Amnon Koren

Mutational heterogeneity in cancer and the search for new cancer-associated genes.

Major international projects are underway that are aimed at creating a comprehensive catalogue of all the genes responsible for the initiation and progression of cancer. These studies involve the sequencing of matched tumour–normal samples followed by mathematical analysis to identify those genes in which mutations occur more frequently than expected by random chance. Here we describe a fundamental problem with cancer genome studies: as the sample size increases, the list of putatively significant genes produced by current analytical methods burgeons into the hundreds. The list includes many implausible genes (such as those encoding olfactory receptors and the muscle protein titin), suggesting extensive false-positive findings that overshadow true driver events. We show that this problem stems largely from mutational heterogeneity and provide a novel analytical methodology, MutSigCV, for resolving the problem. We apply MutSigCV to exome sequences from 3,083 tumour–normal pairs and discover extraordinary variation in mutation frequency and spectrum within cancer types, which sheds light on mutational processes and disease aetiology, and in mutation frequency across the genome, which is strongly correlated with DNA replication timing and also with transcriptional activity. By incorporating mutational heterogeneity into the analyses, MutSigCV is able to eliminate most of the apparent artefactual findings and enable the identification of genes truly associated with cancer.

Whole-Genome Sequencing in Autism Identifies Hot Spots for De Novo Germline Mutation

De novo mutation plays an important role in autism spectrum disorders (ASDs). Notably, pathogenic copy number variants (CNVs) are characterized by high mutation rates. We hypothesize that hypermutability is a property of ASD genes and may also include nucleotide-substitution hot spots. We investigated global patterns of germline mutation by whole-genome sequencing of monozygotic twins concordant for ASD and their parents. Mutation rates varied widely throughout the genome (by 100-fold) and could be explained by intrinsic characteristics of DNA sequence and chromatin structure. Dense clusters of mutations within individual genomes were attributable to compound mutation or gene conversion. Hypermutability was a characteristic of genes involved in ASD and other diseases. In addition, genes impacted by mutations in this study were associated with ASD in independent exome-sequencing data sets. Our findings suggest that regional hypermutation is a significant factor shaping patterns of genetic variation and disease risk in humans.

Cell-of-origin chromatin organization shapes the mutational landscape of cancer

Cancer is a disease potentiated by mutations in somatic cells. Cancer mutations are not distributed uniformly along the human genome. Instead, different human genomic regions vary by up to fivefold in the local density of cancer somatic mutations, posing a fundamental problem for statistical methods used in cancer genomics. Epigenomic organization has been proposed as a major determinant of the cancer mutational landscape. However, both somatic mutagenesis and epigenomic features are highly cell-type-specific. We investigated the distribution of mutations in multiple independent samples of diverse cancer types and compared them to cell-type-specific epigenomic features. Here we show that chromatin accessibility and modification, together with replication timing, explain up to 86% of the variance in mutation rates along cancer genomes. The best predictors of local somatic mutation density are epigenomic features derived from the most likely cell type of origin of the corresponding malignancy. Moreover, we find that cell-of-origin chromatin features are much stronger determinants of cancer mutation profiles than chromatin features of matched cancer cell lines. Furthermore, we show that the cell type of origin of a cancer can be accurately determined based on the distribution of mutations along its genome. Thus, the DNA sequence of a cancer genome encompasses a wealth of information about the identity and epigenomic features of its cell of origin.

Genome-wide patterns and properties of de novo mutations in humans

Mutations create variation in the population, fuel evolution and cause genetic diseases. Current knowledge about de novo mutations is incomplete and mostly indirect. Here we analyze 11,020 de novo mutations from the whole genomes of 250 families. We show that de novo mutations in the offspring of older fathers are not only more numerous but also occur more frequently in early-replicating, genic regions. Functional regions exhibit higher mutation rates due to CpG dinucleotides and show signatures of transcription-coupled repair, whereas mutation clusters with a unique signature point to a new mutational mechanism. Mutation and recombination rates independently associate with nucleotide diversity, and regional variation in human-chimpanzee divergence is only partly explained by heterogeneity in mutation rate. Finally, we provide a genome-wide mutation rate map for medical and population genetics applications. Our results provide new insights and refine long-standing hypotheses about human mutagenesis.

Differential Relationship of DNA Replication Timing to Different Forms of Human Mutation and Variation

Human genetic variation is distributed nonrandomly across the genome, though the principles governing its distribution are only partially known. DNA replication creates opportunities for mutation, and the timing of DNA replication correlates with the density of SNPs across the human genome. To enable deeper investigation of how DNA replication timing relates to human mutation and variation, we generated a high-resolution map of the human genomes replication timing program and analyzed its relationship to point mutations, copy number variations, and the meiotic recombination hotspots utilized by males and females. DNA replication timing associated with point mutations far more strongly than predicted from earlier analyses and showed a stronger relationship to transversion than transition mutations. Structural mutations arising from recombination-based mechanisms and recombination hotspots used more extensively by females were enriched in early-replicating parts of the genome, though these relationships appeared to relate more strongly to the genomic distribution of causative sequence features. These results indicate differential and sex-specific relationship of DNA replication timing to different forms of mutation and recombination.

T cell help controls the speed of the cell cycle in germinal center B cells

B cells have a need for speed High-affinity antibodies provide long-lasting protective immunity against many infections. Generating such antibodies requires help, in the form of T cells, which interact with antibody-producing B cells. As B cells proliferate and mutate their antibody genes, T cells select the cells producing high-affinity antibodies. Gitlin et al. show in mice that B cells that receive T cell help transit through the cell cycle more quickly by increasing the speed at which replication forks progress. Such a rapid cell cycle transition gives high-affinity B cells a selective advantage. Science, this issue p. 643 T cells help select high-affinity antibodies by increasing the speed at which B cells progress through the cell cycle. The germinal center (GC) is a microanatomical compartment wherein high-affinity antibody-producing B cells are selectively expanded. B cells proliferate and mutate their antibody genes in the dark zone (DZ) of the GC and are then selected by T cells in the light zone (LZ) on the basis of affinity. Here, we show that T cell help regulates the speed of cell cycle phase transitions and DNA replication of GC B cells. Genome sequencing and single-molecule analyses revealed that T cell help shortens S phase by regulating replication fork progression, while preserving the relative order of replication origin activation. Thus, high-affinity GC B cells are selected by a mechanism that involves prolonged dwell time in the DZ where selected cells undergo accelerated cell cycles.

Epigenetically-Inherited Centromere and Neocentromere DNA Replicates Earliest in S-Phase

Eukaryotic centromeres are maintained at specific chromosomal sites over many generations. In the budding yeast Saccharomyces cerevisiae, centromeres are genetic elements defined by a DNA sequence that is both necessary and sufficient for function; whereas, in most other eukaryotes, centromeres are maintained by poorly characterized epigenetic mechanisms in which DNA has a less definitive role. Here we use the pathogenic yeast Candida albicans as a model organism to study the DNA replication properties of centromeric DNA. By determining the genome-wide replication timing program of the C. albicans genome, we discovered that each centromere is associated with a replication origin that is the first to fire on its respective chromosome. Importantly, epigenetic formation of new ectopic centromeres (neocentromeres) was accompanied by shifts in replication timing, such that a neocentromere became the first to replicate and became associated with origin recognition complex (ORC) components. Furthermore, changing the level of the centromere-specific histone H3 isoform led to a concomitant change in levels of ORC association with centromere regions, further supporting the idea that centromere proteins determine origin activity. Finally, analysis of centromere-associated DNA revealed a replication-dependent sequence pattern characteristic of constitutively active replication origins. This strand-biased pattern is conserved, together with centromere position, among related strains and species, in a manner independent of primary DNA sequence. Thus, inheritance of centromere position is correlated with a constitutively active origin of replication that fires at a distinct early time. We suggest a model in which the distinct timing of DNA replication serves as an epigenetic mechanism for the inheritance of centromere position.

Random replication of the inactive X chromosome

In eukaryotic cells, genomic DNA replicates in a defined temporal order. The inactive X chromosome (Xi), the most extensive instance of facultative heterochromatin in mammals, replicates later than the active X chromosome (Xa), but the replication dynamics of inactive chromatin are not known. By profiling human DNA replication in an allele-specific, chromosomally phased manner, we determined for the first time the replication timing along the active and inactive chromosomes (Xa and Xi) separately. Replication of the Xi was different from that of the Xa, varied among individuals, and resembled a random, unstructured process. The Xi replicated rapidly and at a time largely separable from that of the euchromatic genome. Late-replicating, transcriptionally inactive regions on the autosomes also replicated in an unstructured manner, similar to the Xi. We conclude that DNA replication follows two strategies: slow, ordered replication associated with transcriptional activity, and rapid, random replication of silent chromatin. The two strategies coexist in the same cell, yet are segregated in space and time.

Thiol Peroxidase Deficiency Leads to Increased Mutational Load and Decreased Fitness in Saccharomyces cerevisiae

Thiol peroxidases are critical enzymes in the redox control of cellular processes that function by reducing low levels of hydroperoxides and regulating redox signaling. These proteins were also shown to regulate genome stability, but how their dysfunction affects the actual mutations in the genome is not known. Saccharomyces cerevisiae has eight thiol peroxidases of glutathione peroxidase and peroxiredoxin families, and the mutant lacking all these genes (∆8) is viable. In this study, we employed two independent ∆8 isolates to analyze the genome-wide mutation spectrum that results from deficiency in these enzymes. Deletion of these genes was accompanied by a dramatic increase in point mutations, many of which clustered in close proximity and scattered throughout the genome, suggesting strong mutational bias. We further subjected multiple lines of wild-type and ∆8 cells to long-term mutation accumulation, followed by genome sequencing and phenotypic characterization. ∆8 lines showed a significant increase in nonrecurrent point mutations and indels. The original ∆8 cells exhibited reduced growth rate and decreased life span, which were further reduced in all ∆8 mutation accumulation lines. Although the mutation spectrum of the two independent isolates was different, similar patterns of gene expression were observed, suggesting the direct contribution of thiol peroxidases to the observed phenotypes. Expression of a single thiol peroxidase could partially restore the growth phenotype of ∆8 cells. This study shows how deficiency in nonessential, yet critical and conserved oxidoreductase function, leads to increased mutational load and decreased fitness.

Analysis of somatic microsatellite indels identifies driver events in human tumors

Microsatellites (MSs) are tracts of variable-length repeats of short DNA motifs that exhibit high rates of mutation in the form of insertions or deletions (indels) of the repeated motif. Despite their prevalence, the contribution of somatic MS indels to cancer has been largely unexplored, owing to difficulties in detecting them in short-read sequencing data. Here we present two tools: MSMuTect, for accurate detection of somatic MS indels, and MSMutSig, for identification of genes containing MS indels at a higher frequency than expected by chance. Applying MSMuTect to whole-exome data from 6,747 human tumors representing 20 tumor types, we identified >1,000 previously undescribed MS indels in cancer genes. Additionally, we demonstrate that the number and pattern of MS indels can accurately distinguish microsatellite-stable tumors from tumors with microsatellite instability, thus potentially improving classification of clinically relevant subgroups. Finally, we identified seven MS indel driver hotspots: four in known cancer genes (ACVR2A, RNF43, JAK1, and MSH3) and three in genes not previously implicated as cancer drivers (ESRP1, PRDM2, and DOCK3).