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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 attack (1). 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 invasion (2-5). 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 environment (6-11). 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., A survey of A. thaliana accessions collected from the wild revealed extensive environment-dependent variation for leaf initiation rate (Supplementary Table 1). One of the strains, Est-1, which produced leaves more [...]

Although pioneered by human geneticists as a potential solution to the challenging problem of finding the genetic basis of common human diseases (1,2), genome-wide association (GWA) studies have, owing to advances in genotyping and sequencing technology, become an obvious general approach for studying the genetics of natural variation and traits of agricultural importance. They are particularly useful when inbred lines are available, because once these lines have been genotyped they can be phenotyped multiple times, making it possible (as well as extremely cost effective) to study many different traits in many different environments, while replicating the phenotypic measurements to reduce environmental noise. Here we demonstrate the power of this approach by carrying out a GWA study of (107 phenotypes in Arabidopsis thaliana, a widely distributed, predominantly self-fertilizing model plant known to harbour considerable genetic variation for many adaptively important traits (3). Our results are dramatically different from those of human GWA studies, in that we identify many common alleles of major effect, but they are also, in many cases, harder to interpret because confounding by complex genetics and population structure make it difficult to distinguish true associations from false. However, a-priori candidates are significantly over-represented among these associations as well, making many of them excellent candidates for follow-up experiments. Our study demonstrates the feasibility of GWA studies in A. thaliana and suggests that the approach will be appropriate for many other organisms., The genotyped sample (Supplementary Table 1) includes a core set of 95 lines (4) for which a wide variety of phenotypes were available, plus a second set of 96 lines [...]

Natural variation presents one of the fundamental challenges of modern biology. Soon, the genome sequences of thousands of individuals will be known for each of several species. But how does the genotypic variation that will be observed among these individuals translate into phenotypic variation? Plants are in many ways ideal for addressing this question, and resources that are unmatched, except in humans, have now been developed., When it comes to dissecting complex traits, genetic studies of plants have always been at the forefront. Work with cereals provided the first demonstrations that segregation at multiple loci could [...]

We present an exact forward-in-time algorithm that can efficiently simulate the evolution of a finite population under the Wright-Fisher model. We used simulations based on this algorithm to verify the accuracy of the ancestral recombination graph approximation by comparing it to the exact Wright-Fisher scenario. We find that the recombination graph is generally a very good approximation for models with complete outcrossing, whereas, for models with self-fertilization, the approximation becomes slightly inexact for some combinations of selfing and recombination parameters.

The molecular basis for variation in vernalization in Arabidopsis natural accessions adapted to different climates is investigated. The results have shown that the variation in epigenetic silencing of the floral repressor gene FLOWERING LOCUS C (FLC) have contributed to Arabidopsis adaptation.

We describe a novel method for jointly estimating crossing-over and gene-conversion rates from population genetic data using summary statistics. The performance of our method was tested on simulated data sets and compared with the composite-likelihood method of R. R. Hudson. For several realistic parameter values, the new method performed similarly to the composite-likelihood approach for estimating crossing-over rates and better when estimating gene-conversion rates. We used our method to analyze a human data set recently genotyped by Perlegen Sciences.

In linkage disequilibrium mapping of genetic variants causally associated with phenotypes, spurious associations can potentially be generated by any of a variety of types of population structure. However, mathematical theory of the production of spurious associations has largely been restricted to population structure models that involve the sampling of individuals from a collection of discrete subpopulations. Here, we introduce a general model of spurious association in structured populations, appropriate whether the population structure involves discrete groups, admixture among such groups, or continuous variation across space. Under the assumptions of the model, we find that a single common principle-applicable to both the discrete and admixed settings as well as to spatial populations--gives a necessary and sufficient condition for the occurrence of spurious associations. Using a mathematical connection between the discrete and admixed cases, we show that in admixed populations, spurious associations are less severe than in corresponding mixtures of discrete subpopulations, especially when the variance of admixture across individuals is small. This observation, together with the results of simulations that examine the relative influences of various model parameters, has important implications for the design and analysis of genetic association studies in structured populations.

We develop methods for exploiting 'single-feature polymorphism' data, generated by hybridizing genomic DNA to oligonucleotide expression arrays. Our methods enable the use of such data, which can be regarded as very high density, but imperfect, polymorphism data, for genomewide association or linkage disequilibrium mapping. We use a simulation-based power study to conclude that our methods should have good power for organisms like Arabidopsis thaliana, in which linkage disequilibrium is extensive, the reason being that the noisiness of single-feature polymorphism data is more than compensated for by their great number. Finally, we show how power depends on the accuracy with which single-feature polymorphisms are called.

In this article we infer the rates of gene conversion and crossing over in Arabidopsis thaliana from population genetic data. Our data set is a genomewide survey consisting of 1347 fragments of length 600 bp sequenced in 96 accessions. It has several orders of magnitude more markers than any previous nonhuman study. This allows for more accurate inference as well as a detailed comparison between theoretical expectations and observations. Our methodology is specifically set to account for deviations such as recurrent mutations or a skewed frequency spectrum. We found that even if some components of the model clearly do not fit, the pattern of LD conforms to theoretical expectations quite well. The ratio of gene conversion to crossing over is estimated to be around one. We also find evidence for fine-scale variations of the crossing-over rate.

Balancing selection may result in trans-specific polymorphism: the maintenance of allelic classes that transcend species boundaries by virtue of being more ancient than the species themselves. At the selected site, gene genealogies are expected not to reflect the species tree. Because of linkage, the same will be true for part of the surrounding chromosomal region. Here we obtain various approximations for the distribution of the length of this region and discuss the practical implications of our results. Our main finding is that the trans-specific region surrounding a single-locus balanced polymorphism is expected to be quite short, probably too short to be readily detectable. Thus lack of obvious trans-specific polymorphism should not be taken as evidence against balancing selection. When trans-specific polymorphism is obvious, on the other hand, it may be reasonable to argue that selection must be acting on multiple sites or that recombination is suppressed in the surrounding region.

The feasibility of using linkage disequilbrium (LD) to fine-map loci underlying natural variation in Arabidopsis thaliana was investigated by looking for associations between flowering time and marker polymorphism in the genomic regions containing two candidate genes, FRI and FLC, both of which are known to contribute to natural variation in flowering. A sample of 196 accessions was used, and polymorphism was assessed by sequencing a total of 17 roughly 500-bp fragments. Using a novel Bayesian algorithm based on haplotype similarity, we demonstrate that LD could have been used to fine-map the FRI gene to a roughly 30-kb region and to identify two common loss-of-function alleles. Interestingly, because of genetic heterogeneity, simple single-marker associations would not have been able to map FRI with nearly the same precision. No clear evidence for previously unknown alleles at either locus was found, but the effect of population structure in causing false positives was evident.

Various expressions related to the length of a conserved haplotype around a polymorphism of known frequency are derived. We obtain exact expressions for the probability that no recombination has occurred in a sample or subsample. We obtain an approximation for the probability that no recombination that could give rise to a detectable recombination event (through the four-gamete test) has occurred. The probabilities can be used to obtain approximate distributions for the length of variously defined haplotypes around a polymorphic site. The implications of our results for data analysis, and in particular for detecting selection, are discussed.