Detection of rare variant effects in association studies: extreme values, iterative regression, and a hybrid approach

We develop statistical methods for detecting rare variants that are associated with quantitative traits. We propose two strategies and their combination for this purpose: the iterative regression strategy and the extreme values strategy. In the iterative regression strategy, we use iterative regression on residuals and a multimarker association test to identify a group of significant variants. In the extreme values strategy, we use individuals with extreme trait values to select candidate genes and then test only these candidate genes. These two strategies are integrated into a hybrid approach through a weighting technology. We apply the proposed methods to analyze the Genetic Analysis Workshop 17 data set. The results show that the hybrid approach is the most powerful approach. Using the hybrid approach, the average power to detect causal genes for Q1 is about 40% and the powers to detect FLT1 and KDR are 100% and 68% for Q1, respectively. The powers to detect VNN3 and BCHE are 34% and 30% for Q2, respectively

Application and comparison of large-scale solution-based DNA capture-enrichment methods on ancient DNA

The development of second-generation sequencing technologies has greatly benefitted the field of ancient DNA (aDNA). Its application can be further exploited by the use of targeted capture-enrichment methods to overcome restrictions posed by low endogenous and contaminating DNA in ancient samples. We tested the performance of Agilent's SureSelect and Mycroarray's MySelect in-solution capture systems on Illumina sequencing libraries built from ancient maize to identify key factors influencing aDNA capture experiments. High levels of clonality as well as the presence of multiple-copy sequences in the capture targets led to biases in the data regardless of the capture method. Neither method consistently outperformed the other in terms of average target enrichment, and no obvious difference was observed either when two tiling designs were compared. In addition to demonstrating the plausibility of capturing aDNA from ancient plant material, our results also enable us to provide useful recommendations for those planning targeted-sequencing on aDNA

Quantifying single nucleotide variant detection sensitivity in exome sequencing

BACKGROUND: The targeted capture and sequencing of genomic regions has rapidly demonstrated its utility in genetic studies. Inherent in this technology is considerable heterogeneity of target coverage and this is expected to systematically impact our sensitivity to detect genuine polymorphisms. To fully interpret the polymorphisms identified in a genetic study it is often essential to both detect polymorphisms and to understand where and with what probability real polymorphisms may have been missed. RESULTS: Using down-sampling of 30 deeply sequenced exomes and a set of gold-standard single nucleotide variant (SNV) genotype calls for each sample, we developed an empirical model relating the read depth at a polymorphic site to the probability of calling the correct genotype at that site. We find that measured sensitivity in SNV detection is substantially worse than that predicted from the naive expectation of sampling from a binomial. This calibrated model allows us to produce single nucleotide resolution SNV sensitivity estimates which can be merged to give summary sensitivity measures for any arbitrary partition of the target sequences (nucleotide, exon, gene, pathway, exome). These metrics are directly comparable between platforms and can be combined between samples to give “power estimates” for an entire study. We estimate a local read depth of 13X is required to detect the alleles and genotype of a heterozygous SNV 95% of the time, but only 3X for a homozygous SNV. At a mean on-target read depth of 20X, commonly used for rare disease exome sequencing studies, we predict 5–15% of heterozygous and 1–4% of homozygous SNVs in the targeted regions will be missed. CONCLUSIONS: Non-reference alleles in the heterozygote state have a high chance of being missed when commonly applied read coverage thresholds are used despite the widely held assumption that there is good polymorphism detection at these coverage levels. Such alleles are likely to be of functional importance in population based studies of rare diseases, somatic mutations in cancer and explaining the “missing heritability” of quantitative traits

Phospholipase A2-activating protein is associated with a novel form of leukoencephalopathy

Leukoencephalopathies are a group of white matter disorders related to abnormal formation, maintenance, and turnover of myelin in the central nervous system. These disorders of the brain are categorized according to neuroradiological and pathophysiological criteria. Herein, we have identified a unique form of leukoencephalopathy in seven patients presenting at ages 2 to 4 months with progressive microcephaly, spastic quadriparesis, and global developmental delay. Clinical, metabolic, and imaging characterization of seven patients followed by homozygosity mapping and linkage analysis were performed. Next generation sequencing, bioinformatics, and segregation analyses followed, to determine a loss of function sequence variation in the phospholipase A2-activating protein encoding gene (PLAA). Expression and functional studies of the encoded protein were performed and included measurement of prostaglandin E2 and cytosolic phospholipase A2 activity in membrane fractions of fibroblasts derived from patients and healthy controls. Plaa-null mice were generated and prostaglandin E2 levels were measured in different tissues. The novel phenotype of our patients segregated with a homozygous loss-of-function sequence variant, causing the substitution of leucine at position 752 to phenylalanine, in PLAA, which causes disruption of the protein's ability to induce prostaglandin E2 and cytosolic phospholipase A2 synthesis in patients' fibroblasts. Plaa-null mice were perinatal lethal with reduced brain levels of prostaglandin E2 The non-functional phospholipase A2-activating protein and the associated neurological phenotype, reported herein for the first time, join other complex phospholipid defects that cause leukoencephalopathies in humans, emphasizing the importance of this axis in white matter development and maintenance

Comparison of Three Targeted Enrichment Strategies on the SOLiD Sequencing Platform

Despite the ever-increasing throughput and steadily decreasing cost of next generation sequencing (NGS), whole genome sequencing of humans is still not a viable option for the majority of genetics laboratories. This is particularly true in the case of complex disease studies, where large sample sets are often required to achieve adequate statistical power. To fully leverage the potential of NGS technology on large sample sets, several methods have been developed to selectively enrich for regions of interest. Enrichment reduces both monetary and computational costs compared to whole genome sequencing, while allowing researchers to take advantage of NGS throughput. Several targeted enrichment approaches are currently available, including molecular inversion probe ligation sequencing (MIPS), oligonucleotide hybridization based approaches, and PCR-based strategies. To assess how these methods performed when used in conjunction with the ABI SOLID3+, we investigated three enrichment techniques: Nimblegen oligonucleotide hybridization array-based capture; Agilent SureSelect oligonucleotide hybridization solution-based capture; and Raindance Technologies' multiplexed PCR-based approach. Target regions were selected from exons and evolutionarily conserved areas throughout the human genome. Probe and primer pair design was carried out for all three methods using their respective informatics pipelines. In all, approximately 0.8 Mb of target space was identical for all 3 methods. SOLiD sequencing results were analyzed for several metrics, including consistency of coverage depth across samples, on-target versus off-target efficiency, allelic bias, and genotype concordance with array-based genotyping data. Agilent SureSelect exhibited superior on-target efficiency and correlation of read depths across samples. Nimblegen performance was similar at read depths at 20× and below. Both Raindance and Nimblegen SeqCap exhibited tighter distributions of read depth around the mean, but both suffered from lower on-target efficiency in our experiments. Raindance demonstrated the highest versatility in assay design

Exome Sequencing Identifies ZNF644 Mutations in High Myopia

Myopia is the most common ocular disorder worldwide, and high myopia in particular is one of the leading causes of blindness. Genetic factors play a critical role in the development of myopia, especially high myopia. Recently, the exome sequencing approach has been successfully used for the disease gene identification of Mendelian disorders. Here we show a successful application of exome sequencing to identify a gene for an autosomal dominant disorder, and we have identified a gene potentially responsible for high myopia in a monogenic form. We captured exomes of two affected individuals from a Han Chinese family with high myopia and performed sequencing analysis by a second-generation sequencer with a mean coverage of 30× and sufficient depth to call variants at ∼97% of each targeted exome. The shared genetic variants of these two affected individuals in the family being studied were filtered against the 1000 Genomes Project and the dbSNP131 database. A mutation A672G in zinc finger protein 644 isoform 1 (ZNF644) was identified as being related to the phenotype of this family. After we performed sequencing analysis of the exons in the ZNF644 gene in 300 sporadic cases of high myopia, we identified an additional five mutations (I587V, R680G, C699Y, 3′UTR+12 C>G, and 3′UTR+592 G>A) in 11 different patients. All these mutations were absent in 600 normal controls. The ZNF644 gene was expressed in human retinal and retinal pigment epithelium (RPE). Given that ZNF644 is predicted to be a transcription factor that may regulate genes involved in eye development, mutation may cause the axial elongation of eyeball found in high myopia patients. Our results suggest that ZNF644 might be a causal gene for high myopia in a monogenic form

A transcriptome-wide association study among 97,898 women to identify candidate susceptibility genes for epithelial ovarian cancer risk

Large-scale genome-wide association studies (GWAS) have identified approximately 35 loci associated with epithelial ovarian cancer (EOC) risk. The majority of GWAS-identified disease susceptibility variants are located in non-coding regions, and causal genes underlying these associations remain largely unknown. Here we performed a transcriptome-wide association study to search for novel genetic loci and plausible causal genes at known GWAS loci. We used RNA sequencing data (68 normal ovarian-tissue samples from 68 individuals and 6,124 cross-tissue samples from 369 individuals) and high-density genotyping data from European descendants of the Genotype-Tissue Expression (GTEx V6) project to build ovarian and cross-tissue models of genetically regulated expression using elastic net methods. We evaluated 17,121 genes for their cis-predicted gene expression in relation to EOC risk using summary statistics data from GWAS of 97,898 women, including 29,396 EOC cases. With a Bonferroni-corrected significance level of P<2.2×10-6, we identified 35 genes including FZD4 at 11q14.2 (Z=5.08, P=3.83×10-7, the cross-tissue model; 1 Mb away from any GWAS-identified EOC risk variant), a potential novel locus for EOC risk. All other 34 significantly-associated genes were located within 1 Mb of known GWAS-identified loci, including 23 genes at 6 loci not previously linked to EOC risk. Upon conditioning on nearby known EOC GWAS-identified variants, the associations for 31 genes disappeared and 3 genes remained (P<1.47 x 10-3). These data identify one novel locus (FZD4) and 34 genes at 13 known EOC risk loci associated with EOC risk, providing new insights into EOC carcinogenesis