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Estimating seven coefficients of pairwise relatedness using population genomic data

Matthew S Ackerman, Parul Johri, Ken Spitze, Sen Xu, Thomas Doak, Kimberly Young, Michael Lynch
doi: https://doi.org/10.1101/049411
Matthew S Ackerman
*Department of Biology, Indiana University, Bloomington, Indiana, USA
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  • For correspondence: matthew.s.ackerman@gmail.com
Parul Johri
*Department of Biology, Indiana University, Bloomington, Indiana, USA
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Ken Spitze
*Department of Biology, Indiana University, Bloomington, Indiana, USA
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Sen Xu
*Department of Biology, Indiana University, Bloomington, Indiana, USA
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Thomas Doak
*Department of Biology, Indiana University, Bloomington, Indiana, USA
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Kimberly Young
*Department of Biology, Indiana University, Bloomington, Indiana, USA
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Michael Lynch
*Department of Biology, Indiana University, Bloomington, Indiana, USA
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ABSTRACT

Population structure can be described by genotypic correlation coefficients between groups of individuals, the most basic of which are the pair-wise relatedness coefficients between any two individuals. There are nine pair-wise relatedness coefficients in the most general model, and we show that these can be reduced to seven coefficients for biallelic loci. Although all nine coefficients can be estimated from pedigrees, six coefficients have been beyond empirical reach. We provide a numerical optimization procedure that estimates them from population-genomic data. Simulations show that the procedure is nearly unbiased, even at 3× coverage, and errors in five of the seven coefficients are statistically uncorrelated. The remaining two coefficients have a negative correlation of errors, but their sum provides an unbiased assessment of the overall correlation of heterozygosity between two individuals. Application of these new methods to four populations of the freshwater crustacean Daphnia pulex reveal the occurrence of half-siblings in our samples, as well as a number of identical individuals that are likely obligately asexual clone-mates. Statistically significant negative estimates of these pair-wise relatedness coefficients, including inbreeding coefficents that were typically negative, underscore the difficulties that arise when interpreting genotypic correlations as estimations of the probability that alleles are identical by descent.

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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 4.0 International license.
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Posted April 20, 2016.
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Estimating seven coefficients of pairwise relatedness using population genomic data
Matthew S Ackerman, Parul Johri, Ken Spitze, Sen Xu, Thomas Doak, Kimberly Young, Michael Lynch
bioRxiv 049411; doi: https://doi.org/10.1101/049411
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Estimating seven coefficients of pairwise relatedness using population genomic data
Matthew S Ackerman, Parul Johri, Ken Spitze, Sen Xu, Thomas Doak, Kimberly Young, Michael Lynch
bioRxiv 049411; doi: https://doi.org/10.1101/049411

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