Grain weight, an essential yield component, is under strong genetic control and markedly influenced by the environment. Here, by genome-wide association analysis with a panel of 94 elite common wheat varieties, 37 loci were found significantly associated with thousand-grain weight (TGW) in one or more environments differing in water and fertiliser levels. Five loci were stably associated with T...

As genetic model systems, fish have played a key role in our understanding of a wide range of biological processes, including vertebrate pigmentation. In this review, we focus on one aspect of pigmentation, skin pigmentation, which has been of momentous importance in human history. Two fish models, medaka and zebrafish, played important roles in demystifying skin color and, by extension, the co...

The identification of genetic factors that confer risk for the common forms of migraine by GWAS has given insight into the genetic underpinning of migraine pathophysiology. Still, the interpretation of the findings of GWAS is not straightforward. Various strategies are being tested to investigate which pathophysiological mechanisms are involved, how they can be studied, and what this means for ...

We present an approach for genome-wide association analysis with improved power on the Wellcome Trust data consisting of seven common phenotypes and shared controls. We achieved improved power by expanding the control set to include other disease cohorts, multiple races, and closely related individuals. Within this setting, we conducted exhaustive univariate and epistatic interaction associatio...

BACKGROUND Obtaining informed consent for participation in genomic research in low-income settings presents specific ethical issues requiring attention. These include the challenges that arise when providing information about unfamiliar and technical research methods, the implications of complicated infrastructure and data sharing requirements, and the potential consequences of future research ...

As investigators plan the next round of genome-wide association studies (GWAS), cohorts of more than 100 000 individuals are being proposed as the solution to the “missing heritability” from first-generation studies.1–6 Although such studies will undoubtedly reveal many additional common alleles contributing to human disease, consideration of the intrinsic design of GWAS, our knowledge of the g...

Genome wide association studies (GWAS) have been very successful over the last decade at identifying genetic variants associated with disease phenotypes. However, interpretation of the results obtained can be challenging. Incorporation of further relevant biological measurements (e.g. 'omics' data) measured in the same individuals for whom we have genotype and phenotype data may help us to lear...

Population structure can be a source of both false-positive and false-negative findings in a genome-wide association study. This article proposes an approach that helps to reduce the false-positives. It consists of homogenizing the diseased/healthy phenotype ratio across the cohort, by decreasing the statistical weight of selected individuals. After homogenization, the cohort is statistically h...

Intensive efforts have been underway to identify common genetic factors that influence health and disease including cancer using genomewide association studies (GWAS). Our experiences have shown that while it is more advantageous to have large detailed data sets, the amount of information generated by GWAS also present major challenges for statistical analyses. While prospects for the oncoming ...

This article compares baseline, average, and longitudinal data analysis methods for identifying genetic variants in genome-wide association study using the Genetic Analysis Workshop 18 data. We apply methods that include (a) linear mixed models with baseline measures, (b) random intercept linear mixed models with mean measures outcome, and (c) random intercept linear mixed models with longitudi...