Evidence map›Paper›PMID 29866053›Full record

ArticleBMC genomics2018

RNA-Seq Meta-analysis identifies genes in skeletal muscle associated with gain and intake across a multi-season study of crossbred beef steers.

Brittney N Keel, Christina M Zarek, John W Keele, Larry A Kuehn, Warren M Snelling, William T Oliver, Harvey C Freetly, Amanda K Lindholm-Perry

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC genomics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed, 2 pooled it
3.1field-weighted citation impact, top 8% 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

21 citing papers in PubMed, 2 syntheses or guidelines pooled it, 33 citations in OpenAlex.

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  12. RNA-Seq Analysis Identifies Differentially Expressed Genes in theInternational journal of molecular sciences · 2022
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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

8 authors at 2 institutions in 1 country.

Brittney N KeelUSDA, ARS, U.S. Meat Animal Research Center, Clay Center, NE, 68933, USA.
Christina M ZarekUSDA, ARS, U.S. Meat Animal Research Center, Clay Center, NE, 68933, USA.
John W KeeleUSDA, ARS, U.S. Meat Animal Research Center, Clay Center, NE, 68933, USA.
Larry A KuehnUSDA, ARS, U.S. Meat Animal Research Center, Clay Center, NE, 68933, USA.
Warren M SnellingUSDA, ARS, U.S. Meat Animal Research Center, Clay Center, NE, 68933, USA.
William T OliverUSDA, ARS, U.S. Meat Animal Research Center, Clay Center, NE, 68933, USA.
Harvey C FreetlyUSDA, ARS, U.S. Meat Animal Research Center, Clay Center, NE, 68933, USA.
Amanda K Lindholm-PerryUSDA, ARS, U.S. Meat Animal Research Center, Clay Center, NE, 68933, USA. amanda.lindholm@ars.usda.gov.ORCID http://orcid.org/0000-0002-5555-118X
Roman L. Hruska U.S. Meat Animal Research Center · USSouthwestern Medical Center · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundFeed intake and body weight gain are economically important inputs and outputs of beef production systems. The purpose of this study was to discover differentially expressed genes that will be robust for feed intake and gain across a large segment of the cattle industry. Transcriptomic studies often suffer from issues with reproducibility and cross-validation. One way to improve reproducibility is by integrating multiple datasets via meta-analysis. RNA sequencing (RNA-Seq) was performed on longissimus dorsi muscle from 80 steers (5 cohorts, each with 16 animals) selected from the outside fringe of a bivariate gain and feed intake distribution to understand the genes and pathways involved in feed efficiency. In each cohort, 16 steers were selected from one of four gain and feed intake phenotypes (n = 4 per phenotype) in a 2 × 2 factorial arrangement with gain and feed intake as main effect variables. Each cohort was analyzed as a single experiment using a generalized linear model and results from the 5 cohort analyses were combined in a meta-analysis to identify differentially expressed genes (DEG) across the cohorts.

resultsA total of 51 genes were differentially expressed for the main effect of gain, 109 genes for the intake main effect, and 11 genes for the gain x intake interaction (P

conclusionsVariation among DEG identified by cohort suggests that environment and breed may play large roles in the expression of genes associated with feed efficiency in the muscle of beef cattle. Meta-analyses of transcriptome data from groups of animals over multiple cohorts may be necessary to elucidate the genetics contributing these types of biological phenotypes.

Indexed as

Hybridization, GeneticRed MeatSeasonsSequence Analysis, RNAAnimal FeedAnimalsCattleEatingMaleMuscle, SkeletalBeef cattleDifferential expressionFeed efficiencyMeta-analysisRNA-SeqTranscriptome

Identifiers

PMID29866053
PMCPMC5987596
OpenAlexW2807407168

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.