scholarly journals Analysis of Growth Performance Data in Sidama Goats using Fixed and Random Regression Models

Author(s):  
Kefelegn K
2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Ellie J. Putz ◽  
Austin M. Putz ◽  
Hyeongseon Jeon ◽  
John D. Lippolis ◽  
Hao Ma ◽  
...  

AbstractIn dairy cows, the period from the end of lactation through the dry period and into the transition period, requires vast physiological and immunological changes critical to mammary health. The dry period is important to the success of the next lactation and intramammary infections during the dry period will adversely alter mammary function, health and milk production for the subsequent lactation. MicroRNAs (miRNAs) are small non-coding RNAs that can post transcriptionally regulate gene expression. We sought to characterize the miRNA profile in dry secretions from the last day of lactation to 3, 10, and 21 days post dry-off. We identified 816 known and 80 novel miRNAs. We found 46 miRNAs whose expression significantly changed (q-value < 0.05) over the first three weeks of dry-off. Additionally, we examined the slopes of random regression models of log transformed normalized counts and cross analyzed the 46 significantly upregulated and downregulated miRNAs. These miRNAs were found to be associated with important components of pregnancy, lactation, as well as inflammation and disease. Detailing the miRNA profile of dry secretions through the dry-off period provides insight into the biology at work, possible means of regulation, components of resistance and/or susceptibility, and outlets for targeted therapy development.


2017 ◽  
Vol 47 (5) ◽  
Author(s):  
Priscila Becker Ferreira ◽  
Paulo Roberto Nogara Rorato ◽  
Fernanda Cristina Breda ◽  
Vanessa Tomazetti Michelotti ◽  
Alexandre Pires Rosa ◽  
...  

ABSTRACT: This study aimed to test different genotypic and residual covariance matrix structures in random regression models to model the egg production of Barred Plymouth Rock and White Plymouth Rock hens aged between 5 and 12 months. In addition, we estimated broad-sense heritability, and environmental and genotypic correlations. Six random regression models were evaluated, and for each model, 12 genotypic and residual matrix structures were tested. The random regression model with linear intercept and unstructured covariance (UN) for a matrix of random effects and unstructured correlation (UNR) for residual matrix adequately model the egg production curve of hens of the two study breeds. Genotypic correlations ranged from 0.15 (between age of 5 and 12 months) to 0.99 (between age of 10 and 11 months) and increased based on the time elapsed. Egg production heritability between 5- and 12-month-old hens increased with age, varying from 0.15 to 0.51. From the age of 9 months onward, heritability was moderate with estimates of genotypic correlations higher than 90% at the age of 10, 11, and 12 months. Results suggested that selection of hens to improve egg production should commence at the ninth month of age.


2013 ◽  
Vol 12 (1) ◽  
pp. 143-153 ◽  
Author(s):  
D.J.A. Santos ◽  
M.G.C.D. Peixoto ◽  
R.R. Aspilcueta Borquis ◽  
R.S. Verneque ◽  
J.C.C. Panetto ◽  
...  

2018 ◽  
Vol 135 (4) ◽  
pp. 275-285
Author(s):  
Kristina Schlicht ◽  
Nina Krattenmacher ◽  
Vincent Lugert ◽  
Carsten Schulz ◽  
Georg Thaller ◽  
...  

2004 ◽  
Vol 87 (6) ◽  
pp. 1917-1924 ◽  
Author(s):  
E. Norberg ◽  
G.W. Rogers ◽  
R.C. Goodling ◽  
J.B. Cooper ◽  
P. Madsen

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