Meta-analysis of genome-wide association data and large-scale replication identifies additional susceptibility loci for type 2 diabetes

Genome-wide association (GWA) studies have identified multiple loci at which common variants modestly but reproducibly influence risk of type 2 diabetes (T2D). Established associations to common and rare variants explain only a small proportion of the heritability of T2D. As previously published analyses had limited power to identify variants with modest effects, we carried out meta-analysis of three T2D GWA scans comprising 10,128 individuals of European descent and approximately 2.2 million SNPs (directly genotyped and imputed), followed by replication testing in an independent sample with an effective sample size of up to 53,975. We detected at least six previously unknown loci with robust evidence for association, including the JAZF1 (P = 5.0 x 10(-14)), CDC123-CAMK1D (P = 1.2 x 10(-10)), TSPAN8-LGR5 (P = 1.1 x 10(-9)), THADA (P = 1.1 x 10(-9)), ADAMTS9 (P = 1.2 x 10(-8)) and NOTCH2 (P = 4.1 x 10(-8)) gene regions. Our results illustrate the value of large discovery and follow-up samples for gaining further insights into the inherited basis of T2D.     

Estimating coverage and power for genetic association studies using near-complete variation data

Although studies suggest that SNPs derived from HapMap provide promising coverage and power for association studies, the lack of alternative variation datasets limits independent analysis. Using near-complete variation data for 76 genes resequenced in HapMap samples, we find that coverage of common variation by commercial genotyping arrays is substantially lower compared to the HapMap-based estimates. We quantify the power offered by these arrays for a range of disease models.     

Evaluating and improving power in whole-genome association studies using fixed marker sets

Emerging technologies make it possible for the first time to genotype hundreds of thousands of SNPs simultaneously, enabling whole-genome association studies. Using empirical genotype data from the International HapMap Project, we evaluate the extent to which the sets of SNPs contained on three whole-genome genotyping arrays capture common SNPs across the genome, and we find that the majority of common SNPs are well captured by these products either directly or through linkage disequilibrium. We explore analytical strategies that use HapMap data to improve power of association studies conducted with these fixed sets of markers and show that limited inclusion of specific haplotype tests in association analysis can increase the fraction of common variants captured by 25-100%. Finally, we introduce a Bayesian approach to association analysis by weighting the likelihood of each statistical test to reflect the number of putative causal alleles to which it is correlated.     

Genomic buffering mitigates the effects of deleterious mutations in bacteria

The relationship between the number of randomly accumulated mutations in a genome and fitness is a key parameter in evolutionary biology. Mutations may interact such that their combined effect on fitness is additive (no epistasis), reinforced (synergistic epistasis) or mitigated (antagonistic epistasis). We measured the decrease in fitness caused by increasing mutation number in the bacterium Salmonella typhimurium using a regulated, error-prone DNA polymerase (polymerase IV, DinB). As mutations accumulated, fitness costs increased at a diminishing rate. This suggests that random mutations interact such that their combined effect on fitness is mitigated and that the genome is buffered against the fitness reduction caused by accumulated mutations. Levels of the heat shock chaperones DnaK and GroEL increased in lineages that had accumulated many mutations, and experimental overproduction of GroEL further increased the fitness of lineages containing deleterious mutations. These findings suggest that overexpression of chaperones contributes to antagonistic epistasis.     

Genomic and functional evolution of the Drosophila melanogaster sperm proteome

In addition to delivering a haploid genome to the egg, sperm have additional critical functions, including egg activation, origination of the zygote centrosome and delivery of paternal factors. Despite this, existing knowledge of the molecular basis of sperm form and function is limited. We used whole-sperm mass spectrometry to identify 381 proteins of the Drosophila melanogaster sperm proteome (DmSP). This approach identified mitochondrial, metabolic and cytoskeletal proteins, in addition to several new functional categories. We also observed nonrandom genomic clustering of sperm genes and underrepresentation on the X chromosome. Identification of widespread functional constraint on the proteome indicates that sexual selection has had a limited role in the overall evolution of D. melanogaster sperm. The relevance of the DmSP to the study of mammalian sperm function and fertilization mechanisms is demonstrated by the identification of substantial homology between the DmSP and proteins of the mouse axoneme accessory structure.     

Genome-wide association study of leaf architecture in the maize nested association mapping population

US maize yield has increased eight-fold in the past 80 years, with half of the gain attributed to selection by breeders. During this time, changes in maize leaf angle and size have altered plant architecture, allowing more efficient light capture as planting density has increased. Through a genome-wide association study (GWAS) of the maize nested association mapping panel, we determined the genetic basis of important leaf architecture traits and identified some of the key genes. Overall, we demonstrate that the genetic architecture of the leaf traits is dominated by small effects, with little epistasis, environmental interaction or pleiotropy. In particular, GWAS results show that variations at the liguleless genes have contributed to more upright leaves. These results demonstrate that the use of GWAS with specially designed mapping populations is effective in uncovering the basis of key agronomic traits.     

A framework for variation discovery and genotyping using next-generation DNA sequencing data

Recent advances in sequencing technology make it possible to comprehensively catalog genetic variation in population samples, creating a foundation for understanding human disease, ancestry and evolution. The amounts of raw data produced are prodigious, and many computational steps are required to translate this output into high-quality variant calls. We present a unified analytic framework to discover and genotype variation among multiple samples simultaneously that achieves sensitive and specific results across five sequencing technologies and three distinct, canonical experimental designs. Our process includes (i) initial read mapping; (ii) local realignment around indels; (iii) base quality score recalibration; (iv) SNP discovery and genotyping to find all potential variants; and (v) machine learning to separate true segregating variation from machine artifacts common to next-generation sequencing technologies. We here discuss the application of these tools, instantiated in the Genome Analysis Toolkit, to deep whole-genome, whole-exome capture and multi-sample low-pass (～4×) 1000 Genomes Project datasets.     

Genomic and metabolic prediction of complex heterotic traits in hybrid maize

Maize is both an exciting model organism in plant genetics and also the most important crop worldwide for food, animal feed and bioenergy production. Recent genome-wide association and metabolic profiling studies aimed to resolve quantitative traits to their causal genetic loci and key metabolic regulators. Here we present a complementary approach that exploits large-scale genomic and metabolic information to predict complex, highly polygenic traits in hybrid testcrosses. We crossed 285 diverse Dent inbred lines from worldwide sources with two testers and predicted their combining abilities for seven biomass- and bioenergy-related traits using 56,110 SNPs and 130 metabolites. Whole-genome and metabolic prediction models were built by fitting effects for all SNPs or metabolites. Prediction accuracies ranged from 0.72 to 0.81 for SNPs and from 0.60 to 0.80 for metabolites, allowing a reliable screening of large collections of diverse inbred lines for their potential to create superior hybrids.     

Genomic structure, evolutionary conservation and aniridia mutations in the human PAX6 gene.

Aniridia is a semidominant disorder in which development of the iris, lens, cornea and retina is disturbed. The mouse mutation Small eye (Sey), which has been proposed as a model for aniridia, results from defects in Pax-6, a gene containing paired-box and homeobox motifs that is specifically expressed in the developing eye and brain. To test the role of PAX6 in aniridia, we isolated human cDNA clones and determined the intron-exon structure of this gene. PAX6 spans 22 kilobases and is divided into 14 exons. Analysis of DNA from 10 unrelated aniridia patients revealed intragenic mutations in three familial and one sporadic case. These findings indicate that the human aniridia and murine Small eye phenotypes arise from homologous defects in PAX6.     

Efficiency and power in genetic association studies

We investigated selection and analysis of tag SNPs for genome-wide association studies by specifically examining the relationship between investment in genotyping and statistical power. Do pairwise or multimarker methods maximize efficiency and power? To what extent is power compromised when tags are selected from an incomplete resource such as HapMap? We addressed these questions using genotype data from the HapMap ENCODE project, association studies simulated under a realistic disease model, and empirical correction for multiple hypothesis testing. We demonstrate a haplotype-based tagging method that uniformly outperforms single-marker tests and methods for prioritization that markedly increase tagging efficiency. Examining all observed haplotypes for association, rather than just those that are proxies for known SNPs, increases power to detect rare causal alleles, at the cost of reduced power to detect common causal alleles. Power is robust to the completeness of the reference panel from which tags are selected. These findings have implications for prioritizing tag SNPs and interpreting association studies.     

Consent and privacy in pharmacogenetic testing.

The clinical use of pharmacogenetic drugs will require that a sample of a patient's DNA be tested before a drug is prescribed. Although pharmacogenetic tests pose fewer risks than genetic tests for disease mutations, they might still reveal personal information that could be used adversely to a patient's interests. Informed consent and privacy of pharmacogenetic test results may be essential in most clinical uses of pharmacogenetic drugs.     

Genome-wide association study of quantitative resistance to southern leaf blight in the maize nested association mapping population

Nested association mapping (NAM) offers power to resolve complex, quantitative traits to their causal loci. The maize NAM population, consisting of 5,000 recombinant inbred lines (RILs) from 25 families representing the global diversity of maize, was evaluated for resistance to southern leaf blight (SLB) disease. Joint-linkage analysis identified 32 quantitative trait loci (QTLs) with predominantly small, additive effects on SLB resistance. Genome-wide association tests of maize HapMap SNPs were conducted by imputing founder SNP genotypes onto the NAM RILs. SNPs both within and outside of QTL intervals were associated with variation for SLB resistance. Many of these SNPs were within or near sequences homologous to genes previously shown to be involved in plant disease resistance. Limited linkage disequilibrium was observed around some SNPs associated with SLB resistance, indicating that the maize NAM population enables high-resolution mapping of some genome regions.     

Genetic testing and quality control in diagnostic laboratories

To evaluate the quality of genetic testing for cystic fibrosis, 136, 145 and 159 laboratories participated in a European study in 1996, 1997 and 1998, respectively. We sent six purified DNA samples carrying the more common CFTR mutations with the request to test them using routine protocols. A panel of experts reviewed the results together with the raw data.     

Efficient and accurate replication in the presence of 7,8-dihydro-8-oxoguanine by DNA polymerase eta

Oxidative damage to DNA has been proposed to have a role in cancer and ageing. Oxygen-free radicals formed during normal aerobic cellular metabolism attack bases in DNA, and 7, 8-dihydro-8-oxoguanine (8-oxoG) is one of the adducts formed. Eukaryotic replicative DNA polymerases replicate DNA containing 8-oxoG by inserting an adenine opposite the lesion; consequently, 8-oxoG is highly mutagenic and causes G:C to T:A transversions. Genetic studies in yeast have indicated a role for mismatch repair in minimizing the incidence of these mutations. In Saccharomyces cerevisiae, deletion of OGG1, encoding a DNA glycosylase that functions in the removal of 8-oxoG when paired with C, causes an increase in the rate of G:C to T:A transversions. The ogg1Delta msh2Delta double mutant displays a higher rate of CAN1S to can1r forward mutations than the ogg1Delta or msh2Delta single mutants, and this enhanced mutagenesis is primarily due to G:C to T:A transversions. The gene RAD30 of S. cerevisiae encodes a DNA polymerase, Poleta, that efficiently replicates DNA containing a cis-syn thymine-thymine (T-T) dimer by inserting two adenines across from the dimer. In humans, mutations in the yeast RAD30 counterpart, POLH, cause the variant form of xeroderma pigmentosum (XP-V), and XP-V individuals suffer from a high incidence of sunlight-induced skin cancers. Here we show that yeast and human POLeta replicate DNA containing 8-oxoG efficiently and accurately by inserting a cytosine across from the lesion and by proficiently extending from this base pair. Consistent with these biochemical studies, a synergistic increase in the rate of spontaneous mutations occurs in the absence of POLeta in the yeast ogg1Delta mutant. Our results suggest an additional role for Poleta in the prevention of internal cancers in humans that would otherwise result from the mutagenic replication of 8-oxoG in DNA.