Skip to main content
Dryad logo

Conservation genetics of Armeria belgenciencis

Citation

Baumel, Alex et al. (2020), Conservation genetics of Armeria belgenciencis, Dryad, Dataset, https://doi.org/10.5061/dryad.cvdncjt17

Abstract

This the data set of the paper "Population genetic structure and management perspectives for Armeria belgenciencis, a narrow endemic plant from Provence (France)" published in Plant Ecology and Evolution: ###############.

The genetic structure of Armeria belgenciensis and geographically close populations of Armeria arenaria was analyzed on the basis of 328 AFLP markers using model-based and model-free clustering methods. In addition, flowering phenology was estimated to address the possibility of pre-zygotic isolation between A. belgenciensis and A. arenaria subsp. peirescii. Key results are available in the companion paper.

Methods

The genetic structure of Armeria belgenciensis and geographically close populations of Armeria arenaria was analyzed on the basis of 328 AFLP markers using model-based and model-free clustering methods. In addition, flowering phenology was estimated to address the possibility of pre-zygotic isolation between A. belgenciensis and A. arenaria subsp. peirescii.

Sampling

Leaves from two hundred samples were collected from six populations. 50 individuals were sampled for A. belgenciensis and 50 for A. arenaria subsp. pereiscii (BEL and PER), 50 individual from two nearby populations of A. arenaria subsp. bupleuroides (situated at “Aiguilles de Valbelle”, named VAL and “Méounes-les-montrieux” named MEO), 25 individuals from a population of A. arenaria subsp. pradetensis situated near the coastline (situated at “Le Pradet” named PRA) and 25 individuals of A. arenaria subsp. bupleuroides (situated at “Gigaro” named GI) from an isolated population, 52 km away from A. belgenciensis. The sampling coordinates are given under supplementary material (with AFLP genotype data set).

AFLP genotyping method

100 ng of DNA was digested using the restriction enzymes Eco RI and Tru 9I (Fisher Scientific, France) for 3 h at 37°C and then for 3h at 65°C in a total volume of 25 µl (15 μL + 10µl of DNA). Digestion products were immediately ligated to 0.5 μL Eco and 25 μL Mse adaptors for 3 h at 37°C and treated with T4 DNA Ligase and 0.1 μL of 100 mM ATP to a final volume of 25 μL (5 μL + 20 µl of restriction products). Ligation products were diluted eight times and pre-selective PCR amplification was performed using EcoR1+A, Mse+C primers and Taq DNA polymerase in a 44.5 μL volume. The pre-amplification thermocycle profile was 94°C for 2 min, followed by 20 cycles at 94°C for 45 s, 56°C for 45 s, 72°C for 1 min and 72°C for 10 min. Four primer combinations were chosen for the selective amplification PCR: ASI: EcoR1-AAC/MseI-CAA, ASII: EcoR1-AGG/ MseI -CGG, ASIII: EcoR1-AGC/ MseI -CAG, ASIV: EcoR1-ATG/ MseI -CTA dyed with 6-FAM fluorescence at 5′ Eco end (Eurofins Genomics, Ebersberg, Germany). Hundred times diluted pre-amplification products were used to perform selective amplification in a final volume of 20 μL (15 μL + 5 μL of diluted pre-amplification products). As selective amplification thermocycle profile, we used 94°C for 2 min, 10 cycles of 94°C for 30 s, 65°C for 30 s (step -1°C per cycle), 72°C for 1 min, followed by 22 cycles at 94°C for 30 s, 56°C for 30 s, 72°C for 1 min, 72°C for 5 min and 4°C for 2h. The fragment length produced by the amplification was separated and quantified by capillary electrophoresis using an ABI 3730xl DNA analyzer (Applied Biosystems, Foster City, California, U.S.A.) with GS600 LIZ size marker.

The marker bands produced by the four primer combinations were entered automatically using the RawGeno application (Arrigo et al. 2009*) with stringent criteria to select markers (minimum size peaks greater than 100 UFR, minimum width of 1.2 bp and maximum of 1.75 bp). Despite the stringency of this automatic procedure, it generates an error rate that may be greater than a manual selection. To reduce this error rate, reproducibility of the markers was tested on 12 samples. Markers not reproducible in 100% of the 12 replicates, i.e., having an error rate equal to or greater than 8.33%, were removed. In addition, markers with a frequency lower than 5% or higher than 95% were also removed. Individuals with very few markers, for which the AFLP procedure was not optimal, were removed as well. After these filtering steps, 328 markers were selected for a total of 187 individuals.

* Arrigo, N., Tuszynski, J. W., Ehrich, D., Gerdes, T., & Alvarez, N. (2009). Evaluating the impact of scoring parameters on the structure of intra-specific genetic variation using RawGeno, an R package for automating AFLP scoring. Bmc Bioinformatics, 10(1), 3

Flowering phenology monitoring

To monitor flowering phenology, six permanent plots were set, three for A. belgenciensis and three for A. arenaria subsp. peirescii. The plots were chosen to cover habitat heterogeneity of each taxa according to previous ecological surveys done by CBNMed. The survey was done once per month from April to September in 2017 and twice per week from June to August in 2018, and from May to August in 2019. For A. belgenciensis the plots AB1 (30m²), AB2 (25m²) and AB3 (25 m²) included 25, 22 and 23 individuals, respectively. For A. arenaria subsp. peirescii the demographic density was much lower and finding optimal condition to monitor individual plants was more difficult. Thus plots AP1 (100 m²), AP2 (5 m²) and AP3 (100 m²) included 14, 10 and 24 individuals, respectively. For each individual, the number of open flowers and the number of capitula with at least one open flower were counted.

Usage Notes

Raw data are provided with R scripts and data formatted to .txt for loading into R.