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Divergence and plasticity shape adaptive potential of the Pacific oyster


The interplay between divergence and phenotypic plasticity is critical to our understanding of a species’ adaptive potential under rapid climate changes. We investigated divergence and plasticity in natural populations of the Pacific oyster Crassostrea gigas with a congeneric oyster Crassostrea angulata from southern China used as an outgroup. Genome re-sequencing of 371 oysters revealed unexpected genetic divergence in a small area that coincided with phenotypic divergence in growth, physiology, heat tolerance and gene expression across environmental gradients. These findings suggest that selection and local adaptation are pervasive and, together with limited gene flow, influence population structure. Genes showing sequence differentiation between populations also diverged in transcriptional response to heat stress. Plasticity in gene expression is positively correlated with evolved divergence, indicating that plasticity is adaptive and favoured by organisms under dynamic environments. Divergence in heat tolerance—partly through acetylation-mediated energy depression—implies differentiation in adaptive potential. Trade-offs between growth and survival may play an important role in local adaptation of oysters and other marine invertebrates.

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Fig. 1: Geographic distribution and population divergence of Pacific oysters in northern China.
Fig. 2: Adaptive divergence in phenotypic traits at morphological, physiological and cellular levels among 11 oyster populations measured in F1 progeny in a common-garden environment.
Fig. 3: Multi-omic analyses of two representative northern (JZ) and southern (QD) oyster populations in response to acute heat stress.
Fig. 4: Relationship between evolved divergence and plasticity.
Fig. 5: Energy repression by acetylation in Pacific oysters.

Data availability

The whole-genome re-sequencing and transcriptome datasets were deposited in the Sequence Read Archive (SRA) database under the accession number PRJNA394055. The proteome and acetylome data are available via the ProteomeXchange Consortium with the identifier PXD008057.


  1. 1.

    Sanford, E. & Kelly, M. W. Local adaptation in marine invertebrates. Annu. Rev. Mar. Sci. 3, 509–535 (2011).

    Article  Google Scholar 

  2. 2.

    Somero, G. N. The physiology of global change: linking patterns to mechanisms. Annu. Rev. Mar. Sci. 4, 39–61 (2012).

    Article  Google Scholar 

  3. 3.

    Bozinovic, F., Calosi, P. & Spicer, J. I. Physiological correlates of geographic range in animals. Annu. Rev. Ecol. Evol. Syst. 42, 155–179 (2011).

    Article  Google Scholar 

  4. 4.

    Nadeau, C. P., Urban, M. C. & Bridle, J. R. Climates past, present, and yet-to-come shape climate change vulnerabilities. Trends Ecol. Evol. 32, 786–800 (2017).

    Article  Google Scholar 

  5. 5.

    Conover, D. O., Clarke, L. M., Munch, S. B. & Wagner, G. N. Spatial and temporal scales of adaptive divergence in marine fishes and the implications for conservation. J. Fish Biol. 69, 21–47 (2006).

    Article  Google Scholar 

  6. 6.

    Zhang, G. et al. Molecular basis for adaptation of oysters to stressful marine intertidal environments. Annu. Rev. Anim. Biosci. 4, 357–381 (2016).

    Article  Google Scholar 

  7. 7.

    Hice, L. A., Duffy, T. A., Munch, S. B. & Conover, D. O. Spatial scale and divergent patterns of variation in adapted traits in the ocean. Ecol. Lett. 15, 568–575 (2012).

    Article  Google Scholar 

  8. 8.

    Burford, M. O., Scarpa, J., Cook, B. J. & Hare, M. P. Local adaptation of a marine invertebrate with a high dispersal potential: evidence from a reciprocal transplant experiment of the eastern oyster Crassostrea virginica. Mar. Ecol. Prog. Ser. 505, 161–175 (2014).

    Article  Google Scholar 

  9. 9.

    Hebert, A. S. et al. Calorie restriction and SIRT3 trigger global reprogramming of the mitochondrial protein acetylome. Mol. Cell 49, 186–199 (2013).

    CAS  Article  Google Scholar 

  10. 10.

    Pfennig, D. W. et al. Phenotypic plasticity’s impacts on diversification and speciation. Trends Ecol. Evol. 25, 459–467 (2010).

    Article  Google Scholar 

  11. 11.

    Agrawal, A. A. Phenotypic plasticity in the interactions and evolution of species. Science 294, 321–326 (2001).

    CAS  Article  Google Scholar 

  12. 12.

    Fischer, E. K., Ghalambor, C. K. & Hoke, K. L. Can a network approach resolve how adaptive vs nonadaptive plasticity impacts evolutionary trajectories? Integr. Comp. Biol. 56, 877–888 (2016).

    Article  Google Scholar 

  13. 13.

    Ghalambor, C. K. et al. Non-adaptive plasticity potentiates rapid adaptive evolution of gene expression in nature. Nature 525, 372–375 (2015).

    CAS  Article  Google Scholar 

  14. 14.

    Schneider, R. F. & Meyer, A. How plasticity, genetic assimilation and cryptic genetic variation may contribute to adaptive radiations. Mol. Ecol. 26, 330–350 (2017).

    Article  Google Scholar 

  15. 15.

    Schaum, C. E. & Collins, S.Plasticity predicts evolution in a marine alga. Proc. R. Soc. B 281, 20141486 (2014).

    Article  Google Scholar 

  16. 16.

    Calosi, P., De Wit, P., Thor, P. & Dupont, S. Will life find a way? Evolution of marine species under global change. Evol. Appl. 9, 1035–1042 (2016).

    Article  Google Scholar 

  17. 17.

    Bay, R. A. et al. Predicting responses to contemporary environmental change using evolutionary response architectures. Am. Nat. 189, 463–473 (2017).

    Article  Google Scholar 

  18. 18.

    Chevin, L. M., Lande, R. & Mace, G. M. Adaptation, plasticity, and extinction in a changing environment: towards a predictive theory. PLoS Biol. 8, e1000357 (2010).

    Article  Google Scholar 

  19. 19.

    Price, T. D., Qvarnstrom, A. & Irwin, D. E. The role of phenotypic plasticity in driving genetic evolution. Proc. R. Soc. Lond. B 270, 1433–1440 (2003).

    Article  Google Scholar 

  20. 20.

    Markov, A. V. & Ivnitsky, S. B. Evolutionary role of phenotypic plasticity. Moscow Univ. Biol. Sci. Bull. 71, 185–192 (2016).

    Article  Google Scholar 

  21. 21.

    Boyd, P. W. et al. Biological responses to environmental heterogeneity under future ocean conditions. Glob. Change Biol. 22, 2633–2650 (2016).

    Article  Google Scholar 

  22. 22.

    Dineshram, R. et al. Quantitative analysis of oyster larval proteome provides new insights into the effects of multiple climate change stressors. Glob. Change Biol. 22, 2054–2068 (2016).

    Article  Google Scholar 

  23. 23.

    Zhang, G. et al. The oyster genome reveals stress adaptation and complexity of shell formation. Nature 490, 49–54 (2012).

    CAS  Article  Google Scholar 

  24. 24.

    Wang, H., Zhang, G., Liu, X. & Guo, X. Classification of common oysters from north China. J. Shellfish Res. 27, 495–503 (2008).

    CAS  Article  Google Scholar 

  25. 25.

    Ju, X. & Xiong, X. Distributions and seasonal changes of water temperature in the Bohai Sea, Yellow Sea and East China Sea.Adv. Mar. Sci. 31, 55–68 (2013).

    Google Scholar 

  26. 26.

    Weng, X., Zhang, Q., Zhang, Y. & Yang, Y. Characteristics of the daily variations of the temperature in the Bohai Sea, Yellow Sea and East China Sea. Mar. Sci. 6, 49–54 (1993).

    Google Scholar 

  27. 27.

    Guo, X., He, Y., Zhang, L., Lelong, C. & Jouaux, A. Immune and stress responses in oysters with insights on adaptation. Fish Shellfish Immunol. 46, 107–119 (2015).

    CAS  Article  Google Scholar 

  28. 28.

    Zhang, L. & Guo, X. Development and validation of single nucleotide polymorphism markers in the eastern oyster Crassostrea virginica Gmelin by mining ESTs and resequencing. Aquaculture 302, 124–129 (2010).

    CAS  Article  Google Scholar 

  29. 29.

    Qi, H. et al. Construction and evaluation of a high-density SNP array for the Pacific oyster (Crassostrea gigas). PLoS ONE 12, e0174007 (2017).

    Article  Google Scholar 

  30. 30.

    Guan, B. & Mao, H. A note on circulation of the East China Sea. Chin. J. Oceanol. Limnol. 1, 5–16 (1982).

    Article  Google Scholar 

  31. 31.

    Zhan, A. et al. Fine-scale population genetic structure of Zhikong scallop (Chlamys farreri): do local marine currents drive geographical differentiation? Mar. Biotechnol. 11, 223–235 (2009).

    CAS  Article  Google Scholar 

  32. 32.

    Kong, L., Bai, J. & Li, Q. Comparative assessment of genomic SSR, EST–SSR and EST–SNP markers for evaluation of the genetic diversity of wild and cultured Pacific oyster, Crassostrea gigas Thunberg. Aquaculture 420–421, S85–S91 (2014).

    Article  Google Scholar 

  33. 33.

    Li, Q., Yu, H. & Yu, R. Genetic variability assessed by microsatellites in cultured populations of the Pacific oyster (Crassostrea gigas) in China. Aquaculture 259, 95–102 (2006).

    CAS  Article  Google Scholar 

  34. 34.

    Qin, Y., Zhao, Y. & Zhao, S. Geology of the Bohai Sea (Science Press, Beijing, 1985).

  35. 35.

    Moreau, P. et al. Autophagy plays an important role in protecting Pacific oysters from OsHV-1 and Vibrio aestuarianus infections. Autophagy 11, 516–526 (2015).

    Article  Google Scholar 

  36. 36.

    Duncan, R. E. & Hershey, J. W. B. Protein-synthesis and protein-phosphorylation during heat-stress, recovery, and adaptation. J. Cell Biol. 109, 1467–1481 (1989).

    CAS  Article  Google Scholar 

  37. 37.

    Helmuth, B. et al. Climate change and latitudinal patterns of intertidal thermal stress. Science 298, 1015–1017 (2002).

    CAS  Article  Google Scholar 

  38. 38.

    Sussarellu, R. et al. Molecular and cellular response to short-term oxygen variations in the Pacific oyster Crassostrea gigas. J. Exp. Mar. Biol. Ecol. 412, 87–95 (2012).

    CAS  Article  Google Scholar 

  39. 39.

    Guévélou, E. et al. Regulation of a truncated isoform of AMP-activated protein kinase α (AMPKα) in response to hypoxia in the muscle of Pacific oyster Crassostrea gigas. J. Comp. Physiol. B 183, 597–611 (2013).

    Article  Google Scholar 

  40. 40.

    Pan, T.-C. F., Applebaum, S. L. & Manahan, D. T. Experimental ocean acidification alters the allocation of metabolic energy. Proc. Natl Acad. Sci. USA 112, 4696–4701 (2015).

    CAS  Article  Google Scholar 

  41. 41.

    Falfushynska, H. I., Phan, T. & Sokolova, I. M. Long-term acclimation to different thermal regimes affects molecular responses to heat stress in a freshwater clam Corbicula fluminea. Sci. Rep. 6, 39476 (2016).

    CAS  Article  Google Scholar 

  42. 42.

    Roy, K., Jablonski, D. & Martien, K. K. Invariant size–frequency distributions along a latitudinal gradient in marine bivalves. Proc. Natl Acad. Sci. USA 97, 13150–13155 (2000).

    CAS  Article  Google Scholar 

  43. 43.

    Sussarellu, R. et al. Oyster reproduction is affected by exposure to polystyrene microplastics. Proc. Natl Acad. Sci. USA 113, 2430–2435 (2016).

    CAS  Article  Google Scholar 

  44. 44.

    Tomanek, L. Proteomics to study adaptations in marine organisms to environmental stress. J. Proteomics 105, 92–106 (2014).

    CAS  Article  Google Scholar 

  45. 45.

    De Wit, P., Dupont, S. & Thor, P. Selection on oxidative phosphorylation and ribosomal structure as a multigenerational response to ocean acidification in the common copepod Pseudocalanus acuspes. Evol. Appl. 9, 1112–1123 (2016).

    CAS  Article  Google Scholar 

  46. 46.

    Pörtner, H. O. Oxygen- and capacity-limitation of thermal tolerance: a matrix for integrating climate-related stressor effects in marine ecosystems. J. Exp. Biol. 213, 881–893 (2010).

    Article  Google Scholar 

  47. 47.

    Schulte, P. M. The effects of temperature on aerobic metabolism: towards a mechanistic understanding of the responses of ectotherms to a changing environment. J. Exp. Biol. 218, 1856–1866 (2015).

    Article  Google Scholar 

  48. 48.

    Sokolova, I. M., Frederich, M., Bagwe, R., Lannig, G. & Sukhotin, A. A. Energy homeostasis as an integrative tool for assessing limits of environmental stress tolerance in aquatic invertebrates. Mar. Environ. Res. 79, 1–15 (2012).

    CAS  Article  Google Scholar 

  49. 49.

    Jombart, T., Devillard, S. & Balloux, F. Discriminant analysis of principal components: a new method for the analysis of genetically structured populations. BMC Genet. 11, 94 (2010).

    Article  Google Scholar 

  50. 50.

    Siljestam, M. & Ostman, O. The combined effects of temporal autocorrelation and the costs of plasticity on the evolution of plasticity. J. Evol. Biol. 30, 1361–1371 (2017).

    CAS  Article  Google Scholar 

  51. 51.

    DeWitt, T. J., Sih, A. & Wilson, D. S. Costs and limits of phenotypic plasticity. Trends Ecol. Evol. 13, 77–81 (1998).

    CAS  Article  Google Scholar 

  52. 52.

    Ghalambor, C. K., McKay, J. K., Carroll, S. P. & Reznick, D. N. Adaptive versus non-adaptive phenotypic plasticity and the potential for contemporary adaptation in new environments. Funct. Ecol. 21, 394–407 (2007).

    Article  Google Scholar 

  53. 53.

    Thor, P. & Dupont, S. Transgenerational effects alleviate severe fecundity loss during ocean acidification in a ubiquitous planktonic copepod. Glob. Change Biol. 21, 2261–2271 (2015).

    Article  Google Scholar 

  54. 54.

    Li, Z., Li, X., Wang, Z., Shen, Q. W. & Zhang, D. Antemortem stress regulates protein acetylation and glycolysis in postmortem muscle. Food Chem. 202, 94–98 (2016).

    CAS  Article  Google Scholar 

  55. 55.

    Li, A., Li, L., Song, K., Wang, W. & Zhang, G. Temperature, energy metabolism, and adaptive divergence in two oyster subspecies. Ecol. Evol. 7, 6151–6162 (2017).

    Article  Google Scholar 

  56. 56.

    Guo, X., Li, Q., Wang, Q. Z. & Kong, L. F. Genetic mapping and QTL analysis of growth-related traits in the Pacific oyster. Mar. Biotechnol. 14, 218–226 (2012).

    CAS  Article  Google Scholar 

  57. 57.

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

    CAS  Article  Google Scholar 

  58. 58.

    McKenna, A. et al. The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. Genome Res. 20, 1297–1303 (2010).

    CAS  Article  Google Scholar 

  59. 59.

    Li, H. et al. The sequence Alignment/Map format and SAMtools. Bioinformatics 25, 2078–2079 (2009).

    Article  Google Scholar 

  60. 60.

    Watterson, G. A. On the number of segregating sites in genetical models without recombination. Theor. Popul. Biol. 7, 256–276 (1975).

    CAS  Article  Google Scholar 

  61. 61.

    Hartl, D. L. The molecular approach to evolution: molecular evolutionary genetics. Science 237, 782 (1987).

    CAS  Article  Google Scholar 

  62. 62.

    Vilella, A. J., Blanco-Garcia, A., Hutter, S. & Rozas, J. VariScan: analysis of evolutionary patterns from large-scale DNA sequence polymorphism data. Bioinformatics 21, 2791–2793 (2005).

    CAS  Article  Google Scholar 

  63. 63.

    Barrett, J. C., Fry, B., Maller, J. & Daly, M. J. Haploview: analysis and visualization of LD and haplotype maps. Bioinformatics 21, 263–265 (2005).

    CAS  PubMed  PubMed Central  Google Scholar 

  64. 64.

    Wang, W. et al. Development of calibration models for rapid determination of chemical composition of Pacific oyster (Crassostrea gigas) by near infrared reflectance spectroscopy. J. Shellfish Res. 34, 303–309 (2015).

    CAS  Article  Google Scholar 

  65. 65.

    Freitas, V. et al. Temperature tolerance and energetics: a dynamic energy budget-based comparison of North Atlantic marine species. Phil. Trans. R. Soc. B 365, 3553–3565 (2010).

    Article  Google Scholar 

  66. 66.

    Zhu, Q., Zhang, L., Li, L., Que, H. & Zhang, G. Expression characterization of stress genes under high and low temperature stresses in the Pacific oyster, Crassostrea gigas. Mar. Biotechnol. 18, 176–188 (2016).

    CAS  Article  Google Scholar 

  67. 67.

    Meng, J. et al. Genome and transcriptome analyses provide insight into the euryhaline adaptation mechanism of Crassostrea gigas. PLoS ONE 8, e58563 (2013).

    CAS  Article  Google Scholar 

  68. 68.

    Livak, K. J. & Schmittgen, T. D. Analysis of relative gene expression data using real-time quantitative PCR and the 2−ΔΔCT method. Methods 25, 402–408 (2001).

    CAS  PubMed  PubMed Central  Google Scholar 

  69. 69.

    Trapnell, C., Pachter, L. & Salzberg, S. L. TopHat: discovering splice junctions with RNA-Seq. Bioinformatics 25, 1105–1111 (2009).

    CAS  Article  Google Scholar 

  70. 70.

    R Development Core Team R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2016).

  71. 71.

    Hadfiel, J. D. MCMC methods for multi-response generalized linear mixed models: the MCMCglmm R package. J. Stat. Softw. 33, 1–22 (2010).

    Google Scholar 

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G.Z. and L.L. are supported by the National Natural Science Foundation of China (31530079 to G.Z. and 31572620 to L.L.). G.Z. is supported by the Strategic Priority Research Program of the ‘Western Pacific Ocean System: Structure, Dynamics and Consequences’ project (XDA 11020305), Blue Life Breakthrough Program of LMBB (MS2018NO02) of Qingdao National Laboratory for Marine Science and Technology, and Modern Agro-industry Technology Research System (CARS-49). X.G. is supported by the ‘Taishan Overseas Scholar Program’ of Shandong and USDA/NJAES project 1004475/NJ32920. We thank J. Yan for suggestions on the experimental design and data analyses, Q. Li, Z. Yu, C. Ke, Z. Zeng, Y. Ning and Y. Bao for sampling collection, and B. Yin and J. Qi for information on marine currents.

Author information




L.L. and G.Z. conceived the study and designed the major scientific objectives. X.G. participated in the final data analysis and interpretation. L.L., W.W., H. Que, F.W., H. Qi, F.X., R.C., B.H., S. Zhang and Y. Li. participated in the collection of wild oysters. L.L., W.W., H. Qi., J.M., S.Z., C.L., T.W. and A.L. participated in oyster breeding for F1 and F2 generations. A.L., X.T., S.Liu, B.L., R.S. and Y. Liu. participated in larval rearing and adult management. J.M., C.L., T.W., X.T. and A.L. conducted DNA extraction and sequencing library preparation. K.S., S.Li, C.Z. and W.H. performed the genome sequencing. K.S., S.Li, C.Z., W.H., S. Zhao and A.L. contributed to the re-sequencing data analysis. A.L. and X.T. participated in the morphological measurements and sample collection for physiological and cellular determinations. A.L. conducted the laboratory experiments for measuring physiological and cellular parameters, as well as data analysis. A.L. conducted messenger RNA extraction for transcriptome and data analysis, and protein extraction for proteome and acetylome analysis. A.L. and C.B. contributed to data analysis of the proteome and acetylome. H.L. collected data on the monthly average SST. L.L., A.L., K.S., X.G., P.D.W., J.M., L.Z. and G.Z. did most of the writing and revision, with input from all authors. All authors approved the manuscript.

Corresponding author

Correspondence to Guofan Zhang.

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Supplementary Information

Supplementary Information

Supplementary Figures and Tables

Reporting Summary

Supplementary Table 3

Mapping statistics for Pacific oyster samples resequenced

Supplementary Table 4

SNP statistics in different genomic regions for each Pacific oyster sample

Supplementary Table 8

Genes from genomic regions under selection in Bohai and southern Yellow Seas and their FST values

Supplementary Table 9

GO enrichment analysis of genes from regions under selection in Bohai and southern Yellow Seas

Supplementary Table 10

Annotation of genes from regions under selection in Bohai and southern Yellow Seas

Supplementary Table 11

Summary statistics of transcriptome dataset

Supplementary Table 12

Genes exhibiting significant transcriptional response at 6 and 24 hr of heat shock in oysters from JZ and QD

Supplementary Table 13

Summary statistics of proteome and acetylome datasets

Supplementary Table 14

Numbers of proteins and acetyl sites showing differential abundance

Supplementary Table 16

Genes exhibiting both significantly differential expression in response to high temperature and differential plasticity at 6 and 24 hr in oysters from JZ and QD

Supplementary Table 17

Acetyl sites exhibiting differential plasticity in proteins of major energy metabolic pathways when oysters were exposed to high temperature for 6 and 24 hr

Supplementary Table 18

Expression level of proteins corresponding to acetyl sites exhibiting differential plasticity in key energy metabolic pathways

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Li, L., Li, A., Song, K. et al. Divergence and plasticity shape adaptive potential of the Pacific oyster. Nat Ecol Evol 2, 1751–1760 (2018).

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