SLAM: Cross-Species Gene Finding and Alignment with a Generalized Pair Hidden Markov Model

  1. Marina Alexandersson1,
  2. Simon Cawley2, and
  3. Lior Pachter3,4
  1. 1Department of Statistics, University of California, Berkeley, Berkeley, California 94720, USA; 2Affymetrix Inc., Santa Clara, California 95051, USA; 3Department of Mathematics, University of California, Berkeley, Berkeley, California 94720, USA

Abstract

Comparative-based gene recognition is driven by the principle that conserved regions between related organisms are more likely than divergent regions to be coding. We describe a probabilistic framework for gene structure and alignment that can be used to simultaneously find both the gene structure and alignment of two syntenic genomic regions. A key feature of the method is the ability to enhance gene predictions by finding the best alignment between two syntenic sequences, while at the same time finding biologically meaningful alignments that preserve the correspondence between coding exons. Our probabilistic framework is the generalized pair hidden Markov model, a hybrid of (1) generalized hidden Markov models, which have been used previously for gene finding, and (2) pair hidden Markov models, which have applications to sequence alignment. We have built a gene finding and alignment program called SLAM, which aligns and identifies complete exon/intron structures of genes in two related but unannotated sequences of DNA. SLAM is able to reliably predict gene structures for any suitably related pair of organisms, most notably with fewer false-positive predictions compared to previous methods (examples are provided for Homo sapiens/Mus musculus andPlasmodium falciparum/Plasmodium vivax comparisons). Accuracy is obtained by distinguishing conserved noncoding sequence (CNS) from conserved coding sequence. CNS annotation is a novel feature of SLAM and may be useful for the annotation of UTRs, regulatory elements, and other noncoding features.

Footnotes

  • 4 Corresponding author.

  • E-MAIL lpachter{at}math.berkeley.edu; FAX (510) 642-8204.

  • Article and publication are at http://www.genome.org/cgi/doi/10.1101/gr.424203. Article published online before print in February 2003.

    • Received May 13, 2002.
    • Accepted December 3, 2002.
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