A rapid insect species identification system using mini‐barcode pyrosequencing

Hsieh, Chi-Hsun; Huang, Chien‐Ling; Wu, Wen‐Jer; Wang, Hurng‐Yi

doi:10.1002/ps.5674

Cited by 7 publications

(4 citation statements)

References 30 publications

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“…Traditional identification of GWF is based on morphological traits, which has several drawbacks, including reliance on expert taxonomists, time-consuming, low resolution in presence of conspecific character, presence of cryptic population, and ergonomic issues 15 – 17 . DNA barcoding-based species identification utilizing mitochondrial cytochrome C oxidase subunit I (mtCOI) offers rapid, reliable detection and study of genetic variation among GWF 18 .…”

Section: Introductionmentioning

confidence: 99%

Unravelling geospatial distribution and genetic diversity of greenhouse whitefly, Trialeurodes vaporariorum (Westwood) from Himalayan Region

Paschapur¹,

Singh²,

Buski³

et al. 2023

Sci Rep

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The Greenhouse whitefly (GWF), Trialeurodes vaporariorum (Westwood) (Hemiptera: Aleyrodidae), is a destructive pest that affects protected cultivation worldwide. The Indian Himalayan region is particularly vulnerable to GWF introduction, invasion, and spread due to the expansion of protected cultivation and climate change. In this study, we collected 32 naturally occurring GWF populations, mainly from the Uttarakhand state in the Indian Himalayan region, to investigate the distribution pattern and genetic diversity of T. vaporariorum. Our sampling was representative of the region's vegetation diversity and geographical location, and we collected samples from multiple sites within each locality to account for local variations. The mtCOI gene was used to accurately detect and identify GWF and to sequence haplotypes prevalent in the Uttarakhand state. The maximum likelihood method used for phylogenetic studies revealed that all 32 whitefly samples in this study belonged to T. vaporariorum and were prevalent in all the collected localities. Our population genetic study using mtCOI showed variation within T. vaporariorum populations, with 20 distinct haplotypes present. Notably, haplotype 2 (H2) was the most dominant haplotype among the sampled populations. These results provide fundamental knowledge for understanding the geographical distribution and ecology of T. vaporariorum in the Uttarakhand state of the Indian Himalayan region. The discovery of geospatial and genetic diversity of GWF in the Himalayan region underscores the importance of pest alertness, research prioritization, and the development of sustainable management strategies to protect crops.

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Section: Introductionmentioning

confidence: 99%

Unravelling geospatial distribution and genetic diversity of greenhouse whitefly, Trialeurodes vaporariorum (Westwood) from Himalayan Region

Paschapur¹,

Singh²,

Buski³

et al. 2023

Sci Rep

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“…al., 2013). Just as Hsieh et al (2020) observed that their 16S minibarcode system had resolution for species identification universality. Whereas Glover et.…”

Section: Resultsmentioning

confidence: 99%

Molecular Characterization of Thripidae (Thysanoptera) Species in Karaman, Konya and Mersin (Turkey)

Negiş

İkten²,

Ünlü³

et al. 2022

SJAFS

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Specimens of Thripidae (Thysanoptera) species collected from Konya, Karaman and Mersin (2015-2017) were studied through molecular analyses as a part of preliminary attempts to establish a barcoding system for Thysanoptera in Turkey. The analyses included 23 species namely; Chirothrips kurdistanus zur Strassen, Chirothrips manicatus Haliday, Frankliniella intonsa (Trybom), Frankliniella occidentalis (Pergande), Frankliniella tenuicornis (Uzel), Limothrips angulicornis Jablanowski, Odontothrips confusus Priesner, Odontothrips dorycnii Priesner, Oxythrips ajugae Uzel, Taeniothrips inconsequens (Uzel), Tenothrips anatolicus (Priesner), Tenothrips discolor (Karny), Tenothrips frici (Uzel), Thermothrips mohelensis Pelikan, Thrips angusticeps Uzel, Thrips atratus Haliday, Thrips italicus Bagnall, Thrips linarius Uzel, Thrips major Uzel, Thrips meridionalis (Priesner), Thrips physapus Linnaeus, Thrips tabaci Lindeman and Thrips trehernei Priesner which were detected in various cultivated plants and weeds. The phylogenetic positions of the 9-genera, with few exceptions, to form their own clades by the 18S Ribosomal RNA data on the NJ tree. The 18S data were discussed for the first time for Th. linarius, Th. angusticeps, Th. italicus, Th. meridionalis, Th. physapus, F. tenuicornis, Ch. kurdistanus, Te. anatolicus, Te. discolor, Ther. mohelensis and Ox. ajugae species. Clearly results from the COI dataset in a single UPGMA tree separated the genera. The COI data of Li. angulicornis, Te. anatolicus, Od. confusus, Od. dorycnii Th. angusticeps, Th. atratus, Th. italicus, Th. linarius and Th. meridionalis were obtained for the first time by this study.

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“…Mini-barcoding by pyrosequencing has been used for species-level identification of Thrips spp. [ 208 ]. A universal primer pair for the 16S rDNA gene yields an amplicon of 120 bp.…”

Section: Pcr-based Identification Of Thrips Using Molecular Markersmentioning

confidence: 99%

Frontiers Approaches to the Diagnosis of Thrips (Thysanoptera): How Effective Are the Molecular and Electronic Detection Platforms?

Ghosh

Jangra

Dietzgen

et al. 2021

Insects

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Thrips are insect pests of economically important agricultural, horticultural, and forest crops. They cause damage by sucking plant sap and by transmitting several tospoviruses, ilarviruses, carmoviruses, sobemoviruses, and machlomoviruses. Accurate and timely identification is the key to successful management of thrips species. However, their small size, cryptic nature, presence of color and reproductive morphs, and intraspecies genetic variability make the identification of thrips species challenging. The use of molecular and electronic detection platforms has made thrips identification rapid, precise, sensitive, high throughput, and independent of developmental stages. Multi-locus phylogeny based on mitochondrial, nuclear, and other markers has resolved ambiguities in morphologically indistinguishable thrips species. Microsatellite, RFLP, RAPD, AFLP, and CAPS markers have helped to explain population structure, gene flow, and intraspecies heterogeneity. Recent techniques such as LAMP and RPA have been employed for sensitive and on-site identification of thrips. Artificial neural networks and high throughput diagnostics facilitate automated identification. This review also discusses the potential of pyrosequencing, microarrays, high throughput sequencing, and electronic sensors in delimiting thrips species.

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A rapid insect species identification system using mini‐barcode pyrosequencing

Cited by 7 publications

References 30 publications

Unravelling geospatial distribution and genetic diversity of greenhouse whitefly, Trialeurodes vaporariorum (Westwood) from Himalayan Region

Unravelling geospatial distribution and genetic diversity of greenhouse whitefly, Trialeurodes vaporariorum (Westwood) from Himalayan Region

Molecular Characterization of Thripidae (Thysanoptera) Species in Karaman, Konya and Mersin (Turkey)

Frontiers Approaches to the Diagnosis of Thrips (Thysanoptera): How Effective Are the Molecular and Electronic Detection Platforms?

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