Generation of kidney transcriptomes using serial analysis of gene expression.

Area of Science:

• Genomics
• Molecular Biology
• Nephrology

Background:

• Chronic kidney disease (CKD) pathogenesis is not fully understood.
• Identifying mechanisms of CKD progression is crucial for effective treatment.
• Genomewide expression monitoring offers a promising approach to uncover these mechanisms.

Purpose of the Study:

• To elucidate the mechanisms underlying progressive kidney disease.
• To utilize Serial Analysis of Gene Expression (SAGE) for comprehensive gene profiling in kidney disease.
• To generate hypothesis for novel pathogenetic mechanisms in CKD.

Main Methods:

• Serial Analysis of Gene Expression (SAGE) for simultaneous, quantitative mRNA analysis.
• Utilizing PCR to minimize distortion and serial concatenation of sequence tags for efficient sequencing.
• Bioinformatic analysis of tag libraries to generate transcriptomes and identify expressed genes.

Main Results:

• SAGE generates comprehensive transcriptome profiles, offering quantitative insights into gene expression patterns.
• Analysis of SAGE kidney transcriptomes from normal and diseased animals is underway.
• This approach allows for the identification of coordinated gene activity changes in kidney disease.

Conclusions:

• SAGE provides a powerful, hypothesis-generating tool for understanding complex diseases like CKD.
• Global gene expression analysis offers insights into gene-gene and gene-environment interactions in disease.
• Further application of SAGE and other 'omics' tools will advance understanding of kidney disease and identify new therapeutic targets.