The honey bee genome-- what has it been good for?

Toth, Amy L.; Zayed, Amro

doi:10.1007/s13592-020-00829-3

Cited by 8 publications

(8 citation statements)

References 146 publications

(136 reference statements)

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“…Thus, the queen's genotype itself is an essential piece of information for genetic analyses aimed at studying the evolution of populations or at performing selective breeding. Even though the field of insect genomics has boomed in the past decades, there still is a need to expand traditional approaches of population genetics for this specific kind of organisms (Toth & Zayed, 2021). Contrary to large animal species, sampling the queen for genotyping without threatening its integrity is risky.…”

Section: Introductionmentioning

confidence: 99%

Reconstructing queen genotypes by pool sequencing colonies in eusocial insects: Statistical Methods and their application to honeybee

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Canale-Tabet

et al. 2022

Molecular Ecology Resources

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Eusocial insects are crucial to many ecosystems, and particularly the honeybee (Apis mellifera). One approach to facilitate their study in molecular genetics, is to consider whole‐colony genotyping by combining DNA of multiple individuals in a single pool sequencing experiment. Cheap and fast, this technique comes with the drawback of producing data requiring dedicated methods to be fully exploited. Despite this limitation, pool sequencing data have been shown to be informative and cost‐effective when working on random mating populations. Here, we present new statistical methods for exploiting pool sequencing of eusocial colonies in order to reconstruct the genotypes of the queen of such colony. This leverages the possibility to monitor genetic diversity, perform genomic‐based studies or implement selective breeding. Using simulations and honeybee real data, we show that the new methods allow for a fast and accurate estimation of the queen's genetic ancestry, with correlations of about 0.9 to that obtained from individual genotyping. Also, it allows for an accurate reconstruction of the queen genotypes, with about 2% genotyping error. We further validate these inferences using experimental data on colonies with both pool sequencing and individual genotyping of drones. In brief, in this study we present statistical models to accurately estimate the genetic ancestry and reconstruct the genotypes of the queen from pool sequencing data from workers of an eusocial colony. Such information allows to exploit pool sequencing for traditional population genetics analyses, association studies and for selective breeding. While validated in Apis mellifera, these methods are applicable to other eusocial hymenopterans.

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Section: Introductionmentioning

confidence: 99%

Reconstructing queen genotypes by pool sequencing colonies in eusocial insects: Statistical Methods and their application to honeybee

Vignal

Basso

Canale-Tabet

et al. 2022

Molecular Ecology Resources

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“…Bees depend on RNA interference (RNAi) as a post-transcriptional gene expression regulatory mechanism and core component of their antiviral immune system. Double-stranded RNA (dsRNA) molecules or hair-pinned microRNAs are processed and then used by the RNA-induced silencing complex (RISC), which triggers an immune cascade that inhibits translation of target RNA molecules in a sequence-specific manner. − Prokaryotic microalgae such as spirulina can produce large quantities of dsRNA using light and CO 2 , making them a sustainable source of dsRNA, which is expensive to produce in vitro. Recently, a honey bee gut symbiont was engineered to deliver sequence-specific dsRNAs, resulting in RNAi activation .…”

Section: Discussionmentioning

confidence: 99%

Efficacy of a Microalgal Feed Additive in Commercial Honey Bee Colonies Used for Crop Pollination

McMenamin,

Weiss,

Meikle

et al. 2023

ACS Agric. Sci. Technol.

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Honey bees are experiencing nutritional deficiencies related to intensive agriculture and climate change, posing major threats to the ecosystem services they provide. Colonies managed for crop pollination are fed artificial diets to offset reduced pollen in the environment and to stimulate population growth. Here, we evaluated the effects of a spirulina microalga feed additive on commercial honey bee colonies in an agriculturally intensive desert environment. One hundred honey bee colonies were used in a randomized block design that was replicated at two apiary sites over 4 months leading up to spring almond pollination. Colonies were fed a pollen-free artificial diet or the same diet containing 25% spirulina. Unfed colonies were randomly assigned within treatment blocks as controls. We measured colony population size, brood production, thermoregulation, and a panel of molecular biomarkers associated with nutritional status, stress responses, and gut microbiota. Hive brood imaging and continuous temperature data enabled sensitive detection of diet treatment effects. Spirulina feed significantly improved brood production and thermoregulation prior to almond pollination relative to unfed controls. Bees fed spirulina had distinct expression profiles of nutrition and stress response genes, but gene expression was primarily driven by the apiary site. We conclude that spirulina is a sustainable feed additive with potential to improve crop pollination efficiency by supporting larger, healthier honey bee colonies.

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“…The honey bee, Apis mellifera , is the most important managed pollinator for crop and wild flora worldwide 1 , 2 . Since the publication of the honey bee genome in 2006 it has received much attention by the scientific community, resulting in an increasing number of papers on honey bee genomics 3 . In fact, numerous whole-genome sequencing studies have been published since, studying honey bee population structure and diversity 4 – 8 , evolutionary history 9 , 10 , and investigating signatures of selection 11 – 13 not only in extant populations, but also museum specimens 14 .…”

Section: Background and Summarymentioning

confidence: 99%

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

et al. 2023

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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.

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The honey bee genome-- what has it been good for?

Cited by 8 publications

References 146 publications

Reconstructing queen genotypes by pool sequencing colonies in eusocial insects: Statistical Methods and their application to honeybee

Reconstructing queen genotypes by pool sequencing colonies in eusocial insects: Statistical Methods and their application to honeybee

Efficacy of a Microalgal Feed Additive in Commercial Honey Bee Colonies Used for Crop Pollination

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

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