Literature DB >> 22178309

Quantifying time-inhomogeneous stochastic introgression processes with hazard rates.

Atiyo Ghosh1, Maria Conceição Serra, Patsy Haccou.   

Abstract

Introgression is the permanent incorporation of genes from one population into another through hybridization and backcrossing. It is currently of particular concern as a possible mechanism for the spread of modified crop genes to wild populations. The hazard rate is the probability per time unit that such an escape takes place, given that it has not happened before. It is a quantitative measure of introgression risk that takes the stochastic elements inherent in introgression processes into account. We present a methodology to calculate the hazard rate for situations with time-varying gene flow from a crop to a large recipient wild population. As an illustration, several types of time-inhomogeneity are examined, including deterministic periodicity as well as random variation. Furthermore, we examine the effects of an extended fitness bottleneck of hybrids and backcrosses in combination with time-varying gene flow. It is found that bottlenecks decrease the hazard rate, but also slow down and delay its changes in reaction to changes in gene flow. Furthermore, we find that random variation in gene flow generates a lower hazard rate than analogous deterministic variation. We discuss the implications of our findings for crop management and introgression risk assessment.
Copyright © 2012 A. Ghosh. Published by Elsevier Inc. All rights reserved.

Mesh:

Year:  2011        PMID: 22178309     DOI: 10.1016/j.tpb.2011.11.006

Source DB:  PubMed          Journal:  Theor Popul Biol        ISSN: 0040-5809            Impact factor:   1.570


  2 in total

1.  Quantifying introgression risk with realistic population genetics.

Authors:  Atiyo Ghosh; Patrick G Meirmans; Patsy Haccou
Journal:  Proc Biol Sci       Date:  2012-10-10       Impact factor: 5.349

2.  Adaptive gene introgression after secondary contact.

Authors:  Hildegard Uecker; Derek Setter; Joachim Hermisson
Journal:  J Math Biol       Date:  2014-07-04       Impact factor: 2.164

  2 in total

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