Estimated breeding values and association mapping for persistency and total milk yield using natural cubic smoothing splines

It has been shown that Natural Cubic Smoothing Splines (NCSS) can model the features of lactation curves with greater flexibility than the traditional parametric methods. NCSS were used to model the sire effect on the lactation curves of cows. The sire solutions for persistency and total milk yield were derived using NCSS and a whole-genome approach based on a hierarchical model was developed for a large association study using single nucleotide polymorphisms (SNP).Estimated sire breeding values (EBV) for persistency and milk yield were calculated using NCSS. Persistency EBV were correlated with peak yield but not with total milk yield. Several SNP were found to be associated with both traits and these were used to identify candidate genes for further investigation.NCSS can be used to estimate EBV for lactation persistency and total milk yield, which in turn can be used in whole-genome association studies.For dairy producers, the accurate description of lactation curves is a valuable tool for selection and management. Lactation curves provide a description of milk yield performance, which make it possible to predict total milk yield from a single or several test days early in lactation. Thus, producers can make early management decisions based on the predicted individual production. Different mathematical equations have been proposed to model lactation curves. Usually such curves are modelled using parametric models with fixed or random coefficients, for example random regression models, Wood's Lactation Curve (the commonly applied gamma equations), Wilmink's Curve and Legendre polynomials. Alternatively, mechanistic models which describe the lactation curves based on the biology of lactation have been used [1]. In 1999, White and colleagues [2] proposed and demonstrated that Natural Cubic Smoothing Splines (NCSS) can model the features of lactation curves with greater flexibility than the traditional parametric methods. This has been further supported by the work o