Evidence map›Paper›PMID 30344530›Full record

ArticleFrontiers in genetics2018

Gene Co-expression Analysis Indicates Potential Pathways and Regulators of Beef Tenderness in Nellore Cattle.

Tássia Mangetti Gonçalves, Luciana Correia de Almeida Regitano, James E Koltes, Aline Silva Mello Cesar, Sónia Cristina da Silva Andrade, Gerson Barreto Mourão, Gustavo Gasparin, Gabriel Costa Monteiro Moreira, Elyn Fritz-Waters, James M Reecy and 1 more

Open access · goldAbstract read
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 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed
4.2field-weighted citation impact, top 6% 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

22 citing papers in PubMed, 47 citations in OpenAlex.

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  15. USP2-Related Cellular Signaling and Consequent Pathophysiological Outcomes.International journal of molecular sciences · 2021
    Review
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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

11 authors at 3 institutions in 2 countries.

Tássia Mangetti GonçalvesDepartment of Animal Science, University of São Paulo, Piracicaba, Brazil.
Luciana Correia de Almeida RegitanoEmbrapa Southeast-Cattle Research Center, São Carlos, Brazil.
James E KoltesDepartment of Animal Science, Iowa State University, Ames, IA, United States.
Aline Silva Mello CesarDepartment of Animal Science, University of São Paulo, Piracicaba, Brazil.
Sónia Cristina da Silva AndradeDepartment of Animal Science, University of São Paulo, Piracicaba, Brazil.
Gerson Barreto MourãoDepartment of Animal Science, University of São Paulo, Piracicaba, Brazil.
Gustavo GasparinDepartment of Animal Science, University of São Paulo, Piracicaba, Brazil.
Gabriel Costa Monteiro MoreiraDepartment of Animal Science, University of São Paulo, Piracicaba, Brazil.
Elyn Fritz-WatersDepartment of Animal Science, Iowa State University, Ames, IA, United States.
James M ReecyDepartment of Animal Science, Iowa State University, Ames, IA, United States.
Luiz Lehmann CoutinhoDepartment of Animal Science, University of São Paulo, Piracicaba, Brazil.
Universidade de São Paulo · BRIowa State University · USBrazilian Agricultural Research Corporation · BR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Beef tenderness, a complex trait affected by many factors, is economically important to beef quality, industry, and consumer's palatability. In this study, RNA-Seq was used in network analysis to better understand the biological processes that lead to differences in beef tenderness. Skeletal muscle transcriptional profiles from 24 Nellore steers, selected by extreme estimated breeding values (EBVs) for shear force after 14 days of aging, were analyzed and 22 differentially expressed transcripts were identified. Among these were genes encoding ribosomal proteins, glutathione transporter ATP-binding cassette, sub-family C (CFTR/MRP), member 4 (

Indexed as

bovinemeatmicroRNAnetworksRNA-Seqtranscriptome

Identifiers

PMID30344530
PMCPMC6182065
OpenAlexW2891811141

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.