Functional prediction of de novo uni-genes from chicken transcriptomic data following infectious bursal disease virus at 3-days post-infection

Abstract Background Infectious bursal disease (IBD) is an economically very important issue to the poultry industry and it one of major threats nation’s food security. The pathogen, a highly pathogenic strain virulent IBD virus causes high mortality immunosuppression in chickens. importance understanding underlying genes that could combat this now global interest order control future outbreaks. We had looked at identified novel elucidate pathogenicity following infection possible resistance present Results A set sequences retrieved from virus-infected chickens did not map chicken reference genome were de novo assembled, clustered analysed. From six inbred lines, we managed assemble 10,828 uni-transcripts screened 618 which most significant known genes, as determined by BLASTX searches. Based on differentially expressed (DEGs) analysis, 12 commonly upregulated 18 downregulated uni-genes all lines with false discovery rate q-value < 0.05. Yet, only 9 13 BLAST hits against Non-redundant Swiss-Prot databases. ontology enrichment keywords these DEGs associated immune response, cell signalling apoptosis. Consequently, Weighted Gene Correlation Network Analysis R tool was used predict functional annotation remaining unknown no hits. Interestingly, functions three predicted be related innate while five surface functions. These results further elucidated supported current molecular knowledge regarding pathophysiology chicken’s infected IBDV. Conclusion Our data revealed up- immune- extracellular binding-related, respectively. Besides, findings are valuable contributions improving existing integrative transcriptomics may pave path towards viral particles especially suppression other infectious diseases