scholarly journals Transcriptome analysis of mRNA and miRNA in skeletal muscle indicates an important network for differential Residual Feed Intake in pigs

2015 ◽  
Vol 5 (1) ◽  
Author(s):  
Lu Jing ◽  
Ye Hou ◽  
Hui Wu ◽  
Yuanxin Miao ◽  
Xinyun Li ◽  
...  
2020 ◽  
Vol 39 (3) ◽  
pp. 404-416 ◽  
Author(s):  
Xinhua Hou ◽  
Lei Pu ◽  
Ligang Wang ◽  
Xin Liu ◽  
Hongmei Gao ◽  
...  

2020 ◽  
Author(s):  
Clare McKenna ◽  
Kate Keogh ◽  
Richard Porter ◽  
Sinead Waters ◽  
Paul Cormican ◽  
...  

Abstract The selection of cattle with enhanced feed efficiency is of paramount importance with regard to reducing feed costs in the beef industry. Global transcriptome profiling was undertaken on liver and skeletal muscle biopsies from Simmental heifers and bulls divergent in residual feed intake (RFI) feed efficiency phenotype, in order to identify genes that may be associated with this trait. We identified 5 genes (adj.p<0.1) to be differentially expressed in skeletal muscle between high and low RFI heifers with all transcripts involved in oxidative phosphorylation and mitochondrial homeostasis. A total of 11 genes (adj.p<0. 1) were differentially expressed in liver tissue between high and low RFI bulls with differentially expressed genes related to amino and nucleotide metabolism as well as endoplasmic reticulum protein processing. No genes were identified as differentially expressed in either heifer liver or bull muscle analyses. Results from this study show a clear effect of gender to the underlying molecular control of RFI in cattle, which may be attributable to differences in the physiological age between heifers and bulls. Despite this we have highlighted a number of genes that may hold potential as molecular biomarkers for RFI cattle.


2021 ◽  
Author(s):  
Amanda C Outhouse ◽  
Brian M Patterson ◽  
Edward M;. Steadham ◽  
Elisabeth J. Huff-Lonergan ◽  
Emma T Helm ◽  
...  

2016 ◽  
Vol 94 (suppl_4) ◽  
pp. 63-64 ◽  
Author(s):  
J. Horodyska ◽  
M. Oster ◽  
K. Wimmers ◽  
A. M. Mullen ◽  
P. G. Lawlor ◽  
...  

2018 ◽  
Vol 8 (1) ◽  
Author(s):  
Priscila S. N. De Oliveira ◽  
Luiz L. Coutinho ◽  
Polyana C. Tizioto ◽  
Aline S. M. Cesar ◽  
Gabriella B. de Oliveira ◽  
...  

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Clare McKenna ◽  
Kate Keogh ◽  
Richard K. Porter ◽  
Sinead M. Waters ◽  
Paul Cormican ◽  
...  

AbstractThe selection of cattle with enhanced feed efficiency is of importance with regard to reducing feed costs in the beef industry. Global transcriptome profiling was undertaken on liver and skeletal muscle biopsies from Simmental heifers and bulls divergent for residual feed intake (RFI), a widely acknowledged feed efficiency phenotype, in order to identify genes that may be associated with this trait. We identified 5 genes (adj. p < 0.1) to be differentially expressed in skeletal muscle between high and low RFI heifers with all transcripts involved in oxidative phosphorylation and mitochondrial homeostasis. A total of 11 genes (adj. p < 0. 1) were differentially expressed in liver tissue between high and low RFI bulls with differentially expressed genes related to amino and nucleotide metabolism as well as endoplasmic reticulum protein processing. No genes were identified as differentially expressed in either heifer liver or bull muscle analyses. Results from this study show that the molecular control of RFI in young cattle is modified according to gender, which may be attributable to differences in physiological maturity between heifers and bulls of the same age. Despite this we have highlighted a number of genes that may hold potential as molecular biomarkers for RFI cattle.


animal ◽  
2020 ◽  
Vol 14 (8) ◽  
pp. 1710-1717
Author(s):  
C. McKenna ◽  
R.K. Porter ◽  
C. Fitzsimons ◽  
S.M. Waters ◽  
M. McGee ◽  
...  

BMC Genomics ◽  
2019 ◽  
Vol 20 (1) ◽  
Author(s):  
Elisa B. Carvalho ◽  
Mateus P. Gionbelli ◽  
Rafael T. S. Rodrigues ◽  
Sarah F. M. Bonilha ◽  
Charles J. Newbold ◽  
...  

2018 ◽  
Vol 2 (2) ◽  
pp. 171-171
Author(s):  
B. M. Patterson ◽  
A. C. Outhouse ◽  
E. T. Helm ◽  
J. C. M. Dekkers ◽  
K. J. Schwartz ◽  
...  

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