about 21.6 million sequencing reads and 10.6 million aligned reads were

obtained for samples sequenced on each lane, which was able to identify > 50%

of all the annotated genes for each sample. Furthermore, from by far the largest

database of transcripts expressed in HCC tissues, we identified 1,378

significantly differently expressed genes (DEGs) and 24,338 differentially

expressed exons (DEEs). Comprehensive function analyses indicated that cell

growth-related, metabolism-related and immune-related pathways were most

significantly enriched by DEGs, pointing to a complex mechanism for HCC

carcinogenesis. Positional gene enrichment analysis showed that DEGs were

most significantly enriched at chromosome 8q21.3-24.3. The most interesting

findings were from the analysis at exon levels where we characterized three

major patterns of expression changes between gene levels and exon levels,

implying a much complex landscape of transcript-specific differential

expressions in HCC. Finally, we identified a novel highly up-regulated

exon-exon junction in ATAD2 gene in HCC tissues. Overall, to our best

knowledge, our study represents the most comprehensive characterization of the

HBV-related HCC transcriptome including exon level expression changes and

novel splicing variants, which illustrated the power of RNA-seq and provided

important clues for understanding the molecular mechanisms of HCC

pathogenesis at system-wide levels.

The key study contents:

(1) evaluation of data quality and sequencing depth required for

transcriptome analysis.

(2) Comparison between RNA-seq and microarray.

(3) The analysis and validation of differential gene expression.