Towards reconstructing the ancestral brain gene-network regulating caste differentiation in ants

Abstract

Specialized queens and life-time unmated workers evolved once in the common ancestor of all ants, but whether caste development across ants continues to be at least partly regulated by a single core set of genes remains obscure. We analysed brain transcriptomes from five ant species (three subfamilies) and reconstructed the origins of genes with caste-biased expression. Ancient genes predating the Neoptera were more likely to regulate gyne (virgin queen) phenotypes, while the caste differentiation roles of younger, ant-lineage-specific genes varied. Transcriptome profiling showed that the ancestral network for caste-specific gene regulation has been maintained, but that signatures of common ancestry are obscured by later modifications. Adjusting for such differences, we identified a core gene-set that: (1) consistently displayed similar directions and degrees of caste-differentiated expression; and (2) have mostly not been reported as being involved in caste differentiation. These core regulatory genes exist in the genomes of ant species that secondarily lost the queen caste, but expression differences for reproductive and sterile workers are minor and similar to social paper wasps that lack differentiated castes. Many caste-biased ant genes have caste-differentiated expression in honeybees, but directions of caste bias were uncorrelated, as expected when permanent castes evolved independently in both lineages.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

Fig. 1: Likelihood ratios of genes with caste-biased expression in the brains of five ant species originating at subsequent phylogenetic nodes.
Fig. 2: Gene expression signatures of species identity and caste type, calculated from 6,672 one-to-one orthologues across 7 ant species.
Fig. 3: PCAs for brain transcriptomes calculated from 6,672 one-to-one orthologues across seven ant species, after adjusting for either species- or colony-level variation in the mean and variance of gene expression.
Fig. 4: Expression levels for conserved caste regulatory genes expressed in the brains of gynes and workers across the five ant species with typical queen–worker differentiation.

Data availability

RNA-Seq data have been deposited under BioProject accession number PRJNA427677 (https://www.ncbi.nlm.nih.gov/sra/SRP127971).

References

  1. 1.

    Wheeler, W. M. The ant‐colony as an organism. J. Morphol. 22, 307–325 (1911).

    Google Scholar 

  2. 2.

    Fisher, R. M., Cornwallis, C. K. & West, S. A. Group formation, relatedness, and the evolution of multicellularity. Curr. Biol. 23, 1120–1125 (2013).

    CAS  PubMed  Google Scholar 

  3. 3.

    Boomsma, J. J. & Gawne, R. Superorganismality and caste differentiation as points of no return: how the major evolutionary transitions were lost in translation. Biol. Rev. 93, 28–54 (2018).

    PubMed  Google Scholar 

  4. 4.

    Ward, P. S. Ants. Curr. Biol. 16, R152–R155 (2006).

    CAS  PubMed  Google Scholar 

  5. 5.

    Gould, S. J. Ontogeny and Phylogeny (Harvard Univ. Press, Cambridge, 1977).

  6. 6.

    Wagner, G. P. Homology, Genes, and Evolutionary Innovation (Princeton Univ. Press, Princeton, 2014).

  7. 7.

    Simola, D. F. et al. Social insect genomes exhibit dramatic evolution in gene composition and regulation while preserving regulatory features linked to sociality. Genome Res. 23, 1235–1247 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  8. 8.

    Morandin, C. et al. Comparative transcriptomics reveals the conserved building blocks involved in parallel evolution of diverse phenotypic traits in ants. Genome Biol. 17, 1 (2016).

    Google Scholar 

  9. 9.

    Toth, A. L. & Robinson, G. E. Evo-devo and the evolution of social behavior. Trends Genet. 23, 334–341 (2007).

    CAS  PubMed  Google Scholar 

  10. 10.

    Carroll, S. B. Evo-devo and an expanding evolutionary synthesis: a genetic theory of morphological evolution. Cell 134, 25–36 (2008).

    CAS  PubMed  Google Scholar 

  11. 11.

    Arendt, D. The evolution of cell types in animals: emerging principles from molecular studies. Nat. Rev. Genet. 9, 868–882 (2008).

    CAS  PubMed  Google Scholar 

  12. 12.

    Barchuk, A. R. et al. Molecular determinants of caste differentiation in the highly eusocial honeybee Apis mellifera. BMC Dev. Biol. 7, 70 (2007).

    PubMed  PubMed Central  Google Scholar 

  13. 13.

    Johnson, B. R. & Tsutsui, N. D. Taxonomically restricted genes are associated with the evolution of sociality in the honey bee. BMC Genomics 12, 164 (2011).

    PubMed  PubMed Central  Google Scholar 

  14. 14.

    Feldmeyer, B., Elsner, D. & Foitzik, S. Gene expression patterns associated with caste and reproductive status in ants: worker‐specific genes are more derived than queen‐specific ones. Mol. Ecol. 23, 151–161 (2014).

    CAS  PubMed  Google Scholar 

  15. 15.

    Sumner, S. The importance of genomic novelty in social evolution. Mol. Ecol. 23, 26–28 (2014).

    PubMed  Google Scholar 

  16. 16.

    Johnson, B. R. & Linksvayer, T. A. Deconstructing the superorganism: social physiology, groundplans, and sociogenomics. Q. Rev. Biol. 85, 57–79 (2010).

    PubMed  Google Scholar 

  17. 17.

    Ding, Y., Zhou, Q. & Wang, W. Origins of new genes and evolution of their novel functions. Annu. Rev. Ecol. Evol. Syst. 43, 345–363 (2012).

    Google Scholar 

  18. 18.

    Chen, S., Krinsky, B. H. & Long, M. New genes as drivers of phenotypic evolution. Nat. Rev. Genet. 14, 645–660 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  19. 19.

    Warner, M. R., Mikheyev, A. S. & Linksvayer, T. A. Genomic signature of kin selection in an ant with obligately sterile workers. Mol. Biol. Evol. 34, 1780–1787 (2016).

    Google Scholar 

  20. 20.

    Ward, P. S. The phylogeny and evolution of ants. Annu. Rev. Ecol. Evol. Syst. 24, 2047–2052 (2014).

    Google Scholar 

  21. 21.

    Mank, J. E. The transcriptional architecture of phenotypic dimorphism. Nat. Ecol. Evol. 1, 0006 (2017).

    Google Scholar 

  22. 22.

    Libbrecht, R., Oxley, P. R. & Keller, D. J. C. Robust DNA methylation in the clonal raider ant brain. Curr. Biol. 26, 391–395 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  23. 23.

    Wagner, G. P. The developmental genetics of homology. Nat. Rev. Genet. 8, 473–479 (2007).

    CAS  PubMed  Google Scholar 

  24. 24.

    Brawand, D. et al. The evolution of gene expression levels in mammalian organs. Nature 478, 343–348 (2011).

    CAS  PubMed  Google Scholar 

  25. 25.

    Roux, J., Rosikiewicz, M. & Robinson-Rechavi, M. What to compare and how: comparative transcriptomics for evo‐devo. J. Exp. Zool. B Mol. Dev. Evol. 324, 372–382 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  26. 26.

    Lucas, E. R., Romiguier, J. & Keller, L. Gene expression is more strongly influenced by age than caste in the ant Lasius niger. Mol. Ecol. 25, 5058–5073 (2017).

    Google Scholar 

  27. 27.

    Patalano, S. et al. Molecular signatures of plastic phenotypes in two eusocial insect species with simple societies. Proc. Natl Acad. Sci. USA 112, 13970–13975 (2015).

    CAS  PubMed  Google Scholar 

  28. 28.

    Monnin, T., Ratnieks, F., Jones, G. R. & Beard, R. Pretender punishment induced by chemical signalling in a queenless ant. Nature 419, 61–65 (2002).

    CAS  PubMed  Google Scholar 

  29. 29.

    Love, M. I., Huber, W. & Anders, S. Moderated estimation of fold change and dispersion for RNA-Seq data with DESeq2. Genome Biol. 15, 550 (2014).

    PubMed  PubMed Central  Google Scholar 

  30. 30.

    Frumhoff, P. C. & Ward, P. S. Individual-level selection, colony-level selection, and the association between polygyny and worker monomorphism in ants. Am. Nat. 139, 559–590 (1992).

    Google Scholar 

  31. 31.

    Schwander, T., Rosset, H. & Chapuisat, M. Division of labour and worker size polymorphism in ant colonies: the impact of social and genetic factors. Behav. Ecol. Sociobiol. 59, 215–221 (2005).

    Google Scholar 

  32. 32.

    Trible, W. & Kronauer, D. J. C. Caste development and evolution in ants: it’s all about size. J. Exp. Biol. 220, 53–62 (2017).

    PubMed  Google Scholar 

  33. 33.

    Nygaard, S. et al. Reciprocal genomic evolution in the ant–fungus agricultural symbiosis. Nat. Commun. 7, 12233 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  34. 34.

    Monnin, T. & Peeters, C. How many gamergates is an ant queen worth? Naturwissenschaften 95, 109–116 (2007).

    PubMed  Google Scholar 

  35. 35.

    Cronin, A. L., Molet, M., Doums, C., Monnin, T. & Peeters, C. Recurrent evolution of dependent colony foundation across eusocial insects. Annu. Rev. Entomol. 58, 37–55 (2013).

    CAS  PubMed  Google Scholar 

  36. 36.

    Heinze, J. The demise of the standard ant (Hymenoptera: Formicidae). Myrmecol. News 11, 9–20 (2008).

    Google Scholar 

  37. 37.

    Rabeling, C. & Kronauer, D. J. C. Thelytokous parthenogenesis in eusocial Hymenoptera. Annu. Rev. Entomol. 58, 273–292 (2013).

    CAS  PubMed  Google Scholar 

  38. 38.

    Luo, W., Friedman, M. S., Shedden, K., Hankenson, K. D. & Woolf, P. J. GAGE: generally applicable gene set enrichment for pathway analysis. BMC Bioinform 10, 161 (2009).

    Google Scholar 

  39. 39.

    Peters, R. S. et al. Evolutionary history of the Hymenoptera. Curr. Biol. 27, 1013–1018 (2017).

    CAS  PubMed  Google Scholar 

  40. 40.

    Corona, M. et al. Vitellogenin, juvenile hormone, insulin signaling, and queen honey bee longevity. Proc. Natl Acad. Sci. 104, 7128–7133 (2007).

    CAS  PubMed  Google Scholar 

  41. 41.

    Vleurinck, C., Raub, S., Sturgill, D., Oliver, B. & Beye, M. Linking genes and brain development of honeybee workers: a whole-transcriptome approach. PLoS ONE 11, e0157980 (2016).

    PubMed  PubMed Central  Google Scholar 

  42. 42.

    LaPolla, J. S., Dlussky, G. M. & Perrichot, V. Ants and the fossil record. Annu. Rev. Entomol. 58, 609–630 (2013).

    CAS  PubMed  Google Scholar 

  43. 43.

    Barden, P. & Grimaldi, D. A. Adaptive radiation in socially advanced stem-group ants from the Cretaceous. Curr. Biol. 26, 515–521 (2016).

    CAS  PubMed  Google Scholar 

  44. 44.

    Peeters, C. in The Evolution of Social Behaviour in Insects and Arachnids (eds Crespi, B. J. & Choe, J. C.) 372–391 (Cambridge Univ. Press, Cambridge, 1997).

  45. 45.

    Girardie, J., Boureme, D., Couillaud, F., Tamarelle, M. & Girardie, A. Anti-juvenile effect of neuroparsin A, a neuroprotein isolated from locust corpora cardiaca. Insect Biochem. 17, 977–983 (1987).

    CAS  Google Scholar 

  46. 46.

    Toth, A. L. et al. Brain transcriptomic analysis in paper wasps identifies genes associated with behaviour across social insect lineages. Proc. R. Soc. B 277, 2139–2148 (2010).

    CAS  PubMed  Google Scholar 

  47. 47.

    Mikheyev, A. S., Linksvayer, T. A. & Khaitovich, P. Genes associated with ant social behavior show distinct transcriptional and evolutionary patterns. eLife 4, e04775 (2015).

    PubMed  PubMed Central  Google Scholar 

  48. 48.

    Pantalacci, S. et al. Transcriptomic signatures shaped by cell proportions shed light on comparative developmental biology. Genome Biol. 18, 29 (2017).

    PubMed  PubMed Central  Google Scholar 

  49. 49.

    Romiguier, J. et al. Phylogenomics controlling for base compositional bias reveals a single origin of eusociality in corbiculate bees. Mol. Biol. Evol. 33, 670–678 (2016).

    CAS  PubMed  Google Scholar 

  50. 50.

    Pontieri, L., Schmidt, A. M., Singh, R., Pedersen, J. S. & Linksvayer, T. A. Artificial selection on ant female caste ratio uncovers a link between female‐biased sex ratios and infection by Wolbachia endosymbionts. J. Evol. Biol. 30, 225–234 (2017).

    CAS  PubMed  Google Scholar 

  51. 51.

    Conesa, A. et al. A survey of best practices for RNA-Seq data analysis. Genome Biol. 17, 13 (2016).

    PubMed  PubMed Central  Google Scholar 

  52. 52.

    Keilwagen, J. et al. Using intron position conservation for homology-based gene prediction. Nucleic Acids Res. 44, e89 (2016).

    PubMed  PubMed Central  Google Scholar 

  53. 53.

    Lechner, M. et al. Proteinortho: detection of (co-)orthologs in large-scale analysis. BMC Bioinform. 12, 124 (2011).

    Google Scholar 

  54. 54.

    Patro, R., Duggal, G., Love, M. I., Irizarry, R. A. & Kingsford, C. Salmon provides fast and bias-aware quantification of transcript expression. Nat. Methods 14, 417–419 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  55. 55.

    Bourgon, R., Gentleman, R. & Huber, W. Independent filtering increases detection power for high-throughput experiments. Proc. Natl Acad. Sci. USA 107, 9546–9551 (2010).

    CAS  PubMed  Google Scholar 

  56. 56.

    Bolstad, B. M., Irizarry, R. A., Åstrand, M. & Speed, T. P. A comparison of normalization methods for high density oligonucleotide array data based on variance and bias. Bioinformatics 107, 9546–9551 (2003).

    Google Scholar 

  57. 57.

    Leek, J. T. svaseq: removing batch effects and other unwanted noise from sequencing data. Nucleic Acids Res. 42, e161 (2014).

    PubMed Central  Google Scholar 

  58. 58.

    Efron, B. in Breakthroughs in Statistics (eds Kotz, S. & Johnson, N. L.) 569–593 (Springer, New York, 1992).

  59. 59.

    Moreau, C. S., Bell, C. D., Vila, R., Archibald, S. B. & Pierce, N. E. Phylogeny of the ants: diversification in the age of angiosperms. Science 312, 101–104 (2006).

    CAS  PubMed  Google Scholar 

  60. 60.

    Ward, P. S., Brady, S. G., Fisher, B. L. & Schultz, T. R. The evolution of myrmicine ants: phylogeny and biogeography of a hyperdiverse ant clade (Hymenoptera: Formicidae). Syst. Entomol. 40, 61–81 (2015).

    Google Scholar 

Download references

Acknowledgements

This work was supported by grants from the Lundbeck Foundation (R190-2014-2827 to G.Z.), Carlsberg Foundation (CF16-0663 to G.Z.), Strategic Priority Research Program of the Chinese Academy of Sciences (XDB13000000 to G.Z.) and Biodiversity Research Center, Academia Sinica (100-2311-B-001-015-MY3, 103-2311-B-001-018-MY3 and 104-2314-B-001-009-MY5 to J.W.), as well as an Academia Sinica Career Development Grant (to J.W.) and an ERC Advanced Grant (323085 to J.J.B.). We thank C. Guo, H. Yu and Q. Li for coordination of the sequencing at BGI.

Author information

Affiliations

Authors

Contributions

G.Z., J.J.B., J.W. and B.Q. designed the experiments. R.S.L., N.-C.C. and B.Q. reared and isolated the ant colonies in the laboratory. B.Q. and N.-C.C. collected the ants, dissected the ant brains and extracted RNA. B.Q. constructed the cDNA libraries. N.-C.C. and J.W. generated the transcriptome data for S. invicta. B.Q. analysed the data. B.Q., G.Z. and J.J.B. interpreted the data and wrote and revised the manuscript.

Corresponding authors

Correspondence to Jacobus J. Boomsma or Guojie Zhang.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Supplementary Information

Supplementary Notes and Supplementary Figures

Reporting Summary

Supplementary Table 1

Study design and sampling information

Supplementary Tables 2-7

Supplementary Table 2: Number and percentage of genes originated (earliest detected) in each phylogenetic lineage

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Qiu, B., Larsen, R.S., Chang, N. et al. Towards reconstructing the ancestral brain gene-network regulating caste differentiation in ants. Nat Ecol Evol 2, 1782–1791 (2018). https://doi.org/10.1038/s41559-018-0689-x

Download citation

Further reading