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

Overview of attention for article published in BMC Genomics, March 2017
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Title
RNA-Seq transcriptomics and pathway analyses reveal potential regulatory genes and molecular mechanisms in high- and low-residual feed intake in Nordic dairy cattle
Published in
BMC Genomics, March 2017
DOI 10.1186/s12864-017-3622-9
Pubmed ID
Authors

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

Abstract

The 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. The 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. We 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.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 116 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 116 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 27 23%
Student > Master 16 14%
Researcher 13 11%
Student > Bachelor 11 9%
Student > Doctoral Student 8 7%
Other 16 14%
Unknown 25 22%
Readers by discipline Count As %
Agricultural and Biological Sciences 50 43%
Biochemistry, Genetics and Molecular Biology 12 10%
Veterinary Science and Veterinary Medicine 8 7%
Medicine and Dentistry 4 3%
Pharmacology, Toxicology and Pharmaceutical Science 2 2%
Other 8 7%
Unknown 32 28%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 12 September 2017.
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#20,411,380
of 22,961,203 outputs
Outputs from BMC Genomics
#9,311
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Outputs of similar age
#269,574
of 309,205 outputs
Outputs of similar age from BMC Genomics
#166
of 200 outputs
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