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      Timing, rates and spectra of human germline mutation

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          Abstract

          Germline mutations are a driving force behind genome evolution and genetic disease. We investigated genome-wide mutation rates and spectra in multi-sibling families. Mutation rate increased with paternal age in all families, but the number of additional mutations per year differed more than two-fold between families. Meta-analysis of 6,570 mutations showed that germline methylation influences mutation rates. In contrast to somatic mutations, we found remarkable consistency of germline mutation spectra between the sexes and at different paternal ages. 3.8% of mutations were mosaic in the parental germline, resulting in 1.3% of mutations being shared between siblings. The number of these shared mutations varied significantly between families. Our data suggest that the mutation rate per cell division is higher during both early embryogenesis and differentiation of primordial germ cells, but is reduced substantially during post-pubertal spermatogenesis. These findings have important consequences for the recurrence risks of disorders caused by de novo mutations.

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          Most cited references31

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          Analysis of genetic inheritance in a family quartet by whole-genome sequencing.

          We analyzed the whole-genome sequences of a family of four, consisting of two siblings and their parents. Family-based sequencing allowed us to delineate recombination sites precisely, identify 70% of the sequencing errors (resulting in > 99.999% accuracy), and identify very rare single-nucleotide polymorphisms. We also directly estimated a human intergeneration mutation rate of approximately 1.1 x 10(-8) per position per haploid genome. Both offspring in this family have two recessive disorders: Miller syndrome, for which the gene was concurrently identified, and primary ciliary dyskinesia, for which causative genes have been previously identified. Family-based genome analysis enabled us to narrow the candidate genes for both of these Mendelian disorders to only four. Our results demonstrate the value of complete genome sequencing in families.
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            Toward better understanding of artifacts in variant calling from high-coverage samples.

            Heng Li (2014)
            Whole-genome high-coverage sequencing has been widely used for personal and cancer genomics as well as in various research areas. However, in the lack of an unbiased whole-genome truth set, the global error rate of variant calls and the leading causal artifacts still remain unclear even given the great efforts in the evaluation of variant calling methods. We made 10 single nucleotide polymorphism and INDEL call sets with two read mappers and five variant callers, both on a haploid human genome and a diploid genome at a similar coverage. By investigating false heterozygous calls in the haploid genome, we identified the erroneous realignment in low-complexity regions and the incomplete reference genome with respect to the sample as the two major sources of errors, which press for continued improvements in these two areas. We estimated that the error rate of raw genotype calls is as high as 1 in 10-15 kb, but the error rate of post-filtered calls is reduced to 1 in 100-200 kb without significant compromise on the sensitivity. BWA-MEM alignment and raw variant calls are available at http://bit.ly/1g8XqRt scripts and miscellaneous data at https://github.com/lh3/varcmp. hengli@broadinstitute.org Supplementary data are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
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              The origins, patterns and implications of human spontaneous mutation.

              J F Crow (2000)
              The germline mutation rate in human males, especially older males, is generally much higher than in females, mainly because in males there are many more germ-cell divisions. However, there are some exceptions and many variations. Base substitutions, insertion-deletions, repeat expansions and chromosomal changes each follow different rules. Evidence from evolutionary sequence data indicates that the overall rate of deleterious mutation may be high enough to have a large effect on human well-being. But there are ways in which the impact of deleterious mutations can be mitigated.
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                Author and article information

                Journal
                9216904
                2419
                Nat Genet
                Nat. Genet.
                Nature genetics
                1061-4036
                1546-1718
                1 December 2015
                14 December 2015
                February 2016
                01 August 2016
                : 48
                : 2
                : 126-133
                Affiliations
                [1 ]Wellcome Trust Sanger Institute, Hinxton, Cambridge, United Kingdom
                [2 ]Institute of Cardiovascular and Medical Sciences, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, United Kingdom
                [3 ]Medical Research Institute, University of Dundee, Dundee, United Kingdom
                [4 ]Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, Scotland, United Kingdom
                [5 ]Department of Human Genetics and Department of Bioinformatics and Computational Biology, Genentech Inc, 1 DNA Way, CA 94080 South San Francisco, USA
                Author notes
                Correspondence should be addressed to M.E.H. ( meh@ 123456sanger.ac.uk )
                [$]

                UK10K membership described in Supplementary Note

                Author Contributions

                R.R., A.W., and M.E.H. developed analytical and/or analysed sequencing data, R.R. performed mutation rate estimate, family comparison, germline mosaicism and validation, A.W. meta-analysed DNMs for mutational spectrum, methylation status, S.J.L., and R.J.H., contributed towards phasing and detection and validation of DNMs, L.B.A. performed mutational signature analysis, S.A.T. contributed to whole genome data analysis, A.D., A.M., D.P., and B.S. provided blood samples of SFHS, M.R.S. advised on mutational processes, UK10K Consortium, contributed sequences for meta-data analysis, R.R., A.W., M.E.H. wrote the manuscript, M.E.H. supervised the project. Authors have no competing financial interests.

                Article
                EMS66128
                10.1038/ng.3469
                4731925
                26656846
                c2940781-bde8-4f7d-9bdc-c20d05ddebb8

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                Genetics
                Genetics

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