Universal mini COI barcode for the identification of fish species in processed products

Accepted Manuscript Universal mini COI barcode for the identification of fish species in processed products

Sharmin Sultana, Md. Eaqub Ali, M.A. Motalib Hossain, Asing, Nina Naquiah, I.S.M. Zaidul PII: DOI: Reference:

S0963-9969(17)30750-0 doi:10.1016/j.foodres.2017.10.065 FRIN 7113

To appear in:

Food Research International

Received date: Revised date: Accepted date:

29 August 2017 27 October 2017 28 October 2017

Please cite this article as: Sharmin Sultana, Md. Eaqub Ali, M.A. Motalib Hossain, Asing, Nina Naquiah, I.S.M. Zaidul , Universal mini COI barcode for the identification of fish species in processed products. The address for the corresponding author was captured as affiliation for all authors. Please check if appropriate. Frin(2017), doi:10.1016/ j.foodres.2017.10.065

This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

ACCEPTED MANUSCRIPT Universal Mini COI Barcode for the Identification of Fish Species in Processed Products

Sharmin Sultana a, Md. Eaqub Ali a, b, c *, M A. Motalib Hossain a, Asing a, Nina Naquiah a, I.S.M. Zaidul d

Nanotechnology and Catalysis Research Centre (NANOCAT), Institute of Graduate Studies,

PT

a

b

RI

University of Malaya, Kuala Lumpur 50603, Malaysia.

Centre for Research in Biotechnology for Agriculture (CEBAR), University of Malaya,

Institute of Halal Research University Malaya (IHRUM), University of Malaya, 50603

NU

c

SC

Kuala Lumpur 50603, Malaysia.

Kuala Lumpur, Malaysia Deparment of Pharmaceutical Technology, Faculty of Pharmacy, International Islamic University,

MA

d

Kuantan 25200, Pahang, Malaysia

D

*Correspondence Author:

PT E

Md. Eaqub Ali, Associate Professor

Abstract

CE

E-mail: [email protected], Tel: +603-7967-6959; Fax: +603-7967-6956.

AC

Species substitution, the use of a low value fish in place of a high value fish, is the biggest problem in international trade and the leading cause of fraud in the fisheries arena sector. Current DNA barcoding systems have partly solved this problem but also failed in many instances to amplify PCR targets from highly processed products because of the degradation of a longer barcode marker (~650 bp). In the present study, a novel mini barcode marker (295 bp) was developed to discriminate fish species in raw and processed states forms. The barcode primers were cross-tested against 33 fish species and 15 other animal species and

1|Page

ACCEPTED MANUSCRIPT found to be universal for all the tested fish varieties. When 20 commercial fish products of five different categories were screened, all commercial fish sample yielded positive bands for the novel fish barcode. PCR product were sequenced to retrieve the species IDs that reflected 55% (11/20) of Malaysian fish products were mislabeled.

PT

Key words: Fraud labeling, fish mini barcode, processed fish and surimi products, DNA breakdown, forensic studies.

RI

1. Introduction

SC

Market demands for fish and fishery products are rapidly expanding in all continents because of the increased public awareness and consumers’ positive attitudes toward fish

NU

products that are healthier than other animals’ and acceptable in all religions and cultures. Fish is a better source of animal proteins than other animal meat. While land animals’ fats

MA

and oils cause or aggravate obesity, diabetes and cardiovascular complications, fish fats and fish oils are known to boost up immunity against these and also many other diseases

PT E

D

(Djoussé, Akinkuolie, Wu, Ding, & Gaziano, 2012; Wu, Micha, Imamura, Pan, Biggs, Ajaz, et al., 2012; Baik, Abbott, Curb, & Shin, 2010 ). Fishery and aquaculture products also have a lower carbon footprint over those of beef and pork and thus are friendlier to environment

CE

(Nijdam, Rood, & Westhoek, 2012). So it is quite rationale that the appeal of fish and fish

AC

products is universal and will rise in future days. However, the blooming trades of fish products are greatly disputed over their frequent fraud labelling incidences in finished products (Rasmussen, Morrissey, & Hebert, 2009). Authentication studies and market monitoring reflect fish products are especially vulnerable to mislabelling than other consumers’ goods (Chang etal., 2016). Mislabelling was detected in 50% fish products in Germany (Kappel & Schröder, 2016), 24% seafood in South Brazil (Carvalho, Palhares, Drummond, & Frigo, 2015), 22% seafood in India (Nagalakshmi,

2|Page

ACCEPTED MANUSCRIPT Annam, Venkateshwarlu, Pathakota, & Lakra, 2016) and 82% commercial fish fillets in Italy (Di Pinto, Marchetti, Mottola, Bozzo, Bonerba, Ceci, et al., 2015). Regulatory laws, public awareness and authentication methods work in parallel to detect mislabelling and bring a greater control over fraud practices in food businesses (Ali,

PT

Sultana, Hamid, Hossain, Yehya, Kader, et al., 2016). In this regard, authentication of fish species in food chain is a need of the day. For instance, current European law on the common

RI

organisation of the markets in fishery and aquaculture products is regulated by the Regulation

SC

(EU) n. 1379/2013 and Regulation (EU) n. 1379/2013. The mandatory labelling requirements established by this regulation are the commercial and scientific names of the species, the

NU

geographic catching area, the used fishing gear if the fish products has been deforested (D’ Amico, Armani, Gianfaldoni, & Guidi, 2016). The aim of this regulation policy is to

MA

guarantee safe supply for consumers and processors, as well as providing consumers with

D

more complete information, in order to protect frauds and illegal fishing.

PT E

In Malaysia, the Food Safety and Quality Division (FSQD) under the Ministry of Health (MOH) monitor the national standards of processed foods, meat, agricultural

CE

commodities, dairy and fisheries products (Chin, Adibah, Hariz, & Azizah, 2016). FSQD mainly follow the FAO Fisheries & Aquaculture guideline for fish products (Fisheries Act

AC

No. 317, 1985). Like European union, Malaysian Food Regulations Act 1983 and Articles 11 (3A), 11 (6) and 11 (7) of Food Regulations Act 1985 also require scientific name of the species in the product labelling if the food products contain more than 3% ingredients from one animal origin (Malaysian Food Act 1983 & 1985). However, the identification of fish species based on their morphological criteria is possible only under raw or lightly processed conditions. Once commercial fish products are prepared, the morphological identification does not work and speciation becomes more

3|Page

ACCEPTED MANUSCRIPT difficult under processed conditions such as battering, crumbing, mincing and frying (Carvalho et al., 2015). This encourages replacement of higher priced fish species by the lower priced one in finished fish products, causing customers’ dissatisfaction, economic cheating and health hazards.

PT

Up to this date, many fish speciation methods based on protein biomarkers such as electrophoretic method (Asensio, González, García, & Martín, 2008; Ataman, Çelik, &

RI

Rehbein, 2006; Mackie, Craig, Etienne, Jerome, Fleurence, Jessen, et al., 2000),

SC

immunological techniques (Fernández, García, Asensio, Rodríguez, González, Lobo, et al., 2002; Ochiai, Ochiai, Hashimoto, & Watabe, 2001) and chromatographic approaches

NU

(Horstkotte & Rehbein, 2003) have been proposed. Some of these are of considerable importance in certain instances but most of them are not suitable for routine commercial fish

MA

sample analysis; this is because of the heat-induced degradation and dependency of proteins on specific cell types (Chin, Adibah, Hariz, & Azizah, 2016). Some proteins also loss

PT E

D

biological activity upon the death of animals and thus are not suitable for forensic studies. On the other hand, DNA-based methods offer better reliability over the protein based methods (Ali, Sultana, Hamid, Hossain, Yehya, Kader, et al., 2016; Lockley & Bardsley, 2000)

CE

because of the greater stability, cellular uniformity and polymorphism of the DNA biomarker

AC

itself (Gil, 2007). Among these methods, DNA barcoding based on mitochondrion genes such as COI (Cytochrome Oxidase Sub-unit I), 16S rRNA, or Cytochrome b amplification and profiling have been widely applied in various branches of biological sciences including forensic genetics (Dawnay, Ogden, McEwing, Carvalho, & Thorpe, 2007), biodiversity (Hardman, 2005) and seafood identifications (Nagalakshmi, Annam, Venkateshwarlu, Pathakota, & Lakra, 2016). The community–based exertions of DNA barcode libraries, such as the Barcode of Life Data systems (BOLD), have greatly eased the expansion of DNA barcoding systems as 4|Page

ACCEPTED MANUSCRIPT an effective means of fish speciation. Out of approximately 30,000 fish species, BOLD database is available for more than 10,000 fish species with the details of origin and location of COI voucher specimens (Gunther, Raupach, & Knebelsberger, 2017). However, currently available seafood barcode systems are based on long-length amplicon (>650bp) of COI gene that fails to be amplified in many instances and limited to only in few some species (Armani,

PT

Guardone, Castellana, Gianfaldoni, Guidi, & Castigliego, 2015; Cawthorn, Steinman, &

RI

Witthuhn, 2012; Chang, Lin, Ren, Lin, & Shao, 2016; Cutarelli, Amoroso, De Roma, Girardi,

SC

Galiero, Guarino, et al., 2014; Holmes, Steinke, & Ward, 2009; Shokralla, Hellberg, Handy, King, & Hajibabaei, 2015). To solve these problem, several mini barcoding approaches have

NU

been demonstrated for species identification in samples with highly degraded DNA (Meusnier et al., 2008; Armani et al., 2015; Hajibabaei, Smith, Janzen, Rodriguez, Whitfield,

MA

& Hebert, 2006; Leray, Yang, Meyer, Mills, Agudelo, Ranwez, & Machida, 2013). However, some of them have utilized too short-lengthamplicon barcode to enhance biomarker stability.

D

For instances, Meusnier et al. (2008) used 130 bp, Armani et al. (2015) used 190 bp and Chin

PT E

et al. (2016) utilized 140 bp. However, when the barcode length is too much shortened (≤150 bp), the target could be amplified by PCR but full core sequences could not be retrieved by

CE

direct sequencing, compromising the species ID (Chin et al., 2016; Gunther et al., 2017). Some of the authors (Amqizal et al., 2017) overcome the problem by cloning the target into a

AC

vector prior to sequencing but that incur about 10 times more cost. Some researchers also did direct sequencing (Meusnier et al., 2008; Armani et al., 2015) but in those cases the similarity scores were (≥ 95%), meaning less reliability in identified IDs. Therefore, here we developed a medium sized (295 bp) universal fish mini barcode that yielded ≤ 97-100% sequence similarities with identified species, bringing more confidence in ID score. Furthermore, crossspecies amplification studies further confirmed that the designed mini barcode primers were highly specific for commercial fish products screening in Malaysian markets.

5|Page

ACCEPTED MANUSCRIPT

2. Materials and Method 2.1 Sample collection Fresh muscle samples of 33 fish species and 15 other animal species were collected. Authenticate muscle tissue of cow (Bos taurus), buffalo (Bubalus bubalis), goat (Capra

PT

hiscus), chicken (Gallus gallus), quail (Coturnix coturnix), frog (Rana kunyuensis), pork (Sus

RI

scrofa), duck (Anas platyrhychos), lamb (Ovis aries), mouse (Rodentia muridae), rabbit

SC

(Leporidae cuniculas), crocodile (Crocodilia niloticus) and box turtle (Cuora amboinensis) were purchased from various wet markets (Pasar Borong Selangor, Pudu Pasar, PJ Old town

NU

and Serdang wet market) and supermarkets (Big Aeon and Tesco) in Malaysia. Meat from three different euthanized dogs (Canis lupus familiaris) and cats (Felis catus) were donated

MA

by Dewan Bandaraya Kuala Lumpur (DBKL) (Table 2). A total of 22 commercial fish products (such as fish ball, fish fingers, canned and fish fillets) were purchased from various

D

supermarkets in the Selangor state of Malaysia (Table 3). All samples were transported under

PT E

ice-chilled and around 50 mg tissues of each samples was taken aseptically and kept stored at -20ºC prior to use. For easy retrieval and cross checking of the data, each sample were

CE

labelled with a unique code number and product details (such as species name, company

AC

name, processing type, region and purchase date) were linked to this code. 2.2 DNA extraction

Total DNA from 33 raw fish species and 15 non-fish species were extracted from 20 mg of muscle tissues using Yeastern Biotech Genomic DNA Mini Kit (Yeastern Biotech Co., Ltd., Taipei, Taiwan) (Hossain et al., 2016). DNA from 22 commercial fish products was extracted using Nucleospin Food DNA mini Kit (Macherey-Nagel GmbH & Co. KG, Duren, Germany) (Ali, Razzak, Hamid, Rahman, Al Amin, & Rashid, 2015; Gunther et al., 2017). Followed by extraction processes, the concentration and purity of the extracted DNA 6|Page

ACCEPTED MANUSCRIPT specimens were determined by measuring the absorbance at 260 nm and 280 nm in a UV-Vis spectrophotometer (Chang et al., 2016; Hossain et al., 2016). 2.3 Design of universal fish biomarker For designing universal fish biomarker, the sequences of the mitochondrial COI

PT

region for 60 fish species of different fish families and 20 non-fish animal species were aligned and compared using MEGA v 5.0 and Clustal W alignment software’s (Rashid, Ali,

RI

Hamid, Rahman, Razzak, Asing, et al., 2015). The target sites were chosen by verifying

other

animal

species.

A

pair

of

SC

sequences having few mismatches within the fish species but maximum differences against universal

primers

(Forward:

NU

ATCACAAAGACATTGGCACCCT and Reverse: AATGAAGGGGGGAGGAGTCAGAA)

USA).

A

set

of

previously

MA

for fish species was constructed using primer 3 plus (Applied Biosystems, Foster City, CA, reported

universal

and

primers

(Forward: Reverse:

D

GGTAGTGACGAAAAATAACAATACAGGAC

eukaryotic

PT E

ATACGCTATTGGAGCTGGAATTACC) targeting a 141 bp site of eukaryotic 18srRNA were used as an internal control (Hossain, et al., 2016). The primers were synthesized by IDT

CE

(Integrated DNA Technologies, Singapore) and were supplied by 1st Base (1st Base Sdn Bhd, Selangor, Malaysia).

AC

2.4 PCR amplification

A 295 bp fragment of fish COI gene was amplified in a PCR having both universal fish and eukaryotic primers as a target and positive control in a 20 µl reaction mixture composed of 5µl of 5X GoTaq Flexi Buffer, 2.4 mM MgCl2, 0.25mM each of deoxy nucleotide triphosphate (dNTPs), 0.6 µM of each primer set, 0.4 µM of 18SrRNA primer, 2 µl of 20 (ng/µl) DNA template and 0.625 units of Go Taq Flexi DNA polymerase (Promega, Madison, USA). The PCR reaction was carried out in a thermal cycler (Applied Biosystems, 7|Page

ACCEPTED MANUSCRIPT Foster City, CA, USA) involving an initial denaturation at 95ºC for 3 min followed by 35-37 cycles of denaturation at 95ºC for 30s, annealing at 59ºC for 30-35 s, extension at 72ºC for 40s and a final extension at 72ºC for 5 min. All the PCR tests were performed in triplicates on three different days to ensure reproducibility and accuracies.

PT

2.5 DNA sequencing PCR products were purified using a PCR purification kit (1st Base, Selangor,

RI

Malaysia) and the quality of the purified sample (1 µl) was visualized in 1.5% agarose gel

SC

that yielded clear bands. The purified PCR products were sequenced in both directions using the BigDye® Terminator v3.1 cycle sequencing kit chemistry (Chang, Lin, Ren, Lin, & Shao,

MA

using both the forward and reverse primers.

NU

2016) in an ABI PRISM 96-capillary 3730xl genetic analyser (Applied Biosystems, USA)

2.6 Data analysis

D

Fish species in different commercial fish products was identified based on sequencing

PT E

results using BOLD and Genbank database search engines (Di Pinto et al., 2015). The highest percentage of pairwise identity of consensus sequences was blasted in NCBI to compare the

CE

similarity scores against BOLD-IDS (Kim, Kumar, Hwang, Kang, Moon, & Shin, 2015). The genetic distance between and within the species was evaluated using Kimura-2-Parameter

AC

(K2P) distance model and Neighbour-joining (NJ) tree of K2P (Kimura, 1980; Ratnasingham & Hebert, 2007).

3. Results and Discussion 3.1 Analyses of extracted DNA In addition to 33 fish species, 15 non-fish species were selected to check the fish barcode specificity against other animal species; so that it could be used as an internal positive control for screening indicating the presence of fish species in any meat speciation 8|Page

ACCEPTED MANUSCRIPT and other forensic studies. We have chosen A total of 33 raw fish were selected from 16 different fish family which are mostly that are commonly consumed in Malaysia. The selection was done to check the performance of the designed universal fish primers in toward relevant fish species detection. Five different categories of processed fish products, namely, fish ball, fish finger, tin & canned, fish chips and fish nuggets were selected randomly from 3

PT

different outlets of Malaysian supermarkets. Out of them, three categories (fish ball, fish

RI

finger & fish chips) contained surimi ingredients, reflecting the global presence of surimi

SC

products in processed fish markets (Keskin & Atar, 2012). It is worthy to note here that a variety of complex processes such as thawing, salting, grinding, shaping and heating are used

NU

in surimi production that often degrade longer DNA targets (Pepe, Trotta, Di Marco, Anastasio, Bautista, & Cortesi, 2007). Thus extraction of DNA from this degraded food

MA

product might pose attribute a significant challenge. For any of the tested sample, if the absorbance ratios were 1.7 to 2.0, extracted DNA samples were used for PCR testing because

D

the absorbance ratios of this range indicate good quality DNA (Chang etal., 2016). Most of

PT E

the samples produced DNA in sufficient quantity and quality but two highly processed fish samples yielded very poor quality DNA (260/280= 0.8 and 1.2) that could not be used for

CE

PCR amplification. These two samples (FC-3 and FC-4) were labelled to contain 68% and 66% surimi fish powder, respectively. The failure to extract good DNA from these samples

AC

might be due to the presence of inhibitors that inactivate enzymes in the extraction kit, extensive putrefaction or presence of other unknown materials. Normal surimi processing factors cannot be the cause because other surimi products (FN-3, FN-4, FC-2, FF-1, FF-4, FB-1, FB-2, FB-5) yielded amplifiable DNA. 3.2 Biomarker specificity In the present study, a 295 bp fragment of COI gene was selected as a marker for the detection of a wide range of fish species, including those 33 commonly consumed fish 9|Page

ACCEPTED MANUSCRIPT varieties. For this purpose, an extensive in silico study was performed to identify homologous regions to find a universal primers sites for fish species. To avoid potential cross homologies, initial specificity of the amplicon (295 bp) was checked by BLAST analyses in NCBI. For comparison studies mismatches were listed in a table for 33 fish targets and 15 non-fish animal species (Table 1). To confirm experimentally the specificity of the primers, initially

PT

33 relevant fish species were tested by PCR. Then primer was further cross-checked against

RI

the DNA of 15 other animal species (beef, buffalo, lamb, pork, chicken, duck, pigeon, quail,

SC

rabbit, goat, frog, box turtle, and quail) (Figure 1c). Non-fish species were selected to cross check the fish barcode specificity with other animal species because processed products are

NU

very complex matrices that may include other animal ingredients, making the outcome dubious. Eukaryotic endogenous primers (141 bp) was added as a positive control in the same

MA

PCR tube to be sure that amplifiable eukaryotic DNA was present in each reaction tube and there was no false positive PCR amplification. Experimental studies, (figure 1 (a-c)), all fish

D

species and their products produced double bands, suggesting the presence of both fish target

PT E

(295 bp) and eukaryotic internal control (IAC)(141 bp) but all the non-fish target yielded 141 bp IAC only (Figure 1c), suggesting that the designed fish primers are highly specific for fish

CE

targets only.

AC

3.3 PCR amplification and DNA sequencing DNA barcoding system based on the COI gene sequence is the most promising approach to detect fish fraud because COI region generally shows greater interspecies than intraspecies variations, allowing discrimination among the species (Aramani et al., 2015). Therefore, many method have been proposed based on the full length COI region (≤650 bp) or 16S rRNA to identify different fish species from other critters (Armani et al., 2015; Chang, Lin, Ren, Lin, & Shao, 2016; Cawthorn, Steinman, & Witthuhn, 2012). Full length COI barcode (650 bp) could be easily sequenced and it provides higher (more than 97%) species 10 | P a g e

ACCEPTED MANUSCRIPT level specificity for mammals, birds, fishes, and various arthropods (Meusnier, Singer, Landry, Hickey, Hebert, & Hajibabaei, 2008). However, full length COI region has shown some weaknesses in cases, where highly processed fish products are involved because of the DNA fragmentation that is induced by

PT

extreme heating and prolonged storage in ethanol, affecting the amplification profile of full length COI barcode. To overcome the limitations, several mini barcodes with very short

RI

amplicon length have been proposed. Previously, Armani et al. (2015) demonstrated that

SC

compared to full length COI barcode (655 bp), mini barcode (190 bp) increased the likelihood of successful PCR detection from degraded DNA sample. They found that while

NU

655 bp amplicon amplified from 91% (fresh), 50% (cooked) and 81% (ethanol-preserved) samples, 190 bp amplicon amplified from 100% (cooked) and 94% (ethanol-preserved)

MA

samples. Similarly, Meusnier et al. (2008), Hajibabaei et al. (2006) & Leray et al. (2013) also reported that universal primers targeting shorter fragments ( length not specified in the study)

D

of the COI gene (Mini barcode) represents can do a valid molecular detection even under the

PT E

state of extreme DNA specimen’s degradation. However, the full core sequences of an extremely short length mini barcode (≤150 bp) cannot be retrieved by the full core sequences

CE

after direct sequencing and thus it often compromises species IDs in many instances (Chin et

AC

al., 2016). Gunther et al (2017) also demonstrated that DNA mini barcodes (≤320 bp) provide a valid contribution to barcoding-based authentication across a wide range of products and taxa. They reported that while the failure rate for full barcode primer was 32.2%, mini barcodes (≤ 320 bp) were successful to detect 43.2% of the failed cases. Therefore, a medium length novel mini DNA barcode (295bp) suitable for direct sequencing based species authentication was documented and validated here for the screening of fish products in Malaysian markets. To evaluate the performance of the mini barcode method, the 295 bp site of the fish COI gene was amplified from 33 different fish species (Table 2) under 11 | P a g e

ACCEPTED MANUSCRIPT raw state; both PCR products (Figure. 1a and 1b) and theoretical data from in-silico studies (Table 1) strongly supported each other. Furthermore, 20 processed fish samples that yielded good quality DNA were tested and clear bands for 295 bp fish target were obtained from all fish products (Figure 2a and 2b). Direct sequencing of the PCR products reflected overall 98.1% sequence similarities with various fish species after trimming the 5′ and 3′ end (Table

PT

4). So the results of this study was in consistent with the previously published reports that

RI

demonstrated that short length amplicon offers higher amplification rate for highly processed

SC

samples (100% ) and could be used to identify samples to the species level. 3.4 Gene bank and BOLD search

NU

Sequencing results and their subsequent comparison with available GenBank and

MA

BOLD data bases allowed the recognition and identification of various fish species present in the analysed commercial fish products with a maximum identity score of 99% in NCBI

D

BLAST (Farrington, Edwards, Guan, Carr, Baerwaldt, & Lance, 2015). The comprehensive

PT E

DNA sequencing results based on BOLD and Genbank data searches are given in table 3, wherein each of the commercial products was identified as a single fish species. Both

CE

Genbank and BOLD database revealed definitive identity scores in the range of 97-99% for consensus sequences for most of the species (FF-2, FB-2, FC-2, FC-1, FF-3, FF-5, FB-1, TC-

AC

1, FN-3, FB-4, TC-2, FB-3, FB-6, TC-3, FN-1, FN-4, FF-1 and FN-2). In most of the cases, BOLD-IDS results were consistent with GenBank results except for 6 samples (FB-2, FB-3, FF-2, FF-5, FN-1, and FC-2) where BOLD-IDS failed to generate any data due to unavailability of resources. Additionally, a phylogenetic analysis was done based on the construction of NJ (Neighbour-joining) tree with validated reference sequences from Genbank and BOLD search to cluster the results and evaluate genetic relationship (Figure 3). The commercial fish species tested in the present study were clustered independently within their corresponding genera. Three distinct samples, FF-3: Megalaspis cordyla, TC-3: Alepes 12 | P a g e

ACCEPTED MANUSCRIPT melanoptera and TC-2: Atule mate, which fall under Carangidae family clustered together and it was supported by a high bootstrap values of 100, 99.1 and 99%, respectively. Similarly, FC-2 (Hemibagrus nemurus) and FB-4 (Mystus gulio) samples were identified as Bagridae family and formed a cohesive group with a bootstrap value of about 97%. On the other hand, FF-2 and TC-4 samples were detected as pink salmon (Oncorhynchus gorbuscha)

PT

under the family of Salmonidae that clustered under the same subclades. In contrast, FB-6

RI

and FB-2 samples were found as Oreochromis niloticus (Cichlidae family) and clustered

SC

together with a maximum identity score of 99%. Interestingly, FN-1 (Barbonymus gonionotus) was represented by Cyprinidae family but did not form an assemblage with

NU

another species FC-1 (Cyprinus pellegrini) from the same family. However, it nicely clustered with sample FF-4 (Sillago sihama) that was from Sillaginidae family. Other

MA

samples such as FN-2 (Decapterus maruadsi), FB-3 (Chanos chanos), and FF-5 (Nemipterus japonicas) came from three different families (Carangidae, Chanidae and Nemipteridae

PT E

D

respectively) and clustered as independent subclades that were away from other clades. 3.5 Discrepancies between Genbank and BOLD Database

CE

Among the two data bases, the BOLD identification is based on verified sequences and tagged specimens (Wong et al., 2011) and consequently gets higher acceptability and

AC

scientific merit. However, BOLD records suffer from some shortcomings (Wong et al., 2011): firstly, BOLD data records are very limited since it is available only for 10,000 species and so it cannot identify all species, bringing ambiguity in gene search results. For example, in this study, Genbank records identified sequences for samples FB-2, FB-3, FF-2, FF-5, FN-1, and FC-2 as Oreochromis niloticus (97%), Chanos chanos (98%), Oncorhynchus gorbuscha (99%), Sillago sihama (94%), Nemipterus japonicas (97%), and Barbonymus gonionotus (97%), respectively; but sequences queries in BOLD-IDS showed “ no matches’’ due to resources limitations. Secondly, BOLD-IDS usually depend on GenBank sequences 13 | P a g e

ACCEPTED MANUSCRIPT for much of its contents; therefore, probability of tentative, incorrect or low quality sequences could be arisen (Wong et al., 2011).

It is also documented that mistakes in private

submission or records gleaned from GenBank database can create incorrect identification when BOLD-IDS are used (Wong et al., 2011). In this study, five samples were found to have different identification between the BOLD and Genbank records. Sample FB-6 was identified

PT

as Oreochromis sp. (97%) in Genbank; but it was identified as Oreochromis aureus (98.82%)

RI

in BOLD databases. On the other hand, sample TC-3 was recognized as Selaroides leptolepis

SC

(98%) in Genbank; but actually it was Alepes melanoptera (99.17%) in BOLD. Similarly, sample FF-1 was identified as Oreochromis mossambicus (99%) in Genbank; but

NU

Oreochromis niloticus (99%) in BOLD. Finally, Figo sea food tofu (FN-3) was identified as Mastacembelus erythrotaenia (98.43%) in BOLD; but it was Mastacembelus unicolor (98%)

MA

in Genbank. Interestingly, sample FF-3 (Grilled mackerel scad) was identified as Megalaspis cordyla both in BOLD and GenBank with identity score 100% and 98.5%, respectively. Thus

D

our study results demonstrated that both Genbank and BOLD data still lack reference

PT E

sequences and contain different kind of problematic sequences (Aramani et al., 2015). Therefore, it is useful to use both the databases to perform a careful analysis and elaboration

CE

of the raw data in order to solve ambiguous results that might cause misidentification. Since Genbank data contains a mixture of validated and non-validated sequences (Wong et al.,

AC

2011); but BOLD is based on both experts identified and verified sequences, this study accepted the BOLD identification in first priority; but also was accepted GeneBank identification where BOLD data was not available. 4. Mislabeling in commercial fish products In the recent decades, ready-to-eat fish products have received huge attention as a staple, attractive and profitable commodity in worldwide food trades (Hubert et al., 2015). Nevertheless, these commercial fish products, such as fish balls, fish fingers, canned curry, 14 | P a g e

ACCEPTED MANUSCRIPT pomfret fry, fish chips and fish burgers are usually prepared from some costly sea fishes such as tuna, salmon, sardine, mackerel, shrimp, cobia and shad (Nagalakshmi et al., 2016). So the costly fish items in these products are highly susceptible to be replaced by some less expensive fish species such as tilapia, milkfish, common carp, mud cap etc. (Hubert et al., 2015; Nagalakshmi et al., 2016; Xiong, D’Amico, Guardone, Castigliego, Guidi, Gianfaldoni,

PT

& Armani, 2016). Proper labeling and their subsequent monitoring are definitely a crucial

RI

factor for ensuring food safety and imposing tariff from farm to fork. For instances, a

SC

preliminary case study conducted by Xiong et al. (2016) in China demonstrated that some economically valuable fish species such as salmon, cod, tuna shows lack of a national

NU

mandatory regulation for fishery products, badly affect the fishing industry, consumers’ rights as well as the preservation of fish stocks

MA

This study confirmed that more than one half of the commercialized fish found in Malaysia were mislabelled (11/20). Out of 11 mislabelled samples, 8 products were surimi’s that were

PT E

D

labelled as Alaska Pollock or Theragra chalcogramma or Gadus chalcogramma Pallas (Table 4). Recently, some other fishes such as Pacific whiting (Merluccius productus), small pelagic sardines (Sardinops sagax and S. neopilchardus) and red tilapia (Oreochromis

CE

mossambicus) have been used for surimi production (Kaewudom, Benjakul, &

AC

Kijroongrojana, 2013; Keskin & Atar, 2012; Mahawanich, Lekhavichitr, & Duangmal, 2010; Norziah, Al-Hassan, Khairulnizam, Mordi, & Norita, 2009). Out of 9 surimi products which were labelled as (Alaska Pollock or Theragra chalcogramma or Gadus chalcogramma Pallas); FB-2, FB-6 and FF-1 were identified as a tilapia flesh (Oreochromis niloticus, Oreochromis sp. and Oreochromis mossambicus); FB-1 and FN-4 identified as North African cat fish (Clarias gariepinus); while other 4 samples (FC-2, FN3, FB-4 and FF-4) were identified as Hemibagrus nemurus, Mastacembelus unicolor, Mystus gulio, and Sillago sihama, respectively. 15 | P a g e

ACCEPTED MANUSCRIPT Previous studies documented that the percentage of fraudulent replacement in surimi-based fish products is very high. Pepe et al. (2007) found 84.2% of the surimi-based products are mislabelled. In Turkey, 86% of the surimi samples of Alaska Pollock origins were found to have mislabelled (Keskin, & Atar, 2012). The findings of this clearly showed that surimi ingredients are highly vulnerable to adulteration because 100 % (9/9) of the surimi based fish

PT

products contained cheaper fish (mostly tilapia and cat fish) flesh instead of what was given

RI

in the label (Theragra chalcogramma or Gadus chalcogramma Pallas).

SC

Several past studies conducted by Chin et al. (2016), Keskin et al. (2012), and Pepe et al. (2007) demonstrated that Sanger method, which has still been used as a gold standard,

NU

method for identifying single target species in surimi based products. Recently, Giusti et al. (2017) used a combination of Meta barcoding along with Next Generation Sequencing (NGS)

MA

to detect multiple species in a mixed sample. This technique is novel that utilized primers with broad binding affinities that require massive parallel cloning prior to sequencing to

D

extract sequence information from complex matrices. No doubt this technique provides better

PT E

detection security and can identify multiple species from surimi based products, but it incurs about 10 times cost of the method we used in this study because of the requirement of

CE

compulsory cloning step prior to sequencing.

AC

Among other commercial products, FN-1 (Subi tempura fish nuggets) were supposed to contain marine fish but they were identified as Barbonymus gonionotus which is a fresh water fish of Cyprinidae family, and FC-1 (Kenko frozen fish chip) did not specify by the name but it was detected to be Cyprinus pellegrini (common carp). Moreover, when canned sardined TC-2 (King cup brand sardines in tomato sauce) was analysed, yellow tail scad (Atule mate), a widespread fish species in Malaysia, was identified suggesting that the chief cause of adulteration is economic gain. It is a very common tendency that some common fish species that have got similar appearances of sardine are canned and sold as sardine products. 16 | P a g e

ACCEPTED MANUSCRIPT However, the remaining 7 products (such as FF-3, FF-2, FF-5, FN-2, FB-3, TC-3 and TC-4) were found correctly labelled. Our study results revealed that Fish Balls (FB) and Fish Nuggets (FN) are highly vulnerable to mislabelling because 4 out of 5 FB and 3 out of 4 FN tested in this study were mislabelled (Table 3). On the other hand, it can be assumed that Fish Fillets (FF) and Tin Canned (TC) products are comparatively less vulnerable to fraud

PT

labelling. Overall, both manufacturers and retailers are inclined to adulterate processed fish

RI

products by replacing a costly fish species by a cheaper one or including a more appetizing

SC

name to increase their profit margins. It has implications in public health because marine fish varieties are rich in some essential nutrients such as omega-3 fatty acids, iodine and calcium

NU

and poor in toxic heavy metals (Chang et al., 2016). Other health risks involve an allergic or toxic species that may come from aquaculture and farm-based fish containing highly

MA

pollutant substances (Jacquet & Pauly, 2008; Khaksar, et al., 2015). Moreover, since the nutrients contents in marine and fresh water fishes are different, health seeking people would

D

be greatly deprived if adulteration practices are continued. Definitely, regulatory laws and

PT E

public awareness are great factors but a confirmatory, reliable and low-cost analytical test can

5. Conclusion

CE

greatly help in the identification and prevention of frauds.

AC

The appeal of fish and fish products is universal and is rapidly expanding because of their healthier attributes and better acceptance in all religions and cultures over conventional animal meat. While animal killing is discouraged and considered as a cruelty and sinful act in Buddhist religion, there is no such restriction in the consumption of fish in any religions. Seafood products are especially vulnerable to adulteration by less costly species. DNA barcoding system has brought a revolution in fish speciation to improve food quality and safety. The short amplicon length universal fish DNA barcode marker that is documented here greatly enhanced the reliability of the existing barcoding methods: firstly, by enhancing 17 | P a g e

ACCEPTED MANUSCRIPT analyte stability because short-length targets are more stable for thermodynamic reasons; secondly, its universal nature that can detect and discriminate fish species by direct sequencing; thirdly, short amplicon length PCR assays are more sensitive than their longer counterparts. Furthermore, the screening of the commercial fish samples reflected that the developed biomarker could be applied for the analysis of real-world samples and about 55%

PT

(11/20) overall commercial fish products available in Malaysian super markets are mislabeled

RI

with their cheaper fish varieties, suggesting economic adulterations are rampant in Malaysian

SC

processed food markets. The method has sufficient merits to be used by regulatory bodies to monitor accurate fishery product labelling around the world.

NU

Abbreviations used

COI, cytochrome oxidase sub-unit I; DNA, Deoxyribonucleic acid; PCR, polymerase chain

MA

reaction; bp, base pair; NJ, Neighbour-joining. Conflicts of interest

Acknowledgments

PT E

D

The authors declare no competing financial or other interests.

This work was supported by University of Malaya Research Grant No. GC001A-14SBS and

CE

PG245-216A to M.E. Ali and Research Initiative Grant Scheme (RIGS16-303-0467) of

AC

International Islamic University Malaysia to I.S.M. Zaidul.

18 | P a g e

ACCEPTED MANUSCRIPT

References

PT

Ali, M. E., Sultana, S., Hamid, S. B. A., Hossain, M. M., Yehya, W. A., Kader, M. A., &

RI

Bhargava, S. K. (2016). Gelatin Controversies in Food, Pharmaceuticals and Personal

SC

Care Products: Authentication Methods, Current Status and Future Challenges. Critical Reviews in Food Science and Nutrition(just-accepted), 00-00.

NU

Ali, M. E., Razzak, M. A., Hamid, S. B. A., Rahman, M. M., Al Amin, M., & Rashid, N. R. A. (2015). Multiplex PCR assay for the detection of five meat species forbidden in

MA

Islamic foods. Food chemistry, 177, 214-224.

Amqizal, H. I. A.; Al-Kahtani, H. A.; Ismail, E. A.; Hayat, K.; Jaswir, I., (2017).

D

Identification and verification of porcine DNA in commercial gelatin and gelatin

PT E

containing processed foods. Food Control, 78, 297-303. Armani, A., Guardone, L., La Castellana, R., Gianfaldoni, D., Guidi, A., & Castigliego, L.

CE

(2015). DNA barcoding reveals commercial and health issues in ethnic seafood sold on the Italian market. Food control, 55, 206-214.

AC

Asensio, L., González, I., García, T., & Martín, R. (2008). Determination of food authenticity by enzyme-linked immunosorbent assay (ELISA). Food control, 19(1), 1-8. Ataman, C., Çelik, U., & Rehbein, H. (2006). Identification of some Aegean fish species by native isoelectric focussing. European Food Research and Technology, 222(1-2), 99104.

19 | P a g e

ACCEPTED MANUSCRIPT Baik, I., Abbott, R. D., Curb, J. D., & Shin, C. (2010). Intake of fish and n-3 fatty acids and future risk of metabolic syndrome. Journal of the American Dietetic Association, 110(7), 1018-1026. Carvalho, D. C., Palhares, R. M., Drummond, M. G., & Frigo, T. B. (2015). DNA Barcoding identification of commercialized seafood in South Brazil: a governmental regulatory

PT

forensic program. Food control, 50, 784-788.

RI

Cawthorn, D.-M., Steinman, H. A., & Witthuhn, R. C. (2012). DNA barcoding reveals a high

SC

incidence of fish species misrepresentation and substitution on the South African market. Food Research International, 46(1), 30-40.

NU

Cawthorn, D.-M., Duncan, J., Kastern, C., Francis, J., & Hoffman, L. C. (2015). Fish species substitution and misnaming in South Africa: an economic, safety and sustainability

MA

conundrum revisited. Food chemistry, 185, 165-181. Chang, C.-H., Lin, H.-Y., Ren, Q., Lin, Y.-S., & Shao, K.-T. (2016). DNA barcode

D

identification of fish products in Taiwan: Government-commissioned authentication

PT E

cases. Food control, 66, 38-43.

Chin, T. C., Adibah, A., Hariz, Z. D., & Azizah, M. S. (2016). Detection of mislabelled

CE

seafood products in Malaysia by DNA barcoding: Improving transparency in food market. Food control, 64, 247-256.

AC

Cutarelli, A., Amoroso, M. G., De Roma, A., Girardi, S., Galiero, G., Guarino, A., & Corrado, F. (2014). Italian market fish species identification and commercial frauds revealing by DNA sequencing. Food control, 37, 46-50. Dawnay, N., Ogden, R., McEwing, R., Carvalho, G. R., & Thorpe, R. S. (2007). Validation of the barcoding gene COI for use in forensic genetic species identification. Forensic Science International, 173(1), 1-6.

20 | P a g e

ACCEPTED MANUSCRIPT Di Pinto, A., Marchetti, P., Mottola, A., Bozzo, G., Bonerba, E., Ceci, E., Bottaro, M., & Tantillo, G. (2015). Species identification in fish fillet products using DNA barcoding. Fisheries Research, 170, 9-13. Djoussé, L., Akinkuolie, A. O., Wu, J. H., Ding, E. L., & Gaziano, J. M. (2012). Fish consumption, omega-3 fatty acids and risk of heart failure: a meta-analysis. Clinical

PT

nutrition, 31(6), 846-853.

RI

Farrington, H. L., Edwards, C. E., Guan, X., Carr, M. R., Baerwaldt, K., & Lance, R. F.

SC

(2015). Mitochondrial genome sequencing and development of genetic markers for the detection of DNA of invasive bighead and silver carp (Hypophthalmichthys

NU

nobilis and H. molitrix) in environmental water samples from the United States. PloS one, 10(2), e0117803.

MA

Fernández, A., García, T., Asensio, L., Rodríguez, M. Á., González, I., Lobo, E., Hernández, P. E., & Martín, R. (2002). Identification of the clam species Ruditapes decussatus

D

(grooved carpet shell), Venerupis rhomboides (yellow carpet shell) and Venerupis

PT E

pullastra (pullet carpet shell) by ELISA. Food and Agricultural immunology, 14(1), 65-71.

CE

Gil, L. A. (2007). PCR-based methods for fish and fishery products authentication. Trends in food science & technology, 18(11), 558-566.

AC

Giusti, A., Tinacci, L., Sotelo, C. G., Marchetti, M., Guidi, A., Zheng, W., & Armani, A. (2017). Seafood Identification in Multispecies Products: Assessment of 16SrRNA, cytb, and COI Universal Primers’ Efficiency as a Preliminary Analytical Step for Setting up Metabarcoding Next-Generation Sequencing Techniques. Journal of Agricultural and Food Chemistry, 65(13), 2902-2912.

21 | P a g e

ACCEPTED MANUSCRIPT Guo, X., Wang, X., Su, W., Zhang, G., & Zhou, R. (2011). DNA barcodes for discriminating the medicinal plant Scutellaria baicalensis (Lamiaceae) and its adulterants. Biological and Pharmaceutical Bulletin, 34(8), 1198-1203. Günther, B., Raupach, M. J., & Knebelsberger, T. (2017). Full-length and mini-length DNA barcoding for the identification of seafood commercially traded in Germany. Food

PT

Control, 73, 922-929.

RI

Hardman, M. (2005). The phylogenetic relationships among non-diplomystid catfishes as

SC

inferred from mitochondrial cytochrome b sequences; the search for the ictalurid sister taxon (Otophysi: Siluriformes). Molecular phylogenetics and evolution, 37(3),

NU

700-720.

Hajibabaei, M., Smith, M., Janzen, D. H., Rodriguez, J.J., Whitfield, J.B., & Hebert, P.D.

MA

(2006). A minimalist barcode can identify a specimen whose DNA is degraded. Molecular Ecology Resources, 6(4), 959-964.

D

Holmes, B. H., Steinke, D., & Ward, R. D. (2009). Identification of shark and ray fins using

PT E

DNA barcoding. Fisheries Research, 95(2), 280-288. Horstkotte, B., & Rehbein, H. (2003). Fish Species Identification by Means of Restriction

CE

Fragment Length Polymorphism and High‐Performance Liquid Chromatography. Journal of food science, 68(9), 2658-2666.

AC

Hossain, M. M., Ali, M. E., Abd Hamid, S. B., Asing, Mustafa, S., Mohd Desa, M. N.-., & Sarker, M. Z. I. (2016). Double Gene Targeting Multiplex PCR-RFLP Assay Discriminates Beef, Buffalo and Pork Substitution in Frankfurter Products. Journal of Agricultural and Food Chemistry. Hubert, N., Caruso, D., Pouyaud, L., Avarre, J.-C., Sulandari, S., Hadiaty, R. K., Wibowo, A., Busson, F., Keith, P., & Nafiqoh, N. (2015). DNA Barcoding Indonesian freshwater fishes: challenges and prospects. DNA Barcodes, 3(1), 144-169.

22 | P a g e

ACCEPTED MANUSCRIPT Jacquet, J. L., & Pauly, D. (2008). Trade secrets: renaming and mislabeling of seafood. Marine Policy, 32(3), 309-318. Kaewudom, P., Benjakul, S., & Kijroongrojana, K. (2013). Properties of surimi gel as influenced by fish gelatin and microbial transglutaminase. Food Bioscience, 1, 39-47. Kappel, K., & Schröder, U. (2016). Substitution of high-priced fish with low-priced species:

PT

adulteration of common sole in German restaurants. Food control, 59, 478-486.

RI

Keskin, E., & Atar, H. (2012). Molecular identification of fish species from surimi‐based

SC

products labeled as Alaskan pollock. Journal of Applied Ichthyology, 28(5), 811-814. Khaksar, R., Carlson, T., Schaffner, D. W., Ghorashi, M., Best, D., Jandhyala, S., Traverso,

NU

J., & Amini, S. (2015). Unmasking seafood mislabeling in US markets: DNA barcoding as a unique technology for food authentication and quality control. Food

MA

control, 56, 71-76.

Kim, H., Kumar, K. S., Hwang, S. Y., Kang, B.-C., Moon, H.-B., & Shin, K.-H. (2015).

D

Utility of stable isotope and cytochrome oxidase I gene sequencing analyses in

PT E

inferring origin and authentication of hairtail fish and shrimp. Journal of Agricultural and Food Chemistry, 63(22), 5548-5556.

CE

Kimura, M. (1980). A simple method for estimating evolutionary rates of base substitutions through comparative studies of nucleotide sequences. Journal of molecular evolution,

AC

16(2), 111-120.

Leray, M., Yang, J. Y., Meyer, C. P., Mills, S. C., Agudelo, N., Ranwez, V., ... & Machida, R. J. (2013). A new versatile primer set targeting a short fragment of the mitochondrial COI region for metabarcoding metazoan diversity: application for characterizing coral reef fish gut contents. Frontiers in zoology, 10(1), 34. Lockley, A., & Bardsley, R. (2000). DNA-based methods for food authentication. Trends in food science & technology, 11(2), 67-77.

23 | P a g e

ACCEPTED MANUSCRIPT Mackie, I., Craig, A., Etienne, M., Jerome, M., Fleurence, J., Jessen, F., Smelt, A., Kruijt, A., Yman, I. M., & Ferm, M. (2000). Species identification of smoked and gravad fish products by sodium dodecylsulphate polyacrylamide gel electrophoresis, urea isoelectric focusing and native isoelectric focusing: a collaborative study. Food chemistry, 71(1), 1-7.

PT

Mahawanich, T., Lekhavichitr, J., & Duangmal, K. (2010). Gel properties of red tilapia

RI

surimi: effects of setting condition, fish freshness and frozen storage. International

SC

Journal of Food Science & Technology, 45(9), 1777-1786.

Meusnier, I., Singer, G. A., Landry, J. F., Hickey, D. A., Hebert, P. D., & Hajibabaei, M.

NU

(2008). A universal DNA mini-barcode for biodiversity analysis. BMC Genomics, 9(1), 214.Miller, D. D., & Mariani, S. (2010). Smoke, mirrors, and mislabeled cod: poor

Environment, 8(10), 517-521.

MA

transparency in the European seafood industry. Frontiers in Ecology and the

D

Nagalakshmi, K., Annam, P.-K., Venkateshwarlu, G., Pathakota, G.-B., & Lakra, W. S.

PT E

(2016). Mislabeling in Indian seafood: an investigation using DNA barcoding. Food control, 59, 196-200.

CE

Nijdam, D., Rood, T., & Westhoek, H. (2012). The price of protein: Review of land use and carbon footprints from life cycle assessments of animal food products and their

AC

substitutes. Food Policy, 37(6), 760-770. Norziah, M., Al-Hassan, A., Khairulnizam, A., Mordi, M., & Norita, M. (2009). Characterization of fish gelatin from surimi processing wastes: Thermal analysis and effect of transglutaminase on gel properties. Food Hydrocolloids, 23(6), 1610-1616. Ochiai, Y., Ochiai, L., Hashimoto, K., & Watabe, S. (2001). Quantitative estimation of dark muscle content in the mackerel meat paste and its products using antisera against myosin light chains. Journal of food science, 66(9), 1301-1305.

24 | P a g e

ACCEPTED MANUSCRIPT Pepe, T., Trotta, M., Di Marco, I., Anastasio, A., Bautista, J. M., & Cortesi, M. L. (2007). Fish species identification in surimi-based products. Journal of Agricultural and Food Chemistry, 55(9), 3681-3685. Rashid, N. R. A., Ali, M. E., Hamid, S. B. A., Rahman, M. M., Razzak, M. A., Asing, & Amin, M. A. (2015). A suitable method for the detection of a potential fraud of

PT

bringing macaque monkey meat into the food chain. Food Additives & Contaminants:

RI

Part A, 32(7), 1013-1022.

SC

Rasmussen, R. S., Morrissey, M. T., & Hebert, P. D. (2009). DNA barcoding of commercially important salmon and trout species (Oncorhynchus and Salmo) from

NU

North America. Journal of Agricultural and Food Chemistry, 57(18), 8379-8385. Ratnasingham, S., & Hebert, P. D. (2007). BOLD: The Barcode of Life Data System

MA

(http://www. barcodinglife. org). Molecular ecology notes, 7(3), 355-364. Regulation (EU) No 1379/2013 of 11 December 2013 on the Common Organisation of the

D

Markets in fishery and aquaculture products, amending Council Regulations (EC) No

PT E

1184/2006 and (EC) No 1224/2009 and repealing Council Regulation (EC) No 104/2000. OJEU 2013; L354.

CE

Santaclara, F. J., Pérez-Martín, R. I., & Sotelo, C. G. (2014). Developed of a method for the genetic identification of ling species (Genypterus spp.) in seafood products by FINS

AC

methodology. Food chemistry, 143, 22-26. Shokralla, S., Hellberg, R. S., Handy, S. M., King, I., & Hajibabaei, M. (2015). A DNA minibarcoding system for authentication of processed fish products. Scientific reports, 5. Torelli, A., Marieschi, M., & Bruni, R. (2014). Authentication of saffron (Crocus sativus L.) in different processed, retail products by means of SCAR markers. Food control, 36(1), 126-131.

25 | P a g e

ACCEPTED MANUSCRIPT Wong, E. H.-K., & Hanner, R. H. (2008). DNA barcoding detects market substitution in North American seafood. Food Research International, 41(8), 828-837. Wong, L. L., Peatman, E., Lu, J., Kucuktas, H., He, S., Zhou, C., Na-Nakorn, U., & Liu, Z. (2011). DNA barcoding of catfish: species authentication and phylogenetic assessment. PloS one, 6(3), e17812.

PT

Wu, J. H., Micha, R., Imamura, F., Pan, A., Biggs, M. L., Ajaz, O., Djousse, L., Hu, F. B., &

RI

Mozaffarian, D. (2012). Omega-3 fatty acids and incident type 2 diabetes: a

SC

systematic review and meta-analysis. British journal of nutrition, 107(S2), S214S227.

NU

Xiong, X., D’Amico, P., Guardone, L., Castigliego, L., Guidi, A., Gianfaldoni, D., & Armani, A. (2016). The uncertainty of seafood labeling in China: A case study on Cod,

AC

CE

PT E

D

MA

Salmon and Tuna. Marine Policy, 68, 123-135.

26 | P a g e

PT

ACCEPTED MANUSCRIPT

RI

Figure Captions

SC

Figure 1. Cross specificity of the universal fish barcode primers against 33 fish (a &b) and

NU

15 non-fish species (c). Lane 1-48: Seriola rivoliana, Salmo salar, Abbottina rivularis, Caranx ignobilis, Seriola lalandi, Esomus metallicus, Chitala lopis, Chaca bankanensis,

MA

Barbonymus gonionotus, Bagarius bagarius, Thunnus alalunga, Clarias fuscus, Anabas testudineus, Aplocheilus panchax, Barbonymus schwanenfeldii, Megalaspis cordyla, Catla

D

catla, Channa marulius, Selaroides leptolepis, Cirrhinus molitorella, Ctenopharyngodon

PT E

idella, Hampala macrolepidota, Hemibagrus nemurus, Hypophthalmichthys molitrix, Ilisha elongata, Labeo rohita, Lates calcarifer, Leptobarbus hoevenii, Mugil cephalus,

CE

Mylopharyngodon piceus, Oreochromis aureus, Oreochromis mossambicus, Oreochromis niloticus, cow (Bos taurus), buffalo (Bubalus bubalis), goat (Capra hiscus), chicken (Gallus

AC

gallus), quail (Coturnix coturnix), frog (Rana kunyuensis), pork (Sus scrofa), duck (Anas platyrhychos), lamb (Ovis aries), turtile (Cuora amboinensis), mouse (Rodentia muridae), rabbit (Leporidae cuniculas), Cat (Felis catus), Dog (Cannis familiaris), Crocodile (Crocodilia niloticus), respectively. Lane L: DNA ladders. Figure 2. Screening of commercial fish products using universal fish barcode primers. Lane 1-20: FB-1 (Figo golden sea food ball), FB-2 (Kenko fried fish ball), FB-3 (Marine Ikan ball), FB-4 (Pacific west popcorn fish), FB-5 (Figo marine fish ball), TC-1 (Pink Perch

27 | P a g e

ACCEPTED MANUSCRIPT Masala), TC-2 (King cup brand sardines in tomato sauce), TC-3 (Ayam brand Mackerel sos tomato curry), TC-4 (Ayam brand curry salmon), FF-1 (Pacific west fish fillets), FF-2 (Salmon fish fingers), FF-3 (Grilled mackerel scad), FF-4 (Pacific west corn flake fish fillets), FF-5 (First pride fish fillets), FN-1 (Subi tempura fish nuggets), FN-2 (Marina Fish Nuggets), FN-3 (Figo sea food tofu), FN-4 (Subi tempura fish bites), FC-1 (Kenko frozen

PT

fish Chip ) and FC-2 (Yoki fish chip) respectively.

RI

Figure 3. Neighbour-joining tree showing the relationship of the identified sequences in

AC

CE

PT E

D

MA

NU

SC

commercial fish products against 20 reference species in Genbank.

28 | P a g e

ACCEPTED MANUSCRIPT Table 1. In silico mismatch table for universal fish biomarker. Universal Forward Primer

Mismatch

Universal Reverse Primer

Mismatch

A

T

C A C A A A G A C A T T G G C A C C C T

T T C T G A C T C C T C C C C C C T T C A T T

Seriolina nigrofasciata

.

.

. .

.

.

.

.

.

.

.

.

. .

.

.

.

.

.

.

.

.

0

. .

.

.

.

.

.

. .

.

. .

.

.

.

.

.

.

.

.

.

.

.

0

Seriola rivoliana

.

.

. .

.

.

.

.

.

.

.

.

. .

.

.

.

.

.

.

.

.

0

. .

.

.

.

.

.

. .

.

. .

.

.

.

.

.

.

.

.

.

.

.

0

Liza macrolepis

.

C

. .

T .

.

.

.

.

.

.

. C .

.

.

.

.

.

.

.

3

. .

T .

.

.

.

.

. .

.

.

T .

.

C .

.

.

.

.

3

Copadichromis virginalis .

C

. .

T .

.

.

.

.

.

.

. .

.

.

.

.

.

.

.

.

2

. .

.

.

.

.

.

. .

.

. T .

.

.

.

.

.

.

.

.

.

.

1

Hypostomus plecostomus . (Cat fish) Esomus metallicus . (Molla) Chitala lopis .

C

. .

.

.

.

.

.

.

.

.

. .

.

.

.

.

.

.

.

.

1

. .

.

.

.

.

.

. A .

. .

.

.

.

.

.

A .

.

.

.

.

2

.

. .

.

.

.

.

.

.

.

.

. .

.

.

.

.

.

.

.

.

0

. .

.

.

.

.

.

. T .

. G .

.

T .

.

A .

.

.

.

.

4

C

. .

.

.

.

.

.

.

.

.

. .

.

.

A .

.

.

.

.

2

. .

T .

.

.

.

. .

. A .

.

.

.

.

.

.

.

.

.

.

2

.

C

. .

T .

.

.

.

.

.

.

. .

.

.

.

.

.

.

.

.

2

. .

.

.

.

.

.

. .

.

. .

.

.

.

.

.

A .

.

T C .

3

Barbonymus gonionotus

.

C

. .

.

.

.

.

.

.

.

.

. .

.

.

T .

.

.

.

.

2

. .

.

.

.

.

T . A .

. A .

.

.

.

.

.

.

.

.

.

.

3

Bagarius bagarius

.

C

. .

T .

.

.

.

.

.

.

. .

.

.

.

.

.

.

.

.

2

. .

.

.

.

.

.

. A .

. G .

.

.

.

.

A .

.

C .

.

4

Siganus guttatus

.

.

. .

.

.

.

.

.

.

.

.

. C .

.

T .

.

.

.

.

2

. .

.

.

.

SC

.

Chaca bankanensis

.

.

. T .

. .

.

.

A .

.

C .

.

T .

.

4

Clarias fuscus (Magur)

.

C

. .

T .

.

.

.

.

.

.

. .

.

.

.

.

.

.

.

.

2

. .

.

.

.

.

T . A .

. A .

.

.

.

.

.

.

.

T .

.

4

Plotosus lineatus

.

.

. .

.

.

.

.

.

.

.

.

. .

.

.

.

.

.

.

.

.

0

. .

.

.

.

.

.

. A .

. .

.

.

.

.

.

C .

.

.

.

.

2

C

. .

.

.

.

.

.

.

.

.

. .

.

.

.

.

.

.

.

.

1

. .

.

.

.

.

.

. .

.

. T .

.

A .

.

.

.

.

C .

.

3

.

.

.

1

. .

.

.

.

.

.

. A .

. T .

.

T .

.

C .

.

C .

.

5

Anabas testudineus (Koi) .

U N

A M

I R

T P

Aplocheilus panchax

.

.

. .

.

.

.

.

.

.

.

.

. .

.

.

T .

.

Barbonymus gonionotus

.

.

. .

.

.

.

.

.

.

.

.

. .

.

.

T .

.

.

.

.

1

. .

.

.

.

.

T . A .

. .

.

.

.

.

.

A .

.

.

.

.

3

Barbonymus schwanenfeldii Catla catla

.

C

. .

.

.

.

.

.

.

.

.

. .

.

.

T .

.

.

.

.

2

. .

.

.

.

.

T . .

.

. G .

.

.

.

.

.

.

.

.

.

.

2

.

C

. .

.

.

.

.

.

.

.

.

. .

.

. T .

Channa marulius (Taki)

.

C

. .

T .

.

.

.

.

.

.

. .

.

Chitala chitala

.

.

. .

.

.

.

.

.

.

.

Cirrhinus molitorella (Mud Carp) Ctenopharyngodon idella (Grass carp) Hampala macrolepidota (Hampala barb) Ilisha elongata

.

C

. .

.

.

.

.

.

.

.

.

C

. .

T .

.

.

.

.

.

.

C

. .

.

.

.

.

.

.

.

.

C

. .

.

.

.

.

.

.

Labeo rohita

.

.

. .

T .

.

Lates calcarifer

.

C

. .

.

.

Leptobarbus hoevenii

.

.

. .

Mugil cephalus

.

.

Mylopharyngodon piceus . Neolissochilus

29 | P a g e

.

D E

E C

PT .

T .

.

.

.

.

2

. .

.

.

.

.

.

. A .

.

.

.

.

A .

.

.

.

.

3

.

.

.

.

.

.

.

2

. .

.

.

.

.

T . G .

. .

.

.

T .

.

.

.

.

.

.

.

3

.

.

.

.

.

.

.

1

. .

T .

.

.

.

. .

. A .

.

.

.

.

A .

.

.

.

.

3

.

A .

.

.

.

.

2

. .

.

.

.

.

.

. T .

. .

.

.

.

.

.

.

.

.

G .

.

2

.

. C .

.

. .

.

C A

.

. .

.

.

.

.

.

.

.

.

2

. .

.

.

.

.

.

. .

.

. A .

.

.

.

.

.

.

.

T .

.

2

.

. .

.

.

T .

.

.

.

.

2

. .

.

.

.

.

.

. A .

. A .

.

A .

.

A .

.

.

.

.

4

.

.

. .

.

.

T .

.

.

.

.

2

. .

T .

.

.

.

. T .

. .

.

.

.

.

.

.

.

.

.

.

.

2

G .

.

.

.

. .

.

.

.

.

.

.

.

.

2

. .

.

.

.

.

.

. .

. A .

.

.

.

.

A .

.

.

.

.

2

.

.

.

.

.

.

. .

.

.

T .

.

.

.

.

2

. .

.

.

.

.

.

. T .

. .

.

.

.

.

.

.

.

.

T .

.

2

T .

.

.

.

.

.

.

. C .

.

.

.

.

.

.

.

2

. .

.

.

.

.

.

. .

.

. T .

.

.

.

.

A .

.

.

.

.

2

. .

.

.

.

.

.

.

T .

. C .

.

.

.

.

.

.

.

2

. .

.

.

.

.

.

. T .

. T .

.

T .

.

.

.

.

.

.

.

3

.

. .

.

.

.

.

.

.

.

.

. C .

.

.

.

.

.

.

.

1

. .

.

.

.

.

.

. T .

. G .

.

.

.

.

.

.

.

T .

.

3

C

. .

.

.

.

.

.

.

.

.

. .

.

T .

.

.

.

.

2

. .

T .

.

.

.

. .

. .

.

.

.

.

A .

.

.

.

2

.

.

.

.

.

.

ACCEPTED MANUSCRIPT hexagonolepis Oreochromis aureus

.

C

. .

.

.

.

.

.

.

.

.

. C .

.

A .

.

.

.

.

3

. .

.

.

.

.

.

. .

.

. .

.

.

T .

.

C .

.

.

.

.

2

Oreochromis mossambicus Oreochromis niloticus

.

.

. .

.

.

.

.

.

.

.

.

. C .

.

.

.

.

.

.

1

. .

T .

.

.

.

. .

.

. T .

.

.

.

.

.

.

.

.

2

.

1

.

.

.

.

.

.

.

.

.

.

.

.

. . C

.

.

. .

.

.

.

.

.

T

.

.

.

.

.

.

.

.

.

.

.

. .

.

.

.

C

.

.

.

.

.

2

Non-Target Animal Species Bos Taurus (Beef)

.

C

. .

T .

.

.

.

.

T .

. .

.

.

T .

6

. .

.

.

.

-

.

C .

.

Sus scrofa

.

C

. .

.

.

.

A .

.

.

.

. C .

.

.

G .

A .

.

5

. .

.

.

.

-

.

C .

A . .

Bubalus bubalis (Buffalo) .

.

. .

T .

.

.

.

.

T .

. C .

.

.

.

.

.

.

.

3

. .

.

.

.

-

.

C .

Felis catus

.

.

. .

T .

.

.

.

.

T .

. .

.

T .

.

T .

.

4

. .

.

.

.

-

.

C .

Crocodylus johnsoni (Crocodial) Capra hircus (Goat)

T

C

T C .

.

G G .

.

T .

A C A .

.

G .

A A .

12

. .

.

T .

.

.

. .

.

C

. C T .

G G .

.

T .

A C A .

.

G .

A A

12

.

.

.

.

.

I R

Apis mellifera

.

.

. .

T .

.

.

A .

T .

. .

.

.

G .

T .

.

.

.

.

.

Meleagris gallopavo (Turkeys) Equus caballus (Horse)

.

C

. .

T .

.

.

.

.

T .

. .

.

.

.

.

.

.

.

.

.

C

. .

.

.

A .

.

.

.

. C .

.

G .

A T .

.

.

.

Panthera tigris

.

.

. C .

.

.

G .

.

T .

. .

.

A .

.

Gallus Gallus

T

.

T .

.

.

.

.

.

T .

. C T .

.

G .

.

A .

Macaca Fascicularis

.

C

. C T .

.

G .

.

T .

. C .

.

.

G .

.

A

Ovis Aries

.

.

. .

T .

.

.

A .

T .

. .

.

.

G .

T .

Rana Kunvuensis

.

C

. .

T .

.

.

.

.

T .

. .

.

.

.

.

Columba livia

.

C

. .

.

A .

.

.

.

. C .

.

.

.

.

30 | P a g e

.

.

.

.

G .

C .

T .

T A .

T A .

T .

T A

A T .

6

.

6

. .

.

.

.

T .

.

C .

.

.

.

3

T .

.

A .

.

A .

.

C .

6

T .

.

.

.

.

C .

.

C .

4

.

.

.

T .

.

A .

.

C .

4

.

.

.

.

.

.

C .

.

.

.

2

T P

.

. .

.

. .

.

. .

-

. C .

. .

.

.

.

.

T .

.

C .

.

.

3

-

. C .

A .

.

T .

.

A .

.

A .

.

C

6

.

-

. C .

. .

.

T .

.

.

.

.

C .

.

C

4

. C .

.

A .

.

C

SC

U N

5

D E

T P E

C C

A

.

A .

.

.

-

. .

.

.

.

.

T .

6

. C T C .

.

G G .

.

T .

.

C .

.

.

G .

A A .

6

. C .

.

T .

.

G .

.

T .

.

C A .

.

G .

A A

8

. .

.

.

T .

.

. A .

T .

.

.

.

.

G .

T .

6

. C .

.

T .

.

. .

.

T .

.

.

.

.

.

.

5

. C .

.

.

.

A . .

.

. .

.

C .

.

G .

A T .

6

. .

.

.

.

.

.

T .

.

.

.

A .

.

A M

.

. .

.

.

.

4 10 9

.

T A

5 5

.

6

T A .

4

ACCEPTED MANUSCRIPT Table 2. List of common fish species that has been tested by using universal fish primer. English name

Common name

Family

1

Seriola rivoliana

Longfin Yellowtail

Escolar

Carangidae

2

Salmo salar

Atlantic Salmon

Salmon

Salmonidae

3

Abbottina rivularis

Ray finned fish

Chinese false gudgeon

Cyprinidae

4

Caranx ignobilis

Giant kingfish

Bagat

Carangidae

5

Seriola lalandi

Yellowtail amberjack

Aji-aji ekor kuning

Loricariidae

6

Esomus metallicus

Striped flying barb

Striped Flying Barb

Cyprinidae

7

Chitala lopis

8

Chaca bankanensis

9

Barbonymus gonionotus

10

Bagarius bagarius

11

Thunnus alalunga

12

Clarias fuscus

13

Anabas testudineus

14

Aplocheilus panchax

15

Barbonymus schwanenfeldii

16

Megalaspis cordyla

17

Catla catla

18

Channa marulius

19

Selaroides leptolepis

20

PT

Scientific name

Chitala

Notopteridae

Angler Catfish

Chacidae

Javanese barb

Cyprinidae

Devil catfish

Bhagar

Sisoridae

Yellow fin tuna

Tuna

Scombridae

Freshwater catfish

Magur

Clariidae

Climbing perch

Pepuyu or Koi

Anabantidae

Ray-finned fishes

White spot

Cyprinodontiformes

Tinfoil barb

Tinfoil barb

Cyprinidae

Mackerel

Mackerel

Scombridae

Catla

Pla kra ho or Catla

Cyprinidae

Snake head catfish

Taki or

Channidae

Yellow striped scad

Selar kuning

Carangidae

Cirrhinus molitorella

Mud Carp

Kap lumpur

Cyprinidae

21

Ctenopharyngodon idella

Grass carp

Kap rumput

Cyprinidae

22

Hampala macrolepidota

Hampala barb

Sebarau

Cyprinidae

23

Hemibagrus nemurus

Asian redtail catfish

River catfish

Bagridae

Angler Catfish

PT E

CE

AC

31 | P a g e

D

MA

NU

Silver barb

SC

Featherbacks or knifefishes

RI

No

Silver carp

Silver carp

Cyprinidae

Elongate ilisha

Elongate ilisha

Pristigasteridae

Rohu

Rohu

Cyprinidae

Lates calcarifer

Barramundi

Cock-up seaperch

Latidae

28

Leptobarbus hoevenii

Hoven's carp

River carp

Cyprinidae

29

Mugil cephalus

Flathead grey mullet

Bully mullet

Mugilidae

30

Mylopharyngodon piceus

Black carp

Black carp

Cyprinidae

31

Oreochromis aureus

Blue Tilapia

Tilapia

Cichlidae

32

Oreochromis mossambicus

Red Tilapia

Tilapia

Cichlidae

33

Oreochromis niloticus

PT

ACCEPTED MANUSCRIPT 24

Hypophthalmichthys molitrix

25

Ilisha elongata

26

Labeo rohita

27

Niloticus

Cichlidae

AC

CE

PT E

D

MA

NU

SC

RI

Niloticus

32 | P a g e

ACCEPTED MANUSCRIPT Table 3. Results of commercially processed fish products tested with DNA barcoding system.

Sample Information Product type

Fish Ball

Sample ID

Fish type

FB -1

Figo golden sea food ball

Surimi

Sample-7

FB-2

Kenko fried fish ball

Surimi

Sample-2

FB -3

Marine Ikan ball

Milk fish

Sample-12

FB -4

Pacific west popcorn fish

Surimi

Sample-10

Surimi

Sample-13

Figo marine fish ball

Sequencing sample ID

D E

PT

TC -1

Pink Perch Masala

Not mentioned

TC -2

King cup brand sardines in tomato sauce

Sardine

Sample-11

Mackerel

Sample-14

TC -3

Fish Filets

Species identification

Product description on label

FB-5

Tin & Canned

DNA barcoding Results

E C

C A

Ayam brand Mackerel sos tomato curry

Sample-8

TC-4

Ayam brand curry salmon

Salmon

Sample-17

FF-1

Pacific west fish fillets

Surimi

Sample-19

33 | P a g e

GenBank (Blast)

BOLD

Clarias gariepinus 287/295 (98%)

Clarias gariepinus (98%)

Oreochromis niloticus 285/295 (97%) Chanos chanos 287/295 (98%)

C S U

N A

M

I R

-

-

Mystus gulio 282/295 (95%)

Mystus gulio (97.53%)

Oreochromis sp. 285/295 (97%)

Oreochromis aureus (98.82%)

Leptobarbus hoevenii 293/295 (99%)

Leptobarbus hoevenii (98.01%)

Atule mate 293/295 (99%)

(+ ) Supposed to be (Theragra chalcogramma or Gadus chalcogramma Pallas) (+ ) Supposed to be (Theragra chalcogramma or Gadus chalcogramma Pallas)

No of mislabeling

4/5

Correctly labelled (+ ) Supposed to be (Theragra chalcogramma or Gadus chalcogramma Pallas) (+ ) Supposed to be (Theragra chalcogramma or Gadus chalcogramma Pallas)

Not mentioned

1/4

(+ ) Supposed to be (Sardinella longiceps)

Selaroides leptolepis 287/295 (98%)

Alepes Melanoptera (99.17%)

Oncorhynchus gorbuscha 288/295 (98%)

Oncorhynchus gorbuscha (98.73%)

Oreochromis mossambicus 253/256 (99%)

T P

Mislabeled

Oreochromis Niloticus (99.27%)

Correctly labelled

Correctly labelled

(+ ) Supposed to be (Theragra chalcogramma or Gadus chalcogramma Pallas)

2/5

ACCEPTED MANUSCRIPT

Fish Nuggets

Fish Chip

FF-2

Salmon fish fingers

Salmon

Sample-1

Salmon (Oncorhynchus gorbuscha) 291/295 (99%)

FF-3

Grilled mackerel scad

Mackerel

Sample-5

Megalaspis cordyla 291/295 (98.5%)

Megalaspis cordyla (100%)

Correctly labelled

FF-4

Pacific west corn flake fish fillets

Surimi

Sample-15

Sillago sihama 277/295 (94%)

-

(+ ) Supposed to be (Theragra chalcogramma or Gadus chalcogramma Pallas)

FF-5

First pride fish fillets

Marine ikan

Sample-6

FN -1

Subi tempura fish nuggets

Marine ikan

Sample-16

FN-2

Marina Fish Nuggets

Marine fish (specific names not given)

Sample-20

FN-3

Figo sea food tofu

Surimi

Sample-9

FN-4

Subi tempura fish bites

Surimi

Sample-18

FC-1

Kenko frozen fish Chip

Ikan (Specific name not mentioned)

FC-2

Yoki fish chip

Surimi

Sample-3

FC-3

Fish chip

Surimi

-

FC-4

Prawn chip

Prawn

-

34 | P a g e

PT

E C

C A

D E

Sample-4

Correctly labelled

SC

Barbonymus gonionotus 284/295 (97%) Decapterus maruadsi 289/295 (98%)

Decapterus maruadsi (98.23%)

Mastacembelus unicolor 249/255 (98%)

Mastacembelus erythrotaenia (98.43%)

Clarias gariepinus 289/295 (98%)

Clarias gariepinus (98.55%)

-

U N

A M

Cyprinus Pellegrini 291/295 (99%) Yellow Catfish (Hemibagrus nemurus) 286/295 (97%) Unsuccessful DNA extraction Unsuccessful DNA extraction

Cyprinus Pellegrini 291/295 (98.76%)

-

T P

I R

Nemipterus japonicas 282/295 (97%)

Correctly labelled

(+ ) Supposed to be marine fish

3\4

Correctly labelled

(+ ) Supposed to be (Theragra chalcogramma or Gadus chalcogramma Pallas) (+ ) Supposed to be (Theragra chalcogramma or Gadus chalcogramma Pallas) (+ ) Supposed to be (Eleutheronema tetradactylum)

-

-

-

-

1/2

ACCEPTED MANUSCRIPT Figure 1 1

2 3 4

(a) 5 6 7

8 9

10 11 12 13 14 15 16 17 18 19 L

PT

295 bp (Fish target) 141 bp (Endogenous control)

25 26 27 28 29

30 31 32 33 L

(c)

AC

CE

PT E

D

34 35 36 37 38 39 40 41 42 43 44 45 46

35 | P a g e

295 bp (Fish target)

141 bp (Endogenous control)

MA

NU

SC

20 21 22 23 24

RI

(b)

47 48 L

141 bp (Endogenous control)

ACCEPTED MANUSCRIPT Figure 2

(a) 1 2

3

4

5

6

7

8

9

10 11 12

13

L

PT

295 bp (Fish Target)

RI

141 bp (Endogenous control)

15

16

17

18

19

20

L

NU

14

SC

(b)

295 bp (Fish target)

AC

CE

PT E

D

MA

141 bp (Endogenous control)

36 | P a g e

ACCEPTED MANUSCRIPT Figure 3 FC-2 Hemibagrus nemurus (KM454860.1) Mystus gulio (KX455905.1) FB-4 FB-1 FN-4 Clarias gariepinus (KT001082.1) Clarias gariepinus (JF292320.1)

PT

FF-5 Nemipterus japonicus (HQ149888.1) Seriola rivoliana Seriolarivoliana(2)

RI

Decapterus maruadsi (KJ004518.1) TC-3

FF-3

SC

Selaroides leptolepis (KM522839.1)

Megalaspis cordyla (KM522836.1) TC-2

NU

Atule mate (KJ502045.1) FN-3

Mastacembelus armatus (KT944644.1) FF-2

MA

TC-4

Oncorhynchus gorbuscha (EF455489.1) Oncorhynchus gorbuscha (FJ998708.1) FB-6 FB-2

AC

CE

PT E

D

FF-1

37 | P a g e

Oreochromis niloticus (GU238433.1) Oreochromis niloticus (GU477631.1) FF-4 Sillago sihama (KR363150.1) FN-1 Barbonymus gonionotus (AB238966) TC-1 Leptobarbushoevenii (AP011286.1) FB-3 Chanos chanos (KX056933.1)(94) FC-1 Cyprinus pelligrarie (KJ511883.1) FN-2 Oreochromis mossambicus (EU751879.1)

ACCEPTED MANUSCRIPT

AC

CE

PT E

D

MA

NU

SC

RI

PT

Graphical abstract

38 | P a g e

ACCEPTED MANUSCRIPT Highlights Novel COI mini barcode (295bp) to authenticate fish species. It was validated against 33 fish and 15 non-fish species. It is suitable to be used as a universal fish positive control under mixed matrices. The screening of 22 Malaysian fish products revealed 55% fraud labelling.

AC

CE

PT E

D

MA

NU

SC

RI

PT

   

39 | P a g e