Evidence map›Paper›PMID 34841597›Full record

ArticleJournal of animal breeding and genetics = Zeitschrift fur Tierzuchtung und Zuchtungsbiologie2022

Single-step genomic evaluation of Russian dairy cattle using internal and external information.

Andrei A Kudinov, Esa A Mäntysaari, Timo J Pitkänen, Ekaterina I Saksa, Gert P Aamand, Pekka Uimari, Ismo Strandén

Abstract read
In one paragraph

Article in Journal of animal breeding and genetics = Zeitschrift fur Tierzuchtung und Zuchtungsbiologie, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
  2. Article
  3. Unravelling Heterozygosity-Rich Regions in the Holstein Genome.Animals : an open access journal from MDPI · 2025
    Article
  4. Article
  5. Article
  6. Article
  7. Single-step genomic evaluation of Russian dairy cattle using internal and external information.Journal of animal breeding and genetics = Zeitschrift fur Tierzuchtung und Zuchtungsbiologie · 2022
    Article
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

7 authors.

Andrei A KudinovNatural Resources Institute Finland (Luke), Jokioinen, Finland.ORCID https://orcid.org/0000-0002-7811-576X
Esa A MäntysaariNatural Resources Institute Finland (Luke), Jokioinen, Finland.ORCID https://orcid.org/0000-0003-0044-8473
Timo J PitkänenNatural Resources Institute Finland (Luke), Jokioinen, Finland.ORCID https://orcid.org/0000-0002-2275-5338
Ekaterina I SaksaRussian Research Institute for Farm Animal Genetics and Breeding - Branch of the L.K. Ernst Federal Science Center for Animal Husbandry (RRIFAGB), St. Petersburg, Russian Federation.
Gert P AamandNordic Cattle Genetic Evaluation (NAV), Aarhus, Denmark.ORCID https://orcid.org/0000-0003-1885-3290
Pekka UimariDepartment of Agricultural Science, University of Helsinki (UH), Helsinki, Finland.ORCID https://orcid.org/0000-0002-5349-3932
Ismo StrandénNatural Resources Institute Finland (Luke), Jokioinen, Finland.ORCID https://orcid.org/0000-0003-0161-2618

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Genomic data are widely used in predicting the breeding values of dairy cattle. The accuracy of genomic prediction depends on the size of the reference population and how related the candidate animals are to it. For populations with limited numbers of progeny-tested bulls, the reference populations must include cows and data from external populations. The aim of this study was to implement state-of-the-art single-step genomic evaluations for milk and fat yield in Holstein and Russian Black & White cattle in the Leningrad region (LR, Russia), using only a limited number of genotyped animals. We complemented internal information with external pseudo-phenotypic and genotypic data of bulls from the neighbouring Danish, Finnish and Swedish Holstein (DFS) population. Three data scenarios were used to perform single-step GBLUP predictions in the LR dairy cattle population. The first scenario was based on the original LR reference population, which constituted 1,080 genotyped cows and 427 genotyped bulls. In the second scenario, the genotypes of 414 bulls related to the LR from the DFS population were added to the reference population. In the third scenario, LR data were further augmented with pseudo-phenotypic data from the DFS population. The inclusion of foreign information increased the validation reliability of the milk yield by up to 30%. Suboptimal data recording practices hindered the improvement of fat yield. We confirmed that the single-step model is suitable for populations with a low number of genotyped animals, especially when external information is integrated into the evaluations. Genomic prediction in populations with a low number of progeny-tested bulls can be based on data from genotyped cows and on the inclusion of genotypes and pseudo-phenotypes from the external population. This approach increased the validation reliability of the implemented single-step model in the milk yield, but shortcomings in the LR data recording scheme prevented improvements in fat yield.

Indexed as

GenomeGenomicsAnimalsCattleFemaleGenotypeMaleMilkModels, GeneticPhenotypeReproducibility of Resultsdairy cattlegenomic predictionmulti-country genomic evaluationsingle-step GBLUP

Identifiers

PMID34841597
PMCPMC9299785

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LicenceCC BY-NC-ND
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Registered trials

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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.