Development and Characterization of a High Density SNP Genotyping Assay for Cattle

The success of genome-wide association (GWA) studies for the detection of sequence variation affecting complex traits in human has spurred interest in the use of large-scale high-density single nucleotide polymorphism (SNP) genotyping for the identification of quantitative trait loci (QTL) and for marker-assisted selection in model and agricultural species. A cost-effective and efficient approach for the development of a custom genotyping assay interrogating 54,001 SNP loci to support GWA applications in cattle is described. A novel algorithm for achieving a compressed inter-marker interval distribution proved remarkably successful, with median interval of 37 kb and maximum predicted gap of <350 kb. The assay was tested on a panel of 576 animals from 21 cattle breeds and six outgroup species and revealed that from 39,765 to 46,492 SNP are polymorphic within individual breeds (average minor allele frequency (MAF) ranging from 0.24 to 0.27). The assay also identified 79 putative copy number variants in cattle. Utility for GWA was demonstrated by localizing known variation for coat color and the presence/absence of horns to their correct genomic locations. The combination of SNP selection and the novel spacing algorithm allows an efficient approach for the development of high-density genotyping platforms in species having full or even moderate quality draft sequence. Aspects of the approach can be exploited in species which lack an available genome sequence. The BovineSNP50 assay described here is commercially available from Illumina and provides a robust platform for mapping disease genes and QTL in cattle

Power to Detect Risk Alleles Using Genome-Wide Tag SNP Panels

Advances in high-throughput genotyping and the International HapMap Project have enabled association studies at the whole-genome level. We have constructed whole-genome genotyping panels of over 550,000 (HumanHap550) and 650,000 (HumanHap650Y) SNP loci by choosing tag SNPs from all populations genotyped by the International HapMap Project. These panels also contain additional SNP content in regions that have historically been overrepresented in diseases, such as nonsynonymous sites, the MHC region, copy number variant regions and mitochondrial DNA. We estimate that the tag SNP loci in these panels cover the majority of all common variation in the genome as measured by coverage of both all common HapMap SNPs and an independent set of SNPs derived from complete resequencing of genes obtained from SeattleSNPs. We also estimate that, given a sample size of 1,000 cases and 1,000 controls, these panels have the power to detect single disease loci of moderate risk (λ ∼ 1.8–2.0). Relative risks as low as λ ∼ 1.1–1.3 can be detected using 10,000 cases and 10,000 controls depending on the sample population and disease model. If multiple loci are involved, the power increases significantly to detect at least one locus such that relative risks 20%–35% lower can be detected with 80% power if between two and four independent loci are involved. Although our SNP selection was based on HapMap data, which is a subset of all common SNPs, these panels effectively capture the majority of all common variation and provide high power to detect risk alleles that are not represented in the HapMap data

Comparison of buccal and blood-derived canine DNA, either native or whole genome amplified, for array-based genome-wide association studies

<p>Abstract</p> <p>Background</p> <p>The availability of array-based genotyping platforms for single nucleotide polymorphisms (SNPs) for the canine genome has expanded the opportunities to undertake genome-wide association (GWA) studies to identify the genetic basis for <it>Mendelian </it>and complex traits. Whole blood as the source of high quality DNA is undisputed but often proves impractical for collection of the large numbers of samples necessary to discover the loci underlying complex traits. Further, many countries prohibit the collection of blood from dogs unless medically necessary thereby restricting access to critical control samples from healthy dogs. Alternate sources of DNA, typically from buccal cytobrush extractions, while convenient, have been suggested to have low yield and perform poorly in GWA. Yet buccal cytobrushes provide a cost-effective means of collecting DNA, are readily accepted by dog owners, and represent a large resource base in many canine genetics laboratories. To increase the DNA quantities, whole genome amplification (WGA) can be performed. Thus, the present study assessed the utility of buccal-derived DNA as well as whole genome amplification in comparison to blood samples for use on the most recent iteration of the canine HD SNP array (Illumina).</p> <p>Findings</p> <p>In both buccal and blood samples, whether whole genome amplified or not, 97% of the samples had SNP call rates in excess of 80% indicating that the vast majority of the SNPs would be suitable to perform association studies regardless of the DNA source. Similarly, there were no significant differences in marker intensity measurements between buccal and blood samples for copy number variations (CNV) analysis.</p> <p>Conclusions</p> <p>All DNA samples assayed, buccal or blood, native or whole genome amplified, are appropriate for use in array-based genome-wide association studies. The concordance between subsets of dogs for which both buccal and blood samples, or those samples whole genome amplified, was shown to average >99%. Thus, the two DNA sources were comparable in the generation of SNP genotypes and intensity values to estimate structural variation indicating the utility for the use of buccal cytobrush samples and the reliability of whole genome amplification for genome-wide association and CNV studies.</p

SNP discovery and allele frequency estimation by deep sequencing of reduced representation libraries

High-density single-nucleotide polymorphism (SNP) arrays have revolutionized the ability of genome-wide association studies to detect genomic regions harboring sequence variants that affect complex traits. Extensive numbers of validated SNPs with known allele frequencies are essential to construct genotyping assays with broad utility. We describe an economical, efficient, single-step method for SNP discovery, validation and characterization that uses deep sequencing of reduced representation libraries (RRLs) from specified target populations. Using nearly 50 million sequences generated on an Illumina Genome Analyzer from DNA of 66 cattle representing three populations, we identified 62,042 putative SNPs and predicted their allele frequencies. Genotype data for these 66 individuals validated 92% of 23,357 selected genome-wide SNPs, with a genotypic and sequence allele frequency correlation of r = 0.67. This approach for simultaneous de novo discovery of high-quality SNPs and population characterization of allele frequencies may be applied to any species with at least a partially sequenced genome