Effects of cow families on type traits in dairy cattle

Genetic parameter estimates for body conformation traits using composite index, principal component, and factor analysis

Information about genetic parameters is population specific and it is crucial for designing animal breeding programs and predicting response to selection. This study was carried out to estimate the genetic parameters for 23 body conformation traits of 45,517 Chinese Holstein reared in Eastern China from 1995 to 2017 with the Bayesian inference method using a linear animal mixed model. The methods to integrate these traits included (1) using the composite index from the Dairy Association of China and (2) applying principal component analysis and factor analysis to explore the relationship between the conformation traits. Estimates of heritability using the composite index were low (0.04; feet and legs) to moderate (0.23; body capacity). Strong genetic correlations were observed between the individual body conformation traits. Both principal components (1 to 7; eigenvalues ≥ 1) and latent factors (1 to 7; eigenvalues ≥ 1) explained 60.37% of total variability. Principal component 1 and factor 1 accounted for the traits that are usually associated with milk production. Moderate to low heritability were estimated through multi-trait analysis for principal components (from 0.07 to 0.21) and latent factors (from 0.07 to 0.23). Genetic correlations among the 2 multivariate techniques are typically lower compared with the one existing among the measured traits. Results from these analyses suggest the possibility of using both principal component analysis and factor analysis in morphological evaluation, simplifying the information given by the body conformation traits into new variables that could be useful for the genetic improvement of the Chinese Holstein population. This information could also be used to avoid analyzing large number of correlated traits, thereby improving precision and reducing computation burdens to analyze large and complex data.

Negative influence of high maternal milk production before and after conception on offspring survival and milk production in dairy cattle

There is a paucity of studies on the effect of intrauterine conditions on subsequent progeny performance in dairy cows. Using a large national data set on Irish Holstein-Friesian dairy cows, the objective of this study was to determine if intrauterine conditions, quantified by a maternal genetic variance component, significantly affected milk production, age at first calving, calving interval, somatic cell score (natural logarithm of somatic cell count) and survival in first-, second-, and third-parity female offspring. Maternal genetic variance for each trait in each parity was estimated in a linear mixed model which included, other than fixed effects, direct additive genetic, maternal genetic, cytoplasmic and permanent environmental effect of the dam, and residual component. A covariance was also estimated between the direct additive and maternal genetic components where possible. Because calves in Irish dairy herds are separated from dams at birth, a significant maternal genetic variance (with all other random effects in the model) indicates a prepartum maternal effect. A significant maternal genetic variance was estimated for 305-d milk yield in first and third lactation, somatic cell score in first lactation, and survival to second lactation from 188,144 lactations on 80,881 animals. Where estimated, a negative correlation existed between the direct additive and maternal genetic components. Regression of maternal mixed model solutions on dam milk production at different stages relative to conception revealed that greater milk yield preconception and during gestation was associated with reduced survival and milk yield and greater somatic cell count in the progeny. This study suggests that offspring survival and performance are affected by prepartum conditions that offspring experience as an oocyte, embryo, or fetus, one of which is mediated through milk production (or factors related to milk production) of the dam.

Precision animal breeding

We accept that we are responsible for the quality of life of animals in our care. We accept that the activities of man affect all the living things with which we share this planet. But we are slow to realize that as a result we have a duty of care for all living things. That duty extends to the breeding of animals for which we are responsible. When animals are bred by man for a purpose, the aim should be to meet certain goals: to improve the precision with which breeding outcomes can be predicted; to avoid the introduction and advance of characteristics deleterious to well-being; and to manage genetic resources and diversity between and within populations as set out in the Convention on Biological Diversity. These goals are summed up in the phrase precision animal breeding. They should apply whether animals are bred as sources of usable products or services for medical or scientific research, for aesthetic or cultural considerations, or as pets. Modern molecular and quantitative genetics and advances in reproductive physiology provide the tools with which these goals can be met.

Bias and Power in the Estimation of a Maternal Family Variance Component in the Presence of Incomplete and Incorrect Pedigree Information

Several studies over the last 15 yr have estimated the magnitude of cytoplasmic inheritance of production and type traits in dairy cattle. Pedigree information can be used to assign maternal lineages, and the between-maternal lineage variance is then assumed to be an estimate of cytoplasmic inheritance. Two potential sources of bias and reduction of the power of estimation of cytoplasmic inheritance using such a method are 1) incomplete and 2) incorrect pedigree information being used in the assignment of maternal lineages. The theoretical bias introduced by these two sources of error is investigated and the results of a simulation study varying the number of families, the percentage of pedigree errors, and the level of incomplete lineage assignment are presented. Pedigree errors were found to have the biggest impact. A pedigree error rate of 8% per generation would result in a 75% reduction in the estimable magnitude of a 5% true component of variance after nine generations. The effect that these mechanisms have on the power of estimation are discussed and investigated by simulation. It was concluded that using historical pedigree, with incomplete and incorrect maternal family information, to assign maternal lineage would cause a downward bias in the magnitude of the cytoplasmic effect estimated. In the future, it will be possible to overcome pedigree problems by using molecular information to directly assign cytoplasmic lineage groups.