Correlations between mitochondrial respiration activity and residual feed intake after divergent genetic selection for high‐ and low‐ oxygen consumption in mice

2019 ◽  
Vol 90 (7) ◽  
pp. 818-826
Author(s):  
Hongyu Darhan ◽  
Atsushi Zoda ◽  
Motoi Kikusato ◽  
Masaaki Toyomizu ◽  
Kazuo Katoh ◽  
...  
1997 ◽  
Vol 127 (12) ◽  
pp. 2371-2376 ◽  
Author(s):  
Jean-François Gabarrou ◽  
Pierre-André Géraert ◽  
Michel Picard ◽  
André Bordas

2014 ◽  
Vol 159 ◽  
pp. 34-40 ◽  
Author(s):  
Jessica D. Colpoys ◽  
Caitlyn E. Abell ◽  
Jennifer M. Young ◽  
Aileen F. Keating ◽  
Nicholas K. Gabler ◽  
...  

2021 ◽  
Vol 12 ◽  
Author(s):  
Aidin Foroutan ◽  
David S. Wishart ◽  
Carolyn Fitzsimmons

Approximately 70% of the cost of beef production is impacted by dietary intake. Maximizing production efficiency of beef cattle requires not only genetic selection to maximize feed efficiency (i.e., residual feed intake (RFI)), but also adequate nutrition throughout all stages of growth and development to maximize efficiency of growth and reproductive capacity, even during gestation. RFI as a measure of feed efficiency in cattle has been recently accepted and used in the beef industry, but the effect of selection for RFI upon the dynamics of gestation has not been extensively studied, especially in the context of fluctuating energy supply to the dam and fetus. Nutrient restriction during gestation has been shown to negatively affect postnatal growth and development as well as fertility of beef cattle offspring. This, when combined with the genetic potential for RFI, may significantly affect energy partitioning in the offspring and subsequently important performance traits. In this review, we discuss: 1) the importance of RFI as a measure of feed efficiency and how it can affect other economic traits in beef cattle; 2) the influence of prenatal nutrition on physiological phenotypes in calves; 3) the benefits of investigating the interaction of genetic selection for RFI and prenatal nutrition; 4) how metabolomics, transcriptomics, and epigenomics have been employed to investigate the underlying biology associated with prenatal nutrition, RFI, or their interactions in beef cattle; and 5) how the integration of omics information is adding a level of deeper understanding of the genetic architecture of phenotypic traits in cattle.


2013 ◽  
Vol 91 (5) ◽  
pp. 2133-2140 ◽  
Author(s):  
J. K. Grubbs ◽  
A. N. Fritchen ◽  
E. Huff-Lonergan ◽  
J. C. M. Dekkers ◽  
N. K. Gabler ◽  
...  

2011 ◽  
Vol 89 (1) ◽  
pp. 258-266 ◽  
Author(s):  
L. J. Sadler ◽  
A. K. Johnson ◽  
S. M. Lonergan ◽  
D. Nettleton ◽  
J. C. M. Dekkers

2016 ◽  
Vol 94 (suppl_2) ◽  
pp. 108-109 ◽  
Author(s):  
D. J. Hewitt ◽  
C. F. M. de Lange ◽  
T. Antonick ◽  
J. C. M. Dekkers ◽  
A. R. Pendleton ◽  
...  

2016 ◽  
Vol 88 (7) ◽  
pp. 959-965 ◽  
Author(s):  
Hongyu Darhan ◽  
Motoi Kikusato ◽  
Masaaki Toyomizu ◽  
Sang-gun Roh ◽  
Kazuo Katoh ◽  
...  

2001 ◽  
Vol 41 (7) ◽  
pp. 1057 ◽  
Author(s):  
D. L. Robinson ◽  
V. H. Oddy

In Australia, a trait under consideration for genetic selection to improve feed efficiency is residual feed intake (RFI), which is defined as the amount of feed eaten by an animal less what would be expected from the animal’s growth rate and body weight. Accurate estimates of RFI therefore require accurate estimates of weight gain. Results presented here on steers finished in a feedlot to liveweights of 540 or 600 kg show that, when feed intake is being measured, weight gain can be estimated more accurately using the amount of feed eaten in the previous 3–5 days (as an adjustment for gut fill) than if feed eaten in the 80 h before weighing is ignored. This is demonstrated by a much lower residual mean square from modelling the weight of each animal as a quadratic growth curve over time if terms are included for feed eaten on the current and previous 3–5 days. An analysis of measurement errors associated with fitting the equation used to calculate RFI: Feed intake = constant + βw x mean metabolic weight + βg x weight gain + error (i.e. RFI) (1) indicates that the relatively high measurement errors associated with weight gain but comparatively low measurement errors associated with metabolic weight will result in upward biases in the partial regression coefficient βw and downward biases in βg. For example, in a 105-day feed intake test of 44 steers (mean start/end weights 440/600 kg), the estimate of βg was 1.26 based on weight gain estimated by a simple linear regression of each animal’s weight over time (LIN), compared with 2.20 using weight gain estimated from the difference between first and last weight of each animal adjusted for the amount of feed eaten on the current and previous 5 days (DIFFadj). From a shorter test, based on weight gains from day 15 to 50 in the automatic feeder pens, the estimate of βg was 0.40 using LIN and 1.67 using DIFFadj. These results illustrate the potential magnitude of the downward bias in βg if inaccurate estimates of weight gain are used to fit equation 1. The higher estimates for βg obtained using DIFFadj may still have some downward bias but are closer to the theoretical values published by SCA (1990) for the amount of metabolisable energy required for weight gain. Adjusting for the amount of feed eaten before weighing therefore increased the accuracy of estimated weight gain and reduced the biases in βg and βw, so providing better and more stable estimates of residual feed intake.


2016 ◽  
Vol 95 (9) ◽  
pp. 1999-2010 ◽  
Author(s):  
L. Drouilhet ◽  
R. Monteville ◽  
C. Molette ◽  
M. Lague ◽  
A. Cornuez ◽  
...  

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