Evidence map›Paper›PMID 33281874›Full record

ArticleFrontiers in genetics2020

Exploring the Potential Genetic Heterogeneity in the Incidence of Hoof Disorders in Austrian Fleckvieh and Braunvieh Cattle.

Barbara Kosińska-Selbi, Tomasz Suchocki, Christa Egger-Danner, Hermann Schwarzenbacher, Magdalena Frąszczak, Joanna Szyda

Open access · goldAbstract read
In one paragraph

Article in Frontiers in genetics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
0.9field-weighted citation impact, top 22% 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

8 citing papers in PubMed, 12 citations in OpenAlex.

  1. 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 at 2 institutions in 1 country.

Barbara Kosińska-SelbiBiostatistic Group, Department of Genetics, Wrocław University of Environmental and Life Sciences, Wrocław, Poland.
Tomasz SuchockiBiostatistic Group, Department of Genetics, Wrocław University of Environmental and Life Sciences, Wrocław, Poland.
Christa Egger-DannerZuchtData EDV-Dienstleistungen GmbH, Vienna, Austria.
Hermann SchwarzenbacherZuchtData EDV-Dienstleistungen GmbH, Vienna, Austria.
Magdalena FrąszczakBiostatistic Group, Department of Genetics, Wrocław University of Environmental and Life Sciences, Wrocław, Poland.
Joanna SzydaBiostatistic Group, Department of Genetics, Wrocław University of Environmental and Life Sciences, Wrocław, Poland.
Wroclaw University of Environmental and Life Sciences · PLNational Research Institute of Animal Production · PL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Genetic heterogeneity denotes the situation when different genetic architectures underlying diverse populations result in the same phenotype. In this study, we explore the genetic background underlying differences in the incidence of hoof disorders between Braunvieh and Fleckvieh cattle in the context of genetic heterogeneity between the breeds. Despite potentially higher power of testing due to twice as large sample size, none of the SNPs was significantly associated with the total number of hoof disorders in Fleckvieh, while 15 SNPs were significant in Braunvieh. The most promising candidate genes in Braunvieh were as follows:

Indexed as

BraunviehFleckviehgenetic heterogeneityGWAShealth traitslinkage disequilibriumprincipal components

Identifiers

PMID33281874
PMCPMC7705352
OpenAlexW3104111239

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.