Next-generation carrier screening.

PURPOSE: Carrier screening for recessive Mendelian disorders traditionally employs focused genotyping to interrogate limited sets of mutations most prevalent in specific ethnic groups. We sought to develop a next-generation DNA sequencing-based workflow to enable analysis of a more comprehensive set of disease-causing mutations. METHODS: We utilized molecular inversion probes to capture the protein-coding regions of 15 genes from genomic DNA isolated from whole blood and sequenced those regions using the Illumina HiSeq 2000 (Illumina, San Diego, CA). To assess the quality of the resulting data, we measured both the fraction of the targeted region yielding high-quality genotype calls, and the sensitivity and specificity of those calls by comparison with conventional Sanger sequencing across hundreds of samples. Finally, to improve the overall accuracy for detecting insertions and deletions, we introduce a novel assembly-based approach that substantially increases sensitivity without reducing specificity. RESULTS: We generated high-quality sequence for at least 99.8% of targeted base pairs in samples derived from blood and achieved high concordance with Sanger sequencing (sensitivity >99.9%, specificity >99.999%). Our novel algorithm is capable of detecting insertions and deletions inaccessible by current methods. CONCLUSION: Our next-generation DNA sequencing-based approach yields the accuracy and completeness necessary for a carrier screening test.

SNAP: a web-based tool for identification and annotation of proxy SNPs using HapMap.

SUMMARY: The interpretation of genome-wide association results is confounded by linkage disequilibrium between nearby alleles. We have developed a flexible bioinformatics query tool for single-nucleotide polymorphisms (SNPs) to identify and to annotate nearby SNPs in linkage disequilibrium (proxies) based on HapMap. By offering functionality to generate graphical plots for these data, the SNAP server will facilitate interpretation and comparison of genome-wide association study results, and the design of fine-mapping experiments (by delineating genomic regions harboring associated variants and their proxies). AVAILABILITY: SNAP server is available at http://www.broad.mit.edu/mpg/snap/.

Orthogonal NGS for High Throughput Clinical Diagnostics.

Next generation sequencing is a transformative technology for discovering and diagnosing genetic disorders. However, high-throughput sequencing remains error-prone, necessitating variant confirmation in order to meet the exacting demands of clinical diagnostic sequencing. To address this, we devised an orthogonal, dual platform approach employing complementary target capture and sequencing chemistries to improve speed and accuracy of variant calls at a genomic scale. We combined DNA selection by bait-based hybridization followed by Illumina NextSeq reversible terminator sequencing with DNA selection by amplification followed by Ion Proton semiconductor sequencing. This approach yields genomic scale orthogonal confirmation of ~95% of exome variants. Overall variant sensitivity improves as each method covers thousands of coding exons missed by the other. We conclude that orthogonal NGS offers improvements in variant calling sensitivity when two platforms are used, better specificity for variants identified on both platforms, and greatly reduces the time and expense of Sanger follow-up, thus enabling physicians to act on genomic results more quickly.

Candidate gene association resource (CARe): design, methods, and proof of concept.

BACKGROUND: The National Heart, Lung, and Blood Institute's Candidate Gene Association Resource (CARe), a planned cross-cohort analysis of genetic variation in cardiovascular, pulmonary, hematologic, and sleep-related traits, comprises >40,000 participants representing 4 ethnic groups in 9 community-based cohorts. The goals of CARe include the discovery of new variants associated with traits using a candidate gene approach and the discovery of new variants using the genome-wide association mapping approach specifically in African Americans. METHODS AND RESULTS: CARe has assembled DNA samples for >40,000 individuals self-identified as European American, African American, Hispanic, or Chinese American, with accompanying data on hundreds of phenotypes that have been standardized and deposited in the CARe Phenotype Database. All participants were genotyped for 7 single-nucleotide polymorphisms (SNPs) selected based on prior association evidence. We performed association analyses relating each of these SNPs to lipid traits, stratified by sex and ethnicity, and adjusted for age and age squared. In at least 2 of the ethnic groups, SNPs near CETP, LIPC, and LPL strongly replicated for association with high-density lipoprotein cholesterol concentrations, PCSK9 with low-density lipoprotein cholesterol levels, and LPL and APOA5 with serum triglycerides. Notably, some SNPs showed varying effect sizes and significance of association in different ethnic groups. CONCLUSIONS: The CARe Pilot Study validates the operational framework for phenotype collection, SNP genotyping, and analytic pipeline of the CARe project and validates the planned candidate gene study of approximately 2000 biological candidate loci in all participants and genome-wide association study in approximately 8000 African American participants. CARe will serve as a valuable resource for the scientific community.

Integrated genotype calling and association analysis of SNPs, common copy number polymorphisms and rare CNVs.

Accurate and complete measurement of single nucleotide (SNP) and copy number (CNV) variants, both common and rare, will be required to understand the role of genetic variation in disease. We present Birdsuite, a four-stage analytical framework instantiated in software for deriving integrated and mutually consistent copy number and SNP genotypes. The method sequentially assigns copy number across regions of common copy number polymorphisms (CNPs), calls genotypes of SNPs, identifies rare CNVs via a hidden Markov model (HMM), and generates an integrated sequence and copy number genotype at every locus (for example, including genotypes such as A-null, AAB and BBB in addition to AA, AB and BB calls). Such genotypes more accurately depict the underlying sequence of each individual, reducing the rate of apparent mendelian inconsistencies. The Birdsuite software is applied here to data from the Affymetrix SNP 6.0 array. Additionally, we describe a method, implemented in PLINK, to utilize these combined SNP and CNV genotypes for association testing with a phenotype.

Integrated detection and population-genetic analysis of SNPs and copy number variation.

Dissecting the genetic basis of disease risk requires measuring all forms of genetic variation, including SNPs and copy number variants (CNVs), and is enabled by accurate maps of their locations, frequencies and population-genetic properties. We designed a hybrid genotyping array (Affymetrix SNP 6.0) to simultaneously measure 906,600 SNPs and copy number at 1.8 million genomic locations. By characterizing 270 HapMap samples, we developed a map of human CNV (at 2-kb breakpoint resolution) informed by integer genotypes for 1,320 copy number polymorphisms (CNPs) that segregate at an allele frequency >1%. More than 80% of the sequence in previously reported CNV regions fell outside our estimated CNV boundaries, indicating that large (>100 kb) CNVs affect much less of the genome than initially reported. Approximately 80% of observed copy number differences between pairs of individuals were due to common CNPs with an allele frequency >5%, and more than 99% derived from inheritance rather than new mutation. Most common, diallelic CNPs were in strong linkage disequilibrium with SNPs, and most low-frequency CNVs segregated on specific SNP haplotypes.