Evidence map›Paper›PMID 26954162›Full record

ArticleAsian-Australasian journal of animal sciences2017

Genome-association analysis of Korean Holstein milk traits using genomic estimated breeding value.

Donghyun Shin, Chul Lee, Kyoung-Do Park, Heebal Kim, Kwang-Hyeon Cho

Abstract read
In one paragraph

Article in Asian-Australasian journal of animal sciences, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Review
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.

Donghyun ShinDepartment of Agricultural Biotechnology, Animal Biotechnology, and Research Institute for Agriculture and Life Sciences, Seoul National University, Seoul 151-921, Korea.
Chul LeeInterdisciplinary Program in Bioinformatics, Seoul National University, Seoul 151-921, Korea.
Kyoung-Do ParkThe Animal Molecular Genetics & Breeding Center, Chonbuk National University, Jeonju 561-756, Korea.
Heebal KimDepartment of Agricultural Biotechnology, Animal Biotechnology, and Research Institute for Agriculture and Life Sciences, Seoul National University, Seoul 151-921, Korea.
Kwang-Hyeon ChoDivision of Animal Breeding and Genetics, National Institute of Animal Science, Rural Development Administration, Cheonan 331-801, Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveHolsteins are known as the world's highest-milk producing dairy cattle. The purpose of this study was to identify genetic regions strongly associated with milk traits (milk production, fat, and protein) using Korean Holstein data.

methodsThis study was performed using single nucleotide polymorphism (SNP) chip data (Illumina BovineSNP50 Beadchip) of 911 Korean Holstein individuals. We inferred each genomic estimated breeding values based on best linear unbiased prediction (BLUP) and ridge regression using BLUPF90 and R. We then performed a genome-wide association study and identified genetic regions related to milk traits.

resultsWe identified 9, 6, and 17 significant genetic regions related to milk production, fat and protein, respectively. These genes are newly reported in the genetic association with milk traits of Holstein.

conclusionThis study complements a recent Holstein genome-wide association studies that identified other SNPs and genes as the most significant variants. These results will help to expand the knowledge of the polygenic nature of milk production in Holsteins.

Indexed as

Genome-wide Association Studies (GWAS)Korean HolsteinMilk FatMilk ProductionMilk Protein

Identifiers

PMID26954162
PMCPMC5337909

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.