Experiences with a single-step genome evaluation

  • Misztal I
  • Aggrey S
  • Muir W
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Genomic selection can be implemented based on the genomic relationship matrix (GBLUP) and can be combined with phenotypes from nongenotyped animals through the use of best linear unbiased prediction (BLUP). A common method to combine both sources of information involves multiple steps, but is difficult to use with complicated models and is nonoptimal. A simpler method, termed single-step GBLUP, or ssGBLUP, integrates the genomically derived relationships (G) with population-based pedigree relationships (A) into a combined relationship matrix (H) and allows for genomic selection in a single step. The ssGBLUP method is easy to implement and uses standard BLUP-based programs. Experiences with field data in chickens, pigs, and dairy indicate that ssGBLUP is more accurate yet much simpler than multi-step methods. The current limits of ssGBLUP are approximately 100,000 genotypes and 18 traits. Models involving 10 million animals have been run successfully. The inverse of H can also be used in existing programs for parameter estimationm, but a properly scaled G is needed for unbiased estimation. Also, as genomic predictions can be converted to SNP effects, ssGBLUP is useful for genomic-wide association studies. The single-step method for genomic selection translates the use of genomic information into standard BLUP, and variance-component estimation programs become a routine.

Author-supplied keywords

  • Best linear unbiased prediction
  • Genome-wide association study
  • Single nucleotide polymorphism
  • Single-step genomic relationship matrix

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  • Ignacy Misztal

  • Samuel E. Aggrey

  • William M. Muir

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