Biology subjects

De Barro, P. J.

Publications and source records attributed to De Barro, P. J..

3 recordsLinked to original sources

bioRxiv2025

Molecular resources for the stored grain Cryptolestes cryptic pest species (Coleoptera: Laemophloeidae)

Recent research activities relating to evolutionary genetics and molecular characterisation of the stored grain Cryptolestes (Ganglbauer) beetle pest species have revealed gaps in public DNA databases, and resulted in molecular diagnostic inconsistencies. This study reports on characterisation of the mitochondrial DNA cytochrome oxidase I (mtCOI) gene from specimens detected during biosecurity inspections at Australias border, and surveys of publicly available mtCOI gene sequences, for re-assessment of Cryptolestes species status. The results enabled clarification of a new putative C. sp. WTT-2016 species, and supported the close evolutionary relationships between C. ferrugineus (Stephens)/C. pusilloides (Steel and Howe), and between C. pusillus (Schonherr) and the previously identified C. sp. WTT-2013 cryptic species. Widespread confusion between C. ferrugineus, C. pusiolloides, C. pusillus and the two putative novel C. sp. WTT-2013 and C. sp. WTT-2016, highlighted the taxonomic challenge surrounding this beetle genus, while inter-specific genetic distances between C. spartii (Curtis)/C. corticinus (Reitter) suggested they belonged to the same species. Assembled and annotated mitochondrial DNA genomes (mitogenomes) of six Cryptolestes species via high throughput sequencing identified assembly errors associated with published mitogenomes of C. ferrugineus and C. turcicus (Grouvelle), and misidentification of C. pusillus. Based on re-evaluation of intra- and inter-specific genetic distances and congruence from phylogenetic inferences, we proposed a Cryptolestes species genetic gap at approximately 5% that could help with defining species boundaries. By reconciling these molecular incongruences, this study will contribute to improving agricultural biosecurity preparedness associated with the economically important Cryptolestes flat grain beetle species.

evolutionary biology↗

bioRxiv2020

A high-throughput amplicon sequencing approach for population-wide species diversity and composition survey

Management of agricultural pests requires an understanding of pest species diversity, their interactions with beneficial insects and spatial-temporal patterns of pest abundance. Invasive and agriculturally important insect pests can build up very high populations, especially in cropping landscapes. Traditionally, sampling effort for species identification involves small sample sizes and is labour intensive. Here, we describe a multi-primer high throughput sequencing (HTS) metabarcoding method and associated analytical workflow for a rapid, intensive, high-volume survey of pest species compositions. We demonstrate our method using the taxonomically challenging Bemisia pest cryptic species complex as examples. The whiteflies Bemisia including the tabaci species are agriculturally important capable of vectoring diverse plant viruses that cause diseases and crop losses. Our multi-primer metabarcoding HTS amplicon approach simultaneously process high volumes of whitefly individuals, with efficiency to detect rare (i.e., 1%) test-species, while our improved whitefly primers for metabarcoding also detected beneficial hymenopteran parasitoid species from whitefly nymphs. Field-testing our redesigned Bemisia metabarcoding primer sets across the Tanzania, Uganda and Malawi cassava cultivation landscapes, we identified the sub-Saharan Africa 1 Bemisia putative species as the dominant pest species, with other cryptic Bemisia species being detected at various abundances. We also provide evidence that Bemisia species compositions can be affected by host crops and sampling techniques that target either nymphs or adults. Our multi-primer HTS metabarcoding method incorporated two over-lapping amplicons of 472bp and 518bp that spanned the entire 657bp 3 barcoding region for Bemisia, and is particularly suitable to molecular diagnostic surveys of this highly cryptic insect pest species complex that also typically exhibited high population densities in heavy crop infestation episodes. Our approach can be adopted to understand species biodiversity across landscapes, with broad implications for improving trans-boundary biosecurity preparedness, thus contributing to molecular ecological knowledge and the development of control strategies for high-density, cryptic, pest-species complexes.

evolutionary biology↗

bioRxiv2019

Take out the rubbish - Removing NUMTs and pseudogenes from the Bemisia tabaci cryptic species mtCOI database

Identification of Bemisia tabaci cryptic whitefly species complex currently relies on molecular characterisation of the mitochondrial DNA cytochrome oxidase subunit I (mtCOI) partial gene, however, nuclear mitochondrial sequences (NUMTs), PCR-derived pseudogenes and/or poor sequence editing have hindered this effort. To-date, ca. 5,175 partial ([≥] 300bp) mtCOI sequences for species identification purposes have been reported. We reviewed ca. 10% of sequences representing the standard B. tabaci species complex mtCOI dataset. We found that 333 sequences (64.9%) were NUMTs, pseudogenes and/or affected by poor sequence quality. Amino acid pattern analyses of high throughput sequencing-derived mtCOI gene from 24 tabaci and non-tabaci species enabled differentiation between NUMTs/pseudogene-affected and likely real mtCOI sequences, and that the SSA4, SSA5/SSA8, AsiaII-2 and AsiaII_4 species were NUMTs/pseudogenes artefacts. Intra-specific uncorrected nucleotide distances (p-dist) from our up-dated dataset ranged from 0-1.98%, inter-specific p-dist within phylogenetic clades ranged between ca. 2.5 and 8%, and 8 and >19% for species between phylogenetic clades. Differentiating between closely related species could therefore utilise an average p-dist of 2.5%. Despite the smaller B. tabaci mtCOI dataset, six putative new species were identified. Adoption of our standardised workflow and up-dated mtCOI clean dataset could facilitate better diagnostics of B. tabaci and non-tabaci cryptic species.

evolutionary biology↗