60 29.30 28.20 30.10 28.90 29.30 30.30 27.30 28.90 31.40 28.60 29.80 30.10 28.60 26.70 33.10
24 Sarotherodon 25.70 24.70 24.50 28.20 26.50 21.80 22.70 25.60 23.80 25.30 28.40 18.60 24.30 23.70 27.90 24.60 26.20 27.40 28.30 25.50 0.50 24.90 27.00
25 Schilbe 24.70 17.30 19.40 26.40 23.00 19.90 24.40 21.40 21.70 25.50 25.60 25.00 24.60 22.90 26.20 24.10 23.20 20.50 25.00 25.30 22.50 27.10 29.20 22.70
26 Synodontis 26.70 19.30 22.10 26.70 24.30 20.30 23.20 22.40 20.50 26.40 26.20 24.80 24.70 23.40 26.70 24.50 25.30 19.70 26.50 25.50 23.70 28.70 29.90 24.00 16.80
27 Tetraodon 27.70 24.90 25.70 27.10 24.50 26.00 26.60 27.80 27.10 27.00 27.10 24.40 26.90 22.50 26.80 24.50 27.10 25.80 27.30 25.50 23.60 26.50 30.80 23.90 26.60 25.60
28 Tilapia 26.00 26.20 26.20 25.70 25.10 22.80 21.70 26.80 24.10 28.90 28.30 19.00 25.30 21.70 25.70 24.40 26.80 28.50 24.40 26.10 12.90 24.80 29.50 13.10 25.40 24.70 22.90
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3.6. Applications of DNA barcode reference data

3.6.1. Identification of unknown fish tissue samples

All sequences of the four unknown fish samples collected from fishermen were successfully amplified. Our query search of COI sequences of unidentified species 1 and 2 in GenBank showed 100% sequence similarity with Auchenoglanis occidentalis (HM882800) and Heterotis niloticus (FJ890318), respectively. The NJ tree analysis clustered unidentified species 1 with A. occidentalis from Rivers Moro and Niger of north‐central Nigeria (Figure 2a). Furthermore, unidentified species 2 clustered with H. niloticus from River Asa (Fig. 2b). Unidentified species 3 and 4 showed, respectively, 99% and 100% DNA sequence similarity with Mormyrops anguilloides (AP011576) and S. intermedius (HM882935). In addition, unidentified species 3 and 4 clustered with M. anguilloides from Rivers Moro and Niger (Fig. 2c), and S. intermedius from River Asa (Fig. 2d), respectively. Therefore, DNA barcoding could aid in identification of unknown tissue samples. These unknown tissues samples could possibly be from fish collected from rivers across Nigeria.

Figure 2.

Figure 2

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Parts of the neighbor‐joining tree of Cytochrome c oxidase I (COI) used to identify (a) unknown tissue 1 (b) unknown tissue 2 (c) unknown tissue 3 (d) unknown tissue 4. Values above branches are bootstrap values >50% and values below 50% are not shown

3.6.2. Uncovering cryptic diversity

Our NJ tree‐based analyses of COI sequences of freshwater fishes from north‐central Nigeria revealed that populations of S. intermedius consist of at least two distinct lineages (bootstrap values = 99%, Fig. 1). This illustrates possibility of cryptic lineage diversity within Nigerian S. intermedius. To test for this, we downloaded 29 sequences of S. intermedius from the GenBank (Table S1). The BI analysis was rooted with Schilbe marmoratus (GenBank no. KT193454) as out‐group taxon Our BI analysis recovered four lineages (A–D) within S. intermedius (Figure 3), with moderate to high support. Lineages corresponded greatly to geography. Lineage A consists of samples distributed in West Africa (north‐central and southeastern Nigeria); lineage B includes samples from East Africa (Mozambique); lineage C restricted to individuals from north‐central Nigeria; while lineage D includes individuals widely distributed in Central Africa (Congo). Based on this result, these lineages were treated as discrete units and the pairwise level of divergence was recalculated. The results showed that the levels of divergence among the lineages were higher than 3% (Table 5). Highest pairwise level of divergence (9.348%) was between the two West African (Nigerian) lineages (lineage A and C) and the least pairwise divergence (6.698%) was between East and Central Africa (Table 5). Intraspecific genetic distances in all groups (except lineage B represented by one individual) fell between 0.091% and 1.31% (Table 5).

Figure 3.

Figure 3

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Matrilineal genealogy of Schilbe intermedius based on the Bayesian inference of COI sequences. Values above branches are Bayesian posterior probabilities (PP ≥ 0.95) and values below (PP < 0.95) are not shown

Table 5.

Estimates of mtDNA (COI) evolutionary divergence (%) over sequence pairs between lineages of Schilbe intermedius using Kimura‐2‐parameter

Lineage A Lineage D Lineage C
Lineage A
Lineage D 8.419
Lineage C 9.348 7.439
Lineage B 6.868 6.698 7.049
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4. DISCUSSION

In our study, DNA barcoding approach was very efficient in species identification. The success rates of DNA barcoding approach in our study (95.60%) was higher than the 93% success rate reported for Canadian freshwater fish (Hubert et al., 2008) and the 90% success rate reported for North American freshwater fish (April, Mayden, Hanner, & Bernatchez, 2011). However, our DNA barcoding success rate was lower when compared to 100% success rate reported by Shen, Guan, Wang, and Gan (2016) and 98.30% success rate reported for Indian freshwater fishes (Lakra et al., 2015). In most cases, our study shows that COI sequences effectively clustered most of the conspecific and congeneric species. This was also observed in similar studies in fishes from Upper Parana River Basin (Pereira, Hanner, Foresti, & Oliveira, 2013), freshwater fishes from southeastern Nigeria (Nwakanma et al., 2015; Nwani et al., 2011) and freshwater fishes from southwestern Nigeria (Falade, Opene, & Benson, 2016). In the studies of Nwani et al. (2011), 70 species of the southeastern Nigeria were well identified using DNA barcoding approach. Most of the species recorded in our present study have been studied using DNA barcoding approach by Falade et al. (2016), Nwakanna et al. (2015), and Nwani et al. (2011). These previous studies represent a potential reference database for the identification of Nigerian ichthyofaunal diversity. This may have accounted for the high identification success observed in our study.

Furthermore, we verified the taxonomic reliability of DNA barcoding against traditional method. Although the traditional method was effective in assigning species names to individuals, yet, this method is always tedious and time consuming, and often requires collaboration of taxonomists to share their expertise and confirm the identity of these species. We observed cases where species names assigned using morphological methods did not agree with names assigned using DNA barcoding approach. Such misidentification is a common challenge in taxonomy especially for morphologically similar species and accurate identification of the species also relies on the level of expertise of the taxonomist. Our study therefore gives strong evidence of integrating morphological and molecular methods in ichthyofaunal studies. However, because Nigerian ichthyofauna are facing threats arising from both climatic change and pollution of water bodies, the use of genetic methods, for example, DNA barcoding, may facilitate species identification. Most Nigerian ichthyofauna are still under‐studied and identification keys are often lacking. Thus, the combined use of morphological and genetic (DNA barcoding) data will aid in the identification of fish species in this region. Hence, developing a complete DNA barcode reference library for Nigerian ichthyofauna will facilitate taxonomy and biodiversity research in this region.

4.1. Application of DNA barcoding reference data

We reported two applications of DNA barcoding: identifying unknown samples from fishermen and uncovering cryptic diversity. In the case of the identification of unknown samples, DNA barcode reference data were very useful in identifying the unknown fish samples. Hence, the acquisition of DNA barcoding data will aid in species identification, which in turn, help in the conservation and management planning of Nigerian fishery resources. In addition, DNA barcoding approach could be a relevant tool for identifying unknown samples for wildlife‐related law enforcement and resolving a civil suit (Jeong, Byeung, Ki, & Su, 2013). It is obvious that the regulatory use of DNA barcoding, as suggested in this study, would be effective if most of the Nigerian freshwater fishes are documented in sequence libraries. This therefore calls for DNA barcoding of more species from other regions in Nigeria that would assist in identification and management of Nigerian freshwater fishes.

Although the primary goal of DNA barcoding is to identify species, intraspecific phylogeographic structure became evident in our study. This reveals applicability of DNA barcoding in uncovering cryptic diversity within species. Detecting cryptic species from molecular biodiversity inventories for many systematic biologists is the most appealing application of DNA barcoding (Knebelsberger et al., 2014). Populations of S. intermedius collected during our field survey were morphologically similar and their identification was controversial. However, in our study, DNA barcoding discriminated S. intermedius population from north‐central Nigeria into two distinct clusters with intraspecific divergence of 4.18%. Our finding was consistent with previous studies (e.g., Benzaquem et al., 2015; Mat Jaafar et al., 2012; Mohammed et al., 2016; Van der Bank, Greenfield, Daru, & Yessoufou, 2012) that showed the effectiveness of DNA barcoding in uncovering cryptic lineage diversities in fishes. There is the possibility that some of the identified lineages exhibit minute morphological differences that may have been overlooked in the past. However, due to the high rate of biodiversity loss, the distinct lineages uncovered from our study require consideration for conservation strategies and fishery management practice (Fraser & Bernatchez, 2001).

Comparison of our COI sequences with others from GenBank revealed existence of several more complexes of potentially cryptic lineages within S. intermedius. Contrary to previous studies (Nwani et al., 2011) that hypothesized two lineages of S. intermedius in Nigeria, our study revealed the presence of more than two lineages within this species in Nigeria. Increasing sample size and geographic sampling range may uncover more cryptic diversity within S. intermedius. Thus, our data is insufficient to explore the hypothesis of speciation within S. intermedius. To explore this hypothesis, it is necessary to sample these species across broad geographic range. Careful examination of possible morphological variations and more genetic analyses would aid in determining whether the detected cryptic lineages be warranted species status. Thus, our study emphasizes the need for a more complete reference DNA barcode data across Nigeria for the detection of more cryptic diversity in freshwater fish.

4.2. Reliability of DNA barcode reference data

The success of using DNA barcoding approach for species identification relies on the availability of high‐quality reference sequences in public sequence libraries such as GenBank and BOLD. Several sequences from the databases, particularly for individuals under the genera Oreochromis, Parachanna, Hyperopisus and Brienomyrus may require further taxonomic validation. In line with the findings of Becker, Hanner, and Steinke (2011), possible taxonomic errors exist for sequences submitted to databases. Possible sources of these errors might be due to either morphological misidentifications of the voucher specimen, contamination during sample processing in the laboratory, insufficient taxonomic identification or synonym and syntax problems (Radulovici, Archambault, & Dufresne, 2010; Tautz, Arctander, Minelli, Thomas, & Vogler, 2003; Ward, 2012). Accurate taxonomic review of already published DNA barcode data would be relevant in resolving such issues. This will increase the reliability of international barcode reference libraries like GenBank and BOLD.

5. CONCLUSION

Our study demonstrates the usefulness of DNA barcoding for the identification of fish species in north‐central Nigeria and uncovering lineage diversity. This study contributes to the construction of DNA reference barcode data for Nigerian fish fauna. This study has therefore contributed important data for the species identification, which in turn will aid the management of freshwater fishes in Nigerian inland water bodies. Furthermore, it has provided additional data to the major databases of GenBank and BOLD. We also confirm that DNA barcoding could assist in resolving issue of ambiguousness in identification of morphologically similar species. Thus, this approach could assist in the discovery and characterization of closely related species. However, we recommend further validation of GenBank sequences with respect to their voucher specimen to prevent future misidentification of fish species. In addition, this study underscores the relevance of combined use of morphological and genetic (DNA barcoding) data in the identification of fish species. Furthermore, our results demonstrate the application of DNA barcode reference data in uncovering cryptic diversity within S. intermedius. Finally, we recommend DNA barcode approach in species identification, ichthyofaunal studies, conservation and management planning of Nigerian fishery resources.

CONFLICT OF INTEREST

None declared.

AUTHORS’ CONTRIBUTIONS

O.A.I., L.M.N., M.K.M., S.O.O., and A.C.A. designed the study; S.O.O. collected and preserved the samples; L.M.N., A.C.A., Y.Y.W., J.C., and W.Z.W. performed the molecular laboratory work and generated the sequence data; L.M.N performed the genetic and morphological analyses; A.C.A provided technical assistance for the study; L.M.N., O.A.I., and S.O.O. wrote the initial draft of the manuscript; M.K.M., C.G.N., I.C.N., A.O.A., C.D.N., O.A.U., A.A.A.U., E.O.F., and A.C.A. critically revised the manuscript. All authors read and approved the final manuscript.

DATA ACCESSIBILITY

DNA sequences: GenBank Accession Nos MG824552–MG824685; for each individual, details on locality information and GenBank Accession no. for its sequence data are shown in Table 1.

Supporting information

 

Click here for additional data file. (14.6KB, docx)

 

Click here for additional data file. (23.7KB, xlsx)

 

Click here for additional data file. (13.2KB, xlsx)

ACKNOWLEDGEMENTS

We thank Mr. Adelakun Kehinde Moruff (Federal College of Wildlife Management, Forestry Research Institute, Nigeria) and Ms. Roseline Adeshike Aderinto for their assistance during the field sampling. This work was supported by the Sino‐Africa Joint Research Center, Chinese Academy of Sciences (SAJC201611 and SAJC201306), the STS program of Chinese Academy of Sciences and the Major Program of Chinese Academy of Sciences (KFZD‐SW‐208).

Iyiola OA, Nneji LM, Mustapha MK, et al. DNA barcoding of economically important freshwater fish species from north‐central Nigeria uncovers cryptic diversity. Ecol Evol. 2018;8:6932–6951. 10.1002/ece3.4210

Contributor Information

Wen‐Zhi Wang, Email: wangwz@mail.kiz.ac.cn.

Adeniyi C. Adeola, Email: chadeola@yahoo.com.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

 

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Data Availability Statement

DNA sequences: GenBank Accession Nos MG824552–MG824685; for each individual, details on locality information and GenBank Accession no. for its sequence data are shown in Table 1.

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