Data from: Assessment of conservation status of Ferula huber-morathii: Association with population genetic structure and regional climate
Data files
Sep 06, 2024 version files 350.22 KB
Oct 24, 2024 version files 73.59 KB
Abstract
Ferula huber-morathii is an endemic and medicinally important plant. This species is distributed in eight Turkish localities, including three newly identified ones. Its extent of occurrence and area of occupancy is determined to be 3963 km2 and 32 km2 respectively. All localities are characterized by East Mediterranean and sub-Mediterranean precipitation regimes; however, temperatures increase excessively and precipitation decreases during the flowering period of the species. The population sizes are quite small, and the number of reproducing individuals in some populations is below ten. Analyses of ISSR markers showed the percentage of polymorphic loci to be 94% at the species level and 56% at the population level. The level of genetic differentiation (measured by GST) was 0.37 and the estimated level of gene flow among populations (NM) was 0.84. The percentage of variance occurring within and among populations, determined by AMOVA, was 75% and 25%, respectively. STRUCTURE analysis revealed two genetic clusters of individuals with a geographic structure similar to that found in UPGMA and an ordination analysis. Some populations turned out to have both low numbers of individuals and low genetic diversity. Since many of the populations are subject to anthropogenic disturbance, the species should remain in the EN category. At the same time, it is suggested that a new in-situ conservation area should be created around nearby dams, situated in the same climate area as the currently known populations.
README: Assessment of conservation status of Ferula huber-morathii: Association with population genetic structure and regional climate
This dataset includes the raw data of Ferula huber-morathii, FR GEN-DIVERSITY data, and Figure 4, and their explanations.
The Raw Data of Ferula huber-morathii
This data was obtained by amplifying plant DNA with diversity primers. The data includes populations and their individuals, presence (1) and absence analyses (0), and primers mentioned in the article. The data was also used in STRUCTURE analysis after being evaluated in GenAlEx and POPGENE programs for studies on population diversity, differentiation among populations, distance among populations, etc.
FR GEN-DIVERSITY data set
Table 4 contains genetic diversity data of F. huber-morathii and its populations.
- N = Sample sizes
- Na = Observed number of alleles
- Ne = Effective number of alleles [Kimura and Crow (1964)]
- H = Nei's (1973) gene diversity
- I = Shannon's Information index [Lewontin (1972)]
Formulas from which data is obtained
N = Sample sizes
Na = Number of Different Alleles
Ne = Number of Effective Alleles = 1 / (p^2 + q^2)
H = Σ(1- pi2– qi2)/n)
I = Shannon's Information Index = -1* (p * Ln (p) + q * Ln(q))
He = Expected Heterozygosity = 2 * p * q
polymorphic locus percentage (PLY)
Where for Diploid Binary data and assuming Hardy-Weinberg Equilibrium, q = (1 - Band Freq.)^0.5 and p = 1 - q.
Figure 4
This was obtained by loading the data generated as a result of structure analysis into the CLUMPACK program. In this data set account for potential recombination in clustering of population individuals, the Mixture model was used to calculate the probabilities of the data from K=1 to K=10 clusters for each cluster K ((Pr(X|K)) or L(K). After performing 100,000 or 300,000 McMC iterations as burn-in time for each K, 10 runs with ten iterations were performed. The amount of variance in the probability of each K was estimated (Evanno et al. 2005).
MCMC: integrates over possible chunk sizes and breakpoints to find different values of K.
The optimal number of groups was determined using K in CLUMPAK (Kopelman et al. 2015).
Retrieving data from files for each K
K: number of populations
K=1 mean: -754.21 K=1 standard deviation: 0.128668393770775 K=1 median: -754.2
K=2 mean: -630.77 K=2 standard deviation: 0.494525586350747 K=2 median: -630.7
K=3 mean: -640.63 K=3 standard deviation: 6.97982011866271 K=3 median: -638.1
K=4 mean: -718.74 K=4 standard deviation: 21.814072929597 K=4 median: -722
K=5 mean: -743.32 K=5 standard deviation: 15.4657902050515 K=5 median: -748
K=6 mean: -743.11 K=6 standard deviation: 17.6488872800022 K=6 median: -739.1
K=7 mean: -728.84 K=7 standard deviation: 18.4378957584644 K=7 median: -732.6
K=8 mean: -882.44 K=8 standard deviation: 502.315585176402 K=8 median: -723.3
K=9 mean: -704.89 K=9 standard deviation: 10.4891954992851 K=9 median: -705.25
K=10 mean: -707.07 K=10 standard deviation: 12.1466090375508 K=10 median: -709.7
* Calculating Best K by Evanno
Delta(K=2) = 269.55127030668 Delta(K=3) = 9.77818895611831 Delta(K=4) = 2.45392046559867
Delta(K=5) = 1.60289255649564 Delta(K=6) = 0.796650790326652 Delta(K=7) = 9.1046181299151
Delta(K=8) = 0.659246915231004 Delta(K=9) = 17.1347745413125 Max Delta K: 269.55127030668
* Optimal K by Evanno is: 2
Change log
Oct 2024: In addition to the previous version, the raw data of Ferula huber-morathii has been added. In particular, it was desired to emphasize the importance of the raw data used in reaching the obtained results in determining both genetic diversity and the relationships among populations.
Methods
The area of occupancy and other distributional data were determined by the Geospatial Conservation Assessment Tool (GeoCat) program (http://geocat.kew.org; Bachman et al. 2011), based on the 2x2 km cell sizes recommended by IUCN and interpopulation distances obtained with the Google Earth program. In accordance with the ICUN criteria (2012; 2019) and the updated population data collected from the field study, these data resulted in a reassessment of the Red List category for the species.
The data obtained using the ISSR markers were scored in a binary matrix as present (1) or absent (0). Allele number observed (Na), effective allele number (Ne), polymorphic locus number (PLS), polymorphic locus percentage (PLY), Nei’s genetic diversity (H) (1973, 1987) as well as Shannon’s information index (Lewontin, 1972), served as general estimators of genetic diversity, calculated using POPGENE ver. 1.32 (Yeh et al. 1997) and GenAlEx ver. 6.5 (Peakall and Smouse, 2012).
Finally, individuals were classified into genetic clusters using STRUCTURE version 2.3.4 (Pritchard et al. 2000). In order to account for potential recombination across inferred clusters, the Admixture model was used to calculate the probabilities of the data for each K ((Pr(X|K)) or L(K) cluster for K=1 through K=10 clusters. After 100,000 or 300,000 McMC replications had been performed as a burn-in period for each K, 10 runs with ten iterations were performed. The amount of variance in each K.'s likelihood was estimated (Evanno et al. 2005). The bestfit number of groups in CLUMPAK (Kopelman et al. 2015) was determined using K.