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. 2015 Nov 14;22(1):97–105. doi: 10.1007/s12298-015-0330-2

Evaluation of genetic diversity amongst Descurainia sophia L. genotypes by inter-simple sequence repeat (ISSR) marker

Sahar Saki 1, Hedayat Bagheri 1,✉, Ali Deljou 1, Mehrshad Zeinalabedini 2
PMCID: PMC4840141  PMID: 27186023

Abstract

Descurainia sophia is a valuable medicinal plant in family of Brassicaceae. To determine the range of diversity amongst D. sophia in Iran, 32 naturally distributed plants belonging to six natural populations of the Iranian plateau were investigated by inter-simple sequence repeat (ISSR) markers. The average percentage of polymorphism produced by 12 ISSR primers was 86 %. The PIC values for primers ranged from 0.22 to 0.40 and Rp values ranged between 6.5 and 19.9. The relative genetic diversity of the populations was not high (Gst =0.32). However, the value of gene flow revealed by the ISSR marker was high (Nm = 1.03). UPGMA clustering method based on Jaccard similarity coefficient grouped the genotypes into two major clusters. Graph results from Neighbor-Net Network generated after a 1000 bootstrap test using Jaccard coefficient, and STRUCTURE analysis confirmed the UPGMA clustering. The first three PCAs represented 57.31 % of the total variation. The high levels of genetic diversity were observed within populations, which is useful in breeding and conservation programs. ISSR is found to be an eligible marker to study genetic diversity of D. sophia.

Keywords: Descurainia sophia, Genetic diversity, Iranian plateau, ISSR marker

Introduction

The global herbal product market has an annual growth rate of 5 to 15 %. It is expected that the world herbal drug market will reach a total of 5 trillion US dollars by 2050 (Joshi et al. 2004). Descurainia sophia L. Webb ex Prantl belongs to Brassicaceae family and is a self-compatible, dicotyledonous plant that grows extensively in forage, rangelands, cultivated crops, disturbed areas, roadsides and waste sites (Mitich 1996; Baskin et al. 2004; Blackshaw et al. 2005; Hernandez Plaza et al. 2011; Li et al. 2011). D. sophia originated in South Europe and North Africa (Zhang 2003). The seeds are widely used for medicinal, food and industrial purposes (Mitich 1996; Peng et al. 1997; Bekker et al. 2005; Sun et al. 2005; Mohamed and Mahrous 2009; Li et al. 2010; Mosaddegh et al. 2012; Khan and Wang 2012). D. sophia seeds contain 3.5–4 % ash, 7.6 % fiber, 22–44 % oil and 25 % protein (Tkachuk and Mellish 1977; Duke and Ayensu 1985; Peng et al. 1997; Bekker et al. 2005). They are expectorant, restorative and stimulant and traditionally used to make a sweet Iranian drink that detoxifies the liver (Pasalar et al. 2013; Khodarahmi et al. 2015). The highest amount of essential un-saturated fatty acid (oleic, linolic, linoleic) in the oil seed of D. sophia is on the average of 71.4 % (Gruzdienė and Bagdonaitė 2003) and the content of essential linoleic fatty acid is as great as 44 % (Maršalkienė et al. 2009).

The role of genetic variation in facilitating plant breeding and preservation strategies has long been acknowledged (Sehgal and Raina 2008; Rivers et al. 2014; Govindaraj et al. 2015). This variation is needed to improve favorite traits for future challenges such as climate change and disease evolution (Kisha and Johnson 2012; Alberto et al. 2013). In Iran, the majority of medicinal plants are still harvested from natural fields and no cultivar have been developed. This will eventually lead to gradual extinction of favorable germplasms. A prerequisite to the identification of species is the analysis of genetic diversity (Chawla 2003). Useful tools such as molecular markers assess genetic variation and provide an efficient mean to link phenotypic and genotypic variation (Varsheny et al. 2005) and to characterize plants (Chawla 2003; Kalia et al. 2011).

The ISSR technique is applied to investigate genetic diversity in a wide range of plant species (Reddy et al. 2002; Liu et al. 2013; Singh et al. 2014). Here, we used ISSR markers to investigate and analyze the genetic diversity of 32 D. sophia plants collected from six locations in Iranian plateau.

Materials and methods

Plant materials

A total of 32 naturally distributed genotypes were collected from six different populations in Iran (Hamedan, Lorestan, Central, Fars, Yazd, Kerman). From Hamedan 12, Lorestan 6, Central 5, Fars 4, Yazd 3 and Kerman 2 individuals were collected (Table 1, Fig. 1).

Table 1.

The list of 32 D. sophia genotypes evaluated in this study with their latitude, longitude and location names

No. Genotypes Latitude and Longitude Location
1 H1 35°23.12 N 49°02.02E Hamedan
2 H2 34°32.53 N 48°26.48E Hamedan
3 H5 35°12.29 N 48°43.26E Hamedan
4 H6 34°48.06 N 48°28.49E Hamedan
5 H22 34°41.57 N 48°37.03E Hamedan
6 H23 34°45.11 N 48°36.22E Hamedan
7 H24 34°44.22 N 48°36.26E Hamedan
8 H29 34°45.23 N 48°36.08E Hamedan
9 H40 34°15.13 N 48°57.46E Hamedan
10 H48 34°36.07 N 48°27.02E Hamedan
11 H52 34°43.14 N 48°23.04E Hamedan
12 H57 34°12.33 N 48°42.21E Hamedan
13 L7 33°29.34 N 49°02.47E Lorestan
14 L4 33°30.09 N 49°02.34E Lorestan
15 L10 33°27.21 N 49°27.20E Lorestan
16 L1 33°53.39 N 48°46.01E Lorestan
17 L12 33°55.01 N 48°43.28E Lorestan
18 L9 34°01.01 N 48°38.29E Lorestan
19 CI1 35°41.46 N 51°25.23E Central
20 CI2 34°38.23 N 50°52.33E Central
21 CI3 36°16.00 N 50°00.00E Central
22 CI4 33°55.39 N 49°24.42E Central
23 CI5 35°34.22 N 53°23.50E Central
24 F2 29°06.15 N 53°02.45E Fars
25 F3 29°35.30 N 52°35.01E Fars
26 F4 28°56.18 N 53°38.54E Fars
27 F5 30°53.56 N 52°41.12E Fars
28 Y2 32°01.48 N 53°32.60E Yazd
29 Y14 31°44.50 N 54°12.32E Yazd
30 Y17 31°07.49 N 53°15.01E Yazd
31 K1 30°24.24 N 55°59.38E Kerman
32 K3 29°13.59 N 56°36.08E Kerman
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Fig. 1.

Fig. 1

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Shematic map of Iran and few places where the D.sophia plant materials were collected from. Letters on map are genotype names based on Table 1

DNA extraction and ISSR analysis

Genomic DNA was isolated from the young leaves of plants according to the modified CTAB method of Doyle and Doyle (1987). Inter simple sequence repeat markers were amplified through PCR by twelve primers listed in Table 2. Thermal cycling (BIO-RAD T100) started with 5 min at 94 °C, and 40 cycles of 1 min at 94 °C, 75 s at each primer’s annealing temperature (Table 2) and 2 min at 72 °C ended by an extension for 10 min at 72 °C. The PCR products were separated on 1.2 % agarose gels, stained with ethidium bromide and documented using a UV transilluminator system (Liu et al. 2007a, 2007b).

Table 2.

Data of ISSR primers used in the present study including primer name, primer sequence, annealing temperature (Ta), size range of amplified fragments (SR), number of total bands (NT), number of polymorphic bands (NP), percentage of polymorphic fragment (PP), polymorphic information content (PICavg) and resolving power (Rp) of 12 primers are presented. (Y* = C or T, R* = G or A)

Primer name Primer seq. Ta SR NT NP PP (%) PICavg Rp
UBC 807 (AG)8 T 54 220–1850 106 74 69 0.22 6.54
UBC 834 (AG)8Y*T 53 150–2250 230 230 100 0.30 14.18
UBC 855 (AC)8YT 54 300–2525 214 182 85 0.26 13.24
UBC 818 (CA)8G 53 400–3000 205 205 100 0.36 12.68
UBC 844 (CT)8R*C 54 350–1350 175 143 81 0.40 10.86
UBC 848 (CT)8RG 42.5 300–3100 260 228 87 0.29 14.28
UBC 811 (GA)8C 51 300–2500 257 225 87 0.34 15.9
UBC 810 (GA)8 T 52 250–2500 244 212 86 0.29 15.08
UBC 841 (GA)8YC 53 150–2250 320 160 50 0.33 19.9
UBC 823 (TC)8C 54 300–2000 156 156 100 0.31 9.64
UBC 830 (TG)8G 52 370–1875 163 163 100 0.33 9.36
M2 GGGC(GA)8 56 425–2500 283 251 88 0.31 17.56
Mean – – – 217.75 185.75 86 0.31 13.26
Total – – – 2613 2229 – – –
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Data analysis

The amplified ISSR fragments were scored for presence (1) or absence (0) of bands. Only clear and reproducible bands were scored. Resolving power (Rp) of ISSR primers which indicates the discriminatory potential of the applied primers was calculated based on Prevost and Wilkinsin (1999) formula: Rp = ∑Ib, where Ib is the band informativeness. Ib is computed via Ib = 1 - [2 × (0.5 - p)], where p is the proportion of the 32 genotypes containing the band. PIC value for each polymorphic locus was calculated according to Roldán-Ruiz et al. (2000): PICi = 2fi(1 - fi), where fi is frequency of fragments present in that locus. To examine different genetic diversity parameters PopGene 32 (Yeh and Boyle 1997) software was used. Number of observed alleles (Na), number of effective alleles (Ne), Nei’s gene diversity (H) and Shannon’s information index (I) were calculated. The Nei’s unbiased measures of genetic identity and genetic distance among populations were obtained by PopGene 32 software. Mantel’s test ( 1967) for Jaccard and Dice coefficients were performed. Other genetic diversity parameters including the number of polymorphic loci (PL), the percentage of polymorphic loci (PPL), gene flow (Nm) based on Nm = 0.5 × (1 - Gst) ÷ Gst were calculated (McDermott and McDonald 1993). Similarity coefficient of Jaccard (1908) was used to calculate the pairwise genetic similarities among individuals. To determine the quality of clustering, cophentic correlation coefficient (r) was measured based on the UPGMA cluster analysis (Rohlf and Sokal 1981). These calculations were carried out by NTSYS 2.02e software package (Rohlf 1992). A dendrogram was developed by the Neighbor-Net Network method, carried out with SplitsTree4 software (Huson and Bryant 2006) after a 1000 bootstrap test using Jaccard coefficient. Nei’s average number of pairwise differences in six populations of D. sophia was accomplished by Arlequin 3.5.1.2 (Excoffier and Lischer 2010). Differences among samples were calculated by use of Structure software version 2.3.3 (Hubisz et al. 2009). Two other multivariate methods such as principle component analysis (PCA) and principle coordinate analysis (PCoA) (Mohammadi and Prasanna 2003) were also calculated to assess genetic diversity. The partitioning of genetic variance was carried out by analysis of molecular variance (AMOVA) (Excoffier et al. 1992) in GenAlEx version 6.4 (Peakall and Smouse 2006).

Results

The twelve ISSR primers produced a total of 2613 reliable fragments, scored in 202 loci, of which 190 were polymorphic. Each primer produced an average of 217.75 bands. The length of amplified bands ranged from 150 bp in primers UBC 834 and UBC 841 to 3100 bp in primer UBC 848. The highest number of fragments (283) was produced by primer M2. M2 also provided the maximum number of polymorphic bands (251). The UBC807 primer developed the lowest number of fragments (106) of which 74 were polymorphic. The ISSR pattern obtained with UBC 848 primer is shown in Fig. 2 (Fig. 2). The mean of polymorphism percentage for all 12 primers was 86 %. The UBC841 primer generated the minimum polymorphism of 50 %. Primers UBC834, UBC818, UBC823 and UBC 830 showed 100 % polymorphism. UBC807 primer with 0.22 and UBC844 primer with 0.40 showed the lowest and the greatest PIC value among all primers, respectively. The mean of Rp for the 12 primers was 13.26, with the highest value in UBC 841 primer (19.9) and the lowest one in UBC 807 primer (6.54) (Table 2).

Fig. 2.

Fig. 2

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ISSR patterns generated by UBC 848 primer on 32 genotypes of D. sophia DNA. The ladder is a VC 100 bp Plus DNA Ladder (Vivantis). Lanes designate 32 genotypes based on Table 1

The similarity value of the 32 genotypes based on Jaccard coefficient varied between 0.265 and 0.806. The lowest similarity was between L9 and Y17 genotypes (0.265) which correspond to their different origins, whereas the highest similarity (0.806) was observed between two genotypes of Lorestan (L4 and L7) (Data not shown).

The UPGMA clustering algorithm from ISSR analysis grouped the 32 genotypes into two clusters at a similarity index value of 0.36 (Fig. 3). The top cluster is smaller and consists of Hamedan, Fars and Lorestan populations. The second cluster embraces populations from Hamedan, Lorestan, Central, Fars, Kerman and Yazd. At similarity index of 0.41 Yazd genotypes (Y14, Y17) have been separated in one cluster. This partitioning of genotypes does not show a precise correlation with the location classification of genotypes. Cophenetic value (r) of 0.90 indicates that cluster analysis strongly represents the similarity matrix (Wang et al. 2011).

Fig. 3.

Fig. 3

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UPGMA clustering of D. sophia genotypes based on Jaccard similarity coefficient calculated from ISSR markers

A dendrogram was constructed based on the binary matrix of the scored ISSR marker data (Fig.4). The displayed clustering corresponds to the two major groups resulted by UPGMA dendrogram. The genotypes in green and red accommodate with the smaller and the second cluster of the UPGMA dendrogram, respectively. The three populations of Yazd could be considered as a separate group.

Fig. 4.

Fig. 4

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The constructed dendrogram based on the binary matrix of the scored ISSR marker data in 32 individuals of D. sophia

In Fig. 5 the average number of pairwise differences between each population in the upper half of the matrix can be observed (green). The average number of pairwise differences within each population is shown in the diagonal (orange), and the lower half of the matrix (blue) shows the corrected average pairwise differences of the populations. Nei’s average numbers of pairwise differences are observed within Hamedan and Fars populations and between populations of Lorestan and Fars.

Fig. 5.

Fig. 5

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Nei’s average number of pairwise differences in six populations of D. sophia

Bar plots of the 32 genotypes generated by Structure software confirmed the constructed dendrogram on the binary matrix in Fig. 4. In Fig. 6 individuals such as 28, 29 and 30 corresponding to genotypes Y2, Y14 and Y17 respectively are between the two other groups according to the dendrogram based on the binary matrix. Individuals placed in the green bar plots (11, 10, 27, 18, 26, 6, 1, 5 and 8 represent genotypes H52, H48, F5, L9, F4, H23, H1, H22 and H29, respectively) are the genotypes that were positioned at the smaller group in UPGMA clustering (Fig. 3). They are also corresponding with genotypes in the green group generated by the Neighbor-Net Network method (Fig. 4).

Fig. 6.

Fig. 6

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Bar plots of D. sophia genotypes generated by Structure software 2.3.3. The groups are represented by different colors. Each bar which is divided into segments indicates its genetic composition. The longer the segment the more a sample resembles one of the groups. The labels below the bar plots are the corresponding numbers for each individual, based on Table 1, including the number of their location in the bracket (1: Hamedan, 2: Lorestan, 3: Central, 4: Fars, 5: Yazd, 6: Kerman)

In the principle component analysis the eigenvalues for the first three PCAs are 14.89, 2.40, and 1.04, respectively that represent 57.31 % of the total variation. This shows a proper distribution of ISSR markers through the entire genome. The cumulative arrangement of the 32 individuals, using genetic similarity based on ISSR markers, is shown in Fig. 7. The graph of PCoA analysis shows two main associations which confirms the partitioning results of the UPGMA clustering.

Fig. 7.

Fig. 7

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Distribution of the 32 D. sophia genotypes revealed by PCoA analysis based on genetic similarity estimates calculated from ISSR data

The PopGene calculations (Table 3) showed that the number of observed alleles and effective alleles ranged between 1.19–1.75 (Kerman- Hamedan) and 1.13–1.37 (Kerman-Lorestan), respectively. Hamedan and Kerman have the highest and the lowest H value among the six populations (0.22 and 0.08, respectively). The average of Shannon’s Information Index (I) for the six populations is 0.26 which again the maximum and the minimum are respectively belonging to Hamedan and Kerman populations. The highest number of polymorphic loci (PL) and percentage of polymorphic loci (PPL) both belong to Hamedan while the lowest, pertains to Kerman. The diversity among populations (Gst) and gene flow (Nm) is 0.32 and 1.03 respectively.

Table 3.

Genetic diversity data and differentiation parameters for six natural populations of D.sophia in Iran. Sample Size (SS), Number of observed alleles (Na), Number of effective alleles (Ne), Nei’s gene diversity (H), Shannon’s information index (I), Number of polymorphic loci (PL), Percentage of polymorphic loci (PPL), Diversity among populations (Gst), Gene flow (Nm), Fixation Index (Fst)

Population SS Na Ne H I PL PPL Gst Nm Fst
Hamedan 12 1.7574 1.3584 0.2238 0.3473 153 75.74
Lorestan 6 1.6337 1.3722 0.2148 0.3230 128 63.37
Central 5 1.5099 1.3045 0.1786 0.2684 103 50.99
Fars 4 1.5297 1.3203 0.1900 0.2851 107 52.97
Yazd 3 1.3960 1.2605 0.1513 0.2242 80 39.60
Kerman 2 1.1931 1.1365 0.0800 0.1168 39 19.31
Mean – 1.5033 1.2920 0.1730 0.2608 – –
Total 32 1.9356 1.4166 0.2588 0.4045 189 93.56 0.3248 1.0394 0.141
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The highest genetic identity is between Fars and Hamedan (0.93) with having the lowest genetic distance (0.06) (Table 4). The maximum genetic distance is between Yazd and Kerman (0.20) with the minimum genetic identity of 0.81.

Table 4.

Nei’s unbiased measures of genetic identity (above diagonal) and genetic distance (below diagonal)

Population Hamedan Lorestan Central Fars Yazd Kerman
Hamedan ***** 0.9162 0.9165 0.9371 0.9077 0.8221
Lorestan 0.0876 ***** 0.9191 0.8782 0.8628 0.8697
Central 0.0872 0.0844 ***** 0.9001 0.9050 0.8820
Fars 0.0650 0.1299 0.1053 ***** 0.8669 0.8222
Yazd 0.0968 0.1476 0.0998 0.1429 ***** 0.8108
Kerman 0.1959 0.1396 0.1255 0.1958 0.2097 *****
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AMOVA analysis shows 86 % and 14 % of genetic variation accounted for within and among D. sphia populations, respectively (Table 5).

Table 5.

Analysis of Molecular Variance (AMOVA) for six populations of D. sophia from Iran by ISSR marker

Source df SS MS Est. Var. %
Among populations 5 255.381 51.076 4.643 14 %
Within populations 26 731.900 28.150 28.150 86 %
Total 31 987.281 - 32.793
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Discussion

The Brassicaceae family is an economically important family containing well-known crop species such as Brassica napus and weedy species like Arabidopsis thaliana. Many genera of this family are distributed in Iran including D. sophia. The economic value of D. sophia is mainly based on the attainability of seed production (Peng et al. 1997; Mokhtassi-Bidgoli et al. 2013). Seeds are well known for their medicinal uses in Iran (Pasalar et al. 2013; Khodarahmi et al. 2015). The aim of this study was to investigate the genetic diversity of this medicinal plant in part of Iran. The chief origin of D. sophia in Iran includes the northern part of the country, such as mountains and elevated areas of Alborz and Zagros (Khezri 2001). The habitats of the 32 natural D. sophia plants collected for this study are diverse, such as from farmland, valley, desert or from the mountain. Different analysis methods of genetic relatedness (UPGMA clustering, binary matrix dendrogarm and STRUCTURE analysis) showed two separated groups but, the observed genetic variation was not completely consistent with lifestyle. Hamedan and Fars genotypes divided in two symmetric groups. This is confirmed by Nei’s average number of pairwise differences within Hamedan and Fars populations (Fig. 5). Results of analysis of molecular variance reveal a higher distribution of genetic variation within D. sophia populations (86 %) as compared to between populations (14 %). This is also supported by Gst value of 0.32. Nei’s average number of pairwise differences data. Therefore there is a significant difference between Fars and Lorestan genotypes while there is a high pairwise difference within Fars and Hamedan genotypes. The AMOVA results confirm the absence of an efficient clustering of genotypes coincident to their geographical locations. However collected plants from dry area (Y2, Y14, Y17) can be considered as a different group according to the constructed dendrogram. The outcome is similar to the results of Stenoien et al. (2005); Bakker et al. (2006) and Jorgensen and Mauricio (2004) on A. thaliana that found no clear association between geographical origin and genetic similarity in populations distributed in different regions. In the present study the gene flow (Nm = 1.03) indicates low genetic differentiation among populations which is corresponding to low Fixation index of 0.141. When gene flow occurs at a high level, the isolated populations will not diverge genetically. Since D. sophia produces many seeds, wind could help in its dispersal. Of course there is a chance of germplasm exchange between regions by human-aided dispersal as seeds commonly used in a sweet Iranian drink. This high genetic diversity will allow them to easily adapt to environmental changes.

The estimated Nei’s gene diversity value of 0.26 also confirms high genetic diversity level within germplasms. Understanding such diversity is useful in the germplasm management. Conservation programs should aim to preserve all the extant populations as genetic differentiation among populations is low. Considering the low correlation between genetic distance and geographical locations in this study on limited populations, a more intricate survey must be investigated for D. sophia, which could include samples from regions that have not been covered in this study. As population sizes could make positive effects on genetic variation within population (Leimu et al. 2006) therefore collection of more individuals will make a better view of genetic variation. Another important implication of the results is selection of diverse parents for plant population construction. This study also shows ISSR technique is an eligible tool to detect the genetic diversity and genetic relatedness of D. sophia germplasm as it revealed 94 % of loci to be polymorphic and the effective number of alleles to be about 1.4 which corresponded with the findings in other medicinal plants (Liu et al. 2013; Bhattacharyya and Kumaria 2015).

In conclusion, the calculated percentage of polymorphic fragments reveals a high degree of genetic variability of this species in Iran.

Acknowledgments

This work was financially supported by a research grant (No. 90322651) from Bu Ali-Sina University, Hamedan, Iran.

Compliance with ethical standards

Author contribution

All authors made substantial contributions to the work presented in this paper.

Conflict of interest

The authors declare that they have no conflict of interest.

Contributor Information

Sahar Saki, Email: sakisahar@gmail.com.

Hedayat Bagheri, Email: bagheri.hedayat@gmail.com.

Ali Deljou, Email: alideljou@yahoo.com.

Mehrshad Zeinalabedini, Email: mzeinolabedini@abrii.ac.ir.

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