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Estimation of DNA Sequence Context-dependent Mutation Rates Using Primate Genomic Sequences

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Abstract

It is understood that DNA and amino acid substitution rates are highly sequence context-dependent, e.g., C→T substitutions in vertebrates may occur much more frequently at CpG sites and that cysteine substitution rates may depend on support of the context for participation in a disulfide bond. Furthermore, many applications rely on quantitative models of nucleotide or amino acid substitution, including phylogenetic inference and identification of amino acid sequence positions involved in functional specificity. We describe quantification of the context dependence of nucleotide substitution rates using baboon, chimpanzee, and human genomic sequence data generated by the NISC Comparative Sequencing Program. Relative mutation rates are reported for the 96 classes of mutations of the form 5′αβγ3′ → 5′αδγ3′, where α, β, γ, and δ are nucleotides and β ≠ δ, based on maximum likelihood calculations. Our results confirm that C→T substitutions are enhanced at CpG sites compared with other transitions, relatively independent of the identity of the preceding nucleotide. While, as expected, transitions generally occur more frequently than transversions, we find that the most frequent transversions involve the C at CpG sites (CpG transversions) and that their rate is comparable to the rate of transitions at non-CpG sites. A four-class model of the rates of context-dependent evolution of primate DNA sequences, CpG transitions > non-CpG transitions ≈ CpG transversions > non-CpG transversions, captures qualitative features of the mutation spectrum. We find that despite qualitative similarity of mutation rates among different genomic regions, there are statistically significant differences.

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Acknowledgments

Dr. Eric Green of NISC generously provided us with the completed sequence contigs of both targets. W. Zhang was supported by a Graduate Research Fellowship from a Vermont EPSCoR grant awarded by the U.S. Department of Energy. The computational studies used infrastructure provided by the Vermont Cancer Center, the Vermont Genetics Network, the DOE EPSCoR initiative in structural and computational biology, and the Vermont Advanced Computing Center.

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Authors and Affiliations

  1. Department of Medicine, University of Chicago, 920 E. 58th St., 515 CLSC, Chicago, Illinois, 60637, USA

    Wei Zhang

  2. Genome Technology Branch, National Human Genome Research Institute, and NIH Intramural Sequencing Center, National Institutes of Health, Bethesda, Maryland, 20892, USA

    Gerard G. Bouffard

  3. Department of Microbiology and Molecular Genetics, Markey Center for Molecular Genetics, University of Vermont, 95 Carrigan Dr., Stafford Hall, Burlington, Vermont, 05405-0068, USA

    Susan S. Wallace & Jeffrey P. Bond

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  1. Wei Zhang
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  2. Gerard G. Bouffard
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NISC Comparative Sequencing Program

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Correspondence to Jeffrey P. Bond.

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Zhang, W., Bouffard, G.G., Wallace, S.S. et al. Estimation of DNA Sequence Context-dependent Mutation Rates Using Primate Genomic Sequences. J Mol Evol 65, 207–214 (2007). https://doi.org/10.1007/s00239-007-9000-5

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