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Genome-wide detection of alternative splicing in expressed sequences using partial order multiple sequence alignment

C Grasso1, B Modrek, Y Xing

  • 1Department of Chemistry and Biochemistry, University of California, 611 Charles E. Young Drive East, Los Angeles, CA 90095-1570, USA.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
|March 3, 2004
PubMed
Summary

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This study introduces a novel method for detecting alternative splicing in expressed sequence data, overcoming common challenges with EST sequences. The approach accurately identifies splicing variations across multiple genomes.

Area of Science:

  • Bioinformatics
  • Genomics
  • Molecular Biology

Background:

  • Expressed Sequence Tags (ESTs) present challenges for alternative splicing detection due to errors and complexity.
  • Accurate inference of splicing patterns is crucial for understanding gene regulation and function.

Purpose of the Study:

  • To develop and validate a robust method for high-throughput alternative splicing detection using EST data.
  • To address inherent limitations of EST sequences, including fragmentation, errors, and chimeric nature.

Main Methods:

  • Utilized the Partial Order Alignment (POA) program for multiple sequence alignment.
  • Employed the Heaviest Bundling function for consensus sequence generation.
  • Integrated expressed sequences with genomic sequences in a unified alignment framework.

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Main Results:

  • Successfully applied the method to human UniGene Cluster Hs.1162 (HLA-DMB gene).
  • Generated comprehensive databases of splicing and alternative splicing relationships for human, mouse, and rat genomes.
  • Demonstrated computational scalability for whole-genome analysis.

Conclusions:

  • The presented method effectively handles complex EST data for accurate alternative splicing detection.
  • The approach is scalable and suitable for large-scale genomic analyses.
  • This work provides valuable resources for studying alternative splicing across species.