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          Abstract

          Genes mutated in congenital malformation syndromes are frequently implicated in oncogenesis1,2, but the causative germline and somatic mutations occur in separate cells at different times of an organism’s life. Here we unify these processes for mutations arising in male germ cells that show a paternal age effect3. Screening of 30 spermatocytic seminomas4,5 for oncogenic mutations in 17 genes identified 2 mutations in FGFR3 (both 1948A>G encoding K650E, which causes thanatophoric dysplasia in the germline)6 and 5 mutations in HRAS. Massively parallel sequencing of sperm DNA showed that the FGFR3 mutation increases with paternal age, with a similar mutation spectrum at the K650 codon to that in bladder cancer7,8. Most spermatocytic seminomas show increased immunoreactivity for FGFR3 and/or HRAS. We propose that paternal age effect mutations activate a common “selfish” pathway supporting proliferation in the testis, leading to diverse phenotypes in the next generation including fetal lethality, congenital syndromes and cancer.

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          Most cited references51

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          Estimate of the mutation rate per nucleotide in humans.

          Many previous estimates of the mutation rate in humans have relied on screens of visible mutants. We investigated the rate and pattern of mutations at the nucleotide level by comparing pseudogenes in humans and chimpanzees to (i) provide an estimate of the average mutation rate per nucleotide, (ii) assess heterogeneity of mutation rate at different sites and for different types of mutations, (iii) test the hypothesis that the X chromosome has a lower mutation rate than autosomes, and (iv) estimate the deleterious mutation rate. Eighteen processed pseudogenes were sequenced, including 12 on autosomes and 6 on the X chromosome. The average mutation rate was estimated to be approximately 2.5 x 10(-8) mutations per nucleotide site or 175 mutations per diploid genome per generation. Rates of mutation for both transitions and transversions at CpG dinucleotides are one order of magnitude higher than mutation rates at other sites. Single nucleotide substitutions are 10 times more frequent than length mutations. Comparison of rates of evolution for X-linked and autosomal pseudogenes suggests that the male mutation rate is 4 times the female mutation rate, but provides no evidence for a reduction in mutation rate that is specific to the X chromosome. Using conservative calculations of the proportion of the genome subject to purifying selection, we estimate that the genomic deleterious mutation rate (U) is at least 3. This high rate is difficult to reconcile with multiplicative fitness effects of individual mutations and suggests that synergistic epistasis among harmful mutations may be common.
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            Frequent activating mutations of FGFR3 in human bladder and cervix carcinomas.

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              Evolution of primate gene expression.

              It has been suggested that evolutionary changes in gene expression account for most phenotypic differences between species, in particular between humans and apes. What general rules can be described governing expression evolution? We find that a neutral model where negative selection and divergence time are the major factors is a useful null hypothesis for both transcriptome and genome evolution. Two tissues that stand out with regard to gene expression are the testes, where positive selection has exerted a substantial influence in both humans and chimpanzees, and the brain, where gene expression has changed less than in other organs but acceleration might have occurred in human ancestors.
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                Author and article information

                Journal
                9216904
                2419
                Nat Genet
                Nat. Genet.
                Nature genetics
                1061-4036
                1546-1718
                2 February 2010
                25 October 2009
                November 2009
                01 May 2010
                : 41
                : 11
                : 1247-1252
                Affiliations
                [1 ] Weatherall Institute of Molecular Medicine, University of Oxford, John Radcliffe Hospital, Oxford OX3 9DS, UK.
                Department of Growth & Reproduction, Copenhagen University Hospital (Rigshospitalet), DK-2100 Copenhagen, Denmark.
                [3 ] Department of Pathology, Copenhagen University Hospital (Rigshospitalet), DK-2100 Copenhagen, Denmark.
                [4 ] Computational Biology Research Group, University of Oxford, Oxford OX3 9DS, UK
                [5 ] Department of Statistics, University of Oxford, South Parks Road, Oxford OX1 3TG, UK
                Author notes

                AUTHOR CONTRIBUTIONS A.G. designed and performed experiments, analyzed data and wrote the paper; R.M.S.H., I.B.T. and I.A.O. performed experiments; G.K.J. collected tumor samples; S.J.McG., S.P.P. and G.A.T.McV. developed analytical tools and analyzed data; E.R.D.M. collected tumor samples, designed and performed experiments; A.O.M.W. designed experiments, analyzed data and wrote the paper.

                Article
                UKMS27834
                10.1038/ng.470
                2817493
                19855393
                110368c6-206d-4ea2-8c40-ca0b1ab174d5

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                History
                Funding
                Funded by: Wellcome Trust :
                Award ID: 078666 || WT
                Categories
                Article

                Genetics
                Genetics

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