Cloning of tissue-specific genes using serial analysis of gene expression and a novel computational substraction approach.

A paradigm of molecular medicine is the identification of functionally specialized genes in the search of defects responsible for human disease. To identify novel genes relevant for thyroid physiology, we applied serial analysis of gene expression (SAGE) and identified 4260 tag sequences that did not match any known gene present in the GenBank database ("no-match" tags). These no-match tags represent still uncharacterized transcripts. Most of them are expected to correspond to housekeeping genes and only a few to genes with a tissue-restricted pattern of expression. To pinpoint the best candidates for tissue-specificity in a large series of tags, we used a computer-based approach. We compared the relative abundance of 80 no match tags in our thyroid SAGE library with the expression level in 14 other SAGE libraries derived from 9 different human tissues. Based on the expression data, we developed the "tissue preferential expression" (TPE) algorithm to discriminate tags expressed specifically in the thyroid. We then selected four tags as preferentially expressed in thyroid. Results were validated by RT-PCR and northern blot on multiple-tissue RNA samples. Finally, the screening of a thyroid cDNA library with expressed sequence tag (EST) sequences related to the selected tags allowed the isolation of four novel thyroid-specific cDNAs. We demonstrate that the computational substraction of SAGE tags by the proposed TPE algorithm is a rapid and reliable way to expedite the cloning of tissue-specific genes through the combined use of SAGE and EST databases.