Phylogeography of a widely distributed plant species reveals cryptic genetic lineages with parallel phenotypic responses to warming and drought conditions
<p>To predict how widely distributed species will perform under future climate change it is crucial to understand and reveal their underlying phylogenetics. However, detailed information about plant adaptation and its genetic basis and history remains scarce and especially widely distributed species receive little attention despite their putatively high adaptability. To examine the adaptation potential of a widely distributed species, we sampled the model plant <em>Silene vulgaris</em> across Europe. In a greenhouse experiment, we exposed the offspring of these populations to a climate-change scenario for central Europe and revealed the population structure through whole genome sequencing. Plants were grown under two temperature (18°C, 21°C) and three precipitation regimes (65 mm, 75 mm, 90 mm) to measure their response in biomass and fecundity related traits. To reveal the population genetic structure, ddRAD sequencing was employed for a whole genome approach. We found three major genetic clusters in <em>S. vulgaris</em> from Europe: one cluster comprising Southern European populations, one cluster of Western European populations and another cluster containing Central European populations. Population genetic diversity decreased with increasing latitude and a Mantel test revealed significant correlations between FST and geographic distances as well as between genetic and environmental distances. Our trait analysis showed that the genetic clusters significantly differed in biomass-related traits and in the days to flowering. However, half of the traits showed parallel response patterns to the experimental climate change scenario. Due to the differentiated but parallel response patterns, we assume that phenotypic plasticity plays an important role for the adaptation of the widely distributed species <em>S. vulgaris</em> and its intraspecific genetic lineages.</p>
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32/100
Overall dataset sharing score
Score breakdown
These five areas show where the dataset supports — or may limit — practical reuse.
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- 8
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