Evidence map›Paper›PMID 31850078›Full record

ArticleFrontiers in genetics2019

Genome-Wide Association Study of Meat Quality Traits in Hanwoo Beef Cattle Using Imputed Whole-Genome Sequence Data.

Mohammed Bedhane, Julius van der Werf, Cedric Gondro, Naomi Duijvesteijn, Dajeong Lim, Byoungho Park, Mi Na Park, Roh Seung Hee, Samuel Clark

Open access · goldAbstract read
In one paragraph

Article in Frontiers in genetics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.

0numbers the graph read from it
0cells of the map it votes in
30citing papers in PubMed
3.6field-weighted citation impact, top 7% 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

30 citing papers in PubMed, 50 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 4 institutions in 3 countries.

Mohammed BedhaneSchool of Environmental and Rural Science, University of New England, Armidale, Australia.
Julius van der WerfSchool of Environmental and Rural Science, University of New England, Armidale, Australia.
Cedric GondroCollege of Agriculture & Natural Resources, Michigan State University, East Lansing, MI, United States.
Naomi DuijvesteijnSchool of Environmental and Rural Science, University of New England, Armidale, Australia.
Dajeong LimDivision of Animal Genomics and Bioinformatics, National Institute of Animal Science, Rural Development Administration, Wanju, South Korea.
Byoungho ParkAnimal Genetic Improvement Division, National Institute of Animal Science, Rural Development Administration, Seonghwan, South Korea.
Mi Na ParkAnimal Genetic Improvement Division, National Institute of Animal Science, Rural Development Administration, Seonghwan, South Korea.
Roh Seung HeeAnimal Genetic Improvement Division, National Institute of Animal Science, Rural Development Administration, Seonghwan, South Korea.
Samuel ClarkSchool of Environmental and Rural Science, University of New England, Armidale, Australia.
University of New England · AUNational Institute of Animal Science · KRRural Development Administration · KRMichigan State University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The discovery of single nucleotide polymorphisms (SNP) and the subsequent genotyping of large numbers of animals have enabled large-scale analyses to begin to understand the biological processes that underpin variation in animal populations. In beef cattle, genome-wide association studies using genotype arrays have revealed many quantitative trait loci (QTL) for various production traits such as growth, efficiency and meat quality. Most studies regarding meat quality have focused on marbling, which is a key trait associated with meat eating quality. However, other important traits like meat color, texture and fat color have not commonly been studied. Developments in genome sequencing technologies provide new opportunities to identify regions associated with these traits more precisely. The objective of this study was to estimate variance components and identify significant variants underpinning variation in meat quality traits using imputed whole genome sequence data. Phenotypic and genomic data from 2,110 Hanwoo cattle were used. The estimated heritabilities for the studied traits were 0.01, 0.16, 0.31, and 0.49 for fat color, meat color, meat texture and marbling score, respectively. Marbling score and meat texture were highly correlated. The genome-wide association study revealed 107 significant SNPs located on 14 selected chromosomes (one QTL region per selected chromosome). Four QTL regions were identified on BTA2, 12, 16, and 24 for marbling score and two QTL regions were found for meat texture trait on BTA12 and 29. Similarly, three QTL regions were identified for meat color on BTA2, 14 and 24 and five QTL regions for fat color on BTA7, 10, 12, 16, and 21. Candidate genes were identified for all traits, and their potential influence on the given trait was discussed. The significant SNP will be an important inclusion into commercial genotyping arrays to select new breeding animals more accurately.

Indexed as

genome-wide association studiesHanwoo cattleimputed sequence datameat qualityquantitative trait loci

Identifiers

PMID31850078
PMCPMC6895209
OpenAlexW2991517562

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.