Search tips
Search criteria 


Logo of bmcmedgenoBioMed Centralsearchsubmit a manuscriptregisterthis articleBMC Medical Genomics
BMC Med Genomics. 2012; 5: 28.
Published online Jun 29, 2012. doi:  10.1186/1755-8794-5-28
PMCID: PMC3428653
A systematic comparison and evaluation of high density exon arrays and RNA-seq technology used to unravel the peripheral blood transcriptome of sickle cell disease
Nalini Raghavachari,corresponding author1 Jennifer Barb,2 Yanqin Yang,1 Poching Liu,1 Kimberly Woodhouse,1 Daniel Levy,4,5 Christopher J O‘Donnell,4,6 Peter J Munson,2 and Gregory J Kato3
1Genomics Core Facility, Genetics and Development Biology, NHLBI, The National Institutes of Health, 10 Center Drive, Bldg 10, 8C 103B, Bethesda, 20892, USA
2Mathematical and Statistical computing Laboratory, Center for Information Technology, National Institutes of Health, Bethesda, MD, USA
3Hematology Branch, National Institutes of Health, Bethesda, MD, USA
4The National Heart, Lung, and Blood Institute’s Framingham Heart Study, Framingham, MA, USA
5The Center for Population Studies and the Division of Intramural Research, National Heart, Lung, and Blood Institute, Bethesda, MD, USA
6The Center for Cardiovascular Genomics and the Division of Intramural Research, National Heart, Lung, and Blood Institute, Bethesda, MD, USA
corresponding authorCorresponding author.
Nalini Raghavachari: nraghavachari/at/; Jennifer Barb: barbj/at/; Yanqin Yang: Yanqin.yang/at/; Poching Liu: pcliu/at/; Kimberly Woodhouse: kwoodhous/at/; Daniel Levy: levyd/at/; Christopher J O‘Donnell: odonnellc/at/; Peter J Munson: munson/at/; Gregory J Kato: gkato/at/
Received November 23, 2011; Accepted June 29, 2012.
Transcriptomic studies in clinical research are essential tools for deciphering the functional elements of the genome and unraveling underlying disease mechanisms. Various technologies have been developed to deduce and quantify the transcriptome including hybridization and sequencing-based approaches. Recently, high density exon microarrays have been successfully employed for detecting differentially expressed genes and alternative splicing events for biomarker discovery and disease diagnostics. The field of transcriptomics is currently being revolutionized by high throughput DNA sequencing methodologies to map, characterize, and quantify the transcriptome.
In an effort to understand the merits and limitations of each of these tools, we undertook a study of the transcriptome in sickle cell disease, a monogenic disease comparing the Affymetrix Human Exon 1.0 ST microarray (Exon array) and Illumina’s deep sequencing technology (RNA-seq) on whole blood clinical specimens.
Analysis indicated a strong concordance (R = 0.64) between Exon array and RNA-seq data at both gene level and exon level transcript expression. The magnitude of differential expression was found to be generally higher in RNA-seq than in the Exon microarrays. We also demonstrate for the first time the ability of RNA-seq technology to discover novel transcript variants and differential expression in previously unannotated genomic regions in sickle cell disease. In addition to detecting expression level changes, RNA-seq technology was also able to identify sequence variation in the expressed transcripts.
Our findings suggest that microarrays remain useful and accurate for transcriptomic analysis of clinical samples with low input requirements, while RNA-seq technology complements and extends microarray measurements for novel discoveries.
Keywords: Sickle cell disease, RNA-Seq, Exon arrays, Transcriptome, Clinical genomics
Articles from BMC Medical Genomics are provided here courtesy of
BioMed Central