Utilisation of genetic variation by marker assisted selection in commercial dairy cattle populations

1999 ◽  
Vol 59 (1) ◽  
pp. 51-60 ◽  
Author(s):  
R.J. Spelman ◽  
D.J. Garrick ◽  
J.A.M. van Arendonk
2003 ◽  
Vol 52 (6) ◽  
pp. 489-500 ◽  
Author(s):  
Yves Barrière ◽  
Jean-Claude Emile ◽  
Fabien Surault

1977 ◽  
Vol 28 (6) ◽  
pp. 1107 ◽  
Author(s):  
ND Herron ◽  
WA Pattie

The structure of the pedigree Australian Illawarra Shorthorn breed in Australia was analysed by using registration data from the Society's Herd Books. The breed may be divided into three broad levels, namely, Breeders' Herds, Multipliers' Herds and Grade (unregistered) Herds. Of the registered herds, 32% are Breeders' Herds and the remainder are Multipliers' Herds. These are each subdivided into four strata depending on their importance as a source of breeding material, and on their registration practices respectively. Of major importance is the highest stratum of the breed. It comprised only 13.6% of all herds, but accounted for 40.5% of male and 24.8% of female registrations. There is a high ratio of females to males registered of 5.9, which indicates considerable selective registration of males. The degree of this selective registration generally increases at the lower strata, ranging from 3.6 at the top of the structure to 8.7 toward the bottom of the structure. Of all new herds initiated from 1931 to 1971, 44% survived less than 5 years. These short-lived herds averaged only 3.3 female registrations per year, but herd size increased as longevity increased. These points highlight the instability of new, small studs, and indicate that few herds are big enough, or exist for long enough, to contribute significantly to breed improvement. It is not likely that there is much genetic variation between herds. Bulls from major breeders' herds are used widely throughout the breed, while 68% of sires and 24% of dams are bred in herds other than the one in which they were used.


2008 ◽  
Vol 91 (4) ◽  
pp. 1628-1639 ◽  
Author(s):  
S. Ansari-Mahyari ◽  
A.C. Sørensen ◽  
M.S. Lund ◽  
H. Thomsen ◽  
P. Berg

2013 ◽  
Vol 4 (3) ◽  
pp. 606-611 ◽  
Author(s):  
E. Strandberg ◽  
M. Felleki ◽  
W. F. Fikse ◽  
J. Franzén ◽  
H. A. Mulder ◽  
...  

This work was part of the EU RobustMilk project. In this work package, we have focused on two aspects of robustness, micro- and macro-environmental sensitivity and applied these to somatic cell count (SCC), one aspect of milk quality. We showed that it is possible to combine both categorical and continuous descriptions of the environment in one analysis of genotype by environment interaction. We also developed a method to estimate genetic variation in residual variance and applied it to both simulated and a large field data set of dairy cattle. We showed that it is possible to estimate genetic variation in both micro- and macro-environmental sensitivity in the same data, but that there is a need for good data structure. In a dairy cattle example, this would mean at least 100 bulls with at least 100 daughters each. We also developed methods for improved genetic evaluation of SCC. We estimated genetic variance for some alternative SCC traits, both in an experimental herd data and in field data. Most of them were highly correlated with subclinical mastitis (>0.9) and clinical mastitis (0.7 to 0.8), and were also highly correlated with each other. We studied whether the fact that animals in different herds are differentially exposed to mastitis pathogens could be a reason for the low heritabilities for mastitis, but did not find strong evidence for that. We also created a new model to estimate breeding values not only for the probability of getting mastitis but also for recovering from it. In a progeny-testing situation, this approach resulted in accuracies of 0.75 and 0.4 for these two traits, respectively, which means that it is possible to also select for cows that recover more quickly if they get mastitis.


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