Percorrer por autor "Verbinnen, Gilles"
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- Bioinformatics pipeline to evaluate patterns of diversity in detoxification genes in the Western honey bee (Apis mellifera)Publication . Barbosa, Daniela; Li, Fernanda; Bashir, Sana; Lopes, Ana Rita; Yadró Garcia, Carlos A.; Quaresma, Andreia; Rufino, José; Rosa-Fontana, Annelise; Verbinnen, Gilles; de Graaf, Dirk C.; De Smet, Lina; Taliadoros, Demetris; Webster, Matthew; Pinto, M. Alice; Henriques, DoraThe Western honey bee, Apis mellifera, displays significant genetic diversity in detoxification genes, which is pivotal for environmental adaptation and resilience. Herein, we developed a bioinformatics pipeline to investigate patterns of diversity in these genes, focusing on single nucleotide polymorphisms (SNPs) across A. mellifera populations, with variant annotation performed using both snpEff and the Variant Effect Predictor (VEP). Our pipeline integrates GATK, VCFtools, PLINK, bcftools, snpEff, and VEP to process genomic data systematically. Regions of interest were defined in a BED file for variant filtering. Using GATK, SNPs were extracted from a VCF file and conversion to PLINK format for population genetics analyses. Variants were filtered by minor allele frequency (MAF) and population differentiation (FST index) to identify SNPs with considerable. Variants were annotated with snpEff and VEP to predict functional impacts, enabling a comparative analysis of their annotation consistency and depth. Custom scripts were developed to map SNPs to detoxification genes, quantify SNP density, and integrated gene descriptions and lineage data. The resulting data were visualized using a combination of and generate different graphs using ggplot2 and chromoMap for chromossomal maps. Quality control steps were applied through the pipeline ensuring data reliability. Our findings reveal distinct SNP patterns in detoxification genes, highlighting candidate SNPs associated with A. mellifera subspecies-specific adaptations. The comparison of snpEff and VEP annotations provides insights into their strengths and limitations, which can help optimize software selection for genomic studies. This pipeline offers a reproducible framework for studying genetic diversity in A. mellifera that is adaptable to other species, advancing conservation and evolutionary genomics.
- The diversity of insecticide target site mutations in Apis melliferaPublication . Verbinnen, Gilles; De Smet, Lina; Henriques, Dora; Tytgat, Jan; Pinto, M. Alice; Graaf, Dirk C. deInsecticides are widely used to combat agricultural pest species, such as aphids, caterpillars, planthoppers and locusts, or to limit the spread of disease-carrying mosquitos. However, these insecticides do not only affect their target species but also non-target species such as pollinators which inadvertently encounter them while foraging. Over one hundred different pesticides and pesticide derivatives have been found in honey bee hives. Insecticides are one of the factors behind the decline of pollinator populations. Pest species, such as aphids and Lepidoptera, have developed widespread resistance to a large number of compounds. However, research on insecticide resistance in honey bees is rather limited and focuses on only one type of resistance: metabolic resistance. Therefore, we aim to expand the available data on insecticide resistance in honey bees by studying another type of insecticide resistance: target site resistance. In this study, we screened 4897 publicly available Apis mellifera genomes for mutations in 17 insecticide target site genes covering all commonly used insecticides. These genomes originated from 54 countries and cover more than 20 subspecies and honey bee breeds. A total of 5269 synonymous and 4465 non-synonymous mutations were identified. These mutations show differing geographical and functional patterns of diversity. While the majority of mutations were classified as rare mutations or could not be linked directly to insecticide resistance, several potential insecticide resistance mutations have been identified. Furthermore, mutations potentially associated with previously reported local adaptation to high altitude and Varroa destructor are described. This study serves as a basis for further research on insecticide resistance and local adaptation in pollinators.
- Diversity patterns of P450 and ABC transporter genes in 17 honey bee subspeciesPublication . Li, Fernanda; Rosa-Fontana, Annelise; Yadró Garcia, Carlos A.; Rufino, José; Verbinnen, Gilles; Graaf, Dirk C. de; De Smet, Lina; Pinto, M. Alice; Henriques, DoraHoney bees (Apis mellifera) inhabit a vast geographical range, spanning diverse natural and agricultural ecosystems. They are exposed to different levels and types of natural (such as plant allelochemicals) and synthetic (such as pesticides) xenobiotics within this range. Several genes have been implicated in the resistance of insects to pesticides, including the P450 monooxygenases superfamily and ATP-binding cassette sub-family F member 1that contain 46 and 41 genes, respectively. Here, the sequences of P450 monooxygenases and ABC transporters from >1500 individuals representing 17 subspecies of the four honey bee main lineages will be analyzed. The functional annotation and effects of each variant will then be predicted using SnpEff and the allele frequency and FST (fixation index) of each SNP per population and evolutionary lineages will be calculated. It is expected to have highly differentiated SNPs among the different subspecies/lineages.
- Diversity patterns of P450 genes in 17 honey bee subspeciesPublication . Li, Fernanda; Yadró Garcia, Carlos A.; Rufino, José; Rosa-Fontana, Annelise; Verbinnen, Gilles; Graaf, Dirk C. de; De Smet, Lina; Pinto, M. Alice; Henriques, DoraHoney bees (Apis mellifera) inhabit a vast geographical range, spanning diverse natural and agricultural ecosystems. They are exposed to different levels and types of natural (such as plant allelochemicals) and synthetic (such as pesticides) xenobiotics within this range. Several genes have been implicated in the resistance of insects to pesticides, including the P450 monooxygenases superfamily that contains 46 genes. Here, the sequences of P450 monooxygenases from >1500 individuals representing 17 subspecies of the four honey bee main lineages will be analyzed. The functional annotation and effects of each variant will then be predicted using SnpEff and the allele frequency and FST (fixation index) of each SNP per population and evolutionary lineages will be calculated. It is expected to have highly differentiated SNPs among the different subspecies/lineages.
- Genetic Diversity of Detoxification Genes in 18 Honey Bee SubspeciesPublication . Li, Fernanda; Barbosa, Daniela; Bashir, Sana; Moreira de Sá, Leandro; Yadró Garcia, Carlos A.; Rufino, José; Rosa-Fontana, Annelise; Verbinnen, Gilles; de Graaf, Dirk; de Smet, Lina; Taliadoros, Demetris; Webster, Matthew; Pinto, M. Alice; Henriques, DoraThe honey bees (Apis mellifera) is a key pollinator that is exposed to a wide array of xenobiotics, both natural (plant allelochemicals) and synthetic (pesticides), while foraging or through contaminated food within the hive. These compounds have both lethal and sub-lethal effects, impairing foraging activity and negatively affecting bee development and colony health. Similar to other insects, honey bees rely on detoxification pathways to metabolise xenobiotics into less toxic or more readily excretable forms. This process is a key mechanism underlying insecticide resistance and is influenced by genetic variation. Therefore, investigating polymorphisms in detoxification-related genes is a promising approach to predict species-specific responses to pesticide exposure. Five major gene families are involved in xenobiotic detoxification: cytochrome P450 monooxygenases (CYPs), carboxyl/cholinesterases (CCEs), glutathione Stransferases (GSTs), ATP-binding cassette transporters (ABCs), and uridine 5′-diphospho-glucuronosyltransferases (UGTs). In this study, we examined the genomic detoxification inventory of over 1,600 individuals representing 18 A. mellifera subspecies representing the four main evolutionary lineages. For each lineage and subspecies, single-nucleotide polymorphism (SNP) loci were identified within these genes, allele frequency and FST (fixation index) were calculated. Additionally, all variants were annotated to assess their potential impact on protein function. Findings from this study have the potential to inform breeding and conservation strategies by identifying populations more vulnerable to chemical stressors, ultimately supporting honey bee health in changing environments.
- Genetic variation of detoxification genes: from genes to proteinsPublication . Henriques, Dora; Li, Fernanda; Bashir, Sana; Quaresma, Andreia; Lopes, Ana Rita; Taliadoros, Demetris; Webster, Matthew; Shiraishi, Carlos S.H.; Yadró Garcia, Carlos A.; Abreu, Rui M.V.; Rufino, José; Rosa-Fontana, Annelise; Verbinnen, Gilles; Graaf, Dirk C. de; De Smet, Lina; Pinto, M. AliceHoney bees (Apis mellifera) are exposed to natural and synthetic xenobiotics, requiring genetic adaptations for survival. Several gene families have been implicated in insect pesticide resistance, including cytochrome P450s, glutathione-S-transferases (GSTs), esterases, and uridine diphosphate (UDP)-glycosyltransferases. This study investigates genetic variation in these detoxification gene families and predicts the structural and functional effects of non-synonymous SNPs (single nucleotide polymorphisms) on protein structure and function. We analyzed SNPs mapped to these detoxification genes extracted from over 1,500 whole genomes representing 15 subspecies and the four main honey bee lineages: M, C, A, and O. Functional annotation and variant effects were predicted using SnpEff. Allele frequencies and each SNP’s fixation index (FST) were calculated per population and evolutionary lineage. Bioinformatics and molecular modeling techniques were employed to evaluate non-synonymous SNPs’ structural and functional consequences. Protein structures were generated from FASTA files using AlphaFold3, converted from mmCIF to PDB format, and visualized in PyMOL. Functional site predictions were performed using Proteins Plus, and molecular dynamics simulations were conducted in YASARA to assess stability and conformational changes in proteins. Our results indicate many non-synonymous SNPs in some subspecies, such as A. m. jemenitica and A. m. intermissa. The genes with the highest number of non-synonymous mutations belong to the CYP family, particularly Probable cytochrome P450 6a14 and CYP9Q1. Conversely, genes such as Cytochrome P450 6k1 and Methyl farnesoate epoxidase exhibit no non-synonymous SNPs. By understanding intraspecific genetic variation, we move closer to reliably predicting how honey bee populations will respond to pesticide exposure.
- Why single snp analyses fail: epistatic structural effects in honey bee CYP336A1Publication . Li, Fernanda; Lima, Daniela; Bashir, Sana; Yadró Garcia, Carlos A.; Graaf, Dirk C. de; De Smet, Lina; Verbinnen, Gilles; Rosa-Fontana, Annelise; Rufino, José; Martín-Hernández, Raquel; Pinto, M. Alice; Henriques, DoraCytochrome P450 enzymes are central to pesticide metabolism and resistance, yet how these proteins diversify substrate specificity while maintaining catalytic function remains poorly understood. A genome-wide analysis of CYP336A1 (a nicotine-metabolizing P450) across 1467 Apis mellifera males from 25 countries spanning the Mediterranean, Middle East, Europe, and Cuba revealed an intricate haplotype architecture. Despite the detection of only 28 single-nucleotide variants (SNPs), 45 distinct haplotypes were detected for CYP336A1. Among these, 23 haplotypes carried at least four SNPs, and four harboured more than 10. A five-SNP haplotype (D202G; M207I; I222V; V226I; Q238K) dominated at 36% frequency, far exceeding the next most common single-SNP haplotype (D262N, 9%). Interestingly, this dominant haplotype was completely absent from the Iberian Peninsula, North Africa, and Oman and, consequently, from five A. mellifera subspecies: iberiensis, intermissa, jemenitica, mellifera and sahariensis. To investigate the functional impact of the identified variants, individually and in combination, we used in sillico protein structural approaches. Protein models were generated with trRosetta, validated with MolProbity, and evaluated using TM-score and RMSD via TM-Align. Structural modelling revealed remarkable fold congruency: the enzyme encoded by the five-SNP haplotype retained a near-identical fold as compared to the wild-type enzyme (TM-score = 0.998, RMSD = 0.34 Å), as did a rarer 13-SNP haplotype (2%) (TM-score = 0.998, RMSD = 0.38 Å). Individual SNPs also produced minimal backbone displacement (0.32–0.54 Å), suggesting that P450 diversification proceeds through subtle structural adjustments rather than major disruption. Moreover, most SNPs clustered within substrate-recognition regions, whereas catalytic residues remained invariant across haplotypes, demonstrating a partitioning between substrate-recognition/binding evolution and preservation of catalytic machinery. Importantly, single-variant effects cannot predict multi-variant haplotype outcomes. As such, heavy reliance on individual SNPs for pesticide risk assessment may misestimate real metabolic capacity.