Molecular diversity in castor (Ricinus communis L.)

Industrial Crops and Products 66 (2015) 271–281

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Molecular diversity in castor (Ricinus communis L.) Prathap Reddy Kallamadi a,b,∗ , V.P.R. Ganga Rao Nadigatla b,c , Sujatha Mulpuri b a

Department of Biotechnology, Sri Venkateswara University, Tirupati 517 502, India Directorate of Oilseeds Research, Rajendranagar, Hyderabad 500 030, India c International Crops Research Institute for the Semi-Arid Tropics, Nairobi 39063-06623, Kenya b

a r t i c l e

i n f o

Article history: Received 13 October 2014 Received in revised form 27 December 2014 Accepted 29 December 2014 Keywords: Castor Genetic diversity ISSR Molecular markers RAPD SCoT

a b s t r a c t Castor (Ricinus communis L.), a non-edible oilseed crop of the tropics assumes commercial importance due to its great utilization value in industry, medicine and agriculture. The present investigation has been undertaken to assess the extent of genetic diversity in 31 accessions of castor representing seven geographic areas in the world using RAPD (random amplified polymorphic DNA), ISSR (inter simple sequence repeat) and SCoT (start codon targeted polymorphism) primers. Among the three marker systems, RAPD had revealed highest average percentage of polymorphism (54) while SCoT markers disclosed the lowest average percentage of polymorphism (21). The average PIC (polymorphic information content) values ranged from 0.20 (ISSR) to 0.24 (RAPD and SCoT). The average marker index for both RAPD and SCoT markers was same (0.07) and it was comparatively low for ISSR markers (0.05). The average resolving power was maximum for ISSR (4.79) compared to that of RAPD and SCoT primers. Out of 157 polymorphic markers, 30 markers resulted in accession specific bands. The accession, RG-1171 had more number of accession specific bands with all the three marker systems, and the RAPD primer OPL-9 produced maximum number of accession specific bands. Combined data of the 3 marker systems classified the accessions into three major clusters, cluster I included 4 accessions each from USA and India; cluster II was large and included 10 accessions from Nigeria, 3 accessions from USA, 2 accessions each from Kenya, India and Egypt, 1 accession each from Brazil and USSR; cluster III included two accessions from India. Use of three dominant marker systems targeting different regions of the genome (random, repeat regions and functional regions of the gene) on castor germplasm from seven geographical regions indicated hither to modest level of genetic variability but led to identification of accessions with several unique bands which could be further investigated for exploitation in the breeding programmes. © 2014 Elsevier B.V. All rights reserved.

1. Introduction Castor bean (Ricinus communis L., 2n = 2x = 20, Euphorbiaceae), is an important non-edible oilseed crop predominantly cultivated in the arid and semi-arid regions of the world with wide use in industrial and agricultural applications. Castor seeds contain around 50–55% oil which is rich in an unusual hydroxy fatty acid, ricinoleic acid which constitutes about 80–90% of the total fatty acids. Owing to its unique chemical and physical properties, the oil from castor seed serves as a renewable source of raw material for varied industrial applications, such as, the manufacture of polymers, surface coatings, lubricants for air crafts, cosmetics, and in the recent past

∗ Corresponding author at: Crop Improvement Section, Indian Institute of Oilseeds Research (Formerly Directorate of Oilseeds Research), Rajendranagar, Hyderabad 500 030, India. Tel.: +91 7702879878; fax: +91 402401796. E-mail addresses: [email protected] (P.R. Kallamadi), [email protected] (V.P.R.G.R. Nadigatla), [email protected] (S. Mulpuri). http://dx.doi.org/10.1016/j.indcrop.2014.12.061 0926-6690/© 2014 Elsevier B.V. All rights reserved.

its use in production of biodiesel is explored (Jeong and Park, 2009; Mutlu and Meier, 2010). The world production of castor seed is around an average of 18.54 lakh tonnes (FAOSTAT, 2013). The major castor producing countries are India, China, Mozambique, Thailand, Brazil, Paraguay, Ethiopia, with India accounting for around 88.6% of the share in production with a production of 16.44 lakhs tonnes (FAOSTAT, 2013) making it the largest producer and exporter of castor. Castor is believed to be a native of tropical Africa as well as India (CSIR, 1972). Castor belongs to a monotypic genus but considered to be a very variable species. It has been divided into a number of varieties and forms based on the variation in morphological features (Weiss, 1971). Some workers have even considered them as distinct species or sub-species based on ecogeographical grouping. Despite the existence of several forms with many well marked characters, they are so thoroughly connected by intermediate forms and hybridization, hence, is not considered as a separate species (CSIR, 1972). Genetic improvement of the crop for yield and yield contributing traits was achieved to a great extent through mutation

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breeding (Kulkarni and Ankineedu, 1966; Ankineedu et al., 1968; Kulkarni and Ramanamurthy, 1977; Lavanya et al., 2003). Wilt resistant pistillate lines from VP-1 and double or triple bloom types from DPC-9 were developed by gamma rays (Lavanya et al., 2008). Early maturing populations were developed by crossing extra early accessions (Anjani, 2010). Brigham, a genotype with 10-fold reduction in ricin was developed by recurrent selection (Auld et al., 2001, 2003). The frequency of pistillate castor plants was increased by employing mass selection with self pollination (Bertozzo et al., 2011). Hybridization involving single, double, or triple crosses was effective for combining the different traits for improvement of castor yield (Severino et al., 2012). Toppa (2011) developed 12 castor cryptic hybrids by a new method of breeding. The hybrid vigor in castor depends mainly on the genetic diversity and individual combining ability of the parents (Lavanya and Chandramohan, 2003; Golakia et al., 2004; Ramana et al., 2005; Lavanya et al., 2006). According to Allard et al. (1991), germplasm collections constitute one of the world’s most readily available sources of plant genetic material. An understanding of the extent of genetic diversity is critical for the success of a breeding program. Traditional methods using morphological characteristics for establishment of genetic diversity and relationships among accessions are largely unsuccessful due to the strong influence of the environment. Existing morphological variation observed in castor bean does not reflect a high genetic diversity for exploitation in breeding programmes for yield and its contributing traits (Vasconcelos et al., 2012). Hence, selection based on genetic information using neutral molecular markers is essential, as it is more reliable and consistent. Regardless of the recent publication of the castor bean genome (Chan et al., 2010), little is known about the actual genetic diversity of castor (Vasconcelos et al., 2012) and very few studies are available. Different molecular marker systems like AFLP and SSR (Allan et al., 2008; Pecina-Quintero et al., 2013), RAPD and ISSR (Gajera et al., 2010; Vasconcelos et al., 2012; Wang et al., 2013; Vivodik et al., 2014), were used for estimating the extent of diversity among castor germplasm accessions. All these studies revealed varying and low levels of molecular genetic diversity depending on the type of molecular markers employed and the population used. A set of novel and polymorphic SSRs and EST-SSRs were developed and tested for characterization of castor (Qiu et al., 2010; Bajay et al., 2011; Pranavi et al., 2011; Seo et al., 2011; Vasconcelos et al., 2012). A lower level of genetic diversity was reported among samples using SNP (Foster et al., 2010) and organelle genome sequencing (Rivarola et al., 2011). Allan et al. (2008) reported low level of genetic diversity among 41 genotypes from five continents which was a result of using few markers (3 AFLP and 9 SSR). Gajera et al. (2010) reported high level of variability in 22 genotypes from India (21 genotypes from Gujarat region and 1 genotype from Andhra Pradesh) with 30 RAPD markers and a low level of variability with 5 ISSR primers. The contradicting observations with the 2 marker systems on the same genotypes was a result of utilization of few markers and differences in the targeting regions in the genome by the marker systems or due to sampling from mostly the same region. Vasconcelos et al. (2012) tested only 3 genotypes with 60 ISSR primers. The utilization of SSRs, EST-SSRs, AFLP, SNP and organelle sequencing are neither simple nor cost effective, which are the main limitations of small laboratories and breeding programs interested in employing DNA-markers for estimation of diversity in the breeding material. Hence, we tried to use 3 different multi-locus dominant marker systems that target different regions of the genome viz. RAPD (specific genes or regions monomorphic for previously characterized markers or to regions sparsely populated with markers), ISSR (inter-simple sequence repeat sequences are abundant, dispersed throughout the genome and highly polymorphic) and SCoT (SCoT is based on the short conserved region in plant genes surrounding the ATG translation start

codon). The amplification products could be run on agarose gels instead of polyacrylamide gels for used SSRs, EST-SSRs, AFLP and hybridization-based methods, enzyme based methods, other postamplification methods based on physical properties of DNA for SNP markers. DNA-fingerprinting analysis of germplasm using multi locus marker systems generates lot of information, which allows a reliable differentiation among cultivars (Tanya et al., 2011). AFLP, ISSR, and RAPD are among the widely used marker systems for assessment of genetic diversity due to their low cost of development, the possibility of generating a large amount of informative marker bands in a short time without a requirement of prior knowledge of the genome (Weising et al., 2005). In the recent past, a novel marker system termed as start codon targeted marker (SCoT) based on the short conserved region flanking the start codon (ATG) in plant genes has been developed (Collard and Mackill, 2009). SCoT is technically simple and employs longer primers (18-mer) producing high polymorphism which is reproducible. It is a dominant (co-dominant) marker system, for which prior sequence information is not a prerequisite and the polymorphism can be correlated to functional genes and their corresponding traits (Sujatha et al., 2013). Use of SCoT markers in diversity analysis and diagnostic fingerprinting was successfully demonstrated in peanut (Xiong et al., 2011), grape (Guo et al., 2012), potato (Gorji et al., 2011), Cicer (Amirmoradi et al., 2012), mango (Luo et al., 2012), chick pea (Pakseresht et al., 2013), dendrobium (Bhattachrayya et al., 2013), and sugarcane (Que et al., 2014). The objective of the present study was to determine the efficiency and comparative assessment of RAPD, ISSR, and SCoT markers for evaluation of genetic diversity among 31 castor accessions that were selected based on diverse attributes and collected from USA, Nigeria, Kenya, Egypt, Brazil, USSR and India. 2. Materials and methods 2.1. Plant material Thirty one accessions of castor representing germplasm from seven countries (USA, Nigeria, Kenya, Egypt, Brazil, USSR and India) were used in the study (Table 1). The plant material comprised of morphologically diverse accessions with variations in maturity, seed characters and yield from seven geographical locations including parental lines of elite hybrids in India. The seeds of all the accessions were raised during the year 2007 under the same conditions at the research farm of the Directorate of Oilseeds Research, Hyderabad, India. 2.2. DNA extraction The total genomic DNA was extracted from younger leaves of ten plants for each of the castor accessions following the standard CTAB method with minor modifications (Doyle and Doyle, 1990). Five grams of leaf tissue was ground in liquid nitrogen, then homogenized in 20 ml of extraction buffer (2% CTAB, 20 mM EDTA, 2% PVP, 1.4 M NaCl, 100 mM Tris–HCl, pH 8.0 and 1% ␤- mercaptoethanol) and incubated at 65 ◦ C for 1 h. The supernatant was twice extracted with chloroform: isoamylalcohol (24:1 v/v), treated with RNase A (100 ␮g/ml) and incubated at 37 ◦ C for 30 min. The DNA was pelleted with isopropanol, rinsed thrice with 70% alcohol, resultant pellet air dried and resuspended in 200 ␮l of sterile MilliQ water and stored at −20 ◦ C. The DNA concentration was determined electrophoretically using known amount of  DNA as standard. Initially DNA from individual plants was tested with 20 primers each of the RAPD and ISSR primers and as there was no detectable intraaccessional variation, equal concentrations of DNA from all the 10 plants was bulked and subjected to molecular analysis.

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Table 1 Geographical location of castor accessions used in diversity analysis and their special characteristics. Sl. no.

Accession number

Collection number

Source/origin

Special attributes

1 2 3 4 5 6 7 8

RG-102 RG-2443 RG-2444 RG-2451 RG-2452 RG-2674 RG-2677 RG-798

EC-80825 EC-397740 (PI-180335) EC-397741 (PI-176751) EC-397748 (PI-258368) EC-397749 (PI-274772) EC-410739 (PI-192949) EC-410742 (PI-182987) EC-14805

USA USA USA USA USA USA USA Nigeria

9 10 11 12 13 14 15 16 17 18 19 20 21 22

RG-799 RG-801 RG-802 RG-1155 RG-1163 RG-1164 RG-1171 RG-1172 RG-1174 RG-1581 RG-1582 RG-761 RG-792 RG-100

EC-14808 EC-14812-A EC-14815-2-2 EC-14808 (Ex-Tv-1) EC-14811A EC-14811B EC-14810B EC-14805 (KABBA mottled) EC-14816 (KABBA black IC-0433168 IC-0433169 871 5391 EC-63295

Nigeria Nigeria Nigeria Nigeria Nigeria Nigeria Nigeria Nigeria Nigeria Kenya Kenya Egypt Egypt Brazil

23 24

RG-117 VP-1

EC-97707 –

USSR India

25

M-574

–

India

26

DPC-9

IC-296788

India

27

DPC-11

–

India

28

DPC-15

–

India

29

DCS-9

–

India

30

48–1

–

India

31

Kranthi

–

India

Female, green stem, double bloom, spiny capsule Male, very small seed, green stem, double bloom, spiny capsule Female, red stem, single bloom, spiny capsule Male, green stem, single bloom, spiny capsule Male, pink stem, zero bloom, spiny capsule Male, red stem, single bloom, spiny capsule Partially female, red stem, single bloom, spiny capsule Partially female, small capsule size and very small seed, green stem, double bloom, spiny capsule Female, red stem, double bloom, spiny capsule Male, red stem, triple bloom, spiny capsule Partially female, red stem, triple bloom, spiny capsule Male, red stem, double bloom, spiny capsule Male, green stem, single bloom, spiny capsule Female, red stem, triple bloom, spiny capsule Male, large leaf size, very small seed size, red stem, triple bloom, spiny capsule Male, umbrella shape spike, red stem, triple bloom, spiny capsule Male, red stem, triple bloom, spiny capsule Male, pink stem with zero bloom, spiny capsule Male, red stem, single bloom, spiny capsule Male, red stem, double bloom, spiny capsule Male, red stem, triple bloom, spiny capsule Female, condensed internodes distance, deep cup leaf shape, triangle shaped spike, green stem, single bloom, spiny capsule Partially female, green stem, zero bloom, spiny capsule Female parent of Indian hybrids, GAUCH-1, GCH-2, GCH-4 and RCH-1, deep cup leaf shape, green stem, triple bloom, spiny capsule Female parent of Indian hybrid, DCH-519, deep cup leaf shape, green stem, dwarf, triple bloom, spiny capsule Female parent of Indian hybrid, DCH-177, green stem, zero bloom, spiny capsule Female line, resistance to wilt, good combiner for seed yield and oil content, green, double bloom, spiny capsule Female line, red capsule color, red stem, triple bloom, dwarf, papaya leaf, non spiny capsule Resistance to Fusarium wilt, male parent of Indian hybrid DCH-177, dark green capsule color, red stem, double bloom, spiny capsule Resistant to Fusarium wilt, tolerant to Botrytis, saline, drought. Red stem, double bloom, non spiny capsule Moderately tolerant to semilooper, resistant to drought, red stem, double bloom, spiny capsule

PI – Plant introduction, EC – Exotic collection, IC – Indigenous collection.

2.3. RAPD analysis The RAPD analysis was done using 214 decamer arbitrary primers (Operon technologies Inc., USA). The PCR amplification reaction (10 ␮l) consisted of 2.5 ng of DNA, 1x PCR buffer (10 mM Tris, pH 9.0, 50 mM KCl and 1.5 mM MgCl2 ), 100 ␮M of each of the four dNTPs, 0.4 ␮M of RAPD primer and 0.3 U of Taq DNA polymerase (Bangalore Genei, India). PCR amplifications were performed with an initial denaturation at 94 ◦ C for 3 min followed by 45 cycles at 94 ◦ C for 45 s, 36 ◦ C for 30 s and 72 ◦ C for 2 min with a final extension at 72 ◦ C for 7 min. The PCR products were separated on 1.5% agarose gel in 1× TAE buffer by electrophoresis at 100 V for 3 h and visualized with ethidium bromide staining. 2.4. ISSR analysis A total of 100 ISSR markers (UBC primer set No. 9, University of British Columbia, Canada) were tested. The PCR amplification reaction (10 ␮l) consisted of 2.5 ng of DNA, 1× PCR buffer (10 mM Tris, pH 9.0, 50 mM KCl and 1.5 mM MgCl2 ), 200 ␮M of each of the four dNTPs, 0.2 ␮l of 25 mM MgCl2, 0.4 ␮M of ISSR primer and 0.6 U of Taq DNA polymerase (Bangalore Genei, India). PCR amplifications were carried out with an initial denaturation at 94 ◦ C for 4 min followed by 35 cycles at 92 ◦ C for 30 s, 1 min at the annealing temperature (36–60 ◦ C depending on the primer) and 72 ◦ C for 2 min with a final extension at 72 ◦ C for 7 min. The PCR products were

separated on 1.7% agarose gel in 1× TAE buffer by electrophoresis at 100 V for 3 h and visualized with ethidium bromide staining. 2.5. SCoT analysis A total of 36 SCoT primers as described by Collard and Mackill (2009) were tested. The PCR amplifications were done with an initial denaturation at 94 ◦ C for 3 min followed by 35 cycles at 94 ◦ C for 1 min, 50 ◦ C for 1 min and 72 ◦ C for 2 min with a final extension at 72 ◦ C for 5 min. The PCR amplification reaction (10 ␮l) consisted of 15 ng of DNA, 1x PCR buffer (10 mM Tris, pH 9.0, 50 mM KCl and 1.5 mM MgCl2 ), 0.25 mM of each of the four dNTPs, 0.2 ␮l of 25 mM MgCl2, 0.8 ␮M of primer and 0.5 U of Taq DNA polymerase (Bangalore Genei, India). The PCR products were separated on 1.2% agarose gel in 1× TAE buffer by electrophoresis at 100 V for 3 h and visualized with ethidium bromide staining. All the PCR reactions were performed in a GeneAmp 9700 Thermal Cycler (PerkinElmer Applied Biosystems). The PCR amplifications included a negative control (no DNA) to avoid erroneous interpretation. The gel images were recorded using the Alpha Innotech Fluorchem gel documentation system. 2.6. Data analysis Since all the markers used were dominant markers, the presence or absence of bands in each accession was visually scored and set

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in a binary matrix. The number of polymorphic and monomorphic fragments for each primer pair was scored and the monomorphic markers were excluded from the analysis. The binary matrices were read using NTSYS-pc version 2.02i (Rohlf, 1993) with Jaccard’s similarity coefficients (Jaccard, 1908) and estimates of genetic distances for all pair wise comparisons between accessions were determined using Similarity for Qualitative Data (SIMQUAL). Dendrograms based on UPGMA (Unweighted Pair Group Method with Arithmetic Mean) were constructed for the three marker systems. The significance of genetic similarity matrix data generated with RAPD, ISSR and SCoT markers was determined using Mantel test (Mantel, 1967). Principal coordinate analysis was performed and the ordination displayed in both two and three dimensions. The efficiency of each marker for estimation of genetic diversity among accessions and the utility of the markers was measured by the following parameters. The polymorphic information content (PIC) of each marker, which measures the informativeness of the marker was calculated according to Roldán-Ruiz et al. (2000); PICi = 2fi (1 − fi), where PICi is the polymorphism information content of each locus i; fi is the frequency of the amplified fragments and 1 − fi is the frequency of non-amplified fragments. The PIC of each primer was calculated using the average PIC value from all loci of respective primers. Marker index was calculated according to Prevost and Wilkinson (1999), as the product of two functions; DI (diversity index) and EMR (effective multiplex ratio). DI of the primer is defined as 1 − pi 2 , where pi is the frequency of the ith allele. EMR of the primer is defined as “the product of the fraction of polymorphic loci and the number of polymorphic loci for an individual assay” (Milbourne et al., 1997). The band informativeness (I) is estimated as I = 1 − [2 × (0.5 − p)] (Prevost and Wilkinson, 1999), where p is the proportion of the accessions containing the band.  The resolving power of the primer (Rp) was measured as Rp = ib .

3. Results 3.1. RAPD Out of 214 RAPD primers tested, 145 primers produced amplification products of which 122 revealed polymorphic fingerprint patterns (Table 2). Out of a total 788 bands, 434 (54%) were polymorphic with an average of 3.5 polymorphic bands per primer. The total number of bands per amplification varied from 1 and 12 in the molecular size range of 200–3800 bp (Fig. 1(a)). The extent of polymorphism ranged from 10% (OPP-14) to 100% (OPB-1, 4, 13, 15, OPC-9, 13, OPD-7, OPM-17 and OPO-2, 8). The high value of PIC/DI was obtained for the primers OPB-16 and OPR-2 (0.49) and a low value for the primer OPL-1 (0.06) with an average PIC/DI of 0.24 for the RAPD marker system (Table 3). In this study, effective multiplex ratio ranged from 0.10 (OPP-10) to 9.00 (OPO-2) with a mean EMR of 2.33 per primer. The highest marker index was observed for the primer OPB-12 (0.209) and the lowest for the primer OPL-1 (0.003) with an average of 0.070 per primer. The resolving power (RP) values ranged from 0.06 (OPC-12) to 12.94 (OPO-11) with an average of 4.33 for primer. Twenty one RAPD primers yielded accession specific bands (Table 4). Similarity matrix values using Jaccard’s coefficient based on RAPD markers ranged from 0.47 between RG102 (USA) and Kranthi (India) to 0.91 between accessions RG-1174 (Nigeria) and RG-1581 (Kenya); RG-1581 and RG-1582 from Kenya. The 31 accessions were separated out into three clusters based on the UPGMA dendrogram (Fig. 2(a)). Cluster I included accessions RG-102, RG-2443, RG-2444 and RG-2451 from USA and DPC-11, DPC-15, DCS-9, 48–1 from India. Cluster II consisted of all the other accessions except two accessions VP-1 and Kranthi from India which were grouped in cluster III.

Table 6 Characteristics of polymorphic SCoT primers in castor. Primer

TNB

NPB

SCoT-1 SCoT-2 SCoT-6 SCoT-10 SCoT-12 SCoT-14 SCoT-15 SCoT-26 SCoT-28 SCoT-31

8 20 13 9 6 6 8 11 16 11

1 7 3 2 1 2 3 2 1 1

PPB 12 35 23 22 16 33 37 18 6 9

PIC/DI

EMR

MI

RP

0.31 0.21 0.29 0.31 0.45 0.06 0.28 0.06 0.06 0.38

0.12 2.45 0.69 0.44 0.16 0.66 1.12 0.36 0.06 0.09

0.097 0.046 0.089 0.101 0.209 0.003 0.084 0.003 0.003 0.146

0.38 9.73 1.93 1.67 1.29 2.00 4.19 0.12 0.06 0.51

TNB – total number of bands, NPB – number of polymorphic bands, PPB – percentage of polymorphic bands, PIC – polymorphism information content, EMR – effective multiplex ratio, DI – diversity index, MI – marker index, RP – resolving power.

3.2. ISSR Of the 100 ISSR tested primers, 42 primers produced amplification products of which 25 revealed polymorphic fingerprint patterns (Table 5). Out of a total of 206 bands, 76 (37%) were polymorphic with an average of 3.0 polymorphic bands per primer. The total number of bands per amplification varied from 1 to 15 in the molecular size range of 200–3100 bp (Fig. 1(b)). The extent of polymorphism varied from 11% (UBC-888) and 80% (UBC-880). Of the five categories (mono-, di-, tri-, tetra-, penta-) of ISSR primers tested, mononucleotide and tetranucleotide primers failed to produce amplification products and most amplified primers were the di-nucleotide repeat primers. The highest polymorphism was 57, 66 and 80% with di-, tri- and penta-nucleotide primers, respectively, with the penta-nucleotide primer UBC-880 giving maximum polymorphism. The high value of PIC/DI was obtained for the primer UBC-809 (0.49) and a low value for the primer UBC-888 (0.03) with an average PIC/DI of 0.20 for the ISSR marker system. The effective multiplex ratio for ISSR primers ranged from 0.11 (UBC-888) to 4.08 (UBC-808) with a mean EMR of 1.34 per primer. The highest marker index was recorded for the primer UBC-809 (0.209) and the lowest for the primer UBC-888 (0.001) with an average of 0.05 per primer. The resolving power (RP) values ranged from 0.12 (UBC-864) to 16.12 (UBC-888) with an average of 4.79 for primer. Three primers UBC-860, 867, 889 resulted in accession specific bands for RG-2451, RG-1171 and RG-2674 accessions, respectively (Table 4). Similarity matrix values ranged from 0.39 between RG-2443 (USA) and VP-1 (India) to 0.94 between RG-1581and RG-1582 from Kenya. Dendrogram analysis separated the accessions into 2 major clusters, with accessions RG-102, RG-117, RG-1155 and VP-1 grouped in cluster I and the remaining 24 accessions in cluster II. The accession, RG-2443 from USA remained as an outlier (Fig. 2(b)). 3.3. SCoT Of the 36 SCoT primers tested, all primers produced amplification products but only 10 primers resulted in polymorphic fingerprint patterns (Table 6). Out of a total of 108 bands, 23 (21%) were polymorphic with an average of 2.1 polymorphic bands per primer. The total number of bands per primer varied from 5 and 20 in the molecular size range of 100–3000 bp (Fig. 1(c)). The extent of polymorphism varied between 6% (SCoT-28) and 37% (SCoT15). The PIC/DI varied from 0.06 for SCoT-28 to 0.45 for SCoT-12 with an average of 0.24 (Table 3). The mean EMR value across SCoT marker system was 0.61 and ranged from 0.06 (SCoT-28) to 2.45 (SCoT-2). The marker index ranged from 0.003 (SCoT-28) to 0.209 (SCoT-12), with an average of 0.07 per marker system. The resolving power was highest for SCoT-2 (9.73) and the lowest was for SCoT-28 (0.06), with a mean value of 2.19. Two SCoT primers viz., 14 and 26 yielded specific bands for accessions RG-

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1171 and RG-801, respectively (Table 4). The pair wise similarity values of accessions based on Jaccard’s coefficient ranged from 0.41 between RG-2451 (USA) and DCS-9 (India) to 1.0 between RG1155 and RG-1171 from Nigeria. The UPGMA dendrogram based on SCoT markers separated the accessions into two major clusters (Fig. 2(c)). Cluster I consisted of accessions RG-102, RG-2444, RG2443, RG-2451, RG-1582, M-574, RG-792, DPC-9, 48–1, Kranthi and RG-761. Cluster II included accessions RG-2452, RG-2674, RG-2677, RG-1164, RG-1171, RG-798, RG-1174, DPC-11, RG-802, RG-1155, RG-1163, RG-1172, RG-799, RG-801, VP-1, RG-1581 and RG-117. The accessions DPC-15, DCS-9 and RG-100 failed to cluster with others accessions.

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RAPD and SCoT marker systems. RAPD markers exhibited a high level of polymorphism (54%) compared to ISSR (38%) and SCoT (21%) markers. Among the three marker systems, the average PIC ranged from 0.20 (ISSR) to 0.24 (RAPD and SCoT). A relatively low average EMR values were observed with SCoT (0.61) compared to the other two systems but the average marker index remained the same for all three marker systems (Table 3). In total, 30 markers resulted in accession specific bands. The accession RG-1171 had more number of accession specific bands and the primer OPL-9 produced maximum number of accession specific bands.

4. Discussion 3.4. RAPD, ISSR and SCoT The RAPD, ISSR and SCoT data were combined for UPGMA cluster analysis. The 31 accessions were classified into three major clusters, cluster I included 4 accessions each from USA and India. Cluster II included 10 accessions from Nigeria, 3 accessions from USA, 2 accessions each from Kenya, India and Egypt, 1 accession each from Brazil and USSR. Cluster III included two accessions from India (Fig. 3(a)). Mantel test values showed a positive correlation between the three marker types. The correlation coefficient (r) was 0.528 between RAPD and ISSR, 0.071 between ISSR and SCoT, and 0.116 between RAPD and SCoT, which showed goodness of fitness between the marker systems. The PCO analysis based on RAPD, ISSR and SCoT polymorphism grouped the accessions into three clusters (Fig. 3(b) and (c)). Eigen values indicated that the three major axes explain 78.94% of the total variation. The accession RG-102 was in cluster I with all the three marker systems and accessions RG-2443, RG-2444, RG-2451 and 48–1 were grouped in cluster I with both RAPD and SCoT markers. Cluster II included accessions RG-2452, RG-798, RG-2677, RG-1174, RG-1581, RG-801, RG-1172, RG-1163, RG-1164, RG-802, RG-2674, and RG-1171 with all the three marker systems and accessions RG-1582, RG-761, RG-792, RG-100, DPC-9 and M-574 with both RAPD and ISSR marker systems and the accessions RG-799, RG-1155 and RG-117 with both

Understanding the extent of genetic diversity is essential for exploitation of germplasm in castor breeding programs. Assessment of genetic diversity of worldwide castor bean germplasm showed low levels of variability regardless of the marker systems employed (Allan et al., 2008; Foster et al., 2010; Qiu et al., 2010 Rivarola et al., 2011). Castor has extensive morphological diversity for vegetative, reproductive and seed traits but is not corroborated with the genotypic variability. Geographically isolated populations also disclosed limited intra-accessional variability (Allan et al., 2008; Foster et al., 2010; Qiu et al., 2010 Rivarola et al., 2011). The low genetic variation in castor could probably be due to selected cultivation, domestication and long term propagation of few varieties (reviewed by Sujatha et al., 2008). However, use of few markers for evaluating the genetic variation might be the reason for detecting contradictory levels of diversity in castor (Allan et al., 2008; Gajera et al., 2010; Pecina-Quintero et al., 2013; Wang et al., 2013; Vivodik et al., 2014). It also could be due to the type of marker system used in the study i.e. microsatellites that target variation only in repeat region (Allan et al., 2008; Qiu et al., 2010; Bajay et al., 2011; Pranavi et al., 2011; Seo et al., 2011; Sharma and Chauhan, 2011; Vasconcelos et al., 2012), AFLP markers which are very limited in number (Allan et al., 2008; Pecina-Quintero et al., 2013), and SNP markers that are biallelic (Foster et al., 2010). In the present investigation, RAPD, ISSR and SCoT markers targeting different

Table 2 Characteristics of polymorphic RAPD primers in castor. Primer series OPB OPC OPD OPE OPF OPH OPI OPK OPL OPM OPO OPP OPR

Total primers tested 10 13 8 4 7 8 16 4 12 10 14 7 7

TNB

NPB

PPB

PIC/DI

EMR

MI

RP

Range

Mean

Range

Mean

Range

Mean

Range

Mean

Range

Mean

Range

Mean

Range

Mean

3–6 3–10 3–9 3–11 3–11 4–9 2–12 5–12 6–11 3–11 5–10 2–10 3–10

5 5 6 7 7 6 7 8 8 6 8 7 6

1–5 1–9 2–7 2–5 2–9 2–7 1–9 2–8 1–7 1–6 1–9 1–5 1–4

3 3 4 3 4 4 4 5 4 3 4 2 2

33–100 17–100 33–100 29–67 33–83 43–88 20–88 33–88 14–87 33–86 14–100 10–62 20–67

70 60 65 49 61 65 54 57 50 51 51 31 36

0.09–0.37 0.06–0.33 0.16–0.43 0.06–0.39 0.06–0.33 0.19–0.43 0.09–0.47 0.09–0.29 0.06–0.49 0.06–0.38 0.08–0.36 0.17–0.45 0.06–0.49

0.24 0.19 0.26 0.21 0.20 0.31 0.27 0.21 0.23 0.19 0.21 0.30 0.26

0.33–5.00 0.25–8.10 0.33–7.00 0.57–3.12 0.66–7.36 1.00–6.12 0.20–6.75 0.66–6.12 0.14–6.12 0.33–6.00 0.14–8.00 0.10–0.57 0.12–0.66

2.60 2.46 3.03 1.61 2.88 2.88 2.63 3.22 2.08 1.99 2.59 0.74 0.77

0.008–0.245 0.003–0.109 0.025–0.089 0.003–0.154 0.003–0.110 0.039–0.187 0.008–0.225 0.008–0.088 0.003–0.245 0.003–0.145 0.005–0.135 0.030–0.209 0.003–0.245

0.07 0.04 0.07 0.06 0.05 0.10 0.08 0.05 0.07 0.04 0.05 0.10 0.08

1.74–7.22 0.06–8.12 1.54–11.03 2.00–5.03 3.67–10.25 1.41–9.29 0.51–11.93 2.64–9.16 1.93–11.29 0.06–4.77 0.32–12.96 0.19–8.12 0.06–3.54

4.62 4.39 4.82 3.61 5.42 4.48 4.52 5.78 5.82 2.70 4.94 2.27 1.90

TNB – total number of bands, NPB – number of polymorphic bands, PPB – percentage of polymorphic bands, PIC – polymorphism information content, EMR – effective multiplex ratio, DI – diversity index, MI – marker index, RP – resolving power.

Table 3 Comparative analysis of marker characteristics of the three types of markers. Marker system

Average PPB (%)

Average PIC/DI

Average EMR

Average MI

Average RP

RAPD ISSR SCoT

54 38 21

0.24 0.20 0.24

2.33 1.34 0.61

0.07 0.05 0.07

4.33 4.79 2.19

PPB – percentage of polymorphic bands, PIC – polymorphism information content, EMR – effective multiplex ratio, DI – diversity index, MI – marker index, RP – resolving power.

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Table 4 Primers that produced accession specific bands in castor. Sl. no.

Accession

RAPD

1 2 3 4

RG-102 RG-2443 RG-2444 RG-2451

5

RG-2452

6 7 8

RG-2674 RG-2677 RG-798

9 10 11 12 13 14

RG-799 RG-801 RG-802 RG-1155 RG-1163 RG-1164

15

RG-1171

16 17 18 19 20 21 22 23

RG-1172 RG-1174 RG-1581 RG-1582 RG-761 RG-792 RG-100 RG-117

24 25 26 27 28 29 30

VP-1 M-574 DPC-9 DPC-11 DPC-15 DCS-9 48–1

31

Kranthi

OPM-18 – – OPB-17 OPC-1 OPE-15 OPH-3 OPM-18 OPH-15 – OPC-4 OPH-3 – OPD-14 OPO-2 – OPL-11 OPI-13 OPL-9 OPI-16 OPK-12 OPO-9 OPC-16 – – – – – OPH-15 OPF-8 OPO-3 – – – – OPO-9 OPL-9 OPF-7 OPL-9 –

Size of the fragment (Kb)

ISSR

Size of the fragment (Kb)

SCoT

Size of the fragment (Kb)

1.30 – – 0.752.20

– – – UBC-860

– – – 1.30

– – – –

– – – –

1.600.201.26

–

–

–

–

0.60 –

UBC-889 – –

1.60 – –

– – –

– – –

– 0.60 0.70 – 0.50 2.200.95

– – – – – –

– – – – – –

– SCoT-26 – – – –

– 0.50 – – – –

0.600.971.25

UBC-867

1.20

SCoT-14

0.45

1.00 – – – – – 1.37 1.400.87

– – – – – – – –

– – – – – – – –

– – – – – – – –

– – – – – – – –

– – – – 0.97 2.20

– – – – – – –

– – – – – – –

– – – – – – –

– – – – – – –

–

–

–

–

–

0.50

1.20

Some primers gave accession specific bands in 2 or more genotypes (represented in bold letters).

Table 5 Characteristics of polymorphic ISSR primers in castor. Primer

Nucleotiderepeat

UBC-807 UBC-808 UBC-809 UBC-812 UBC-825 UBC-827 UBC-829 UBC-830 UBC-834 UBC-835 UBC-836 UBC-840 UBC-843 UBC-847 UBC-848 UBC-850 UBC-855 UBC-860 UBC-864 UBC-865 UBC-866 UBC-867 UBC-880 UBC-888 UBC-889

didididididididididididididididididitritritritripentadidi-

TNB 9 12 8 7 9 8 8 8 11 3 8 8 10 4 5 15 8 7 8 12 9 6 5 9 9

NPB

PPB

PIC/DI

EMR

MI

RP

4 7 1 4 5 3 3 2 3 1 4 2 4 2 1 4 3 2 1 6 2 4 4 1 3

44 58 12 57 55 37 37 25 27 33 50 25 40 50 20 26 37 28 12 50 22 66 80 11 33

0.17 0.33 0.49 0.25 0.24 0.17 0.14 0.14 0.15 0.43 0.09 0.04 0.29 0.11 0.17 0.27 0.36 0.09 0.12 0.34 0.07 0.22 0.22 0.03 0.11

1.77 4.08 0.12 2.28 2.77 1.12 1.12 0.50 0.81 0.33 2.00 0.50 1.60 1.00 0.20 1.06 1.12 0.57 0.12 3.00 0.44 2.66 3.20 0.11 1.00

0.029 0.110 0.249 0.066 0.060 0.029 0.021 0.021 0.025 0.191 0.008 0.001 0.084 0.014 0.030 0.077 0.136 0.008 0.014 0.121 0.005 0.048 0.050 0.001 0.013

5.41 7.41 1.03 5.87 6.77 5.41 2.06 0.32 5.41 1.35 12.38 14.12 4.25 2.12 0.19 4.83 2.70 1.93 0.12 5.22 3.16 3.29 4.58 16.12 3.74

TNB – total number of bands, NPB – number of polymorphic bands, PPB – percentage of polymorphic bands, PIC – polymorphism information content, EMR – effective multiplex ratio, DI – diversity index, MI – marker index, RP – resolving power.

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277

Fig. 1. (a) Electrophoretic analysis of DNA amplification produced using RAPD primer OPO-15. Lanes designated as M represents  DNA double digest with EcoRI and HindIII restriction enzymes, Nc-negative (no DNA) control, and 1–31 represent the DNA samples of 31 genotypes used in the study as given in Table 1. Arrows indicate polymorphic loci. (b) Electrophoretic analysis of DNA amplification produced using ISSR primer UBC-834. Lanes designated as M represents  DNA double digest with EcoRI and HindIII restriction enzymes, Nc-negative (no DNA) control, and 1–31 represent the DNA samples of 31 genotypes used in the study as given in Table 1. Arrows indicate polymorphic loci. (c) Electrophoretic analysis of DNA amplification produced using SCoT primer SCoT-15. Lanes designated as M represents  DNA double digest with EcoRI and HindIII restriction enzymes, Nc-negative (no DNA) control, and 1–31 represent the DNA samples of 31 genotypes used in the study as given in Table 1. Arrows indicate polymorphic loci.

regions of the genome were employed for assessment of genetic variation in castor accessions obtained from different geographical regions. Keeping in view the limitations with use of limited set of markers, we used a good number of RAPD (214), ISSR (100) and SCoT (36) primers targeting different regions of the genome. RAPD markers exhibited a relatively higher level of polymorphism (54%) as compared to ISSR markers (38%) and SCoT markers (21%). In the present study, SCoT markers were used for characterization of castor germplasm for the first time which indicated a relatively low level of the average percentage of polymorphism as compared

with the other two marker systems. Gorji et al. (2011) also reported a low level of average percentage of polymorphism in potato with SCoT primers as compared to RAPD and ISSR markers. Amirmoradi et al. (2012) and Luo et al. (2011) reported high level of polymorphism in SCoT analysis when compared with that of ISSR primers which might be due to utilization of a small number of primers for evaluation, 10, 18 (SCoT) and 15, 18 (ISSR), respectively. However, in crops like peanut (Xiong et al., 2011), grape (Guo et al., 2012), Cicer (Amirmoradi et al., 2012) and mango (Luo et al., 2012), high polymorphism with SCoT primers has been reported. The low

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Fig. 2. (a) UPGMA dendrogram representing genetic relationships among 31 accessions of castor based on genetic similarity matrix obtained using polymorphic RAPD primers. (b) UPGMA dendrogram representing genetic relationships among 31 accessions of castor based on genetic similarity matrix obtained using polymorphic ISSR primers. (c) UPGMA dendrogram representing genetic relationships among 31 accessions of castor based on genetic similarity matrix obtained using polymorphic SCoT primers.

level of SCoT polymorphism in castor could be due to very low genetic variation in the functional regions of the genome. Nevertheless, accession specific bands with the 2 SCoT primers (SCoT-14, 26) and amplicons specific to certain accessions (Table 4) could be sequenced characterized as reported in the case of Jatropha (Sujatha et al., 2013) to understand the variation in genes as the draft genome sequence is available for castor (Chan et al., 2010). The average marker index which measures the overall efficiency of a marker system was only slightly higher for both RAPD and SCoT markers when compared to ISSR markers. The closest values of the marker index of all three marker systems indicated equal efficiency of all three marker systems for fingerprinting of the germplasm.

The average marker index was low for ISSR system but it was observed that it had the highest average resolving power, which indicates that the two marker characteristics were independent of each other (Prevost and Wilkinson, 1999). The analysis of various marker characteristics showed the ability of the three marker systems to distinguish the genotypes. UPGMA dendrogram of RAPD, ISSR and SCoT displayed similar grouping of accessions with minor deviations. The deviation in the grouping of genotypes with three marker systems could probably be due to variation in their target site in the genome. The lowest similarity values were observed between the genotypes from India and USA with all the (three) marker systems and highest similarity

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279

Fig. 3. (a) UPGMA dendrogram representing genetic relationships among 31 accessions of castor based on genetic similarity matrix obtained using the pooled allelic profile of RAPD + ISSR + SCoT primers. (b) Two-dimensional plot of 31 accessions of castor by principal coordinate analysis using the combined Jaccard’s similarity coefficients from RAPD, ISSR and SCoT analysis. The numbers represent the accession codes as given in Table 1. (c) Three-dimensional plot of 31 accessions of castor by principal coordinate analysis using the combined Jaccard’s similarity coefficients from RAPD, ISSR and SCoT analysis. The numbers represent the accession codes as given in Table 1.

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values were observed among the accessions of Kenya (RAPD and ISSR) and Nigeria (SCoT). The dendrograms of RAPD and pooled RAPD + ISSR + SCoT showed similar grouping which might be due to highest sharing of RAPD polymorphic bands in the pooled data. The UPGMA dendrogram of pooled data classified the 31 accessions into three main clusters. Cluster II is the major cluster with 21 accessions and cluster III with two accessions. The clustering of two and three dimensional ordination was mostly similar with the UPGMA clustering of pooled data. This study indicated similarity values of 51.51 and 46.42 between VP-1 and DCS-9 with RAPD and ISSR markers, respectively. However, Gajera et al. (2010) reported 97.8% similarity coefficient values between accessions VP-1 and DCS-9 with both the RAPD and ISSR markers. The differing values of similarity in both these studies could be due to use of different RAPD and ISSR marker series. The other studies on characterization of castor germplasm using RAPD (Vivodik et al., 2014) and ISSR (Wang et al., 2013) were with different germplasm accessions. The different levels of diversity observed by all three marker systems in the present study could be due to several factors such as., number of markers used, genome coverage and nature of evolutionary mechanism underlying the variation as described by Powell et al. (1996). The present study showed divergence among the Indian elite parental lines and exotic germplasm but the overall level of genetic variation was modest despite the geographical distance. Conventionally morphological descriptors are used for varietal and parental identification. But morphological characters are influenced by environment, epistatic interactions, and pleiotropic effects. Further, employing these characters for identification of variety or parental lines on a large scale is time consuming and often not cost effective. From the past two decades many powerful DNA-based marker techniques were used as alternative methods for addressing these problems. The present study resulted in 30 accession specific markers that could be used as signature profiles for 16 out of the 31 accessions studied. The RAPD markers OPF-7 and OPL-9 produced specific bands for Indian variety and male parental line, 48–1 (Jwala), and can be distinguished from other genotypes, VP-1 and Kranthi. The RAPD marker OPO-9 gave specific band to DPC-15, another important parental line. The RAPD marker OPL-9 resulted in a specific band to distinguish the variety DCS-9, which is also used as a male parent of the hybrid, DCH-177. Amplicons specific to the widely used pistillate line VP-1 were not observed with the tested primers which probably could be due to the inclusion of VP-1 derivatives like M-574 and DPC-9 in the study. A total of 13 exotic accessions had diagnostic bands, which can be used in identifying the accessions using different primers (Table 4). The accession RG-1171 from Nigeria had maximum accession specific bands (five) with all the 3 marker systems. These accession specific bands can be converted to Sequence Characterized Amplified Regions (SCAR) or sequence tagged sites (STS) markers for improving their reliability and reproducibility. Castor is being cultivated predominantly in Asia (India, China, and Thailand), Africa (Mozambique and Ethiopia) and South America (Brazil and Paraguay). It is good to go through the breeding programs and selection history operating in these countries to understand the extent of variability existing in the on-going breeding populations and ex-situ collections available in these regions. In the earlier studies on assessment of the extent of genetic diversity of castor, naturally occurring populations (Wang et al., 2013), land races (Seo et al., 2011) and germplasm maintained in gene banks (Allan et al., 2008; Foster et al., 2010; Pecina-Quintero et al., 2013) were subjected to molecular analysis with the exception of the study of Gajera et al. (2010) wherein parental lines and inbreds used in hybrid development programmes were characterized. In the present study, trait specific elite material from six countries along with parental lines of popular Indian hybrids have been char-

acterized for broadening the genetic base of castor. Studies of Gajera et al. (2010) showed the pistillate line, VP-1 to be the most divergent with 25 polymorphic primers. In our study also, VP-I was found to be genetically distinct with 157 polymorphic primers. VP-1 is a stable pistillate line which is derived from an exotic pistillate line, TSP-10-R (TSP-10-R × J-1 F2) × (JP-5 × 26006) F2 . Presumably, crossing of this exotic line derivative with Indian accessions would have resulted in significant heterosis and led to the development of several hybrids (GAUCH-1, GCH-2, GCH-4, RHC-1, PCH-1), variety (TMV-6), pistillate and inbred lines (M-574, DPC-9, SKP-84, SKI-147, JI-244) (DOR, 2009; Gajera et al., 2010). However, vulnerability of VP-1 to fusarial wilt besides low genetic variability for productivity traits and resistance to major biotic stresses in the cultivar germplasm (Hegde et al., 2003), warrants continued efforts in development of new breeding materials. (whole paragraph has been added) In all 3 dendrograms regardless of the marker type, the parental lines VP-1 and 48–1 were quite distinct and invariably clustered in different groups. Both these genotypes are morphological distinct with absence and presence of anthocyanin coloration in hypocotyls, green versus red stems, triple versus double bloom, deep cup shaped versus flat shaped leaves, condensed versus elongated internodes, convergent versus divergent branching, basal location versus top location of branches, dwarf versus normal plant type, spiny versus non-spiny capsules in VP-1 and 48–1, respectively. These are the parental lines of the hybrid GCH-4, which is released in India during 1986 and despite its cultivation for the past three decades, it continues to be cultivated in the country. Similarly, the parental lines of the hybrid DCH-177 (DPC-9 and DCS-9), which are very distinct in morphological characters showed distinct variation with the three marker systems. This investigation shows that the morphologically diverse germplasm and breeding lines from other coutries are distinct at molecular level as well and could be exploited in the breeding programmes.

5. Conclusion India is the largest producer and exporter of castor in the world and contributes to 88% of world castor production. The development of an indigenous pistillate line, VP-1 followed by few other pistillate and male lines has made a significant contribution to increased production of castor in India via hybrid development (Hegde et al., 2003). It is essential to broaden the genetic base and utilize genotypes that are morphologically, geographically and genetically distinct for exploitation of useful heterosis in castor. The present study investigates on the genetic relation between the elite parental lines of India along with the morphologically diverse exotic germplasm from six countries for capturing new genetic variability, development of heterotic gene pools and avoid genetic vulnerability by using a single source of female line in cultivar development.

Acknowledgements The authors are thankful to Dr. D.M. Hegde, Project Director, Directorate of Oilseeds Research (DOR), Hyderabad, India for extending all the facilities for the work and Dr. C. Lavanya and Dr. K. Anjani, Plant Breeders, DOR, for providing seed material of the parental lines and germplasm. KPR is grateful to the Head, Department of Biotechnology, Sri Venkateswara University, Tirupati for granting permission for doing summer project at DOR.

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References Allan, G., Williams, A., Rabinowicz, P., Chan, A., Ravel, J., Keim, P., 2008. Worldwide genotyping of castor bean germplasm (Ricinus communis L.) using AFLPs and SSRs. Genet. Resour. Crop Evol. 55, 365–378. Allard, R.M., Alvim, P.D.T., Ashri, A., Barton, J.H., 1991. Managing Global Genetic Resources, the U.S. National Plant Germplasm System, Elements of the National Plant Germplasm System. The National Academies Press, Washington DC, pp. 43–86. Amirmoradi, B., Talebi, R., Karami, E., 2012. Comparison of genetic variation and differentiation among annual Cicer species using start codon targeted (SCoT) polymorphism, DAMD-PCR, and ISSR markers. Plant Syst. Evol. 298, 1679–1688. Anjani, K., 2010. Extra-early maturing germplasm for utilization in castor improvement. Ind. Crops Prod. 31, 139–144. Ankineedu, G., Sharma, D., Kulkarni, L.G., 1968. Effect of fast neutrons and gamma rays on castor. Indian J. Genet. Plant Breed. 28, 37–43. Auld, D.L., Pinkerton, S.D., Boroda, E., Lombard, K.A., Murphy, C.K., Kenworthy, K.E., Becker, W.D., Rolfe, R.D., Ghetie, V., 2003. Registration of TTU-LRC castor germplasm with reduced levels of ricin and RCA120 . Crop Sci. 43, 746–747. Auld, D.L., Rolfe, R.D., McKeon, T.A., 2001. Development of castor with reduced toxicity. J. New Seeds 3, 61–69. Bajay, M.M., Zucchi, M.I., Kiihl, T.A., Batista, C.E., Monteiro, M., Pinheiro, J.B., 2011. Development of a novel set of microsatellite markers for castor bean, Ricinus communis (Euphorbiaceae). Amer. J. Bot. 98, 87–89. Bertozzo, F., Lara, A.C.C., Zanotto, M.D., 2011. Genetic improvement of castor bean in order to increase female flowers. Bragantia 70, 271–277. Bhattachrayya, P., Kumaria, S., Kumar, S., Tandon, P., 2013. Start Codon Targeted (SCoT) marker reveals genetic diversity of Dendrobium nobile Lindl., an endangered medicinal orchid species. Gene 529, 21–26. Chan, A.P., Crabtree, J., Zhao, Q., Lorenzi, H., Orvis, J., Puiu, D., Melake-Berhan, A., Jones, K.M., Redman, J., Chen, G., Cahoon, E.B., Gedil, M., Stanke, M., Haas, B.J., Wortman, J.R., Fraser-Liggett, C.M., Ravel, J., Rabinowicz, P.D., 2010. Draft genome sequence of the oilseed species Ricinus communis. Nat. Biotechnol. 28, 951–956. Collard, B.Y., Mackill, D., 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. CSIR, 1972. The Wealth of India, a Dictionary of Indian Raw Material and Industrial Products, Raw Material 9 Rh-So. CSIR, New Delhi India. DOR, 2009. Guidelines for quality seed production in castor. In: Directorate of Oilseeds Research. DOR, Hyderabad, India, pp. 55. Doyle, J.J., Doyle, J.L., 1990. Isolation of plant DNA from fresh tissue. Focus 12, 13–15. Food and Agriculture Organization of United Nations. http://faostat.fao.org 2013. (accessed 09.14.). Foster, J.T., Allan, G.J., Chan, A.P., Rabinowicz, P.D., Ravel, J., Jackson, P.J., Keim, P., 2010. Single nucleotide polymorphisms for assessing genetic diversity in castor bean (Ricinus communis). BMC Plant Biol. 10, 1–11. Gajera, B.B., Kumar, N., Singh, A.S., Punvar, B.S., Ravikiran, R., Subhash, N., Jadeja, G.C., 2010. Assessment of genetic diversity in castor (Ricinus communis L.) using RAPD and ISSR markers. Ind. Crop. Prod. 32, 491–498. Golakia, P.R., Madaria, R.B., Kavani, R.H., Mehta, D.R., 2004. Gene effects, heterosis and inbreeding depression in castor, Ricinus communis L. J. Oilseeds Res. 21, 270–273. Gorji, A., Poczai, P., Polgar, Z., Taller, J., 2011. Efficiency of arbitrarily amplified dominant markers (SCOT, ISSR and RAPD) for diagnostic fingerprinting in tetraploid potato. Amer. J. Pot. Res. 88, 226–237. Guo, D.L., Zhang, J.Y., Liu, C.H., 2012. Genetic diversity in some grape varieties revealed by SCoT analyses. Mol. Biol. Rep. 39, 5307–5313. Hegde, D.M., Sujatha, M., Singh, N.B., 2003. Castor in India, Directorate of Oilseeds Research, Hyderabad, India. Jaccard, P., 1908. Nouvelles recherché sur la distribution florale. Bull. Soc. Vaud. Sci. Nat. 44, 223–270. Jeong, G.T., Park, D.H., 2009. Optimization of biodiesel production from castor oil using response surface methodology. Appl. Biochem. Biotech. 156, 1–11. Kulkarni, L.G., Ankineedu, G., 1966. Isolation of pistillate lines in castor for exploitation of hybrid vigour. Indian J. Genet. Plant Breed. 26, 363–365. Kulkarni, L.G., Ramanamurthy, G.V., 1977. Castor. ICAR, New Delhi. Lavanya, C., Chakrabarthy, S.K., Ramachandran, M., Rao, C.H., Raoof, M.A., 2003. Development of wilt resistant pisitillate lines in castor through mutation breeding. J. Oilseeds Res. 20, 48–50. Lavanya, C., Chandramohan, Y., 2003. Combining ability and heterosis for seed yield and yield components in castor. J. Oilseeds Res. 20, 220–224. Lavanya, C., Murthy, G.S.S., Lakshminarayana, M., 2008. Use of gamma rays for the development of leaf hopper resistant pistillate lines in castor (Ricinus communis L.). In: Proceeding of International Symposium on Induced Mutations in Plants, IAEA, Vienna, Austria. Int. Atomic Energy Agency, Vienna. Lavanya, C., Ramanarao, P.V., Gopinath, V.V., 2006. Studies on combining ability and heterosis in castor hybrids. J. Oilseeds Res. 23, 174–177. Luo, C., He, X.H., Chen, H., Ou, S.J., Gao, M.P., Brown, J.S., Tondo, C.T., Schnell, R.J., 2011. Genetic diversisty of mango cultivars estimated using SCoT and ISSR markers. Biochem. Syst. Ecol. 39, 676–684. Luo, C., He, X.H., Chen, H., Hu, Y., Ou, S.J., 2012. Genetic relationship and diversity of Mangifera indica L.: revealed through SCoT analysis. Genet. Resour. Crop Evol. 59, 1505–1515.

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Mantel, N., 1967. The detection of disease clustering and generalized regression approach. Cancer Res. 27, 209–220. Milbourne, D., Meyer, R., Bradshaw, J., Baird, E., Bonar, N., Provan, J., Powell, W., Waugh, R., 1997. Comparison of PCR-based marker systems for the analysis of genetic relationships in cultivated potato. Mol. Breed. 3, 127–136. Mutlu, H., Meier, M.A.R., 2010. Castor oil as a renewable resource for the chemical industry. Eur. J. Lipid Sci. Technol., http://dx.doi.org/10.1002/ejlt.200900138. Pakseresht, F., Talebi, R., Karami, E., 2013. Comparative assessment of ISSR, DAMD and SCoT markers for evaluation of genetic diversity and conservation of landrace chickpea (Cicer arietinum L.) genotypes collected from north-west of Iran. Physiol. Mol. Biol. Plants 19, 563–574. Powell, W., Morigantem, M., Andre, C., Hanafey, M., Vogel, J., Tingoy, S., Rafalski, A., 1996. The comparasion of RFLP, RAPD, AFLP and SSR (microsatelites) markers for germplasm analysis. Mol. Breed. 2, 225–238. ˜ Pecina-Quintero, P.V., Anaya-López, J.L., Núnez-Colín, C.A., Zamarripa-Colmenero, A., Montes-García, N., Solís-Bonilla, J.L., Aguilar-Rangel, M.R., 2013. Assessing the genetic diversity of castor bean from Chiapas, México using SSR and AFLP markers. Ind. Crops Prod. 41, 134–143. Pranavi, B., Sitaram, G., Yamini, K.N., Dinesh Kumar, V., 2011. Development of EST-SSR markers in castor bean (Ricinus communis L.) and their utilization for genetic purity testing of hybrids. Genome 54, 684–691. Prevost, A., Wilkinson, M.J., 1999. A new system of comparing PCR primers applied to ISSR fingerprinting of potato cultivars. Theor. Appl. Genet. 98, 107–112. Qiu, L., Yang, C., Tian, B., Yang, J.B., Liu, A., 2010. Exploiting EST databases for the development and characterization of EST-SSR markers in castor bean (Ricinus communis L.). BMC Plant Biol. 10, 1–11. Que, Y., Pan, Y., Lu, Y., Yang, C., Yang, Y., Huang, N., Xu, L., 2014. Genetic analysis of diversity within a Chinese local sugarcane germplasm based on start codon targeted polymorphism. BioMed. Res. Intl. 14, 1–10. Ramana, P.V., Lavanya, C., Ratnasree, P., 2005. Combining ability and heterosis studies under rainfed conditions in castor (Ricinus communis L.). Indian J. Genet. Plant Breed. 65, 325–326. Rivarola, M., Foster, J.T., Chan, A.P., Williams, A.L., Rice, D.W., Liu, X., Melake-Berhan, A., Huot Creasy, H., Puiu, D., Rosovitz, M.J., Khouri, H.M., Beckstrom-Sternberg, S.M., Allan, G.J., Keim, P., Ravel, J., Rabinowicz, P.D., 2011. Castor bean organelle genome sequencing and worldwide genetic diversity analysis. PLoS ONE 6, 1–9. Rohlf, F.J., 1993. NT-SYS-pc: Numerical Taxonomy and Multivariate Analysis System, Version 2.11W. Exteer Software, Setauket. Roldán-Ruiz, I., Dendauw, J., Van Bockstaele, E., Depicker, A., De Loose, M., 2000. AFLP markers reveal high polymorphic rates in ryegrasses (Lolium spp.). Mol. Breed. 6, 125–134. Seo, K.I., Lee, G.A., Ma, K.H., Hyun, D.Y., Park, Y.J., Jung, J.W., Lee, S.Y., Gwag, J.G., Kim, C.K., Lee, M.C., 2011. Isolation and characterization of 28 polymorphic SSR loci from castor bean (Ricinus communis L.). J. Crop Sci. Biotechnol. 14, 97–103. Severino, L.S., Auld, D.L., Baldanzi, M., Cândido, M.J.D., Chen, G., Crosby, W., Tan, D., He, X., Lakshmamma, P., Lavanya, C., Machado, O.L.T., Mielke, T., Milani, M., Miller, T.D., Morris, J.B., Morse, S.A., Navas, A.A., Soares, D.J., Sofiatti, V., Wang, M.L., Zanotto, M.D., Zieler, H., 2012. A review on the challenges for increased production of castor. Agron. J. 104, 853–880. Sharma, A., Chauhan, R.S., 2011. Repertoire of SSRs in the castor bean genome and their utilization in genetic diversity analysis in Jatropha curcas. Comp. Funct. Genomics 2011, 1–9. Sujatha, M., Muddanuru, T., Francis, G., 2013. Start codon targeted (SCoT) polymorphism in toxic and non-toxic accessions of Jatropha curcas L. and development of a codominant SCAR marker. Plant Sci. 207, 117–127. Sujatha, M., Reddy, T.P., Mahasi, M.J., 2008. Role of biotechnological interventions in the improvement of castor (Ricinus communis L.) and Jatropha curcas L. Biotech. Adv. 26, 424–435. Tanya, P., Taeprayoon, P., Hadkam, Y., Srinives, P., 2011. Genetic diversity among Jatropha and Jatropha-related species based on ISSR markers. Plant Mol. Biol. Rep. 29, 252–264. Toppa, E.V.B., 2011. Analise Comparativa Da Produtividade De Hibridos De Mamoneira (Ricinus communis L.) Obtidos Por Meio Da Hibridacao Convencionale Do Metodo Dos Hibridos Cripticos. MS diss. Faculdade de Ciencias Agronomicas da UNESP, Botucatu. Vasconcelos, S., Onofre, A.V.C., Milani, M., Benko-Iseppon, A.M., Brasileiro-Vidal, A.C., 2012. Molecular markers to access genetic diversity of castor bean, current status and prospects for breeding purposes. In: Ibrokhim, A. (Ed.), In Plant Breeding. InTech, http://dx.doi.org/10.5772/27144. Vivodik, M., Balazova, Z., Galova, Z., 2014. RAPD analysis of genetic diversity of castor bean. Int. J. Biol. Vet. Agri. Food Eng. 8, 597–600. Wang, C., Li, G.R., Zhang, Z.Y., Peng, M., Yu, S.I., Luo, R., Chen, Y.S., 2013. Genetic diversity of castor bean (Ricinus communis L.) in Northeast China revealed by ISSR markers. Biochem. Syst. Ecol. 51, 301–307. Weising, K., Nybom, H., Wolff, K., Kahl, G., 2005. DNA Fingerprinting in Plants: Principles, Methods, and Applications, second ed. CRC Press, Boca Raton, USA. Weiss, E.A., 1971. Castor, Sesame and Safflower. Leonard Hill, London, chapter11. Xiong, F., Zhong, R., Han, Z., Jiang, J., He, L., Zhuang, W., Tang, R., 2011. Start codon targeted polymorphism for evaluation of functional genetic variation and relationships in cultivated peanut (Arachis hypogaea L.) genotypes. Mol. Biol. Rep. 38, 3487–3494.