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.     

Genomic segmental polymorphisms in inbred mouse strains

By analyzing genomic copy-number differences using high-resolution mouse whole-genome BAC arrays, we uncover substantial differences in regional DNA content between inbred strains of mice. The identification of these apparently common segmental polymorphisms suggests that these differences can contribute to genetic variability and pathologic susceptibility.     

Fine points in mapping autoimmunity

An efficient way to design genotyping arrays for fine mapping is to group phenotypes with common biology. The first application of the Immunochip to celiac disease provides an insightful view of what this strategy can achieve.     

Extremely low-coverage sequencing and imputation increases power for genome-wide association studies

Genome-wide association studies (GWAS) have proven to be a powerful method to identify common genetic variants contributing to susceptibility to common diseases. Here, we show that extremely low-coverage sequencing (0.1-0.5×) captures almost as much of the common (>5%) and low-frequency (1-5%) variation across the genome as SNP arrays. As an empirical demonstration, we show that genome-wide SNP genotypes can be inferred at a mean r(2) of 0.71 using off-target data (0.24× average coverage) in a whole-exome study of 909 samples. Using both simulated and real exome-sequencing data sets, we show that association statistics obtained using extremely low-coverage sequencing data attain similar P values at known associated variants as data from genotyping arrays, without an excess of false positives. Within the context of reductions in sample preparation and sequencing costs, funds invested in extremely low-coverage sequencing can yield several times the effective sample size of GWAS based on SNP array data and a commensurate increase in statistical power.     

Genome-wide mapping with biallelic markers in Arabidopsis thaliana.

Single-nucleotide polymorphisms, as well as small insertions and deletions (here referred to collectively as simple nucleotide polymorphisms, or SNPs), comprise the largest set of sequence variants in most organisms. Positional cloning based on SNPs may accelerate the identification of human disease traits and a range of biologically informative mutations. The recent application of high-density oligonucleotide arrays to allele identification has made it feasible to genotype thousands of biallelic SNPs in a single experiment. It has yet to be established, however, whether SNP detection using oligonucleotide arrays can be used to accelerate the mapping of traits in diploid genomes. The cruciferous weed Arabidopsis thaliana is an attractive model system for the construction and use of biallelic SNP maps. Although important biological processes ranging from fertilization and cell fate determination to disease resistance have been modelled in A. thaliana, identifying mutations in this organism has been impeded by the lack of a high-density genetic map consisting of easily genotyped DNA markers. We report here the construction of a biallelic genetic map in A. thaliana with a resolution of 3.5 cM and its use in mapping Eds16, a gene involved in the defence response to the fungal pathogen Erysiphe orontii. Mapping of this trait involved the high-throughput generation of meiotic maps of F2 individuals using high-density oligonucleotide probe array-based genotyping. We developed a software package called InterMap and used it to automatically delimit Eds16 to a 7-cM interval on chromosome 1. These results are the first demonstration of biallelic mapping in diploid genomes and establish means for generalizing SNP-based maps to virtually any genetic organism.     

Genomic profiling of drug sensitivities via induced haploinsufficiency

Lowering the dosage of a single gene from two copies to one copy in diploid yeast results in a heterozygote that is sensitized to any drug that acts on the product of this gene. This haploinsufficient phenotype thereby identifies the gene product of the heterozygous locus as the likely drug target. We exploited this finding in a genomic approach to drug-target identification. Genome sequence information was used to generate molecularly tagged heterozygous yeast strains that were pooled, grown competitively in drug and analysed for drug sensitivity using high-density oligonucleotide arrays. Individual heterozygous strain analysis verified six known drug targets. Parallel analysis identified the known target and two hypersensitive loci in a mixed culture of 233 strains in the presence of the drug tunicamycin. Our discovery that both drug target and hypersensitive loci exhibit drug-induced haploinsufficiency may have important consequences in pharmacogenomics and variable drug toxicity observed in human populations.     

Mapping autism risk loci using genetic linkage and chromosomal rearrangements

Autism spectrum disorders (ASDs) are common, heritable neurodevelopmental conditions. The genetic architecture of ASDs is complex, requiring large samples to overcome heterogeneity. Here we broaden coverage and sample size relative to other studies of ASDs by using Affymetrix 10K SNP arrays and 1,181 [corrected] families with at least two affected individuals, performing the largest linkage scan to date while also analyzing copy number variation in these families. Linkage and copy number variation analyses implicate chromosome 11p12-p13 and neurexins, respectively, among other candidate loci. Neurexins team with previously implicated neuroligins for glutamatergic synaptogenesis, highlighting glutamate-related genes as promising candidates for contributing to ASDs.     

Epigenome analyses using BAC microarrays identify evolutionary conservation of tissue-specific methylation of SHANK3

CpG islands are present in one-half of all human and mouse genes and typically overlap with promoters or exons. We developed a method for high-resolution analysis of the methylation status of CpG islands genome-wide, using arrays of BAC clones and the methylation-sensitive restriction enzyme NotI. Here we demonstrate the accuracy and specificity of the method. By computationally mapping all NotI sites, methylation events can be defined with single-nucleotide precision throughout the genome. We also demonstrate the unique expandability of the array method using a different methylation-sensitive restriction enzyme, BssHII. We identified and validated new CpG island loci that are methylated in a tissue-specific manner in normal human tissues. The methylation status of the CpG islands is associated with gene expression for several genes, including SHANK3, which encodes a structural protein in neuronal postsynaptic densities. Defects in SHANK3 seem to underlie human 22q13 deletion syndrome. Furthermore, these patterns for SHANK3 are conserved in mice and rats.     

Discovery of previously unidentified genomic disorders from the duplication architecture of the human genome

Genomic disorders are characterized by the presence of flanking segmental duplications that predispose these regions to recurrent rearrangement. Based on the duplication architecture of the genome, we investigated 130 regions that we hypothesized as candidates for previously undescribed genomic disorders. We tested 290 individuals with mental retardation by BAC array comparative genomic hybridization and identified 16 pathogenic rearrangements, including de novo microdeletions of 17q21.31 found in four individuals. Using oligonucleotide arrays, we refined the breakpoints of this microdeletion, defining a 478-kb critical region containing six genes that were deleted in all four individuals. We mapped the breakpoints of this deletion and of four other pathogenic rearrangements in 1q21.1, 15q13, 15q24 and 17q12 to flanking segmental duplications, suggesting that these are also sites of recurrent rearrangement. In common with the 17q21.31 deletion, these breakpoint regions are sites of copy number polymorphism in controls, indicating that these may be inherently unstable genomic regions.     

Analysis of yeast protein kinases using protein chips

We have developed a novel protein chip technology that allows the high-throughput analysis of biochemical activities, and used this approach to analyse nearly all of the protein kinases from Saccharomyces cerevisiae. Protein chips are disposable arrays of microwells in silicone elastomer sheets placed on top of microscope slides. The high density and small size of the wells allows for high-throughput batch processing and simultaneous analysis of many individual samples. Only small amounts of protein are required. Of 122 known and predicted yeast protein kinases, 119 were overexpressed and analysed using 17 different substrates and protein chips. We found many novel activities and that a large number of protein kinases are capable of phosphorylating tyrosine. The tyrosine phosphorylating enzymes often share common amino acid residues that lie near the catalytic region. Thus, our study identified a number of novel features of protein kinases and demonstrates that protein chip technology is useful for high-throughput screening of protein biochemical activity.     

A genome-wide scalable SNP genotyping assay using microarray technology

Oligonucleotide probe arrays have enabled massively parallel analysis of gene expression levels from a single cDNA sample. Application of microarray technology to analyzing genomic DNA has been stymied by the sequence complexity of the entire human genome. A robust, single base-resolution direct genomic assay would extend the reach of microarray technology. We developed an array-based whole-genome genotyping assay that does not require PCR and enables effectively unlimited multiplexing. The assay achieves a high signal-to-noise ratio by combining specific hybridization of picomolar concentrations of whole genome-amplified DNA to arrayed probes with allele-specific primer extension and signal amplification. As proof of principle, we genotyped several hundred previously characterized SNPs. The conversion rate, call rate and accuracy were comparable to those of high-performance PCR-based genotyping assays.     

Comparing strategies to fine-map the association of common SNPs at chromosome 9p21 with type 2 diabetes and myocardial infarction

Noncoding variants at human chromosome 9p21 near CDKN2A and CDKN2B are associated with type 2 diabetes, myocardial infarction, aneurysm, vertical cup disc ratio and at least five cancers. Here we compare approaches to more comprehensively assess genetic variation in the region. We carried out targeted sequencing at high coverage in 47 individuals and compared the results to pilot data from the 1000 Genomes Project. We imputed variants into type 2 diabetes and myocardial infarction cohorts directly from targeted sequencing, from a genotyped reference panel derived from sequencing and from 1000 Genomes Project low-coverage data. Polymorphisms with frequency >5% were captured well by all strategies. Imputation of intermediate-frequency polymorphisms required a higher density of tag SNPs in disease samples than is available on first-generation genome-wide association study (GWAS) arrays. Our association analyses identified more comprehensive sets of variants showing equivalent statistical association with type 2 diabetes or myocardial infarction, but did not identify stronger associations than the original GWAS signals.     

Large-scale discovery and genotyping of single-nucleotide polymorphisms in the mouse

Single-nucleotide polymorphisms (SNPs) have been the focus of much attention in human genetics because they are extremely abundant and well-suited for automated large-scale genotyping. Human SNPs, however, are less informative than other types of genetic markers (such as simple-sequence length polymorphisms or microsatellites) and thus more loci are required for mapping traits. SNPs offer similar advantages for experimental genetic organisms such as the mouse, but they entail no loss of informativeness because bi-allelic markers are fully informative in analysing crosses between inbred strains. Here we report a large-scale analysis of SNPs in the mouse genome. We characterized the rate of nucleotide polymorphism in eight mouse strains and identified a collection of 2,848 SNPs located in 1,755 sequence-tagged sites (STSs) using high-density oligonucleotide arrays. Three-quarters of these SNPs have been mapped on the mouse genome, providing a first-generation SNP map of the mouse. We have also developed a multiplex genotyping procedure by which a genome scan can be performed with only six genotyping reactions per animal.     

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.