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Selection and gene flow shape niche-associated variation in pheromone response

Nature Ecology & Evolution volume 3, pages 1455–1463 (2019)Cite this article

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Abstract

From quorum sensing in bacteria to pheromone signalling in social insects, chemical communication mediates interactions among individuals in local populations. In Caenorhabditis elegans, ascaroside pheromones can dictate local population density; high levels of pheromones inhibit the reproductive maturation of individuals. Little is known about how natural genetic diversity affects the pheromone responses of individuals from diverse habitats. Here, we show that a niche-associated variation in pheromone receptor genes contributes to natural differences in pheromone responses. We identified putative loss-of-function deletions that impair duplicated pheromone receptor genes (srg-36 and srg-37), which were previously shown to be lost in population-dense laboratory cultures. A common natural deletion in srg-37 arose recently from a single ancestral population that spread throughout the world; this deletion underlies reduced pheromone sensitivity across the global C. elegans population. We found that many local populations harbour individuals with a wild-type or a deletion allele of srg-37, suggesting that balancing selection has maintained the recent variation in this pheromone receptor gene. The two srg-37 genotypes are associated with niche diversity underlying boom-and-bust population dynamics. We hypothesize that human activities likely contributed to the gene flow and balancing selection of srg-37 variation through facilitating the migration of species and providing a favourable niche for the recently arisen srg-37 deletion.

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Fig. 1: An HTDA measures the natural variation of the dauer-pheromone response.
Fig. 2: GWA mapping reveals four major loci underlying natural variation in the dauer-pheromone response.
Fig. 3: A natural variant in the ascr#5 receptor gene, srg-37, underlies natural differences in dauer formation.
Fig. 4: Worldwide and niche-associated gene flow shapes the ascr#5 pheromone receptor locus.

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Data availability

All datasets, including HTDA raw data, for generating figures are available on GitHub (https://github.com/AndersenLab/DauerSRG3637).

Code availability

All code for generating figures is available on GitHub (https://github.com/AndersenLab/DauerSRG3637).

References

  1. Cassada, R. C. & Russell, R. L. The dauerlarva, a post-embryonic developmental variant of the nematode Caenorhabditis elegans. Dev. Biol. 46, 326–342 (1975).

    Article  CAS  PubMed  Google Scholar 

  2. Golden, J. W. & Riddle, D. L. The Caenorhabditis elegans dauer larva: developmental effects of pheromone, food, and temperature. Dev. Biol. 102, 368–378 (1984).

    Article  CAS  PubMed  Google Scholar 

  3. Schaedel, O. N., Gerisch, B., Antebi, A. & Sternberg, P. W. Hormonal signal amplification mediates environmental conditions during development and controls an irreversible commitment to adulthood. PLoS Biol. 10, e1001306 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Schroeder, F. C. Modular assembly of primary metabolic building blocks: a chemical language in C. elegans. Chem. Biol. 22, 7–16 (2015).

    Article  CAS  PubMed  Google Scholar 

  5. Ludewig, A. H. & Schroeder, F. C. in WormBook (ed. The C. elegans Research Community) https://doi.org/10.1895/wormbook.1.155.1 (2013).

  6. Félix, M.-A. & Braendle, C. The natural history of Caenorhabditis elegans. Curr. Biol. 20, R965–R969 (2010).

    Article  PubMed  Google Scholar 

  7. Frézal, L. & Félix, M.-A. C. elegans outside the Petri dish. Elife 4, e05849 (2015).

    Article  PubMed Central  Google Scholar 

  8. Lee, H. et al. Nictation, a dispersal behavior of the nematode Caenorhabditis elegans, is regulated by IL2 neurons. Nat. Neurosci. 15, 107–112 (2011).

    Article  CAS  PubMed  Google Scholar 

  9. Lee, D. et al. The genetic basis of natural variation in a phoretic behavior. Nat. Commun. 8, 273 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  10. Viney, M. E., Gardner, M. P. & Jackson, J. A. Variation in Caenorhabditis elegans dauer larva formation. Dev. Growth Differ. 45, 389–396 (2003).

    Article  PubMed  Google Scholar 

  11. Harvey, S. C., Shorto, A. & Viney, M. E. Quantitative genetic analysis of life-history traits of Caenorhabditis elegans in stressful environments. BMC Evol. Biol. 8, 15 (2008).

    Article  PubMed  PubMed Central  Google Scholar 

  12. Green, J. W. M., Snoek, L. B., Kammenga, J. E. & Harvey, S. C. Genetic mapping of variation in dauer larvae development in growing populations of Caenorhabditis elegans. Heredity 111, 306–313 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Green, J. W. M., Stastna, J. J., Orbidans, H. E. & Harvey, S. C. Highly polygenic variation in environmental perception determines dauer larvae formation in growing populations of Caenorhabditis elegans. PLoS ONE 9, e112830 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  14. Diaz, S. A. et al. Diverse and potentially manipulative signalling with ascarosides in the model nematode C. elegans. BMC Evol. Biol. 14, 46 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  15. O’Donnell, M. P., Chao, P.-H., Kammenga, J. E. & Sengupta, P. Rictor/TORC2 mediates gut-to-brain signaling in the regulation of phenotypic plasticity in C. elegans. PLoS Genet. 14, e1007213 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  16. Nika, L., Gibson, T., Konkus, R. & Karp, X. Fluorescent beads are a versatile tool for staging Caenorhabditis elegans in different life histories. G3 (Bethesda) 6, 1923–1933 (2016).

    Article  Google Scholar 

  17. Evans, K. S. et al. Correlations of genotype with climate parameters suggest Caenorhabditis elegans niche adaptations. G3 (Bethesda) 7, 289–298 (2017).

    Article  CAS  Google Scholar 

  18. Schulenburg, H. & Félix, M.-A. The natural biotic environment of Caenorhabditis elegans. Genetics 206, 55–86 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. McGrath, P. T. et al. Parallel evolution of domesticated Caenorhabditis species targets pheromone receptor genes. Nature 477, 321–325 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Bargmann, C. I. & Horvitz, H. R. Control of larval development by chemosensory neurons in Caenorhabditis elegans. Science 251, 1243–1246 (1991).

    Article  CAS  PubMed  Google Scholar 

  21. Schackwitz, W. S., Inoue, T. & Thomas, J. H. Chemosensory neurons function in parallel to mediate a pheromone response in C. elegans. Neuron 17, 719–728 (1996).

    Article  CAS  PubMed  Google Scholar 

  22. Cook, D. E., Zdraljevic, S., Roberts, J. P. & Andersen, E. C. CeNDR, the Caenorhabditis elegans Natural Diversity Resource. Nucleic Acids Res. 45, D650–D657 (2017).

    Article  CAS  PubMed  Google Scholar 

  23. Hahnel, S. R. et al. Extreme allelic heterogeneity at a Caenorhabditis elegans beta-tubulin locus explains natural resistance to benzimidazoles. PLoS Pathog. 14, e1007226 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  24. Kim, H. et al. A co-CRISPR strategy for efficient genome editing in Caenorhabditis elegans. Genetics 197, 1069–1080 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  25. Paix, A., Folkmann, A., Rasoloson, D. & Seydoux, G. High efficiency, homology-directed genome editing in Caenorhabditis elegans using CRISPR–Cas9 ribonucleoprotein complexes. Genetics 201, 47–54 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Biswas, S. & Akey, J. M. Genomic insights into positive selection. Trends Genet. 22, 437–446 (2006).

    Article  CAS  PubMed  Google Scholar 

  27. Chang, J.-M., Di Tommaso, P., Taly, J.-F. & Notredame, C. Accurate multiple sequence alignment of transmembrane proteins with PSI-Coffee. BMC Bioinformatics 13, S1 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Andersen, E. C. et al. Chromosome-scale selective sweeps shape Caenorhabditis elegans genomic diversity. Nat. Genet. 44, 285–290 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Félix, M.-A. & Duveau, F. Population dynamics and habitat sharing of natural populations of Caenorhabditis elegans and C. briggsae. BMC Biol. 10, 59 (2012).

    Article  PubMed  PubMed Central  Google Scholar 

  30. Barrière, A. & Félix, M.-A. High local genetic diversity and low outcrossing rate in Caenorhabditis elegans natural populations. Curr. Biol. 15, 1176–1184 (2005).

    Article  PubMed  Google Scholar 

  31. Hu, P. J. in WormBook (ed. The C. elegans Research Community) https://doi.org/10.1895/wormbook.1.144.1 (2007).

  32. Lee, S. S. & Schroeder, F. C. Steroids as central regulators of organismal development and lifespan. PLoS Biol. 10, e1001307 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Gumienny, T. L. & Savage-Dunn, C. in WormBook (ed. The C. elegans Research Community) https://doi.org/10.1895/wormbook.1.22.2 (2013).

  34. Murphy, C. T. & Hu, P. J. in WormBook (ed. The C. elegans Research Community) https://doi.org/10.1895/wormbook.1.164.1 (2013).

  35. Gompel, N. & Prud’homme, B. The causes of repeated genetic evolution. Dev. Biol. 332, 36–47 (2009).

    Article  CAS  PubMed  Google Scholar 

  36. Greene, J. S. et al. Balancing selection shapes density-dependent foraging behaviour. Nature 539, 254–258 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  37. Greene, J. S., Dobosiewicz, M., Butcher, R. A., McGrath, P. T. & Bargmann, C. I. Regulatory changes in two chemoreceptor genes contribute to a Caenorhabditis elegans QTL for foraging behavior. Elife 5, e21454 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  38. Charlesworth, D. Balancing selection and its effects on sequences in nearby genome regions. PLoS Genet. 2, e64 (2006).

    Article  PubMed  PubMed Central  Google Scholar 

  39. Andersen, E. C., Bloom, J. S., Gerke, J. P. & Kruglyak, L. A variant in the neuropeptide receptor NPR-1 is a major determinant of Caenorhabditis elegans growth and physiology. PLoS Genet. 10, e1004156 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  40. Boyd, W. A., Smith, M. V. & Freedman, J. H. Caenorhabditis elegans as a model in developmental toxicology. Methods Mol. Biol. 889, 15–24 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Zhang, Y. K., Sanchez-Ayala, M. A., Sternberg, P. W., Srinivasan, J. & Schroeder, F. C. Improved synthesis for modular ascarosides uncovers biological activity. Org. Lett. 19, 2837–2840 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Chen, W.-C., Maitra, R. & Melnykov, V. A quick guide for the EMCluster package. R Vignette package version 0.2-12 http://cran.r-project.org/package=EMCluster (2012).

  43. Li, H. A statistical framework for SNP calling, mutation discovery, association mapping and population genetical parameter estimation from sequencing data. Bioinformatics 27, 2987–2993 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Purcell, S. et al. PLINK: a tool set for whole-genome association and population-based linkage analyses. Am. J. Hum. Genet. 81, 559–575 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Chang, C. C. et al. Second-generation PLINK: rising to the challenge of larger and richer datasets. Gigascience 4, 7 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  46. Endelman, J. B. Ridge regression and other kernels for genomic selection with R package rrBLUP. Plant Genome 4, 250–255 (2011).

    Article  Google Scholar 

  47. Qiu, Y. RSpectra Version 0.15-0 (Github, 2019).

  48. Bilgrau, A. E. correlateR Version 0.1 (Github, 2018).

  49. Li, J. & Ji, L. Adjusting multiple testing in multilocus analyses using the eigenvalues of a correlation matrix. Heredity 95, 221–227 (2005).

    Article  CAS  PubMed  Google Scholar 

  50. Covarrubias-Pazaran, G. Quantitative genetics using the Sommer package. R package version 4.0.4 https://cran.r-project.org/web/packages/sommer/vignettes/sommer.pdf (2018).

  51. Li, H. & Durbin, R. Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics 25, 1754–1760 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Picard Tools (Broad Institute, 2019); http://broadinstitute.github.io/picard/

  53. Cook, D. E. et al. The genetic basis of natural variation in Caenorhabditis elegans telomere length. Genetics 204, 371–383 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Tarasov, A., Vilella, A. J., Cuppen, E., Nijman, I. J. & Prins, P. Sambamba: fast processing of NGS alignment formats. Bioinformatics 31, 2032–2034 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Chen, X. et al. Manta: rapid detection of structural variants and indels for germline and cancer sequencing applications. Bioinformatics 32, 1220–1222 (2016).

    Article  CAS  PubMed  Google Scholar 

  56. Shin, H. et al. Transcriptome analysis for Caenorhabditis elegans based on novel expressed sequence tags. BMC Biol. 6, 30 (2008).

    Article  PubMed  PubMed Central  Google Scholar 

  57. Gerstein, M. B. et al. Integrative analysis of the Caenorhabditis elegans genome by the modENCODE project. Science 330, 1775–1787 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  58. Mortazavi, A. et al. Scaffolding a Caenorhabditis nematode genome with RNA-seq. Genome Res. 20, 1740–1747 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. Stadler, M. & Fire, A. Wobble base-pairing slows in vivo translation elongation in metazoans. RNA 17, 2063–2073 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  60. Lamm, A. T., Stadler, M. R., Zhang, H., Gent, J. I. & Fire, A. Z. Multimodal RNA-seq using single-strand, double-strand, and CircLigase-based capture yields a refined and extended description of the C. elegans transcriptome. Genome Res. 21, 265–275 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  61. Maxwell, C. S., Antoshechkin, I., Kurhanewicz, N., Belsky, J. A. & Baugh, L. R. Nutritional control of mRNA isoform expression during developmental arrest and recovery in C. elegans. Genome Res. 22, 1920–1929 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  62. Steijger, T. et al. Assessment of transcript reconstruction methods for RNA-seq. Nat. Methods 10, 1177–1184 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  63. Grün, D. et al. Conservation of mRNA and protein expression during development of C. elegans. Cell Rep. 6, 565–577 (2014).

    Article  PubMed  Google Scholar 

  64. Wang, J.-J. et al. The influences of PRG-1 on the expression of small RNAs and mRNAs. BMC Genom. 15, 321 (2014).

    Article  Google Scholar 

  65. Dillman, A. R. et al. Comparative genomics of Steinernema reveals deeply conserved gene regulatory networks. Genome Biol. 16, 200 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  66. Pfeifer, B., Wittelsbürger, U., Ramos-Onsins, S. E. & Lercher, M. J. PopGenome: an efficient Swiss army knife for population genomic analyses in R. Mol. Biol. Evol. 31, 1929–1936 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  67. Browning, B. L. & Browning, S. R. Genotype imputation with millions of reference samples. Am. J. Hum. Genet. 98, 116–126 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  68. Danecek, P. et al. The variant call format and VCFtools. Bioinformatics 27, 2156–2158 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  69. Warnes, G., Gorjanc, G., Leisch, F. & Man, M. Genetics: population genetics. R package version 1.3.6 (2012).

  70. Browning, B. L. & Browning, S. R. Detecting identity by descent and estimating genotype error rates in sequence data. Am. J. Hum. Genet. 93, 840–851 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  71. Li, H. A statistical framework for SNP calling, mutation discovery, association mapping and population genetical parameter estimation from sequencing data. Bioinformatics 27, 2987–2993 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  72. Felsenstein, J. PHYLIP—Phylogeny Inference Package (version 3.2). Cladistics 5, 164–166 (1989).

    Google Scholar 

  73. Tavaré, S. Some probabilistic and statistical problems on the analysis of DNA sequences. Lect. Math. Life Sci. 17, 57–86 (1986).

    Google Scholar 

  74. Lanave, C., Preparata, G., Saccone, C. & Serio, G. A new method for calculating evolutionary substitution rates. J. Mol. Evol. 20, 86–93 (1984).

    Article  CAS  PubMed  Google Scholar 

  75. Yu, G., Smith, D. K., Zhu, H., Guan, Y. & Lam, T. T.-Y. ggtree: an r package for visualization and annotation of phylogenetic trees with their covariates and other associated data. Methods Ecol. Evol. 8, 28–36 (2017).

    Article  Google Scholar 

  76. R Core Team R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2013).

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Acknowledgements

This work was supported by an NSF CAREER Award to E.C.A. S.Z was supported by the Cell and Molecular Basis of Disease training grant (no. T32GM008061) and the Bernard and Martha Rappaport Fellowship. D.E.C. received the National Science Foundation Graduate Research Fellowship (no. DGE-1324585). Members of the Andersen Lab helped with manuscript editing, and Y. K. Zhang assisted with the synthesis of ascarosides. Some strains were provided by the CGC, which is funded by the NIH Office of Research Infrastructure Programs (grant no. P40 OD010440). We thank WormBase for providing genomic data on Caenorhabditis species.

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  1. Daniel E. Cook

    Present address: The Francis Crick Institute, London, UK

Authors and Affiliations

  1. Department of Molecular Biosciences, Northwestern University, Evanston, IL, USA

    Daehan Lee, Stefan Zdraljevic, Daniel E. Cook & Erik C. Andersen

  2. Interdisciplinary Biological Sciences Program, Northwestern University, Evanston, IL, USA

    Stefan Zdraljevic & Daniel E. Cook

  3. Institut de Biologie de l’Ecole Normale Supérieure, CNRS, Inserm, École Normale Supérieure, Paris Sciences et Lettres, Paris, France

    Lise Frézal & Marie-Anne Félix

  4. Biodiversity Research Center, Academia Sinica, Taipei, Taiwan

    Jung-Chen Hsu & John Wang

  5. Laboratory of Nematology, Wageningen University and Research, Wageningen, The Netherlands

    Mark G. Sterken, Joost A. G. Riksen & Jan E. Kammenga

  6. Université Côte d’Azur, CNRS, Inserm, IBV, Nice, France

    Christian Braendle

  7. Boyce Thompson Institute and Department of Chemistry and Chemical Biology, Cornell University, Ithaca, NY, USA

    Frank C. Schroeder

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Contributions

D.L. and E.C.A. conceived and designed the study. D.L. performed the high-throughput assay, CRISPR–Cas9 genome editing, population genomic analyses and niche enrichment tests. S.Z. performed the GWA mapping, identified genetic variants in the dauf-1 locus, generated the genome-wide tree of 249 wild C. elegans strains and edited the manuscript. D.E.C. analysed the haplotype composition of 249 wild strains. L.F., J-C.H., M.G.S., J.A.G.R., J.W., J.E.K., C.B. and M.-A.F. contributed wild isolates to the C. elegans strain collection. F.C.S. provided the dauer pheromone. D.L. and E.C.A. analysed the data and wrote the manuscript.

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Correspondence to Erik C. Andersen.

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Supplementary Information

Supplementary Figs. 1–16 and Table 1.

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Supplementary Data 1

Information for wild C. elegans strains isolated in the cosampling zone.

Supplementary Data 2

Sampling information for wild C. elegans strains.

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Lee, D., Zdraljevic, S., Cook, D.E. et al. Selection and gene flow shape niche-associated variation in pheromone response. Nat Ecol Evol 3, 1455–1463 (2019). https://doi.org/10.1038/s41559-019-0982-3

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