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

By Lakshmi K. Matukumalli, C. Lawley, Robert D. Schnabel, Jeremy F. Taylor, M. Allan, M. P. Heaton, J. O’Connell, S. Moore, T. Smith, Tad Stewart Sonstegard and 1 more. PLoS ONE, 2009

989 citations recorded by the source corpus.

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.

Subfields: Genetics, Plant Science

View Paper: https://www.semanticscholar.org/paper/62c8bb218ad2f4dda766b3349b0185e3ee4ec2cd

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Genetics

In Plant Science

Citations in the corpus

LinkImpute: Fast and Accurate Genotype Imputation for Nonmodel Organisms (2015, methodology): “Arrays are widely used for GWA studies in humans (Stranger et al. 2011) and have also been developed for several agricultural species [ e.g. , cattle (Matukumalli et al. 2009), rice (Zhao et al. 2011), grape (Myles et al. 2010), and apple (Chagné et al. 2012)].”
Finding genes for economically important traits: Brahman cattle puberty (2012, methodology): “The Illumina BovineSNP50 array (Van Tassell et al. 2008; Matukumalli et al. 2009) was used to genotype samples according to the manufacturer’s protocols (Illumina Inc.”
Linkage disequilibrium levels in Bos indicus and Bos taurus cattle using medium and high density SNP chip data and different minor allele frequency distributions (2014, result): “individuals and a higher number of indicine reference populations (Illumina Inc, 2012) as compared to the 50K chip (Illumina Inc, 2011), the analysis of the MAF distributions is consistent with previous reports (McKay et al., 2008; Matukumalli et al., 2009) where the indicine breeds analyzed show la”
Improving accuracy of genomic predictions within and between dairy cattle breeds with imputed high-density single nucleotide polymorphism panels. (2012, methodology): “Allele frequencies of the SNP on the 50K panel are more or less distributed uniformly (i.e., it is a selection where SNP with very low minor allele frequency are underrepresented; e.g., Matukumalli et al., 2009).”
Design of a High Density SNP Genotyping Assay in the Pig Using SNPs Identified and Characterized by Next Generation Sequencing Technology (2009, methodology): “Final SNP selection was performed in waves [15] resulting in only 832 or 1.”
Development and Application of High-density SNP Arrays in Genomic Studies of Domestic Animals (2010, positive): “…the SNP is included in at least two sequence reads; ii) no repetitive elements surrounding the SNP (within 100 bp); iii) the SNP must be predicted by a minimum of six sequence reads; and iv) predicted SNPs cannot overlap with complex regions (e.g. duplicated sequences) (Matukumalli et al., 2009).”