Xiao-Lin Wu

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The Animal QTL database (QTLdb; http://www.animalgenome.org/QTLdb) is designed to house all publicly available QTL and single-nucleotide polymorphism/gene association data on livestock animal species. An earlier version was published in the Nucleic Acids Research Database issue in 2007. Since then, we have continued our efforts to develop new and improved(More)
Phenotypic traits may exert causal effects between them. For example, on the one hand, high yield in dairy cows may increase the liability to certain diseases and, on the other hand, the incidence of a disease may affect yield negatively. Likewise, the transcriptome may be a function of the reproductive status in mammals and the latter may depend on other(More)
People with obesity, especially extreme obesity, are at risk for many health problems. However, the responsible genes remain unknown in >95% of severe obesity cases. Our previous genome-wide scan of Wagyu x Limousin F2 cattle crosses with extreme phenotypes revealed a molecular marker significantly associated with intramuscular fat deposition.(More)
A Bayesian nonparametric form of regression based on Dirichlet process priors is adapted to the analysis of quantitative traits possibly affected by cryptic forms of gene action, and to the context of SNP-assisted genomic selection, where the main objective is to predict a genomic signal on phenotype. The procedure clusters unknown genotypes into groups(More)
Porcine reproductive and respiratory syndrome (PRRS) has devastated pig industries worldwide for many years. It is caused by a small RNA virus (PRRSV), which targets almost exclusively pig monocytes or macrophages. In the present study, five SAGE (serial analysis of gene expression) libraries derived from 0 hour mock-infected and 6, 12, 16 and 24 hours(More)
Structural equation models (SEMs) are multivariate specifications capable of conveying causal relationships among traits. Although these models offer insights into how phenotypic traits relate to each other, it is unclear whether and how they can improve multiple-trait selection. Here, we explored concepts involved in SEMs, seeking for benefits that could(More)
Six genes involved in the heparan sulfate and heparin metabolism pathway, DSEL (dermatan sulfate epimerase-like), EXTL1 (exostoses (multiple)-like 1), HS6ST1 (heparan sulfate 6-O-sulfotransferase 1), HS6ST3 (heparan sulfate 6-O-sulfotransferase 3), NDST3 (N-deacetylase/N-sulfotransferase (heparan glucosaminyl) 3), and SULT1A1 (sulfotransferase family,(More)
High-throughput computing (HTC) uses computer clusters to solve advanced computational problems, with the goal of accomplishing high-throughput over relatively long periods of time. In genomic selection, for example, a set of markers covering the entire genome is used to train a model based on known data, and the resulting model is used to predict the(More)
Most Bayesian models for the analysis of complex traits are not analytically tractable and inferences are based on computationally intensive techniques. This is true of Bayesian models for genome-enabled selection, which uses whole-genome molecular data to predict the genetic merit of candidate animals for breeding purposes. In this regard, parallel(More)
In the present study, thirteen genes involved in the reverse cholesterol transport (RCT) pathway were investigated for their associations with three fat depositions, eight fatty acid compositions and two growth-related phenotypes in a Wagyu x Limousin reference population, including 6 F(1) bulls, 113 F(1) dams, and 246 F(2) progeny. A total of 37 amplicons(More)