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Abstract Number: 524

RNA-Sequencing Identifies Novel Differentially Expressed Coding and Non-Coding Transcripts in Sjögren’s Syndrome

Indra Adrianto1, Graham B. Wiley1, John A. Ice1, He Li1, Jennifer A. Kelly2, Astrid Rasmussen1, Stuart B. Glenn3, Kimberly Hefner4, Donald U. Stone5, Raj Gopalakrishnan6, Glen D. Houston7, David M. Lewis8, Michael Rohrer6, James A. Lessard9, Juan-Manuel Anaya10, Barbara M. Segal11, Nelson L. Rhodus12, Lida Radfar13, John B. Harley14, Judith A. James2, Courtney G. Montgomery1, R. Hal Scofield15, Patrick M. Gaffney1, Kathy Moser Sivils2 and Christopher J. Lessard16, 1Arthritis and Clinical Immunology Research Program, Oklahoma Medical Research Foundation, Oklahoma City, OK, 2Oklahoma Medical Research Foundation, Oklahoma City, OK, 3Arthritis and Clinical Immunology, Oklahoma Medical Research Foundation, Oklahoma City, OK, 4Hefner Eye Care and Optical Center, Oklahoma City, OK, 5Ophthalmology, University of Oklahoma Health Sciences Center, Oklahoma City, OK, 6Diagnostic and Biological Sciences, University of Minnesota, Minneapolis, MN, 7Collage of Denistry, University of Oklahoma Health Sciences Center, Oklahoma City, OK, 8College of Dentistry, University of Oklahoma Health Sciences Center, Oklahoma City, OK, 9Valley Bone and Joint Clinic, Grand Forks, ND, 10School of Medicine and Health Sciences, Universidad del Rosario. Center for Autoimmune Diseases Research (CREA), Bogotá, Colombia, 11Rheumatology, Hennepin County Medical Center, Minneapolis, MN, 12University of Minnesota, Minneapolis, MN, 13University of Oklahoma Health Sciences Center, Oklahoma City, OK, 14Division of Rheumatology and The Center for Autoimmune Genomics & Etiology, University of Cincinnati, Cincinnati Children's Hospital Medical Center; US Department of Veterans Affairs Medical Center, Cincinnati, OH, 15Arthritis and Clinical Immunology Program, Oklahoma Medical Research Foundation, Oklahoma City, OK, 16Arthritis and Clinical Immunology Research Program, Oklahoma Medical Research Foundation; University of Oklahoma Health Sciences Center, Oklahoma City, OK

Meeting: 2012 ACR/ARHP Annual Meeting

Keywords: RNA, Sjogren's syndrome and genomics

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Session Information

Title: Sjögren's Syndrome - Pathogenesis

Session Type: Abstract Submissions (ACR)

Background/Purpose:

Sjögren’s syndrome (SS) is a common, clinically heterogeneous autoimmune disease characterized by exocrine gland dysfunction that involves both innate and adaptive immune responses.  SS etiology is complex, with both environmental and genetic/genomic factors contributing.  Recent genetic studies in complex disease have shown that ~80% of associations map to transcriptionally active non-protein coding DNA sequences that comprise ~60% of the human genome.   Microarray technology, which requires prior knowledge of the transcripts being interrogated, has been extensively used to study gene expression of mRNA.  Far more powerful, emerging RNA-sequencing (RNA-seq) technology allows for unbiased transcript identification and quantification across the genome. We used RNA-seq to identify differentially expressed (DE) protein-coding (~3% of the genome) and non-coding transcripts in 60 SS cases and 30 healthy controls.

Methods:

RNA samples were isolated from whole blood and prepared for sequencing using the NuGEN Encore kit, and sequencing was performed using the Illumina HiSeq 2000. Quality of raw sequence data was assessed using FASTQC.  Raw FASTQ files were aligned to the human genome (hg19) using TOPHAT.  Probable transcripts were assembled using CUFFLINKS, and DE transcripts were determined using CUFFDIFF using a false discovery rate (FDR) q-value of 0.1.  Fold change (FC; positive values = overexpressed and negative values = underexpressed) calculations were obtained using the log2(FPKMCases/FPKMControls), where FPKM is the fragments per kilobase of exon model per million mapped fragments.  Transcripts were verified using the Integrated Genome Viewer (IGV).

Results:

The average number of reads per sample was 38.6 million, representing 346,234 transcripts across the genome.  Of the protein-coding regions, TGF-beta activated kinase 1/MAP3K7 binding protein 1 (TAB1) was the most statistically DE locus (p=3.03x10E-7, q=0.049, FC=1.56).  TAB1, regulates MAP kinase kinase kinase MAP3K7/TAK1 and is involved in TGF beta, interleukin 1, WNT-1, NF-


Disclosure:

I. Adrianto,
None;

G. B. Wiley,
None;

J. A. Ice,
None;

H. Li,
None;

J. A. Kelly,
None;

A. Rasmussen,
None;

S. B. Glenn,
None;

K. Hefner,
None;

D. U. Stone,
None;

R. Gopalakrishnan,
None;

G. D. Houston,
None;

D. M. Lewis,
None;

M. Rohrer,
None;

J. A. Lessard,
None;

J. M. Anaya,
None;

B. M. Segal,
None;

N. L. Rhodus,
None;

L. Radfar,
None;

J. B. Harley,

ERBA Diagnostics,

7,

ERBA Diagnostics ,

5,

ERBA DIagnostics,

1;

J. A. James,
None;

C. G. Montgomery,
None;

R. H. Scofield,
None;

P. M. Gaffney,
None;

K. Moser Sivils,
None;

C. J. Lessard,
None.

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