Title
Development of an unbiased statistical method for the analysis of unigenic evolution.
Abstract
Background: Unigenic evolution is a powerful genetic strategy involving random mutagenesis of a single gene product to delineate functionally important domains of a protein. This method involves selection of variants of the protein which retain function, followed by statistical analysis comparing expected and observed mutation frequencies of each residue. Resultant mutability indices for each residue are averaged across a specified window of codons to identify hypomutable regions of the protein. As originally described, the effect of changes to the length of this averaging window was not fully eludicated. In addition, it was unclear when sufficient functional variants had been examined to conclude that residues conserved in all variants have important functional roles. Results: We demonstrate that the length of averaging window dramatically affects identification of individual hypomutable regions and delineation of region boundaries. Accordingly, we devised a region-independent chi-square analysis that eliminates loss of information incurred during window averaging and removes the arbitrary assignment of window length. We also present a method to estimate the probability that conserved residues have not been mutated simply by chance. In addition, we describe an improved estimation of the expected mutation frequency. Conclusion: Overall, these methods significantly extend the analysis of unigenic evolution data over existing methods to allow comprehensive, unbiased identification of domains and possibly even individual residues that are essential for protein function.
Year
DOI
Venue
2006
10.1186/1471-2105-7-150
BMC Bioinformatics
Keywords
Field
DocType
statistical analysis,bioinformatics,microarrays,algorithms,genetic variation,proteins,genetics,computer simulation
Missense mutation,Biology,Genetic variation,Gene product,DNA Mutational Analysis,Mutagenesis,Bioinformatics,Genetics,DNA microarray,Mutation,Statistical analysis
Journal
Volume
Issue
ISSN
7
1
1471-2105
Citations 
PageRank 
References 
22
0.51
1
Authors
5
Name
Order
Citations
PageRank
Colleen D. Behrsin1220.51
Chris J. Brandl2220.51
David W. Litchfield3220.51
Brian H. Shilton4220.51
Lindi M. Wahl5354.32