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RaBoT: a rarefaction-by-bootstrap method to compare genome-wide levels of genetic diversity

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Abstract

Context

No efficient method is available to compare multi-locus estimates of diversity while taking into account inter-locus and inter-population stochastic variance. The advent of genome scan approaches makes the development of such tests absolutely necessary.

Aims

We developed a method to compare genome-wide diversity estimates while taking into account—and factoring out—variation in census size and making use of inter-locus variance to assess significance of differences in diversity levels.

Methods

An approach based on rarefaction with bootstrap re-sampling (RaBoT) was implemented into a test of multi-locus comparison of diversity coded in R. The properties of the test were studied by applying it to simulated populations with varying diversity levels and varying differences in diversity levels. The test was then applied to empirical data from disturbed and undisturbed populations of Virola michelii (Myristicaceae) genotyped at 693 amplified fragment length polymorphism (AFLP) markers.

Results

RaBoT was found to be rather conservative, with large numbers of false negatives when the diversity in the compared populations was similar, and false positives mostly associated to comparisons of populations with extremely high levels of diversity. When applied to empirical data, RaBoT detected higher genetic diversity in a post-disturbance than in an undisturbed population and lower genetic diversity in a seedling than in the corresponding adult population, but it also revealed differences in diversity between subgroups within the disturbed and undisturbed plots.

Conclusion

RaBoT is a sensitive method to compare multi-locus levels of diversity that can be applied both at the genotype level for dominant markers (e.g. AFLP) and at the allele level for biallelic codominant markers (e.g. single-nucleotide polymorphisms).

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Acknowledgments

The authors wish to thank Saint-Omer Cazal for plant material collection and DNA extractions. We wish to thank Eric Marcon, Caroline Scotti-Saintagne, Rosane G. Collevatti, Andrea Piotti and Pierre-Michel Forget for critically reading the manuscript.

Funding

The research was funded by the “ECOFOR—Biodiversité et gestion forestière” program.

Author information

Authors and Affiliations

  1. Unité Mixte de Recherche “Ecologie des Forêts de Guyane” (EcoFoG), INRA—Institut National de la Recherche Agronomique, BP 709, 97387, Kourou Cedex, French Guiana, France

    Ivan Scotti

  2. Unité Mixte de Recherche “Ecologie des Forêts de Guyane” (EcoFoG), Université des Antilles et de la Guyane, Kourou, French Guiana, France

    William Montaigne

  3. Department of Forest Tree Breeding, Experiment Station and Arboretum, Forest Research Institute, Sárvár, Hungary

    Klára Cseke

  4. Unité Mixte de Recherche “Ecologie des Forêts de Guyane” (EcoFoG), AgroParisTech, Kourou, French Guiana, France

    Stéphane Traissac

Authors
  1. Ivan Scotti
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  2. William Montaigne
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  3. Klára Cseke
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  4. Stéphane Traissac
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Corresponding author

Correspondence to Ivan Scotti.

Additional information

Handling Editor: Bruno Fady

Contribution of the co-authors

IS designed the experiment, ran data analyses and wrote the paper.

WM collected data, ran data analyses and wrote the paper.

KC collected data and ran data analyses.

ST ran data analyses and wrote the paper.

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Scotti, I., Montaigne, W., Cseke, K. et al. RaBoT: a rarefaction-by-bootstrap method to compare genome-wide levels of genetic diversity. Annals of Forest Science 70, 631–635 (2013). https://doi.org/10.1007/s13595-013-0302-z

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  • DOI: https://doi.org/10.1007/s13595-013-0302-z

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