ETph: enhancers and their targets in pig and human database

Enhancers, as the genomic non-coding sequences, play a key role in the activation of gene expression. They have been widely identified in the human genome. Pig is an important biomedical model for human health. Few studies have been performed to explore the enhancers in the pig genome. The human enhancer information may be useful to identify enhancers in the pig genome. In addition, the genetic background of pig traits could be useful to annotate human enhancers and diseases. Thus, in order to further study enhancers and their potential roles in human and pig, we developed a public database, ETph (Enhancers and their Targets in pig and human). ETph integrates the information on human enhancers, pig putative enhancers, target genes, pig QTL terms, human diseases, GO terms and the KEGG pathway. A total of 25 182 enhancers were identified in the pig genome using the human homology sequence information. Among them, 6232 high-confidence enhancers were used to build the ETph. ETph provides a convenient platform to search, browse and download data. Moreover, a web-based analytical tool was designed to visualize networks and topology graphs among pig putative enhancers, target genes, pig QTL traits and human diseases. ETph might provide a useful tool for researchers to investigate the genetic background of pig traits and human diseases. ETph is freely accessible at http://klab.sjtu.edu.cn/enhancer/.

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.