Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Review Article
  • Published:

Towards identifying genes underlying ecologically relevant traits in Arabidopsis thaliana

Key Points

  • Identifying the genetic basis of ecologically important characters is a first step in retracing the trajectory of adaptive traits in natural populations of plants as well as in potentially improving crop yield and quality.

  • Genome-wide association (GWA) mapping is a highly effective means of gene discovery in Arabidopsis thaliana, with a substantial fraction of phenotypic variation being explained by few quantitative trait loci (QTLs).

  • Dual linkage and association mapping clearly outperforms each method in isolation.

  • The scale of adaptation, which depends on the ecological factors acting as selective pressures, will determine the scale at which GWA mapping populations should be constructed.

  • Combining genotypic and epigenetic information will help to tease apart the effect of DNA sequence variants from that of DNA methylation variants.

  • The genetic basis of genotype–environment interactions remains to be determined in A. thaliana.

  • The heterogeneity encountered by A. thaliana suggests that the phenotyping of ecologically relevant traits should be performed in natural populations, not only in the greenhouse.

  • The current revolution in next-generation sequencing facilitates a direct access to the causal mutations that underlie adaptive trait variation.

  • The next challenge for dissecting the genetic bases of adaptive variation is the high-throughput phenotyping of complex traits under natural conditions.

Abstract

A major challenge in evolutionary biology and plant breeding is to identify the genetic basis of complex quantitative traits, including those that contribute to adaptive variation. Here we review the development of new methods and resources to fine-map intraspecific genetic variation that underlies natural phenotypic variation in plants. In particular, the analysis of 107 quantitative traits reported in the first genome-wide association mapping study in Arabidopsis thaliana sets the stage for an exciting time in our understanding of plant adaptation. We also argue for the need to place phenotype–genotype association studies in an ecological context if one is to predict the evolutionary trajectories of plant species.

This is a preview of subscription content, access via your institution

Access options

Rent or buy this article

Prices vary by article type

from$1.95

to$39.95

Prices may be subject to local taxes which are calculated during checkout

Figure 1: Linkage mapping populations in Arabidopsis thaliana.
Figure 2: Advantages of combining association and traditional linkage mapping methods.
Figure 3: Genetic and allelic heterogeneity.
Figure 4: Reaction norms of flowering time between the greenhouse and the common garden.
Figure 5: Unravelling the origin of genetic correlations.

Similar content being viewed by others

References

  1. Fisher, R. A. (ed.) The Genetical Theory of Natural Selection (Clarendon, Oxford, 1930).

    Google Scholar 

  2. Hermisson, J. & Pennings, P. S. Soft sweeps: molecular population genetics of adaptation from standing genetic variation. Genetics 169, 2335–2352 (2005).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Orr, H. A. The genetic theory of adaptation: a brief history. Nature Rev. Genet. 6, 119–127 (2005).

    CAS  PubMed  Google Scholar 

  4. Kopp, M. & Hermisson, J. Adaptation of a quantitative trait to a moving optimum. Genetics 176, 715–719 (2007).

    CAS  PubMed  PubMed Central  Google Scholar 

  5. Kopp, M. & Hermisson, J. The genetic basis of phenotypic adaptation I: fixation of beneficial mutations in the moving optimum model. Genetics 182, 233–249 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  6. Stern, D. L. & Orgogozo, V. Is genetic evolution predictable? Science 323, 746–751 (2009). An interesting review on the predictability of genetic evolution, with a special emphasis on the factors that influence the distribution of mutations relevant for phenotypic evolution.

    CAS  PubMed  PubMed Central  Google Scholar 

  7. Rafalski, J. A. Association genetics on crop improvement. Curr. Opin. Plant Biol. 13, 1–7 (2010).

    Google Scholar 

  8. Erickson, D. L., Fenster, C. B., Stenoien, H. K. & Price, D. Quantitative trait locus analyses and the study of evolutionary process. Mol. Ecol. 13, 2505–2522 (2004).

    CAS  PubMed  Google Scholar 

  9. Mitchell-Olds, T. & Schmitt, J. Genetic mechanisms and evolutionary significance of natural variation in Arabidopsis. Nature 441, 947–952 (2006).

    CAS  PubMed  Google Scholar 

  10. Ellegren, H. & Sheldon, B. C. Genetic basis of fitness differences in natural populations. Nature 452, 169–175 (2008).

    CAS  PubMed  Google Scholar 

  11. Bergelson, J., Stahl, E., Dudek, S. & Kreitman, M. Genetic variation within and among populations of Arabidopsis thaliana. Genetics 148, 1311–1323 (1998).

    CAS  PubMed  PubMed Central  Google Scholar 

  12. Le Corre, V. Variation at two flowering time genes within and among populations of Arabidopsis thaliana: comparison with markers and traits. Mol. Ecol. 14, 4181–4192 (2005).

    CAS  PubMed  Google Scholar 

  13. Bomblies, K. et al. Local-scale patterns of genetic variability, outcrossing, and spatial structure in natural stands of Arabidopsis thaliana. PLoS Genet. 6, e10000890 (2010).

    Google Scholar 

  14. Platt, A. et al. The scale of population structure in Arabidopsis thaliana. PLoS Genet. 6, 1–8 (2010). References 13 and 14 describe the scale and patterns of genetic variability in natural populations of A. thaliana , using either local stands or worldwide samples, respectively.

    Google Scholar 

  15. Koornneef, M., Alonso-Blanco, C. & Vreugdenhil, D. Naturally occurring genetic variation in Arabidopsis thaliana. Annu. Rev. Plant Biol. 55, 141–172 (2004).

    CAS  PubMed  Google Scholar 

  16. Alonso, J. M. & Ecker, J. R. Moving forward in reverse: genetic technologies to enable genome-wide phenomic screens in Arabidopsis. Nature Rev. Genet. 7, 524–536 (2006).

    CAS  PubMed  Google Scholar 

  17. Atwell, S. et al. Genome-wide association study of 107 phenotypes in a common set of Arabidopsis thaliana inbred lines. Nature 465, 627–631 (2010). This first report of GWA mapping in plants highlights both advantages and pitfalls related to GWA mapping.

    CAS  PubMed  PubMed Central  Google Scholar 

  18. Nordborg, M. & Weigel, D. Next-generation genetics in plants. Nature 456, 720–723 (2008).

    CAS  PubMed  Google Scholar 

  19. Myles, S. et al. Association mapping: critical considerations shift from genotyping to experimental design. Plant Cell 21, 2194–2202 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  20. Mitchell-Olds, T. Complex-traits analysis in plants. Genome Biol. 11, 113 (2010).

    PubMed  PubMed Central  Google Scholar 

  21. Rosenberg, N. A. et al. Genome-wide association studies in diverse populations. Nature Rev. Genet. 11, 356–366 (2010).

    CAS  PubMed  Google Scholar 

  22. Frenkel, M., Jänkänpää, H. J. & Jansson, S. An illustrated gardener's guide to transgenic Arabidopsis field experiments. New Phytol. 180, 545–555 (2008).

    PubMed  Google Scholar 

  23. Brachi, B. et al. Linkage and association mapping of Arabidopsis thaliana flowering time in nature. PLoS Genet. 6, e1000940 (2010). The first report of dual linkage–GWA mapping in a common garden, strengthening evidence for the need to use complementary methods to decrease both false-positive and false-negative rates in A. thaliana.

    PubMed  PubMed Central  Google Scholar 

  24. Wilczek, A. M. et al. Effects of genetic perturbation on seasonal life history plasticity. Science 323, 930–934 (2009). This outstanding paper links functional genomics and ecologically realistic conditions for a better understanding of selection on flowering-time genes in A. thaliana.

    CAS  PubMed  Google Scholar 

  25. Thomas, D. Gene–environment-wide association studies: emerging approaches. Nature Rev. Genet. 11, 259–272 (2010).

    CAS  PubMed  Google Scholar 

  26. Roff, D. A. Contributions of genomics to life-history theory. Nature Rev. Genet. 8, 116–125 (2007).

    CAS  PubMed  Google Scholar 

  27. Lister, R., Gregory, B. D. & Ecker, J. R. Next is now: new technologies for sequencing of genomes, transcriptomes, and beyond. Curr. Opin. Plant Biol. 12, 107–118 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  28. Metzker, M. L. Sequencing technologies - the next generation. Nature Rev. Genet. 11, 31–46 (2010). A well-illustrated review of NGS technologies.

    CAS  PubMed  Google Scholar 

  29. Delseny, M., Han, B. & Hsing, Y. I. High throughput DNA sequencing: the new sequencing revolution. Plant Sci. 179, 407–422 (2010).

    CAS  PubMed  Google Scholar 

  30. Kowalski, S. P., Lan, T. H., Feldmann, K. A. & Paterson, A. H. QTL mapping of naturally-occurring variation in flowering time of Arabidopsis thaliana. Mol. Genet. Genomics 245, 548–555 (1994).

    CAS  Google Scholar 

  31. Kover, P. X. et al. A multiparent advanced generation inter-cross to fine-map quantitative traits in Arabidopsis thaliana. PLoS Genet. 5, e1000551 (2009).

    PubMed  PubMed Central  Google Scholar 

  32. Lynch, M. & Walsh, S. Genetics and Analysis of Quantitative Traits (Sinauer Associates, Sunderland, Massachusetts, 1998).

    Google Scholar 

  33. Price, A. H. Believe it or not, QTLs are accurate! Trends Plant Sci. 11, 213–216 (2006).

    CAS  PubMed  Google Scholar 

  34. Borevitz, J. & Chory, J. Genomics tools for QTL analysis and gene discovery. Curr. Opin. Plant Biol. 7, 132–136 (2004).

    CAS  PubMed  Google Scholar 

  35. Tuinstra, M. R., Ejeta, G. & Goldsbrough, P. B. Heterogeneous inbred family (HIF) analysis: a method for developing near-isogenic lines that differ at quantitative trait loci. Theor. Appl. Genet. 95, 1005–1011 (1997).

    CAS  Google Scholar 

  36. Keurentjes, J. J. B. et al. Development of a near-isogenic line population of Arabidopsis thaliana and comparison of mapping power with a recombinant inbred line population. Genetics 175, 891–905 (2007).

    CAS  PubMed  PubMed Central  Google Scholar 

  37. Roosens, N. H., Willems, G. & Saumitou-Laprade, P. Using Arabidopsis to explore zinc tolerance and hyperaccumulation. Trends Plant Sci. 13, 208–215 (2008).

    CAS  PubMed  Google Scholar 

  38. Verbruggen, N., Hermans, C. & Schat, H. Molecular mechanisms of metal hyperaccumulation in plants. New Phytol. 181, 759–776 (2009).

    CAS  PubMed  Google Scholar 

  39. Schneeberger, K. et al. SHOREmap: simultaneous mapping and mutation identification by deep sequencing. Nature Methods 6, 550–551 (2009).

    CAS  PubMed  Google Scholar 

  40. Laitinen, R. A., Schneeberger, K., Jelly, N. S., Ossowski, S. & Weigel, D. Identification of a spontaneous frame shift mutation in a nonreference Arabidopsis accession using while genome sequencing. Plant Physiol. 153, 652–654 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  41. Ehrenreich, I. M. et al. Dissection of genetically complex traits with extremely large pools of yeast segregants. Nature 464, 1039–1042 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  42. Ehrenreich, I. M. et al. Candidate gene association mapping of Arabidopsis flowering time. Genetics 183, 325–335 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  43. Zhu, C., Gore, M., Buckler, E. S. & Yu, J. Status and prospects of association mapping in plants. Plant Genome 1, 5–20 (2008).

    CAS  Google Scholar 

  44. Kim, S. et al. Recombination and linkage disequilibrium in Arabidopsis thaliana. Nature Genet. 39, 1151–1155 (2007).

    CAS  PubMed  Google Scholar 

  45. Zhang, X., Richards, E. J. & Borevitz, J. O. Genetic and epigenetics dissection of cis regulatory variation. Curr. Opin. Plant Biol. 10, 142–148 (2007).

    CAS  PubMed  Google Scholar 

  46. Aranzana, M. J. et al. Genome-wide association mapping in Arabidopsis identifies previously known flowering time and pathogen resistance genes. PLoS Genet. 1, e60 (2005).

    PubMed  PubMed Central  Google Scholar 

  47. Warren, R. F., Henk, A., Mowery, P., Holub, E. & Innes, R. W. A mutation within the leucine-rich repeat domain of the Arabidopsis disease resistance gene RPS5 partially suppresses multiple bacterial and downy mildew resistance genes. Plant Cell 10, 1439–1452 (1998).

    CAS  PubMed  PubMed Central  Google Scholar 

  48. Grant, M. R. et al. Structure of the Arabidopsis RPM1 gene enabling dual specificity disease resistance. Science 269, 843–846 (1995).

    CAS  PubMed  Google Scholar 

  49. Nemri, A. et al. Genome-wide survey of Arabidopsis natural variation in downy mildew resistance using combined association and linkage mapping. Proc. Natl Acad. Sci. USA 107, 10302–10307 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  50. Todesco, M. et al. Natural allelic variation underlying a major fitness trade-off in Arabidopsis thaliana. Nature 465, 632–636 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  51. Manolio, T. A. et al. Finding the missing heritability of complex diseases. Nature 461, 747–753 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  52. Zhao, K. et al. An Arabidopsis example of association mapping in structured samples. PLoS Genet. 3, e4 (2007).

    PubMed  PubMed Central  Google Scholar 

  53. Manenti, G. et al. Mouse genome-wide association mapping needs linkage analysis to avoid false-positive loci. PLoS Genet. 5, e1000331 (2009).

    PubMed  PubMed Central  Google Scholar 

  54. Dillmann, C., Bar-Hen, A., Guérin, D., Charcosset, A. & Murigneux, A. Comparison of RFLP and morphological distances between maize Zea mays L. inbred lines. Consequences for germplasm protection purposes. Theor. Appl. Genet. 95, 92–102 (1997).

    CAS  Google Scholar 

  55. Vignieri, S. N., Larson, J. G. & Hoekstra, H. E. The selective advantage of crypsis in mice. Evolution 64, 2153–2158 (2010).

    PubMed  Google Scholar 

  56. Hoekstra, H. E., Hirschmann, R. J., Bundey, R. A., Insel, P. A. & Crossland, J. P. A single amino-acid mutation contributes to adaptive beach mouse color pattern. Science 313, 101–104 (2003). A well-designed study to functionally validate the genetic basis of an adaptive trait in a non-model species.

    Google Scholar 

  57. Veyrieras, J.-B., Goffinet, B. & Charcosset, A. MetaQTL: a package of new computational methods for the meta-analysis of QTL mapping experiments. BMC Bioinformatics 8, 49–64 (2007).

    PubMed  PubMed Central  Google Scholar 

  58. Simon, M. et al. Quantitative trait loci mapping in five new large recombinant inbred line populations of Arabidopsis thaliana genotyped with consensus single-nucleotide polymorphism markers. Genetics 178, 2253–2264 (2008).

    CAS  PubMed  PubMed Central  Google Scholar 

  59. Johanson, U. et al. Molecular analysis of FRIGIDA, a major determinant of natural variation in Arabidopsis flowering time. Science 290, 344–347 (2000).

    CAS  PubMed  Google Scholar 

  60. Le Corre, V., Roux, F. & Reboud, X. DNA polymorphism at the FRIGIDA gene in Arabidopsis thaliana: extensive nonsynonymous variation is consistent with local selection for flowering time. Mol. Biol. Evol. 19, 1261–1271 (2002).

    CAS  PubMed  Google Scholar 

  61. Yan, L. et al. The wheat VRN2 gene is a flowering repressor down-regulated by vernalization. Science 303, 1640–1644 (2004).

    CAS  PubMed  PubMed Central  Google Scholar 

  62. Buckler, E. S. et al. The genetic architecture of maize flowering time. Science 325, 714–718 (2009). An ambitious mapping study using the NAM populations of maize in a set of field experiments that reveals that, unlike in A. thaliana , many alleles of small effect mediate flowering time in an additive fashion.

    CAS  PubMed  Google Scholar 

  63. Yu, J., Holland, J. B., McMullen, M. D. & Buckler, E. S. Genetic design and statistical power of nested association mapping in maize. Genetics 178, 539–551 (2008).

    PubMed  PubMed Central  Google Scholar 

  64. Stich, B. Comparison of mating designs for establishing nested association mapping populations in maize and Arabidopsis thaliana. Genetics 183, 1525–1534 (2009).

    PubMed  PubMed Central  Google Scholar 

  65. Nordborg, M. et al. The pattern of polymorphism in Arabidopsis thaliana. PLoS Biol. 3, e196 (2005).

    PubMed  PubMed Central  Google Scholar 

  66. Bergelson, J., Kreitman, M., Stahl, E. A. & Tian, D. Evolutionary dynamics of plant R-genes. Science 292, 2281–2285 (2001).

    CAS  PubMed  Google Scholar 

  67. Stahl, E. A., Dwyer, G., Mauricio, R., Kreitman, M. & Bergelson, J. Dynamics of disease resistance polymorphism at the Rpm1 locus of Arabidopsis. Nature 400, 667–671 (1999).

    CAS  PubMed  Google Scholar 

  68. Bakker, E., Traw, B. M., Toomajian, C., Kreitman, M. & Bergelson, J. Low levels of polymorphism in genes that control the activation of defense response in Arabidopsis thaliana. Genetics 178, 2031–2043 (2008).

    CAS  PubMed  PubMed Central  Google Scholar 

  69. Weigel, D. & Mott, R. The 1001 genomes project for Arabidopsis thaliana. Genome Biol. 10, 107 (2009).

    PubMed  PubMed Central  Google Scholar 

  70. Caicedo, A. L., Richards, C., Ehrenreich, I. M. & Purugganan, M. Complex rearrangements lead to novel chimeric gene fusion polymorphisms at the Arabidopsis thaliana MAF2–5 flowering time gene cluster. Mol. Biol. Evol. 26, 699–711 (2009).

    CAS  PubMed  Google Scholar 

  71. Kroymann, J., Donnerhacke, S., Schnabelrauch, D. & Mitchell-Olds, T. Evolutionary dynamics of an Arabidopsis insect resistance quantitative trait locus. Proc. Natl Acad. Sci. USA 100, 14587–14592 (2003).

    CAS  PubMed  PubMed Central  Google Scholar 

  72. Richards, E. J. Inheritance epigenetic variation — revisiting soft inheritance. Nature Rev. Genet. 7, 395–401 (2006).

    CAS  PubMed  Google Scholar 

  73. Bossdorf, O., Richards, C. L. & Pigliucci, M. Epigenetics for ecologists. Ecol. Lett. 11, 106–115 (2008).

    PubMed  Google Scholar 

  74. Vaughn, M. W. et al. Epigenetic natural variation in Arabidopsis thaliana. PLoS Biol. 5, e174 (2007).

    PubMed  PubMed Central  Google Scholar 

  75. Johannes, F. et al. Assessing the impact of transgenerational epigenetic variation on complex traits. PLoS Genet. 5, e10000530 (2009). References 74 and 75 demonstrate the importance of epigenetic alterations in A. thaliana as a possible source of heritable phenotypic variation and the need to epigenotype natural accessions to infer causal relationships between genotype and phenotype.

    Google Scholar 

  76. Lister, R. et al. Highly integrated single-base resolution maps of the epigenome in Arabidopsis. Cell 133, 1–14 (2008).

    Google Scholar 

  77. Zhang, X., Shiu, S., Cal, A. & Borevitz, J. O. Global analysis of genetic, epigenetic and transcriptional polymorphisms in Arabidopsis thaliana using whole genome tilling arrays. PLoS Genet. 4, e1000032 (2008).

    PubMed  PubMed Central  Google Scholar 

  78. Laird, P. W. Principles and challenges of genome-wide DNA methylation analysis. Nature Rev. Genet. 11, 191–203 (2010).

    CAS  PubMed  Google Scholar 

  79. Sillanpää, M. J. Overview of techniques to account for confounding due to population stratification and cryptic relatedness in genomic data association analyses. Heredity 14 Jul 2010 (doi: 10.1038/hdy.2010.91).

    PubMed  PubMed Central  Google Scholar 

  80. Kang, H. M. et al. Efficient control of population structure in model organism association mapping. Genetics 178, 1709–1723 (2008).

    PubMed  PubMed Central  Google Scholar 

  81. Price, A. L., Zaitlen, N. A., Reich, D. & Patterson, N. New approaches to population stratification in genome-wide association studies. Nature Rev. Genet. 11, 459–463 (2010).

    CAS  PubMed  Google Scholar 

  82. El-Din El-Assal, S., Alonso-Blanco, C., Peeters, A. J. M., Raz, V. & Koornneef, M. A QTL for flowering time in Arabidopsis reveals a novel allele of CRY2. Nature Genet. 29, 435–440 (2001).

    CAS  PubMed  Google Scholar 

  83. Zhang, Z. et al. Mixed linear model approach adapted for genome-wide association studies. Nature Genet. 42, 355–360 (2010).

    CAS  PubMed  Google Scholar 

  84. Bradbury, P. J. et al. TASSEL: software for association mapping of complex traits in diverse samples. Bioinformatics 29, 2633–2635 (2007).

    Google Scholar 

  85. Kang, H. M. et al. Variance component model to account for sample structure in genome-wide association studies. Nature Genet. 42, 348–354 (2010).

    CAS  PubMed  Google Scholar 

  86. Kim, S. & Xing, E. P. Statistical estimation of correlated genome associations to a quantitative trait network. PLoS Genet. 5, e1000587 (2009).

    PubMed  PubMed Central  Google Scholar 

  87. Tishkoff, S. A. et al. Convergent adaptation of human lactase persistence in Africa and Europe. Nature Genet. 39, 31–40 (2007).

    CAS  PubMed  Google Scholar 

  88. Puniyani, K., Kim, S. & Xing, E. P. Multi-population GWA mapping via multi-task regularized regression. Bioinformatics 26, i208–i216 (2010). This paper describes the development of a promising multi-population GWA mapping method that enables the detection of causal genetic markers that are unique to a subset of the populations.

    CAS  PubMed  PubMed Central  Google Scholar 

  89. O'Malley, R. C. & Ecker, J. R. Linking genotype to phenotype using the Arabidopsis unimutant collection. Plant J. 61, 928–940 (2010).

    CAS  PubMed  Google Scholar 

  90. Weinig, C. et al. Novel loci control variation in reproductive timing in Arabidopsis thaliana in natural environments. Genetics 162, 1875–1884 (2002). The first paper describing QTL mapping in outdoor conditions. It makes clear that phenotypes should be assessed in ecologically realistic conditions to allow the detection of genes underlying natural variation in A. thaliana.

    CAS  PubMed  PubMed Central  Google Scholar 

  91. Tian, D., Traw, M. B., Chen, J. Q., Kreitman, M. & Bergelson, J. Fitness costs of R-gene-mediated resistance in Arabidopsis thaliana. Nature 423, 74–77 (2003).

    CAS  PubMed  Google Scholar 

  92. Vergunst, A. C. & Hooykaas, P. J. Cre/lox-mediated site-specific integration of Agrobcaterium T-DBA in Arabidopsis thaliana by transient expression of cre. Plant Mol. Biol. 38, 393–406 (1998).

    CAS  PubMed  Google Scholar 

  93. Alonso-Blanco, C. et al. What has natural variation taught us about plant development, physiology, and adaptation? Plant Cell 21, 1877–1896 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  94. Egli, D. B. Seed-fill duration and yield of grain crops. Adv. Agron. 83, 243–279 (2004).

    Google Scholar 

  95. Kover, P. X. & Schaal, B. A. Genetic variation for disease resistance and tolerance among Arabidopsis thaliana accessions. Proc. Natl Acad. Sci. USA 99, 11270–11274 (2002).

    CAS  PubMed  PubMed Central  Google Scholar 

  96. Gao, L., Roux, F. & Bergelson, J. Quantitative fitness effects of infection in a gene-for-gene system. New Phytol. 184, 485–494 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  97. Levins, R. Evolution in Changing Environments (Princeton Univ. Press, New Jersey, 1968).

    Google Scholar 

  98. Becker, U., Dostal, P., Jorritsma-Wienk, L. D. & Matthies, D. The spatial scale of adaptive population differentiation in a wide-spread, well-dispersed plant species. Oikos 117, 1865–1976 (2008).

    Google Scholar 

  99. Caicedo, A. L., Stinchcombe, J. R., Olsen, K. M. & Purugganan, M. Epistatic interaction between Arabidopsis FRI and FLC flowering time genes generates a latitudinal cline in a life history trait. Proc. Natl Acad. Sci. USA 101, 15670–15675 (2004).

    CAS  PubMed  PubMed Central  Google Scholar 

  100. Stinchcombe, J. R. et al. A latitudinal cline in flowering time in Arabidopsis thaliana modulated by the flowering time gene FRIGIDA. Proc. Natl Acad. Sci. USA 101, 4712–4717 (2004).

    CAS  PubMed  PubMed Central  Google Scholar 

  101. Marquis, R. in Plant Resistance to Herbivores and Pathogens: Ecology, Evolution and Genetics (eds Fritz, R. S. & Simms, E. L.) 301–325 (Univ. Chicago Press, Illinois, 1992).

    Google Scholar 

  102. Stratton, D. A. & Bennington, C. C. Measuring spatial variation in natural selection using randomly-sown seeds of Arabidopsis thaliana. J. Evol. Biol. 9, 215–228 (1996).

    Google Scholar 

  103. Goss, E. M. & Bergelson, J. Fitness consequences of pathogen infection of Arabidopsis thaliana with its natural bacterial pathogen Pseudomonas viridiflava. Oecologia 152, 71–81 (2007).

    PubMed  Google Scholar 

  104. Mani, G. S. Evolution of resistance in the presence of two insecticides. Genetics 109, 761–783 (1985).

    CAS  PubMed  PubMed Central  Google Scholar 

  105. Roux, F., Paris, M. & Reboud, X. Delaying weed adaptation to herbicide by environmental heterogeneity: a simulation approach. Pest Manag. Sci. 64, 16–29 (2008).

    CAS  PubMed  Google Scholar 

  106. Kassen, R. & Bell, G. Experimental evolution in Chlamydomonas. IV. Selection in environments that vary through time at different scales. Heredity 80, 732–741 (1998).

    Google Scholar 

  107. Kassen, R. The experimental evolution of specialists, generalists, and the maintenance of diversity. J. Evol. Biol. 15, 173–190 (2002).

    Google Scholar 

  108. Bell, G. Fluctuating selection: the perpetual renewal of adaptation in variable environments. Philos. Trans. R. Soc. Lond. B 365, 87–97 (2010).

    Google Scholar 

  109. Lennartsson, T., Tuomi, J. & Nilsson, P. Evidence for an evolutionary history of overcompensation in the grassland biennial Gentianella campestris (Gentianaceae). Am. Nat. 149, 1147–1155 (1997).

    CAS  PubMed  Google Scholar 

  110. Poveda, K., Steffan-Dewenter, I., Scheu, S. & Tscharntke, T. Effects of below- and above-ground herbivores on plant growth, flower visitation and seed set. Oecologia 135, 601–605 (2003).

    PubMed  Google Scholar 

  111. Lefebvre, V., Kiani, S. P. & Durand-Tardif, M. A focus on natural variation for abiotic constraints response in the model species Arabidopsis thaliana. Int. J. Mol. Sci. 10, 3547–3582 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  112. Wielgolaski, F. E. Phenological modifications in plants by various edaphic factors. Int. J. Biometeorol.. 45, 196–202 (2001).

    CAS  PubMed  Google Scholar 

  113. Nord, E. A. & Lynch, J. P. Delayed reproduction in Arabidopsis thaliana improves fitness in soil with suboptimal phosphorus availability. Plant Cell Environ. 31, 1432–1441 (2008).

    CAS  PubMed  Google Scholar 

  114. Baxter, I. et al. A coastal cline in sodium accumulation in Arabidopsis thaliana is driven by natural variation of the sodium transporter AtHKT1-1. PLoS Genet. (in the press).

  115. Gardner, K. M. & Latta, R. G. Identifying loci under selection across contrasting environments in Avena barbata using quantitative trait locus mapping. Mol. Ecol. 15, 1321–1333 (2006).

    CAS  PubMed  Google Scholar 

  116. Weinig, C. et al. Heterogeneous selection at specific loci in natural environments in Arabidopsis thaliana. Genetics 165, 321–329 (2003).

    CAS  PubMed  PubMed Central  Google Scholar 

  117. Malmberg, R. L., Held, S., Waits, A. & Mauricio, R. Epistasis for fitness-related quantitative traits in Arabidopsis thaliana grown in the field and in the greenhouse. Genetics 171, 2013–2027 (2005).

    CAS  PubMed  PubMed Central  Google Scholar 

  118. Li, Y., Roycewicz, P., Smith, E. & Borevitz, J. O. Genetics of local adaptation in the laboratory: flowering time quantitative trait loci under geographic and seasonal conditions in Arabidopsis. PLoS ONE 1, e105 (2006).

    PubMed  PubMed Central  Google Scholar 

  119. Scarcelli, N., Cheverud, J. M., Schaal, B. A. & Kover, P. X. Antagonistic pleiotropic effects reduce the potential adaptive value of the FRIGIDA locus. Proc. Natl Acad. Sci. USA 104, 16986–16991 (2007).

    CAS  PubMed  PubMed Central  Google Scholar 

  120. Kover, P. X. et al. Pleiotropic effects of environment-specific adaptation in Arabidopsis thaliana. New Phytol. 183, 816–825 (2009).

    CAS  PubMed  Google Scholar 

  121. Dorn, L. A., Pyle, E. H. & Schmitt, J. Plasticity to light cues and resources in Arabidopsis thaliana: testing for adaptive value and costs. Evolution 54, 1982–1994 (2000).

    CAS  PubMed  Google Scholar 

  122. Weinig, C., Stinchcombe, J. R. & Schmitt, J. QTL architecture of resistance and tolerance traits in Arabidopsis thaliana in natural environments. Mol. Ecol. 12, 1153–1163 (2003).

    CAS  PubMed  Google Scholar 

  123. Roux, F., Gao, L. & Bergelson, J. Impact of initial pathogen density on resistance and tolerance in a polymorphic disease resistance gene system in Arabidopsis thaliana. Genetics 185, 283–291 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  124. Kingsolver, J. G., Pfennig, D. W. & Servedio, M. R. Migration, local adaptation and the evolution of plasticity. Trends Ecol. Evol. 17, 540–541 (2002).

    Google Scholar 

  125. Weinig, C. & Schmitt, J. Environmental effects on the expression of quantitative trait loci and implications for phenotypic evolution. Bioscience 54, 627–635 (2004).

    Google Scholar 

  126. Donohue, K. et al. Environmental and genetic influences on the germination of Arabidopsis thaliana in the field. Evolution 59, 740–757 (2005).

    PubMed  Google Scholar 

  127. Kliebenstein, D., Figuth, A. & Mitchell-Olds, T. Genetic architecture of plastic methyl jasmonate responses in Arabidopsis thaliana. Genetics 161, 1685–1696 (2002).

    CAS  PubMed  PubMed Central  Google Scholar 

  128. Rauh, B. L., Basten, C. & Buckler, E. S. Quantitative trait loci analysis of growth response to varying nitrogen sources in Arabidopsis thaliana. Theor. Appl. Genet. 104, 743–750 (2002).

    CAS  PubMed  Google Scholar 

  129. Loudet, O., Chaillou, S., Krapp, A. & Daniel-Vedele, F. Quantitative trait loci analysis of water and anion contents in interaction with nitrogen availability in Arabidopsis thaliana. Genetics 163, 711–722 (2003).

    CAS  PubMed  PubMed Central  Google Scholar 

  130. Ungerer, M. C., Halldorsdottir, S. S., Purugganan, M. D. & Mackay, T. F. Genotype-environment interactions at quantitative trait loci affecting inflorescence development in Arabidopsis thaliana. Genetics 165, 353–365 (2003).

    CAS  PubMed  PubMed Central  Google Scholar 

  131. Hausmann, N. J. et al. Quantitative trait loci affecting δ13C and response to differential water availability in Arabidopsis thaliana. Evolution 59, 81–96 (2005).

    CAS  PubMed  Google Scholar 

  132. Botto, J. F. & Coluccio, M. P. Seasonal and plant-density dependency for quantitative trait loci affecting flowering time in multiple populations of Arabidopsis thaliana. Plant Cell Environ. 30, 1465–1479 (2007).

    PubMed  Google Scholar 

  133. Li, Y., Huang, Y., Bergelson, J., Nordborg, M. & Borevitz, J. Association mapping of local climate sensitive QTL in Arabidopsis thaliana. Proc. Natl Acad. Sci. USA (in the press).

  134. Mackay, T. F., Stone, E. A. & Ayroles, J. F. The genetics of quantitative traits: challenges and prospects. Nature Rev. Genet. 10, 565–577 (2009). A comprehensive Review of the consensus and challenges for obtaining a better understanding of the genetic architecture of complex phenotypic traits.

    CAS  PubMed  Google Scholar 

  135. Carlson, C. S., Eberle, M. A., Kruglyak, L. & Nickerson, D. A. Mapping complex disease loci in whole-genome association studies. Nature 429, 446–452 (2004).

    CAS  PubMed  Google Scholar 

  136. Bergelson, J. The effects of genotype and the environment on costs of resistance in lettuce. Am. Nat. 143, 349–359 (1994).

    Google Scholar 

  137. Byers, D. L. Evolution in heterogeneous environments and the potential of maintenance of genetic variation in traits of adaptive significance. Genetica 123, 107–124 (2005).

    PubMed  Google Scholar 

  138. Gardner, K. M. & Latta, R. G. Shared quantitative trait loci underlying the genetic correlation between continuous traits. Mol. Ecol. 16, 4195–4209 (2007).

    PubMed  Google Scholar 

  139. Armbruster, W. S. & Schwaegerle, K. E. Causes of covariation of phenotypic traits among populations. J. Evol. Biol. 6, 261–276 (1996).

    Google Scholar 

  140. Li, B., Suzuki, J.-I. & Hara, T. Latitudinal variation in plant size and relative growth rate in Arabidopsis thaliana. Oecologia 115, 293–301 (1998).

    PubMed  Google Scholar 

  141. Flint, J. & Mackay, T. F. C. Genetic architecture of quantitative traits in mice, flies, and humans. Genome Res. 19, 723–733 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  142. Toomajian, C. et al. A nonparametric test reveals selection for rapid flowering in the Arabidopsis genome. PLoS Biol. 4, e137 (2006).

    PubMed  PubMed Central  Google Scholar 

  143. Ungerer, M., Johnson, L. C. & Herman, M. A. Ecological genomics: understanding gene and genome function in the natural environment. Heredity 100, 178–183 (2008).

    CAS  PubMed  Google Scholar 

  144. Jansen, M. et al. Simultaneous phenotyping of leaf growth and chlorophyll fluorescence via GROWSCREEN FLUORO allows detection of stress tolerance in Arabidopsis thaliana and other rosette plants. Funct. Plant Biol. 11, 902–914 (2009).

    Google Scholar 

  145. Massonnet, C. et al. Probing the reproducibility of leaf growth and molecular phenotypes: a comparison of three Arabidopsis accessions cultivated in ten laboratories. Plant Physiol. 152, 2142–2157 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  146. Hagenblad, J. & Nordborg, M. Sequence variation and haplotype structure surrounding the flowering time locus FRI in Arabidopsis thaliana. Genetics 161, 289–298 (2002).

    CAS  PubMed  PubMed Central  Google Scholar 

  147. Ehrenreich, I. M., Stafford, P. A. & Purugganan, M. The genetic architecture of shoot branching in Arabidopsis thaliana: a comparative assessment of candidate gene associations vs. quantitative trait locus mapping. Genetics 173, 1223–1236 (2007).

    Google Scholar 

  148. McMullen, M. D. et al. Genetic properties of the maize nested association mapping population. Science 325, 737–740 (2009).

    CAS  PubMed  Google Scholar 

  149. Kusterer, B. et al. Analysis of triple testcross design with recombinant inbred lines reveals a significant role for epistasis in heterosis for biomass-related traits in Arabidopsis. Genetics 175, 2009–2017 (2007).

    CAS  PubMed  PubMed Central  Google Scholar 

  150. Kusterer, B. et al. Heterosis for biomass-related traits in Arabidopsis investigated by quantitative trait loci analysis of the triple testcross design with recombinant inbred lines. Genetics 177, 1839–1850 (2007).

    CAS  PubMed  PubMed Central  Google Scholar 

  151. Shindo, C., Lister, C., Crevillen, P., Nordborg, M. & Dean, C. Variation in the epigenetic silencing of FLC contributes to natural variation in Arabidopsis vernalization response. Genes Dev. 20, 3079–3083 (2006).

    CAS  PubMed  PubMed Central  Google Scholar 

  152. Darvasi, A. & Soller, M. Advanced intercross lines, an experimental population for fine genetic mapping. Genetics 141, 1199–1207 (1995).

    CAS  PubMed  PubMed Central  Google Scholar 

  153. Balasubramanian, S. et al. QTL mapping in new Arabidopsis thaliana advanced intercross-recombinant inbred lines. PLoS ONE 4, e4318 (2009).

    PubMed  PubMed Central  Google Scholar 

  154. Loudet, O., Gaudon, V., Trubuil, A. & Daniel-Vedele, F. Quantitative trait loci controlling root growth and architecture in Arabidopsis thaliana confirmed by heterogeneous inbred family. Theor. Appl. Genet. 110, 742–753 (2005).

    CAS  PubMed  Google Scholar 

Download references

Acknowledgements

The authors give special thanks to M. Horton and B. Brachi for stimulating discussions on placing GWA mapping studies in an ecological context, to O. Loudet for links to automated platforms of phenotyping and to E. Xing for links to the GenAMap platform for structured GWA mapping. We are grateful for funding from the US National Science Foundation (MCB-0603515), the US National Institutes of Health (GM083068) and the French l'Agence Nationale de la Recherche (NT09_473214).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Joy Bergelson.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Related links

Related links

FURTHER INFORMATION

Joy Bergelson's homepage

1001 Genomes Project

Arabidopsis Tiling Array information (Borevitz laboratory)

Arabidopsis Tiling Array information (Nordborg laboratory)

Ecological Genomics of Arabidopsis Development

GenAMap (an integrated analytic and visualization platform for eQTL and GWA study analysis)

Genomic analysis of the genotype–phenotype map

International Plant Phenomics Network

Nature Reviews Genetics series on Genome-wide association studies

Nature Reviews Genetics series on Study designs

RegMap lines

Results of GWA studies for 107 traits

Glossary

Adaptive walk

The evolutionary path taken by a population towards a new phenotypic optimum; it is defined by the number, phenotypic size and temporal sequence of genetic changes.

Life history

Life history traits are closely related to fitness traits, such as number and size of offspring, age at first reproduction, and reproductive lifespan and ageing.

Quantitative trait locus

Genomic region containing one or more genes that affect the variation of a quantitative trait.

Genome-wide association

Whole-genome scans that test the association between the genotypes at each locus and a given phenotype.

Seed dormancy

Mechanism that prevents seed germination, even under conditions that promote germination.

Ionomics

The study of the composition of mineral nutrients and trace elements in living organisms.

Genotype–environment interaction

An effect of a locus that changes in magnitude or direction across environments.

Trade-off

Negative genetic and phenotypic correlation between two traits arising from the need of the individual to allocate resources to alternative functions.

Genetic map

Representation of the position of genetic markers relative to each other, with distances between loci expressed in terms of recombination frequency.

Recombinant inbred lines

Quasi-homozygous lines produced from an initial cross between two individuals, followed by six to eight generations of selfing.

Population structure

Differentiation in allele frequencies among multiple populations.

Linkage disequilibrium

Nonrandom allelic association such that two alleles at two or more loci are more or less frequently associated than predicted by their individual frequencies.

SNP-tiling array

A microarray platform combining SNP genotyping and whole-genome tiling; it contains probes for each allele and each strand of several thousands of SNPs.

Non-singleton SNP

A SNP polymorphism that is present in at least two individuals.

Genetic heterogeneity

The same phenotypic value caused by different mutations at different genes.

Allelic heterogeneity

The same phenotypic value caused by different mutations at the same gene.

Crypsis

Capacity of an organism to avoid detection by other organisms by blending into the environment.

Balancing selection

Evolutionary processes that maintain genetic diversity within a population for longer than expected under neutrality. Processes include heterozygote advantage, frequency-dependent selection and variation of fitness in space and time.

Epigenetic RILs

Quasi-homozygous lines that are almost identical at the genetic level but segregate at the DNA methylation level. EpiRILs are produced from an initial cross between two individuals with few DNA sequence differences but contrasting DNA methylation profiles, followed by six to eight generations of selfing.

Non-parametric methods

Statistical methods, also called distribution free methods, that are not based on a normal distribution of data.

Mixed linear model

Statistical model containing both fixed effects and random effects.

Multi-task regularized regression

Joint association analysis of multiple populations with a multi-population group lasso using L1/L2 regression.

T-DNA

Transferred DNA of the tumour-inducing (Ti) plasmid of some bacterial species into the nuclear DNA genome of the host plant.

Unimutant collection

A collection of 31,033 publically available homozygous T-DNA insertion lines in Arabidopsis thaliana representing 18,506 individual genes; produced by the Salk Institute.

AmiRNA

Artificial microRNAs that target specific genes for silencing.

Cre–lox

Transgenic technology creating isolines with identical genomes, except for the gene of interest. The resulting paired isolines are created by first introducing the gene of interest with a selectable marker into the genome and then excising the gene of interest. Modifications of this approach can be used to create allelic series.

Environmental grain

The scale of temporal and spatial environmental variation that is perceived by an organism.

Phenotypic plasticity

The ability of an organism to develop a phenotypic state, depending on its external and internal environment.

Reaction norm

The set of phenotypes expressed by a genotype under different environmental conditions.

Path analysis

A statistical method that provides estimates of the magnitude and significance of causal relationships between two or more variables.

Pleiotropy

The effect of a gene on more than one phenotypic trait.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Bergelson, J., Roux, F. Towards identifying genes underlying ecologically relevant traits in Arabidopsis thaliana. Nat Rev Genet 11, 867–879 (2010). https://doi.org/10.1038/nrg2896

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/nrg2896

This article is cited by

Search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing