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Jay Shendure, Greg Cooper and colleagues report a framework for annotation of genetic variation, Combined Annotation–Dependent Depletion (CADD), integrating diverse annotations into a single C score. They show that C scores correlate with annotations of functionality, pathogenicity and experimentally measured regulatory effects.
Douglas Higgs and colleagues report a high-throughput approach, called Capture-C, to analyze interactions between cis regulatory elements. Using Capture-C, the authors interrogated hundreds of specific interactions at high resolution in a single experiment.
Gonçalo Abecasis, Dajiang Liu and colleagues report a meta-analysis framework to identify rare variant associations based on gene-level tests and the use of shared summary statistics provided by individual studies. They demonstrate their approach on a meta-analysis of blood lipid levels including 18,699 individuals, drawn from across 7 studies and genotyped with exome arrays.
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.
Mark DePristo and colleagues report an analytical framework to discover and genotype variation using whole exome and genome resequencing data from next-generation sequencing technologies. They apply these methods to low-pass population sequencing data from the 1000 Genomes Project.
Sakari Kauppinen and colleagues report a method for silencing miRNA families in vivo. They find that seed-targeting 8-mer LNA oligonucleotides, termed tiny LNAs, can lead to long-term miRNA silencing in normal tissues and breast tumors in mice.
Francois Spitz and colleagues report GROMIT, a Sleeping Beauty transposon–based system for mapping genetic regulatory architecture in mouse. GROMIT is a regulatory sensor that responds to the activity of nearby enhancers.
Steven McCarroll and colleagues report an analytical framework for characterizing genome deletion polymorphism in populations, applied here to the low coverage genome sequences of 168 individuals from the 1000 Genomes Project. Their population-aware analysis enables structural inference with greater accuracy than previous methods.
Zhiwu Zhang and colleagues report a mixed linear model approach for correcting for population structure and family relatedness in genome-wide association studies.
Eleazar Eskin and colleagues report a variance component model for correcting for sample structure in association studies. The EMMAX program is publicly available and may be used for analysis of genome-wide association study datasets.
Kokubu and colleagues have developed a method for mapping cis-regulatory elements in the mouse using targeted integration of the Sleeping Beauty transposon. This method also gives researchers the ability to generate targeted deletions for testing loss-of-function effects.
Zsuzsanna Izsvák and colleagues report the generation of a hyperactive version of the Sleeping Beauty transposase that supports efficient and stable gene transfer into human CD34+ cells enriched for hematopoietic stem or progenitor cells.