A compositional segmentation of the human mitochondrial genome is related to heterogeneities in the guanine mutation rate

Abstract

We applied a hidden Markov model segmentation method to the human mitochondrial genome to identify patterns in the sequence, to compare these patterns to the gene structure of mtDNA and to see whether these patterns reveal additional characteristics important for our understanding of genome evolution, structure and function. Our analysis identified three segmentation categories based upon the sequence transition probabilities. Category 2 segments corresponded to the tRNA and rRNA genes, with a greater strand-symmetry in these segments. Category 1 and 3 segments covered the protein- coding genes and almost all of the non-coding D-loop. Compared to category 1, the mtDNA segments assigned to category 3 had much lower guanine abundance. A comparison to two independent databases of mitochondrial mutations and polymorphisms showed that the high substitution rate of guanine in human mtDNA is largest in the category 3 segments. Analysis of synonymous mutations showed the same pattern. This suggests that this heterogeneity in the mutation rate is partly independent of respiratory chain function and is a direct property of the genome sequence itself. This has important implications for our understanding of mtDNA evolution and its use as a 'molecular clock' to determine the rate of population and species divergence.

Figure 1

Sequence transition probability distributions between nucleotides for the three segmentation categories. Red: category 1. Blue: category 2. Green: category 3.

Figure 2

Probability map of assignment of the human mtDNA genome to the three segmentation categories. Protein gene annotations are given in (a) for categories 1 and 3. tRNA and rRNA annotations are given in (b) for category 2. The arrows give the direction of translation of the gene. Color codes are the same as in Figure 1.

Figure 3

A comparison of the positions of the category 3 segments, shaded in green, to (A) guanine distribution and (B) predicted hydrophobicity. The guanine abundance was calculated using a sliding window of length 201 bp. The predicted hydrophobicity was calculated using the Kyte-Doolittle scale averaged over a sliding window of 21 amino acids and is plotted as a function of the base pair position of the codons for each amino acid. Due to the rapid variations in predicted hydrophobicity, only three genes (ND1, ND2 and COX I) are plotted. No relationship between the predicted protein hydrophobicity and the category 3 locations is apparent in this plot, but the location of the category 3 segments clearly corresponds to sequence regions with low guanine abundance. This plot shows that the low guanine content of category 3 is true for each segment individually, not just for the average taken over all the segments.

Figure 3

A comparison of the positions of the category 3 segments, shaded in green, to (A) guanine distribution and (B) predicted hydrophobicity. The guanine abundance was calculated using a sliding window of length 201 bp. The predicted hydrophobicity was calculated using the Kyte-Doolittle scale averaged over a sliding window of 21 amino acids and is plotted as a function of the base pair position of the codons for each amino acid. Due to the rapid variations in predicted hydrophobicity, only three genes (ND1, ND2 and COX I) are plotted. No relationship between the predicted protein hydrophobicity and the category 3 locations is apparent in this plot, but the location of the category 3 segments clearly corresponds to sequence regions with low guanine abundance. This plot shows that the low guanine content of category 3 is true for each segment individually, not just for the average taken over all the segments.