Open Access

Computation of identity by descent probabilities conditional on DNA markers via a Monte Carlo Markov Chain method

Genetics Selection Evolution200032:467

https://doi.org/10.1186/1297-9686-32-5-467

Received: 11 January 2000

Accepted: 05 June 2000

Published: 15 September 2000

Abstract

The accurate estimation of the probability of identity by descent (IBD) at loci or genome positions of interest is paramount to the genetic study of quantitative and disease resistance traits. We present a Monte Carlo Markov Chain method to compute IBD probabilities between individuals conditional on DNA markers and on pedigree information. The IBDs can be obtained in a completely general pedigree at any genome position of interest, and all marker and pedigree information available is used. The method can be split into two steps at each iteration. First, phases are sampled using current genotypic configurations of relatives and second, crossover events are simulated conditional on phases. Internal track is kept of all founder origins and crossovers such that the IBD probabilities averaged over replicates are rapidly obtained. We illustrate the method with some examples. First, we show that all pedigree information should be used to obtain line origin probabilities in F2 crosses. Second, the distribution of genetic relationships between half and full sibs is analysed in both simulated data and in real data from an F2 cross in pigs.

Keywords

DNA markers identity by descent probability Monte Carlo Markov Chain

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Authors’ Affiliations

(1)
Area de Producció Animal, Centre UdL-IRTA
(2)
Department of Animal Science, Iowa State University
(3)
Station d'amélioration génétique des animaux, Institut national de la recherche agronomique

Copyright

© INRA, EDP Sciences 2000

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