Evidence map›Paper›PMID 30459810›Full record

ArticleFrontiers in genetics2018

A Meta-Analysis Including Pre-selected Sequence Variants Associated With Seven Traits in Three French Dairy Cattle Populations.

Andrew G Marete, Bernt Guldbrandtsen, Mogens S Lund, Sébastien Fritz, Goutam Sahana, Didier Boichard

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In one paragraph

Article in Frontiers in genetics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed, 1 pooled it
–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

18 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Genome-wide association study identifies significant SNPs for milk production and stature traits in Karan Fries cattle.Mammalian genome : official journal of the International Mammalian Genome Society · 2026
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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

6 authors.

Andrew G MareteUMR GABI, INRA, AgroParisTech, Université Paris Saclay, 78350 Jouy en Josas, France.
Bernt GuldbrandtsenCenter for Quantitative Genetics and Genomics, Aarhus University, Aarhus, Denmark.
Mogens S LundCenter for Quantitative Genetics and Genomics, Aarhus University, Aarhus, Denmark.
Sébastien FritzUMR GABI, INRA, AgroParisTech, Université Paris Saclay, 78350 Jouy en Josas, France.
Goutam SahanaCenter for Quantitative Genetics and Genomics, Aarhus University, Aarhus, Denmark.
Didier BoichardUMR GABI, INRA, AgroParisTech, Université Paris Saclay, 78350 Jouy en Josas, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A within-breed genome-wide association study (GWAS) is useful when identifying the QTL that segregates in a breed. However, an across-breed meta-analysis can be used to increase the power of identification and precise localization of QTL that segregate in multiple breeds. Precise localization will allow including QTL information from other breeds in genomic prediction due to the persistence of the linkage phase between the causal variant and the marker. This study aimed to identify and confirm QTL detected in within-breed GWAS through a meta-analysis in three French dairy cattle breeds. A set of sequence variants selected based on their functional annotations were imputed into 50 k genotypes for 46,732 Holstein, 20,096 Montbeliarde, and 11,944 Normande cows to identify QTL for milk production, the success rate at insemination of cows (fertility) and stature. We conducted within-breed GWAS followed by across-breed meta-analysis using a weighted Z-scores model on the GWAS summary data (i.e.,

Indexed as

candidate genescandidate SNPGWASmeta-analysissequence imputation

Identifiers

PMID30459810
PMCPMC6232291

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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.