An Automated Computer System to Support Ultra High Throughput SNP Genotyping

Heil, Jeremy; Glanowski, Stephen; Scott, Joan A.; Winn-Deen, Emily S.; McMullen, Ivy; Wu, Lingyun; Gire, C.; Sprague, Arlan C

doi:10.1142/9789812799623_0004

Cited by 8 publications

(9 citation statements)

References 11 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…After the design of primers and TaqMan probes, a computational quality-control step was performed to ensure uniqueness of the predicted amplicons in the genome assembly. This allowed us to eliminate potentially problematic SNP targets that may arise from repeated genomic regions, pseudo-SNPs, and other possible assembly artifacts (Heil et al 2002).…”

Section: Assay Development and Genotypingmentioning

confidence: 99%

The linkage disequilibrium maps of three human chromosomes across four populations reflect their demographic history and a common underlying recombination pattern

Vega¹,

Isaac²,

Collins

et al. 2005

Genome Res.

108

View full text Add to dashboard Cite

The extent and patterns of linkage disequilibrium (LD) determine the feasibility of association studies to map genes that underlie complex traits. Here we present a comparison of the patterns of LD across four major human populations (African-American, Caucasian, Chinese, and Japanese) with a high-resolution single-nucleotide polymorphism (SNP) map covering almost the entire length of chromosomes 6, 21, and 22. We constructed metric LD maps formulated such that the units measure the extent of useful LD for association mapping. LD reaches almost twice as far in chromosome 6 as in chromosomes 21 or 22, in agreement with their differences in recombination rates. By all measures used, out-of-Africa populations showed over a third more LD than African-Americans, highlighting the role of the population's demography in shaping the patterns of LD. Despite those differences, the long-range contour of the LD maps is remarkably similar across the four populations, presumably reflecting common localization of recombination hot spots. Our results have practical implications for the rational design and selection of SNPs for disease association studies.

show abstract

Section: Assay Development and Genotypingmentioning

confidence: 99%

The linkage disequilibrium maps of three human chromosomes across four populations reflect their demographic history and a common underlying recombination pattern

Vega¹,

Isaac²,

Collins

et al. 2005

Genome Res.

108

View full text Add to dashboard Cite

show abstract

“…A high-resolution linkage map facilitates fine mapping of quantitative trait loci (QTLs) and can be produced because of the abundance of SNPs within the genome [18]. SNP based genotyping is preferred because it is highly accurate, quick and automated, using limited human intervention.…”

Section: Introductionmentioning

confidence: 99%

A SNP based linkage map of the turkey genome reveals multiple intrachromosomal rearrangements between the Turkey and Chicken genomes

et al. 2010

View full text Add to dashboard Cite

BackgroundThe turkey (Meleagris gallopavo) is an important agricultural species that is the second largest contributor to the world's poultry meat production. The genomic resources of turkey provide turkey breeders with tools needed for the genetic improvement of commercial breeds of turkey for economically important traits. A linkage map of turkey is essential not only for the mapping of quantitative trait loci, but also as a framework to enable the assignment of sequence contigs to specific chromosomes. Comparative genomics with chicken provides insight into mechanisms of genome evolution and helps in identifying rare genomic events such as genomic rearrangements and duplications/deletions.ResultsEighteen full sib families, comprising 1008 (35 F1 and 973 F2) birds, were genotyped for 775 single nucleotide polymorphisms (SNPs). Of the 775 SNPs, 570 were informative and used to construct a linkage map in turkey. The final map contains 531 markers in 28 linkage groups. The total genetic distance covered by these linkage groups is 2,324 centimorgans (cM) with the largest linkage group (81 loci) measuring 326 cM. Average marker interval for all markers across the 28 linkage groups is 4.6 cM. Comparative mapping of turkey and chicken revealed two inter-, and 57 intrachromosomal rearrangements between these two species.ConclusionOur turkey genetic map of 531 markers reveals a genome length of 2,324 cM. Our linkage map provides an improvement of previously published maps because of the more even distribution of the markers and because the map is completely based on SNP markers enabling easier and faster genotyping assays than the microsatellitemarkers used in previous linkage maps. Turkey and chicken are shown to have a highly conserved genomic structure with a relatively low number of inter-, and intrachromosomal rearrangements.

show abstract

“…All information on the SNPs used in this study may be found in table S1 in our online supplement (http://linkage.rockefeller.edu/ derek/tables1-4.html) [26][27][28][29] . All the genotype data used here is available through the SNPbrowser™ Software genotype export function (see Online Database Information, below).…”

Section: Snp Used In Studymentioning

confidence: 99%

Power and Sample Size Calculations for Genetic Case/Control Studies Using Gene-Centric SNP Maps: Application to Human Chromosomes 6, 21, and 22 in Three Populations

Vega

Gordon

et al. 2005

Hum Hered

View full text Add to dashboard Cite

Power and sample size calculations are critical parts of any research design for genetic association. We present a method that utilizes haplotype frequency information and average marker-marker linkage disequilibrium on SNPs typed in and around all genes on a chromosome. The test statistic used is the classic likelihood ratio test applied to haplotypes in case/control populations. Haplotype frequencies are computed through specification of genetic model parameters. Power is determined by computation of the test’s non-centrality parameter. Power per gene is computed as a weighted average of the power assuming each haplotype is associated with the trait. We apply our method to genotype data from dense SNP maps across three entire chromosomes (6, 21, and 22) for three different human populations (African-American, Caucasian, Chinese), three different models of disease (additive, dominant, and multiplicative) and two trait allele frequencies (rare, common). We perform a regression analysis using these factors, average marker-marker disequilibrium, and the haplotype diversity across the gene region to determine which factors most significantly affect average power for a gene in our data. Also, as a ‘proof of principle’ calculation, we perform power and sample size calculations for all genes within 100 kb of the PSORS1 locus (chromosome 6) for a previously published association study of psoriasis. Results of our regression analysis indicate that four highly significant factors that determine average power to detect association are: disease model, average marker-marker disequilibrium, haplotype diversity, and the trait allele frequency. These findings may have important implications for the design of well-powered candidate gene association studies. Our power and sample size calculations for the PSORS1 gene appear consistent with published findings, namely that there is substantial power (>0.99) for most genes within 100 kb of the PSORS1 locus at the 0.01 significance level.

show abstract

An Automated Computer System to Support Ultra High Throughput SNP Genotyping

Cited by 8 publications

References 11 publications

The linkage disequilibrium maps of three human chromosomes across four populations reflect their demographic history and a common underlying recombination pattern

The linkage disequilibrium maps of three human chromosomes across four populations reflect their demographic history and a common underlying recombination pattern

A SNP based linkage map of the turkey genome reveals multiple intrachromosomal rearrangements between the Turkey and Chicken genomes

Power and Sample Size Calculations for Genetic Case/Control Studies Using Gene-Centric SNP Maps: Application to Human Chromosomes 6, 21, and 22 in Three Populations

Contact Info

Product

Resources

About