Elsevier

DNA Repair

Volume 81, September 2019, 102647
DNA Repair

Review Article
Scales and mechanisms of somatic mutation rate variation across the human genome,☆☆

https://doi.org/10.1016/j.dnarep.2019.102647Get rights and content

Abstract

Cancer genome sequencing has revealed that somatic mutation rates vary substantially across the human genome and at scales from megabase-sized domains to individual nucleotides. Here we review recent work that has both revealed the major mutation biases that operate across the genome and the molecular mechanisms that cause them. The default mutation rate landscape in mammalian genomes results in active genes having low mutation rates because of a combination of factors that increase DNA repair: early DNA replication, transcription, active chromatin modifications and accessible chromatin. Therefore, either an increase in the global mutation rate or a redistribution of mutations from inactive to active DNA can increase the rate at which consequential mutations are acquired in active genes. Several environmental carcinogens and intrinsic mechanisms operating in tumor cells likely cause cancer by this second mechanism: by specifically increasing the mutation rate in active regions of the genome.

Introduction

The large-scale sequencing of tumors and healthy somatic cells presents a unique opportunity to learn about somatic mutation processes and how mutation rates vary across the human genome. The primary motivation for tumor genome sequencing was to identify the ‘driver’ mutations that cause cancer. Driver mutations are selected because they promote the expansion or survival of tumor clones. However, most somatic mutations in cancer genomes are inconsequential ‘passenger’ mutations that are under very weak or no selection and statistical analyses of these passenger mutations have provided many fundamental insights into the mutation processes that operate in human cells and how these processes vary across the genome, cell types and individuals.

Absolute mutation rates are difficult to determine for tumor cells, primarily because the number of cell divisions that a tumor cell has undergone is hard to establish. However, it has long been appreciated that many tumors have have an elevated mutation rate, for example because of inactivated DNA repair pathways [[1], [2], [3]]. In this review, we will not focus on the general acceleration in mutation rates in a cancer cell. Instead, we focus on relative mutation rates, which are more straightforward to quantify from regional densities of mutations in the genome. We provide an overview of the patterns of mutations that are observed across regions of the human genome and our current understanding about their mechanistic underpinnings when this is known (although often a detailed mechanistic understanding is still lacking). We place an emphasis on the insight and the novel hypotheses that cancer genomes have yielded about the organization of mutation processes. Our primary focus is on single nucleotide substitutions and short insertions and deletions. The reasons for this are pragmatic: structural variation is much more challenging to precisely infer using short-read sequencing and although progress is being made in both identifying and understanding structural variation, the influences on its regional rates in the soma are far less well understood [4].

Variability in mutation rates across the genome may result from two broad causes: differential accrual of DNA damage and also base mispairing during DNA replication (variation in mutation supply) or differential repair of damage and mispairs (variation in DNA repair). These influences are, of course, not mutually exclusive. Recent work has suggested, however, that the latter – differential DNA repair – appears to play a quantitatively more important role in shaping the mutation landscape in the human soma. This is consistent with the expectation that mutation rates are more sensitive to changes in repair rates than to changes in damage rates because the vast majority of instances of damage are repaired [5].

Section snippets

Somatic mutation rates vary at multiple resolutions

As we discuss below, mutation rates in the human genome vary at multiple different scales from single nucleotides to megabase-sized domains. Importantly, the mechanisms underlying variation at these different genomic resolutions may be quite different and this often confounds statistical analyses performed at a certain resolution. For instance, at the resolution of a single nucleotide, mutation rates are highly dependant on the 5′ and 3′ neighboring nucleotides. For example, in the human

Features and mechanisms associated with mutation rate variation

In the following sections we provide an overview of genomic and epigenomic variables known to be statistically associated with mutation rates at various resolutions. We also highlight examples where the underlying molecular mechanisms are known or suspected.

The redistribution of mutations in cancer

It is well expected that exposures to DNA damaging agents and failing DNA repair increase overall mutation rates. However genome sequencing of cancers has also provided evidence of another, less appreciated, but similarly widespread phenomenon: that exposure to mutagens and DNA repair failures also cause changes in the relative mutation rates of chromosomal regions. Such ‘redistribution’ of mutations across the genome due to mutagenic exposures is likely to have important functional

Outlook: challenges in genomic studies of mutation patterns

Statistical analyses of mutation distributions across the genomes of somatic cells – including not only tumors but also healthy cells [96,97] and cell lines [26,98,99] – have provided valuable insights into the mechanisms that underlie mutation rate variation. The approaches that have been used can, however, likely still be improved to provide deeper insights into mechanisms of DNA repair and mutagenesis.

First, of course, there is a need for more data. A larger number of whole genome sequences

Acknowledgements

This work was funded by the ERC Starting Grant “HYPER-INSIGHT” (to F.S.) and the ERC Consolidator Grant “IR-DC” (to B.L.). F.S. and B.L. are funded by the ICREA Research Professor programme. F.S. acknowledges support of the Severo Ochoa Centres of Excellence programme to the IRB Barcelona, and B.L. to CRG.

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    This Special Issue is edited by Philip C. Hanawalt.

    ☆☆

    This article is part of the special issue Cutting-edge Perspectives in Genomic Maintenance VI.

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