Papers by Dmitry Gordenin
Genome Research, 2014
Mutational heterogeneity must be taken into account when reconstructing evolutionary histories, c... more Mutational heterogeneity must be taken into account when reconstructing evolutionary histories, calibrating molecular clocks, and predicting links between genes and disease. Selective pressures and various DNA transactions have been invoked to explain the heterogeneous distribution of genetic variation between species, within populations, and in tissue-specific tumors. To examine relationships between such heterogeneity and variations in leading- and lagging-strand replication fidelity and mismatch repair, we accumulated 40,000 spontaneous mutations in eight diploid yeast strains in the absence of selective pressure. We found that replicase error rates vary by fork direction, coding state, nucleosome proximity, and sequence context. Further, error rates and DNA mismatch repair efficiency both vary by mismatch type, responsible polymerase, replication time, and replication origin proximity. Mutation patterns implicate replication infidelity as one driver of variation in somatic and germline evolution, suggest mechanisms of mutual modulation of genome stability and composition, and predict future observations in specific cancers.
Nature, 2013
Major international projects are underway that are aimed at creating a comprehensive catalogue of... more 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 1-9 . 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 falsepositive 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.
Mutations are the frequent cause of cancer. They are mostly viewed as independent events distribu... more Mutations are the frequent cause of cancer. They are mostly viewed as independent events distributed randomly across chromosomes. However, mutation distribution can be affected by permanent or transient features of genome structure and function. The extreme form of nonrandom distributions is a mutation cluster with multiple mutations concentrated in a tiny fraction of the genome. Multiple lesions in abnormally long regions of transient single-stranded deoxyribonucleic acid (DNA) can cause mutation clusters, which have been found in a majority of human cancer types. Mutation spectra indicated that many clusters in cancer genomes were caused by a subclass of apolipoprotein B mRNA-editing polypeptide-like (APOBEC) cytidine deaminases. These enzymes function to restrict retroviruses and retrotransposons by converting cytidine to uridine in single-stranded complementary DNAs (cDNAs). The simple mutation spectra in clusters aided in highlighting APOBECs among the complex set of mutagenic mechanisms operating throughout many cancer genomes. Thus, clusters are an analytical tool for deciphering cancer mutation mechanisms.
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Papers by Dmitry Gordenin