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A Non-EST-Based Method for Exon-Skipping Prediction
 

Summary: A Non-EST-Based Method
for Exon-Skipping Prediction
Rotem Sorek,1,2,4
Ronen Shemesh,2
Yuval Cohen,2
Ortal Basechess,2
Gil Ast,1
and Ron Shamir3
1
Department of Human Genetics, Sackler Faculty of Medicine, Tel Aviv University, Ramat Aviv 69978, Israel; 2
Compugen, Tel
Aviv 69512, Israel; 3
School of Computer Science, Sackler Faculty of Exact Sciences, Tel Aviv University, Tel Aviv 69978, Israel
It is estimated that between 35% and 74% of all human genes can undergo alternative splicing. Currently, the most
efficient methods for large-scale detection of alternative splicing use expressed sequence tags (ESTs) or microarray
analysis. As these methods merely sample the transcriptome, splice variants that do not appear in deeply sampled
tissues have a low probability of being detected. We present a new method by which we can predict that an internal
exon is skipped (namely whether it is a cassette-exon) merely based on its naked genomic sequence and on the
sequence of its mouse ortholog. No other data, such as ESTs, are required for the prediction. Using our method,
which was experimentally validated, we detected hundreds of novel splice variants that were not detectable using

  

Source: Ast, Gil - Department of Molecular Genetics and Biochemistry, Tel Aviv University

 

Collections: Biology and Medicine