Evidence map›Paper›PMID 22122853›Full record

ArticleGenetics, selection, evolution : GSE2011

Accuracies of genomic breeding values in American Angus beef cattle using K-means clustering for cross-validation.

Mahdi Saatchi, Mathew C McClure, Stephanie D McKay, Megan M Rolf, JaeWoo Kim, Jared E Decker, Tasia M Taxis, Richard H Chapple, Holly R Ramey, Sally L Northcutt and 7 more

Abstract readValidation Study
In one paragraph

Article in Genetics, selection, evolution : GSE, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 98 papers.

0numbers the graph read from it
0cells of the map it votes in
98citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

98 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Strategies to improve genomic predictions for 35 duck carcass traits in an FJournal of animal science and biotechnology · 2023
    Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Predicting the accuracy of genomic predictions.Genetics, selection, evolution : GSE · 2021
    Article
  17. Article
  18. Article
  19. Validation of single-step GBLUP genomic predictions from threshold models using the linear regression method: An application in chicken mortality.Journal of animal breeding and genetics = Zeitschrift fur Tierzuchtung und Zuchtungsbiologie · 2021
    Article
  20. Article

38 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

17 authors.

Mahdi SaatchiDepartment of Animal Science, Iowa State University, Ames, IA 50011, USA.
Mathew C McClure
Stephanie D McKay
Megan M Rolf
JaeWoo Kim
Jared E Decker
Tasia M Taxis
Richard H Chapple
Holly R Ramey
Sally L Northcutt
Stewart Bauck
Brent Woodward
Jack C M Dekkers
Rohan L Fernando
Robert D Schnabel
Dorian J Garrick
Jeremy F Taylor

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundGenomic selection is a recently developed technology that is beginning to revolutionize animal breeding. The objective of this study was to estimate marker effects to derive prediction equations for direct genomic values for 16 routinely recorded traits of American Angus beef cattle and quantify corresponding accuracies of prediction.

methodsDeregressed estimated breeding values were used as observations in a weighted analysis to derive direct genomic values for 3570 sires genotyped using the Illumina BovineSNP50 BeadChip. These bulls were clustered into five groups using K-means clustering on pedigree estimates of additive genetic relationships between animals, with the aim of increasing within-group and decreasing between-group relationships. All five combinations of four groups were used for model training, with cross-validation performed in the group not used in training. Bivariate animal models were used for each trait to estimate the genetic correlation between deregressed estimated breeding values and direct genomic values.

resultsAccuracies of direct genomic values ranged from 0.22 to 0.69 for the studied traits, with an average of 0.44. Predictions were more accurate when animals within the validation group were more closely related to animals in the training set. When training and validation sets were formed by random allocation, the accuracies of direct genomic values ranged from 0.38 to 0.85, with an average of 0.65, reflecting the greater relationship between animals in training and validation. The accuracies of direct genomic values obtained from training on older animals and validating in younger animals were intermediate to the accuracies obtained from K-means clustering and random clustering for most traits. The genetic correlation between deregressed estimated breeding values and direct genomic values ranged from 0.15 to 0.80 for the traits studied.

conclusionsThese results suggest that genomic estimates of genetic merit can be produced in beef cattle at a young age but the recurrent inclusion of genotyped sires in retraining analyses will be necessary to routinely produce for the industry the direct genomic values with the highest accuracy.

Indexed as

BreedingAnimalsCattleCluster AnalysisFemaleGenomicsMaleModels, GeneticPedigreeQuantitative Trait, Heritable

Identifiers

PMID22122853
PMCPMC3250932

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.