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Chromatin Immunoprecipitation (ChIP) using Drosophila tissue
Published on: March 23, 2012
Parametric alignment of Drosophila genomes
Colin N Dewey1, Peter M Huggins, Kevin Woods
1Department of Electrical Engineering and Computer Sciences, University of California Berkeley, Berkeley, California, USA.
Plos Computational Biology
|June 23, 2006
Summary
Parametric alignment addresses inconsistencies in whole genome alignment by finding all optimal alignments across all possible parameters. This method reveals conserved regulatory elements in Drosophila, improving biological inference.
Area of Science:
- Computational Biology
- Genomics
- Bioinformatics
Background:
- Standard whole genome alignment methods like Needleman-Wunsch and Smith-Waterman rely on fixed parameters and produce single alignments.
- Existing methods struggle with complex genome rearrangements and show significant variation in results, especially in non-coding regions.
- Disagreements among alignment programs highlight the need for more robust alignment methodologies.
Purpose of the Study:
- To introduce and apply parametric alignment as a solution to the parameter sensitivity and result variability in whole genome alignment.
- To construct a whole genome parametric alignment for Drosophila melanogaster and Drosophila pseudoobscura.
- To demonstrate the utility of parametric alignment for biological inference and quantitative assessment of evolutionary parameters.
Main Methods:
- Utilized existing heuristics to divide whole genomes into smaller, alignable segments.
- Developed novel methods for computing convex polytopes to enable parametric alignment of non-coding regions using biologically realistic models.
- Applied parametric alignment to a pair hidden Markov model (PHMM) framework to find all optimal alignments for all possible parameters.
Main Results:
- Successfully constructed a whole genome parametric alignment of Drosophila melanogaster and Drosophila pseudoobscura.
- Identified that cis-regulatory elements are more conserved between these species than previously understood.
- Demonstrated a method for quantitatively assessing the dependence of evolutionary branch length estimates on alignment parameters.
Conclusions:
- Parametric alignment offers a robust alternative to traditional methods, resolving issues of parameter dependence and improving alignment accuracy.
- The developed methodology enhances the ability to infer biological insights, such as the conservation of regulatory elements.
- Whole genome parametric alignment provides a quantitative framework for evolutionary analyses.
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