zed below, adapted from the article's abstracts: 1. 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. BACKGROUND: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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. 2. A novel molecular signature for elevated tricuspid regurgitation velocity in sickle cell disease. Rationale: An increased tricuspid regurgitation jet velocity (TRV >2.5 m/s) and pulmonary hypertension defined by right heart catheterization both independently confer increased mortality in sickle cell disease (SCD). Objectives: We explored the usefulness of peripheral blood mononuclear cell-derived gene signatures as biomarkers for an elevated TRV in SCD. Methods: Twenty-seven patients with SCD underwent echocardiography and peripheral blood mononuclear cell isolation for expression profiling and 112 patients with SCD were genotyped for single-nucleotide polymorphisms. Measurements and Main Results: Genome-wide gene and miRNA expression profiles were correlated against TRV, yielding 631 transcripts and 12 miRNAs. Support vector machine analysis identified a 10-gene signature including GALNT13 (encoding polypeptide N-acetylgalactosaminyltransferase 13) that discriminates patients with and without increased TRV with 100% accuracy. This finding was then validated in a cohort of patients with SCD without (n = 10) and with pulmonary hypertension (n = 10, 90% accuracy). Increased TRV-related miRNAs revealed strong in silico binding predictions of miR-301a to GALNT13 corroborated by microarray analyses demonstrating an inverse correlation between their expression. A genetic association study comparing patients with an elevated (n = 49) versus normal (n = 63) TRV revealed five significant single-nucleotide polymorphisms within GALNT13 (P <0.005), four trans-acting (P <2.1 10(-7)) and one cis-acting (P = 0.6 10(-4)) expression quantitative trait locus upstream of the adenosine-A2B receptor gene (ADORA2B). Conclusions: These studies validate the clinical usefulness of genomic signatures as potential biomarkers and highlight ADORA2B and GALNT13 as potential candidate genes in SCD-associated elevated TRV.

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