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Genetic diversity in Indian poppy (P. somniferum L.) germplasm using multivariate and SCoT marker analyses
Industrial Crops & Products 144 (2020) 112050
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Genetic diversity in Indian poppy (P. somniferum L.) germplasm using multivariate and SCoT marker analyses
T
Abhilasha Srivastavaa,d, Soni Guptaa, Karuna Shankerb,d, Namita Guptab, Anil Kumar Guptaa,d,*, R.K. Lalc a
Department of Genetic Resource Management, CSIR- Central Institute of Medicinal and Aromatic Plants, Lucknow, 226015, India Analytical Chemistry Department, CSIR- Central Institute of Medicinal and Aromatic Plants, Lucknow, 226015, India c Division of Genetics and Plant Breeding, CSIR- Central Institute of Medicinal and Aromatic Plants, Lucknow, 226015, India d Academy of Scientific and Innovative Research (AcSIR), Ghaziabad-201002 b
ARTICLE INFO
ABSTRACT
Keywords: Alkaloids Cluster analysis Genotyping Mahalanobis D2 Polymorphism
The current study was undertaken to estimate the morphological and molecular diversity present among the 51 accessions of Indian opium poppy germplasm using Mahalanobis D2 and SCoT (Start Codon Targeted Polymorphism) marker analyses, respectively. A good range of morphological variations were observed among the accessions. The accessions were clumped into nine clusters and the morphological diversity recorded was 69%. Clusters VII and IX showed the maximum inter-cluster distance (117.97) whereas it was found to be minimum (21.53) in case of clusters II and III. The morphological trait, seed yield per capsule, contributed maximum (17.30%) towards the genetic divergence followed by thebaine content (14.56%) and papaverine content (14.06%). In contrast to the morphological diversity, genetic diversity at molecular level was found to be limited (33%), although successfully detected by utilizing DNA markers targeting coding regions of genome (SCoT markers). The outcome of the study has prospects in identification of lines with desirable traits to be utilized in future breeding programmes.
1. Introduction Opium poppy (Papaver somniferum L.), family Papaveraceae, is one of the highly traded medicinal plants grown since centuries for its valuable alkaloids (Neligan, 1927). The plant is the source of opium gum containing several pharmaceutically important alkaloids, such as morphine, codeine, thebaine, papaverine, noscapine etc. (Frick et al., 2005). World Health Organisation has recommended morphine and codeine as an essential therapeutic tool with a wide range of medical application and recently in treatment of cancer-related pain (Mansfield, 2001). In several countries including India, opium poppy is cultivated as a dual purpose crop for seeds and opium. Its seeds are highly nutritious and contain about 24% protein. The seed oil contains high percent of linoleic acid found to be useful in the treatment of cardiovascular diseases and also helps in lowering blood cholesterol level (Vos and Cunnne, 2003; Sacks and Campos, 2006). The free cultivation of opium poppy is restricted due to easy acetylation of morphine into a notorious narcotic derivative - heroin. It is cultivated in other countries such as USSR, Egypt, China, Poland,
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Czechoslovakia, Japan, and Yugoslavia etc. under the strict control of Central Bureau of Narcotics, Vienna (Austria) (Vesselovskaya, 1976; Singh et al., 1995). The opium producing countries, except India, directly extract alkaloids from concentrate of poppy straw (CPS). India is the largest producer and exporter of opium worldwide where licit gum harvest is allowed through lancing of poppy capsules under strict licensing in its three states (Madhya Pradesh, Rajasthan, and Uttar Pradesh). The total area under poppy cultivation is governed by the United Nations according to the global demand of opium. Half of the opium used by the pharmaceutical industries is produced by India itself. Taking into account the wide pharmaceutical importance of opium poppy, constant research and development work needs to be taken up towards the genetic improvement of the crop. The basic step towards the genetic improvement of any crop includes the study of genetic diversity among the available germplasm at morphological as well as molecular level. This genetic diversity study helps in the selection of diverse parents which can later be utilized to obtain desirable recombinants under different hybridization programmes. The morphological diversity can be studied using multivariate analysis, principal
Corresponding author. E-mail address: [email protected] (A.K. Gupta).
https://doi.org/10.1016/j.indcrop.2019.112050 Received 19 September 2019; Received in revised form 23 November 2019; Accepted 14 December 2019 0926-6690/ © 2019 Elsevier B.V. All rights reserved.
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component analysis, D2 analysis, metroglyph analysis etc. A number of studies using these analyses have been attempted in poppy as well as in other crops, such as rice, wheat, Withania, Curcuma, Vetiver, Ocimum, Isabgol etc. by Singh et al. (2004); Yadav et al. (2007a), b); Sanni et al. (2012); Lal (2013); Bhanupriya et al. (2014); Gupta et al. (2011, 2015), Sarkar et al. (2015); Srivastava et al. (2018). The usefulness of D2 statistics for choosing parents has already been demonstrated by Bhatt (1973) in wheat crop. D2 determines the diversity present among the germplasm at genotypic level and also gives information about the relative contribution of different characters towards total diversity at inter and intra-cluster levels, respectively. DNA markers, since long have been used for the assessment of molecular diversity in the germplasm. Several studies using RAPD, ISSR and AFLP markers have been taken up to record the genetic diversity in opium poppy germplasm. Celik et al. (2016) in his study on Turkish opium poppy reported association mapping in opium poppy for the first time. He reported significant association of morphine content with one SSR and three AFLP loci; and six SSR and 14 AFLP with five other economic traits. In another study, Saunders et al. (2001) analysed 40 accessions of P. somniferum and two other species, P. bracteatum and P. setigerum (using AFLP analysis) from a commercial collection in Tasmania, Australia. They reported 73% polymorphism reflecting narrow genetic diversity in their analysed population although the collection consisted of accessions from different countries. Dubey et al. (2010) during his screening of 32 distinct accessions of opium poppy for alkaloid content in straw, identified some AFLP fragments which could differentiate high and low morphinan alkaloid producing genotypes. Darokar et al. (2014) used AFLP to differentiate high and low alkaloid yielding cultivars. The choice of marker system being used in studies is largely dependent on crop to be studied, available equipment, technical expertise, and available funds. In most of the genotypic studies across several crop species, markers employed were phenotypically neutral because these were derived from random genomic regions (Kage et al., 2015). The fast paced genomic research has facilitated researchers to move towards markers with targeted coding regions of the genome instead of random ones (Andersen and Lubberstedt, 2003; Gupta and Rustgi, 2004). Some of the examples of DNA markers targeting coding regions are expressed sequence tag-simple sequence repeat (EST-SSR), cDNA-amplified fragment length polymorphism (cDNA-AFLP), sequence-related amplified polymorphism (SRAP), Single nucleotide polymorphism (SNPs) etc. A novel marker system known as start codon targeted (SCoT) polymorphism was developed by Collard and Mackill (2009), which utilises the short conserved regions around the ATG initiation codon in plant genes. The marker technique has been reported in several crops such as rice, capsicum, barley, durum wheat etc. (Gupta et al., 2019; Qaderi et al., 2019; Aboulila and Mansour, 2017; Etminan et al., 2016). Like RAPD and ISSR, the SCoT marker system also uses a single primer amplification reaction. The SCoT primers are such designed considering these markers to be distributed within genic regions on both sense and anti-sense DNA strands. These markers have been anticipated for three main applications (QTL mapping, genetic diversity studies and bulk segregant analysis). With this background, we have attempted genetic diversity analyses in Indian opium poppy germplasm using gene targeted SCoT markers along with morpho-chemotypic clustering by D2 analysis. This is the first report of utilizing SCoT markers for characterizing opium poppy germplasm.
and Aromatic Plants (CSIR-CIMAP), Lucknow, India. The accessions comprised of breeding lines (45), mutants (3) and released varieties (3) (Supplementary Table 1) and were grown in the field for two consecutive years during the cropping season (November - April) of 201617 and 2017-18 at the research farm of CSIR-CIMAP, Lucknow (26.5 °N and 80.50 °E; having sandy loam soil and sub-tropical climate). The experiment was conducted in the second week of November in a randomized block design with three replications. Row to row spacing of 40 cm and a plant to plant distance of 10 cm was maintained, the latter being achieved by thinning the rows when the seedlings were 3–4 weeks old. Other recommended standard cultivation operations were followed while raising the experimental populations. 2.2. Phenotyping The observations were recorded on five randomly selected plants of each accession in three replicates for days to 50% flowering, plant height (cm), pedicel length (cm), number of capsules per plant, capsule index, husk weight per capsule (g), seed yield per capsule (g), disease severity index (DSI), and alkaloid content (morphine, codeine, thebaine, papaverine in percent). The vegetative growth characters (except days to 50% flowering) were recorded on fully mature plants growing in the field while the yield related characters and the alkaloid analyses were recorded post-harvest. The downy mildew disease incidence was scored on five plants in each replication for all accessions based on 0–9 scale (Dubey, 2008). The scale for scoring was taken as follows: 0–1.0 = 0–10 % infection, 1.1–2.0 = 11–20 %, 2.1–3.0 = 21–30 %, through 8.1–9.0 = 80–90 % infection on leaves (disease intensity). DSI was calculated for each of the 51 accessions by the following formula (Kim et al., 1999):
DSI=
(ratingofeachplant) X100 9xnumbersofplantsrated
On the basis of the DSI values calculated, the accessions were categorized into five types, namely, highly resistant (0.00–12.21), resistant (12.22–33.33), tolerant (33.34–55.55), susceptible (55.56–77.77) and highly susceptible (77.78–99.99). 2.3. Extraction and quantification of alkaloids by HPLC For the extraction of the alkaloids, dried capsules were powdered and 1 g sample was extracted in methanol (10 ml) by sonication for 30 min in an ultrasonic water bath at 40−45 °C. The extract was filtered in another tube and the above process was repeated two more times. The pooled filtrate was then completely dried in water bath and dissolved in 1 ml HPLC grade methanol for the HPLC analysis. Prior to HPLC injection, solutions were filtered through 0.45 μm nylon membrane filter unit (Millipore vacuum filtration). The HPLC analysis was performed on a Waters Modular HPLC system (Waters, Miliford, MA, United States) consisting of 2996 PDA detector, 600 controller, column oven and 717 Plus auto sampler. Separation was carried out at 30 °C using the Phenomenex Luna® column C18 (2) (4.6 × 250 mm, particle size is 5 μm) reverse phase comprised of isocratic elution with 0.1 M sodium phosphate buffer (pH 3.5) (A) and acetonitrile (B) in a ratio of 77: 23 (v/v). The flow rate was 1.0 ml / min. A 20 μl aliquot of standard and sample solution was injected into the HPLC system. Chromatographic data acquisition was carried out at 240 nm using Empower Software. Quantification of data was based on the peak area measurement using external standard method.
2. Materials and methods 2.1. Plant material, experimental site and design
2.4. DNA isolation
A total of 51 accessions were taken from the genetic stock of opium poppy (P. somniferum L.) maintained in the National Gene Bank for medicinal and aromatic plants at CSIR-Central Institute of Medicinal
The total genomic DNA of 51 accessions was extracted from the fresh leaf tissue of 3–4 week field grown plants using the DNeasy Plant 2
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Mini Kit (QIAGEN) following manufacturer’s instructions. The quality and quantity of the DNA were checked by agarose gel electrophoresis and spectrometrically using Nanodrop ND1000 (JH Bio). DNA samples were diluted to a final concentration of 25−30 ng /μl before PCR amplification.
Table 1 ANOVA for twelve characters of Opium poppy. S. No.
2.5. Genotyping by SCoT markers
1 2 3 4 5 6 7 8 9 10 11 12
Thirty six SCoT primers were synthesized as suggested by Collard and Mackill (2009). PCR were carried out in a 20 μl reaction volume containing 25−30 ng of template DNA,10X PCR buffer, 2.5 mM of each dNTP’s, 10 pmol of primer and 3U of Taq DNA polymerase (GeNei). Additionally, three SCoT primers were used in different combinations as double and triple SCoT to increase the polymorphism among the accessions. The PCR amplifications were performed on a thermal cycler (ProFlex, Applied Biosystems) programmed for initial denaturation at 94 °C for 3 min; 40 cycles of denaturation at 94 °C for 1 min, annealing at 50 °C (for all primers) for 1 min and extension at 72 °C for 2 min; final extension at 72 °C for 5 min and 12 °C forever. The amplified PCR products were separated on a 1.5 % agarose gel, using a horizontal gel electrophoresis unit for 2 h and documented under UV light using GelDoc-It imager (UVP, Analytik Jena, Germany). The molecular size of the amplified products was determined against a 100 bp −3 kb DNA Ladder (GeNei). The presence and absence of the bands were scored and similarity indices were generated using Jaccard’s coefficient. A dendogram was constructed based on similarity matrix by UPGMA (unweighted pairgroup method of arithmetic averages) method in NTSYS software. Cophenetic correlation ratio was also estimated to find the good of fit of dendogram to that of data matrix.
Characters
Plant Height No. of capsules per plant Days to 50% flowering Pedicel length Capsule Index Husk weight per capsule Seed yield per capsule Disease severity index Morphine content Codeine content Thebaine Content Papaverine content
MEAN SUM OF SQUARES Replication (d.f. = 2)
Treatment (d.f. = 50)
Error (d.f. = 100)
84.73 0.253 0.53 1.29 0.031 7.72 0.41 0.36 0.002 0.002 0.0002 0.00001
133.60** 1.13** 47.12** 14.01** 0.48** 10.11** 5.53** 551.26** 0.007** 0.009** 0.005** 0.005**
37.53 0.092 3.01 6.78 0.006 0.25 0.38 2.50 0.00004 0.0001 0.00003 0.00001
** Significant at 1% level of significance.
variability in the germplasm for all the characters. Also the morphine content in the peduncle ranged between 0.001–0.24% and in capsule between 0.02–1.05 %. A study by Saikia and Gupta (2014) on 108 accessions of opium poppy for five morphometric traits revealed considerable genetic variability among the accessions. In a study by Brezinova et al. (2009), the genetic diversity of 404 lines of poppy was studied based on their morphological characters. Dittbrenner et al. (2009) studied 35 morphological and agronomic traits for 300 accessions of opium poppy and reported high significant correlation between alkaloid content and morphological traits. In accordance with these studies we too found considerable phenotypic variations.
2.6. Statistical analysis
3.2. Clustering of accessions
The Statistical Software (version 4.0), available in the Division of Genetics and Plant Breeding of the CSIR–CIMAP was used to analyse the replicated two years pooled mean data for ANOVA and D2 analysis as prescribed by Singh and Chaudhary (1979). Methods described by Mahalanobis (1936) were followed to study the genetic diversity using the D2 analysis. The grouping of the genotypes into clusters was done following the Tocher’s method (Rao, 1952).
The existing variability among the 51 accessions was evaluated using the analysis of variance (ANOVA), which revealed high level of statistically significant variation (p < 0.01) for all the twelve characters studied (Table 1). A total of 1275 pairwise combinations of all 51 accessions {calculated by the formula, n (n-1)/2, where n is the number of accessions} were obtained by D2 analysis. The maximum and minimum D2 values were 13915.96 and 53.24, respectively. The vast difference between the maximum and the minimum D2 value showed that there was adequate diversity present among the accessions. The 51 accessions were grouped into nine clusters (Fig. 1, Supplementary Table 3) with 69% diversity based on the λ1 and λ2 values. The largest cluster was Cluster I with 18 accessions followed Cluster II (14 accessions), cluster III (11 accessions) and 2 accessions each in clusters IV and V. Cluster VI, VII, VIII, and IX contained 1 accession each, revealing its uniqueness and maximum genetic diversity. Earlier, studies by Singh et al. (2004) on genetic divergence in 101 germplasm lines for seed and opium yield per plant using multivariate and canonical analysis grouped them into 13 clusters (68% lines were genetically similar and grouped into 6 clusters and 32% lines formed the rest 7 clusters). Singh et al. (2017) studied the genetic divergence among 28 germplasm lines for 14 morpho-metric traits and reported a total of 6 clusters grouping the accessions. In another study by Shukla et al. (2018) on 55 accessions of opium poppy by D2 analysis, the accessions were grouped into seven clusters. Shukla et al. (2010) studied the diversity in alkaloid profile of 122 poppy accessions by Mahalanobis D2 analysis. Based on the relationship between the alkaloid content in raw opium, the accessions were grouped into 11 clusters. The diversity of alkaloid revealed very low correlation between content of individual alkaloid. The inter- and intra-cluster distances are represented in the Fig. 2 and Supplementary Table 4. The intra-cluster distance depicts the variability present within a cluster. The intra cluster distances in
3. Results and discussion 3.1. Morpho-chemotypic variability in genetic stock Morphological variations recorded for the 12 characters among the germplasm accessions are enlisted in Supplementary Table 2. Good range of variations were observed in several characters such as plant height {85–116 cm (max. in CIM 142 and least in CIM 139)}; number of capsules per plant {1–3.99 (max. in CIM 120 and least in CIM 123)}; husk weight per capsule {1.48–7.84 g (max. in CIM 123 and least in CIM 112)} and seed yield per capsule (0.44–6.22 g) (Supplementary Fig. 1). Based on 50% flowering data, variety Sapna and yellow mutant (YM) were found to be the early and late maturing lines among the germplasm accessions, respectively. The disease severity index revealed that a total of 16 accessions were resistant, 25 tolerant and 10 susceptible to downy mildew disease. None of the accessions were found to be either highly susceptible or highly resistant. The alkaloid content variations are depicted in Supplementary Fig. 2. Similar kind of variations has also been reported by Gumuscu et al. (2008) during the evaluation of alkaloids in poppy husk (CPS) of 99 lines {morphine (0.11–1.14%), thebaine (0.005–0.134%), codeine (0.005–0.27%), papaverine (0.001–0.44%) and noscapine (0.006–0.418%)}. Bajpai et al. (2000) did her study on 208 Indian and 2 Thai accessions of P. somniferum for variations in 17 morphological characters and reported high 3
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Fig. 1. Spatial distribution of 51 genetic stocks of opium poppy in λ1-λ2 chart. The numbers 1-51 represents the 51 accessions taken in the study (serial no. 1-51 as mentioned in Supplementary Table 1).
maximum towards the diversity, followed by thebaine content (14.56%), papaverine content (14.06%), number of capsules per plant (12.79%), and husk weight per capsule (9.40%). The percent contribution and the rank of all the traits are represented in the Table 2. Shukla et al. (2018) in their study on opium poppy, reported codeine content as the highest contributor (32.86%) followed by papaverine content (10.41%). In future, these characters contributing towards genetic divergence can be given due value during the selection of accessions for further breeding programmes.
decreasing order were found in clusters I (21.52), V (21.16), II (18.84), III (17.15), and IV (14.66) revealing the fact that the accessions in cluster I were relatively more diverse whereas those in cluster IV were least. The inter-cluster distance reveals the divergence of one cluster from the other. The inter cluster distances were greater than the intra cluster distance. The largest inter cluster distance was between cluster VII and cluster IX (117.97), followed by cluster VI and IX (103.20), cluster I and IX (102.78) and Cluster III and IX (100.98). The cluster means values shed light on the desirability of accessions in a particular cluster for genetic improvement of the trait(s). The cluster mean for plant height {maximum - cluster IX (110.27); minimum - cluster V (88.37), number of capsules per plant {maximum cluster VIII (3.90); minimum - cluster VII (1.18)}, days to 50% flowering {maximum - cluster IX (112.33); minimum - cluster VI (104.0)}, pedicel length {maximum - cluster IV (24.83); minimum - cluster VII (21.47)}, capsule index {maximum - cluster IV (2.01); minimum cluster VI (1.19)}, husk weight per capsule {maximum - cluster VIII (7.04); minimum - cluster IX (2.31)}, seed yield per capsule {maximum - cluster IV (5.52); minimum - cluster IX (1.21), disease severity index {maximum - cluster VI (68.89); minimum - cluster IX (24.10)}, morphine content {maximum - cluster VI and VII (0.26); minimum - cluster IX (0.10)}, codeine content {maximum - cluster VII (0.23) and minimum - cluster III (0.08)}, thebaine content {maximum - cluster VII (0.23); minimum - cluster IX (0)}, papaverine content {maximum cluster IX (0.26); minimum - cluster VII (0)} are presented in the Supplementary Table 5. As can be seen from the above data, none of the clusters had accessions with all the desirable traits for direct selection and exploitation. However, cluster IX was categorized by desirable traits like papaverine content and resistance towards diseases. Similarly, cluster IV is categorized by traits like high pedicel length, capsule index and seed yield per capsule, whereas the other clusters were high in one or other trait. Therefore, for the effective improvement of individual trait, accessions need to be selected from the corresponding clusters.
3.4. Desirable accessions for future breeding programmes Though all the characters taken for study are of agronomic importance but certain traits directly contribute towards the economic importance of the plant such as: (i) Number of capsules per plant: The accession CIM 120 had the highest number of capsules per plant (3.99). Since the number of capsules directly contributes towards the husk yield leading to high alkaloid, the accession CIM 120 may be exploited while making selections for this trait. (ii) Husk weight per capsule: This is also an important trait as the husk weight contributes towards the total alkaloid content of the plant. The accession CIM 123 possessed around 7.84 g of husk weight which was highest among all the accessions. However, the seed yield of this accession was very less (2.85 g) which is an undesirable trait. (iii) Seed yield per capsule: Poppy seeds are used for culinary purposes and so seed yield is an economically important trait during selections for edible lines. Accession CIM 131 contained around 6.22 g of seeds per capsule followed by accession CIM 142 (6.02 g). (iv) Disease severity index (DSI): Downy mildew is a major disease that causes huge losses in the yield in opium poppy. Rakshit is a downy mildew resistant variety released by CSIR-CIMAP. In our study, 16 accessions were found to be downy mildew resistant, 25 accessions were tolerant while 10 accessions were susceptible. None of the accessions ranged in the category of highly resistant and highly susceptible lines. Thus, the resistant accessions can be given due importance while selections for further breeding programmes. The variety Rakshit and the mutant Pps-1 were in the category of resistant lines.
3.3. Maximum contributing trait The selection and choice of parents largely depends upon the contribution of different traits towards the genetic divergence. Among the twelve characters studied, seed yield per capsule (17.30%) contributed 4
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Fig. 2. Cluster diagram with their genetic distances of 51 genetic stocks of opium poppy germplasm.
(v) Alkaloid content: Lines with high alkaloid content are pharmaceutically important. Rakshit can be selected for morphine and codeine content (0.37%; 0.26%), CIM 110 for thebaine content (0.23%) and CIM 377 (0.26%) for papaverine content.
Table 2 Character contribution (%) towards total divergence and rank of the twelve traits in Opium poppy. Characters
Character Contribution %
Rank
Plant height Number of capsules per plant Days to 50% flowering Pedicel length Capsule Index Husk weight per capsule Seed yield per capsule Disease severity index Morphine content Codeine content Thebaine content Papaverine content
5.03 12.79 1.33 8.86 4.20 9.40 17.30 2.98 2.51 6.98 14.56 14.06
8th 4th 12th 6th 9th 5th 1st 10th 11th 7th 2nd 3rd
Identification of genotypes as parents for hybridization from different clusters might lead to segregants with combination of superior alleles. Genotypes namely, CIM 120, CIM 123, CIM 131, CIM 142, Rakshit and Pps-1 may be considered as elite lines and crosses using these lines are likely to result in desirable segregants for yield and related traits. For culinary purpose, high seed yield can be achieved through crossing CIM 120 and CIM 131 which may act as donors for high number of capsules per plant and seed yield per capsule and simultaneously are genetically diverse belonging to cluster VIII and IV, respectively. Similarly for pharmaceutical use, diverse lines CIM 110 (rich in thebaine content) and CIM 377 (rich in papaverine content) can
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Table 3 Primer name, sequence, molecular size range, bands number and percentage of polymorphism as detected by SCoT markers. Molecular marker technique
Primer name
Primer sequence (5´→ 3´)
Molecular size range (bp)
TAB
PB
P (%)
Single SCoT
SCoT SCoT SCoT SCoT SCoT SCoT + SCoT SCoT + SCoT SCoT + SCoT
CAACAATGGCTACCACCG CAACAATGGCTACCACGG ACGACATGGCGACCGCGA ACCATGGCTACCACCGCG CATGGCTACCACCGGCCC CAACAATGGCTACCACCG ACGACATGGCGACCGCGA
700–1050 950–1300 150–2100 450–1300 200–1200 80–1100
2 2 7 6 6 7
1 1 7 5 1 6
50 50 100 83.33 16.66 85.71
CAACAATGGCTACCACCG ACCATGGCTACCACCGCG
150–1300
6
4
66.66
ACGACATGGCGACCGCGA ACCATGGCTACCACCGCG
220–1100
6
3
50
Double SCoT Double SCoT Double SCoT
3 7 15 20 35 3 15 3 20 15 20
TAB = Total number of amplified bands, PB = number of polymorphic bands, P (%) = polymorphism percentage.
between 0.500 – 0.970 (Supplementary Table 6) which was used for clustering the accessions by UPGMA method (Fig. 3). Two major clusters were formed. These major clusters were further divided into several sub-clusters. Among the cultivars, Rakshit showed maximum similarity with Sapna (76%) followed by Vivek (74%). Rakshit and Pps-1 clustered together in same cluster in both SCoT marker and morphological clustering. The three mutants Pps-1, YM and OM showed 76%, 73% and 68% similarity with Rakshit, respectively. Sapna and Vivek showed 70% genetic similarity with each other. These cultivars showed moderate genetic similarity with the three mutants. The co-phenetic correlation coefficient (r) was found to be 0.921, suggesting a good fit of the tree with that of the data. We initially screened our germplasm using Inter simple sequence repeats markers (ISSR, Supplementary Fig. 3), but in contrast to earlier reports we did not observe any polymorphism (data not shown). This was very surprising fact considering the robustness, utility, and widespread use of ISSR markers for genetic diversity studies. The failure of not detecting polymorphism with ISSR markers (which are largely a part of non-coding region) made us shift to DNA markers targeting genic regions (SCoT markers) to genotype population which was observed to be phenotypically diverse. This further proves the utility of DNA markers targeting coding regions in genotyping phenotypically variable germplasm having limited genetic variation. As seen from the Figs. 1 and 3, the morphological clustering was found to show no correlation with the molecular clustering pattern. There are several studies where weak or no correlation between molecular marker analysis (AFLP, RAPD, SSR) and geographical location of cultivars or the morphological/ agronomic traits were recorded (Kölliker et al., 2001; Zhang et al., 2010). Zhang et al. (2010) observed no correlation between leaf size and molecular markers (SSR and RAPD) diversity patterns in white clover. The evident disparity between molecular and morphological clustering patterns is due to the fact that the molecular markers have a larger representation of the genome than morphological markers which are controlled by a relatively few specific loci in the genome (Bruschi et al., 2003). The SCoT markers may not have necessarily screened those loci of the genome that determine the morphological traits taken in the study. Also, the influence of the environment is more pronounced than the molecular markers. Thus, clustering pattern based on morphological traits and molecular markers may not be correlated in every case. The genetic diversity based on morphological traits (∼69%) was higher than those of molecular markers (33%) in our study, a fact that was also reported by Zhang et al. (2010) which implies that the genetic base, although narrow, is capable of manifesting into much wider morphological variations. One of the reasons for low genetic diversity may be the fact that this study comprised of only Indian accessions and lacked any exotic collection(s). The
be hybridized with Rakshit to get segregating generations rich in pharmaceutically important alkaloids. In all cases Rakshit may be used to transfer disease resistance in future breeding programmes. 3.5. Molecular diversity in the opium poppy germplasm Out of the 36 primers tested, five of them showed polymorphism (SCoT 3, SCoT 7, SCoT 15, SCoT 20, SCoT 35) (Supplementary Fig. 2). A total of 23 bands were generated by the five primers when used singly, out of which 15 showed polymorphism. When used in combination, a total of 19 bands were generated, among which 13 showed polymorphism. Maximum alleles (7) were amplified with SCoT 15 and minimum (2) were generated each with SCoT 3 and 7, respectively. The amplified products ranged from 200 to 2100 bp size (Table 3). Aboulila and Mansour (2017) reported an increase in polymorphism (89.47%; 94.4%) in barley when using combination of two SCoT and three SCoT primers, respectively. Interestingly, in our study we observed decrease in polymorphism while multiplexing SCoT markers. SCoT 15 individually produced 100% polymorphism but when used in combination with other SCoT primers produced just 85.71% (SCoT 3 and 15) and 50% (SCoT 20 and SCoT 15) polymorphism, respectively. Similarly, a combination of SCoT 3 and SCoT 20 produced 66.66% polymorphism which was in contrast to 83.33% polymorphism when SCoT 20 was used singly. On closer analysis of the amplicons resolved on agarose gels we found that the markers when used singly produced higher molecular weight products than those when used in combination. For example, the range of products with SCoT 15 varied from 2100 to 400 bp and that of SCoT 20 varied from 1750-600. The highest molecular weight amplicons in SCoT 15 (∼2100 bp) and SCoT 20 (∼1750 bp) accounted for 100% and 83.33% polymorphism respectively when used singly in the reaction. However, the reaction kinetics during multiplexing of SCoT primers, preferred the exponential amplification of lower molecular weight products [(1050-50 bp in case of SCoT 3 + 15) and 1300-250 bp in case of SCoT 3 + 20)]. In both of these PCR profiles the highest molecular weight band was absent accounting for drop in polymorphism percent when used in combination (85% when SCoT 3 + 15 were used and 66% when SCoT 3 + 20 were used). The multiplexing of SCoT primers probably led to binding of primers to sense and anti-sense strands of DNA at close proximities than when used singly. It would be interesting to see the results of similar studies with double and triple SCoT primers in other species by other researchers. In our genotyping work, we used one accession of another species, P. rhoeas as an outgroup showing ∼10% similarity to Papaver somniferum accessions. All the P. somniferum accessions when clustered showed similarity of ∼ 67%. The Jaccard’s similarity indices ranged 6
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Fig. 3. Clustering of opium poppy accessions based on SCoT marker analysis.
Central Instrumentation Facility, CSIR–CIMAP, Lucknow for HPLC analysis of the samples and Director, CSIR–CIMAP for providing all the required facilities and encouragement are duly acknowledged. Dr. Sougata Sarkar is acknowledged for his inputs in Figs. 1 and 2. The authors are thankful to Dr. Mohammed Talha for making Supplementary Fig. 1. This manuscript is approved as original research article by the publication committee of CSIR-CIMAP (CIMAP Publication No. CIMAP/PUB/2019/SEP/72).
role of other possible factors such as genetic drift as a result of reduced levels of gene flow due to restricted cultivation/ breeding programmes leading to limited genetic diversity cannot be denied. This situation can further aggravate if such populations have been founded by limited number of individuals (founder effect). 4. Conclusions Study of genetic diversity paves a path for the selection of important accessions which can be exploited for further breeding programmes. The promising accessions with specific traits can be used as parents for hybridization programs. In our study, we studied the morphological variability among the opium poppy germplasm where the diversity was found to be 69%. Accession CIM 120 had the highest number of capsules per plant (∼3.99) directly contributing towards the husk weight. Accession CIM 123 had the highest husk weight (7.84 g) contributing towards the alkaloid content of the plant. Accession CIM 131 contained around 6.22 g seeds per capsule which is an important trait. CIM 110 and CIM 377 can be selected for high thebaine and papaverine content, respectively. The SCoT markers were used to access the molecular diversity which was found to be 33% revealing a narrow genetic base in the germplasm because of genetically close accessions and also no exotic collection in the germplasm. However, SCoT markers were able to generate the polymorphism among the accessions at molecular level where ISSR markers had failed. As SCoT markers target regions of the genome that are expressed, so the variability among the accessions as revealed by these markers is indicative of the morphological variations observed among the accessions to some extent.
Appendix A. Supplementary data Supplementary material related to this article can be found, in the online version, at doi:https://doi.org/10.1016/j.indcrop.2019.112050. References Aboulila, A.A., Mansour, M., 2017. Efficiency of Triple-SCoT primer in characterization of genetic diversity and genotype-specific markers against SSR fingerprint in some Egyptian barley genotypes. Am. J. Mol. Biol. 7, 123–137. https://doi.org/10.4236/ ajmb.2017.73010. Andersen, J.R., Lubberstedt, T., 2003. Functional markers in plants. Trends Plant Sci. 8, 554–650. https://doi.org/10.1016/j.tplants.2003.09.010. Bajpai, S., Gupta, A.P., Gupta, M.M., Sharma, S., Govil, C.M., Kumar, S., 2000. Interrelation between descriptors and morphine yield in Asian germplasm of opium poppy Papaver somniferum. Genet. Resour. Crop Ev. 47, 315–322. https://doi.org/10.1023/ A:1008752805362. Bhanupriya, B., Satyanarayana, N.H., Mukherjee, S., Sarkar, K.K., 2014. Genetic diversity of wheat genotypes based on principal component analysis in Gangetic alluvial soil of West Bengal. J. Crop Weed. 10 (2), 104–107. Bhatt, G.M., 1973. Comparison of various methods of selecting parents for hybridization in common bread wheat. Aust. J. Agric. Res. 24, 457–464. https://doi.org/10.1071/ AR9730457. Brezinova, B., Macak, M., Eftimova, J., 2009. The morphological diversity of selected traits of world collection of poppy genotypes (Genus Papaver). J. Cent. Eur. Agric. 10 (2), 183–190. Bruschi, P., Vendramin, F., Bussotti, P., Grossoni, G.G., 2003. Morphological and molecular diversity among Italian populations of Quercus petraea (Fagaceae). Ann. Bot. 91, 707–716. Celik, I., Camci, H., Kose, A., Kosar, F.C., Doganlar, S., Frary, A., 2016. Molecular genetic diversity and association mapping of morphine content and agronomic traits in Turkish opium poppy (Papaver somniferum) germplasm. Mol. Breeding. 36 (4), 46. https://doi.org/10.1007/s11032-016-0469-8. Collard, B.C.Y., Mackill, D.J., 2009. Start Codon targeted (SCoT) Polymorphism: a simple, novel DNA marker technique for generating gene-targeted markers in plants. Plant Mol. Biol. Rep. 27, 86–93. https://doi.org/10.1007/s11105-008-0060-5. Darokar, M.P., Dhawan, S.S., Shukla, A.K., Thul, S.T., Lal, R.K., Shasany, A.K., Khanuja, S.P.S., 2014. Assessment of genetic relatedness among selected cultivars of opium poppy (Papaver somniferum L.) through DNA profiling. Acta Hortic. 1036, 21–28. https://doi.org/10.17660/ActaHortic.2014.1036.2. Dittbrenner, A., Mock, H.P., Borner, A., Lohwasser, U., 2009. Variability of alkaloid content in Papaver somniferum L. J. Appl. Bot. Food Qual. 82 (2), 103–107. Dubey, M.K., Shasany, A.K., Dhawan, O.P., Shukla, A.K., Shanker, K., Khanuja, S.P.S., 2010. Detection of DNA polymorphism in Papaver somniferum genotypes differing in
AuthorContributions AKG, SG were involved in planning; AS, SG in actual experimentation; KS, NG in chemical analyses by HPLC; AS, AKG, RKL in statistical analyses; and SG, AS, AKG in manuscript preparation. Declaration of Competing Interest None. Acknowledgements This study is a part of the Ph.D work of the first author and Academy of Scientific and Innovative Research is acknowledged for giving an opportunity to carry out the present work. 7
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Genetic diversity in Indian poppy (P. somniferum L.) germplasm using multivariate and SCoT marker analyses
T
Abhilasha Srivastavaa,d, Soni Guptaa, Karuna Shankerb,d, Namita Guptab, Anil Kumar Guptaa,d,*, R.K. Lalc a
Department of Genetic Resource Management, CSIR- Central Institute of Medicinal and Aromatic Plants, Lucknow, 226015, India Analytical Chemistry Department, CSIR- Central Institute of Medicinal and Aromatic Plants, Lucknow, 226015, India c Division of Genetics and Plant Breeding, CSIR- Central Institute of Medicinal and Aromatic Plants, Lucknow, 226015, India d Academy of Scientific and Innovative Research (AcSIR), Ghaziabad-201002 b
ARTICLE INFO
ABSTRACT
Keywords: Alkaloids Cluster analysis Genotyping Mahalanobis D2 Polymorphism
The current study was undertaken to estimate the morphological and molecular diversity present among the 51 accessions of Indian opium poppy germplasm using Mahalanobis D2 and SCoT (Start Codon Targeted Polymorphism) marker analyses, respectively. A good range of morphological variations were observed among the accessions. The accessions were clumped into nine clusters and the morphological diversity recorded was 69%. Clusters VII and IX showed the maximum inter-cluster distance (117.97) whereas it was found to be minimum (21.53) in case of clusters II and III. The morphological trait, seed yield per capsule, contributed maximum (17.30%) towards the genetic divergence followed by thebaine content (14.56%) and papaverine content (14.06%). In contrast to the morphological diversity, genetic diversity at molecular level was found to be limited (33%), although successfully detected by utilizing DNA markers targeting coding regions of genome (SCoT markers). The outcome of the study has prospects in identification of lines with desirable traits to be utilized in future breeding programmes.
1. Introduction Opium poppy (Papaver somniferum L.), family Papaveraceae, is one of the highly traded medicinal plants grown since centuries for its valuable alkaloids (Neligan, 1927). The plant is the source of opium gum containing several pharmaceutically important alkaloids, such as morphine, codeine, thebaine, papaverine, noscapine etc. (Frick et al., 2005). World Health Organisation has recommended morphine and codeine as an essential therapeutic tool with a wide range of medical application and recently in treatment of cancer-related pain (Mansfield, 2001). In several countries including India, opium poppy is cultivated as a dual purpose crop for seeds and opium. Its seeds are highly nutritious and contain about 24% protein. The seed oil contains high percent of linoleic acid found to be useful in the treatment of cardiovascular diseases and also helps in lowering blood cholesterol level (Vos and Cunnne, 2003; Sacks and Campos, 2006). The free cultivation of opium poppy is restricted due to easy acetylation of morphine into a notorious narcotic derivative - heroin. It is cultivated in other countries such as USSR, Egypt, China, Poland,
⁎
Czechoslovakia, Japan, and Yugoslavia etc. under the strict control of Central Bureau of Narcotics, Vienna (Austria) (Vesselovskaya, 1976; Singh et al., 1995). The opium producing countries, except India, directly extract alkaloids from concentrate of poppy straw (CPS). India is the largest producer and exporter of opium worldwide where licit gum harvest is allowed through lancing of poppy capsules under strict licensing in its three states (Madhya Pradesh, Rajasthan, and Uttar Pradesh). The total area under poppy cultivation is governed by the United Nations according to the global demand of opium. Half of the opium used by the pharmaceutical industries is produced by India itself. Taking into account the wide pharmaceutical importance of opium poppy, constant research and development work needs to be taken up towards the genetic improvement of the crop. The basic step towards the genetic improvement of any crop includes the study of genetic diversity among the available germplasm at morphological as well as molecular level. This genetic diversity study helps in the selection of diverse parents which can later be utilized to obtain desirable recombinants under different hybridization programmes. The morphological diversity can be studied using multivariate analysis, principal
Corresponding author. E-mail address: [email protected] (A.K. Gupta).
https://doi.org/10.1016/j.indcrop.2019.112050 Received 19 September 2019; Received in revised form 23 November 2019; Accepted 14 December 2019 0926-6690/ © 2019 Elsevier B.V. All rights reserved.
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component analysis, D2 analysis, metroglyph analysis etc. A number of studies using these analyses have been attempted in poppy as well as in other crops, such as rice, wheat, Withania, Curcuma, Vetiver, Ocimum, Isabgol etc. by Singh et al. (2004); Yadav et al. (2007a), b); Sanni et al. (2012); Lal (2013); Bhanupriya et al. (2014); Gupta et al. (2011, 2015), Sarkar et al. (2015); Srivastava et al. (2018). The usefulness of D2 statistics for choosing parents has already been demonstrated by Bhatt (1973) in wheat crop. D2 determines the diversity present among the germplasm at genotypic level and also gives information about the relative contribution of different characters towards total diversity at inter and intra-cluster levels, respectively. DNA markers, since long have been used for the assessment of molecular diversity in the germplasm. Several studies using RAPD, ISSR and AFLP markers have been taken up to record the genetic diversity in opium poppy germplasm. Celik et al. (2016) in his study on Turkish opium poppy reported association mapping in opium poppy for the first time. He reported significant association of morphine content with one SSR and three AFLP loci; and six SSR and 14 AFLP with five other economic traits. In another study, Saunders et al. (2001) analysed 40 accessions of P. somniferum and two other species, P. bracteatum and P. setigerum (using AFLP analysis) from a commercial collection in Tasmania, Australia. They reported 73% polymorphism reflecting narrow genetic diversity in their analysed population although the collection consisted of accessions from different countries. Dubey et al. (2010) during his screening of 32 distinct accessions of opium poppy for alkaloid content in straw, identified some AFLP fragments which could differentiate high and low morphinan alkaloid producing genotypes. Darokar et al. (2014) used AFLP to differentiate high and low alkaloid yielding cultivars. The choice of marker system being used in studies is largely dependent on crop to be studied, available equipment, technical expertise, and available funds. In most of the genotypic studies across several crop species, markers employed were phenotypically neutral because these were derived from random genomic regions (Kage et al., 2015). The fast paced genomic research has facilitated researchers to move towards markers with targeted coding regions of the genome instead of random ones (Andersen and Lubberstedt, 2003; Gupta and Rustgi, 2004). Some of the examples of DNA markers targeting coding regions are expressed sequence tag-simple sequence repeat (EST-SSR), cDNA-amplified fragment length polymorphism (cDNA-AFLP), sequence-related amplified polymorphism (SRAP), Single nucleotide polymorphism (SNPs) etc. A novel marker system known as start codon targeted (SCoT) polymorphism was developed by Collard and Mackill (2009), which utilises the short conserved regions around the ATG initiation codon in plant genes. The marker technique has been reported in several crops such as rice, capsicum, barley, durum wheat etc. (Gupta et al., 2019; Qaderi et al., 2019; Aboulila and Mansour, 2017; Etminan et al., 2016). Like RAPD and ISSR, the SCoT marker system also uses a single primer amplification reaction. The SCoT primers are such designed considering these markers to be distributed within genic regions on both sense and anti-sense DNA strands. These markers have been anticipated for three main applications (QTL mapping, genetic diversity studies and bulk segregant analysis). With this background, we have attempted genetic diversity analyses in Indian opium poppy germplasm using gene targeted SCoT markers along with morpho-chemotypic clustering by D2 analysis. This is the first report of utilizing SCoT markers for characterizing opium poppy germplasm.
and Aromatic Plants (CSIR-CIMAP), Lucknow, India. The accessions comprised of breeding lines (45), mutants (3) and released varieties (3) (Supplementary Table 1) and were grown in the field for two consecutive years during the cropping season (November - April) of 201617 and 2017-18 at the research farm of CSIR-CIMAP, Lucknow (26.5 °N and 80.50 °E; having sandy loam soil and sub-tropical climate). The experiment was conducted in the second week of November in a randomized block design with three replications. Row to row spacing of 40 cm and a plant to plant distance of 10 cm was maintained, the latter being achieved by thinning the rows when the seedlings were 3–4 weeks old. Other recommended standard cultivation operations were followed while raising the experimental populations. 2.2. Phenotyping The observations were recorded on five randomly selected plants of each accession in three replicates for days to 50% flowering, plant height (cm), pedicel length (cm), number of capsules per plant, capsule index, husk weight per capsule (g), seed yield per capsule (g), disease severity index (DSI), and alkaloid content (morphine, codeine, thebaine, papaverine in percent). The vegetative growth characters (except days to 50% flowering) were recorded on fully mature plants growing in the field while the yield related characters and the alkaloid analyses were recorded post-harvest. The downy mildew disease incidence was scored on five plants in each replication for all accessions based on 0–9 scale (Dubey, 2008). The scale for scoring was taken as follows: 0–1.0 = 0–10 % infection, 1.1–2.0 = 11–20 %, 2.1–3.0 = 21–30 %, through 8.1–9.0 = 80–90 % infection on leaves (disease intensity). DSI was calculated for each of the 51 accessions by the following formula (Kim et al., 1999):
DSI=
(ratingofeachplant) X100 9xnumbersofplantsrated
On the basis of the DSI values calculated, the accessions were categorized into five types, namely, highly resistant (0.00–12.21), resistant (12.22–33.33), tolerant (33.34–55.55), susceptible (55.56–77.77) and highly susceptible (77.78–99.99). 2.3. Extraction and quantification of alkaloids by HPLC For the extraction of the alkaloids, dried capsules were powdered and 1 g sample was extracted in methanol (10 ml) by sonication for 30 min in an ultrasonic water bath at 40−45 °C. The extract was filtered in another tube and the above process was repeated two more times. The pooled filtrate was then completely dried in water bath and dissolved in 1 ml HPLC grade methanol for the HPLC analysis. Prior to HPLC injection, solutions were filtered through 0.45 μm nylon membrane filter unit (Millipore vacuum filtration). The HPLC analysis was performed on a Waters Modular HPLC system (Waters, Miliford, MA, United States) consisting of 2996 PDA detector, 600 controller, column oven and 717 Plus auto sampler. Separation was carried out at 30 °C using the Phenomenex Luna® column C18 (2) (4.6 × 250 mm, particle size is 5 μm) reverse phase comprised of isocratic elution with 0.1 M sodium phosphate buffer (pH 3.5) (A) and acetonitrile (B) in a ratio of 77: 23 (v/v). The flow rate was 1.0 ml / min. A 20 μl aliquot of standard and sample solution was injected into the HPLC system. Chromatographic data acquisition was carried out at 240 nm using Empower Software. Quantification of data was based on the peak area measurement using external standard method.
2. Materials and methods 2.1. Plant material, experimental site and design
2.4. DNA isolation
A total of 51 accessions were taken from the genetic stock of opium poppy (P. somniferum L.) maintained in the National Gene Bank for medicinal and aromatic plants at CSIR-Central Institute of Medicinal
The total genomic DNA of 51 accessions was extracted from the fresh leaf tissue of 3–4 week field grown plants using the DNeasy Plant 2
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Mini Kit (QIAGEN) following manufacturer’s instructions. The quality and quantity of the DNA were checked by agarose gel electrophoresis and spectrometrically using Nanodrop ND1000 (JH Bio). DNA samples were diluted to a final concentration of 25−30 ng /μl before PCR amplification.
Table 1 ANOVA for twelve characters of Opium poppy. S. No.
2.5. Genotyping by SCoT markers
1 2 3 4 5 6 7 8 9 10 11 12
Thirty six SCoT primers were synthesized as suggested by Collard and Mackill (2009). PCR were carried out in a 20 μl reaction volume containing 25−30 ng of template DNA,10X PCR buffer, 2.5 mM of each dNTP’s, 10 pmol of primer and 3U of Taq DNA polymerase (GeNei). Additionally, three SCoT primers were used in different combinations as double and triple SCoT to increase the polymorphism among the accessions. The PCR amplifications were performed on a thermal cycler (ProFlex, Applied Biosystems) programmed for initial denaturation at 94 °C for 3 min; 40 cycles of denaturation at 94 °C for 1 min, annealing at 50 °C (for all primers) for 1 min and extension at 72 °C for 2 min; final extension at 72 °C for 5 min and 12 °C forever. The amplified PCR products were separated on a 1.5 % agarose gel, using a horizontal gel electrophoresis unit for 2 h and documented under UV light using GelDoc-It imager (UVP, Analytik Jena, Germany). The molecular size of the amplified products was determined against a 100 bp −3 kb DNA Ladder (GeNei). The presence and absence of the bands were scored and similarity indices were generated using Jaccard’s coefficient. A dendogram was constructed based on similarity matrix by UPGMA (unweighted pairgroup method of arithmetic averages) method in NTSYS software. Cophenetic correlation ratio was also estimated to find the good of fit of dendogram to that of data matrix.
Characters
Plant Height No. of capsules per plant Days to 50% flowering Pedicel length Capsule Index Husk weight per capsule Seed yield per capsule Disease severity index Morphine content Codeine content Thebaine Content Papaverine content
MEAN SUM OF SQUARES Replication (d.f. = 2)
Treatment (d.f. = 50)
Error (d.f. = 100)
84.73 0.253 0.53 1.29 0.031 7.72 0.41 0.36 0.002 0.002 0.0002 0.00001
133.60** 1.13** 47.12** 14.01** 0.48** 10.11** 5.53** 551.26** 0.007** 0.009** 0.005** 0.005**
37.53 0.092 3.01 6.78 0.006 0.25 0.38 2.50 0.00004 0.0001 0.00003 0.00001
** Significant at 1% level of significance.
variability in the germplasm for all the characters. Also the morphine content in the peduncle ranged between 0.001–0.24% and in capsule between 0.02–1.05 %. A study by Saikia and Gupta (2014) on 108 accessions of opium poppy for five morphometric traits revealed considerable genetic variability among the accessions. In a study by Brezinova et al. (2009), the genetic diversity of 404 lines of poppy was studied based on their morphological characters. Dittbrenner et al. (2009) studied 35 morphological and agronomic traits for 300 accessions of opium poppy and reported high significant correlation between alkaloid content and morphological traits. In accordance with these studies we too found considerable phenotypic variations.
2.6. Statistical analysis
3.2. Clustering of accessions
The Statistical Software (version 4.0), available in the Division of Genetics and Plant Breeding of the CSIR–CIMAP was used to analyse the replicated two years pooled mean data for ANOVA and D2 analysis as prescribed by Singh and Chaudhary (1979). Methods described by Mahalanobis (1936) were followed to study the genetic diversity using the D2 analysis. The grouping of the genotypes into clusters was done following the Tocher’s method (Rao, 1952).
The existing variability among the 51 accessions was evaluated using the analysis of variance (ANOVA), which revealed high level of statistically significant variation (p < 0.01) for all the twelve characters studied (Table 1). A total of 1275 pairwise combinations of all 51 accessions {calculated by the formula, n (n-1)/2, where n is the number of accessions} were obtained by D2 analysis. The maximum and minimum D2 values were 13915.96 and 53.24, respectively. The vast difference between the maximum and the minimum D2 value showed that there was adequate diversity present among the accessions. The 51 accessions were grouped into nine clusters (Fig. 1, Supplementary Table 3) with 69% diversity based on the λ1 and λ2 values. The largest cluster was Cluster I with 18 accessions followed Cluster II (14 accessions), cluster III (11 accessions) and 2 accessions each in clusters IV and V. Cluster VI, VII, VIII, and IX contained 1 accession each, revealing its uniqueness and maximum genetic diversity. Earlier, studies by Singh et al. (2004) on genetic divergence in 101 germplasm lines for seed and opium yield per plant using multivariate and canonical analysis grouped them into 13 clusters (68% lines were genetically similar and grouped into 6 clusters and 32% lines formed the rest 7 clusters). Singh et al. (2017) studied the genetic divergence among 28 germplasm lines for 14 morpho-metric traits and reported a total of 6 clusters grouping the accessions. In another study by Shukla et al. (2018) on 55 accessions of opium poppy by D2 analysis, the accessions were grouped into seven clusters. Shukla et al. (2010) studied the diversity in alkaloid profile of 122 poppy accessions by Mahalanobis D2 analysis. Based on the relationship between the alkaloid content in raw opium, the accessions were grouped into 11 clusters. The diversity of alkaloid revealed very low correlation between content of individual alkaloid. The inter- and intra-cluster distances are represented in the Fig. 2 and Supplementary Table 4. The intra-cluster distance depicts the variability present within a cluster. The intra cluster distances in
3. Results and discussion 3.1. Morpho-chemotypic variability in genetic stock Morphological variations recorded for the 12 characters among the germplasm accessions are enlisted in Supplementary Table 2. Good range of variations were observed in several characters such as plant height {85–116 cm (max. in CIM 142 and least in CIM 139)}; number of capsules per plant {1–3.99 (max. in CIM 120 and least in CIM 123)}; husk weight per capsule {1.48–7.84 g (max. in CIM 123 and least in CIM 112)} and seed yield per capsule (0.44–6.22 g) (Supplementary Fig. 1). Based on 50% flowering data, variety Sapna and yellow mutant (YM) were found to be the early and late maturing lines among the germplasm accessions, respectively. The disease severity index revealed that a total of 16 accessions were resistant, 25 tolerant and 10 susceptible to downy mildew disease. None of the accessions were found to be either highly susceptible or highly resistant. The alkaloid content variations are depicted in Supplementary Fig. 2. Similar kind of variations has also been reported by Gumuscu et al. (2008) during the evaluation of alkaloids in poppy husk (CPS) of 99 lines {morphine (0.11–1.14%), thebaine (0.005–0.134%), codeine (0.005–0.27%), papaverine (0.001–0.44%) and noscapine (0.006–0.418%)}. Bajpai et al. (2000) did her study on 208 Indian and 2 Thai accessions of P. somniferum for variations in 17 morphological characters and reported high 3
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Fig. 1. Spatial distribution of 51 genetic stocks of opium poppy in λ1-λ2 chart. The numbers 1-51 represents the 51 accessions taken in the study (serial no. 1-51 as mentioned in Supplementary Table 1).
maximum towards the diversity, followed by thebaine content (14.56%), papaverine content (14.06%), number of capsules per plant (12.79%), and husk weight per capsule (9.40%). The percent contribution and the rank of all the traits are represented in the Table 2. Shukla et al. (2018) in their study on opium poppy, reported codeine content as the highest contributor (32.86%) followed by papaverine content (10.41%). In future, these characters contributing towards genetic divergence can be given due value during the selection of accessions for further breeding programmes.
decreasing order were found in clusters I (21.52), V (21.16), II (18.84), III (17.15), and IV (14.66) revealing the fact that the accessions in cluster I were relatively more diverse whereas those in cluster IV were least. The inter-cluster distance reveals the divergence of one cluster from the other. The inter cluster distances were greater than the intra cluster distance. The largest inter cluster distance was between cluster VII and cluster IX (117.97), followed by cluster VI and IX (103.20), cluster I and IX (102.78) and Cluster III and IX (100.98). The cluster means values shed light on the desirability of accessions in a particular cluster for genetic improvement of the trait(s). The cluster mean for plant height {maximum - cluster IX (110.27); minimum - cluster V (88.37), number of capsules per plant {maximum cluster VIII (3.90); minimum - cluster VII (1.18)}, days to 50% flowering {maximum - cluster IX (112.33); minimum - cluster VI (104.0)}, pedicel length {maximum - cluster IV (24.83); minimum - cluster VII (21.47)}, capsule index {maximum - cluster IV (2.01); minimum cluster VI (1.19)}, husk weight per capsule {maximum - cluster VIII (7.04); minimum - cluster IX (2.31)}, seed yield per capsule {maximum - cluster IV (5.52); minimum - cluster IX (1.21), disease severity index {maximum - cluster VI (68.89); minimum - cluster IX (24.10)}, morphine content {maximum - cluster VI and VII (0.26); minimum - cluster IX (0.10)}, codeine content {maximum - cluster VII (0.23) and minimum - cluster III (0.08)}, thebaine content {maximum - cluster VII (0.23); minimum - cluster IX (0)}, papaverine content {maximum cluster IX (0.26); minimum - cluster VII (0)} are presented in the Supplementary Table 5. As can be seen from the above data, none of the clusters had accessions with all the desirable traits for direct selection and exploitation. However, cluster IX was categorized by desirable traits like papaverine content and resistance towards diseases. Similarly, cluster IV is categorized by traits like high pedicel length, capsule index and seed yield per capsule, whereas the other clusters were high in one or other trait. Therefore, for the effective improvement of individual trait, accessions need to be selected from the corresponding clusters.
3.4. Desirable accessions for future breeding programmes Though all the characters taken for study are of agronomic importance but certain traits directly contribute towards the economic importance of the plant such as: (i) Number of capsules per plant: The accession CIM 120 had the highest number of capsules per plant (3.99). Since the number of capsules directly contributes towards the husk yield leading to high alkaloid, the accession CIM 120 may be exploited while making selections for this trait. (ii) Husk weight per capsule: This is also an important trait as the husk weight contributes towards the total alkaloid content of the plant. The accession CIM 123 possessed around 7.84 g of husk weight which was highest among all the accessions. However, the seed yield of this accession was very less (2.85 g) which is an undesirable trait. (iii) Seed yield per capsule: Poppy seeds are used for culinary purposes and so seed yield is an economically important trait during selections for edible lines. Accession CIM 131 contained around 6.22 g of seeds per capsule followed by accession CIM 142 (6.02 g). (iv) Disease severity index (DSI): Downy mildew is a major disease that causes huge losses in the yield in opium poppy. Rakshit is a downy mildew resistant variety released by CSIR-CIMAP. In our study, 16 accessions were found to be downy mildew resistant, 25 accessions were tolerant while 10 accessions were susceptible. None of the accessions ranged in the category of highly resistant and highly susceptible lines. Thus, the resistant accessions can be given due importance while selections for further breeding programmes. The variety Rakshit and the mutant Pps-1 were in the category of resistant lines.
3.3. Maximum contributing trait The selection and choice of parents largely depends upon the contribution of different traits towards the genetic divergence. Among the twelve characters studied, seed yield per capsule (17.30%) contributed 4
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Fig. 2. Cluster diagram with their genetic distances of 51 genetic stocks of opium poppy germplasm.
(v) Alkaloid content: Lines with high alkaloid content are pharmaceutically important. Rakshit can be selected for morphine and codeine content (0.37%; 0.26%), CIM 110 for thebaine content (0.23%) and CIM 377 (0.26%) for papaverine content.
Table 2 Character contribution (%) towards total divergence and rank of the twelve traits in Opium poppy. Characters
Character Contribution %
Rank
Plant height Number of capsules per plant Days to 50% flowering Pedicel length Capsule Index Husk weight per capsule Seed yield per capsule Disease severity index Morphine content Codeine content Thebaine content Papaverine content
5.03 12.79 1.33 8.86 4.20 9.40 17.30 2.98 2.51 6.98 14.56 14.06
8th 4th 12th 6th 9th 5th 1st 10th 11th 7th 2nd 3rd
Identification of genotypes as parents for hybridization from different clusters might lead to segregants with combination of superior alleles. Genotypes namely, CIM 120, CIM 123, CIM 131, CIM 142, Rakshit and Pps-1 may be considered as elite lines and crosses using these lines are likely to result in desirable segregants for yield and related traits. For culinary purpose, high seed yield can be achieved through crossing CIM 120 and CIM 131 which may act as donors for high number of capsules per plant and seed yield per capsule and simultaneously are genetically diverse belonging to cluster VIII and IV, respectively. Similarly for pharmaceutical use, diverse lines CIM 110 (rich in thebaine content) and CIM 377 (rich in papaverine content) can
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Table 3 Primer name, sequence, molecular size range, bands number and percentage of polymorphism as detected by SCoT markers. Molecular marker technique
Primer name
Primer sequence (5´→ 3´)
Molecular size range (bp)
TAB
PB
P (%)
Single SCoT
SCoT SCoT SCoT SCoT SCoT SCoT + SCoT SCoT + SCoT SCoT + SCoT
CAACAATGGCTACCACCG CAACAATGGCTACCACGG ACGACATGGCGACCGCGA ACCATGGCTACCACCGCG CATGGCTACCACCGGCCC CAACAATGGCTACCACCG ACGACATGGCGACCGCGA
700–1050 950–1300 150–2100 450–1300 200–1200 80–1100
2 2 7 6 6 7
1 1 7 5 1 6
50 50 100 83.33 16.66 85.71
CAACAATGGCTACCACCG ACCATGGCTACCACCGCG
150–1300
6
4
66.66
ACGACATGGCGACCGCGA ACCATGGCTACCACCGCG
220–1100
6
3
50
Double SCoT Double SCoT Double SCoT
3 7 15 20 35 3 15 3 20 15 20
TAB = Total number of amplified bands, PB = number of polymorphic bands, P (%) = polymorphism percentage.
between 0.500 – 0.970 (Supplementary Table 6) which was used for clustering the accessions by UPGMA method (Fig. 3). Two major clusters were formed. These major clusters were further divided into several sub-clusters. Among the cultivars, Rakshit showed maximum similarity with Sapna (76%) followed by Vivek (74%). Rakshit and Pps-1 clustered together in same cluster in both SCoT marker and morphological clustering. The three mutants Pps-1, YM and OM showed 76%, 73% and 68% similarity with Rakshit, respectively. Sapna and Vivek showed 70% genetic similarity with each other. These cultivars showed moderate genetic similarity with the three mutants. The co-phenetic correlation coefficient (r) was found to be 0.921, suggesting a good fit of the tree with that of the data. We initially screened our germplasm using Inter simple sequence repeats markers (ISSR, Supplementary Fig. 3), but in contrast to earlier reports we did not observe any polymorphism (data not shown). This was very surprising fact considering the robustness, utility, and widespread use of ISSR markers for genetic diversity studies. The failure of not detecting polymorphism with ISSR markers (which are largely a part of non-coding region) made us shift to DNA markers targeting genic regions (SCoT markers) to genotype population which was observed to be phenotypically diverse. This further proves the utility of DNA markers targeting coding regions in genotyping phenotypically variable germplasm having limited genetic variation. As seen from the Figs. 1 and 3, the morphological clustering was found to show no correlation with the molecular clustering pattern. There are several studies where weak or no correlation between molecular marker analysis (AFLP, RAPD, SSR) and geographical location of cultivars or the morphological/ agronomic traits were recorded (Kölliker et al., 2001; Zhang et al., 2010). Zhang et al. (2010) observed no correlation between leaf size and molecular markers (SSR and RAPD) diversity patterns in white clover. The evident disparity between molecular and morphological clustering patterns is due to the fact that the molecular markers have a larger representation of the genome than morphological markers which are controlled by a relatively few specific loci in the genome (Bruschi et al., 2003). The SCoT markers may not have necessarily screened those loci of the genome that determine the morphological traits taken in the study. Also, the influence of the environment is more pronounced than the molecular markers. Thus, clustering pattern based on morphological traits and molecular markers may not be correlated in every case. The genetic diversity based on morphological traits (∼69%) was higher than those of molecular markers (33%) in our study, a fact that was also reported by Zhang et al. (2010) which implies that the genetic base, although narrow, is capable of manifesting into much wider morphological variations. One of the reasons for low genetic diversity may be the fact that this study comprised of only Indian accessions and lacked any exotic collection(s). The
be hybridized with Rakshit to get segregating generations rich in pharmaceutically important alkaloids. In all cases Rakshit may be used to transfer disease resistance in future breeding programmes. 3.5. Molecular diversity in the opium poppy germplasm Out of the 36 primers tested, five of them showed polymorphism (SCoT 3, SCoT 7, SCoT 15, SCoT 20, SCoT 35) (Supplementary Fig. 2). A total of 23 bands were generated by the five primers when used singly, out of which 15 showed polymorphism. When used in combination, a total of 19 bands were generated, among which 13 showed polymorphism. Maximum alleles (7) were amplified with SCoT 15 and minimum (2) were generated each with SCoT 3 and 7, respectively. The amplified products ranged from 200 to 2100 bp size (Table 3). Aboulila and Mansour (2017) reported an increase in polymorphism (89.47%; 94.4%) in barley when using combination of two SCoT and three SCoT primers, respectively. Interestingly, in our study we observed decrease in polymorphism while multiplexing SCoT markers. SCoT 15 individually produced 100% polymorphism but when used in combination with other SCoT primers produced just 85.71% (SCoT 3 and 15) and 50% (SCoT 20 and SCoT 15) polymorphism, respectively. Similarly, a combination of SCoT 3 and SCoT 20 produced 66.66% polymorphism which was in contrast to 83.33% polymorphism when SCoT 20 was used singly. On closer analysis of the amplicons resolved on agarose gels we found that the markers when used singly produced higher molecular weight products than those when used in combination. For example, the range of products with SCoT 15 varied from 2100 to 400 bp and that of SCoT 20 varied from 1750-600. The highest molecular weight amplicons in SCoT 15 (∼2100 bp) and SCoT 20 (∼1750 bp) accounted for 100% and 83.33% polymorphism respectively when used singly in the reaction. However, the reaction kinetics during multiplexing of SCoT primers, preferred the exponential amplification of lower molecular weight products [(1050-50 bp in case of SCoT 3 + 15) and 1300-250 bp in case of SCoT 3 + 20)]. In both of these PCR profiles the highest molecular weight band was absent accounting for drop in polymorphism percent when used in combination (85% when SCoT 3 + 15 were used and 66% when SCoT 3 + 20 were used). The multiplexing of SCoT primers probably led to binding of primers to sense and anti-sense strands of DNA at close proximities than when used singly. It would be interesting to see the results of similar studies with double and triple SCoT primers in other species by other researchers. In our genotyping work, we used one accession of another species, P. rhoeas as an outgroup showing ∼10% similarity to Papaver somniferum accessions. All the P. somniferum accessions when clustered showed similarity of ∼ 67%. The Jaccard’s similarity indices ranged 6
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Fig. 3. Clustering of opium poppy accessions based on SCoT marker analysis.
Central Instrumentation Facility, CSIR–CIMAP, Lucknow for HPLC analysis of the samples and Director, CSIR–CIMAP for providing all the required facilities and encouragement are duly acknowledged. Dr. Sougata Sarkar is acknowledged for his inputs in Figs. 1 and 2. The authors are thankful to Dr. Mohammed Talha for making Supplementary Fig. 1. This manuscript is approved as original research article by the publication committee of CSIR-CIMAP (CIMAP Publication No. CIMAP/PUB/2019/SEP/72).
role of other possible factors such as genetic drift as a result of reduced levels of gene flow due to restricted cultivation/ breeding programmes leading to limited genetic diversity cannot be denied. This situation can further aggravate if such populations have been founded by limited number of individuals (founder effect). 4. Conclusions Study of genetic diversity paves a path for the selection of important accessions which can be exploited for further breeding programmes. The promising accessions with specific traits can be used as parents for hybridization programs. In our study, we studied the morphological variability among the opium poppy germplasm where the diversity was found to be 69%. Accession CIM 120 had the highest number of capsules per plant (∼3.99) directly contributing towards the husk weight. Accession CIM 123 had the highest husk weight (7.84 g) contributing towards the alkaloid content of the plant. Accession CIM 131 contained around 6.22 g seeds per capsule which is an important trait. CIM 110 and CIM 377 can be selected for high thebaine and papaverine content, respectively. The SCoT markers were used to access the molecular diversity which was found to be 33% revealing a narrow genetic base in the germplasm because of genetically close accessions and also no exotic collection in the germplasm. However, SCoT markers were able to generate the polymorphism among the accessions at molecular level where ISSR markers had failed. As SCoT markers target regions of the genome that are expressed, so the variability among the accessions as revealed by these markers is indicative of the morphological variations observed among the accessions to some extent.
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AuthorContributions AKG, SG were involved in planning; AS, SG in actual experimentation; KS, NG in chemical analyses by HPLC; AS, AKG, RKL in statistical analyses; and SG, AS, AKG in manuscript preparation. Declaration of Competing Interest None. Acknowledgements This study is a part of the Ph.D work of the first author and Academy of Scientific and Innovative Research is acknowledged for giving an opportunity to carry out the present work. 7
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