Directional and stabilizing selection shaped morphological, reproductive, and physiological traits of the invader Solidago canadensis
Data files
Aug 04, 2023 version files 334.29 KB
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EE_data_for_Dryad.xlsx
327.95 KB
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README.md
6.33 KB
Aug 03, 2023 version files 333.72 KB
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EE_data_for_Dryad.xlsx
327.95 KB
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README.md
5.77 KB
Abstract
Trait evolution in invasive plant species is important because it can impact demographic parameters key to invasion success. Invasive plant species often show phenotypic clines along geographic and climatic gradients. However, the relative contributions of natural selection and neutral evolutionary processes to phenotypic trait variation among populations of invasive plants remains unclear. A common method to assess whether a trait has been shaped by natural selection or neutral evolutionary processes is to compare the geographical pattern for the trait of interest to the divergence in neutral genetic loci (i.e., QST-FST comparisons). A redundancy analysis (RDA) can facilitate identification of putative agents of natural selection on the trait. Here, we employed both a QST-FST comparisons approach and RDA to infer whether natural selection shaped traits of invasive populations of S. canadensis in China and identify the potential environmental drivers of natural selection. We addressed two questions: (1) Does natural selection drive phenotypic trait variation among S. canadensis populations? (2) Do climatic, latitudinal, longitudinal, and altitudinal gradients drive patterns of genetic variation among S. canadensis populations? We found significant directional selection for several morphological and reproductive traits (i.e., QST >FST) and stabilizing selection for physiological traits (i.e., QST < FST). The RDA showed that stem biomass of S. canadensis was strongly positively correlated with longitude, while leaf width ratio and specific leaf area were significantly positively correlated with mean diurnal range. Stem biomass had a strong negative correlation with annual precipitation. Moreover, height of S. canadensis individuals was strongly positively correlated with altitude and precipitation of the wettest quarter. Precipitation seasonality that was associated with longitudinal shift in China likely selected for larger stem biomass in S. canadensis. Overall, these results suggest that longitudinal and altitudinal clines in climate exerted strong selection pressures that shaped phenotypic traits of S. canadensis.
README: Title of Dataset
This README file was generated on 2023-08-03 by Junmin Li.
Directional and stabilizing selection shaped morphological, reproductive, and physiological traits of the invader Solidago canadensis
Date of data collection
Phenotypic tratis were collected on 2014 and 2015. SSR data were collected on 2013.
Links to publications that cite or use the data
Du LS, Oduor AMO, Zuo W, Liu HY, Li JM. Directional and stabilizing selection shaped morphological, reproductive, and physiological traits of the invader Solidago canadensis. Ecology and Evolution, 2023.
File interview
This dataset include five worksheets. The first two sheets were the phenotypic traits in the common garden collected in Year 1. The third and fourth sheets were the phenotypic traits in the common garden collected in Year 2. The fifth sheet is the SSR data.
Description of the data
The first sheet.
Number of variables: 25
Number of cases/rows: 453
Variable List:
YEAR: The data collection year. 1-2014
Location: Sample collection site.
genotype: 1-12, number of genotype.
repeat:1-3, repetitive number
Longitude: The longitude of the sample collection site
Latitude: The latitude of the sample collection site
Altitude: The altitude of the sample collection site
PC1: the first axis of PCA score of climate data
PC2: the second axis of PCA score of climate data
Plant heigth The heigth of whole plant (mm)
basal diameter: The basal diameter of plant (mm)
leaf length: The length of the largest leaf (mm)
leaf widthThe width of the largest leaf (mm)
L/W ratio: the ratio of leaf length/ leave width
SLA: specific leaf area, ratio of leave biomass/ leaf area
stem biomass: the dry weight of the stem (g)
leaf biomass: the dry weight of the leaf (g)
Vegetation biomass: above ground biomass, leaf biomass +stem biomass
number of inflorescence: The number of inlorescence (#)
seed number: The number of seeds (#)
Seeds biomass: The dry weight of all seeds (g)
1000-seed weight: The dry weight of 1000 seeds (g)
number of sprouts: The number of new born sprouts (#)
seeds biomass/aboveground biomass: the ratio of seeds biomass/above ground biomass
chlorophyll content: the relative chlorophyll content (SPAD values)The second sheet.
Number of variables: 13
Number of cases/rows: 242
Variable List:
YEAR: The data collection year. 1-2014
Location: Sample collection site.
genotype: 1-12, number of genotype.
repeat:1-3, repetitive number
Longitude: The longitude of the sample collection site
Latitude: The latitude of the sample collection site
Altitude: The altitude of the sample collection site
PC1: the first axis of PCA score of climate data
PC2: the second axis of PCA score of climate data
net photosynthetic rate: The amount of CO2 absorbed per unit time and per unit leaf area (molCO2/m/s)
stomatal conductance: A measure of the rate of diffusion of CO2 into the leaf or water vapor molecules out of the cavities behind the stomata mmol H2O/m2/s
intercellulare CO2 concentration (molCO2/mol)
transpiration rate: The amount of water lost per unit leaf area by a plant in a given period of timemmol H2O/m2/sThe third sheet.
Number of variables: 22
Number of cases/rows: 412
Variable List:
YEAR: The data collection year. 2-2015
Location: Sample collection site.
genotype: 1-12, number of genotype.
repeat:1-3, repetitive number
Longitude: The longitude of the sample collection site
Latitude: The latitude of the sample collection site
Altitude: The altitude of the sample collection site
PC1: the first axis of PCA score of climate data
PC2: the second axis of PCA score of climate data
Plant heigth The heigth of whole plant (mm)
basal diameter: The basal diameter of plant (mm)
stem biomass: The dry weight of the stem (g)
leaf biomass: The dry weight of the leaf (g)
Vegetation biomass: Above ground biomass, leaf biomass +stem biomass
Root biomass: The dry weight of the root (g)
Total biomass: The dry weight of leaves, stems and roots
number of inflorescence: The number of inlorescence (#)
seed number: The number of seeds (#)
Seeds biomass: The dry weight of all seeds (g)
1000-seed weight: The dry weight of 1000 seeds (g)
number of sprouts: The number of new born sprouts (#)
seeds biomass/aboveground biomass: the ratio of seeds biomass/above ground biomassThe forth sheet.
Number of variables: 13
Number of cases/rows: 281
Variable List:
YEAR: The data collection year. 2-2015
Location: Sample collection site.
genotype: 1-12, number of genotype.
repeat:1-3, repetitive number
Longitude: The longitude of the sample collection site
Latitude: The latitude of the sample collection site
Altitude: The altitude of the sample collection site
PC1: the first axis of PCA score of climate data
PC2: the second axis of PCA score of climate data
net photosynthetic rate: The amount of CO2 absorbed per unit time and per unit leaf area (molCO2/m/s)
stomatal conductance: A measure of the rate of diffusion of CO2 into the leaf or water vapor molecules out of the cavities behind the stomata mmol H2O/m2/s
intercellulare CO2 concentration (molCO2/mol)
transpiration rate: The amount of water lost per unit leaf area by a plant in a given period of timemmol H2O/m2/sThe fifth sheet
Number of rows: 422
Number of lines: 50
The first row: Primer name
The second row: Locus
The 3rd-422th row: the number of individuals.
Methods
Common garden experiment
In April 2013, we established a common-garden experiment on Linhai campus of Taizhou University (121˚17´E, 28˚87´N) to assess quantitative trait variation among S. canadensis individuals from the 14 populations. We obtained three similar-sized (ca. 15 cm) plantlets for each of the 12 families in the 14 populations from the pre-experiment cultivation of plants described above. The plantlets were grown in a common garden in the field in three blocks. Thus, the total number of experimental plants was 504: 14 populations × 12 individuals (representing 12 maternal families) per population × 3 blocks. Within a block, the 12 individuals were planted in 12 separate plots that each measured 1.5 m × 1.5 m. The individual plants were grown 30 cm apart from each other. Throughout, the experimental plants received only rain-fed water and were not fertilized.
Phenotypic trait measurement in the common garden
One month after transplant (21st - 27th May 2013), we took in situ measurements of photosynthesis on the third fully expanded leaf from the top using a portable photosynthesis meter (LI-6400 XT, Li-COR, Inc., Lincoln, NE, USA). The measurements were taken between 9:00 and 11:00 AM under the following conditions: a photosynthetically active radiation of 1,400 μmol m-2 s-1, leaf temperature of 25°C, CO2 concentration of 400 ppm, and relative humidity of 70%. For each plant, we recorded net photosynthetic rate (Pn), intercellular CO2 concentration (Ci), stomatal conductance (Gs), and transpiration rate (Tr). These measurements were taken six times on different dates, and the average of the six were used in the statistical analyses described below. Seven months after transplant (November 2013), we measured various morphological, physiological, and reproductive traits of the S. canadensis individuals. Individual plant height, leaf length (L), and leaf width (L) for the third leaf per plant were measured to a precision of 0.1 cm. We used the L and W dimensions to compute the L/W ratio. Chlorophyll content of the third leaf was measured using a portable chlorophyll meter. We also measured basal stem diameter to an accuracy of 0.01 cm. After 97% of the plants had flowered, we counted the total number of inflorescences per individual plant. Then after the plants had matured, we obtained a total seed count and 1000-seed weight per plant. We also measured the total leaf area per plant using a WinFOLIA computer image analysis system (Regent Instruments Inc, Quebec, Canada) for use in computation of specific leaf area (SLA). The above-ground plant parts were then harvested and separated into shoots, leaves, and seeds. Biomass of the stem, leaf, and seed were measured after the samples had been dried at 80 °C for 72 h. We measured biomass using an electronic balance to an accuracy of 0.01 g. To obtain total vegetative biomass per S. canadensis individual, we summed up oven-dried stem and leaf biomass of the individuals. We computed SLA as the ratio of leaf area to leaf dry biomass.
A year later (November 2014), we repeated measurements of the same traits above from the same S. canadensis individuals. After the measurements had been taken, the whole root system for each S. canadensis individual was dug up and washed free of soil particles under running water. The roots and shoots were then dried at 80 °C for 72 h and then weighed individually to the nearest 0.01 g.
Analysis of neutral genetic diversity
Leaf sampling
In October 2012, we collected leaf tissues from 30 S. canadensis individuals in the same 14 populations that we sampled for rhizomes as described above. We kept the minimum distance between the sampled S. canadensis individuals at 10 m to reduce the chance of sampling the same maternal family more than once. The sampled leaves were immediately immersed in self-sealing plastic bags that contained silica gel and then stored in the laboratory at room temperature until use in DNA extraction.
Microsatellite analysis
In November 2012, genomic DNA was extracted from 0.1 g of each leaf sample using a modified sodium dodecyl sulfate protocol on a FastPrep-24 Automated Lysis and Homogenization System (MP Biomedicals, Santa Ana, CA, USA). Total DNA concentration was determined with a NanoDrop 2000 Lite Spectrophotometers (ThermoFisher Scientific, Inc. Rockford, IL, USA). The DNA samples were then diluted to 10 ng/μL and stored at -20°C until use in simple sequence repeats (SSR) analyses. Five prime pairs (synthesized by Boshang Biotechonology Co., Ltd. in China) were used in SSR amplifications (Wieczorek and Geber 2002). We ran PCR in a 20 μL volume that was made up of 1 × PCR reaction buffer, 1.5 mM Mg2+, 4 ng template DNA, 0.2 μM each of forward and reverse primers, 0.2 mM 4 × dNTP mixture, and 1 U Taq polymerase (Promega Cooperation, Madison, WI, USA). We performed PCR amplifications using a PTC 220 Peltier Thermal Cycler (Bio-Rad Laboratories, Hercules, CA, USA) with the following settings: denaturation at 95 ºC for 5 min, followed by 34 cycles of 30 s at 95 ºC, 30 s at 58 ºC (﹣1 ºC per cycle), 45 s at 72 ºC, with a final elongation of 7 min at 72 ºC. We analyzed the PCR products using a Fragment Analyzer™ Automated CE System (Advanced Analytical Technologies, Inc, Ankeny, IA, USA) with an 80 cm-long capillary column. We used a DNF-900 35-500 bp ds DNA Reagent Kit in the analysis. We genotyped DNA fragments using PROSize® 2.0 Data Analysis Software based on the elution time compared with a size standard.
Usage notes
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