ABSTRACT
Milking speed is an important trait influencing udder health of dairy cows as well as labor efficiency. Yet, it has received little attention in genomic association studies. The main objective of this study was to determine regions and genes on the genome with a potential effect on milking speed in Fleckvieh (dual purpose Simmental) cattle. Genome-wide association studies were conducted using de-regressed breeding values of bulls as phenotypes. Six SNP on 4 autosomes were significantly associated with milking speed for additive effects. Significant regions on BTA4 and BTA19 correspond with findings for other dairy cattle breeds. Based on the observation of Fleckvieh breed managers, variation of milking speed in batches of daughters of some bulls is much higher than in daughter groups of other bulls. This difference in within family variation may be caused by transmission of alternative alleles of bulls being heterozygous for a gene affecting milking speed. To check on this, we considered standard deviation of yield deviations in milking speed of half-sib daughters as a new trait and performed GWAS for dominance effects. One signal on BTA5 passed the genome wide Bonferroni threshold that corresponded to the significant signal from standard GWAS on de-regressed breeding values. The key conclusion of this study is that several strong genomic signals were found for milking speed in Fleckvieh cattle and that the strongest of them are supported by similar findings in Brown Swiss and Holstein Friesian cattle. Milking speed is a complex trait whose sub-processes have not yet been elucidated in detail. Hence, it remains a challenge to link the associated regions on the genome with causal genes and their functions.
ABSTRACT
A comprehensive dynamic simulation model was developed to describe a community-based breeding program for the Menz sheep population of Ethiopia. Selection of male and female animals based on their own and maternal performance was simulated. The breeding goal traits were 6-mo weight, preweaning survival, and fertility rate. The model input data were obtained from the flock book, questionnaires, and references. The simulation model used a mix of deterministic and stochastic procedures to model the complex system. In the baseline scenario, the proportion of selected male and female animals varied between 20 and 30% and between 70 and 80%, respectively. A reasonable annual genetic gain was predicted for the breeding goal traits at the village level. For 6-mo weight and preweaning survival rate, the annual genetic gain varied from 0.213 to 0.214 kg and 0.255 to 0.256%, respectively. For fertility rate, an annual genetic gain of 0.063% was obtained. The predicted rate of inbreeding per year was between 0.094 and 0.116%. Furthermore, a scenario analysis was conducted by varying the proportions of selected animals. Annual genetic gains of 0.230 kg, 0.277%, and 0.069% were obtained for 6-mo weight, preweaning survival rate, and fertility rate, respectively, when the proportion of selected male and female animals decreased by 10%. The annual genetic gains decreased to 0.198 kg, 0.236%, and 0.059%, respectively, when the selection proportion of male and female animals increased by 10%. The lowest rate of inbreeding per year, ranging from 0.065 to 0.079%, was achieved when the selection proportion of selected male and female animals increased. The model is relevant for the step-by-step evaluation of more than one round of selection. It is flexible and usage driven. The model is a valuable tool to design different population structures and can be easily expanded to adopt different breeding strategies. Hence, the system dynamics modeling approach is a potential tool to describe complex breeding programs.
