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Phylogeography of a widely distributed plant species reveals cryptic genetic lineages with parallel phenotypic responses to warming and drought conditions

Citation

Kahl, Sandra; Kappel, Christian; Joshi, Jasmin; Lenhard, Michael (2022), Phylogeography of a widely distributed plant species reveals cryptic genetic lineages with parallel phenotypic responses to warming and drought conditions, Dryad, Dataset, https://doi.org/10.5061/dryad.0p2ngf227

Abstract

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 Silene vulgaris 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 S. vulgaris 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 S. vulgaris and its intraspecific genetic lineages.

Methods

traitsgreenhouse_final_Dryad.txt is raw data of plant traits that have been measured on offspring plants grown in the greenhouse from open pollinated plants collected at the stated sites. 

matrix_worldclim.txt contains the data acquired from the WorldClim database from 1970–2000 (Fick and Hijmans, 2017) for sites of the open ollinated plants. 

sumstat_final_2020.txt and matrix_fst_final contain the genetic data (summary statistics) acquired via ddRAD sequencing and calculated via STACKS (v.2.4)

Usage Notes

traitsgreenhouse_final_Dryad.txt contains the raw data of plant traits measured as described above. Abbreviations: ID: plant identifier, dtg: days to germination, dtf: days to flowering, Sex: sex of the individuals, HI: first height measurement, HII: final hight measuremnt of flowering plants, BM: dry biomass, f: number of flowers, b: number of branches, l: number of leaves, Svvl: Survival, germ: germination, flow, flowering, la: leaf area, lm: leaf mass, sla: specific leaf area, lround: shape of the leaf, lperi: leaf perimeter, Popsize: population size, Mother: mother plant, Pop: population, clust2021: genetic gluster correspondence to STRUCTURE analysis, Elev: elevation of population, Lat: latitude of population, Trtmnt: Treatment in greenhouse experiment, Prec: precipitation treatment in greenhouse experiment, Temp: temperature treatment in greenhouse experiment, Tray_grad: arrangement of trays (with plant pots) in the greenhouse, Tray_ind: individual tray number (with plant pots) in the greenhouse.

matrix_worldclim.txt - abbreviations of content: bio_1: annual mean temperature, bio_2: mean diurnal range (mean of monthly (max temp - min temp)), bio_3: isothermality (bio_2/bio_7), bio_4: temperature seasonality (standard deviation), bio_5: maximum temperature warmest month, bio_6: minimum temperature coldest month, bio_7: temperature annual range (bio_5-bio_6), bio_8: mean temperature of wettest quarter, bio_9: mean temperature of driest quarter, bio_10: mean temperature of warmest quarter, bio_11: mean temperature of coldest quarter. All temperature variables are in °C. bio_12: annual mean precipitation, bio_13: precipitation wettest month, bio_14: precipitation driest month, bio_15: precipitation seasonality (coefficient of variation), bio_16: precipitation wettest quarter, bio_17: precipitation driest quarter, bio_18: precipitation warmest quarter, bio_19: precipitation coldest quarter, s_rad: solar radiation in kJ/(m²*d), w_sp: wind speed in m*s-1, w_v_pr: water vapor pressure in kPa. All precipitation variables are in mm.

sumstat_final_2020.txt - abbreviations: Fis: inbreeding coefficient, Pi: nucleotide diversity, He: expected heterozygosity, Ho: observed heterozygosity

matrix_fst_final - the abbeviations stand for the different populations of sampled Silene vulgaris populations. The file contains a matrix of their interpopulation component Fst 

Funding

Universität Potsdam