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Infinium Assay for Large-scale SNP Genotyping Applications
13:33

Infinium Assay for Large-scale SNP Genotyping Applications

Published on: November 19, 2013

Genomic evaluations with many more genotypes.

Paul M VanRaden1, Jeffrey R O'Connell, George R Wiggans

  • 1Animal Improvement Programs Laboratory, USDA, Building 5 BARC-West, Beltsville, MD 20705-2350, USA. Paul.VanRaden@ars.usda.gov

Genetics, Selection, Evolution : GSE
|March 4, 2011
PubMed
Summary
This summary is machine-generated.

Genomic evaluations in Holstein cattle are more reliable and cost-effective by combining different marker densities. Increasing the number of animals genotyped offers greater reliability gains than increasing marker numbers.

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Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry

Published on: June 21, 2018

Area of Science:

  • Animal Genetics
  • Quantitative Genetics
  • Bioinformatics

Background:

  • Genomic evaluations in Holstein dairy cattle have improved with increased genotyping density (50,000 markers).
  • New genotyping chips (770,000 or 2,900 markers) allow for variable marker densities in evaluations.
  • Cost-effective selection is achieved by imputing missing genotypes from lower-density panels.

Purpose of the Study:

  • To evaluate the efficiency and reliability of genomic evaluations using mixed marker densities.
  • To compare imputation strategies for combining different marker densities.
  • To determine the impact of increasing marker numbers versus animal numbers on evaluation reliability.

Main Methods:

  • Simulated 500,000 marker genotypes for 33,414 Holstein cattle with existing 50,000 marker data.
  • Created mixed-density datasets by retaining 50,000 markers for most animals.
  • Imputed missing genotypes using population and pedigree haplotyping, comparing linear and nonlinear evaluation methods.

Main Results:

  • Combined differing marker sets efficiently within hours; achieved >95% accuracy in allele determination and missing genotype imputation.
  • Reliability with 50,000 markers was high (84.4%); increasing to 500,000 markers yielded only a 1.6% gain.
  • Higher density genotyping of a small subset of young bulls contributed significantly to the reliability gain.

Conclusions:

  • Genotype imputation and genomic evaluation methods are affordable and scalable for increased marker densities.
  • Individual animal reliabilities can be adjusted based on imputation success.
  • Combining marker densities and increasing the number of genotyped animals offers a cost-effective strategy for improving genomic evaluations, with greater gains expected from more animals.