Evidence map›Paper›PMID 30481306›Full record

ArticleJournal of animal science2019

Multivariate genomic predictions for age at puberty in tropically adapted beef heifers.

Bailey N Engle, Nicholas J Corbet, Jamie M Allen, Alan R Laing, Geoffry Fordyce, Michael R McGowan, Brian M Burns, Russell E Lyons, Ben J Hayes

Open access · bronzeAbstract read
In one paragraph

Article in Journal of animal science, 2019. 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
2.2field-weighted citation impact, top 11% of its field
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, 20 citations in OpenAlex.

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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

9 authors at 5 institutions in 2 countries.

Bailey N EngleDepartment of Animal Science, Texas A&M University, College Station, TX.
Nicholas J CorbetCentral Queensland University, School of Health, Medical and Applied Sciences, Rockhampton, QLD, Australia.
Jamie M AllenAgricultural Business Research Institute, University of New England, Armidale, NSW, Australia.
Alan R LaingDepartment of Agriculture and Fisheries, Ayr, QLD, Australia.
Geoffry FordyceQueensland Alliance for Agriculture and Food Innovation, Centre for Animal Science, University of Queensland, St Lucia, QLD, Australia.
Michael R McGowanUniversity of Queensland, School of Veterinary Science, Gatton, QLD, Australia.
Brian M BurnsDepartment of Agriculture and Fisheries, Ayr, QLD, Australia.
Russell E LyonsNeoGen, University of Queensland, School of Veterinary Science, Gatton, QLD, Australia.
Ben J HayesQueensland Alliance for Agriculture and Food Innovation, Centre for Animal Science, University of Queensland, St Lucia, QLD, Australia.
University of Queensland · AUAgriculture and Food · AUCentral Queensland University · AUTexas A&M University · USUniversity of New England · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Heifers that have an earlier age at puberty often have greater lifetime productivity. Age at puberty is moderately heritable so selection should effectively reduce the number of days to puberty, and improve heifer productivity and profitability as a result. However, recording age at puberty is intensive, requiring repeat ovarian scanning to determine age at first corpus luteum (AGECL). Genomic selection has been proposed as a strategy to select for earlier age at puberty; however, large reference populations of cows with AGECL records and genotypes would be required to generate accurate GEBV for this trait. Reproductive maturity score (RMS) is a proxy trait for age at puberty for implementation in northern Australia beef herds, where large scale recording of AGECL is not feasible. RMS assigns a score of 0 to 5 from a single ovarian scan to describe ovarian maturity at ~600 d. Here we use multivariate genomic prediction to evaluate the value of a large RMS data set to improve accuracy of GEBV for age at puberty (AGECL). There were 882 Brahman and 990 Tropical Composite heifers with AGECL phenotypes, and an independent set of 974 Brahman, 1,798 Santa Gertrudis, and 910 Droughtmaster heifers with RMS phenotypes. All animals had 728,785 real or imputed SNP genotypes. The correlation of AGECL and RMS (h2 = 0.23) was estimated as -0.83 using the genomic information. This result also demonstrates that using genomic information it is possible to estimate genetic correlations between traits collected on different animals in different herds, with minimal or unknown pedigree linkage between them. Inclusion of heifers with RMS in the multi-trait model improved the accuracy of genomic evaluations for AGECL. Accuracy of RMS GEBV generally did not improve by adding heifers with AGECL phenotypes into the reference population. These results suggest that RMS and AGECL may be used together in a multi-trait prediction model to increase the accuracy of prediction for age at puberty in tropically adapted beef cattle.

Indexed as

GenomicsAnimalsAustraliaBreedingCattleFemaleGenomeGenotypeMultivariate AnalysisPedigreePhenotypeReproductionSexual Maturation

Identifiers

PMID30481306
PMCPMC6313118
OpenAlexW2902909862

What OpenQuestion holds

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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.