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MOTIVATION: The two mutation processes that have the largest impact on genome evolution at small scales are substitutions, and sequence insertions and deletions (indels). While the former have been studied extensively, indels have received less attention, and in particular, the problem of inferring indel rates between pairs of divergent sequence remains unsolved. Here, I describe a novel and accurate method for estimating neutral indel rates between divergent pairs of genomes. RESULTS: Simulations suggest that new method for estimating indel rates is accurate to within 2%, at divergences corresponding to that of human and mouse. Applying the method to these species, I show that indel rates are up to twice higher than is apparent from alignments, and depend strongly on the local G + C content. These results indicate that at these evolutionary distances, the contribution of indels to sequence divergence is much larger than hitherto appreciated. In particular, the ratio of substitution to indel rates between human and mouse appears to be around gamma = 8, rather than the currently accepted value of about gamma = 14.

Original publication

DOI

10.1093/bioinformatics/btm185

Type

Journal article

Journal

Bioinformatics

Publication Date

01/07/2007

Volume

23

Pages

i289 - i296

Keywords

Algorithms, Animals, Base Composition, Base Sequence, Chromosome Mapping, DNA Mutational Analysis, DNA Transposable Elements, Evolution, Molecular, Gene Deletion, Genome, Genome, Human, Humans, Mice, Models, Genetic, Models, Statistical, Molecular Sequence Data, Mutation, Sequence Alignment, Sequence Analysis, DNA