RNA-seq and microarray complement each other in transcriptome profiling
Citrus Research and Education Center, Department of Microbiology and Cell Science, Institute of Food and Agricultural Sciences, University of Florida, 700 Experiment Station Road, Lake Alfred, 33850, USA
BMC Genomics 2012, 13:629 doi:10.1186/1471-2164-13-629Published: 15 November 2012
RNA-seq and microarray are the two popular methods employed for genome-wide transcriptome profiling. Current comparison studies have shown that transcriptome quantified by these two methods correlated well. However, none of them have addressed if they complement each other, considering the strengths and the limitations inherent with them. The pivotal requirement to address this question is the knowledge of a well known data set. In this regard, HrpX regulome from pathogenic bacteria serves as an ideal choice as the target genes of HrpX transcription factor are well studied due to their central role in pathogenicity.
We compared the performance of RNA-seq and microarray in their ability to detect known HrpX target genes by profiling the transcriptome from the wild-type and the hrpX mutant strains of γ-Proteobacterium Xanthomonas citri subsp. citri. Our comparative analysis indicated that gene expression levels quantified by RNA-seq and microarray well-correlated both at absolute as well as relative levels (Spearman correlation-coefficient, rs > 0.76). Further, the expression levels quantified by RNA-seq and microarray for the significantly differentially expressed genes (DEGs) also well-correlated with qRT-PCR based quantification (rs = 0.58 to 0.94). Finally, in addition to the 55 newly identified DEGs, 72% of the already known HrpX target genes were detected by both RNA-seq and microarray, while, the remaining 28% could only be detected by either one of the methods.
This study has significantly advanced our understanding of the regulome of the critical transcriptional factor HrpX. RNA-seq and microarray together provide a more comprehensive picture of HrpX regulome by uniquely identifying new DEGs. Our study demonstrated that RNA-seq and microarray complement each other in transcriptome profiling.