Quantifying Influences on Intragenomic Mutation Rate

Context and Mutation in Gymnosperm Chloroplast DNA

Mutations and subsequent repair processes are known to be strongly context-dependent in the flowering-plant chloroplast genome. At least six flanking bases, three on each side, can have an influence on the relative rates of different types of mutation at any given site. In this analysis, examine context and substitution at noncoding and fourfold degenerate coding sites in gymnosperm DNA. The sequences are analyzed in sets of three, allowing the inference of the substitution direction and the generation of context-dependent rate matrices. The size of the dataset limits the analysis to the tetranucleotide context of the sites, but the evidence shows that there are significant contextual effects, with patterns that are similar to those observed in angiosperms. These effects most likely represent an influence on the underlying mutation/repair dynamics. The data extend the plastome lineages that feature very complex patterns of mutation, which can have significant effects on the evolutionary dynamics of the chloroplast genome.

CDMAP/CDVIS: context-dependent mutation analysis package and visualization software

The Context-dependent Mutation Analysis Package and Visualization Software (CDMAP/CDVIS) is an automated, modular toolkit used for the analysis and visualization of context-dependent mutation patterns (site-specific variation in mutation rate from neighboring-nucleotide effects). The CDMAP computes context-dependent mutation rates using a Variant Call File (VCF), Genbank file, and reference genome and can generate high-resolution figures to analyze variation in mutation rate across spatiotemporal scales. This algorithm has been benchmarked against mutation accumulation data but can also be used to calculate context-dependent mutation rates for polymorphism or closely related species as long as the input requirements are met. Output from CDMAP can be integrated into CDVIS, an interactive database for visualizing mutation patterns across multiple taxa simultaneously.

Substitution rate heterogeneity across hexanucleotide contexts in noncoding chloroplast DNA

Substitutions between closely related noncoding chloroplast DNA sequences are studied with respect to the composition of the 3 bases on each side of the substitution, that is the hexanucleotide context. There is about 100-fold variation in rate, among the contexts, particularly on substitutions of A and T. Rate heterogeneity of transitions differs from that of transversions, resulting in a more than 200-fold variation in the transitions: transversion bias. The data are consistent with a CpG effect, and it is shown that both the A + T content and the arrangement of purines/pyrimidines along the same DNA strand are correlated with rate variation. Expected equilibrium A + T content ranges from 36.4% to 82.8% across contexts, while G–C skew ranges from −77.4 to 72.2 and A–T skew ranges from −63.9 to 68.2. The predicted equilibria are associated with specific features of the content of the hexanucleotide context, and also show close agreement with the observed context-dependent compositions. Finally, by controlling for the content of nucleotides closer to the substitution site, it is shown that both the third and fourth nucleotide removed on each side of the substitution directly influence substitution dynamics at that site. Overall, the results demonstrate that noncoding sites in different contexts are evolving along very different evolutionary trajectories and that substitution dynamics are far more complex than typically assumed. This has important implications for a number of types of sequence analysis, particularly analyses of natural selection, and the context-dependent substitution matrices developed here can be applied in future analyses.

Relative Frequencies of PAX6 Mutational Events in a Russian Cohort of Aniridia Patients in Comparison with the World's Population and the Human Genome

Genome-wide sequencing metadata allows researchers to infer bias in the relative frequencies of mutational events and to predict putative mutagenic models. In addition, much less data could be useful in the evaluation of the mutational frequency spectrum and the prevalent local mutagenic process. Here we analyzed the PAX6 gene locus for mutational spectra obtained in our own and previous studies and compared them with data on other genes as well as the whole human genome. MLPA and Sanger sequencing were used for mutation searching in a cohort of 199 index patients from Russia with aniridia and aniridia-related phenotypes. The relative frequencies of different categories of PAX6 mutations were consistent with those previously reported by other researchers. The ratio between substitutions, small indels, and chromosome deletions in the 11p13 locus was within the interval previously published for 20 disease associated genomic loci, but corresponded to a higher end due to very high frequencies of small indels and chromosome deletions. The ratio between substitutions, small indels, and chromosome deletions for disease associated genes, including the PAX6 gene as well as the share of PAX6 missense mutations, differed considerably from those typical for the whole genome.

Factors Associated with Mutations: Their Matching Rates to Cardiovascular and Neurological Diseases

Monogenic hypertension is rare and caused by genetic mutations, but whether factors associated with mutations are disease-specific remains uncertain. Given two factors associated with high mutation rates, we tested how many previously known genes match with (i) proximity to telomeres or (ii) high adenine and thymine content in cardiovascular diseases (CVDs) related to vascular stiffening. We extracted genomic information using a genome data viewer. In human chromosomes, 64 of 79 genetic loci involving >25 rare mutations and single nucleotide polymorphisms satisfied (i) or (ii), resulting in an 81% matching rate. However, this high matching rate was no longer observed as we checked the two factors in genes associated with essential hypertension (EH), thoracic aortic aneurysm (TAA), and congenital heart disease (CHD), resulting in matching rates of 53%, 70%, and 75%, respectively. A matching of telomere proximity or high adenine and thymine content projects the list of loci involving rare mutations of monogenic hypertension better than those of other CVDs, likely due to adoption of rigorous criteria for true-positive signals. Our data suggest that the factor–disease matching rate is an accurate tool that can explain deleterious mutations of monogenic hypertension at a >80% match—unlike the relatively lower matching rates found in human genes of EH, TAA, CHD, and familial Parkinson’s disease.