Long-term balancing selection drives evolution of immunity genes in Capsella
Abstract
Genetic drift is expected to remove polymorphism from populations over long periods of time, with the rate of polymorphism loss being accelerated when species experience strong reductions in population size. Adaptive forces that maintain genetic variation in populations, or balancing selection, might counteract this process. To understand the extent to which natural selection can drive the retention of genetic diversity, we document genomic variability after two parallel species-wide bottlenecks in the genus Capsella. We find that ancestral variation preferentially persists at immunity related loci, and that the same collection of alleles has been maintained in different lineages that have been separated for several million years. By reconstructing the evolution of the disease related locus MLO2b, we find that divergence between ancient haplotypes can be obscured by referenced based re-sequencing methods, and that trans-specific alleles can encode substantially diverged protein sequences. Our data point to long term balancing selection as an important factor shaping the genetics of immune systems in plants and as the predominant driver of genomic variability after a population bottleneck.
Data availability
All raw sequencing data are depsoited under the accession codes PRJEB6689.
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Whole genome resequencing of Capsella speciesEuropean Nucleotide Archive, PRJEB6689.
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Capsella grandiflora WGSEuropean Nucleotide Archive, PRJEB6689.
Article and author information
Author details
Funding
European Research Council (IMMUNEMESIS)
- Detlef Weigel
Human Frontier Science Program (LT000783/2010-L)
- Daniel Koenig
Deutsche Forschungsgemeinschaft (WE 2897/4-2)
- Detlef Weigel
Max-Planck-Gesellschaft (Open-access funding)
- Detlef Weigel
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Copyright
© 2019, Koenig et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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