Evidence map›Paper›PMID 23943656›Full record

ArticleBioinformatics and biology insights2013

Bioinformatics analysis of transcriptome dynamics during growth in angus cattle longissimus muscle.

Sonia J Moisá, Daniel W Shike, Daniel E Graugnard, Sandra L Rodriguez-Zas, Robin E Everts, Harris A Lewin, Dan B Faulkner, Larry L Berger, Juan J Loor

Open access · goldAbstract read
In one paragraph

Article in Bioinformatics and biology insights, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
0.7field-weighted citation impact, top 28% 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

11 citing papers in PubMed, 19 citations in OpenAlex.

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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

9 authors at 2 institutions in 1 country.

Sonia J MoisáMammalian NutriPhysioGenomics, Department of Animal Sciences, University of Illinois, Urbana, Illinois, USA. ; Division of Nutritional Sciences, University of Illinois, Urbana, Illinois USA.
Daniel W Shike
Daniel E Graugnard
Sandra L Rodriguez-Zas
Robin E Everts
Harris A Lewin
Dan B Faulkner
Larry L Berger
Juan J Loor
University of Illinois Urbana-Champaign · USUniversity of Nebraska–Lincoln · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Transcriptome dynamics in the longissimus muscle (LM) of young Angus cattle were evaluated at 0, 60, 120, and 220 days from early-weaning. Bioinformatic analysis was performed using the dynamic impact approach (DIA) by means of Kyoto Encyclopedia of Genes and Genomes (KEGG) and Database for Annotation, Visualization and Integrated Discovery (DAVID) databases. Between 0 to 120 days (growing phase) most of the highly-impacted pathways (eg, ascorbate and aldarate metabolism, drug metabolism, cytochrome P450 and Retinol metabolism) were inhibited. The phase between 120 to 220 days (finishing phase) was characterized by the most striking differences with 3,784 differentially expressed genes (DEGs). Analysis of those DEGs revealed that the most impacted KEGG canonical pathway was glycosylphosphatidylinositol (GPI)-anchor biosynthesis, which was inhibited. Furthermore, inhibition of calpastatin and activation of tyrosine aminotransferase ubiquitination at 220 days promotes proteasomal degradation, while the concurrent activation of ribosomal proteins promotes protein synthesis. Therefore, the balance of these processes likely results in a steady-state of protein turnover during the finishing phase. Results underscore the importance of transcriptome dynamics in LM during growth.

Indexed as

growthintramuscular fatlongissimus musclenutrition

Identifiers

PMID23943656
PMCPMC3738383
OpenAlexW2069419824

What OpenQuestion holds

Textmetadata
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.