A brief inventory of bruchids (Chrysomelidae, Bruchinae) and similar pest beetles occurring on peas in the Republic of Congo: barcoding and prospects

A brief inventory of bruchids (Chrysomelidae, Bruchinae) and similar pest beetles occurring on peas in the Republic of Congo: barcoding and prospects | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article A brief inventory of bruchids (Chrysomelidae, Bruchinae) and similar pest beetles occurring on peas in the Republic of Congo: barcoding and prospects Mireille Belle Mbou Okassa, Matito Mavanga Mabika, Valentin Dibangou, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3617667/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 5 You are reading this latest preprint version Abstract The seed beetles of the family Chrysomelidae, subfamily Bruchinae, are pest species that cause substantial damage to legume crops, affecting supply for human and animal consumption. Legumes are a staple of the Congolese population due to their protein-rich seeds, productivity, and ability to improve soil fertility when combined with cereals. In this study, we focused on bruchids that attack two varieties of peas, Cajanus cajan and Vigna unguiculata subsp. cylindrica , in the Republic of Congo. 80 individuals of bruchids were considered from the two main pea-growing departments: Bouenza and Niari. Specimens were collected using baited traps placed in the field and by manually selecting affected seeds from the storage areas. Individuals were categorised at the species level based on morphological traits and molecular barcode analyses. This is the second time that 12S rRNA sequences of bruchids from the Republic of Congo have been deposited in the GenBank database. This study emphasises the need to enrich the GenBank database with DNA sequences originating from areas where the technical means to carry out quality morphological analyses are limited. Bruchine species peas storage areas 12S rRNA genetic distance methods Figures Figure 1 Introduction Domestic Fabaceae cultivars, such as groundnuts, beans, and peas, are the most vulnerable to infestation by bruchids. In the Republic of Congo (RC), the production of these legumes is primarily a traditional concern, wherein most producers are smallholders grouped in agricultural cooperatives or family communities and maintain relatively low productivity. Some of the most important factors limiting the productivity of Congolese agriculture are 1) the absence of crop protection systems and 2) the high level of post-harvest losses. These two factors result in consistently low yields, forcing the local markets to import legumes from Cameroon and consequently increase their prices. Post-harvest losses (fruit weight loss, reduced nutritional value, and impeded germination capacity) are mainly caused by small Coleoptera belonging to the Chrysomelidae family (Borowiec 1987; Delobel 2000; Keneni et al. 2011) . The most economically damaging genera are Acanthoscelides , Bruchidius , Bruchus , Callosobruchus , Caryedon , and Zabrotes (Johnson 1981, Huignard et al. 2011) . The affected seeds become unfit for human (1-3% threshold) and animal (10%) consumption and are unviable for planting due to reduced germination capacity. Although legume growers have difficulty estimating the level of crop loss to bruchids, it is generally claimed that insects cause the most damage to reserve stocks (Boxall 1986) . A necessary prerequisite to reduce post-harvest losses and improve biosecurity is establishing an accurate database of Chrysomelidae pests that affect economically important legumes (FAOSTAT, 2010). For decades, morphospecies have been identified exclusively using morphological diagnostics provided by taxonomic studies (Borowiec 1987) . This identification method requires specialised skills that are often acquired through long-term experience that only experts, such as taxonomists and qualified technicians, possess (Raupach et al. 2010). In view of the decreasing number of experts (Agnarsson and Kuntner 2007) and the loss of biodiversity, an alternative method is needed to rapidly collate biodiversity inventories and allow species identification by non-specialists. Hebert et al. (2003) proposed a morphospecies identification method using a short mitochondrial DNA sequence. This tool makes it possible to identify insect species in their developmental stages (Bakhoum et al. 2018), morphospecies without sufficient discriminating characteristics, and cryptic species. The scientific value of barcoding has been shown in the biomonitoring of several insect pests that cause significant economic damage to important crops worldwide (Boykin et al. 2012; Ashfaq and Hebert 2016). Some authors have tested tested the effectiveness of mitochondrial cytochrome c oxidase gene I (COI) on nearly 7,237 sequences, representing 542 species of Chrysomelidae (Magoga et al. 2018). The barcoding efficiency was 94%, and 6% of the sequences were misidentified. Other molecular markers have been successfully developed since the article of Hebert et al. (2003) was published (Hebert et al. 2003), including 12S rRNA, Cytb, and ITSS (Tixier et al. 2006; Okassa et al. 2009, 2010; M Hernández-Triana et al. 2019). From in 2021 (Dibangou et al. 2021) , scientific studies began using barcoding to assess the biodiversity and distribution of insects belonging to the Chrysomelidae family in Congo. , In fact, until recently, the only data available came from reports carried out by the Ministry of Scientific Research and the French Institute of Scientific Research for Development in Cooperation (Delobel and Epouna-Mouinga 1984) with a pre-survey was conducted in the Bouenza region on Farmers' storage structures in the RC. The following points were highlighted in these reports: : The samples collected had an average seed weight of between 100 and 200 g. First, the species Callosobruchus maculatus was identified on the Cajuns cajan pea variety from the department of Madingou. Secondly, of the three samples collected (two from Mouyondi and one from Loudima) three species C. maculatus, Callosobruchus rhodesianus and last Bruchidius atrolineatus were identified avec les proportions de two thirds, two thirds and one third respectively. In another report by Delobel in 1984, he states that C. maculatus is the most common bruchid species on all the leguminous varieties grown in the department of Bouenza , only the Psophocarpus tetragonolobus variety has proved resistant to its development (Delobel 1984). A recent study has been published on the diversity of cytochrome oxidase 1 insect pests of peas and beans. The method used is phylogenetic reconstruction (Roy et al. 2023). In our study we are interested in the biodiversity of insect pests on two pea varieties. To achieve this goal, we will use the genetic distance method with the 12S rRNA marker. We believe that the use of markers other than COI would enrich the database, making multilocus barcoding more accessible and speeding up the biodiversity inventory. Our study focused on the identification by the 12S rRNA fragment of the bruchids that attack two pea varieties in RC: Cajanus cajan and Vigna unguiculata subsp. cylindrica . These two varieties are widely consumed by the Congolese population. Methods Bruchids survey A random sampling of different populations of bruchid species was carried out from April 2019 to August 2019 in the departments of Niari and Bouenza (Table 1, Fig. 1 ). In this study 80 individuals were considered. The random sampling is a method of randomly and independently taking 'n' sample units from a population of 'N' elements. The samples are distributed randomly. Each point in the space studied therefore has an equal chance of being sampled. The data collected in this way are not biased. For this study, eight plots of pea fields were selected at each locality with a minimum distance of 4 km between plots. Twelve yellow sticking traps were set up on each plot. Traps were checked once per week, and bruchid-like beetles were collected manually. Individuals were collected from seed-baited traps and crop storage areas. The samples were placed in closed plastic containers with a paper towel soaked in ethyl acetate for 24 h. This procedure prevents the specimens from becoming rigid. Specimens were then labelled according to plot location and preserved in 70% ethanol for morphological analysis and 95% ethanol for molecular analysis. Morphological analyses Each bruchid specimen was placed on a Petri dish lid and observed under a Leica MZ6 modular stereomicroscope (Leica Microsystems GmbH, Wetzla, Germany). Specimens were classified using species identification keys (Kingsolver et al. 2017 ). Molecular analyses DNA extraction Total genomic DNA was extracted from 20 individuals, 10 and 10 from Bouenza and Niari. The total DNA was purified using the spin-column protocol (Qiagen, Hilden, Germany). In this protocol, insects are frozen in liquid nitrogen and then ground with a mortar and pestle or disposable microtube pestle, or homogenised using the Tissue Ruptor (Qiagen), an equivalent electric homogeniser. Samples were then processed using the DNeasy® Blood & Tissue Kit (Qiagen). DNA elution was performed in Tris-acetate-EDTA (TAE) instead of water. DNA amplification and sequencing The 12S rRNA mitochondrial fragments were amplified and sequenced. The primers used for amplification of the 12S rRNA gene were 12S-F 5′-TACTATGTTACGACTTAT-3‘ and 12S-R 5′-AAACTAGGATTAGATACCC-3′ (Tixier et al. 2006 ; Okassa et al. 2009 , 2010 ; M Hernández-Triana et al. 2019 ). The amplification reactions for 12S fragments were carried out with Dr. MAX DNA Polymerase (Doctor protein INC, Korea, cat.no.: DR00302). A Bio-Rad DNA Engine Tetrad 2 Peltier Thermal Cycler (Bio-Rad Laboratories, Inc., Hercules, CA, USA) was used for PCR amplification. To amplify the 12S rRNA fragments, samples were denatured at 95°C for 1 min, followed by 40 cycles of denaturation at 94°C for 30 s, annealing at 40°C for 30 s, extension at 72°C for 1 min, and a final step at 72°C for 5 min. After amplification, 5 µL of the PCR reaction was analysed by 1% agarose gel electrophoresis running for 20 min at 300 V, 200 A, and 2 µL of DNA loaded. PCR products were purified using a Multiscreen filter plate (MilliporeSigma, Burlington, MA, USA). The amplified 12S rRNA fragments containing visible and single bands were directly sequenced using an ABI PRISM 3730XL Analyser (96 capillary type) with a BigDye® Terminator ver. 3.1 Cycle Sequencing Kit (Applied Biosystems, Waltham, MA, USA) DNA Blast The Geneious Prime 2019.2 (Raupach et al. 2010 ) was used to correct and assemble the raw data into sequence contigs. The assignment of each query sequence was performed using the local basic alignment search tool (MegaBLAST) on an external NCBI database. An aligned set of potentially related sequences were obtained, ranked according to their similarity. This similarity takes into account different parameters, with the most relevant being the bit score, E-value, percent identity, and grade (Okassa et al. 2020 ; Dibangou et al. 2021 ). Sequence variation and divergence analysis To the obtained sequence data set were added three sequences of C. maculatus , with two sequence de C. maculatus from the department of Bouenza accidentally identified on the bean (Dibangou et al. 2021 ) and one sequence from the country of Senegal (Kergoat et al. 2005 ). In last, one sequence of Bruchus pisorum from the country of Italy (Kergoat et al. 2007 ) was considered as outgroup species. The sequences were aligned using the MUSCLE alignment procedure with gap penalities, iteration and clustering method (Edgar 2004 ). An analysis zone was defined from sites 17 to 402 in order to consider only the same number of character states for all the sequences studied, either 386 sites. The best sequence evolution model of 24 models was determined using Molecular Evolution Genetics Analysis (MEGA) version 11 (Tamura et al. 2021 ) with maximum likelihood (Kumar et al. 2016 ). Models with the lowest Bayesian Information Criterion (BIC) scores were considered to best describe the substitution pattern. The corrected Akaike information criterion, maximum likelihood value (ML), and number of parameters (including branch length) were included in each model (Nei et al. 2000 ).The non-uniformity of evolutionary rates among sites were modelled using a discrete Gamma distribution (+ G) with 5 rated categories, assuming that a certain fraction of the sites are evolutionarily invariable (+ I). Whenever applicable, estimates of the gamma shape parameter and/or the estimated fraction of invariant sites were reported. MEGA 11 was employed also to analyze nucleotide composition, conserved sites, variable sites, singleton sites and parsimony-informative sites (Tamura et al. 2021 ). At last, analyses estimates of evolutionary divergence between sequences were conducted using the Tamura 3-parameter model (Tamura 1992 ). The rate variation among sites was modeled with a gamma distribution (shape parameter = 1). Genetic diversity Evaluation of the number of haplotypes and haplotype diversity between all populations considered were performed using DnaSP software version 6.12 (Librado and Rozas 2009 ). Results and discussion Morphological analyses The use of an identification key allowed us to assign each individual to a specific rank (Kingsolver et al. 2017 ). Individuals belonging to Callosobruchus maculatus because they have the following two characteristics 1) hind femur with a spine or denticles on both latero ventral and mesoventral carinae and 2) Elytral stria originating at basal margin and lacking denticles or gibbosity. A second species belonging to the Curculionidae family was identified, she is characterised by the presence of a rostrum extended beyond the eyes, with mouth parts situated at its apex. This morphological trait is one of the most typical features of the family of Curculionidae. Molecular analyses Sequence variation Fragments of 423 bp were aligned for 12S rRNA and contained 344 conserved, 76 variables, 31 parsimony-informative, and 40 singleton sites. All new sequences herein obtained have been deposited in GenBank and are shown in Table 2. Genetic distances Mean genetic Tamura 3 parameter (substitutions models) and evolutionary rates among sites (+ G = discrete gamma) distances (minimum and maximum values) within and between all populations studied with outgroup species B. pisorum for 12S rRNA are shown in Table 2 First, the genetic distances between the populations of C. maculatus originating from different localities in Congo were very small and had little variation (0–0.8% with a mean of 0.2%). This low genetic variability can be explained by host plants (pea variety) occurring in similar climatic conditions (temperature and hygrometry) between Bouenza and Niari. In addition, little genetic divergence was found between C. maculatus collected from pea and C. maculatus collected from bean (0–1.5% with an mean of 0.6%). The genetic distances between C. maculatus populations originating from the Republic of Congo and those from Senegal were greater and varied between 3.3–4.2%, which corresponds to interspecific variation. For example, for Acanthoceslides obtectus , which are in the same family, the mean intrapecific variation was 0 and 0.62% for specimens from Bouenza and Niari. The host plant and climatic differences between these two countries could explain this variability. Second, the genetic distances between C. maculatus populations and the population comprising individual 26 belonging to the Curculionidae family were 12.7%, showing interspecific variation at a threshold greater than 3%. These results confirm our morphological observations and support the presence of another important biological pest, belonging to an other family. A last, a comparison of the DNA sequence of B. pisorum from Italy, retrieved from GenBank, was performed. The genetic distances between the different populations of C. maculatus and B. pisorum varied from 13.9 to 16.4%, and corresponded to interspecific variation . Except for the case of C. maculatus from Senegal,, the assignment of each individual adhered to two principles of the barcode: that 1) intraspecific variation was less than interspecific variation and 2) the absence of overlap between intra- and interspecific variation (presence of a gap) (Hebert et al. 2003 ). Haplotypic diversity Nine haplotypes were identified in the study species (Table 2), with significant haplotype diversity (Hd = 0.8182). With regards to our sample size, the number of distinct haplotypes and the degree of haplotype diversity showed a high degree of haplotype differentiation in the beetles in our dataset. The results of this study were similar to those obtained by other authors hypothesised, based on their results, that natural selection, particularly frequency dependent selection, could play a role in the differentiation of mitochondrial genetic variation by maintaining within C. maculatus populations a variation of mitochondrial DNA haplotypes (Tuda et al. 2014 ). Conclusion This study has demonstrated the potential role of integrative taxonomy (Morphological and molecular analyses) in classifying important pest species belonging to the Chrysomelidae family and confirmed their presence in domestic pea varieties of the Republic of Congo. This tool allowed us to identify the species C. maculatus , which is the most dominant pest on C. cajan and V. u. cylindrica varieties in agricultural fields and storage systems in Niari and Bouenza. In view of the dispersal capacity and voracity of these pests, implementing an effective and environmentally friendly integrated biological control system is urgent. In addition, in contrast to the report published by to Delobel in 1984 we did not identify Callosobruchus rhodesianus and Bruchidius atrolineatus were not identified in our study. In order to have a complete overview of the biodiversity of Bruchidia on pea, it would be necessary in a future study to expand the sample area. Declarations Conflict of Interest The authors declare that they have no conflict of interest. Acknowledgments We would like to thank Professor Paul Attibayeba and Dr Joseph MPIKA for their logistical support, and also to all the producers who grow beans in the departments of Niari and Bouenza. Indeed, the latter did not hesitate to give their time to facilitate our field sampling. References Agnarsson I, Kuntner M (2007) Taxonomy in a Changing World: Seeking Solutions for a Science in Crisis. Syst Biol 56:531–539 Ashfaq M, Hebert PDN (2016) DNA barcodes for bio-surveillance: regulated and economically important arthropod plant pests. Genome 59:933–945 Bakhoum MT, Sarr M, Fall AG, Huber K, Fall M, Sembène M, Seck MT, Labuschagne K, Gardès L, Ciss M, Gimonneau G, Bouyer J, Baldet T, Garros C (2018) DNA barcoding and molecular identification of field-collected Culicoides larvae in the Niayes area of Senegal. Parasit Vectors 11:615 Borowiec L (1987) The genera of seed-beetles (Coleoptera, Bruchidae). Pol Pismo Entomol 57:2–207 Boxall RA (1986) A critical review of the methodology for assessing farm-level grain losses after harvest. Tropical Development and Research Institute, London Boykin LM, Armstrong KF, Kubatko L, De Barro P (2012) Species delimitation and global biosecurity. Evol Bioinforma Online 8:1–37 Delobel A (1984) Les Coléoptères des denrées stockées en République Populaire du Congo (liste provisoire). 28 p. multigr. Delobel A (2000) Comportements de ponte chez les Caryedon (Olivier). Laboratoire ITA/IRD de Protection des Stocks, Delobel A, Epouna-Mouinga S (1984) Les structures paysannes de stockage en République Populaire du Congo : pré-enquête dans la région de la Bouenza. Dibangou V, Okassa MBM, Mazikou GFM, Lenga A (2021) Molecular characterization of pests (Chrysomelidae: Bruchinae) of beans (Phaseolus vulgaris) in the Republic of Congo. Afr Zool 56:35–43 Edgar RC (2004) MUSCLE: a multiple sequence alignment method with reduced time and space complexity. BMC Bioinformatics 5:113 Hebert PDN, Cywinska A, Ball SL, deWaard JR (2003) Biological identifications through DNA barcodes. Proc Biol Sci 270:313–321 Huignard J, Glitho I, Monge J-P, Régnault-Roger C (2011) Insectes ravageurs des graines de légumineuses - Biologie des bruchinae et lutte raisonnée en Afrique. Jeyaprakash A, Hoy MA (2002) Mitochondrial 12S rRNA sequences used to design a molecular ladder assay to identify six commercially available phytoseiids (Acari: Phytoseiidae). Biol Control 25:136–142 Jeyaprakash A, Hoy MA (2007) The mitochondrial genome of the predatory mite Metaseiulus occidentalis (Arthropoda: Chelicerata: Acari: Phytoseiidae) is unexpectedly large and contains several novel features. Gene 391:264–274 Johnson CD (1981) Seed beetle host specificity and the systematics of the Leguminosae. Adv Legume Syst Keneni G, Bekele E, Getu E, Imtiaz M, Damte T, Mulatu B, Dagne K (2011) Breeding Food Legumes for Resistance to Storage Insect Pests: Potential and Limitations. Sustainability 3:1399–1415 Kergoat GJ, Delobel A, Fédière G, Rü BL, Silvain J-F (2005) Both host-plant phylogeny and chemistry have shaped the African seed-beetle radiation. Mol Phylogenet Evol 35:602–611 Kergoat GJ, Silvain J-F, Delobel A, Tuda M, Anton K-W (2007) Defining the limits of taxonomic conservatism in host–plant use for phytophagous insects: Molecular systematics and evolution of host–plant associations in the seed-beetle genus Bruchus Linnaeus (Coleoptera: Chrysomelidae: Bruchinae). Mol Phylogenet Evol 43:251–269 Kingsolver J, Tuñón JB, Nápoles J, Thomas M (2017) Bruchidae of Chile (Insecta: Coleoptera). Insecta Mundi Kumar S, Stecher G, Tamura K (2016) MEGA7: Molecular Evolutionary Genetics Analysis Version 7.0 for Bigger Datasets. Mol Biol Evol 33:1870–1874 Librado P, Rozas J (2009) DnaSP v5: a software for comprehensive analysis of DNA polymorphism data. Bioinformatics 25:1451–1452 M Hernández-Triana L, A Brugman V, I Nikolova N, Ignacio Ruiz-Arrondo null, Barrero E, Thorne L, Fernández de Marco M, Krüger A, Lumley S, Johnson N, R Fooks A (2019) DNA barcoding of British mosquitoes (Diptera, Culicidae) to support species identification, discovery of cryptic genetic diversity and monitoring invasive species. ZooKeys 832:57–76 Magoga G, Sahin DC, Fontaneto D, Montagna M (2018) Barcoding of Chrysomelidae of Euro-Mediterranean area: efficiency and problematic species. Sci Rep 8:13398 Nei P of PGB of the C for D and PGM, Nei M, Kumar S, Nei EPP of BM (2000) Molecular Evolution and Phylogenetics. Oxford University Press, Okassa M, Tixier M-S, Cheval B, Kreiter S (2009) Molecular and morphological evidence for a new species status within the genus Euseius (Acari: Phytoseiidae). Can J Zool 87:689–698 Okassa M, Tixier M-S, Kreiter S (2010) Morphological and molecular diagnostics of Phytoseiulus persimilis and Phytoseiulus macropilis (Acari: Phytoseiidae). Exp Appl Acarol 52:291–303 Okassa MBM, Ntabi DM, Lenga A (2020) Morphological and molecular identification of specimens in the genus Euseius (Acari: Phytoseiidae) from the Republic of Congo. Zootaxa 4768:479–498 Raupach MJ, Astrin JJ, Hannig K, Peters MK, Stoeckle MY, Wägele J-W (2010) Molecular species identification of Central European ground beetles (Coleoptera: Carabidae) using nuclear rDNA expansion segments and DNA barcodes. Front Zool 7:26 Roy V, Mpika J, Kergoat G, Mboussy GFT, Attibayeba A (2023) Diversity of insect pests of common bean and pigeon pea in the Republic of Congo revealed by DNA barcoding. Afr Entomol 31: Tamura K (1992) Estimation of the number of nucleotide substitutions when there are strong transition-transversion and G+C-content biases. Mol Biol Evol 9:678–687 Tamura K, Stecher G, Kumar S (2021) MEGA11: Molecular Evolutionary Genetics Analysis Version 11. Mol Biol Evol 38:3022–3027 Tixier M-S, Kreiter S, Barbar Z, Ragusa S, Cheval B (2006) Status of two cryptic species, Typhlodromus exhilaratus Ragusa and Typhlodromus phialatus Athias-Henriot (Acari: Phytoseiidae): consequences for taxonomy. Zool Scr 35:115–122 Tuda M, Kagoshima K, Toquenaga Y, Arnqvist G (2014) Global Genetic Differentiation in a Cosmopolitan Pest of Stored Beans: Effects of Geography, Host-Plant Usage and Anthropogenic Factors. PLOS ONE 9:e106268 Tables Table 1 Sampling locations of different populations of species considered in this study. Table 2. Characteristics of individuals and species considered in the molecular analysis with their accession numbers. The sequences directly retrieved from Genbank database have an asterisk. RC: Republic of Congo. Table 3. Genetic distances between and within Callosobruchus maculatus from Republic of Congo and Senegal, individual belonging to the family of Curculionidae and outgroup species Bruchus species for the one molecular marker used 12S rRNA. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Major revisions 20 Feb, 2024 Reviewers agreed at journal 06 Jan, 2024 Reviewers invited by journal 06 Jan, 2024 Editor assigned by journal 17 Nov, 2023 First submitted to journal 16 Nov, 2023 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3617667","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":265712304,"identity":"2b493254-0b83-4f41-8ac7-3a8607ad1a56","order_by":0,"name":"Mireille Belle Mbou Okassa","email":"data:image/png;base64,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","orcid":"https://orcid.org/0000-0002-4033-1731","institution":"Marien Ngouabi University Faculty of Science: Universite Marien Ngouabi Faculte des Sciences","correspondingAuthor":true,"prefix":"","firstName":"Mireille","middleName":"Belle Mbou","lastName":"Okassa","suffix":""},{"id":265712305,"identity":"7b501c3a-63ce-4393-8c9a-66a723c6a19c","order_by":1,"name":"Matito Mavanga Mabika","email":"","orcid":"","institution":"Marien Ngouabi University Faculty of Science: Universite Marien Ngouabi Faculte des Sciences","correspondingAuthor":false,"prefix":"","firstName":"Matito","middleName":"Mavanga","lastName":"Mabika","suffix":""},{"id":265712306,"identity":"1bab7238-ead9-4206-a262-da960e869467","order_by":2,"name":"Valentin Dibangou","email":"","orcid":"","institution":"Marien Ngouabi University Faculty of Science: Universite Marien Ngouabi Faculte des Sciences","correspondingAuthor":false,"prefix":"","firstName":"Valentin","middleName":"","lastName":"Dibangou","suffix":""},{"id":265712307,"identity":"05c5b512-ad51-4630-a6ed-bfd99d243fcc","order_by":3,"name":"Arsène Lenga","email":"","orcid":"","institution":"Marien Ngouabi University Faculty of Science: Universite Marien Ngouabi Faculte des Sciences","correspondingAuthor":false,"prefix":"","firstName":"Arsène","middleName":"","lastName":"Lenga","suffix":""}],"badges":[],"createdAt":"2023-11-16 01:41:27","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3617667/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3617667/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":49385992,"identity":"f4201536-a3aa-4380-bd0f-cbc3d31f7fcb","added_by":"auto","created_at":"2024-01-09 19:52:29","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":11835323,"visible":true,"origin":"","legend":"\u003cp\u003eSampling locations of different populations of specimens considered in this study. Site 1 blue, Site 2 orange, Site 3 green, Site 4 purple, Site 5 yellow, Site 6 brown, site 7 black\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-3617667/v1/f9eb2aeaf72e75c29ae1b7e6.png"},{"id":49386774,"identity":"a37d3103-eaba-48f1-88df-49e94a8452cb","added_by":"auto","created_at":"2024-01-09 20:00:35","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1936867,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3617667/v1/cd54ce95-f365-4198-bc9d-5b686b0b8cc8.pdf"}],"financialInterests":"","formattedTitle":"A brief inventory of bruchids (Chrysomelidae, Bruchinae) and similar pest beetles occurring on peas in the Republic of Congo: barcoding and prospects","fulltext":[{"header":"Introduction","content":"\u003cp\u003eDomestic Fabaceae cultivars, such as groundnuts, beans, and peas, are the most vulnerable to infestation by\u0026nbsp;bruchids. In the Republic of Congo (RC), the production of these legumes is primarily a traditional concern, wherein most producers are smallholders grouped in agricultural cooperatives or family communities and maintain relatively low productivity.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSome of the most important factors limiting the productivity of Congolese agriculture are 1) the absence of crop protection systems and 2) the high level of post-harvest losses. These two factors result in consistently low yields,\u0026nbsp;forcing the local markets to import legumes from Cameroon and consequently increase their prices. Post-harvest losses (fruit weight loss, reduced nutritional value, and impeded germination capacity) are mainly caused by small Coleoptera belonging to the\u0026nbsp;Chrysomelidae family\u0026nbsp;(Borowiec 1987; Delobel 2000; Keneni et al. 2011)\u0026nbsp;.\u0026nbsp;The most economically damaging\u0026nbsp;genera are\u0026nbsp;\u003cem\u003eAcanthoscelides\u003c/em\u003e, \u003cem\u003eBruchidius\u003c/em\u003e, \u003cem\u003eBruchus\u003c/em\u003e, \u003cem\u003eCallosobruchus\u003c/em\u003e, \u003cem\u003eCaryedon\u003c/em\u003e,\u0026nbsp;and \u003cem\u003eZabrotes\u0026nbsp;\u003c/em\u003e(Johnson 1981, Huignard et al. \u0026nbsp;2011)\u0026nbsp;. The affected seeds\u0026nbsp;become unfit for human (1-3% threshold) and animal (10%) consumption and\u0026nbsp;are unviable for planting due to reduced germination capacity. Although legume growers have difficulty estimating the level of crop loss to bruchids, it is generally claimed that insects cause the most damage to reserve stocks\u0026nbsp;(Boxall 1986)\u0026nbsp;.\u003c/p\u003e\n\u003cp\u003eA necessary prerequisite to reduce post-harvest losses and improve biosecurity is establishing an accurate database of Chrysomelidae pests that affect economically important legumes (FAOSTAT, 2010). For decades, morphospecies have been identified exclusively using morphological diagnostics provided by taxonomic studies\u0026nbsp;(Borowiec 1987)\u0026nbsp;.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis identification method requires specialised skills that are often acquired through long-term experience that only experts, such as taxonomists and qualified technicians, possess\u0026nbsp;(Raupach et al. 2010). In view of the decreasing number of experts\u0026nbsp;(Agnarsson and Kuntner 2007)\u0026nbsp;and the loss of biodiversity, an alternative method is needed to rapidly collate biodiversity inventories and allow species identification by non-specialists. Hebert et al. (2003) proposed a morphospecies identification method using a short mitochondrial DNA sequence. This tool makes it possible to identify insect species in their developmental stages\u0026nbsp;(Bakhoum et al. \u0026nbsp;2018), morphospecies without sufficient discriminating characteristics, and cryptic species. The scientific value of barcoding has been shown in the biomonitoring of several insect pests that cause significant economic damage to important crops worldwide\u0026nbsp;(Boykin et al. 2012; Ashfaq and Hebert 2016). Some authors have tested tested the effectiveness of mitochondrial cytochrome c oxidase gene I (COI) on nearly 7,237 sequences, representing 542 species of Chrysomelidae\u0026nbsp;(Magoga et al. 2018). The barcoding efficiency was 94%, and 6% of the sequences were misidentified. Other molecular markers have been successfully developed since the article of Hebert et al. (2003) was published\u0026nbsp;(Hebert et al. 2003), including 12S rRNA, Cytb,\u0026nbsp;and ITSS\u0026nbsp;(Tixier et al. 2006; Okassa et al. 2009, 2010; M Hern\u0026aacute;ndez-Triana et al. 2019).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFrom in 2021\u0026nbsp;(Dibangou et al. 2021)\u0026nbsp;, scientific studies began using barcoding to assess the biodiversity and distribution of insects belonging to the Chrysomelidae family in Congo. \u0026nbsp;, In fact, until recently, the only data available came from reports\u0026nbsp;carried out by the Ministry of Scientific Research and the French Institute of Scientific Research for Development in Cooperation\u0026nbsp;(Delobel and Epouna-Mouinga 1984)\u0026nbsp;with a pre-survey was conducted in the Bouenza region on Farmers\u0026apos; storage structures in the RC.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; The following points were highlighted in these reports: :\u003c/p\u003e\n\u003cp\u003eThe samples collected had an average seed weight of between 100 and 200 g.\u0026nbsp;First, the species \u003cem\u003eCallosobruchus maculatus\u003c/em\u003e was identified on the \u003cem\u003eCajuns cajan\u003c/em\u003e pea variety from the department of Madingou.\u0026nbsp;Secondly, of the three samples collected (two from Mouyondi and one from Loudima) three species \u003cem\u003eC. maculatus,\u003c/em\u003e \u003cem\u003eCallosobruchus rhodesianus\u003c/em\u003e and last \u003cem\u003eBruchidius atrolineatus\u003c/em\u003e were identified avec les proportions de two thirds, two thirds and one third respectively. In another report by Delobel in 1984, he states that \u003cem\u003eC. maculatus\u003c/em\u003e is the most common bruchid species on all the leguminous varieties grown in the department of Bouenza , only the \u003cem\u003ePsophocarpus tetragonolobus\u003c/em\u003e variety has proved resistant to its development\u0026nbsp;(Delobel 1984).\u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eA recent study has been published on the diversity of cytochrome oxidase 1 insect pests of peas and beans. \u0026nbsp;The method used is phylogenetic reconstruction\u0026nbsp;(Roy et al. 2023). In our study we are interested in the biodiversity of insect pests on two pea varieties. To achieve this goal, we will use the genetic distance method with the 12S rRNA marker. We believe that the use of markers other than COI would enrich the database, making multilocus barcoding more accessible and speeding up the biodiversity inventory. Our study focused on the identification by the 12S rRNA fragment of the bruchids that attack two pea varieties in RC: \u003cem\u003eCajanus cajan\u003c/em\u003e and \u003cem\u003eVigna unguiculata\u003c/em\u003e subsp. \u003cem\u003ecylindrica\u003c/em\u003e. These two varieties are widely consumed by the Congolese population.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec2\" class=\"Section2\"\u003e \u003ch2\u003eBruchids survey\u003c/h2\u003e \u003cp\u003eA random sampling of different populations of bruchid species was carried out from April 2019 to August 2019 in the departments of Niari and Bouenza (Table\u0026nbsp;1, Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). In this study 80 individuals were considered. The random sampling is a method of randomly and independently taking 'n' sample units from a population of 'N' elements. The samples are distributed randomly. Each point in the space studied therefore has an equal chance of being sampled. The data collected in this way are not biased. For this study, eight plots of pea fields were selected at each locality with a minimum distance of 4 km between plots. Twelve yellow sticking traps were set up on each plot. Traps were checked once per week, and bruchid-like beetles were collected manually. Individuals were collected from seed-baited traps and crop storage areas. The samples were placed in closed plastic containers with a paper towel soaked in ethyl acetate for 24 h. This procedure prevents the specimens from becoming rigid. Specimens were then labelled according to plot location and preserved in 70% ethanol for morphological analysis and 95% ethanol for molecular analysis.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eMorphological analyses\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eEach bruchid specimen was placed on a Petri dish lid and observed under a Leica MZ6 modular stereomicroscope (Leica Microsystems GmbH, Wetzla, Germany). Specimens were classified using species identification keys (Kingsolver et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eMolecular analyses\u003c/h2\u003e \u003cdiv id=\"Sec5\" class=\"Section3\"\u003e \u003ch2\u003eDNA extraction\u003c/h2\u003e \u003cp\u003eTotal genomic DNA was extracted from 20 individuals, 10 and 10 from Bouenza and Niari. The total DNA was purified using the spin-column protocol (Qiagen, Hilden, Germany). In this protocol, insects are frozen in liquid nitrogen and then ground with a mortar and pestle or disposable microtube pestle, or homogenised using the Tissue Ruptor (Qiagen), an equivalent electric homogeniser. Samples were then processed using the DNeasy\u0026reg; Blood \u0026amp; Tissue Kit (Qiagen). DNA elution was performed in Tris-acetate-EDTA (TAE) instead of water.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eDNA amplification and sequencing\u003c/h2\u003e \u003cp\u003eThe 12S rRNA mitochondrial fragments were amplified and sequenced. The primers used for amplification of the 12S rRNA gene were 12S-F 5\u0026prime;-TACTATGTTACGACTTAT-3\u0026lsquo; and 12S-R 5\u0026prime;-AAACTAGGATTAGATACCC-3\u0026prime; (Tixier et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Okassa et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2009\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; M Hern\u0026aacute;ndez-Triana et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). The amplification reactions for 12S fragments were carried out with Dr. MAX DNA Polymerase (Doctor protein INC, Korea, cat.no.: DR00302). A Bio-Rad DNA Engine Tetrad 2 Peltier Thermal Cycler (Bio-Rad Laboratories, Inc., Hercules, CA, USA) was used for PCR amplification. To amplify the 12S rRNA fragments, samples were denatured at 95\u0026deg;C for 1 min, followed by 40 cycles of denaturation at 94\u0026deg;C for 30 s, annealing at 40\u0026deg;C for 30 s, extension at 72\u0026deg;C for 1 min, and a final step at 72\u0026deg;C for 5 min. After amplification, 5 \u0026micro;L of the PCR reaction was analysed by 1% agarose gel electrophoresis running for 20 min at 300 V, 200 A, and 2 \u0026micro;L of DNA loaded. PCR products were purified using a Multiscreen filter plate (MilliporeSigma, Burlington, MA, USA). The amplified 12S rRNA fragments containing visible and single bands were directly sequenced using an ABI PRISM 3730XL Analyser (96 capillary type) with a BigDye\u0026reg; Terminator ver. 3.1 Cycle Sequencing Kit (Applied Biosystems, Waltham, MA, USA)\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eDNA Blast\u003c/h2\u003e \u003cp\u003eThe Geneious Prime 2019.2 (Raupach et al. \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2010\u003c/span\u003e) was used to correct and assemble the raw data into sequence contigs. The assignment of each query sequence was performed using the local basic alignment search tool (MegaBLAST) on an external NCBI database. An aligned set of potentially related sequences were obtained, ranked according to their similarity. This similarity takes into account different parameters, with the most relevant being the bit score, E-value, percent identity, and grade (Okassa et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Dibangou et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eSequence variation and divergence analysis\u003c/h2\u003e \u003cp\u003eTo the obtained sequence data set were added three sequences of \u003cem\u003eC. maculatus\u003c/em\u003e, with two sequence de \u003cem\u003eC. maculatus\u003c/em\u003e from the department of Bouenza accidentally identified on the bean (Dibangou et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) and one sequence from the country of Senegal (Kergoat et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). In last, one sequence of \u003cem\u003eBruchus pisorum\u003c/em\u003e from the country of Italy (Kergoat et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2007\u003c/span\u003e) was considered as outgroup species.\u003c/p\u003e \u003cp\u003eThe sequences were aligned using the MUSCLE alignment procedure with gap penalities, iteration and clustering method (Edgar \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). An analysis zone was defined from sites 17 to 402 in order to consider only the same number of character states for all the sequences studied, either 386 sites. The best sequence evolution model of 24 models was determined using Molecular Evolution Genetics Analysis (MEGA) version 11 (Tamura et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) with maximum likelihood (Kumar et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Models with the lowest Bayesian Information Criterion (BIC) scores were considered to best describe the substitution pattern. The corrected Akaike information criterion, maximum likelihood value (ML), and number of parameters (including branch length) were included in each model (Nei et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2000\u003c/span\u003e).The non-uniformity of evolutionary rates among sites were modelled using a discrete Gamma distribution (+\u0026thinsp;G) with 5 rated categories, assuming that a certain fraction of the sites are evolutionarily invariable (+\u0026thinsp;I). Whenever applicable, estimates of the gamma shape parameter and/or the estimated fraction of invariant sites were reported.\u003c/p\u003e \u003cp\u003eMEGA 11 was employed also to analyze nucleotide composition, conserved sites, variable sites, singleton sites and parsimony-informative sites (Tamura et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAt last, analyses estimates of evolutionary divergence between sequences were conducted using the Tamura 3-parameter model (Tamura \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e1992\u003c/span\u003e). The rate variation among sites was modeled with a gamma distribution (shape parameter\u0026thinsp;=\u0026thinsp;1).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eGenetic diversity\u003c/h2\u003e \u003cp\u003eEvaluation of the number of haplotypes and haplotype diversity between all populations considered were performed using DnaSP software version 6.12 (Librado and Rozas \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2009\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e"},{"header":"Results and discussion","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eMorphological analyses\u003c/h2\u003e \u003cp\u003eThe use of an identification key allowed us to assign each individual to a specific rank (Kingsolver et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Individuals belonging to \u003cem\u003eCallosobruchus maculatus\u003c/em\u003e because they have the following two characteristics 1) hind femur with a spine or denticles on both latero ventral and mesoventral carinae and 2) Elytral stria originating at basal margin and lacking denticles or gibbosity. A second species belonging to the Curculionidae family was identified, she is characterised by the presence of a rostrum extended beyond the eyes, with mouth parts situated at its apex. This morphological trait is one of the most typical features of the family of Curculionidae.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eMolecular analyses\u003c/h2\u003e \u003cdiv id=\"Sec13\" class=\"Section3\"\u003e \u003ch2\u003eSequence variation\u003c/h2\u003e \u003cp\u003eFragments of 423 bp were aligned for 12S rRNA and contained 344 conserved, 76 variables, 31 parsimony-informative, and 40 singleton sites. All new sequences herein obtained have been deposited in GenBank and are shown in Table\u0026nbsp;2.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eGenetic distances\u003c/h2\u003e \u003cp\u003eMean genetic Tamura 3 parameter (substitutions models) and evolutionary rates among sites (+\u0026thinsp;G\u0026thinsp;=\u0026thinsp;discrete gamma) distances (minimum and maximum values) within and between all populations studied with outgroup species B. pisorum for 12S rRNA are shown in Table\u0026nbsp;2\u003c/p\u003e \u003cp\u003eFirst, the genetic distances between the populations of \u003cem\u003eC. maculatus\u003c/em\u003e originating from different localities in Congo were very small and had little variation (0\u0026ndash;0.8% with a mean of 0.2%). This low genetic variability can be explained by host plants (pea variety) occurring in similar climatic conditions (temperature and hygrometry) between Bouenza and Niari. In addition, little genetic divergence was found between \u003cem\u003eC. maculatus\u003c/em\u003e collected from pea and \u003cem\u003eC. maculatus\u003c/em\u003e collected from bean (0\u0026ndash;1.5% with an mean of 0.6%). The genetic distances between \u003cem\u003eC. maculatus\u003c/em\u003e populations originating from the Republic of Congo and those from Senegal were greater and varied between 3.3\u0026ndash;4.2%, which corresponds to interspecific variation. For example, for \u003cem\u003eAcanthoceslides obtectus\u003c/em\u003e, which are in the same family, the mean intrapecific variation was 0 and 0.62% for specimens from Bouenza and Niari. The host plant and climatic differences between these two countries could explain this variability.\u003c/p\u003e \u003cp\u003eSecond, the genetic distances between \u003cem\u003eC. maculatus\u003c/em\u003e populations and the population comprising individual 26 belonging to the Curculionidae family were 12.7%, showing interspecific variation at a threshold greater than 3%. These results confirm our morphological observations and support the presence of another important biological pest, belonging to an other family.\u003c/p\u003e \u003cp\u003eA last, a comparison of the DNA sequence of \u003cem\u003eB. pisorum\u003c/em\u003e from Italy, retrieved from GenBank, was performed. The genetic distances between the different populations of \u003cem\u003eC. maculatus\u003c/em\u003e and \u003cem\u003eB. pisorum\u003c/em\u003e varied from 13.9 to 16.4%, and corresponded to interspecific variation .\u003c/p\u003e \u003cp\u003eExcept for the case of \u003cem\u003eC. maculatus\u003c/em\u003e from Senegal,, the assignment of each individual adhered to two principles of the barcode: that 1) intraspecific variation was less than interspecific variation and 2) the absence of overlap between intra- and interspecific variation (presence of a gap) (Hebert et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2003\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eHaplotypic diversity\u003c/h2\u003e \u003cp\u003eNine haplotypes were identified in the study species (Table\u0026nbsp;2), with significant haplotype diversity (Hd\u0026thinsp;=\u0026thinsp;0.8182). With regards to our sample size, the number of distinct haplotypes and the degree of haplotype diversity showed a high degree of haplotype differentiation in the beetles in our dataset. The results of this study were similar to those obtained by other authors hypothesised, based on their results, that natural selection, particularly frequency dependent selection, could play a role in the differentiation of mitochondrial genetic variation by maintaining within \u003cem\u003eC. maculatus\u003c/em\u003e populations a variation of mitochondrial DNA haplotypes (Tuda et al. \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2014\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study has demonstrated the potential role of integrative taxonomy (Morphological and molecular analyses) in classifying important pest species belonging to the Chrysomelidae family and confirmed their presence in domestic pea varieties of the Republic of Congo. This tool allowed us to identify the species \u003cem\u003eC. maculatus\u003c/em\u003e, which is the most dominant pest on \u003cem\u003eC. cajan\u003c/em\u003e and \u003cem\u003eV. u. cylindrica\u003c/em\u003e varieties in agricultural fields and storage systems in Niari and Bouenza. In view of the dispersal capacity and voracity of these pests, implementing an effective and environmentally friendly integrated biological control system is urgent. In addition, in contrast to the report published by to Delobel in 1984 we did not identify \u003cem\u003eCallosobruchus rhodesianus\u003c/em\u003e and \u003cem\u003eBruchidius atrolineatus\u003c/em\u003e were not identified in our study. In order to have a complete overview of the biodiversity of Bruchidia on pea, it would be necessary in a future study to expand the sample area.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eConflict of Interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;The authors declare that they have no conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe would like to thank Professor Paul Attibayeba and Dr Joseph MPIKA for their logistical support, and also to all the producers who grow beans in the departments of Niari and Bouenza. Indeed, the latter did not hesitate to give their time to facilitate our field sampling.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAgnarsson I, Kuntner M (2007) Taxonomy in a Changing World: Seeking Solutions for a Science in Crisis. Syst Biol 56:531\u0026ndash;539 \u003c/li\u003e\n\u003cli\u003eAshfaq M, Hebert PDN (2016) DNA barcodes for bio-surveillance: regulated and economically important arthropod plant pests. Genome 59:933\u0026ndash;945 \u003c/li\u003e\n\u003cli\u003eBakhoum MT, Sarr M, Fall AG, Huber K, Fall M, Semb\u0026egrave;ne M, Seck MT, Labuschagne K, Gard\u0026egrave;s L, Ciss M, Gimonneau G, Bouyer J, Baldet T, Garros C (2018) DNA barcoding and molecular identification of field-collected Culicoides larvae in the Niayes area of Senegal. Parasit Vectors 11:615 \u003c/li\u003e\n\u003cli\u003eBorowiec L (1987) The genera of seed-beetles (Coleoptera, Bruchidae). Pol Pismo Entomol 57:2\u0026ndash;207 \u003c/li\u003e\n\u003cli\u003eBoxall RA (1986) A critical review of the methodology for assessing farm-level grain losses after harvest. Tropical Development and Research Institute, London \u003c/li\u003e\n\u003cli\u003eBoykin LM, Armstrong KF, Kubatko L, De Barro P (2012) Species delimitation and global biosecurity. Evol Bioinforma Online 8:1\u0026ndash;37 \u003c/li\u003e\n\u003cli\u003eDelobel A (1984) Les Col\u0026eacute;opt\u0026egrave;res des denr\u0026eacute;es stock\u0026eacute;es en R\u0026eacute;publique Populaire du Congo (liste provisoire). 28 p. multigr. \u003c/li\u003e\n\u003cli\u003eDelobel A (2000) Comportements de ponte chez les Caryedon (Olivier). Laboratoire ITA/IRD de Protection des Stocks, \u003c/li\u003e\n\u003cli\u003eDelobel A, Epouna-Mouinga S (1984) Les structures paysannes de stockage en R\u0026eacute;publique Populaire du Congo : pr\u0026eacute;-enqu\u0026ecirc;te dans la r\u0026eacute;gion de la Bouenza. \u003c/li\u003e\n\u003cli\u003eDibangou V, Okassa MBM, Mazikou GFM, Lenga A (2021) Molecular characterization of pests (Chrysomelidae: Bruchinae) of beans (Phaseolus vulgaris) in the Republic of Congo. Afr Zool 56:35\u0026ndash;43 \u003c/li\u003e\n\u003cli\u003eEdgar RC (2004) MUSCLE: a multiple sequence alignment method with reduced time and space complexity. BMC Bioinformatics 5:113 \u003c/li\u003e\n\u003cli\u003eHebert PDN, Cywinska A, Ball SL, deWaard JR (2003) Biological identifications through DNA barcodes. Proc Biol Sci 270:313\u0026ndash;321 \u003c/li\u003e\n\u003cli\u003eHuignard J, Glitho I, Monge J-P, R\u0026eacute;gnault-Roger C (2011) Insectes ravageurs des graines de l\u0026eacute;gumineuses - Biologie des bruchinae et lutte raisonn\u0026eacute;e en Afrique. \u003c/li\u003e\n\u003cli\u003eJeyaprakash A, Hoy MA (2002) Mitochondrial 12S rRNA sequences used to design a molecular ladder assay to identify six commercially available phytoseiids (Acari: Phytoseiidae). Biol Control 25:136\u0026ndash;142 \u003c/li\u003e\n\u003cli\u003eJeyaprakash A, Hoy MA (2007) The mitochondrial genome of the predatory mite Metaseiulus occidentalis (Arthropoda: Chelicerata: Acari: Phytoseiidae) is unexpectedly large and contains several novel features. Gene 391:264\u0026ndash;274 \u003c/li\u003e\n\u003cli\u003eJohnson CD (1981) Seed beetle host specificity and the systematics of the Leguminosae. Adv Legume Syst \u003c/li\u003e\n\u003cli\u003eKeneni G, Bekele E, Getu E, Imtiaz M, Damte T, Mulatu B, Dagne K (2011) Breeding Food Legumes for Resistance to Storage Insect Pests: Potential and Limitations. Sustainability 3:1399\u0026ndash;1415 \u003c/li\u003e\n\u003cli\u003eKergoat GJ, Delobel A, F\u0026eacute;di\u0026egrave;re G, R\u0026uuml; BL, Silvain J-F (2005) Both host-plant phylogeny and chemistry have shaped the African seed-beetle radiation. Mol Phylogenet Evol 35:602\u0026ndash;611 \u003c/li\u003e\n\u003cli\u003eKergoat GJ, Silvain J-F, Delobel A, Tuda M, Anton K-W (2007) Defining the limits of taxonomic conservatism in host\u0026ndash;plant use for phytophagous insects: Molecular systematics and evolution of host\u0026ndash;plant associations in the seed-beetle genus Bruchus Linnaeus (Coleoptera: Chrysomelidae: Bruchinae). Mol Phylogenet Evol 43:251\u0026ndash;269 \u003c/li\u003e\n\u003cli\u003eKingsolver J, Tu\u0026ntilde;\u0026oacute;n JB, N\u0026aacute;poles J, Thomas M (2017) Bruchidae of Chile (Insecta: Coleoptera). Insecta Mundi \u003c/li\u003e\n\u003cli\u003eKumar S, Stecher G, Tamura K (2016) MEGA7: Molecular Evolutionary Genetics Analysis Version 7.0 for Bigger Datasets. Mol Biol Evol 33:1870\u0026ndash;1874 \u003c/li\u003e\n\u003cli\u003eLibrado P, Rozas J (2009) DnaSP v5: a software for comprehensive analysis of DNA polymorphism data. Bioinformatics 25:1451\u0026ndash;1452 \u003c/li\u003e\n\u003cli\u003eM Hern\u0026aacute;ndez-Triana L, A Brugman V, I Nikolova N, Ignacio Ruiz-Arrondo null, Barrero E, Thorne L, Fern\u0026aacute;ndez de Marco M, Kr\u0026uuml;ger A, Lumley S, Johnson N, R Fooks A (2019) DNA barcoding of British mosquitoes (Diptera, Culicidae) to support species identification, discovery of cryptic genetic diversity and monitoring invasive species. ZooKeys 832:57\u0026ndash;76 \u003c/li\u003e\n\u003cli\u003eMagoga G, Sahin DC, Fontaneto D, Montagna M (2018) Barcoding of Chrysomelidae of Euro-Mediterranean area: efficiency and problematic species. Sci Rep 8:13398 \u003c/li\u003e\n\u003cli\u003eNei P of PGB of the C for D and PGM, Nei M, Kumar S, Nei EPP of BM (2000) Molecular Evolution and Phylogenetics. Oxford University Press, \u003c/li\u003e\n\u003cli\u003eOkassa M, Tixier M-S, Cheval B, Kreiter S (2009) Molecular and morphological evidence for a new species status within the genus Euseius (Acari: Phytoseiidae). Can J Zool 87:689\u0026ndash;698 \u003c/li\u003e\n\u003cli\u003eOkassa M, Tixier M-S, Kreiter S (2010) Morphological and molecular diagnostics of Phytoseiulus persimilis and Phytoseiulus macropilis (Acari: Phytoseiidae). Exp Appl Acarol 52:291\u0026ndash;303 \u003c/li\u003e\n\u003cli\u003eOkassa MBM, Ntabi DM, Lenga A (2020) Morphological and molecular identification of specimens in the genus Euseius (Acari: Phytoseiidae) from the Republic of Congo. Zootaxa 4768:479\u0026ndash;498 \u003c/li\u003e\n\u003cli\u003eRaupach MJ, Astrin JJ, Hannig K, Peters MK, Stoeckle MY, W\u0026auml;gele J-W (2010) Molecular species identification of Central European ground beetles (Coleoptera: Carabidae) using nuclear rDNA expansion segments and DNA barcodes. Front Zool 7:26 \u003c/li\u003e\n\u003cli\u003eRoy V, Mpika J, Kergoat G, Mboussy GFT, Attibayeba A (2023) Diversity of insect pests of common bean and pigeon pea in the Republic of Congo revealed by DNA barcoding. Afr Entomol 31: \u003c/li\u003e\n\u003cli\u003eTamura K (1992) Estimation of the number of nucleotide substitutions when there are strong transition-transversion and G+C-content biases. Mol Biol Evol 9:678\u0026ndash;687 \u003c/li\u003e\n\u003cli\u003eTamura K, Stecher G, Kumar S (2021) MEGA11: Molecular Evolutionary Genetics Analysis Version 11. Mol Biol Evol 38:3022\u0026ndash;3027 \u003c/li\u003e\n\u003cli\u003eTixier M-S, Kreiter S, Barbar Z, Ragusa S, Cheval B (2006) Status of two cryptic species, Typhlodromus exhilaratus Ragusa and Typhlodromus phialatus Athias-Henriot (Acari: Phytoseiidae): consequences for taxonomy. Zool Scr 35:115\u0026ndash;122 \u003c/li\u003e\n\u003cli\u003eTuda M, Kagoshima K, Toquenaga Y, Arnqvist G (2014) Global Genetic Differentiation in a Cosmopolitan Pest of Stored Beans: Effects of Geography, Host-Plant Usage and Anthropogenic Factors. PLOS ONE 9:e106268 \u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTable 1 Sampling locations of different populations of species considered in this study.\u003c/p\u003e\n\u003cp\u003e\u003cimg src=\"https://myfiles.space/user_files/122228_c8a1650c59388082/122228_custom_files/img1704791991.png\"\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cu\u003eTable 2.\u003c/u\u003e\u003c/strong\u003e Characteristics of individuals and species considered in the molecular analysis with their accession numbers. The sequences directly retrieved from Genbank database have an asterisk. RC: Republic of Congo.\u003c/p\u003e\n\u003cp\u003e\u003cimg src=\"https://myfiles.space/user_files/122228_c8a1650c59388082/122228_custom_files/img1704792042.png\"\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cu\u003eTable 3.\u003c/u\u003e\u003c/strong\u003e Genetic distances between and within \u003cem\u003eCallosobruchus maculatus from\u0026nbsp;\u003c/em\u003eRepublic of Congo and Senegal, individual belonging to the family of Curculionidae and outgroup species Bruchus species for the one molecular marker used 12S rRNA. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cimg src=\"https://myfiles.space/user_files/122228_c8a1650c59388082/122228_custom_files/img1704792077.png\"\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"international-journal-of-tropical-insect-science","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jtis","sideBox":"Learn more about [International Journal of Tropical Insect Science](http://link.springer.com/journal/42690)","snPcode":"42690","submissionUrl":"https://www.editorialmanager.com/jtis/default2.aspx","title":"International Journal of Tropical Insect Science","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Bruchine species, peas, storage areas, 12S rRNA, genetic distance methods","lastPublishedDoi":"10.21203/rs.3.rs-3617667/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3617667/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe seed beetles of the family Chrysomelidae, subfamily Bruchinae, are pest species that cause substantial damage to legume crops, affecting supply for human and animal consumption. Legumes are a staple of the Congolese population due to their protein-rich seeds, productivity, and ability to improve soil fertility when combined with cereals. In this study, we focused on bruchids that attack two varieties of peas, \u003cem\u003eCajanus cajan\u003c/em\u003e and \u003cem\u003eVigna unguiculata\u003c/em\u003e subsp. \u003cem\u003ecylindrica\u003c/em\u003e, in the Republic of Congo. 80 individuals of bruchids were considered from the two main pea-growing departments: Bouenza and Niari. Specimens were collected using baited traps placed in the field and by manually selecting affected seeds from the storage areas. Individuals were categorised at the species level based on morphological traits and molecular barcode analyses. This is the second time that 12S rRNA sequences of bruchids from the Republic of Congo have been deposited in the GenBank database. This study emphasises the need to enrich the GenBank database with DNA sequences originating from areas where the technical means to carry out quality morphological analyses are limited.\u003c/p\u003e","manuscriptTitle":"A brief inventory of bruchids (Chrysomelidae, Bruchinae) and similar pest beetles occurring on peas in the Republic of Congo: barcoding and prospects","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-01-09 19:52:25","doi":"10.21203/rs.3.rs-3617667/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Major revisions","date":"2024-02-20T06:53:26+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"","date":"2024-01-06T19:28:21+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-01-06T16:34:11+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2023-11-17T08:46:32+00:00","index":"","fulltext":""},{"type":"submitted","content":"International Journal of Tropical Insect Science","date":"2023-11-16T15:10:55+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"international-journal-of-tropical-insect-science","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jtis","sideBox":"Learn more about [International Journal of Tropical Insect Science](http://link.springer.com/journal/42690)","snPcode":"42690","submissionUrl":"https://www.editorialmanager.com/jtis/default2.aspx","title":"International Journal of Tropical Insect Science","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"e4e96d7a-b969-4e93-8a68-900bac5fbcef","owner":[],"postedDate":"January 9th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2024-06-21T21:54:07+00:00","versionOfRecord":[],"versionCreatedAt":"2024-01-09 19:52:25","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3617667","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3617667","identity":"rs-3617667","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}