Evidence map›Paper›PMID 28340555›Full record

ArticleBMC genomics2017

RNA-Seq transcriptomics and pathway analyses reveal potential regulatory genes and molecular mechanisms in high- and low-residual feed intake in Nordic dairy cattle.

M S Salleh, G Mazzoni, J K Höglund, D W Olijhoek, P Lund, P Løvendahl, H N Kadarmideen

Open access · goldAbstract read
In one paragraph

Article in BMC genomics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
42citing papers in PubMed, 2 pooled it
4.9field-weighted citation impact, top 3% 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

42 citing papers in PubMed, 2 syntheses or guidelines pooled it, 113 citations in OpenAlex.

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  17. Interference WithFrontiers in veterinary science · 2021
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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

7 authors at 3 institutions in 1 country.

M S SallehAnimal Breeding, Quantitative Genetics and Systems Biology Group, Department of Veterinary and Animal Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, DK-1870, Frederiksberg C, Denmark.
G MazzoniAnimal Breeding, Quantitative Genetics and Systems Biology Group, Department of Veterinary and Animal Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, DK-1870, Frederiksberg C, Denmark.
J K HöglundDepartment of Molecular Biology and Genetics - Center for Quantitative Genetics and Genomics, Aarhus University, AU Foulum, DK-8830, Tjele, Denmark.
D W OlijhoekDepartment of Molecular Biology and Genetics - Center for Quantitative Genetics and Genomics, Aarhus University, AU Foulum, DK-8830, Tjele, Denmark.
P LundDepartment of Animal Science - Animal Nutrition and Physiology, Aarhus University, AU Foulum, DK-8830, Tjele, Denmark.
P LøvendahlDepartment of Molecular Biology and Genetics - Center for Quantitative Genetics and Genomics, Aarhus University, AU Foulum, DK-8830, Tjele, Denmark.
H N KadarmideenDepartment of Bio and Health Informatics, Technical University of Denmark, DK-2800, Kgs. Lyngby, Denmark. hajak@dtu.dk.
Aarhus University · DKUniversity of Copenhagen · DKTechnical University of Denmark · DK

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe selective breeding of cattle with high-feed efficiencies (FE) is an important goal of beef and dairy cattle producers. Global gene expression patterns in relevant tissues can be used to study the functions of genes that are potentially involved in regulating FE. In the present study, high-throughput RNA sequencing data of liver biopsies from 19 dairy cows were used to identify differentially expressed genes (DEGs) between high- and low-FE groups of cows (based on Residual Feed Intake or RFI). Subsequently, a profile of the pathways connecting the DEGs to FE was generated, and a list of candidate genes and biomarkers was derived for their potential inclusion in breeding programmes to improve FE.

resultsThe bovine RNA-Seq gene expression data from the liver was analysed to identify DEGs and, subsequently, identify the molecular mechanisms, pathways and possible candidate biomarkers of feed efficiency. On average, 57 million reads (short reads or short mRNA sequences < ~200 bases) were sequenced, 52 million reads were mapped, and 24,616 known transcripts were quantified according to the bovine reference genome. A comparison of the high- and low-RFI groups revealed 70 and 19 significantly DEGs in Holstein and Jersey cows, respectively. The interaction analysis (high vs. low RFI x control vs. high concentrate diet) showed no interaction effects in the Holstein cows, while two genes showed interaction effects in the Jersey cows. The analyses showed that DEGs act through certain pathways to affect or regulate FE, including steroid hormone biosynthesis, retinol metabolism, starch and sucrose metabolism, ether lipid metabolism, arachidonic acid metabolism and drug metabolism cytochrome P450.

conclusionWe used RNA-Seq-based liver transcriptomic profiling of high- and low-RFI dairy cows in two breeds and identified significantly DEGs, their molecular mechanisms, their interactions with other genes and functional enrichments of different molecular pathways. The DEGs that were identified were the CYP's and GIMAP genes for the Holstein and Jersey cows, respectively, which are related to the primary immunodeficiency pathway and play a major role in feed utilization and the metabolism of lipids, sugars and proteins.

Indexed as

Animal FeedAnimal Nutritional Physiological PhenomenaGene Expression ProfilingGene Expression RegulationSignal TransductionTranscriptomeAnimalsBreedingCattleChromosome MappingCluster AnalysisGene Regulatory NetworksGenes, RegulatorHigh-Throughput Nucleotide SequencingLiverDairy cattleDifferentially expressed genesFeed efficiencyPathwaysResidual feed intakeRNA-Seq

Identifiers

PMID28340555
PMCPMC5366136
OpenAlexW2603613888

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.