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Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin

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Motif Yggdrasil: sampling sequence motifs from a tree mixture model.

Samuel A Andersson¹, Jens Lagergren

¹Stockholm Bioinformatics Center and School of Computer Science and Communication, Royal Institute of Technology, Stockholm, Sweden. samme@csc.kth.se

Journal of Computational Biology : a Journal of Computational Molecular Cell Biology

|August 9, 2007

Summary

The Motif Yggdrasil sampler is the first Gibbs sampler to use a general phylogenetic tree for motif discovery in unaligned sequences. This approach significantly improves motif identification accuracy, even with errors in the phylogenetic tree.

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Area of Science:

Bioinformatics
Computational Biology
Genomics

Background:

Phylogenetic footprinting identifies regulatory elements by searching for common motifs in orthologous gene upstream regions.
Existing tree-based methods often require aligned sequences or simplified tree structures (e.g., star-shaped).

Purpose of the Study:

To introduce the Motif Yggdrasil sampler, a novel Gibbs sampler for motif discovery using general phylogenetic trees and unaligned sequences.
To present a probabilistic model (MY model) that accommodates sequence variations and does not require sequence alignment or edge lengths.

Main Methods:

Developed the Motif Yggdrasil sampler, a Gibbs sampler based on a general tree structure.
Introduced the MY model for probabilistic description of upstream sequences with regulatory elements.
Applied the collapsing technique to simplify parameter sampling and derived a predictive update formula.

Main Results:

The MY model enhances the modeling of challenging motif instances.
Incorporating the phylogenetic tree significantly increases the nucleotide-level correlation coefficient.
The sampler demonstrates robust performance even with random or erroneous tree inputs, comparable to methods using aligned sequences.

Conclusions:

The Motif Yggdrasil sampler offers a powerful new tool for motif discovery in comparative genomics.
The tree-based approach provides a substantial improvement in identifying conserved regulatory elements.
The method is robust to inaccuracies in phylogenetic tree reconstruction.