Natural allelic variation underlying a major fitness trade-off in Arabidopsis thaliana

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Plants can defend themselves against a wide array of enemies, from microbes to large animals, yet there is great variability in the effectiveness of such defences, both within and between species. Some of this variation can be explained by conflicting pressures from pathogens with different modes of attack1. A second explanation comes from an evolutionary ‘tug of war’, in which pathogens adapt to evade detection, until the plant has evolved new recognition capabilities for pathogen invasion2, 3, 4, 5. If selection is, however, sufficiently strong, susceptible hosts should remain rare. That this is not the case is best explained by costs incurred from constitutive defences in a pest-free environment6, 7, 8, 9, 10, 11. Using a combination of forward genetics and genome-wide association analyses, we demonstrate that allelic diversity at a single locus, ACCELERATED CELL DEATH 6 (ACD6)12, 13, underpins marked pleiotropic differences in both vegetative growth and resistance to microbial infection and herbivory among natural Arabidopsis thaliana strains. A hyperactive ACD6 allele, compared to the reference allele, strongly enhances resistance to a broad range of pathogens from different phyla, but at the same time slows the production of new leaves and greatly reduces the biomass of mature leaves. This allele segregates at intermediate frequency both throughout the worldwide range of A. thaliana and within local populations, consistent with this allele providing substantial fitness benefits despite its marked impact on growth.

At a glance


  1. Identification of a natural ACD6 allele affecting growth and defence traits.
    Figure 1: Identification of a natural ACD6 allele affecting growth and defence traits.

    a, Top: rosettes of 6-week-old plants. Bottom: close-up of twelfth leaf, stained with Trypan blue for dead cells. gACD6.Est is an acd6-2 mutant in Col-0 (which is morphologically normal; Supplementary Fig. 3) transformed with an Est-1 genomic fragment. Scale bars: 1cm (top); 1mm (bottom). b, Leaf initiation rates. c, QTL maps. The dashed black line indicates significance threshold; ticks indicate positions of genetic markers14. LOD, logarithm of odds. d, PR1 expression in the sixth leaf (two biological replicates each), normalized to those in 12-day-old Est-1 plants. e, PR1 expression in different genotypes. f, Leaf initiation rates. g, SA content in the sixth leaf of 35-day-old plants. Only wild-type Est-1 was significantly different from any of the other lines (P<0.005). The 35S::amiR-ACD6 construct had no effect on SA levels in Col-0. FW, fresh weight. Standard errors are indicated in panels b, eg.

  2. Effects of a natural ACD6 allele on leaf biomass, pathogen susceptibility and metabolite content.
    Figure 2: Effects of a natural ACD6 allele on leaf biomass, pathogen susceptibility and metabolite content.

    a, Leaf biomass. The difference between wild-type and transgenic lines was significant for all accessions but Col-0 (P<0.001). b, G. orontii T1 conidiophores on 4-week-old plants, 5 days post inoculation (d.p.i.). c, H. arabidopsidis Noco2 sporangiophores on 2-week-old seedlings (5d.p.i.). cot., cotyledon. d, P. syringae DC3000 growth. 35S::amiR-ACD6 did not affect susceptibility of Col-0. e, Camalexin and jasmonate concentrations. The difference between Est-1 and the other genotypes was significant (P<0.005). Standard errors are indicated in panels a, b, d, e.

  3. Effects of a natural ACD6 allele on pathogen susceptibility.
    Figure 3: Effects of a natural ACD6 allele on pathogen susceptibility.

    a, Infection of 4-week-old plants by G. orontii T1 (5d.p.i.). Arrows indicate fungal growth. b, Trypan blue staining of inoculated leaves. Dead plant cells (dc), hyphae (hy) and mature conidiophores (cp) are indicated. c, Infection of 6-week-old plants with G. cichoracearum UCSC1 (10d.p.i.). Note the increasing severity of infection symptoms from left to right. d, Five-week-old plants inoculated with H. arabidopsidis Noco2. Trypan blue staining of the fourth leaf (7d.p.i.) is shown. Hyphal growth (hy), which was seldom observed in Est-1, as well as oosporangia (os) were common in 35S::amiR-ACD6 Est-1 plants. See Supplementary Fig. 7 for adult leaves. In Col-0, many sporangiophores (sp) were seen. For both powdery and downy mildews, pathogen susceptibility and ACD6 expression levels in 35S::amiR-ACD6 lines were correlated (see Supplementary Fig. 2a). Scale bars: 1cm in a and c; 1mm in b and d.

  4. ACD6 sequence diversity in Arabidopsis.
    Figure 4: ACD6 sequence diversity in Arabidopsis.

    a, Hierarchical clustering of ACD6 alleles. Col-0 and Est-1 are indicated with arrows, and Est-1-like sequences are highlighted. Yellow indicates mild, orange intermediate and red severe late-onset necrosis. KZ-10-like alleles are grey. b, Pair-wise identity of ACD6 alleles. c, Whole-genome scan of 216,130 SNPs for association with necrosis across 96 accessions shown in a24. d, Genomic region containing 9 of 15 SNPs with lowest P-values. e, Polymorphism and divergence levels at ACD6 (see also Supplementary Figs 8 and 10 and Supplementary Table 6). Blue lines indicate non-synonymous SNPs shared among Est-1-like alleles, and Fab-2 and Fab-4 (Supplementary Fig. 5). The two causal SNPs (see f) are indicated by asterisks, as is the acd6-1 mutation. dN, rate of non-synonymous substitutions; dS, rate of synonymous substitutions. f, Six-week-old acd6-2 plants transformed with modified genomic clones of ACD6, in which two codons were swapped between Est-1 and Col-0. See also Supplementary Fig. 6. Compare to Fig. 1a and Supplementary Fig. 3a for unmutated versions. Scale bars: 1cm.

  5. Correlation between late-onset necrosis, growth and defence traits.
    Figure 5: Correlation between late-onset necrosis, growth and defence traits.

    a, Late-onset necrosis in accessions with an Est-1-like ACD6 allele is suppressed by 35S::amiR-ACD6, or by nahG-mediated SA depletion. See Supplementary Fig. 9 for additional accessions. Scale bars: 2cm for rosettes; 1mm for micrographs. b, Correlation between late-onset necrosis and different traits across 96 accessions used for genome-wide association studies24. Lesioning scores reflect the range of symptoms indicated in Fig. 4a.

Accession codes

Primary accessions


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Author information

  1. These authors contributed equally to this work.

    • Marco Todesco &
    • Sureshkumar Balasubramanian


  1. Department of Molecular Biology, Max Planck Institute for Developmental Biology, 72076 Tübingen, Germany

    • Marco Todesco,
    • Sureshkumar Balasubramanian,
    • Sridevi Sureshkumar,
    • Christa Lanz,
    • Roosa A. E. Laitinen &
    • Detlef Weigel
  2. Molecular and Computational Biology, University of Southern California, Los Angeles, California 90089, USA

    • Tina T. Hu,
    • Yu Huang &
    • Magnus Nordborg
  3. Department of Biological Sciences, University of Pittsburgh, Pittsburgh, Pennsylvania 15238, USA

    • M. Brian Traw
  4. Department of Ecology and Evolution, University of Chicago, Chicago, Illinois 60637, USA

    • Matthew Horton,
    • Justin O. Borevitz &
    • Joy Bergelson
  5. Department of Biology, University of North Carolina, Chapel Hill, North Carolina 27599, USA

    • Petra Epple &
    • Jeffery L. Dangl
  6. The Sainsbury Laboratory, John Innes Centre, Colney, Norwich NR4 7UH, UK

    • Christine Kuhns &
    • Volker Lipka
  7. Albrecht von Haller Institute for Plant Sciences, Georg August University Göttingen, 37073 Göttingen, Germany

    • Christine Kuhns &
    • Volker Lipka
  8. Plant Biology Laboratory, The Salk Institute for Biological Studies, La Jolla, California 92037, USA

    • Christopher Schwartz &
    • Joanne Chory
  9. Department of Biochemistry, University of Wisconsin, Madison, Wisconsin 53706, USA

    • Christopher Schwartz
  10. Howard Hughes Medical Institute, The Salk Institute for Biological Studies, La Jolla, California 92037, USA

    • Joanne Chory
  11. Department of Microbiology and Immunology, Curriculum in Genetics and Carolina Center for Genome Sciences, University of North Carolina, Chapel Hill, North Carolina 27599, USA

    • Jeffery L. Dangl
  12. Gregor Mendel Institute, 1030 Vienna, Austria

    • Magnus Nordborg
  13. Present addresses: School of Biological Sciences, University of Queensland, St Lucia, Queensland 4072, Australia (S.B., S.S.); Lewis-Sigler Institute, Princeton University, Princeton, New Jersey 08544, USA (T.T.H.).

    • Sureshkumar Balasubramanian,
    • Tina T. Hu &
    • Sridevi Sureshkumar


M.T., S.B., J.C., V.L., J.O.B., J.L.D., J.B., M.N. and D.W. conceived the study; M.T., S.B., M.B.T., M.H., P.E., C.K., S.S., C.S., C.L. and R.A.E.L. performed the experiments; M.T., S.B., T.T.H., M.B.T., Y.H., J.B., M.N. and D.W. analysed the data; and M.T., S.B. and D.W. wrote the paper with contributions from all authors.

Competing financial interests

The authors declare no competing financial interests.

Corresponding author

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DNA sequences have been deposited in GenBank under accession numbers HM053468 and HM053469 and HM214805 to HM214897.

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  1. Supplementary Information (1.7M)

    This file contains Supplementary Methods, References, Supplementary Tables 1-9 and Supplementary Figures 1-13 with legends.

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