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Extremely rare variants reveal patterns of germline mutation rate heterogeneity in humans

View ORCID ProfileJedidiah Carlson, View ORCID ProfileAdam E Locke, View ORCID ProfileMatthew Flickinger, View ORCID ProfileMatthew Zawistowski, View ORCID ProfileShawn Levy, The BRIDGES Consortium, View ORCID ProfileRichard M Myers, View ORCID ProfileMichael Boehnke, View ORCID ProfileHyun Min Kang, View ORCID ProfileLaura J Scott, View ORCID ProfileJun Z Li, Sebastian Zöllner
doi: https://doi.org/10.1101/108290
Jedidiah Carlson
1Department of Computational Medicine & Bioinformatics, University of Michigan, Ann Arbor, MI, USA
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Adam E Locke
2McDonnell Genome Institute & Department of Medicine, Washington University, St. Louis, MO, USA
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Matthew Flickinger
3Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA
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Matthew Zawistowski
3Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA
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Shawn Levy
4HudsonAlpha Institute for Biotechnology, Huntsville, AL, USA
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Richard M Myers
4HudsonAlpha Institute for Biotechnology, Huntsville, AL, USA
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Michael Boehnke
3Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA
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Hyun Min Kang
3Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA
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Laura J Scott
3Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA
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Jun Z Li
1Department of Computational Medicine & Bioinformatics, University of Michigan, Ann Arbor, MI, USA
5Department of Human Genetics, University of Michigan, Ann Arbor, MI, USA
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Sebastian Zöllner
3Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA
6Department of Psychiatry, University of Michigan, Ann Arbor, MI, USA
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Abstract

A detailed understanding of the genome-wide variability of single-nucleotide germline mutation rates is essential to studying human genome evolution. Here we use ∼36 million singleton variants from 3,560 whole-genome sequences to infer fine-scale patterns of mutation rate heterogeneity. Mutability is jointly affected by adjacent nucleotide context and diverse genomic features of the surrounding region, including histone modifications, replication timing, and recombination rate, sometimes suggesting specific mutagenic mechanisms. Remarkably, GC content, DNase hypersensitivity, CpG islands, and H3K36 trimethylation are associated with both increased and decreased mutation rates depending on nucleotide context. We validate these estimated effects in an independent dataset of ∼46,000 de novo mutations, and confirm our estimates are more accurate than previously published estimates based on ancestrally older variants without considering genomic features. Our results thus provide the most refined portrait to date of the factors contributing to genome-wide variability of the human germline mutation rate.

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  • ↵* a full list of BRIDGES collaborators is provided in the supplementary material

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-ND 4.0 International license.
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Posted October 05, 2017.
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Extremely rare variants reveal patterns of germline mutation rate heterogeneity in humans
Jedidiah Carlson, Adam E Locke, Matthew Flickinger, Matthew Zawistowski, Shawn Levy, The BRIDGES Consortium, Richard M Myers, Michael Boehnke, Hyun Min Kang, Laura J Scott, Jun Z Li, Sebastian Zöllner
bioRxiv 108290; doi: https://doi.org/10.1101/108290
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Extremely rare variants reveal patterns of germline mutation rate heterogeneity in humans
Jedidiah Carlson, Adam E Locke, Matthew Flickinger, Matthew Zawistowski, Shawn Levy, The BRIDGES Consortium, Richard M Myers, Michael Boehnke, Hyun Min Kang, Laura J Scott, Jun Z Li, Sebastian Zöllner
bioRxiv 108290; doi: https://doi.org/10.1101/108290

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