Details regarding how adaptation proceeds remain elusive. From a theoretical perspective, several ques- tions have been addressed 1–6 . How many genes are expected to be involved in a specific adaptation? Does the origin of adaptation (new mutations versus stand- ing genetic variation) affect the adaptive walk to a new phenotypic optimum? What is the distribution of phe- notypic effects that are fixed during an adaptive walk? Unfortunately, as in other long-standing debates in evolutionary ecology, arguments can flourish in the absence of data. To fill the gap between theory and data, an important goal is to identify the genetic basis of adaptive trait variation. In plants, the identification of genes that underlie phenotypic variation can have enormous practical implications by providing a means to increase crop yield and quality in an agricultural context 7 . At the same time, the identification of ecologically important genes should help in predicting the evolutionary trajec- tories of plant populations 3,8–10 . Arabidopsis thaliana is a convenient species for these pursuits because it has a worldwide distribution and, as such, encounters diverse ecological conditions 9,11–14 , leading to adaptive varia- tion for many morphology, life history and other fitness- related traits 15 . During the past two decades, molecular tools have been developed to assist in the mapping of quantitative trait loci (QTLs) in experimental popula- tions, but these tools remain laborious 16 . Recently, the first study of genome-wide association (GWA) mapping in plants was reported 17 , bringing a breath of fresh air to the area of gene discovery. The high resolution con- ferred by GWA mapping facilitated mapping of the genetic bases of 107 diverse phenotypes, including flow- ering time, pathogen resistance, seed dormancy, ionomics and vegetative growth. Long considered the privilege of human mapping studies, GWA mapping has now emerged as a powerful alternative approach to finely dissect the intraspecific genetic variation that underlies phenotypic variation in plants 18–20 . Here we describe the connections among long- established strategies (such as traditional linkage map- ping), recently developed approaches (such as GWA mapping) and upcoming methods (such as nested association mapping (NAM)) for finely mapping QTLs underlying natural variation. We review several pow- erful GWA mapping approaches and analytical meth- ods that have been developed, as well as the available genotypic and phenotypic resources that are linked to the approaches. Because genetic variation is exposed to natural selection in contrasting ecological habitats, we emphasize the importance of ecological context. First, the spatial and temporal scale at which selection acts will determine the appropriate populations for GWA mapping 21 . Second, the cues perceived by a plant are far more complex, and not well captured, by simple growth- chamber conditions. This highlights the need to meas- ure phenotypes in realistic conditions 22,23 . Third, the heterogeneity of the habitats encountered by A. thaliana suggests that experiments designed to phenotype plants in multiple locations will provide more robust results than *Department of Ecology and Evolution, University of Chicago, 1101 E. 57 th Street, Chicago, Illinois 60637, USA. ‡ Laboratoire Génétique et Evolution des Populations Végétales, FRE CNRS 3268, Université des Sciences et Technologies de Lille – Lille 1, F‑59655 Villeneuve d’Ascq cedex, France. Correspondence to J.B. e‑mail: jbergels@uchicago.edu doi:10.1038/nrg2896 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. Towards identifying genes underlying ecologically relevant traits in Arabidopsis thaliana Joy Bergelson* and Fabrice Roux ‡ 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. GENOME-WIDE ASSOCIATION STUDIES REVIEWS NATURE REVIEWS | GENETICS VOLUME 11 | DECEMBER 2010 | 867 © 20 Macmillan Publishers Limited. All rights reserved 10