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Yurii Aulchenko and colleagues report a variance components–based method, GRAMMAR-Gamma, for genome-wide association studies including a large number of individuals and genetic markers. They demonstrate, using simulations as well as human and Arabidopsis thaliana data sets, that their method provides unbiased estimates of SNP effect and increases computational efficiency, which may facilitate analysis of human whole-genome resequencing studies.
Magnus Nordborg and colleagues report a parameterized multi-trait mixed model (MTMM) method applied to genome-wide association studies of correlated phenotypes. They test this approach, using both human and Arabidopsis thaliana data sets, and demonstrate how it can be used to identify pleiotropic loci and gene by environment interactions.
Gonçalo Abecasis, Jonathan Marchini and colleagues report a pre-phasing strategy for genotype imputation in GWAS, which they show maintains accuracy while substantially lowering computational costs. Their approach has been implemented in both MACH and IMPUTE 2.0 software.
Matthew Stephens and Xiang Zhou report an efficient exact method for accounting for population stratification and relatedness in genome-wide association analyses. Their method, genome-wide efficient mixed-model association (GEMMA) is implemented in freely available software.
Magnus Nordborg and colleagues report a multi-locus mixed-model method (MLMM) for genome-wide association studies in structured populations. Their simulations show that MLMM offers increased power and a reduced false discovery rate, and applications to both human and Arabidopsis thaliana data sets identify new associations and allelic heterogeneity.
Eleazar Eskin and colleagues report a new method to model the spatial structure of genetic variation, using a spatial ancestry analysis (SPA) approach for modeling of genotypes in two- or three-dimensional space. They apply this approach to a sample of 3,000 European individuals and identify SNPs that show extreme allele frequency gradients.
Eric Schadt and colleagues report a Bayesian method to predict individual SNP genotypes based on RNA expression data. Using simulations and empirical data sets, they show that it is possible to infer a genotypic barcode specific to an individual, although the identification of an individual as a participant in a study is limited by factors such as the availability of large-scale expression quantitative trait loci (eQTLs) and expression data sets.
To take advantage of hybrid vigor, most crop plants are grown with hybrid seeds, which are produced afresh by crossing elite inbred lines. Here, Erik Wijnker and colleagues demonstrate the feasibility of reverse breeding, a method that enables the generation of homozygous parental lines from a hybrid individual in the plant model organism Arabidopsis thaliana. Homozygous parents can be maintained indefinitely, better facilitating future improvements.
Gil McVean and colleagues report algorithms for de novo assembly and genotyping of variants using colored de Bruijn graphs and provide these in a software implementation called Cortex. Their methods can detect and genotype both simple and complex genetic variants in either an individual or a population.
