Evidence map›Paper›PMID 34207091›Full record

ArticleAnimals : an open access journal from MDPI2021

Genomic Prediction in Local Breeds: The Rendena Cattle as a Case Study.

Enrico Mancin, Beniamino Tuliozi, Cristina Sartori, Nadia Guzzo, Roberto Mantovani

Abstract read
In one paragraph

Article in Animals : an open access journal from MDPI, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Article
  2. Article
  3. Multi-Breed Genomic Predictions for Average Daily Gain in Three Italian Beef Cattle Breeds.Journal of animal breeding and genetics = Zeitschrift fur Tierzuchtung und Zuchtungsbiologie · 2026
    Article
  4. Efficiency of Recurrent Genomic Selection in Panmictic Populations.Animals : an open access journal from MDPI · 2025
    Article
  5. Heterogeneity of Variances in Milk Yield in Murrah Buffaloes.Animals : an open access journal from MDPI · 2025
    Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. 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

5 authors.

Enrico MancinDepartment of Agronomy, Food, Natural Resources, Animals and Environment, University of Padua, Viale dell'Università, 16, 35020 Legnaro, Italy.ORCID 0000-0002-4130-4639
Beniamino TulioziDepartment of Agronomy, Food, Natural Resources, Animals and Environment, University of Padua, Viale dell'Università, 16, 35020 Legnaro, Italy.ORCID 0000-0001-5656-4858
Cristina SartoriDepartment of Agronomy, Food, Natural Resources, Animals and Environment, University of Padua, Viale dell'Università, 16, 35020 Legnaro, Italy.ORCID 0000-0002-2091-2280
Nadia GuzzoDepartment of Comparative Biomedicine and Food Science, University of Padua, Viale dell'Università, 16, 35020 Legnaro, Italy.
Roberto MantovaniDepartment of Agronomy, Food, Natural Resources, Animals and Environment, University of Padua, Viale dell'Università, 16, 35020 Legnaro, Italy.ORCID 0000-0002-1919-0559

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The maintenance of local cattle breeds is key to selecting for efficient food production, landscape protection, and conservation of biodiversity and local cultural heritage. Rendena is an indigenous cattle breed from the alpine North-East of Italy, selected for dual purpose, but with lesser emphasis given to beef traits. In this situation, increasing accuracy for beef traits could prevent detrimental effects due to the antagonism with milk production. Our study assessed the impact of genomic information on estimated breeding values (EBVs) in Rendena performance-tested bulls. Traits considered were average daily gain, in vivo EUROP score, and in vivo estimate of dressing percentage. The final dataset contained 1691 individuals with phenotypes and 8372 animals in pedigree, 1743 of which were genotyped. Using the cross-validation method, three models were compared: (i) Pedigree-BLUP (PBLUP); (ii) single-step GBLUP (ssGBLUP), and (iii) weighted single-step GBLUP (WssGBLUP). Models including genomic information presented higher accuracy, especially WssGBLUP. However, the model with the best overall properties was the ssGBLUP, showing higher accuracy than PBLUP and optimal values of bias and dispersion parameters. Our study demonstrated that integrating phenotypes for beef traits with genomic data can be helpful to estimate EBVs, even in a small local breed.

Indexed as

cross-validationgenomic predictionlocal cattle breedsssGBLUP

Identifiers

PMID34207091
PMCPMC8234894

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.