It has long been suspected that the rate of mutation varies across the human genome at a large scale based on the divergence between humans and other species. However, it is now possible to directly investigate this question using the large number of de novo mutations (DNMs) that have been discovered in humans through the sequencing of trios. We investigate a number of questions pertaining to the distribution of mutations using more than 130,000 DNMs from three large datasets. We demonstrate that the amount and pattern of variation differs between datasets at the 1MB and 100KB scales probably as a consequence of differences in sequencing technology and processing. In particular, datasets show different patterns of correlation to genomic variables such as replication time. Never-the-less there are many commonalities between datasets, which likely represent true patterns. We show that there is variation in the mutation rate at the 100KB, 1MB and 10MB scale that cannot be explained by variation at smaller scales, however the level of this variation is modest at large scales–at the 1MB scale we infer that ~90% of regions have a mutation rate within 50% of the mean. Different types of mutation show similar levels of variation and appear to vary in concert which suggests the pattern of mutation is relatively constant across the genome. We demonstrate that variation in the mutation rate does not generate large-scale variation in GC-content, and hence that mutation bias does not maintain the isochore structure of the human genome. We find that genomic features explain less than 40% of the explainable variance in the rate of DNM. As expected the rate of divergence between species is correlated to the rate of DNM. However, the correlations are weaker than expected if all the variation in divergence was due to variation in the mutation rate. We provide evidence that this is due the effect of biased gene conversion on the probability that a mutation will become fixed. In contrast to divergence, we find that most of the variation in diversity can be explained by variation in the mutation rate. Finally, we show that the correlation between divergence and DNM density declines as increasingly divergent species are considered.

Background: Familial isolated hyperparathyroidism (FIHP) is a hereditary disorder characterised by uni-or multiglandular parathyroid disease. A subset of families are likely to be genetic variants of other familial tumour syndromes in which PHPT is the main feature, for example multiple endocrine neoplasia type 1 (MEN 1) and the hyperparathyroidism-jaw tumour syndrome (HPT-JT). Objective: To investigate seven families diagnosed with FIHP, each with two to eight affected family members, to clarify the underlying genetic mechanism. Methods: The entire MEN1 gene was sequenced for germline mutations and, in addition, tumour specimens were analysed in comparative genomic hybridisation and loss of heterozygosity studies. Results: Two families exhibited MEN1 mutations, L112V and 1658delG, which were associated with loss of the wild-type 11q13 alleles in all tumours analysed. In the remaining five families, no MEN1 mutation was identified. Conclusion: These results support the involvement of the MEN1 tumour suppressor gene in the pathogenesis of some of the FIHP kindreds. However, loss on chromosome 11 was seen in all tumours exhibiting somatic deletions, although in two families the tumour deletions involved 11q distal to MEN1. We conclude that the altered MEN1 gene function is of importance in the development of FIHP.

(2016) Extensive variation in the mutation rate between and within human genes associated with Mendelian disease. Human Mutation, 37 (5). pp. 488-494. ISSN 1059-7794 This version is available from Sussex Research Online: http://sro.sussex.ac.uk/60084/ This document is made available in accordance with publisher policies and may differ from the published version or from the version of record. If you wish to cite this item you are advised to consult the publisher's version. Please see the URL above for details on accessing the published version. Copyright and reuse:Sussex Research Online is a digital repository of the research output of the University.Copyright and all moral rights to the version of the paper presented here belong to the individual author(s) and/or other copyright owners. To the extent reasonable and practicable, the material made available in SRO has been checked for eligibility before being made available.Copies of full text items generally can be reproduced, displayed or performed and given to third parties in any format or medium for personal research or study, educational, or not-for-profit purposes without prior permission or charge, provided that the authors, title and full bibliographic details are credited, a hyperlink and/or URL is given for the original metadata page and the content is not changed in any way. AbstractWe have investigated whether the mutation rate varies between genes and sites using de novo mutations (DNMs) from three genes associated with Mendelian diseases. We show that the relative frequency of mutations at CpG dinucleotides relative to non-CpG sites varies between genes and relative to the genomic average. In particular we show that the rate of transition mutation at CpG sites relative to the rate of non-CpG transversion is substantially higher in our the disease genes than amongst DNMs in general; the rate of CpG transition can be several hundred-fold greater than the rate of non-CpG transversion. We also show that the mutation rate varies significantly between sites of a particular mutational type, such as non-CpG transversion, within a gene. We estimate that for all categories of sites, except CpG transitions, 3 there is at least a 30-fold difference in the mutation rate between the 10% of sites with the highest and lowest mutation rates. However, our best estimate is that the mutation rate varies by several hundred-fold variation. We suggest that the presence of hypermutable sites may be one reason certain genes are associated with disease.

The rate of divergence between species, and the level diversity within a species, are expected to depend on the rate of mutation. Here we investigate the relationship between divergence, diversity and the rate of mutation across the human genome at scales of 1MB and 100KB using >40,000 de novo mutations (DNM). We show that there is significant variation in the rate of DNM across the human genome, but that the variation is modest. Different types of mutation show similar levels of variation and appear to vary in concert. Regressing the rate of DNM against a range of genomic features suggests that nucleosome occupancy is the most important correlate, but that GC content, recombination rate, replication time and various histone methylation signals also correlate significantly. In total the model explains 75% of the explainable variance. As expected the rate of divergence between species and the level of diversity within humans is correlated to the rate of DNM. However, the correlations are weaker than if all the variation in divergence was due to variation in the mutation rate. We provide evidence that this is due the effect of biased gene conversion on the probability that a mutation will become fixed. Finally, we show that the correlation between divergence and DNM density declines as increasingly divergent species are considered. Our results have important implications for the use of divergence and diversity data to study variation in the mutation rate.

Across independent 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 likely 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 errors in this dataset, but that the rate of error varies by thousands-of-fold between sites.