Literature DB >> 35774258

Metabarcoding of Fish Larvae in the Merbok River Reveals Species Diversity and Distribution Along its Mangrove Environment.

Norli Fauzani Mohd Abu Hassan Alshari1, Siti Zuliana Ahmad1, Azali Azlan1, Youn-Ho Lee2, Ghows Azzam1, Siti Azizah Mohd Nor1,3.   

Abstract

The Merbok River (north-west of Peninsular Malaysia) is a mangrove estuary that provides habitat for over 100 species of fish, which are economically and ecologically important. Threats such as habitat loss and overfishing are becoming a great concern for fisheries conservation and management. The identification of larval fish in this estuarine system is important to complement information on the adults. This is because the data could inform the spawning behaviour, reproductive biology, selection of nursery grounds and migration route of fish. Such information is invaluable for fisheries and aquatic environmental monitoring, and thus for their conservation and management. However, identifying fish larvae is a challenging task based only on morphology and even traditional DNA barcoding. To address this, DNA metabarcoding was utilised to detect the diversity of fish in the Merbok River. To complete the study, the fish larvae were collected at six sampling sites of the river. The extracted larval DNA was amplified for the Cytochrome Oxidase subunit 1 (COI) and 12S ribosomal RNA (12S rRNA) genes based on the metabarcoding approach using shotgun sequencing on the next-generation sequencing (NGS) Illumina MiSeq platform. Eighty-nine species from 65 genera and 41 families were detected, with Oryzias javanicus, Oryzias dancena, Lutjanus argentimaculatus and Lutjanus malabaricus among the most common species. The lower diversity observed from previous morphological studies is suggested to be mainly due to seasonal variation over the sampling period between the two methods and limited 12S rRNA sequences in current databases. The metabarcode data and a validation Sanger sequencing step using 15 species-specific primer pairs detected three species in common: Oryzias javanicus, Decapterus maruadsi and Pennahia macrocephalus. Several discrepancies observed between the two molecular approaches could be attributed to contaminants during sampling and DNA extraction, which could mask the presence of target species, especially when DNA from the contaminants is more abundant than the target organisms. In conclusion, this rapid and cost-effective identification method using DNA metabarcoding allowed the detection of numerous fish species from bulk larval samples in the Merbok River. This method can be applied to other sites and other organisms of interest.

Entities:  

Keywords:  DNA metabarcoding; Fish larvae; Mangrove estuary; Merbok River; Next-generation sequencing

Year:  2021        PMID: 35774258      PMCID: PMC9169113          DOI: 10.6620/ZS.2021.60-76

Source DB:  PubMed          Journal:  Zool Stud        ISSN: 1021-5506            Impact factor:   1.904


  40 in total

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Journal:  Proc Biol Sci       Date:  2003-02-07       Impact factor: 5.349

2.  Quantification of the detrimental effect of a single primer-template mismatch by real-time PCR using the 16S rRNA gene as an example.

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Journal:  Ecol Lett       Date:  2013-08-04       Impact factor: 9.492

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Authors:  Gentile F Ficetola; Johan Pansu; Aurélie Bonin; Eric Coissac; Charline Giguet-Covex; Marta De Barba; Ludovic Gielly; Carla M Lopes; Frédéric Boyer; François Pompanon; Gilles Rayé; Pierre Taberlet
Journal:  Mol Ecol Resour       Date:  2014-11-10       Impact factor: 7.090

5.  Error filtering, pair assembly and error correction for next-generation sequencing reads.

Authors:  Robert C Edgar; Henrik Flyvbjerg
Journal:  Bioinformatics       Date:  2015-07-02       Impact factor: 6.937

6.  DNA barcoding Australia's fish species.

Authors:  Robert D Ward; Tyler S Zemlak; Bronwyn H Innes; Peter R Last; Paul D N Hebert
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2005-10-29       Impact factor: 6.237

7.  DNA Metabarcoding of Amazonian Ichthyoplankton Swarms.

Authors:  M E Maggia; Y Vigouroux; J F Renno; F Duponchelle; E Desmarais; J Nunez; C García-Dávila; F M Carvajal-Vallejos; E Paradis; J F Martin; C Mariac
Journal:  PLoS One       Date:  2017-01-17       Impact factor: 3.240

8.  Automated high throughput animal CO1 metabarcode classification.

Authors:  Teresita M Porter; Mehrdad Hajibabaei
Journal:  Sci Rep       Date:  2018-03-09       Impact factor: 4.379

Review 9.  Prospects and challenges of implementing DNA metabarcoding for high-throughput insect surveillance.

Authors:  Alexander M Piper; Jana Batovska; Noel O I Cogan; John Weiss; John Paul Cunningham; Brendan C Rodoni; Mark J Blacket
Journal:  Gigascience       Date:  2019-08-01       Impact factor: 6.524

10.  DNA metabarcoding and morphological macroinvertebrate metrics reveal the same changes in boreal watersheds across an environmental gradient.

Authors:  Caroline E Emilson; Dean G Thompson; Lisa A Venier; Teresita M Porter; Tom Swystun; Derek Chartrand; Scott Capell; Mehrdad Hajibabaei
Journal:  Sci Rep       Date:  2017-10-06       Impact factor: 4.379

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