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Non-crossover gene conversions show strong GC bias and unexpected clustering in humans

Amy L. Williams, Giulio Genovese, Thomas Dyer, Katherine Truax, Goo Jun, Nick Patterson, Joanne E. Curran, Ravi Duggirala, John Blangero, David Reich, Molly Przeworski, T2D-GENES Consortium
doi: https://doi.org/10.1101/009175
Amy L. Williams
1Biological Sciences Department, Columbia University, New York, NY 10027, USA
2Department of Systems Biology, Columbia University, New York, NY 10032, USA
3Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA
† Current affiliation: Department of Biological Statistics and Computational Biology, Cornell University, Ithaca, NY 14853, USA
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  • For correspondence: alw289@cornell.edu
Giulio Genovese
3Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA
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Thomas Dyer
4Department of Genetics, Texas Biomedical Research Institute, San Antonio, TX 78227, USA
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Katherine Truax
4Department of Genetics, Texas Biomedical Research Institute, San Antonio, TX 78227, USA
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Goo Jun
5Department of Biostatistics, University of Michigan, Ann Arbor, MI 48109, USA
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Nick Patterson
3Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA
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Joanne E. Curran
4Department of Genetics, Texas Biomedical Research Institute, San Antonio, TX 78227, USA
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Ravi Duggirala
4Department of Genetics, Texas Biomedical Research Institute, San Antonio, TX 78227, USA
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John Blangero
4Department of Genetics, Texas Biomedical Research Institute, San Antonio, TX 78227, USA
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David Reich
3Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA
6Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
7Howard Hughes Medical Institute, Harvard Medical School, Boston, MA 02115, USA
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Molly Przeworski
1Biological Sciences Department, Columbia University, New York, NY 10027, USA
2Department of Systems Biology, Columbia University, New York, NY 10032, USA
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Abstract

Although the past decade has seen tremendous progress in our understanding of fine-scale recombination, little is known about non-crossover (or “gene conversion”) resolutions. We report the first genome-wide study of non-crossover gene conversion events in humans. Using SNP array data from 94 meioses, we identified 107 sites affected by non-crossover events, of which 51/53 were confirmed in sequence data. Our results suggest that a site is involved in a non-crossover event at a rate of 6.7×10−6/bp/generation, consistent with results from sperm-typing studies. Observed non-crossover events show strong allelic bias, with 70% (61–79%) of events transmitting GC alleles (P=7.9×10−5), and have tracts lengths that vary over more than an order of magnitude. Strikingly, in 4 of 15 regions with available resequencing data, multiple (∼2–4) distinct non-crossover events cluster within ∼20–30 kb. This pattern has not been reported previously in mammals and is inconsistent with canonical models of double strand break repair.

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Posted September 16, 2014.
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Non-crossover gene conversions show strong GC bias and unexpected clustering in humans
Amy L. Williams, Giulio Genovese, Thomas Dyer, Katherine Truax, Goo Jun, Nick Patterson, Joanne E. Curran, Ravi Duggirala, John Blangero, David Reich, Molly Przeworski, T2D-GENES Consortium
bioRxiv 009175; doi: https://doi.org/10.1101/009175
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Non-crossover gene conversions show strong GC bias and unexpected clustering in humans
Amy L. Williams, Giulio Genovese, Thomas Dyer, Katherine Truax, Goo Jun, Nick Patterson, Joanne E. Curran, Ravi Duggirala, John Blangero, David Reich, Molly Przeworski, T2D-GENES Consortium
bioRxiv 009175; doi: https://doi.org/10.1101/009175

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