Extensive Variation in the Mutation Rate Between and Within Human Genes Associated with Mendelian Disease

Smith, Thomas; Ho, Gladys; Christodoulou, John; Price, Elizabeth; Onadim, Zerrin; Gauthier‐Villars, Marion; Dehainault, Catherine; Houdayer, Claude; Parfait, Béatrice; Minkelen, Rick van; Lohman, Dietmar; Eyre‐Walker, Adam

doi:10.1002/humu.22967

Cited by 21 publications

(27 citation statements)

References 26 publications

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“…We hypothesized that we might achieve a better fit if we consider the fact that some sites have higher intrinsic mutation rates than the mean for the particular nucleotide change at that site; this notion has received increasing support in the recent decade from both evolutionary and family-based studies of human mutation rates [32–35,37,60–62]. We therefore augmented the Jukes-Cantor model by incorporating additional variation in mutation rates across sites belonging to each mutation type (see Materials and Methods).…”

Section: Resultsmentioning

confidence: 99%

Mutation Rate Variation is a Primary Determinant of the Distribution of Allele Frequencies in Humans

2016

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The site frequency spectrum (SFS) has long been used to study demographic history and natural selection. Here, we extend this summary by examining the SFS conditional on the alleles found at the same site in other species. We refer to this extension as the “phylogenetically-conditioned SFS” or cSFS. Using recent large-sample data from the Exome Aggregation Consortium (ExAC), combined with primate genome sequences, we find that human variants that occurred independently in closely related primate lineages are at higher frequencies in humans than variants with parallel substitutions in more distant primates. We show that this effect is largely due to sites with elevated mutation rates causing significant departures from the widely-used infinite sites mutation model. Our analysis also suggests substantial variation in mutation rates even among mutations involving the same nucleotide changes. In summary, we show that variable mutation rates are key determinants of the SFS in humans.

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Section: Resultsmentioning

confidence: 99%

Mutation Rate Variation is a Primary Determinant of the Distribution of Allele Frequencies in Humans

2016

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“…However, there is limited knowledge available for the somatic mutations in normal cells, particularly in WBCs, which are the main contributors for the background mutations. Human genomic mutations occur at a rate of approximately 2.5 × 10 8 per base per cell generation 14 . The Campbell group studied the background mutation spectrum of skin samples and focused on 74 cancer genes in normal skin samples from four individuals; their results proved that somatic mutations accumulate in normal cells, although the mechanisms were poorly understood 15 .…”

Section: Introductionmentioning

confidence: 99%

Statistical analysis of mutant allele frequency level of circulating cell-free DNA and blood cells in healthy individuals

Xia

Zhou

et al. 2017

Sci Rep

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Cell-free DNA (cfDNA) in plasma has emerged as a potential important biomarker in clinical diagnostics, particularly in cancer. However, somatic mutations are also commonly found in healthy individuals, which interfere with the effectiveness for cancer diagnostics. This study examined the background somatic mutations in white blood cells (WBC) and cfDNA in healthy controls based on sequencing data from 821 non-cancer individuals and several cancer samples with the aim of understanding the patterns of mutations detected in cfDNA. We determined the mutation allele frequencies in both WBC and cfDNA using a panel of 50 cancer-associated genes that covers 20 K-nucleotide region and ultra-deep sequencing with average depth >40000-fold. Our results showed that most of the mutations in cfDNA were highly correlated to WBC. We also observed that the NPM1 gene was the most frequently mutated gene in both WBC and cfDNA. Our study highlighted the importance of sequencing both cfDNA and WBC to improve the sensitivity and accuracy for calling cancer-related mutations from circulating tumour DNA, and shedded light on developing a strategy for early cancer diagnosis by cfDNA sequencing.

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“…Third, the level of variation in the density of SNVs is much greater than has been observed or suggested for variation in the mutation rate (Hodgkinson & Eyre-Walker, 2011;Kong et al, 2012;Michaelson et al, 2012) though see a recent analysis of de novo germ-line mutations which suggests there could be extreme mutational heterogeneity (Smith et al, 2016); some sites are estimated to have rates of SNV production that are tens of thousands of times faster than the genomic average.…”

Section: Parameter Estimationmentioning

confidence: 95%

“…However, as yet there has been no attempt to quantify the level of cryptic variation in the mutation rate at the single nucleotide level in the somatic genome. This is an important property to understand; for example a site which experiences a recurrence of SNVs across many cancer genomes would be of interest as a potential driver of cancer (Lawrence et al, 2013), however, this site might simply be cryptically hypermutable (Hodgkinson, Ladoukakis & Eyre-Walker, 2009;Eyre-Walker & Eyre-Walker, 2014;Smith et al, 2016). Here we examine the distribution of recurrent SNVs taken from 507 whole genome sequences made publicly available by Alexandrov et al (2013) to investigate the level of cryptic variation in the mutation rate for somatic tissues.…”

Section: Introductionmentioning

confidence: 99%

Are sites with multiple single nucleotide variants in cancer genomes a consequence of drivers, hypermutable sites or sequencing errors?

Smith

Carr

Eyre‐Walker

2016

Preprint

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Across indepedent cancer genomes it has been observed that some sites have been recurrently hit by single nucleotide variants (SNVs). Such recurrently hit sites might be either i) drivers of cancer that are postively selected during oncogenesis, ii) due to mutation rate variation, or iii) due to sequencing and assembly errors. We have investigated the cause of recurrently hit sites in a dataset of >3 million SNVs from 507 complete cancer genome sequences. We find evidence that many sites have been hit significantly more often than one would expect by chance, even taking into account the effect of the adjacent nucleotides on the rate of mutation. We find that the density of these recurrently hit sites is higher in non-coding than coding DNA and hence conclude that most of them are unlikely to be drivers. We also find that most of them are found in parts of the genome that are not uniquely mappable and hence are likly to be due to mapping errors. In support of the error hypothesis, we find that recurently hit sites are not randomly distributed across sequences from different laboratories. We fit a model to the data in which the rate of mutation is constant across sites but the rate of error varies. This model suggests that ~4% of all SNVs are error in this dataset, but that the rate of error varies by thousands-of-fold. Abstract.Across indepedent cancer genomes it has been observed that some sites have been recurrently hit by single nucleotide variants (SNVs). Such recurrently hit sites might be either i) drivers of cancer that are postively selected during oncogenesis, ii) due to mutation rate variation, or iii) due to sequencing and assembly errors. We have investigated the cause of recurrently hit sites in a dataset of >3 million SNVs from 507 complete cancer genome sequences. We find evidence that many sites have been hit significantly more often than one would expect by chance, even taking into account the effect of the adjacent nucleotides on the rate of mutation. We find that the density of these recurrently hit sites is higher in non-coding than coding DNA and hence conclude that most of them are unlikely to be drivers. We also find that most of them are found in parts of the genome that are not uniquely mappable and hence are likly to be due to mapping errors. In support of the error hypothesis, we find that recurently hit sites are not randomly distributed across sequences from different laboratories. We fit a model to the data in which the rate of mutation is constant across sites but the rate of error varies. This model suggests that ~4% of all SNVs are error in this dataset, but that the rate of error varies by thousands-of-fold.

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Extensive Variation in the Mutation Rate Between and Within Human Genes Associated with Mendelian Disease

Cited by 21 publications

References 26 publications

Mutation Rate Variation is a Primary Determinant of the Distribution of Allele Frequencies in Humans

Mutation Rate Variation is a Primary Determinant of the Distribution of Allele Frequencies in Humans

Statistical analysis of mutant allele frequency level of circulating cell-free DNA and blood cells in healthy individuals

Are sites with multiple single nucleotide variants in cancer genomes a consequence of drivers, hypermutable sites or sequencing errors?

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