First Record of Tylosurus crocodilus (Péron & Lesueur, 1821) (Beloniformes: Belonidae) from Odisha Coast, Bay of Bengal, India: Exploration of a Biological Invasion Using DNA Barcoding

  • T. K. Barik
  • S. N. Swain
  • B. Sahu
  • B. Tripathy
  • U. R. Acharya
Article
  • 25 Downloads

Abstract

Adult hound needlefish Tylosurus crocodilus (Péron & Lesueur, 1821) were collected from the Buxipalli fish landing center (FLC) of Gopalpur-on-sea, Odisha coast. Using conventional morpho-taxonomy methods, the fish was morphologically identified as Tylosurus crocodilus (Péron & Lesueur, 1821) belonging to the family Belonidae. The capture of the hound needlefish of the Odisha coast is of particular interest in that it represents an early extension to the known range of this species in the north-eastern part of Bay of Bengal and the first record in Odisha coast. In order to ascertain the phylogenetic relationships with other allied species and to understand the genetic uniqueness of the fish, DNA barcoding approach was attempted, which is reportedly known as a promising tool to aid species identification over the traditional morpho-taxonomy or cyto-taxonomy methods. Cytochrome Oxidase subunit I (COI) gene sequence of the mitochondrial genome, which acts as a marker for discriminating a species from the other, was analyzed. No stop codons, insertions or deletions were found in the amplified sequences, showing that they constitute functional mitochondrial COI sequence. The amplified COI gene sequence exhibit unique barcode haplotype which permitted the discrimination of species. The phylogenetic trees revealed distinct clusters in concurrence with the taxonomic status of the species. Morphometric, meristic and molecular data confirmed the first record of Tylosurus crocodilus in Odisha coast of Bay of Bengal.

Keywords

First record Tylosurus crocodilus Bay of Bengal Odisha coast COI gene 

Introduction

Biological invasions are increasingly impacting ecological and economic balances in marine habitats (Mack et al. 2000). Some of these invasions become numerically and ecologically dominant in their new environment, causing reflective ecological impacts (Simberloff and Rejmánek 2011), while others fail to survive without any satisfactory reasons (Ζenetos et al. 2015). Studies indicate that Bay of Bengal has become more vulnerable and invasion of many new marine species because of its suitable environment for growth, development and reproduction. (Barik et al. 2017).

Fishes are the largest vertebrate group comprising more than 30, 000 species (Eschmeyer 2013). Since long, identification of fish species has been carried out mainly by examining morphometric and meristic characters of specimens (Strauss and Bond 1990). On the contrary, identification of fish species through traditional morpho-taxonomic means has sometimes become controversial mainly due to the lack of criteria for character selection and sometimes morphomeristic data sets happens to be quite arbitrary. On the other hand, it becomes very difficult to identify a fish absolutely in decaying condition. Under such situations, molecular taxonomy in the form of DNA barcoding might have been the ultimate tool and is most often applied for the identification of unknown specimens (Hebert et al. 2003; Hebert and Gregory 2005). The discriminatory power of DNA barcodes is predicted on the demonstration that divergence within species is smaller than between species (Kochzius et al. 2010). For this and other particular reasons, DNA barcoding is the most widely used molecular approach for exotic species recognition (Cross et al. 2011) which facilitates the identification of individuals of unconfirmed identity. DNA barcoding also supports the monitoring of exotic species in many other ways, such as detection in environmental samples (Takahara et al. 2013), assessing introduction effect (Lockwood et al. 2005), assessing the invasion potential (Jackson et al. 2015) and recognizing multiple species in complex samples (Côté et al. 2013).

Out of several potential barcode regions that have already been proposed, the mitochondrial cytochrome oxidase subunit I (COI) was suggested as a standard system for cataloguing most forms of life (Hebert et al. 2003; Radulovici et al. 2010). COI sequences often show a high interspecific and low intraspecific divergence, permitting efficient species identification (Hebert et al. 2003; Ward et al. 2009).

Needlefishes are a relatively small family (Belonidae) of beloniform fishes that differ from other members of the order in having both the upper and lower jaws extended into long beaks filled with sharp teeth (except in the neotenic Belonion). The needlefishes are epipelagic, feeding near the surface and are often observed leaping and skittering over the surface of water. The family Belonidae comprises of 10 genera and 47 species. Eight of the genera are monotypic or contain only two or three species. Two genera, Tylosurus and Strongylura, contain most of the species in the family. The genus Tylosurus comprises ten species (Froese and Pauly 2016). It is very difficult to discriminate among the species of the genus Tylosurus due to absence of data on diagnostic features such as morphometrics, meristics and molecular (Imsiridou et al. 2016).

The present investigation intends to provide morphometric data of T. crocodilus and its genetic reconfirmation using DNA barcoding. Furthermore, the study will justify the phylogenetic relationship of T. crocodilus with the allied species of genus Tylosurus. Moreover, it will confirm its appearance i.e. first record from the Odisha coast, Bay of Bengal.

Materials and Methods

Sample Collection

Fish specimen belonging to the family Belonidae in the range of sub-adult to adult size were collected through frequent sampling with the marginal fishers engaged in commercial fishing at Gopalpur-on-sea (Lat 19.26° N and Long 84.86° E), Odisha coast, Bay of Bengal, India (Fig. 1) during the year 2015. The species was photographed (Fig. 2) for morpho-taxonomy studies and muscle tissue samples were invariably collected aseptically from behind the dorsal fin of the fresh specimen and preserved in absolute ethanol under low temperature (−20 °C) condition.
Fig. 1

Map of study site, star mark indicates the collection site

Fig. 2

Tylosurus crocodilus, caught from Odisha coast of Bay of Bengal

We collected three individual hound needlefish (Tylosurus crocodilus) specimens from the study site and analyzed. However, only one individual was taken into consideration for both morphometric analysis as well as for barcoding study.

Taxonomic Identification

Specimens were categorized systematically based on the taxonomic characters available from the original description as well as subsequent re-descriptions and taxonomic reviews. The morphometric variables were measured and were confirmed by comparing with the described taxonomic keys available in the leading taxonomic guides. However, the samples were designated into the respective species as per the authoritative taxonomic keys and species nomenclature follows the Catalog of Fishes (http://research.calacademy.org/ichthyology).

DNA Extraction & Quantification

Total genomic DNA was isolated from the muscle tissue according to the salting out method of Sambrook et al. (2001) with minor modifications. The concentration and purity of the isolated DNA samples were analyzed using NanoDrop Lite spectrophotometer (Thermo Scientific, USA). Further, the concentrations of the DNA samples were adjusted to 100 ng/μl by diluting with double distilled water.

Amplification & Sequencing

The COI gene was amplified with a set of published primers: FishF1–5′ TCAACCAACCACAAAGACATTGGCAC 3′ and FishR1–5′ TAGACTTCTGGGTGGCCAAAGAATCA 3′ (Ward et al. 2005). The amplification was performed in 25-μl reaction mixture of 100 ng template DNA, 10 μM of each specific primer, 10 mM of dNTPs mix, 10% Trehalose, 1.0 unit of DreamTaq DNA polymerase (Thermo Scientific, USA) and 1X PCR Assay buffer containing 20 mM MgCl2. The PCR conditions were initial denaturation at 95 °C for 4 min, followed by 35 cycles of 60s at 94 °C, 60s at 52 °C, 60s at 72 °C and final extension at 72 °C for 10 min. The PCR products were visualized on 1.2% agarose gel containing ethidium bromide (10 mg/ml) and the amplicons were purified by PCR purification kit (Qiagen, USA) following the manufacture’s protocol. The most intense purified products were sequenced commercially by Bioserve Biotechnologies Pvt. Ltd., Hyderabad, India.

Sequence Quality Measures

Two electropherograms that represent sequences of both the DNA strands were obtained. The PCR amplified products as well as their corresponding DNA sequences were larger than 550 bp. The noisy sequences were trimmed at both ends using SeqMan Pro (DNASTAR, Lasergene, USA), and greater than 2% ambiguous bases were discarded, using the quality value of >40 for bidirectional reads. In some cases of discrepancy, both the sequences were reviewed and quality value of the sequences were considered to determine the most likely nucleotide using the software SeqScanner version 2.0 (Applied Biosystems, Thermo Fisher Scientific Inc.). BLASTN program implemented in NCBI (National Center for Biotechnology Information, www.ncbi.nlm.nih.gov) web server, was used to compare the sequences retrieved from two electropherograms (Altschul et al. 1990) and the fragment showing 100% alignment with no gap or indel (insertion/deletions) was selected. The assembled sequences were aligned using MAFFT algorithm (Katoh et al. 2009) using BLOSUM62 as the scoring matrix as an option G-INS_I strategy for optimal results for sequences with global alignment, with default parameters. The alignment conservation and confidence score was calculated using GUIDANCE2 server (Sela et al. 2015) (http://guidance.tau.ac.il/ver2/). The overall nucleotide frequencies within the sequence were calculated using BioEdit software version 7.2.5 (Hall 1999). Finally, the sequence was submitted to NCBI-Barcode of Life Database.

Phylogenetic Analysis: Likelihood, Neighbor-Joining and Parsimony

The phylogenetic position of T. crocodilus in relation to other species of family Belonidae, was investigated using comprehensive mitochondrial sequence datasets. The sampled specimen was invariably sequenced and their congeneric sequences were acquired from the database (GenBank) to examine the level of intraspecific variation. Analysis was based on a total datasets of 37 COI barcode sequences of species belonging to Belonidae family. Out of 37 sequences, 3 sequences of Xenentodon cancilla represent the out-group in this study. GenBank accession numbers along with respective species names of the developed as well as acquired sequences are given in Figs. 3, 4 and 5.
Fig. 3

Molecular Phylogenetic analysis by Maximum Likelihood method based on the HKY model. Branches corresponding to partitions reproduced in less than 50% bootstrap replicates are collapsed. The percentage of replicate trees in which the associated taxa clustered together are shown next to the branches. Underlined species along with the NCBI accession no. indicates the generated sequence

Fig. 4

Evolutionary relationships of taxa inferred by Neighbor-Joining method. Branches corresponding to partitions reproduced in less than 50% bootstrap replicates are collapsed. The percentage of replicate trees in which the associated taxa clustered together are shown next to the branches. The evolutionary distances were computed using the Kimura 2-parameter method and are in the units of the number of base substitutions per site. Underlined species along with the NCBI accession no. indicates the generated sequence

Fig. 5

Evolutionary relationships of taxa inferred by Maximum Parsimony method. The MP tree was obtained using TBR algorithm. Branches corresponding to partitions reproduced in less than 50% bootstrap replicates are collapsed. This phylogeny has a length of 762 steps, consistency index 0.453, retention index 0.792 and composite index 0.378 respectively. The percentage of replicate trees in which the associated taxa clustered together are shown next to the branches. NCBI accession no. within the rectangle along with the species name indicates the generated sequence

Phylogenetic analyses were conducted using MEGA7 (Kumar et al. 2016). Prior to that, elimination of the least likely models from a limited set was carried out by using Model Test version 3.7 (Posada and Crandall 1998). Model with the lowest Bayesian information criterion (BIC) scores are considered to describe the substitution pattern the best. We adopted the recommended model that was (HKY + I + G; Hasegawa et al. 1985) (No. of DGC = 6, No. of Threads = 1) for this analysis. The bootstrap consensus tree inferred from 500 replicates was taken to represent the evolutionary history of the analyzed taxa (Felsenstein 1985). Branches corresponding to partitions reproduced in <50% bootstrap replicates were collapsed. A heuristic likelihood search with 37 random sequence additions was used to find out the optimal tree. ML tree was used as a frame work to compare sequence divergence for COI gene fragments. The scores for likelihood were calculated in MEGA7 using ML tree.

Parsimonious phylogenetic relationships among the haplotypes were inferred by means of Bayesian phylogenetic Inference (BI), implemented in MrBayes 3.2.6 (Ronquist et al. 2012). Posterior probabilities were obtained, using tree-bisection reconnection (TBR) branch swapping method. Four Markov chains (three heated chain and one cold chain) were run for 30,000 generations and trees were sampled every 100th generation. The gaps were treated as missing characters and all the sites were equally weighted. All trees were rooted with Xenentodon species, whereas only branches with >50% bootstraps were considered for phylogenetic inference (Hillis and Bull 1993).

Results

Tylosurus crocodilus were collected in adult stage from the Buxipalli fish landing center (FLC) of Gopalpur-on-sea of Odisha coast (Fig. 2). It lives mostly in inshore and offshore water. Upper surface of head are back dark bluish green in colour, minutely dotted with black, silvery below. Fins were largely yellow-green, dusky on pectoral and caudal fins. Scales are small; lateral line forms a very slight keel on caudal peduncle. Gill rakers are absent. Body was elongated and rounded in cross section. Upper and lower jaws were greatly elongated and studded with sharp teeth. No spines in fins; anterior part of dorsal and anal fins with relatively highlobes. A small black lateral keel on caudal peduncle; caudal fin deeply forked, lower lobe much longer than upper. Predorsal scales in front of dorsal fin numerous and tiny (Allen and Erdmann 2012). The morphometric characters of Tylosurus crocodilus are given in Table 1.
Table 1

Morphometric data of Tylosurus crocodilus

Morphometric data

Tylosurus crocodilus (cm.)

Total length (TL)

34.7 cm

Fork length (FL)

32.7 cm

Precaudal length

30.1 cm

Predorsal length

24.2 cm

Head length

9.9 cm

Pre orbital length

6.5 cm

Pre anal length

23.0 cm

Eye diameter

1.0 cm

Body depth

2.1 cm

Pre pectoral length

10.7 cm

Standard length

31.6 cm

Caudal height

2.3 cm

Dorsal fin length

6.2 cm

Caudal fin length

3.7 cm

Pre pelvic length

18.7 cm

Snout length

6.1 cm

Genetic Analysis Based on COI Gene

No stop codons, insertions or deletions were found in any of the amplified sequences, showing that all of them constitute functional mitochondrial COI sequences. Of the 569 bases, 351 nucleotide sites are variable and most substitutions occurred in the third nucleotide position within codons. The nucleotide frequency were C (25.13%), T (33.74%), A (24.78%), and G (16.34%). Nearly all amplified sequences exhibited unique barcode haplotypes or cohesive clusters of very closely related haplotypes, which permitted the discrimination of species. The estimated alignment confidence score was found to be 0.99. This clearly indicates the elimination of the unreliable regions in the multiple sequence alignment that have direct consequences while constructing phylogenetic relationships.

Phylogenetic Analysis Based on COI Gene

Maximum Likelihood phylogenetic analysis resulted in a well-resolved hypothesis of relationships at the species level and the tree topology supported monophyly of Belonidae family fishes. In Neighbor-Joining phylogenetic tree (Fig. 4), the new sequence of Tylosurus crocodilus grouped in same cluster. Besides, where applicable, sequences from the same species (newly obtained in this work and retrieved from NCBI) grouped together, showing homology and more or less conspecific distance between them. Furthermore, sequences from the same species retrieved from NCBI grouped together in the same cluster. Nevertheless, some species were found mixed. Both Likelihood and Parsimony (Figs. 3 and 5) trees shows the genetic divergence among the species of the family Belonidae. Both the Maximum Likelihood and Maximum Parsimony phylogenetic trees shows the same topology.

Discussion

The present fish T. crocodilus belongs to family Belonidae, which has other three allied species namely Xenontodon cancilla (Hamilton, 1827), Strongylura strongylura (VanHasselt, 1823) and Strongylura leiura (Bleeker, 1850) that are commonly found in Odisha coast. However, Tylosurus crocodilus has never been reported from Odisha coast. Hence, this happens to be the first record from Odisha coast.

The morphological characters outlined in all the three specimens the same and are in accordance with the characters of T. crocodilus demonstrated by Collette and Parin (1986) along with the meristic features as reported by Tortonese (1970); Collette (1984) and Collette (2006). However, the smaller size, lower weight, decreased body height and body length (Table 1) compared to the previously reported specimens possibly indicates its juvenile stage. The rarity of occurrence of the present species, probably attributed to the limited number of specimens, which must have migrated from Indian Ocean to the Odisha coast of Bay of Bengal. Moreover, such behavior of the fish very likely focuses either its solitary or else its occurrence in small groups as reported earlier (Froese and Pauly 2016). Of note, T. crocodilus is reportedly an open sea species living in a depth of 13 – 15 m (Smith 1965; Sinis 2005; Froese and Pauly 2016). Migration of fish from one locality to other is not an uncommon phenomena. Therefore, in the present study, sudden appearance of T. crocodilus in the Odisha coast is believed to be a process of migration from Indian Ocean. The underlined factors behind this migration are probably due mainly to increased temperature range of surface water, in addition to food search (Robins and Ray 1986). However, earlier reports depict that some species of Tylosurus approach to coast line and surface water for gonadal maturation and reproduction. Hence, it might be allegedly suspected that juvenile forms of T. crocodilus were caught from Odisha coast. Furthermore, migration of new species of fishes in Odisha coast happens to be a noteworthy phenomenon. It is also very recently two such immigrants namely Pinjalo pinjalo belonging to family Lutjanidae and Ulua mentalis of Carangidae were reported by us from Odisha caost (Barik et al. 2017). Consequently, the aforesaid information have compelled the present authors to believe that the present specimens are definitely T. crocodilus and represent the first record status from Odisha coast.

In order to strengthen morphometric and identification and to deduce the phylogenetic relationship of T. crocodilus with other allied species of family Belonidae, we have analyzed and compared the COI gene sequences. The phylogenetic analysis carried out in this study shows that T. crocodilus genetically forms a clade with same species and with T. acus acus with a 95% bootstrap value, which is very similar with earlier studies on systematic and phylogeny of needlefishes (Imsiridou et al. 2016). Thus, the results of the present genetic study along with the detailed morphometrical analysis have been profoundly considered to approve the first record status of T. crcodilus in the Odisha coast, Bay of Bengal.

First records of commercially important fish populations may be useful for marine ecologists, fisheries and conservation management to improve our understanding of declining and migrating of fish population, population dynamics, marine habitat assessments and abiotic data such as sea bottom, middle and surface temperatures (Arvedlund 2009). The first record of a fish species in an unusual habitat or in a new geographical area is an indicator of climate changes or just a natural part of this species dispersal pattern (Arvedlund 2009). In order to find out solutions to the problem of occasional immigration of fishes to different places, as in the present situation, seems to be overwhelmed by a number of reasons. One such strong reason may possibly be the acute climatic changes of the coastal environment demanding shifting of specimens to new regions. The present study would certainly be helpful to identify future scenarios and trajectories of Bay of Bengal ecosystems might be resulted in serious ecological impacts.

Notes

Acknowledgements

This research was funded by Department of Biotechnology (DBT), Govt. of India (BT/PR5259/AAQ/3/592/2012).

Compliance with Ethical Standards

Conflict of Interest

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

References

  1. Allen GR, Erdmann MV (2012) Reef fishes of the East Indies. Volumes I-III. Tropical Reef Research. (Catalog of fishes, Ref: 31980). University of Hawaii Press, PerthGoogle Scholar
  2. Altschul SF, Gish W, Miller W, Myers EW, Lipman DJ (1990) Basic local alignment search tool. J Mol Biol 215:403–410CrossRefGoogle Scholar
  3. Arvedlund M (2009) First records of unusual marine fish distributions: can they predict climate changes? J Mar Biol Assoc U K 89:863–866CrossRefGoogle Scholar
  4. Barik TK, Swain SN, Sahu B, Tripathy B, Acharya UR (2017) Morphological and genetic analyses of the first record of longrakered trevally, Ulua mentalis (Perciformes: Carangidae) and of the pinjalo snapper, Pinjalo pinjalo (Perciformes: Lutjanidae) in the Odisha coast, Bay of Bengal. Mitochondrial DNA Part AGoogle Scholar
  5. Collette BB (1984) Belonidae. In: Fischer W, Bianchi G (eds) FAO species identification sheets for fishery purposes. Western Indian Ocean; (Fishing Area 51), vols 1-6. pag. var. Prepared and printed with the support of the Danish International Development Agency (DANIDA). Food and Agricultural Organization of the United Nations, RomeGoogle Scholar
  6. Collette BB (2006) Belonidae: needlefishes. In: Richards WJ (ed) Early stages of Atlantic fishes. An identification guide for the western central north Atlantic, Vol I., pp. 909-931. CRC Press, Taylor & Francis Group, Boca RatonGoogle Scholar
  7. Collette BB, Parin NV (1986) Belonidae. In: Whitehead PJP, Bauchot ML, Hureau JC, Nielsen J, Tortonese E, eds. Fishes of the northeastern Atlantic and the Mediterranean. Vol. 2. UNESCO, Paris: 604-609Google Scholar
  8. Côté I, Green S, Morris J, Akins J, Steinke D (2013) Diet richness of invasive Indo-Pacific lionfish revealed by DNA barcoding. Mar Ecol Prog Ser 472:249–256CrossRefGoogle Scholar
  9. Cross HB, Lowe AJ, Gurgel CFD. (2011). DNA barcoding of invasive species. Fifty years of invasion ecology: the legacy of Charles Elton (ed. by D. Richardson), pp.289–299. Wiley, HobokenGoogle Scholar
  10. Eschmeyer WN (2013) Catalog of fishes: genera, species, references. Available at: http://researcharchive.calacademy.org/ research/ichthyology/catalog/fishcatmain.asp
  11. Felsenstein J (1985) Confidence limits on phylogenies: An approach using the bootstrap. Evolution 39:783–791CrossRefGoogle Scholar
  12. Froese R, Pauly D (2016) Fish Base World Wide Web electronic publication Ver 10/2016 Available at: http://www.fishbase.org. Accessed May 2016
  13. Hall TA (1999) BioEdit: a user-friendly biological sequence alignment editor and analysis program for Windows 95/98/NT. Nucleic Acids Symp Ser 41:95–98Google Scholar
  14. Hasegawa M, Kishino H, Yano T (1985) Dating of the human-ape splitting by a molecular clock of mitochondrial DNA. J Mol Evol 22:160–174CrossRefGoogle Scholar
  15. Hebert PDN, Cywinska A, Ball SL (2003) Biological identifications through DNA barcodes. Proceedings of the Royal Society of London. Series B: Biol Sci 270(1512):313–321Google Scholar
  16. Hebert PDN, Gregory TR (2005) The promise of DNA barcoding for taxonomy. Syst Biol 54:852–859CrossRefGoogle Scholar
  17. Hebert PDN, Ratnasingham S, deWaard JR (2003) Barcoding animal life: cytochrome c oxidase subunit 1 divergences among closely related species. Proc R Soc London, Ser B 270(Suppl 1):96–99CrossRefGoogle Scholar
  18. Hillis DM, Bull JJ (1993) An empirical test of bootstrapping as a method for assessing confidence in phylogenetic analysis. Syst Biol 42:182–192CrossRefGoogle Scholar
  19. Imsiridou A, Minos G, Kokokiris L, Alexandrou M, Kyriakidou M, Karidas T (2016) Genetic and phenotypic identification of Tylosurus acus imperialis in Thermaikos Gulf, North Aegean Sea. Cah Biol Mar 57:9–15Google Scholar
  20. Jackson AM, Tenggardjaja K, Perez G, Azzurro E, Golani D, Bernardi G (2015) Phylogeography of the bluespotted cornetfish, Fistularia commersonii: a predictor to bioinvasion success? Mar Ecol 36:887–896CrossRefGoogle Scholar
  21. Katoh K, Asimenos G, Toh H (2009) Multiple Alignment of DNA Sequences with MAFFT. Bioinformatics for DNA Sequence Analysis. Methods Mol Biol 537:39–64CrossRefGoogle Scholar
  22. Kochzius M, Seidel C, Antoniou A et al (2010) Identifying fishes through DNA barcodes and microarrays. PLoS One 5:e12620CrossRefGoogle Scholar
  23. Kumar S, Stecher G, Tamura K (2016) MEGA7: Molecular Evolutionary Genetics Analysis version 7.0 for bigger datasets. Mol Biol Evol 33:1870–1874CrossRefGoogle Scholar
  24. Lockwood JL, Cassey P, Blackburn T (2005) The role of propagule pressure in explaining species invasions. Trends Ecol Evol 20:223–228CrossRefGoogle Scholar
  25. Mack RN, Simberloff D, Lonsdale WM, Evans H, Clout M, Bazzaz FA (2000) Biotic invasions: causes, epidemiology, global consequences, and control. Ecol Appl 10:689–710CrossRefGoogle Scholar
  26. Posada D, Crandall KA (1998) Modeltest: testing the model of DNA substitution. Bioinformatics 14:817–818CrossRefGoogle Scholar
  27. Radulovici AE, Archambault P, Dufresne F (2010) DNA barcodes for marine biodiversity: moving fast forward? Diversity 2:450–472CrossRefGoogle Scholar
  28. Robins CR, Ray GC (1986) A field guide to Atlantic coast fishes of North America. Houghton Mifflin Company, Boston, 354 pGoogle Scholar
  29. Ronquist F, Teslenko M, Mark PV, Ayres DL, Darling A, Ohna S, Larget B, Liu L, Suchard MA, Huelsenbeck JP (2012) MrBayes 3.2: Efficient Bayesian phylogenetic inference and model choice across a large model space. Syst Biol 61:539–542CrossRefGoogle Scholar
  30. Sambrook SJ, Russel DW, Janssen KA, Irwuin NJ (2001) Molecular cloning, a laboratory manual, Third edn. Cold Spring Harbor Laboratory Press, New YorkGoogle Scholar
  31. Sela I, Ashkenazy H, Katoh K, Pupko T (2015) GUIDANCE2: accurate detection of unreliable alignment regions accounting for the uncertainty of multiple parameters. Nucleic Acids Res 43(Web Server Issue):W7–W14CrossRefGoogle Scholar
  32. Simberloff D, Rejmánek M (2011) Encyclopedia of Biological Invasions. University of California Press, BerkeleyGoogle Scholar
  33. Sinis AI (2005) First record of Tylosurus crocodilus (Péron & Lesueur, 1821) (Pisces:Belonidae) in the Mediterranean (North Aegean Sea, Greece). J Biol Res 4:221–224Google Scholar
  34. Smith JLB (1965) The sea fishes of southern Africa. Central News Agency, LTD., South AfricaGoogle Scholar
  35. Strauss RE, Bond CE (1990) Taxonomic methods: Morphology. Methods for Fish Biology. American Fisheries Society, Bethesda, pp 109–140Google Scholar
  36. Takahara T, Minamoto T, Doi H (2013) Using environmental DNA to estimate the distribution of an invasive fish species in ponds. PLoS One 8:e56584CrossRefGoogle Scholar
  37. Tortonese E (1970) Fauna d’Italia. Osteichthyes. Vol X. Calderini, Bologna, 636 ppGoogle Scholar
  38. Ward RD, Hanner R, Hebert PDN (2009) The campaign to DNA barcode all fishes, FISH-BOL. J Fish Biol 74:329–356CrossRefGoogle Scholar
  39. Ward RD, Zemlak TS, Innes BH, Last PR, Hebert PDN (2005) DNA barcoding Australia's fish species. Philos Trans R Soc B: Biol Sci 360(1462):1847-1857Google Scholar
  40. Ζenetos Α, Akel EHH, Apostolidis C, Bilecenoglu M, Bitar G, Buchet V, Chalari N, Corsini-Foka M, Crocetta F, Dogrammatzi A, Drakulić M, Fanelli G, Ggiglio G, Imsiridou A, Kapiris K, Karachle PK, Kavadas S, Kondylatos G, Lefkaditou E, Lipej L, Mavrič B, Minos G, Moussa R, Pancucci-Papadopoulou MA, Prato E, Renda W, RÍos N, Rizkalla SI, Russo F, Servonnat M, Siapatis A, Sperone E, Theodorou JA, Tiralongo F, Tzovenis I (2015) New mediterranean biodiversity records (April 2015). Mediterranean Marine Science. Collective Article A 16(1):266–284Google Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • T. K. Barik
    • 1
  • S. N. Swain
    • 1
  • B. Sahu
    • 1
  • B. Tripathy
    • 1
  • U. R. Acharya
    • 1
  1. 1.P.G. Department of ZoologyBerhampur UniversityBerhampurIndia

Personalised recommendations