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Surprising impacts of crossover interference and sex-specific genetic maps on identical by descent distributions

View ORCID ProfileMadison Caballero, View ORCID ProfileDaniel N. Seidman, View ORCID ProfileThomas D. Dyer, View ORCID ProfileDonna M. Lehman, Joanne E. Curran, Ravindranath Duggirala, View ORCID ProfileJohn Blangero, View ORCID ProfileAmy L. Williams
doi: https://doi.org/10.1101/527655
Madison Caballero
1 Cornell University;
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  • For correspondence: mc2698@cornell.edu
Daniel N. Seidman
1 Cornell University;
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  • For correspondence: dns67@cornell.edu
Thomas D. Dyer
2 University of Texas Rio Grande Valley School of Medicine;
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  • For correspondence: thomas.dyer@utrgv.edu
Donna M. Lehman
3 University of Texas Health Science Center at San Antonio
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  • For correspondence: lehman@uthscsa.edu
Joanne E. Curran
2 University of Texas Rio Grande Valley School of Medicine;
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  • For correspondence: joanne.curran@utrgv.edu
Ravindranath Duggirala
2 University of Texas Rio Grande Valley School of Medicine;
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  • For correspondence: ravindranath.duggirala@utrgv.edu
John Blangero
2 University of Texas Rio Grande Valley School of Medicine;
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  • For correspondence: john.blangero@utrgv.edu
Amy L. Williams
1 Cornell University;
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  • For correspondence: awilliams@cornell.edu
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Abstract

Simulations of relatives and identical by descent (IBD) segments are common in genetic studies, yet nearly all past efforts have utilized sex averaged genetic maps while ignoring crossover interference, thus omitting factors known to affect the breakpoints of IBD segments. We developed a method for simulating relatives called Ped-sim that can utilize either sex-specific or sex averaged genetic maps and also either a model of crossover interference or the traditional Poisson distribution for inter-crossover distances. To characterize the impact of previously ignored mechanisms, we simulated data for all four possible combinations of these factors using high resolution human genetic maps and interference parameters. Modeling crossover interference heavily influences the distribution of the proportion of their genome relatives share IBD, decreasing the standard deviation by 11.2% on average for relatives ranging from full siblings to second cousins. By contrast, sex-specific maps increase the standard deviation of IBD proportion by an average of 3.37%, and also impact the number of segments relatives share, most notably producing a bimodal distribution in segment numbers shared by half-siblings. We further compared IBD sharing rates between simulated and real relatives, finding that the combination of sex-specific maps and interference modeling most accurately captures real IBD sharing rates for the relationships we considered. Under this model, pairwise IBD sharing rates depend on the sexes of the individuals through which they are related. For example, when connected only through females (and their common fifth great-grandfather), 12.8% of sixth cousins have some IBD sharing, while this rate drops to 9.05% for male-descent sixth cousins. These analyses demonstrate that sex-specific maps and interference are key factors impacting IBD sharing and underscore the necessity of incorporating these effects into simulations.

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Posted January 22, 2019.
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Surprising impacts of crossover interference and sex-specific genetic maps on identical by descent distributions
Madison Caballero, Daniel N. Seidman, Thomas D. Dyer, Donna M. Lehman, Joanne E. Curran, Ravindranath Duggirala, John Blangero, Amy L. Williams
bioRxiv 527655; doi: https://doi.org/10.1101/527655
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Surprising impacts of crossover interference and sex-specific genetic maps on identical by descent distributions
Madison Caballero, Daniel N. Seidman, Thomas D. Dyer, Donna M. Lehman, Joanne E. Curran, Ravindranath Duggirala, John Blangero, Amy L. Williams
bioRxiv 527655; doi: https://doi.org/10.1101/527655

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