Relative mutation rates of each nucleotide for another estimated from allele frequency spectra at human gene loci

Abstract

This study aims to comprehensively examine the mutation rates of one base for another in human gene loci. In contrast to most previous efforts based on divergence data from untranscribed regions, the present study employs the basic theory of the reversible recurrent mutation model using large-scale, high-quality re-sequencing data from public databases of gene loci. Population mutation parameters (4Nnu and 4Nmu) are obtained for each pair of base substitutions. The estimated parameters show good strand reversal symmetry, supporting the existence of mutation-drift equilibrium. Analysis of specific gene regions including mRNA, coding sequence (CDS), 5'-untranslated region (5'-UTRs), 3'-UTR and intron shows that there are clear differences in the mutation rates of each base for another depending on the location of the base in question. Results from analyses that take the adjacent bases into account exhibit excellent strand reversal symmetry, confirming that the identity of an adjacent base influences mutation rates. The CpG to TpG (or CpG to CpA) substitution is found at a rate approximately seven-fold higher than the reverse transition in intron regions due to cytosine deamination, but the effect is strongly reduced in mRNA regions and almost entirely lost in 5'-UTRs. However, from the overall increased transitions in sites other than CpGs and the proportion of CpGs in the total sequence, CpG methylation is not the main factor responsible for the increased rate of transitions as compared with transversions. In this report, after adjusting average mutation rates to the sequence compositions, no substitution bias is found between A+T and C+G, indicating base composition equilibrium in human gene loci. Population differences are also identified between groups of people of African and European descent, presumably due to past population histories. By applying the basic theory of population genetics to re-sequenced data, this study contributes new, detailed information regarding mutations in human gene regions.