Detection of different expressed genes in newborn piglet liver using RNA-seq to analyze negative effects caused by dietary tryptophan

Purpose: Next-generation sequencing (NGS) has revolutionized systems-based analysis of the expression of genes. The goals of this study are to reveal the mechanism of side effect of excess diet tryptophan in newborn piglets through optimal high-throughput data analysis. Methods: Liver mRNA profiles of newborn piglets feeded by different tryptophan mode were generated by deep sequencing, in triplicate, using Illumina HiSeq 2500. The sequence reads that passed quality filters were analyzed at the genes level with two methods: Burrows–Wheeler Aligner (BWA) followed by ANOVA (ANOVA) and TopHat followed by Cufflinks and Then, differential expression genes analysis between these two groups (three biological replicates per condition) was performed using Cuffdiff. The P values were adjusted using the Benjamini & Hochberg method. qRT–PCR validation was performed using TaqMan and SYBR Green assays Results: Using an optimized data analysis workflow, we mapped about 30 to 40 million sequence reads per sample to the pig genome (build susScr3) and identified 11,314 transcripts in the liver of newborn piglets with TopHat workflow. RNA-seq data confirmed 88 different expressed genes between the High-Low group and the 2×Trp group, and 10 of these were validated with qRT–PCR. RNA-seq data had a linear relationship with qRT–PCR. Conclusions: Our study represents the first detailed analysis of liver transcriptomes of newborn piglets from the groups that sow feed by High-Low and the 2×Trp methods, with biologic replicates, generated by RNA-seq technology. Functional analyses of DEGs in livers revealed that certain genes associated with cellular stress and exogenous stimulus response were strongly associated with the dysfunction of liver metabolism in newborn piglets. Overall design: Liver mRNA profiles of newborn piglets were generated by deep sequencing, in triplicate, using Illumina 2500.