Molecular Biology and Evolution, Vol 15, 1224-1231, Copyright © 1998 by Society for Molecular Biology and Evolution
JA Lake
Nucleotide substitution rates vary at different positions within genes and
genomes, but rates are difficult to estimate, because they are masked by
the stochastic nature of substitutions. In this paper, a linear method,
pattern filtering, is described which can optimally separate the signals
(related to substitution rates or to other measures of sequence change)
from stochastic noise. Pattern filtering promises to be useful in both
genomic and molecular evolution studies. In an example using mitochondrial
genomes, it is shown that pattern filtering can reveal coding and
non-coding regions without the need for prior identification of reading
frames or other knowledge of the sequence and promises to be an important
tool for genomic analysis. In a second example, it is shown that pattern
filtering allows one to classify sites on the basis of an estimator of
substitution rates. Using elongation factor EF-1 alpha sequences, it is
shown that the fastest sites favor archaea as the sister taxon of
eukaryotes, whereas the slower sites support the eocyte prokaryotes as the
sister taxon of eukaryotes, suggesting that the former result is an
artifact of "long branch attraction."
ORIGINAL ARTICLE
Optimally recovering rate variation information from genomes and sequences: pattern filtering
Molecular Biology Institute, University of California, Los Angeles 90095, USA. lake@mbi.ucla.edu
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