Using network modeling to identification immunomodulators of induced immune response under stress condition

RNA-Seq is a revolutionary DNA sequencing technology recently developed that provides a large amount of gene expression information. Bayesian network is one of the statistical approaches that used for extracting meaningful biological knowledge from this information by predicts interactions between genes. In current study we focused on Bayesian gene network on bovine leukocytes RNA-seq data to reflect the major genes that affect immune system under weaning stress. Gene detection and level of gene expression was performed by Tophat2 and HTseq. Bayesian network was constructed on genes with differential expression by networkBMA package. Genes that expressed as regulators in this network usually have conserved sequence and effect on immune function by influencing apoptosis, RNA splicing, DNA repairing and regulating cell division. It is recommended that these genes can be used in gene assessed selection, designing of microarray and genomic selection by researching on these genes polymorphisms and evaluating relationship between different alleles and immune response.

Using network modeling to identification immunomodulators of induced immune response under stress condition Keywords:

RNA-seq , bovine , Bayesian network , immune regulator genes