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Attack of the dark clones the genetics of reproductive and color traits of South African honey bees (Apis mellifera spp.)

  • Laura Patterson Rosa ,

    Roles Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Validation, Visualization, Writing – original draft, Writing – review & editing

    ‡ LPR and AE are first co-authors and contributed equally to the work and SAB and JDE are co-senior authors and contributed equally to the work.

    Affiliation Honey Bee Research and Extension Laboratory, Entomology and Nematology Department, University of Florida, Gainesville, Florida, United States of America

  • Amin Eimanifar ,

    Roles Conceptualization, Investigation, Writing – original draft, Writing – review & editing

    ‡ LPR and AE are first co-authors and contributed equally to the work and SAB and JDE are co-senior authors and contributed equally to the work.

    Affiliation Independent Senior Research Scientist, Industrial District, Easton, Maryland, United States of America

  • Abigail G. Kimes,

    Roles Data curation, Formal analysis, Investigation, Validation, Writing – original draft, Writing – review & editing

    Affiliation Department of Animal Sciences, University of Florida, Gainesville, Florida, United States of America

  • Samantha A. Brooks ,

    Roles Conceptualization, Investigation, Methodology, Project administration, Software, Supervision, Writing – review & editing

    ‡ LPR and AE are first co-authors and contributed equally to the work and SAB and JDE are co-senior authors and contributed equally to the work.

    Affiliations Department of Animal Sciences, University of Florida, Gainesville, Florida, United States of America, UF Genetics Institute, University of Florida, Gainesville, Florida, United States of America

  • James D. Ellis

    Roles Conceptualization, Formal analysis, Funding acquisition, Project administration, Resources, Supervision, Writing – review & editing

    ‡ LPR and AE are first co-authors and contributed equally to the work and SAB and JDE are co-senior authors and contributed equally to the work.

    Affiliation Honey Bee Research and Extension Laboratory, Entomology and Nematology Department, University of Florida, Gainesville, Florida, United States of America


The traits of two subspecies of western honey bees, Apis mellifera scutellata and A.m. capensis, endemic to the Republic of South Africa (RSA), are of biological and commercial relevance. Nevertheless, the genetic basis of important phenotypes found in these subspecies remains poorly understood. We performed a genome wide association study on three traits of biological relevance in 234 A.m. capensis, 73 A.m. scutellata and 158 hybrid individuals. Thirteen markers were significantly associated to at least one trait (P ≤ 4.28 × 10−6): one for ovariole number, four for scutellar plate and eight for tergite color. We discovered two possible causative variants associated to the respective phenotypes: a deletion in GB46429 or Ebony (NC_007070.3:g.14101325G>del) (R69Efs*85) and a nonsense on GB54634 (NC_007076.3:g.4492792A>G;p.Tyr128*) causing a premature stop, substantially shortening the predicted protein. The mutant genotypes are significantly associated to phenotypes in A.m. capensis. Loss-of-function of Ebony can cause accumulation of circulating dopamine, and increased dopamine levels correlate to ovary development in queenless workers and pheromone production. Allelic association (P = 1.824 x 10−5) of NC_007076.3:g.4492792A>G;p.Tyr128* to ovariole number warrants further investigation into function and expression of the GB54634 gene. Our results highlight genetic components of relevant production/conservation behavioral phenotypes in honey bees.


Modern western honey bees (Apis mellifera) show substantial genetic and phenotypic variation across their extensive geographic range [1]. They occur naturally in Europe, the Middle East, western Asia, and Africa, where the species is composed of between 25–35 subspecies [24]. This bee has been spread outside its native range to the Americas, Australia, New Zealand, and other locations globally, largely due its ability to produce honey and its use as the principal pollinator of a variety of agricultural crops.

Two subspecies of western honey bees, A.m. scutellata and A.m. capensis, are among those endemic to the Republic of South Africa (RSA) [5]. Apis mellifera scutellata is a light-colored phenotype and is adapted for survival in hot and arid climates in central and southern Africa [6]. It also displays behavioral traits that many beekeepers outside its native range consider undesirable. These include excessive swarming (colony-level reproduction), absconding (complete nest abandonment), usurpation (swarm takeover of another colony) and heightened defensiveness [68]. This honey bee subspecies was introduced into Brazil in the 1950’s in an effort to improve the Brazilian beekeeping industry [9]. It hybridized with local stocks of European-derived honey bees, becoming known as “Africanized” or “killer” bees. They are now considered invasive throughout South America, Central America and southern regions of North America [7, 10].

Apis mellifera capensis is a darker colored honey bee subspecies found in the Fynbos region of RSA, where the climate is Mediterranean with rainy winters. In contrast to A.m. scutellata, this bee can act as a social parasite, given its workers can reproduce via thelytoky [6], a type of parthenogenesis in which female offspring can result from unfertilized eggs. This trait allows some worker bees to develop into pseudoqueens with semi-developed spermathecae, that remain unused, and a larger-than-normal number of ovarioles [1115]. These worker bees, then, can fly into neighboring hives and replace the queens contained within, becoming the reproductive in the nest [16]. Interestingly, colonies headed by A.m. capensis workers are doomed, as laying workers cannot maintain the egg output of that of a normal queen. The colonies eventually dwindle and die, resulting in the ‘capensis calamity’ that has plagued the South African beekeeping industry in the past [17].

Despite the perceived drawbacks associated with these bees outside their native range, beekeepers in RSA keep both subspecies for management purposes. Nevertheless, the potential movement of both bee subspecies beyond where they currently occur remains a concern of beekeepers and regulatory officials in many areas globally. These concerns have led to the search for better methods to identify both bee subspecies and their hybrids quickly and reliably. Recently developed techniques based on the reduction of genome complexity, such as Genotyping by Sequencing (GBS), have the potential to provide a large number of SNPs in understudied genomes, enabling genetic diagnostics for monitoring these two subspecies [18]. Despite genomic studies on various honey bee subspecies, the genetic basis of important phenotypes found in A.m. scutellata and A.m. capensis remain poorly understood, though progress has been made with the thelytoky trait [1925]. We have the opportunity to fill this gap given recent work [26] that used traditional morphometric techniques to identify populations of both bees from samples collected in RSA.

In the present study, we performed a genome wide association study (GWAS) on three traits (number of ovarioles, tergite and scutellar plate color) measured in 464 A.m. capensis, A.m. scutellata and hybrid individuals (S1 Table) [26]. These same bees had been examined previously using GBS [18]. Apis mellifera capensis is known to be darker and have a greater number of ovarioles per ovary than does A.m. scutellata. Accordingly, the GWAS allowed us to determine what chromosomal regions are most associated with these phenotypic traits. The detected associations provide improved understanding of the genetic basis of phenotypic and behavioral differentiation between A.m. capensis and A.m. scutellata from RSA.


GWAS associates traits mainly to two chromosomes

The GWAS resulted in significant associations to markers on chromosomes LG1, LG2, LG7, LG9 and LG10. Thirteen markers were significantly associated to at least one trait (P ≤ 4.28 x 10−6): one for ovariole number, four for scutellar plate and eight for tergite color. A total of 10 genes are annotated in candidate regions determined by markers within r2 ≥ 0.2 to the most significant marker, and adjacent genes (Fig 1 and Table 1).

Fig 1. Manhattan and QQ plots of the respective genome wide association study for a. tergite color ranked-transformed; b. scutellar plate color ranked-transformed; and c. ovariole number rank-transformed.

Respective annotated genes within the shared regions in chromosomes LG1 and LG7, as well as genes possessing non-synonymous variants (in bold), are also shown. The red line represents the Bonferroni corrected threshold value of P ≤ 4.28 x 10−6, and markers above this line are significantly correlated to the respective trait.

Table 1. Genome wide association study traits, significant markers, respective chromosome (Chr) location, number of base pairs, statistical information, and within region/nearby annotated genes.

A frameshift and a nonsense mutation are associated to color and ovariole number

Functional inspection of annotated genes within each candidate region indicated two genes with coding variants. The likely candidate gene for tergite and scutellar plate color is GB46429, mycosubtilin synthase subunit C, also known as Ebony, a non-ribosomal peptide synthetase, which also has sequence similarities to microbial enzymes [27]. This gene shares 46.99% (EnsemblMetazoa release 103, LOC409109) [28] of its sequence with the Drosophila melanogaster Ebony gene. A deletion identified by the GBS pipeline in GB46429 (NC_007070.3:g.14101325G>del) (R69Efs*85) leads to an early stop codon and truncates the normal amino acid sequence from the predicted 860aa to only 85 amino acids.

A single variant was found for ovariole number within the coding region of GB54634. The nonsense SNP (NC_007076.3:g.4492792A>G;p.Tyr128*) causes a premature stop, shortening the protein by two of the six predicted exons (45% of the protein sequence) (Fig 2).

Fig 2. Predicted protein structure (Phyre2) for both wild type and discovered variants of genes.

a.GB46429 (Ebony), correlated to both scutellar plate and tergite color phenotypes., and b. GB54634, correlated to ovariole number.

The distribution of causative variants demonstrates that the mutant form is significantly associated to phenotypes in A.m. capensis, while the wildtype locus is associated to A.m. scutellata phenotypes (Fig 3). No coding variants were discovered in our GBS dataset for the other annotated genes within each candidate region; yet these could hold biological effects of interest for the honey bee.

Fig 3. Allele distribution for variants discovered in GB54634 and GB46429 (Ebony), as well as respective color phenotypes.

a. Ruttner [2] ranking for tergite color, also applied to scutellar plate phenotyping [19]; b. Allelic distribution of the NC_007070.3:g.14101325G>del;p.R69Efs*85 variant for tergite color and c. scutellar plate color; d. Allelic distribution of the NC_007076.3:g.4492792A>G;p.Tyr128* variant for ovariole number; and e. Individuals from the Apis mellifera scutellata (above) and A.m. capensis (below) representing the variation in color [29].


Color variation in honey bees may have diverse biological implications [30]. For example, Gloger’s rule states that coloration changes according to environmental effects, and species tend to be darker in hot and humid environments [31]. Yet, this rule might not apply to the present case, as the A.m. scutellata individuals were collected from, on average, warm semi-arid zones, while the A.m. capensis or hybrid samples came from cooler, Mediterranean or cool subtropical zones; yet, A.m. scutellata had significantly lighter phenotypes both in tergite and scutellar plate color [26]. Additionally, previous thelytoky genome mapping efforts pointed to a locus near GB46429 [24]. However further inspection into expression and gene function demonstrated that this gene has no apparent effect on the mode of parthenogenesis in the honey bee, but segregates according to subspecies and color [32].

In Drosophila melanogaster, the orthologous gene to GB46429 is Ebony (named after the mutant phenotype): darker Drosophila flies have lower expression, while lighter individuals have normal to high expression of Ebony [33]. Variants in Ebony also contribute to diverse phenotypic variations including behavioral, neurologic, locomotor, and visual ability [34, 35]. Some Drosophila Ebony mutants’ electroretinograms lacked the on- and off-transients of light response [36, 37]. Most importantly, Ebony participates in dopaminergic neuron function, metabolizing dopamine into N-β-alanyl dopamine (NBAD) [38]. We discovered a single nonsense variant in GB46429 (Ebony) significantly associated to color phenotypes in both honey bee subspecies and hybrids of the two. Furthermore, this variant severely impacts the predicted protein structure and may lead to loss-of-function of this protein. Consistent with our findings, loss-of-function Ebony mutants in Drosophila accumulate circulating dopamine, which is then directed to other pathways [39]. In the honey bee, increased dopamine levels correlate to ovary development in queenless workers, as the queen mandibular pheromone (QMP) regulates dopamine pathways in the worker bees [40, 41]. In A.m. capensis, pheromonal dominance allows for parasitic behavior, even in the presence of an A.m. scutellata queen [42]. We postulate that the mutant GB46429 causes a darker pigmentation phenotype and may play a role in dopaminergic pathways and parasitic behavior in A.m. capensis. This gene’s contribution to behavioral and reproductive traits in honey bees is worthy of further investigation.

Previous work evaluating quantitative trait loci (QTLs) impacting the number of ovarioles in honey bees resulted in a significant QTL on LG11 [43]. Although our GWAs did not associate any markers on LG11 to ovariole number, this difference in findings could be due to population genetic differences as the LG11 QTL resulted from Africanized Honey Bees (AHB) collected in Arizona, USA, compared to European Honey Bee samples collected from US commercial colonies.

Unfortunately, there is little information of the function and expression of the GB54634 gene in honey bees even though we found the significant (P = 1.824 x 10−5) allelic association of the NC_007076.3:g.4492792A>G;p.Tyr128* variant to ovariole number (Fig 3). The GB54634 gene was tagged by genomic sweeps associated to social parasitic behavior [44] and A.m. capensis versus A.m. scutellata differentiation [18], although candidate genes for thelytoky phenotype recently reported do not implicate GB54634 in this specific phenotype [24, 25]. Additionally, this uncharacterized protein (LOC725260 isoform X1) does not seem to differ in expression and splicing in the presence or absence of queen pheromones [45]. Yet, this expression analysis was conducted in an uncharacterized A. mellifera subspecies; thus, findings could be different for A. m. capensis and A. m. scutellata. Given the correlation reported here, further investigation into association of this variant to social parasitic traits such as the number of ovarioles, as well as possible pleiotropic effects, warrants additional exploration and biological characterization of GB54634.

Although we did not discover coding sequence variants for the other genes within candidate regions, biological functions related to A. m. capensis phenotypes may be of interest for future analysis. For instance, candidate regions for the color traits GB43750 (prefoldin subunit 5) are located within a haplotype associated to high altitude adaptation in A. m. scutellata [46].

TK (prepro-AmTRP or tachykinin) was also found in the candidate region associated to ovariole number in the GWAS. Previously implicated in female-related behavior, the expression levels of prepro-AmTRP are present only in the brain of female bees (queens and workers) and show lower expression levels according to labor division (lower in younger/nurse bees, higher in queens and foragers) [47]. The tachykinin neuropeptide also controls metabolic and desiccation responses in Drosophila [48, 49] and is related to aggression in other insects, such as the Leaf-Cutting Ant Acromyrmex echinatior [50]. Other AmTRP neuropeptides are implicated in the defensive behavior of Africanized honey bees [51].

Several genomic regions are likely involved in ovariole number, a social parasitism-related phenotype of A.m. capensis colonies [44]. The GB46427 gene (LOC409096) within the ovariole number LG1 candidate region is implicated in parasitism behavior and was deemed the thelytoky gene [24], also demonstrating Log2-fold differential expression of 3.24 to 4.68 between thelytokous A.m. capensis and arrhenotokous A.m. scutellata [24, 44]. A non-synonymous variant (p.Thr400Ile) likely responsible for this differential expression was suggested as the sole change responsible for thelytoky in worker bees [24]. Our GBS dataset did not possess any variants within the coding region of this gene; thus, we could not evaluate the phenotypic repercussions. Furthermore, GB46500 (LOC724495 or Ethr) is also in linkage with GB46427 [24]. In Drosophila, lower levels of the hormones transcribed by Ethr halt oogenesis and ovulation during nutritional or heat stress [52]. Therefore, its effects on honey bee social parasitism might be of biological relevance, though we could not find coding variants for this gene.


We associated genomic regions with important biological phenotypes as tergite color, scutellar plate color, and ovariole number within A.m. capensis and A.m. scutellata populations from RSA. Among the 28 candidate genes identified, Ebony, within the tergite color candidate region on chrLG1, possessed a variant predicted to alter protein structure significantly. Furthermore, non-functional variants of Ebony impacting pigmentation are well-documented in other insect species. Although the candidate variant correlated to ovariole number is in an uncharacterized gene, further investigations into its function are warranted given its biological implications. Our results help pave the way for the development of marker-assisted selection and diagnostic genetic differentiation in the honey bee and highlight potentially production/conservation relevant pleiotropic behavioral phenotypes.

Material and methods

Honey bee samples

The samples included 464 adult worker honey bees collected from RSA in 2013 and 2014. The samples were collected from managed colonies of A. mellifera with permission granted by the owner beekeepers (see Acknowledgements). Location data for the samples, including GIS coordinates, can be found in S1 File. Combined morphometrics, SNP, microsatellite and mitochondrial DNA data were used to determine that 73 bees were A.m. scutellata, 234 were A.m. capensis and 158 were hybrids of the two subspecies [18, 26, 53, 54]. Phenotyping methods as described in [19] determined morphometric phenotypes that significantly differed between the two subspecies of honey bees. We utilized the following traits in a GWA: number of ovarioles, pigmentation of abdominal tergite (A3) and pigmentation of the scutellar plate (Fig 4 and S1 File). The distribution for these quantitative phenotypes within the 464 samples was not normal; thus, we normalized the data prior to the GWAs using a Rank normalization on JMP®, Version 15 (SAS Institute Inc., Cary, NC, 1989–2019).

Fig 4. Distribution of morphometric phenotypic traits per subspecies, representing a. Ovariole Number quantile, b. Tergite Color quantile and c. Scutellar Plate color ranking.

Red represents increased number of ovarioles (a) or lighter phenotypes (b and c), while blue represents lower number of ovarioles (a) and darker phenotypes (b and c). The visual distribution seems to correlate to the subspecies or hybrid geographical distribution.

Genotyping and SNP QC

DNA extraction, library construction, sequencing and quality control criteria were conducted by The Genomic Diversity Facility at Cornell University. The GBS methods were previously described [18], and resulted in an average of 70,475 SNPs per individual sample. We filtered GBS SNPs (coded as major/minor allele) using VCFtools version 0.1.15 [55] and the following criteria: (1) no more than two alleles, neither of which was a gap allele, (2) a minor allele frequency (MAF) of at least 5%, (3) no more than 92% missing data, (4) mapped to one of the 16 assembled A. mellifera chromosomes in the Amel4.5 assembly [56] and (5) with an index of panmixia (FIT) of at least −0.2. After quality control, 20,006 SNPs were left. We then imputed missing genotypes for the 20,006 loci using Beagle 4.1 [57] with a window and overlap of 500 and 50 sites, respectively. After imputation, the SNPs were again filtered for MAF of at least 5%, resulting in a total of 11,656 SNPs retained per individual. The resulting VCF file was converted to PLINK format/binary ped format with the—recode—make-bed command in PLINK version 1.90b3.39 [58].

Genome wide association study

We performed a GWAS using a mixed linear model (MLM) analysis with the interrogated SNPs falling on the same chromosome as the given candidate SNP excluded from the genetic relationship matrix calculation (—mlma-loco) in GCTA ver. 1.25.2 [59]. A genetic relationship matrix (GRM) was included in the MLM analysis to compensate for population structure within the sample. We utilized a Bonferroni corrected threshold of P ≤ 1.429 × 10−6 as the significance cutoff based on 11,656 SNPs tested and the three traits analyzed (α = 0.05). We visualized GWA results in JMP®, Version 15 (SAS Institute Inc., Cary, NC, 1989–2019).

Identification of candidate genes and functional variants

Markers above Bonferroni correction were inspected for supporting linkage (r2) in PLINK (—chr [ChromosomeNumber]—r2—ld-snp [MarkerID]—ld-window-r2 0.00—ld-window 100000). Loci with a r2 ≥ 0.2 to the lowest p-value SNP defined the boundaries of candidate regions considered for further analysis [60, 61]. We also evaluated genes adjacent to each candidate region, determined using the NCBI/GenBank annotation GCF_000002195.4 /GCA_000002195.1 (Amel 4.5) [56]. Gene function was also reported based on its homology to functionally characterized genes from the A. mellifera genome (Amel 4.5) using the EnsemblMetazoa database (release 103) [28] and a comprehensive scientific literature search on other Hymenoptera order members [62, 63].

Visual inspection of genomic regions for polymorphisms within coding regions was performed on the unfiltered, not imputed, GBS generated. vcf file, aligned, and uploaded to NCBI Apis mellifera 4.5 (accession number GCF_000002195.4), coded as major/minor allele. For candidate mutations, we evaluated protein impact using Phyre2, modeling both the wild type and the sequence containing mutation(s) [64]. Allelic association of causative polymorphisms to traits was performed on JMP®, Version 15 (SAS Institute Inc., Cary, NC, 1989–2019) using ANOVA, with the significance threshold set to P ≤ 0.00833 based on multiple tests per allele (0.05/6).

Supporting information

S1 File. Phenotypic information, geographical coordinates and candidate variant genotypes for samples used in this study.

Ovary number value, scutellar plate and tergite color scores and respective rank transformations, as well as respective combined probable Apis mellifera subspecies ID and candidate variant genotypes per sample.


S2 File. Candidate variant distribution of alleles per subspecies.


S1 Table. Sample Apis mellifera subspecies assignment per source information.

Hybrid = A cross between A.m. scutellata and A.m. capensis. NA = bee samples from that location were not included in the respective analysis. The “Combined Probable ID” is inferred from the most common identification (ID) made across the four referenced studies and it parallels the identifications assigned using SNPs.



We thank current and former members of the University of Florida Honey Bee Research and extension Laboratory who collected honey bee samples across the Republic of South Africa: Tomas Bustamante, Mark Dykes, Ashley Mortensen, and Daniel Schmehl. We also thank Mathias Ellis for assistance with sample collection. We graciously acknowledge Mike Allsopp (ARC-Plant Protection Research Institute, RSA), Christian Pirk (University of Pretoria, RSA), and Garth Cambray for the assistance they provided in coordinating field sample collections and/or providing samples. We also thank the RSA beekeepers who allowed us to sample their colonies. We thank Dr. Ann Staiger for all the scientific input that improved the outcome of this research.


  1. 1. Wallberg A, Han F, Wellhagen G, Dahle B, Kawata M, Haddad N, et al. A worldwide survey of genome sequence variation provides insight into the evolutionary history of the honeybee Apis mellifera. Nature genetics. 2014;46(10):1081–8. pmid:25151355
  2. 2. Ruttner F. Biogeography and taxonomy of honeybees. 1988 3540177817.
  3. 3. Alburaki M, Bertrand B, Legout H, Moulin S, Alburaki A, Sheppard WS, et al. A fifth major genetic group among honeybees revealed in Syria. BMC genetics. 2013;14(1):1–11. pmid:24314104
  4. 4. Sheppard W. Honey Bee Diversity–Races, Ecotypes and Strains. The hive and the honey bee. 2015:53–67.
  5. 5. Jaffé R, Dietemann V, Crewe RM, Moritz RFA. Temporal variation in the genetic structure of a drone congregation area: an insight into the population dynamics of wild African honeybees (Apis mellifera scutellata). Molecular Ecology. 2009;18(7):1511–22. pmid:19368651
  6. 6. Hepburn HR, Radloff SE. Honeybees of Africa. 1998.
  7. 7. Rinderer TE, Oldroyd BP, Sheppard WS. Africanized bees in the US. Scientific American. 1993;269(6):84–90.
  8. 8. Seeley TD. Honeybee ecology: a study of adaptation in social life: Princeton University Press; 2014.
  9. 9. Caron DM. Africanized honey bees in the Americas: AI Root Co.; 2001.
  10. 10. Kono Y, Kohn JR. Range and frequency of Africanized honey bees in California (USA). PLoS One. 2015;10(9):e0137407. pmid:26361047
  11. 11. Onions GW. South African Fertile-Worker Bees. Agricultural Journal of the Union of South Africa. 1912;3(5):720.
  12. 12. Phiancharoen M, Pirk CWW, Radloff SE, Hepburn R. Clinal nature of the frequencies of ovarioles and spermathecae in Cape worker honeybees, Apis mellifera capensis. Apidologie. 2010;41(2):129–34.
  13. 13. Ruttner F, editor The cape bee: a biological curiosity1977.
  14. 14. Härtel S, Neumann P, Kryger P, Von Der Heide C, Moltzer G-J, Crewe RM, et al. Infestation levels of Apis mellifera scutellata swarms by socially parasitic Cape honeybee workers (Apis mellifera capensis). Apidologie. 2006;37(4):462–70.
  15. 15. Mumoki FN, Yusuf AA, Pirk CWW, Crewe RM. The Biology of the Cape Honey Bee, Apis mellifera capensis (Hymenoptera: Apidae): A Review of Thelytoky and Its Influence on Social Parasitism and Worker Reproduction. Annals of the Entomological Society of America. 2021;114(2):219–28.
  16. 16. Neumann P, Radloff SE, Moritz RFA, Hepburn HR, Reece SL. Social parasitism by honeybee workers (Apis mellifera capensis Escholtz): host finding and resistance of hybrid host colonies. Behavioral Ecology. 2001;12(4):419–28.
  17. 17. Allsopp M. The capensis calamity, S. Afr. Bee J. 64, 52–57. the text. 1992.
  18. 18. Eimanifar A, Brooks SA, Bustamante T, Ellis JD. Population genomics and morphometric assignment of western honey bees (Apis mellifera L.) in the Republic of South Africa. BMC genomics. 2018;19(1):1–26. pmid:29291715
  19. 19. Moritz RFA, Haberl M. Lack of meiotic recombination in thelytokous parthenogenesis of laying workers of Apis mellifera capensis (the Cape honeybee). Heredity. 1994;73(1):98–102.
  20. 20. Lattorff HMG, Moritz RFA, Fuchs S. A single locus determines thelytokous parthenogenesis of laying honeybee workers (Apis mellifera capensis). Heredity. 2005;94(5):533–7. pmid:15741997
  21. 21. Goudie F, Allsopp MH, Solignac M, Beekman M, Oldroyd BP. The frequency of arrhenotoky in the normally thelytokous Apis mellifera capensis worker and the Clone reproductive parasite. Insectes Sociaux. 2015;62(3):325–33.
  22. 22. Chapman NC, Beekman M, Allsopp MH, Rinderer TE, Lim J, Oxley PR, et al. Inheritance of thelytoky in the honey bee Apis mellifera capensis. Heredity. 2015;114(6):584–92. pmid:25585920
  23. 23. Cole-Clark MP, Barton DA, Allsopp MH, Beekman M, Gloag RS, Wossler TC, et al. Cytogenetic basis of thelytoky in Apis mellifera capensis. Apidologie. 2017;48(5):623–34.
  24. 24. Aumer D, Stolle E, Allsopp M, Mumoki F, Pirk CWW, Moritz RFA. A Single SNP Turns a Social Honey Bee (Apis mellifera) Worker into a Selfish Parasite. Molecular biology and evolution. 2019;36(3):516–26. pmid:30624681.
  25. 25. Yagound B, Dogantzis KA, Zayed A, Lim J, Broekhuyse P, Remnant EJ, et al. A Single Gene Causes Thelytokous Parthenogenesis, the Defining Feature of the Cape Honeybee Apis mellifera capensis. Current Biology. 2020;30(12):2248–59.e6. pmid:32386531
  26. 26. Bustamante T, Baiser B, Ellis JD. Comparing classical and geometric morphometric methods to discriminate between the South African honey bee subspecies Apis mellifera scutellata and Apis mellifera capensis (Hymenoptera: Apidae). Apidologie. 2020;51(1):123–36.
  27. 27. Hovemann BT, Ryseck R-P, Walldorf U, Störtkuhl KF, Dietzel ID, Dessen E. The Drosophila ebony gene is closely related to microbial peptide synthetases and shows specific cuticle and nervous system expression. Gene. 1998;221(1):1–9. pmid:9852943
  28. 28. Yates AD, Achuthan P, Akanni W, Allen J, Allen J, Alvarez-Jarreta J, et al. Ensembl 2020. Nucleic Acids Research. 2020;48(D1):D682–D8. pmid:31691826
  29. 29. van Noort S. WaspWeb: Hymenoptera of the Afrotropical region. 2021 [cited 2021 4/29].
  30. 30. Gruber K, Schöning C, Otte M, Kinuthia W, Hasselmann M. Distinct subspecies or phenotypic plasticity? Genetic and morphological differentiation of mountain honey bees in East Africa. Ecology and Evolution. 2013;3(10):3204–18. pmid:24223262
  31. 31. Delhey K. A review of Gloger’s rule, an ecogeographical rule of colour: Definitions, interpretations and evidence. Biological Reviews. 2019;94(4):1294–316. pmid:30892802
  32. 32. Christmas MJ, Smith NMA, Oldroyd BP, Webster MT. Social Parasitism in the Honeybee (Apis mellifera) Is Not Controlled by a Single SNP. Molecular Biology and Evolution. 2019;36(8):1764–7. pmid:31028394
  33. 33. Takahashi A, Takahashi K, Ueda R, Takano-Shimizu T. Natural variation of ebony gene controlling thoracic pigmentation in Drosophila melanogaster. Genetics. 2007;177(2):1233–7. pmid:17660557
  34. 34. Pigmentation Takahashi A. and behavior: potential association through pleiotropic genes in Drosophila. Genes & genetic systems. 2013;88(3):165–74. pmid:24025245
  35. 35. Newby LM, Jackson FR. Drosophila Ebony Mutants Have Altered Circadian Activity Rhythms but Normal Eclosion Rhythms. Journal of Neurogenetics. 1991;7(2–3):85–101. pmid:1903161
  36. 36. Hotta Y, Benzer S. Abnormal Electroretinograms in Visual Mutants of Drosophila. Nature. 1969;222(5191):354–6. pmid:5782111
  37. 37. Heisenberg M. Separation of Receptor and Lamina Potentials in the Electroretinogram of Normal and Mutant Drosophila. Journal of Experimental Biology. 1971;55(1):85–100.
  38. 38. Yamamoto S, Seto ES. Dopamine dynamics and signaling in Drosophila: an overview of genes, drugs and behavioral paradigms. Experimental animals. 2014;63(2):107–19. pmid:24770636
  39. 39. Massey JH, Akiyama N, Bien T, Dreisewerd K, Wittkopp PJ, Yew JY, et al. Pleiotropic Effects of ebony and tan on Pigmentation and Cuticular Hydrocarbon Composition in Drosophila melanogaster. Frontiers in Physiology. 2019;10:518. pmid:31118901
  40. 40. Dombroski TCD, Simões ZLP, Bitondi MMG. Dietary dopamine causes ovary activation in queenless Apis mellifera workers. Apidologie. 2003;34(3):281–9.
  41. 41. Beggs KT, Glendining KA, Marechal NM, Vergoz V, Nakamura I, Slessor KN, et al. Queen pheromone modulates brain dopamine function in worker honey bees. Proceedings of the National Academy of Sciences. 2007;104(7):2460. pmid:17287354
  42. 42. Dietemann V, Neumann P, HÄRtel S, Pirk CWW, Crewe RM. Pheromonal dominance and the selection of a socially parasitic honeybee worker lineage (Apis mellifera capensis Esch.). Journal of Evolutionary Biology. 2007;20(3):997–1007. pmid:17465910
  43. 43. Linksvayer TA, Rueppell O, Siegel A, Kaftanoglu O, Page RE, Amdam GV. The Genetic Basis of Transgressive Ovary Size in Honeybee Workers. Genetics. 2009;183(2):693. pmid:19620393
  44. 44. Wallberg A, Pirk CW, Allsopp MH, Webster MT. Identification of Multiple Loci Associated with Social Parasitism in Honeybees. PLoS genetics [Internet]. 2016 2016/06//; 12(6):[e1006097 p.]. Available from: Available from: Available from: Available from:
  45. 45. Holman L, Helanterä H, Trontti K, Mikheyev AS. Comparative transcriptomics of social insect queen pheromones. Nature Communications. 2019;10(1):1593. pmid:30962449
  46. 46. Wallberg A, Schöning C, Webster MT, Hasselmann M. Two extended haplotype blocks are associated with adaptation to high altitude habitats in East African honey bees. PLOS Genetics. 2017;13(5):e1006792. pmid:28542163
  47. 47. Takeuchi H, Yasuda A, Yasuda-Kamatani Y, Kubo T, Nakajima T. Identification of a tachykinin-related neuropeptide from the honeybee brain using direct MALDI-TOF MS and its gene expression in worker, queen and drone heads. Insect Mol Biol. 2003;12(3):291–8. Epub 2003/05/20. pmid:12752663.
  48. 48. Kahsai L, Kapan N, Dircksen H, Winther ÅME, Nässel DR. Metabolic Stress Responses in Drosophila Are Modulated by Brain Neurosecretory Cells That Produce Multiple Neuropeptides. PLOS ONE. 2010;5(7):e11480. pmid:20628603
  49. 49. Nässel DR, Wu S-F. Leucokinins: Multifunctional Neuropeptides and Hormones in Insects and Other Invertebrates. International Journal of Molecular Sciences. 2021;22(4). pmid:33546414
  50. 50. Howe J, Schiøtt M, Boomsma JJ. Tachykinin Expression Levels Correlate with Caste-Specific Aggression in Workers of the Leaf-Cutting Ant Acromyrmex echinatior. Frontiers in Ecology and Evolution. 2016;4:55.
  51. 51. Pratavieira M, Menegasso A, Esteves FG, Sato KU, Malaspina O, Palma MS. MALDI Imaging Analysis of Neuropeptides in Africanized Honeybee (Apis mellifera) Brain: Effect of Aggressiveness. J Proteome Res. 2018;17(7):2358–69. Epub 2018/05/19. pmid:29775065.
  52. 52. Meiselman MR, Kingan TG, Adams ME. Stress-induced reproductive arrest in Drosophila occurs through ETH deficiency-mediated suppression of oogenesis and ovulation. BMC Biology. 2018;16(1):18. pmid:29382341
  53. 53. Eimanifar A, Kimball RT, Braun EL, Ellis JD. Mitochondrial genome diversity and population structure of two western honey bee subspecies in the Republic of South Africa. Scientific reports. 2018;8(1):1–11. pmid:29311619
  54. 54. Eimanifar A, Pieplow JT, Asem A, Ellis JD. Genetic diversity and population structure of two subspecies of western honey bees (Apis mellifera L.) in the Republic of South Africa as revealed by microsatellite genotyping. PeerJ. 2020;8:e8280. pmid:31915579
  55. 55. Danecek P, Auton A, Abecasis G, Albers CA, Banks E, DePristo MA, et al. The variant call format and VCFtools. Bioinformatics. 2011;27(15):2156–8. pmid:21653522
  56. 56. Wallberg A, Bunikis I, Pettersson OV, Mosbech M-B, Childers AK, Evans JD, et al. A hybrid de novo genome assembly of the honeybee, Apis mellifera, with chromosome-length scaffolds. BMC Genomics. 2019;20(1):275. pmid:30961563
  57. 57. Browning BL, Browning SR. Genotype imputation with millions of reference samples. The American Journal of Human Genetics. 2016;98(1):116–26. pmid:26748515
  58. 58. Purcell S, Neale B, Todd-Brown K, Thomas L, Ferreira MAR, Bender D, et al. PLINK: a tool set for whole-genome association and population-based linkage analyses. The American Journal of Human Genetics. 2007;81(3):559–75. pmid:17701901
  59. 59. Yang J, Lee SH, Goddard ME, Visscher PM. GCTA: a tool for genome-wide complex trait analysis. The American Journal of Human Genetics. 2011;88(1):76–82. pmid:21167468
  60. 60. Brooks S, Patterson Rosa L, Mallicote M, Long M. Metabogenomics reveals four candidate regions involved in the pathophysiology of Equine Metabolic Syndrome. Molecular and Cellular Probes. 2020. pmid:32659253
  61. 61. Weich K, Affolter V, York D, Rebhun R, Grahn R, Kallenberg A, et al. Pigment Intensity in Dogs is Associated with a Copy Number Variant Upstream of KITLG. Genes. 2020;11(1). pmid:31936656
  62. 62. Kriventseva EV, Kuznetsov D, Tegenfeldt F, Manni M, Dias R, Simão FA, et al. OrthoDB v10: sampling the diversity of animal, plant, fungal, protist, bacterial and viral genomes for evolutionary and functional annotations of orthologs. Nucleic acids research. 2019;47(D1):D807–D11. pmid:30395283
  63. 63. Shultz M. Comparing test searches in PubMed and Google Scholar. Journal of the Medical Library Association: JMLA. 2007;95(4):442–5. pmid:17971893.
  64. 64. Kelley LA, Mezulis S, Yates CM, Wass MN, Sternberg MJE. The Phyre2 web portal for protein modeling, prediction and analysis. Nature Protocols. 2015;10(6):845–58. pmid:25950237