AmelHap: Leveraging drone whole-genome sequence data to create a honey bee HapMap.

TitleAmelHap: Leveraging drone whole-genome sequence data to create a honey bee HapMap.
Publication TypeJournal Article
Year of Publication2023
AuthorsParejo, M, Talenti, A, Richardson, M, Vignal, A, Barnett, M, Wragg, D
JournalSci Data
Date Published2023 Apr 10
KeywordsAnimals, Base Sequence, Bees, Biological Evolution, Female, Genome, Insect, Genotype, HapMap Project

Honey bee, Apis mellifera, drones are typically haploid, developing from an unfertilized egg, inheriting only their queen's alleles and none from the many drones she mated with. Thus the ordered combination or 'phase' of alleles is known, making drones a valuable haplotype resource. We collated whole-genome sequence data for 1,407 drones, including 45 newly sequenced Scottish drones, collectively representing 19 countries, 8 subspecies and various hybrids. Following alignment to Amel_HAv3.1, variant calling and quality filtering, we retained 17.4 M high quality variants across 1,328 samples with a genotyping rate of 98.7%. We demonstrate the utility of this haplotype resource, AmelHap, for genotype imputation, returning >95% concordance when up to 61% of data is missing in haploids and up to 12% of data is missing in diploids. AmelHap will serve as a useful resource for the community for imputation from low-depth sequencing or SNP chip data, accurate phasing of diploids for association studies, and as a comprehensive reference panel for population genetic and evolutionary analyses.

Alternate JournalSci Data
PubMed ID37037860
PubMed Central IDPMC10086014