ArticleScientific data2016
A variant reference data set for the Africanized honeybee, Apis mellifera.
Article in Scientific data, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Are you my mother? When host genetics and gut microbiota tell different phylogenetic stories in the Africanized honey bee hybrid (Microbiology spectrum · 2025Article
- Accurate Detection ofEcology and evolution · 2024Article
- HBeeID: a molecular tool that identifies honey bee subspecies from different geographic populations.BMC bioinformatics · 2024Article
- Article
- Article
- Selection and hybridization shaped the rapid spread of African honey bee ancestry in the Americas.PLoS genetics · 2020Article
- Defense Response in Brazilian Honey Bees (Apis mellifera scutellata × spp.) Is Underpinned by Complex Patterns of Admixture.Genome biology and evolution · 2020Article
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The Africanized honeybee (AHB) is a population of Apis mellifera found in the Americas. AHBs originated in 1956 in Rio Clara, Brazil where imported African A. m. scutellata escaped and hybridized with local populations of European A. mellifera. Africanized populations can now be found from Northern Argentina to the Southern United States. AHBs-often referred to as 'Killer Bees'- are a major concern to the beekeeping industry as well as a model for the evolutionary genetics of colony defence. We performed high coverage pooled-resequencing of 360 diploid workers from 30 Brazilian AHB colonies using Illumina Hi-Seq (150 bp PE). This yielded a high density SNP data set with an average read depth at each site of 20.25 reads. With 3,606,720 SNPs and 155,336 SNPs within 11,365 genes, this data set is the largest genomic resource available for AHBs and will enable high-resolution studies of the population dynamics, evolution, and genetics of this successful biological invader, in addition to facilitating the development of SNP-based tools for identifying AHBs.
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