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Abstract Number: 2194

RNA-Sequencing In Peripheral Blood Mononuclear Cells  Identifies Novel Differentially Expressed Coding and Non-Coding Transcripts In Juvenile Idiopathic Arthritis

Kaiyu Jiang1, Xiaoyun Sun2, Yanmin Chen1, Yufeng Shen2 and James N. Jarvis1, 1Pediatrics, The University at Buffalo, Buffalo, NY, 2Center for Computational Biology & Bioinformatics, Columbia University, New York, NY

Meeting: 2013 ACR/ARHP Annual Meeting

Keywords: Genomics and juvenile idiopathic arthritis (JIA), RNA

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Session Information

Title: Pediatric Rheumatology - Pathogenesis and Genetics

Session Type: Abstract Submissions (ACR)

Background/Purpose:  Juvenile idiopathic arthritis (JIA) is the most common rheumatic disease of childhood. The aetiology of JIA remains largely unknown, but the interplay between genes and environment is likely to be important. Recent genetic studies in complex disease have shown that 80% of disease-associated SNPs map to non-protein coding DNA sequences that comprise 80% of the human genome. However, data from projects like NIH’s ENCODE consortium suggest that much of the genome is transcriptionally active.  We used RNA-sequencing (RNA-seq) to identify differentially expressed (DE) protein-coding and non- coding transcripts in 3 JIA patients with active disease (AD), 3 patients at clinical remission on medicine (CRM), and 3 healthy controls.

Methods: RNA samples were isolated from peripheral blood mononuclear cells and prepared for sequencing using the Illumina TruSeq RNA prep kit. Sequencing was performed using the Illumina HiSeq 2000. The pass filter reads were mapped to the genome (Enseml/GRch37) using Tophat (version 1.3.3). Probable transcripts were assembled using CUFFLINKS, and DE transcripts were determined using CUFFDIFF using an adjusted P-value of 0.01. Fold change (FC) calculations were obtained using the log2(FPKM) ratio,

Results:

The average number of reads per sample was 42.95 million, and average number of mapped to genome was 32.9 million. Of the protein-coding regions, there are 119 DE genes (83 down-regulated, 36 up-regulated) in fold change 1.2 or greater when AD compared to HC, 83 DE genes (62 down-regulated, 21 up-regulated) in the AD vs CRM comparison and 19 DE (11 up-regulated, 7 down-regulated) in CRM vs HC. DE genes in AD vs HC and AD vs CRM predictably included those associated with connective tissue disorders, immunological disease and inflammatory disease (e.g. CCR5, IL3RA, IL8 etc. ). Among non-protein coding transcripts, we observed DE of two long non-coding RNA (lncRNA) at 10p12.1 (p=0.001, FC= -3.73 and -4.74) and one lncRNA at 5q33.3 (p=0.023, FC=3.99) when AD compared to HC. Biological functions of these LncRNAs are unclear.

Conclusion: In this RNA-seq study in JIA, we identified DE genes in different disease states in JIA. These data also confirmed our previous observations using microarray technology. Three DE lncRNAs were observed in JIA. Future studies in JIA are warranted to further elucidate the functional consequences of these novel lncRNA associations.


Disclosure:

K. Jiang,
None;

X. Sun,
None;

Y. Chen,
None;

Y. Shen,
None;

J. N. Jarvis,
None.

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