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Bioinformatics pipeline to evaluate patterns of diversity in detoxification genes in Western Honey Bee

2025Conference object Open access
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datacite.subject.fosCiências Agrárias::Biotecnologia Agrária e Alimentar
datacite.subject.sdg02:Erradicar a Fome
datacite.subject.sdg03:Saúde de Qualidade
dc.contributor.authorBarbosa, Daniela
dc.contributor.authorLi, Fernanda
dc.contributor.authorBashir, Sana
dc.contributor.authorLopes, Ana
dc.contributor.authorYadró García, Carlos A.
dc.contributor.authorQuaresma, Andreia
dc.contributor.authorRufino, José
dc.contributor.authorRosa-Fontana, Annelise
dc.contributor.authorVerbinnen, Gilles
dc.contributor.authorGraaf, Dirk C.
dc.contributor.authorSmet, Lina de
dc.contributor.authorPinto, Maria Alice
dc.contributor.authorHenriques, Dora
dc.date.accessioned2025-06-24T15:26:04Z
dc.date.available2025-06-24T15:26:04Z
dc.date.issued2025
dc.description.abstractThe 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.eng
dc.identifier.urihttp://hdl.handle.net/10198/34621
dc.language.isoeng
dc.peerreviewedno
dc.publisherSPG
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectBioinformatics pipeline
dc.titleBioinformatics pipeline to evaluate patterns of diversity in detoxification genes in Western Honey Beeeng
dc.typeconference object
dspace.entity.typePublication
oaire.citation.conferenceDate2025
oaire.citation.conferencePlaceOeiras
oaire.citation.endPage66
oaire.citation.startPage66
oaire.citation.titleVI International Conference of the Portuguese Society of Genetics
oaire.versionhttp://purl.org/coar/version/c_be7fb7dd8ff6fe43
person.familyNameLopes
person.familyNameYadró García
person.familyNameQuaresma
person.familyNameRufino
person.familyNamePinto
person.familyNameHenriques
person.givenNameAna
person.givenNameCarlos A.
person.givenNameAndreia
person.givenNameJosé
person.givenNameMaria Alice
person.givenNameDora
person.identifier.ciencia-idF014-6835-054D
person.identifier.ciencia-idF71F-B08E-EC39
person.identifier.ciencia-id4F1A-4E4A-3F23
person.identifier.ciencia-idC414-F47F-6323
person.identifier.ciencia-idF814-A1D0-8318
person.identifier.ciencia-id291F-986F-07DA
person.identifier.orcid0000-0002-1888-2262
person.identifier.orcid0000-0002-6916-3647
person.identifier.orcid0000-0002-8678-5800
person.identifier.orcid0000-0002-1344-8264
person.identifier.orcid0000-0001-9663-8399
person.identifier.orcid0000-0001-7530-682X
person.identifier.scopus-author-id57119742600
person.identifier.scopus-author-id55947199100
person.identifier.scopus-author-id8085507800
person.identifier.scopus-author-id55761737300
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