Regional variation in mutation rates is an important phenomenon that affects genome evolution. It is determined by features of genomic landscape, with chromatin having an important influence.
Pairwise studies have revealed the complexity of correlation between chromatin and mutation rates. Some studies support a link between open chromatin and repressed mutations, whereas some argue for a link between closed chromatin and decreased mutation rates. Other studies highlight patterns that are base-specific, depend on epigenomic modifications in a genomic region, or are shaped by selection.
As features characterizing chromatin states are correlated with each other and with other genomic landscape features, multivariate segmentation analyses (using hidden Markov models) are providing a more nuanced depiction of the relationship between chromatin and germline mutation rates. Specifically, a prevalent genomic state with moderately high substitution and deletion rates is located in regions with closed chromatin, whereas a less abundant state with very high substitution, insertion and deletion rates is located in regions with open chromatin.
Several recent studies indicate a positive association between increased somatic mutation rates and closed chromatin in cancer genomes.
In several types of cancer, driver mutations are located in genes that regulate chromatin, leading to the hypothesis that consequent global or local chromatin remodelling results in malignancy.
Transcription of genes is influenced by chromatin state and leads to a biased substitution pattern that is probably due to transcription-coupled repair.
The variation in local rates of mutations can affect both the evolution of genes and their function in normal and cancer cells. Deciphering the molecular determinants of this variation will be aided by the elucidation of distinct types of mutations, as they differ in regional preferences and in associations with genomic features. Chromatin organization contributes to regional variation in mutation rates, but its contribution differs among mutation types. In both germline and somatic mutations, base substitutions are more abundant in regions of closed chromatin, perhaps reflecting error accumulation late in replication. By contrast, a distinctive mutational state with very high levels of insertions and deletions (indels) and substitutions is enriched in regions of open chromatin. These associations indicate an intricate interplay between the nucleotide sequence of DNA and its dynamic packaging into chromatin, and have important implications for current biomedical research. This Review focuses on recent studies showing associations between chromatin state and mutation rates, including pairwise and multivariate investigations of germline and somatic (particularly cancer) mutations.
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K.D.M. is supported by the US National Science Foundation grant DBI-0965596, and R.C.H. is supported by the US National Institutes of Health grants R01DK065806, RC2HG005573 and U54HG006998. The authors are grateful to P. Kuruppumullage Don and R. Campos-Sanchez for help with Figure 1.
The authors declare no competing financial interests.
- Regional variation in mutation rates
(RViMR). The phenomenon whereby the rate of mutation changes along individual chromosomes.
- Nucleosome occupancy
A measure of the degree to which a certain DNA region is packaged into a nucleosome, with the DNA wrapped tightly around a core of eight histone proteins.
- Epigenomic features
Biochemical features that are associated with genomic DNA sequences but that are not the sequences themselves; examples include DNA methylation, histone modifications in chromatin, nuclease accessibility and transcription factor binding.
- Genomic landscape features
Features that characterize the genome at levels beyond the primary DNA sequence. These include GC content, recombination rates, proximity to the closest telomere and replication timing.
- CpG dinucleotides
Positions in the DNA sequence in which a cytosine is followed by a guanine.
- Open chromatin
Chromatin in which the DNA is readily accessible to enzymes in the nucleus; it can be interpreted as regions with less compaction than bulk nucleosomes, depleted of nucleosomes or having highly remodelled nucleosomes.
- Chromosome conformation capture
A method to quantitatively estimate the frequency of interaction between two different genomic regions using a crosslinking and intermolecular ligation assay to identify interacting sites.
- Chromatin acetylation
Covalent modification of specific lysine residues in the amino-terminal tails of histones by the addition of an acetyl group.
- Canonical correlation analysis
(CCA). A statistical analysis that considers two groups of variables simultaneously and finds significant linear combinations between them that have maximum correlations with each other.
- Hidden Markov model
(HMM). A statistical model that analyses a sequence of observations defined by underlying states that are not observable ('hidden') but that can be inferred from the data. These states alternate along the sequence following a Markovian structure; that is, the state defining a given observation depends on the state governing the preceding observation.
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Makova, K., Hardison, R. The effects of chromatin organization on variation in mutation rates in the genome. Nat Rev Genet 16, 213–223 (2015). https://doi.org/10.1038/nrg3890
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