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.     

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.     

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.     

Abnormal cerebellar development and axonal decussation due to mutations in AHI1 in Joubert syndrome

Joubert syndrome is a congenital brain malformation of the cerebellar vermis and brainstem with abnormalities of axonal decussation (crossing in the brain) affecting the corticospinal tract and superior cerebellar peduncles. Individuals with Joubert syndrome have motor and behavioral abnormalities, including an inability to walk due to severe clumsiness and 'mirror' movements, and cognitive and behavioral disturbances. Here we identified a locus associated with Joubert syndrome, JBTS3, on chromosome 6q23.2-q23.3 and found three deleterious mutations in AHI1, the first gene to be associated with Joubert syndrome. AHI1 is most highly expressed in brain, particularly in neurons that give rise to the crossing axons of the corticospinal tract and superior cerebellar peduncles. Comparative genetic analysis of AHI1 indicates that it has undergone positive evolutionary selection along the human lineage. Therefore, changes in AHI1 may have been important in the evolution of human-specific motor behaviors.     

Screening a large reference sample to identify very low frequency sequence variants: comparisons between two genes

Most human sequence variation is in the form of single-nucleotide polymorphisms (SNPs). It has been proposed that coding-region SNPs (cSNPs) be used for direct association studies to determine the genetic basis of complex traits. The success of such studies depends on the frequency of disease-associated alleles, and their distribution in different ethnic populations. If disease-associated alleles are frequent in most populations, then direct genotyping of candidate variants could show robust associations in manageable study samples. This approach is less feasible if the genetic risk from a given candidate gene is due to many infrequent alleles. Previous studies of several genes demonstrated that most variants are relatively infrequent (<0.05). These surveys genotyped small samples (n<75) and thus had limited ability to identify rare alleles. Here we evaluate the prevalence and distribution of such rare alleles by genotyping an ethnically diverse reference sample that is more than six times larger than those used in previous studies (n=450). We screened for variants in the complete coding sequence and intron-exon junctions of two candidate genes for neuropsychiatric phenotypes: SLC6A4, encoding the serotonin transporter; and SLC18A2, encoding the vesicular monoamine transporter. Both genes have unique roles in neuronal transmission, and variants in either gene might be associated with neurobehavioral phenotypes.     

Systematic screen for human disease genes in yeast

High similarity between yeast and human mitochondria allows functional genomic study of Saccharomyces cerevisiae to be used to identify human genes involved in disease. So far, 102 heritable disorders have been attributed to defects in a quarter of the known nuclear-encoded mitochondrial proteins in humans. Many mitochondrial diseases remain unexplained, however, in part because only 40-60% of the presumed 700-1,000 proteins involved in mitochondrial function and biogenesis have been identified. Here we apply a systematic functional screen using the pre-existing whole-genome pool of yeast deletion mutants to identify mitochondrial proteins. Three million measurements of strain fitness identified 466 genes whose deletions impaired mitochondrial respiration, of which 265 were new. Our approach gave higher selection than other systematic approaches, including fivefold greater selection than gene expression analysis. To apply these advantages to human disorders involving mitochondria, human orthologs were identified and linked to heritable diseases using genomic map positions.     

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.     

A rare variant in MYH6 is associated with high risk of sick sinus syndrome

Through complementary application of SNP genotyping, whole-genome sequencing and imputation in 38,384 Icelanders, we have discovered a previously unidentified sick sinus syndrome susceptibility gene, MYH6, encoding the alpha heavy chain subunit of cardiac myosin. A missense variant in this gene, c.2161C>T, results in the conceptual amino acid substitution p.Arg721Trp, has an allelic frequency of 0.38% in Icelanders and associates with sick sinus syndrome with an odds ratio = 12.53 and P = 1.5 × 10?2?. We show that the lifetime risk of being diagnosed with sick sinus syndrome is around 6% for non-carriers of c.2161C>T but is approximately 50% for carriers of the c.2161C>T variant.     

Exclusion of DNA changes in the beta-subunit of the c-GMP phosphodiesterase gene as the cause for Huntington's disease.

To identify expressed sequences within candidate regions for the Huntington's disease (HD) gene in 4p16.3, we isolated the gene encoding the beta subunit of the human cGMP phosphodiesterase (PDEB). We formally assessed this as a candidate gene for HD based on it's expression in brain, the demonstration of linkage disequilibrium between intragenic DNA markers and HD, and the demonstration that mice with a mutation in this gene have a reduction of neurons in particular brain regions. We investigated all 22 exons of PDEB and 5'-flanking region for point mutations in 16 HD patients of different ethnic origins using single strand conformational polymorphism analysis. The underlying DNA changes found initially exclusively in HD patients were excluded as the cause for HD.     

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.     

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.     

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.     

Population genomics of human gene expression

Genetic variation influences gene expression, and this variation in gene expression can be efficiently mapped to specific genomic regions and variants. Here we have used gene expression profiling of Epstein-Barr virus-transformed lymphoblastoid cell lines of all 270 individuals genotyped in the HapMap Consortium to elucidate the detailed features of genetic variation underlying gene expression variation. We find that gene expression is heritable and that differentiation between populations is in agreement with earlier small-scale studies. A detailed association analysis of over 2.2 million common SNPs per population (5% frequency in HapMap) with gene expression identified at least 1,348 genes with association signals in cis and at least 180 in trans. Replication in at least one independent population was achieved for 37% of cis signals and 15% of trans signals, respectively. Our results strongly support an abundance of cis-regulatory variation in the human genome. Detection of trans effects is limited but suggests that regulatory variation may be the key primary effect contributing to phenotypic variation in humans. We also explore several methodologies that improve the current state of analysis of gene expression variation.     

A genome-wide scan identifies mutations in the gene encoding phosphodiesterase 11A4 (PDE11A) in individuals with adrenocortical hyperplasia

Phosphodiesterases (PDEs) regulate cyclic nucleotide levels. Increased cyclic AMP (cAMP) signaling has been associated with PRKAR1A or GNAS mutations and leads to adrenocortical tumors and Cushing syndrome. We investigated the genetic source of Cushing syndrome in individuals with adrenocortical hyperplasia that was not caused by known defects. We performed genome-wide SNP genotyping, including the adrenocortical tumor DNA. The region with the highest probability to harbor a susceptibility gene by loss of heterozygosity (LOH) and other analyses was 2q31-2q35. We identified mutations disrupting the expression of the PDE11A isoform-4 gene (PDE11A) in three kindreds. Tumor tissues showed 2q31-2q35 LOH, decreased protein expression and high cyclic nucleotide levels and cAMP-responsive element binding protein (CREB) phosphorylation. PDE11A codes for a dual-specificity PDE that is expressed in adrenal cortex and is partially inhibited by tadalafil and other PDE inhibitors; its germline inactivation is associated with adrenocortical hyperplasia, suggesting another means by which dysregulation of cAMP signaling causes endocrine tumors.