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Efficiency of DNA Barcodes for Identification and Documenting Aquatic Insect Diversity in Rice Fields

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Efficiency of DNA Barcodes for Identification and Documenting Aquatic Insect Diversity in Rice Fields Tropical Natural History 20(2): 169–181, August 2020 2020 by Chulalongkorn University Efficiency of DNA Barcodes for Identification and Documenting Aquatic Insect Diversity in Rice Fields PAIROT PRAMUAL1*, ISARA THANEE1, YANNAWUT UTTARUK1, JIRAPORN THAIJARERN1, KOMGRIT WONGPAKAM2 1Department of Biology, Faculty of Science, Mahasarakham University, Maha Sarakham 44150, THAILAND 2Walai Rukhavej Botanical Research Institute, Mahasarakham University, Maha Sarakham 44150, THAILAND * Corresponding author. Pairot Pramual ([email protected]) Received: 31 January 2019; Accepted: 23 March 2020 ABSTRACT.– Rapid and accurate identifications are crucial for biodiversity assessment. Yet, traditional methods for species identification have some limitations. In this study, we tested the efficiency of mitochondrial cytochrome c oxidase I barcoding sequences for species identification and documenting diversity of aquatic insects in the rice fields of Thailand. Considerable success rate (80%) for species identification was found among the species of the order Odonata. Unidentifiable specimens of immatures were successfully associated with conspecific adults or by matching with reference sequences in the public DNA barcoding library. However, some specimens were ambiguous, possibly due to incomplete lineage sorting of closely related species or erroneous identification of the sequences in the public database. The technique was less successful for other insect orders because a lack of reference sequences in the DNA barcode library limits the utility of DNA barcoding. The Poisson tree process and Automatic Barcode Gap Discovery species delimitations revealed that the number of species recognized is more than twice that based on morphological identification. Therefore, DNA barcoding has potential for use in species identification and biodiversity assessment of the aquatic insects in the rice field ecosystem. KEY WORDS: biodiversity, COI, rice field, species delimitation other inappropriate managements could INTRODUCTION reduce biodiversity in agricultural ecosystems (Wilson et al., 2008; Watanabe et al., 2013). Rice fields are an important artificial Thus, information regarding species diversity wetland ecosystem possessing different in the rice field is needed for monitoring as categories of the environmental conditions well as appropriate management. and providing habitats for different faunas Aquatic insects are among the major (Lawler, 2001; Bambaradeniya and components of the rice field faunas and play Amerasinghe, 2003). Diverse groups of diverse roles in this ecosystem. For organisms from microbial, fungi, plankton example, members of the order Odonata are and macroinvertebrates to large vertebrates the major predator while the orders Diptera, such as fishes, snakes and birds utilize this Coleoptera and Lepidoptera are largely pests artificial ecosystem (Edirisinghe and of the rice (Bambaradeniya et al., 2004). In Bambaradeniya, 2010). It has been found addition, aquatic insects could also have that biological diversity is positively related applications as bioindicators of the with the productivity of agricultural ecosystem (Federico Rizo-Patrón et al., ecosystems (Roger et al., 1991; Scherr and 2013). Therefore, understanding taxonomy McNeely, 2008; Tscharntke et al., 2012). and biodiversity of these insects is important However, using chemical pesticides and for applications as well as appropriate and 170 TROPICAL NATURAL HISTORY 20(2), AUGUST 2020 sustainable management of the rice field document species diversity in the rice field ecosystem. ecosystem in northeastern Thailand. The traditional method of species identification based on morphological MATERIALS AND METHODS characters has some limitations such as incomplete taxonomic knowledge, high Specimen collection and identification intraspecific morphological variation, a lack Insects were collected from the eight rice of valid morphological characters for fields in four provinces in northeastern species recognition of particular life stages Thailand between September and November and damaged specimens. Beside these 2017 (Table 1). Specimens were collected limitations, insufficient expertise or lack of using the kick-sampling method with a 500- an expert who has experience in the μm mesh hand net. Adult flying insects taxonomy of relevant insect groups also were collected using a sweep net along a present major obstacles. One possible way line transect across the rice field. To to solve these issues is using the DNA compare the efficiency of DNA barcoding barcode. Although there are also some with morphological taxonomy in real limitations of using molecular genetic data practice (i.e. when monitoring / examining for species identification (Frézal and species diversity in the rice field, which Leblois, 2008) this method has more usually involves people who are not an advantages compared to traditional expert in particular insect groups), taxonomy (Sweeney et al., 2011, Gill et al., identifications of the specimens were carried 2013). DNA barcoding has been used out by university students who had skills at successfully for species identification and the taxonomic level of order / family of documenting biodiversity of many insect aquatic insects. Specimens were identified groups (Rach et al., 2008; Damm et al., using the available keys and descriptions of 2010; Jinbo et al., 2011; Sweeney et al., the aquatic insects in Thailand (Sangpradub 2011; Jackson et al., 2014). Thus, this DNA and Boonsoong, 2006; Boonsoong, 2014; marker can potentially be used for Sangpradub, 2016). identification and documenting species DNA extraction, polymerase chain reaction diversity of rice field aquatic insects. (PCR) and sequencing Thailand is the major rice exporting Genomic DNA was extracted from larva, country. Approximately 18% (about 9 nymph or soft tissue part of the adult using million hectares) of the land is used for rice the Genomic DNA Extraction mini kit (GF- cultivation (http://www.ricethailand.go.th). 1 Tissue DNA Extraction Kit, Vivantis, However, data on biodiversity of the insects Selangor Darul Ehsan, Malaysia). Polymerase in rice fields is scanty due largely to the lack chain reactions (PCR) were conducted for of the taxonomic knowledge. In this study, cytochrome c oxidase subunit I (COI) using we used DNA barcoding sequences to test primers LCO1490 (5′-GGTCAACAAATC the efficiency of this molecular marker for ATAAAGATATTGG-3′) and HCO2198 (5′- species identification using public DNA TAAACTTCAGGGTGACCAAAAAATCA- barcode libraries (i.e. BOLD and GenBank). 3′) (Folmer et al., 1994). PCR reaction and We also used the species delimitation conditions followed the method of Rivera approach based on the mitochondrial and Currie (2009). Agarose gel electrophoresis cytochrome c oxidase I (COI) sequence to PRAMUAL ET AL. — DNA BARCODES FOR AQUATIC INSECT DIVERSITY IN RICE FIELDS 171 TABLE 1. Sampling locations of the aquatic insects used in this study Location Code Latitude / Longitude Date Yang Ta Lad, Kalasin Province KS1 16° 29' 13" N/103° 12' 42" E 30 Sep 2017 Khao Wong 1, Kalasin Province KS2 16° 38' 22" N/104° 08' 39" E 07 Oct 2017 Khao Wong 2, Kalasin Province KS3 16° 32' 09" N/104° 07' 15" E 07 Oct 2017 Yang Sisurat 1, Maha Sarakham Province MK1 15° 40' 23" N/103° 09' 48" E 28 Oct 2017 Yang Sisurat 2, Maha Sarakham Province MK2 15° 36' 15" N/103° 09' 41" E 28 Oct 2017 Na Dun, Maha Sarakham Province MK3 15° 41' 00" N/103° 14' 10" E 28 Oct 2017 Mueang Amnat Charoen, Amnat Charoen Province AM 15° 49′ 03′′ N/104° 37′ 48′′ E 4 Nov 2017 Prangku, Si Sa Ket Province SK 14° 48′ 59′′ N/104° 04′ 00′′ E 23 Oct 2017 was used to check the PCR products. The thinning value of 100 and 10% burn-in. In HiYield Gel/PCR DNA Extraction Kit addition to the tree-based (i.e. PTP) we also (RBC BIOSCIENCE, Taiwan) was used to used a distance-based species delimitation purified the PCR products and send for method called Automatic Barcode Gap sequencing at 1st Base sequencing service Discovery (ABGD) (Puillandre et al., 2012). (Malaysia) using the same primers as in the ABGD analysis was performed in web PCR. server version (https://bioinfo.mnhn.fr/abi/ Data analysis public/abgd/abgdweb.html). Criteria setting A total of 98 sequences were included in for ABGD analysis as follow: prior range data analyses. Sequences were deposited in for maximum intraspecific divergence GenBank under accession numbers: (0.001, 0.1), minimum slope increase (X) of MH881228–MH881247 and MH881249– 1.0 and genetic distance calculated based on MH881326. To assess the species identification K80 corrected distances. based on COI DNA sequence data, the To indicate phylogenetic relationships “identification” menu with “Species Level between sequences of the rice field insects Barcode Records” option in Barcoding of included in this study, three methods of Life Data Systems (http://v4.boldsystems.org) phylogenetic analyses were conducted was used. In addition, we also used the including the neighbor-joining (NJ) tree, the Poisson tree processes (PTP) (Zhang et al., maximum likelihood (ML) and the Bayesian 2013) to delimit species of rice field insects analysis (BA). Because specimens were and to investigate hidden diversity in from distantly related taxa, the phylogenetic morphological species. The maximum trees were analyzed separately for likelihood tree was inferred in the RAxML specimens from each order (i.e. Odonata, web server version (https://embnet.vital- Ephemeroptera and Hemiptera). The NJ it.ch/raxml-bb/) (Stamatakis et al., 2008).
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