Evidence map›Paper›PMID 38974678›Full record

ArticleJournal of data mining in genomics & proteomics2024

Large-Sample Genomic Data Mining for Quantitative Traits in U.S. Holstein Cows.

Yang Da, Dzianis Prakapenka, Zuoxiang Liang

Abstract read
In one paragraph

Article in Journal of data mining in genomics & proteomics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

3 authors.

Yang DaDepartment of Animal Science, University of Minnesota, Saint Paul, USA.
Dzianis PrakapenkaDepartment of Animal Science, University of Minnesota, Saint Paul, USA.
Zuoxiang LiangDepartment of Animal Science, University of Minnesota, Saint Paul, USA.

Funding

Genomic discovery and prediction for quantitative traits with complex genetic mechanismsR01HG012425 · NHGRI · UNIVERSITY OF MINNESOTA · PI DA, YANG · 2022 to 2024
$729k
NHGRI NIH HHS R01 HG012425
6 · The paper itself

Abstract

The U.S. Holstein cattle have unprecedentedly large samples for genomic evaluation with genotypes of Single Nucleotide Polymorphism (SNP) markers and phenotypic observations of dairy quantitative traits. Such large samples provided unprecedented opportunities for the discovery of genetic variants and mechanisms affecting quantitative traits in Holstein cattle. Recent studies using the Holstein large samples on finding genetic variants affecting quantitative traits included a fat percentage study and two studies on reproductive traits. The fat percentage study confirmed that a chromosome region interacted with all chromosomes and the reproductive studies detected sharply negative homozygous recessive genotypes that were recommended for heifer culling. These novel findings provided examples showing the power of large-sample genomic mining for quantitative traits.

Indexed as

EpistasisGenomic evaluationSingle nucleotide polymorphism

Identifiers

PMID38974678
PMCPMC11225865

What OpenQuestion holds

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Registered trials

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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.