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TRANSCRIPTOME 2002: From Functional Genomics to Systems
Biology |
P-27
In Silico Detection and Characterisation of Cancer-Specific Transcript Isoforms
Janet Kelso, The JambORESTES Consortium, Winston Hidel, South African National Bioinformatics Institute, University of the Western Cape, Bellville, SOUTH AFRICA
Large-scale mining of expressed sequence tags (ESTs) and comparison with available human genome sequence has allowed us to detect variations in the exon composition of the mature transcripts of genes commonly associated with cancer. The occurrence of exon skipping, the most common form of alternative splicing, has been linked to various disease phenotypes including cancer. Disease-specific transcript isoforms may prove to be useful diagnostic markers or therapeutic targets. We have developed and implemented a controlled vocabulary, which partitions expression information extracted from cDNA library annotation into four categories: anatomical site, cell type, developmental stage and pathological state, to determine the specificity of the expression state of both skip and constitutive transcript isoforms. We have detected and characterised 323 exon skipping events in 241 genes, some of which are uniquely associated with cancer.
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