Using linked markers to estimate the genetic age of a volunteer population: a theoretical and empirical approach.
Volunteers deriving from unharvested seeds of a crop can lead to persistent feral populations and participate in genetic exchanges across the agro-ecosystem, both between crop varieties and between crops and their wild relatives. A first step to understand the importance of volunteers is to characterize their capacity to reproduce autonomously for several generations. For that purpose, we constructed and evaluated a maximum-likelihood method to estimate the genetic age of a population deriving from one of the most common field crop type: an F1-hybrid variety. The method estimates the number of reproduction cycles that occurred since the cultivation of that variety. It makes use of genotypic data at a number of linked microsatellite loci pairs, thus exploiting the recombination of parental haplotypes, which is expected to occur as the population is reproducing. Estimates with moderate bias and variance were found for a broad range of parameter values in simulations, and the method revealed robust to some deviations from the assumptions of the underlying model. We propose a specific procedure to test the hypothesis of persistence, that is has a given volunteer population experienced more than one cycle of reproduction since the F1-hybrid state? The method was applied to both an experimental and a natural sunflower volunteer population and revealed promising, considering these ideal case studies. Possible further developments toward more complex natural systems are discussed.
Ostrowski
M-F
MF
UMR DIA-PC 1097, INRA Montpellier, Domaine de Melgueil, Mauguio, France.
Rousselle
Y
Y
Tsitrone
A
A
Santoni
S
S
David
J
J
Reboud
X
X
Muller
M-H
MH
D003198:Computer Simulation; D018556:Crops, Agricultural / Q000235:genetics*; D036262:Empirical Research; D051456:Gene Flow; D005787:Gene Frequency; D008040:Genetic Linkage; D005819:Genetic Markers / Q000502:physiology; D049810:Genetic Speciation; D005828:Genetics, Population / Q000379:methods* / Q000706:statistics & numerical data; D006368:Helianthus / Q000235:genetics; D016013:Likelihood Functions; D008962:Models, Theoretical; D013223:Statistics as Topic / Q000379:methods*; D013997:Time Factors
D005819:Genetic Markers