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

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Summary

Honey bee drones provide a valuable haplotype resource due to their haploid nature. This new resource, AmelHap, enables accurate genotype imputation and phasing for diverse bee populations.

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Area of Science:

  • Genomics
  • Population Genetics
  • Entomology

Background:

  • Honey bee (Apis mellifera) drones are haploid, inheriting alleles solely from their queen.
  • This haploid nature makes them ideal for establishing known allele combinations (haplotypes).
  • Existing haplotype resources for honey bees are limited.

Purpose of the Study:

  • To create a comprehensive haplotype resource for honey bees using whole-genome sequencing data.
  • To demonstrate the utility of this resource for genotype imputation and phasing.
  • To provide a reference panel for population genetic and evolutionary analyses.

Main Methods:

  • Collation of whole-genome sequence data from 1,407 honey bee drones across 19 countries and 8 subspecies.
  • Alignment to the Amel_HAv3.1 reference genome.
  • Variant calling and quality filtering to identify high-quality genetic variants.

Main Results:

  • A high-quality variant dataset of 17.4 million variants across 1,328 samples was generated.
  • The AmelHap resource achieved >95% concordance for genotype imputation, even with significant data loss.
  • Demonstrated high accuracy for phasing diploid honey bee genomes.

Conclusions:

  • The AmelHap resource is a valuable tool for honey bee genetic research.
  • It facilitates accurate genotype imputation from low-depth sequencing or SNP chip data.
  • It serves as a comprehensive reference panel for population genetics and evolutionary studies.