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

被引:422
作者
Van Tassell, Curtis P. [1 ]
Smith, Timothy P. L. [2 ]
Matukumalli, Lakshmi K. [1 ,3 ]
Taylor, Jeremy F. [4 ]
Schnabel, Robert D. [4 ]
Lawley, Cynthia Taylor [5 ]
Haudenschild, Christian D. [5 ]
Moore, Stephen S. [6 ]
Warren, Wesley C. [7 ]
Sonstegard, Tad S. [1 ]
机构
[1] USDA ARS, Bovine Funct Genom Lab, Beltsville, MD 20705 USA
[2] USDA ARS, Meat Anim Res Ctr, Clay Ctr, NE 68933 USA
[3] George Mason Univ, Manassas, VA 20110 USA
[4] Univ Missouri, Div Anim Sci, Columbia, MO 65211 USA
[5] Illumina Inc, Hayward, CA 94545 USA
[6] Univ Alberta, Dept Agr Food & Nutr Sci, Edmonton, AB T6G 2P5, Canada
[7] Washington Univ, Sch Med, Genome Sequencing Ctr, St Louis, MO 63108 USA
关键词
D O I
10.1038/NMETH.1185
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
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.
引用
收藏
页码:247 / 252
页数:6
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