Relationship between lactation curve function and phenotypic variance in random regression Test Day models

In Random Regression models (RRM), the most updated version of Test Day (TD) models, the lactation curve is split into a fixed average curve and a random animal specific part (deviation from the average curve) (Schaeffer, 2004). The variance component of the RR coefficients determines the (co) variance function of each pair of days in milk (DIM) (Pool and Meuwissen, 2000). Very different patterns of variance functions have been reported in literature, and several authors pointed out a possible rule of the type of function chosen as RR sub-model and data structure (Kettunen et al., 2000; Meyer, 1998). Aim of this work is to investigate some possible reasons for such results, in particular the effects of the mathematical function and of the possible occurrence of different shapes of lactation curve (regular and atypical)

Effects of Age and Calving Season on Lactation Curves of Milk Production Traits in Italian Water Buffaloes

Test day (TD) records of milk production traits (milk yield, fat, and protein percentages) of 534 Italian buffalo cows were analyzed with a mixed linear model in order to estimate lactation curves pertaining to different ages at calving and different seasons of calving. Milk yield lactation curves of younger animals were lower than those of older animals until 20 wk from parturition. No effect of age at calving could be observed for fat and protein percentages. Season of calving affected milk yield only in the first phase of lactation, with the lowest production levels for summer calvings; no effect could be observed on fat and protein contents. Average correlations among TD measures within lactation were 0.59, 0.31, and 0.36 for milk yield, fat, and protein percentages, respectively. Five standard linear functions of time were able to reconstruct the average lactation curves. Goodness of fit was satisfactory for all models considered, although only the five-parameter model was flexible enough to fit all the three traits considered with excellent results

Microarray data analysis of gene expression levels in lactating cows treated with bovine somatotropin

Administration of bovine somatotropin (bST) to lactating cows results in an increase in milk production from 10 to 15%. While physiological mechanisms involved in bST administration are well known, there is limited knowledge about the mechanisms that regulate the bST action at genetic level. For this reason, a microarray experiment was conducted to identify differentially expressed genes when bST is given to milking cows. Sixteen high-density microarrays for cattle, each containing 18,263 gene spots, were used. RNA was extracted from the mammary tissue of four lactating Holstein cows, five and two days before, and one and six days after bST administration. A total of 1,251 and 1,167 differentially expressed genes were detected for mean and median expression intensities, respectively. Only the 115 genes which were identified by both mean and median intensities were taken into account. These genes were grouped into 8 clusters according to changes in expression through time points

issues and perspectives in dairy sheep breeding

The present review consists of two parts. In the first part, the authors briefly describe the state of the art of breedingprogrammes for Italian dairy sheep; then they report new models for genetic evaluation and consider the problem ofgenotype x environment interaction and the impact of farming systems on the genetic merit of animals. In the secondpart new breeding goals regarding the evolution of milk quality concept and the increasing importance of functional traitsare reported. Regarding milk quality, the authors especially focus on the traits related to cheese-making ability and onthe nutraceutical aspects of milk. Among functional traits, resistance to diseases (mastitis and Scrapie) has been highlightedfor its great importance in livestock species. Finally, the perspectives of marker-assisted selection have also beenreported

Mapping quantitative trait loci (QTL) in sheep. II. Meta-assembly and identification of novel QTL for milk production traits in sheep

An (Awassi × Merino) × Merino backcross family of 172 ewes was used to map quantitative trait loci (QTL) for different milk production traits on a framework map of 200 loci across all autosomes. From five previously proposed mathematical models describing lactation curves, the Wood model was considered the most appropriate due to its simplicity and its ability to determine ovine lactation curve characteristics. Derived milk traits for milk, fat, protein and lactose yield, as well as percentage composition and somatic cell score were used for single and two-QTL approaches using maximum likelihood estimation and regression analysis. A total of 15 significant (P < 0.01) and additional 25 suggestive (P < 0.05) QTL were detected across both single QTL methods and all traits. In preparation of a meta-analysis, all QTL results were compared with a meta-assembly of QTL for milk production traits in dairy ewes from various public domain sources and can be found on the ReproGen ovine gbrowser http://crcidp.vetsci.usyd.edu.au/cgi-bin/gbrowse/oaries_genome/. Many of the QTL for milk production traits have been reported on chromosomes 1, 3, 6, 16 and 20. Those on chromosomes 3 and 20 are in strong agreement with the results reported here. In addition, novel QTL were found on chromosomes 7, 8, 9, 14, 22 and 24. In a cross-species comparison, we extended the meta-assembly by comparing QTL regions of sheep and cattle, which provided strong evidence for synteny conservation of QTL regions for milk, fat, protein and somatic cell score data between cattle and sheep