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Analysis of EST-driven gene annotation in human genomic sequence

L C Bailey1, D B Searls, G C Overton

  • 1Computational Biology and Informatics Laboratory, Department of Genetics, University of Pennsylvania School of Medicine, Philadelphia, Pennsylvania 19104, USA. bailey@www.cbil.upenn.edu

Genome Research
|June 13, 1998
PubMed
Summary

Similarity searches using expressed sequence tags (ESTs) effectively identify human genes for automated genome annotation. This method aids in gene prediction, alternative splicing analysis, and expression profiling, proving valuable for genomic research.

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Area of Science:

  • Genomics
  • Bioinformatics

Background:

  • Automated genome annotation is crucial for understanding genomic function.
  • Expressed sequence tags (ESTs) represent gene expression and can be used for gene discovery.

Purpose of the Study:

  • To systematically analyze gene identification in genomic sequences using similarity searches against ESTs.
  • To assess the suitability of EST similarity searches for automated human genome annotation.

Main Methods:

  • A BLAST-based strategy was employed to search for similarities between human genomic sequences and ESTs.
  • The strategy was tested on human genomic sequences (>5 kb) from public databases and a 300 kb benchmark sequence.

Main Results:

  • High-stringency searches detected 70%-90% of annotated genes, with >95% of ESTs overlapping genes.
  • Lower stringency identified up to 97% of annotated genes, though with a higher false-positive rate (up to 55%).
  • EST alignments facilitated gene prediction, alternative splicing elucidation, and crude expression profiling.

Conclusions:

  • EST similarity search is a practical and effective technique for automated genome annotation.
  • This method complements pattern recognition approaches for gene characterization.
  • ESTs provide access to cDNA clones for further laboratory validation and biological analysis.