The gene expression patterns of peripheral blood mononuclear cells in patients with systemic lupus erythematosus.
- Author:
Shouxin, LI
;
Wei, JIANG
;
Rui, HUANG
;
Xiaohui, WANG
;
Wen, LIU
;
Shouyin, SHEN
- Publication Type:Journal Article
- MeSH:
Expressed Sequence Tags;
Gene Expression Profiling/*methods;
Leukocytes, Mononuclear/*metabolism;
Lupus Erythematosus, Systemic/blood;
Lupus Erythematosus, Systemic/*genetics;
Sequence Tagged Sites;
Transcription, Genetic
- From:
Journal of Huazhong University of Science and Technology (Medical Sciences)
2007;27(4):367-71
- CountryChina
- Language:English
-
Abstract:
This study examined the gene expression patterns of peripheral blood mononuclear cells (PBMCs) in patients with systemic lupus erythematosus (SLE) by using serial analysis of gene expression (SAGE) technology. Following the construction of serial analysis of gene expression (SAGE) library of PBMCs collected from 3 cases of familial SLE patients, a large scale of tag sequencing was performed. The data extracted from sequencing files was analyzed with SAGE 2000 V 4.5 software. The top 30 expressed genes of SLE patients were uploaded to http://david.niaid.nih.gov/david/ease.htm and the functional classification of genes was obtained. The differences among those expressed gene were analyzed by Chi-square tests. The results showed that a total of 1286 unique SAGE tags were identified from 1814 individual SAGE tags. Among the 1286 unique tags, 86.8% had single copy, and only 0.2% tags had more than 20 copies. And 68.4% of the tags matched known expressed sequences, 41.1% of which matched more than one known expressed sequence. About 31.6% of the tags had no match and could represent potentially novel genes. Approximately one third of the top 30 genes were ribosomal protein, and the rest were genes related to metabolism or with unknown functions. Eight tags were found to express differentially in SAGE library of SLE patients. This study draws a profile of gene expression patterns of PBMCs in patients with SLE. Comparison of SAGE database from PBMCs between normal individuals and SLE patients will help us to better understand the pathogenesis of SLE.
