Parameters of genetic diversity within volunteer and feral populations among loci*.
Abstract
Unpredicted persistence of all forms of B. napus present in the agro-ecosystem is the most common consequence of preservation and self-recruitment of seeds originating from soil seed bank. In nature, spontaneous intra- and inter-specific hybridization of B. napus is possible with sexually compatible species from the Brassicaceae family. The aim of this chapter is (a) to identify the distribution pattern and population dynamics of volunteers and feral populations along statistical regions in Slovenia; (b) to assess the global diversity of naturally appearing B. napus plants; (c) to evaluate the genetic differentiation between volunteers and feral populations; (d) to obtain the spatial and temporal distribution of spontaneous pollination potential and estimation of gene flow conservation; (e) to find the empirically assigned out-crossing rate of B. napus under a fragmented landscape structure, during 4-year monitoring; and (f) to observe that ecologically, evolutionary, and agronomically oriented studies could be conducted at the DNA level using short sequence repeat (SSR) markers. In total, we collected 261 samples of volunteer and feral populations. Our results showed that alleles from both volunteer and feral populations were distributed in three genetic clusters with relatively similar levels of diversity. Naturally occurring out-crossing rate is 13.71%. The global Mantel correlation coefficient of genetic and spatial relatedness between genotypes is 0.044.
Keywords
- Brassica napus L.
- feral populations
- volunteers
- spontaneous pollination
- out-crossing rate
- temporal and spatial distribution
- SSR markers
- genetic diversity
- population structure
1. Introduction
Pollination relations occur among all existing forms of
Different marker systems including short sequence repeat (SSR) markers are used for genetic characterization of agro-economically important plant species [10, 34, 35, 36, 37]. To assess the molecular variation, genetic structure and gene flow potential among
Fragmented landscape and small-sized field structure reflect the heterogeneous growth conditions in several parts of Europe and world. The presence of ecological barriers like landscape structural elements (small woods, hedges, overgrown paths, and hills) and the influence of different agro-climatic conditions manage pollen and seed distribution [45]. Consequently, the persistence of
2. Materials and methods
2.1. Study area
For the purpose of the study, we have selected macro-locations on a regional level—regions along Slovenia with high crop production share of
2.2. Field survey
Field survey was conducted in a 4-year period from 2007 to 2010 every year during the flowering time of the biennial
2.3. DNA extraction
The leaf apex of each sample from the five young plants was bulked for DNA extraction with BioSprint 15 DNA Plant Kit (Qiagen) on a KingFisher (Thermo) isolation robot following the optimized method according to manufacturer’s instructions.
2.4. Genotyping procedure
A total of 45 nuclear SSR markers originating from different Brassicaceae family species, with various nucleotide repeat motives (listed in Table 1) were used. Thirty-seven SSR markers (with Na, Ol, Ni, Ra) were developed by Lowe et al. [46]; two SSR markers (with BRMS) were published by Suwabe et al. [47]; two SSR markers (with MR) were by Uzanova and Ecke [48]; one SSR marker (named BN83B1) was developed by Szewc-McFadden et al. [49]; and two SSR markers (with RES) were published by Wang et al. [50]. PCR reactions were performed on a final volume of 11.5 μl, containing 30 ng of genomic DNA and the following reagents with initial concentrations of: 10 x PCR buffer (Biotools), 10 mM of each dNTPs, 50 mM MgCl2 (Biotools), 10 μM of each primer, 10 μM 5′ fluorescently labeled universal primer (6-FAM, NED, HEX), and 0. 5 U of Taq DNA polymerase (Biotools). The forward primer of each SSR was appended with 18 bp tail sequence 5’-TGTAAAACGACGGCCAGT-3′ (M13(−21) as described by Schuelke [51]. PCR analyses were performed on ATC 401 (Apollo Instrumentations) under the following “touch-down” conditions, dependent on each primer pair: 94°C for 4 min; 15 cycles at 94°C for 1 min; auto decrement temperature from 60 (62)°C at 0.7°C per cycle for 30 s; 72°C for 1 min, followed by 23 cycles at 94°C for 30 s; 53°C for 30 s; 72°C for 1 min; and final extension for 5 min at 72°C. Fragment analysis was performed on a 3130XL genetic analyzer (ABI); the allele lengths were determined by comparison to a size standard GeneScan-350 ROX (ABI) using GeneMapper 4.0 (ABI).
Locus | Repeat motif | Ra[bp] | n | He | Ho | N0 | PI | PIC | F |
---|---|---|---|---|---|---|---|---|---|
(GT/CA)11 | 160–190 | 13 | 0.601 | 0.473 | 0.077 | 0.197 | 0.573 | 0.003 | |
(GA/CT)18 | 135–221 | 27 | 0.862 | 0.767 | 0.034 | 0.030 | 0.845 | 0.005 | |
(GA/CT)50 | 259–349 | 21 | 0.711 | 0.388 | 0.169 | 0.107 | 0.691 | 0.008 | |
(GT/CA)10 | 102–176 | 21 | 0.730 | 0.866 | −0.078 | 0.099 | 0.704 | 0.003 | |
(GA/CT)50 | 144–254 | 22 | 0.876 | 0.749 | 0.069 | 0.027 | 0.858 | 0.005 | |
(GA/CT)29 | 108–184 | 16 | 0.722 | 0.871 | −0.077 | 0.117 | 0.678 | 0.001 | |
(GA/CT)17 | 139–215 | 16 | 0.817 | 0.729 | 0.045 | 0.059 | 0.791 | 0.008 | |
(GA/CT)18 | 99–171 | 20 | 0.690 | 0.747 | −0.033 | 0.138 | 0.641 | 0.002 | |
(GA/CT)25 | 162–246 | 22 | 0.911 | 0.932 | −0.008 | 0.016 | 0.899 | 0.002 | |
(GA/CT)47 | 105–195 | 11 | 0.422 | 0.436 | −0.017 | 0.394 | 0.388 | 0.005 | |
(GA/CT)28 | 137–205 | 17 | 0.778 | 0.415 | 0.203 | 0.066 | 0.753 | 0.003 | |
(GA/CT)23, | 162–252 | 12 | 0.816 | 0.730 | 0.052 | 0.055 | 0.790 | 0.006 | |
(GA/CT)37 | 153–285 | 19 | 0.895 | 0.702 | 0.095 | 0.213 | 0.880 | 0.002 | |
(GA/CT)21 | 107–217 | 21 | 0.700 | 0.723 | −0.012 | 0.118 | 0.677 | 0.002 | |
(GT/CA)10 | 102–182 | 15 | 0.758 | 0.969 | −0.120 | 0.091 | 0.725 | 0.005 | |
(GA)11 (AAG)4 | 135–232 | 13 | 0.414 | 0.201 | 0.139 | 0.393 | 0.396 | 0.011 | |
(TG)11 | 80–116 | 12 | 0.743 | 0.938 | −0.106 | 0.108 | 0.699 | 0.001 | |
(GA/CT)60 | 260–348 | 10 | 0.619 | 0.350 | 0.147 | 0.205 | 0.562 | 0.007 | |
(GT/CA)14 | 132–134 | 16 | 0.872 | 0.253 | 0.334 | 0.026 | 0.848 | 0.029 | |
(GA/CT)20 | 106–190 | 21 | 0.793 | 0.938 | −0.089 | 0.067 | 0.767 | 0.003 | |
(GA/CT)52 | 111–209 | 32 | 0.931 | 0.685 | 0.145 | 0.009 | 0.920 | 0.007 | |
(GGC/CCG)5 | 99–197 | 15 | 0.831 | 0.959 | −0.065 | 0.051 | 0.806 | 0.004 | |
(AAT/AAG)18 | 128–218 | 12 | 0.802 | 0.713 | 0.047 | 0.070 | 0.772 | 0.003 | |
(GA/CT)17 | 120–202 | 15 | 0.449 | 0.410 | 0.023 | 0.328 | 0.428 | 0.002 | |
(GA/CT)36 | 122–244 | 20 | 0.516 | 0.405 | 0.069 | 0.256 | 0.493 | 0.004 | |
(GA/CT)32 | 101–193 | 17 | 0.770 | 0.665 | 0.048 | 0.068 | 0.745 | 0.003 | |
(GGC/CCG)4 | 103–193 | 11 | 0.703 | 0.875 | −0.095 | 0.118 | 0.653 | 0.007 | |
(GGC/CCG)9 | 94–257 | 13 | 0.854 | 0.921 | −0.045 | 0.039 | 0.832 | 0.001 | |
(GT/CA)14 | 124–254 | 17 | 0.707 | 0.660 | 0.023 | 0.130 | 0.678 | 0.016 | |
(GA/CT)11 | 126–232 | 17 | 0.729 | 0.770 | −0.043 | 0.118 | 0.684 | 0.002 | |
(GA/CT)19 | 98–144 | 12 | 0.671 | 0.910 | −0.149 | 0.171 | 0.611 | 0.001 | |
(GT/CA)107 | 170–296 | 13 | 0.648 | 0.313 | 0.195 | 0.177 | 0.608 | 0.007 | |
(GA/CT)18 | 187–319 | 19 | 0.589 | 0.334 | 0.165 | 0.226 | 0.555 | 0.010 | |
(GA/CT)19 | 96–218 | 18 | 0.657 | 0.925 | −0.155 | 0.174 | 0.593 | 0.002 | |
(GA/CT)32 | 115–281 | 24 | 0.782 | 0.769 | 0.018 | 0.069 | 0.757 | 0.002 | |
(GA/CT)34 | 151–307 | 29 | 0.797 | 0.929 | −0.068 | 0.065 | 0.768 | 0.003 | |
(GA/CT)19 | 168–266 | 21 | 0.740 | 0.461 | 0.159 | 0.096 | 0.717 | 0.007 | |
(GT/CA)65 | 183–285 | 11 | 0.656 | 0.735 | −0.038 | 0.165 | 0.607 | 0.003 | |
(GA/CT)23 | 122–202 | 13 | 0.779 | 0.823 | −0.025 | 0.072 | 0.760 | 0.006 | |
(CA)10(GA)4 | 100–178 | 15 | 0.813 | 0.976 | −0.082 | 0.055 | 0.786 | 0.001 | |
(AAT)4(TC)19(TTC)3 | 143–215 | 14 | 0.361 | 0.292 | 0.047 | 0.473 | 0.345 | 0.013 | |
(AG)23(AGG)5 | 101–189 | 18 | 0.600 | 0.450 | 0.103 | 0.175 | 0.579 | 0.001 | |
(CCT)5 | 104–199 | 16 | 0.812 | 0.912 | −0.058 | 0.064 | 0.782 | 0.002 | |
(ATG)7 | 148–223 | 10 | 0.373 | 0.244 | 0.088 | 0.426 | 0.352 | 0.003 | |
(GATT)4 | 93–133 | 9 | 0.596 | 0.415 | 0.116 | 0.191 | 0.556 | 0.003 | |
2.5. Data analysis
Parameters of genetic diversity among loci including ranges of allele lengths (Ra), numbers of alleles (n), frequencies of null alleles (No), and probability of identity (PI) were calculated using Identity v.1.0 [52]. MsToolkit [53] was used to evaluate expected heterozygosities (He), observed heterozygosities (Ho), and polymorphic information content (PIC). Locus-specific fixation indices and deviations of volunteer and feral populations from the Hardy–Weinberg equilibrium (HWE) were calculated using the GenAlEx v.6.4. [54]. Detecting the loci under selection was performed using Arlequin v.3.5.1.2 software [55] with 20,000 simulations. FSTAT v.2.9.3.2 [56] was used to determine allelic richness (R) as a measure of the number of alleles independent of sample size after 2000 permutations. The calculations of population statistics parameters at the spatial and temporal level including numbers of different alleles (Na), numbers of private alleles (Np), numbers of effective alleles (Ne), number of locally common alleles, fixation indices (F), population-specific expected heterozygosities (He), Shannon’s information index (I), and pairwise Nei’s genetic correlations were obtained using GenAlEx v.6.4 [54]. The out-crossing rate (t) was calculated from the fixation index using the equation
3. Results
3.1. The dataset
In the 4-year period, 261 samples were collected in total—66 samples of volunteer populations and 195 samples of feral populations within 10 statistical regions in Slovenia (Figure 1).
3.2. Evaluation of genetic diversity
Genotypic results for 45 analyzed loci are summarized in Table 1. All loci were 100% polymorphic in both volunteer and feral populations. The selected set of SSR markers is highly applicable for genetic differentiation analysis within
According to the exact HWE test, both volunteer and feral populations do not meet HWE conditions (P < 0.05) for any of the 45 loci, which is confirmed by the mean positive value of F (0.005) (Table 1), indicating spontaneous random mating and inbreeding potential. These findings reflect the characteristics of natural populations during the 4-year monitoring of non-cultivated
The MCMC structure of 45 SSRs showed moderate genetic structure. When Evanno’s [63] ad hoc estimator of the real number of clusters was used, it indicated modes at K = 3 (Figure 2). The average genetic distances between genotypes in the first cluster is 0.794 (Fst = 0.062), following 0.627 (Fst = 0.169) in the second cluster and 0.646 (Fst = 0.092) in the third genetic cluster.
3.3. Regional-spatial assessment of gene flow in fragmented field landscapes
Genetic diversity and allelic structure of volunteer and feral populations along statistical regions are presented in Figure 3 and Table 2. According to the highest values of expected heterozygosity (He) and Shannon’s information index (I), the most genetically diverse genotypes are from JVS (He = 0.731; I = 1.779), SAV (He = 0.726; I = 1.729), OSR (He = 0.688; I = 1.627), and POM (He = 0.662; I = 1.482) regions (Figure 3). The highest number of private alleles, Np = 0.867, was detected among genotypes from OSR (Figure 3); the out-crossing rate inside this region reached 10.45%. The highest out-crossing rate was calculated within SAV (
GOR | JVS | NTK | OBK | OSR | POD | POM | SAV | SPS | ZAS | |
---|---|---|---|---|---|---|---|---|---|---|
* | 0.032 | 0.020 | 0.076 | 0.006 | 0.010 | 0.010 | 0.017 | 0.012 | 0.070 | |
0.857 | * | 0.034 | 0.096 | 0.026 | 0.027 | 0.030 | 0.015 | 0.038 | 0.066 | |
0.919 | 0.850 | * | 0.093 | 0.019 | 0.019 | 0.022 | 0.020 | 0.022 | 0.072 | |
0.820 | 0.724 | 0.761 | * | 0.073 | 0.079 | 0.077 | 0.085 | 0.088 | 0.122 | |
0.977 | 0.874 | 0.921 | 0.826 | * | 0.009 | 0.009 | 0.012 | 0.013 | 0.067 | |
0.958 | 0.874 | 0.921 | 0.801 | 0.963 | * | 0.010 | 0.015 | 0.016 | 0.063 | |
0.963 | 0.865 | 0.911 | 0.813 | 0.963 | 0.955 | * | 0.014 | 0.017 | 0.067 | |
0.929 | 0.923 | 0.915 | 0.772 | 0.941 | 0.934 | 0.940 | * | 0.021 | 0.061 | |
0.957 | 0.842 | 0.913 | 0.788 | 0.951 | 0.937 | 0.936 | 0.919 | * | 0.068 | |
0.770 | 0.763 | 0.764 | 0.711 | 0.774 | 0.789 | 0.774 | 0.785 | 0.778 | * |
The estimation of
According to the results from Table 2, the included genotypes are relatively homogenously dispersed along all geographic areas and no grouping of genetically similar genotypes within statistical regions was observed. This finding was confirmed by a global Mantel test, which compares the genetic and geographic distance matrix of all 261 genotypes. The Mantel correlation coefficient of genetic and spatial relatedness between genotypes was low, but positive (rxy = 0.044, P = 0.01), due to minor spatial linkage on the basis of genetic structure. The summary of the mean within region pairwise values, based on genetic and geographic distance, is presented in Figure 4.
3.4. Temporal distribution of landscape gene flow and conservation of genetic variation
Temporal distribution of genetic variation, according to 100% polymorphic loci during the 4-year monitoring is presented in Table 3. Increasing values of Np, m, and molecular variance for every successive year, signify the gene flow potential, distribution, and conservation of new alleles into
Parameter of population diversity and genetics | Ecological interpretation | 2007 | 2008 | 2009 | 2010 |
---|---|---|---|---|---|
Ne | Allelic diversity | 4.01 | 3.80 | 3.64 | 4.17 |
Np | Estimation of spontaneous gene flow conservation into naturally appearing populations | 0.58 | 0.93 | 0.98 | 1.64 |
F | Estimated level of spontaneous gene flow | 0.03 | 0.01 | 0.07 | 0.05 |
t (%) | Actual gene flow potential | 5.74 | 2.81 | 13.27 | 12.52 |
Molecular variance (%) | Conservation of naturally occurring spontaneous gene flow | 1.64 | 1.78 | 2.77 | 6.1 |
m | Level of gene flow | 2.16 | 3.36 | 4.41 | 5.47 |
R | Basic genetic diversity parameter; allelic richness | 3.41 | 1.67 | 3.23 | 5.64 |
According to PCoA results, there is a decreasing pattern of genetic linkages between all genotypes from 2007 to 2010 (Figure 5). This genetic differentiation reflects the spontaneous gene flow through the 4-year period in the surveyed agro-ecosystem.
4. Discussion
According to the 4-year field monitoring, volunteer/feral populations appeared within statistical regions, where
In this study, spatial and temporal determination of genetic changes on 45 loci inside the
Variable out-crossing rate, being a biological characteristic of
Our study suggests that there is no specific distribution of genetically similar genotypes present within the same statistical region. Conversely, the proportion of shared molecular variability of volunteers/feral populations between regions is high (96%). These large-scale genetic similarities could be caused by common ancestry from commercial varieties of
5. Conclusions
Distribution of volunteer and feral populations represents the highly developed
Our empirically obtained results show the existing potential of large-scale spontaneous pollination and gene flow conservation into the
Acknowledgments
The authors acknowledge the financial support from the Slovenian Research Agency (research core funding No. (Agrobiodiversity P4-0072 and Young researcher grant: B. Pipan, contract number 1000-07-310099)). We are also grateful to MatejKnapič for spatial visualization of sampling locations.
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