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. 2017 Oct 11;23(4):925–931. doi: 10.1007/s12298-017-0472-5

Mining and characterization of EST-SSR markers for Zingiber officinale Roscoe with transferability to other species of Zingiberaceae

Praveen Awasthi 1, Ashish Singh 1, Gulfam Sheikh 1,2, Vidushi Mahajan 1,2, Ajai Prakash Gupta 1, Suphla Gupta 1,2, Yashbir S Bedi 1,2, Sumit G Gandhi 1,2,✉
PMCID: PMC5671454  PMID: 29158639

Abstract

Zingiber officinale is a model spice herb, well known for its medicinal value. It is primarily a vegetatively propagated commercial crop. However, considerable diversity in its morphology, fiber content and chemoprofiles has been reported. The present study explores the utility of EST-derived markers in studying genetic diversity in different accessions of Z. officinale and their cross transferability within the Zingiberaceae family. A total of 38,115 ESTs sequences were assembled to generate 7850 contigs and 10,762 singletons. SSRs were searched in the unigenes and 515 SSR-containing ESTs were identified with a frequency of 1 SSR per 25.21 kb of the genome. These ESTs were also annotated using BLAST2GO. Primers were designed for 349 EST-SSRs and 25 primer pairs were randomly picked for EST SSR study. Out of these, 16 primer pairs could be optimized for amplification in different accessions of Z. officinale as well as other species belonging to Zingiberaceae. GES454, GES466, GES480 and GES486 markers were found to exhibit 100% cross-transferability among different members of Zingiberaceae.

Electronic supplementary material

The online version of this article (doi:10.1007/s12298-017-0472-5) contains supplementary material, which is available to authorized users.

Keywords: Microsatellite, Curcuma, Zingiber zerumbet, Hedychium spicatum, Ginger

Introduction

Zingiber officinale Roscoe (Zingiberaceae) is a perennial plant. It is native to tropical climates of India, Malaysia, Australia, China, Brazil, United States and several other parts of the world (Langner et al. 1998). Rhizome of Z. officinale, commonly called as ginger, is generally consumed as a spice for its flavor enhancing effects. Gingerols, shogaols, paradols and zingerone are the main phytoconstituents responsible for its pungency and flavor (Pour et al. 2014). Ginger is also an age old medicine used for its wide array of pharmacological activities. It has been reported to have carminative, gastroprotective, antiemetic, antitussive, antipyretic, spasmolytic, analgesic and peripheral circulatory stimulant effects (Suekawa et al. 1984; Ghosh et al. 2011; Marx et al. 2013; Haniadka et al. 2013; Pour et al. 2014). The extract of ginger was shown to posses anti-inflammatory and anticancer activities (Miyoshi et al. 2003; Habib et al. 2008). It has also shown prominent and effective glycaemic control properties in diabetes mellitus and related complications (Li et al. 2012).

Most commercially cultivated varieties of Z. officinale rarely flower and generally do not produce viable seeds (Inden et al. 1988). However, it is noteworthy that considerable diversity is known in terms of color of rhizome, its size, aroma, fiber content and chemical profiles, in various cultivated varieties (Pandotra et al. 2013a; Khan et al. 2016). Present study was planned to understand the genetic basis of such high morphological diversity observed in Z. officinale, despite being a vegetatively propagated plant. For this, expressed sequence tag (EST) databases offer a rich source of information and EST-SSRs have been widely used for diversity analysis and development of new molecular markers in plant species. Simple sequence repeats (SSRs) or microsatellites are short repetitive DNA sequences which occur due to slipped strand mispairing (Leclercq et al. 2010). It has also been shown that SSRs found in coding sequences (EST-SSRs) are polymorphic across species which may be helpful in phylogenetic analysis (Gandhi et al. 2010; Awasthi et al. 2012) as well as plant breeding studies (Scott et al. 2000; Pashley et al. 2006).

Earlier, we have studied chemical diversity, differential ability to accumulate heavy metals, morphological diversity and genetic diversity on the basis of inter simple sequence repeat and retrotransposon based markers in various accession of Z. officinale (Pandotra et al. 2013a, b; Khan et al. 2016). Present study involves characterization of the ESTs of Z. officinale for the type of SSRs present, annotation of their putative function and roles in different biological processes. Apart from studying diversity in accession of Z. officinale, the EST-SSR markers developed in this study were also assessed for their ability to be cross-transferred to other species of Zingiberaceae family.

Materials and methods

Collection of plant material

25 accessions of Z. officinale were collected from different locations in India, as shown in Table 1. Zingiber zerumbet (L.) Roscoe ex Sm. (Zingiberaceae), Hedychium spicatum Sm. (Zingiberaceae), Curcuma longa L. (Zingiberaceae), C. amada Roxb. (Zingiberaceae), C. aeruginosa Roxb. (Zingiberaceae), C. aromatica Salisb. (Zingiberaceae) and C. angustifolia Roxb. (Zingiberaceae) plants were used to assess the cross species transferability of EST-SSR markers. These plants were grown in institutional experimental farms [Jammu, India 32°44′N:74°54′E], as described earlier (Pandotra et al. 2013b).

Table 1.

Locations of different accessions of Z. officinale collected from various regions of India

S. no. Accession code Location Longitude E (°) Latitude N (°)
1 Zo51 Nainital 79.2700 29.2300
2 Zo63 Bhageshwar 79.7700 29.8500
3 Zo75 Tehri 78.4800 30.3800
4 Zo76 Tehri 78.4800 30.3800
5 Zo77 Dehradun 78.0290 30.3180
6 Zo78 Nainital 79.2700 29.2300
7 Zo91 Sagar 78.6667 23.8000
8 Zo142 R S Pura 74.7300 32.6300
9 Zo148 Jammu 74.8700 32.7500
10 Zo151 Sagar 78.6667 23.8000
11 Zo154 Sagar 78.6667 23.8000
12 Zo160 Calicut 75.7700 11.2500
13 Zo162 Calicut 75.7700 11.2500
14 Zo164 Calicut 75.7700 11.2500
15 Zo241 Barabanki 81.2000 26.9200
16 Zo254 Sagar 78.6667 23.8000
17 Zo256 Sagar 78.6667 23.8000
18 Zo257 Sagar 78.6667 23.8000
19 Zo287 Bhageshwar 79.7700 29.8500
20 Zo292 Tehri 78.4800 30.3800
21 Zo293 Tehri 78.4800 30.3800
22 Zo294 Bhageshwar 79.7700 29.8500
23 Zo197 Tehri 78.4800 30.3800
24 Zo308 Sirmour 77.2940 30.5594
25 Zo322 Sagar 78.6667 23.8000
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Data mining for EST-SSR markers and primer designing

38,115 EST sequences of Z. officinale were downloaded from the NCBI GenBank database (http://www.ncbi.nlm.nih.gov). EST-SSRs were mined using MIcroSAtellite identification tool (MISA, http://pgrc.ipk-gatersleben.de/misa/). The parameters used for identification of SSRs were same as described in our previous study (Awasthi et al. 2012; Gandhi et al. 2010; Mahajan et al. 2015). Primers used for EST-SSR study were designed using PRIMER3 software (http://primer3.ut.ee/).

DNA isolation and amplification of genic microsatellite markers

Total DNA was isolated from young leaves, by CTAB method (Doyle and Doyle 1987), and analyzed using electrophoresis and NanoDrop 2000c spectrophotometer (Thermo Scientific, MA, USA). 20 µl polymerase chain reaction (PCR) was carried out in a PCR machine (Eppendorf, Germany). The reaction mixture comprises of 50–100 ng of genomic DNA, PCR buffer (10×; with MgCl2), 2 µl dNTPs (2 mM), 2 µl of each primer (0.5 µM), 1U of Taq DNA polymerase (New England Biolabs, England, UK). The PCR was set at following conditions: initial denaturation at 95 °C for 5 min, followed by 35 cycles at 95 °C for 1 min, 1 min at Tm (for detail see Table 2), 1 min at 72 °C, and final extension at 72 °C for 10 min followed by hold at 4 °C. A control reaction was performed using 18S rDNA primers to ascertain the presence of amplifiable genomic DNA. PCR products were evaluated by polyacrylamide gel electrophoresis (PAGE) for changes in amplicon size. Amplicon size changes up to ± 15 base pairs were taken into consideration, remaining were discarded as possible indels and mispriming.

Table 2.

Primers used in the study

Locus name Primer sequence (5′ → 3′) Repeat motif Tm (°C) Product size (bp) Orientation
GES421 TGCTCCACTAGAAGAAGCCT (AT)n 55 478 Forward
CACTTGAAGACCATGTCGAG Reverse
GES 423 CTCATGCTCTCCGACATCT (TA)n 54 226 Forward
CACTTACACGTACGGCACAT Reverse
GES 425 GACTGTACCGACTGCAAGTG (AATAT)n 54 367 Forward
AGAGACACACAGATGCATGG Reverse
GES 426 GCAGAGACACCCTTTTGAAG (ATATT)n 53 369 Forward
GACTGTACCGACTGCAAGTG Reverse
GES 438 ACCTCCTCCTCCTCTTCAAC (GCCGAC)n 52 493 Forward
GAACAGTCGAACATACAGCG Reverse
GES 440 CCTCCTTCCAAACACAACAC (CAGC)n 55 243 Forward
CAGTGATGTTAGCGTCGTCT Reverse
GES 444 GGTCGAGACTGAAGACAAGG (TCTT)n 52 456 Forward
AGGCACGACCTCAGATTAAC Reverse
GES 449 TGAGCTGAGTCGAGTTGTGT (AAT)n 53 187 Forward
ATCTGCCTCTCTTGGTCTTG Reverse
GES 452 CTGGTACTGCAAGTACGTCG (GGATCC)n 51 287 Forward
GTTCAATCTCCTGGAAGCAG Reverse
GES 453 AGCCGAAATCTGTCCTGTAG (GGA)n 53 467 Forward
TTGACACTGTATCACTGGGG Reverse
GES 454 AGAGCTTTCTGCACTTCCAC (AAT)n 52 329 Forward
GAAGTGTGCCCAAATAGCAC Reverse
GES 456 CCTGAGAATAGCCAAGAGGA (TACCA)n 58 206 Forward
CACATTCAAGTGCTATCCCC Reverse
GES 457 ACACCTTGAAGACCATCCTC (TATC)n 50 243 Forward
AGATGGAAGTTGGTAGGCAG Reverse
GES 459 ACCCAATAGCACAACCTCAG (TGG)n 51 283 Forward
CCTCAATGCTGCCACTAAC Reverse
GES 464 CGAACACTACTGGATGAGCA (GGT)n 54 252 Forward
CTCCGTACTACCATCAACCC Reverse
GES 466 CTGTCTTCATCCACTTTCCC (CT)n 55 165 Forward
TAGGCACAGACACGGACATA Reverse
GES 472 TCACGTGACACAAGAGAAGC (AG)n 55 474 Forward
CACTGTTCGACGCACTAATC Reverse
GES 475 ATGTGCAGGCCATTGTTG (TA)n 54 357 Forward
CAGGAGGTGCAAGAGAGAAT Reverse
GES 480 GTCGTGGGTGCGAGATTA (TA)n 52 231 Forward
AATATGGGATCCACTCTCCC Reverse
GES 481 CAAGTGCTTCAGCTCCTACA (TATAT)n 55 410 Forward
GCTAGCAGAAGGAAAAGTGC Reverse
GES 486 ACTCACCGAGTCGGAAATAG (GATTG)n 53 308 Forward
GTAGTGAGGCTTTGGCAGAT Reverse
GES 495 GTGAGGGAGAAGGAGAAAGA (AGAAGG)n 51 135 Forward
ATCGAGGTAGGTTTGGAGGT Reverse
GES 497 AGCCCTTCCATGAGTTCTCT (CAG)n 53 237 Forward
TCTGAACAGCTGGGTACTGA Reverse
GES 511 GCAGGATAGGCTTCCTCTAT (TCT)n 53 305 Forward
CGATAAGATGGAGAAGGAGG Reverse
GES 512 GGGAGAGTAAACGGAAGTGA (GGC)n 51 268 Forward
ATCCCTGTACTCCACGATGT Reverse
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Statistical evaluations

EST-SSR bands were scored as discrete variables. Presence and absence of a band was scored as 1 and 0 respectively (binary data). Dice coefficient of similarity (Dice 1945) was calculated for the accessions, to examine the genetic relatedness. Further, for plotting of dendrogram, a similarity matrix generated using the Dice coefficient was clustered in ‘SAHN’ subroutine using UPGMA (Unweighted Pair Group Method with Arithmetic mean) method. NTSYSpc ver 2.2 tool was used for statistical evaluation.

Results

Identification and characterization of EST SSR marker from Z. officinale

We mined the EST resource of Z. officinale containing a total of 38,115 ESTs, and clustered them using MegaBLAST. Clusters were assembled using a CAP3 assembly to generate 7850 contigs and 10,762 singletons. SSRs were searched in these unigenes and 512 microsatellite containing ESTs were identified with 500 ESTs having single SSRs while 15 ESTs had more than 2 SSRs. 349 EST sequences were found appropriate for primer designing. The frequency of SSR was 1 per 25.21 kb. Five different repeat motifs were identified (di-, tri-tetra-, penta- and hexanucleotide). As expected, tri-repeats were the most abundant (39.74%) SSR in the ESTs followed by di-(24.48%), hexa-(13.75%), tetra-(12.24%) and penta (9.79%) as summarized in Supplementary Table 1. Among the di-nucleotide repeats, there was a distinct predominance of TA (24.6%, 32/130) and GA (21.5%, 28/130) repeats, with low frequencies of other di-nucleotide repeats. Amongst trinucleotide repeats, CGC (5.2%, 11/211), CTC (5.2%, 11/211), GAG (5.2%, 11/211), GGA (5.6%, 12/211) and TCC (7.1%, 15/211) repeats were found to be in majority. The most frequent tetra- and penta-nucleotide repeats were TTTG (6.1%, 4/65) and AATAT (7.6%, 4/52) respectively, but their frequencies were low. We also identified hexa-nucleotide repeats but most of them were found only once (Supplementary Table 2).

Functional annotation and classification of EST SSR sequences from Z. officinale

The annotations of 349 EST sequences were performed using Blast2GO tool (Conesa et al. 2005). The query sequence was aligned with the non-redundant protein sequences from NCBI database. A match with an E-value of 10−6 or less was considered as significant. Gene ontology analysis was performed to determine biological process, molecular functions and cellular component of these ESTs. Several ESTs were found to be involved in different biological processes like transport, protein modification, metabolic processes, response to different stresses while many had hydrolase, kinase activity and binding domains for nucleic acid, lipids and proteins (Supplementary Fig. 1).

EST SSR marker development and its cross transferability study within Zingiberaceae

25 accessions of Z. officinale, collected from different regions of India were used for wet lab validation of EST-SSR markers (Table 1). Prior to validation studies, cross-species transferability of these EST-SSR markers was assessed by carrying out in silico PCR against Curcuma longa unigenes. 12,565 ESTs from C. longa were assembled in the same way as described for Z. officinale into 2978 contigs and 4072 singletons. 116 primer pairs resulted in successful in silico amplification (data not shown). Out of 349 primer pairs that were designed from EST database of Z. officinale, PCR was carried for 25 primer pairs, selected in an arbitrary and random fashion for experiments. PCR products were run on agarose to check for gross amplification results, mispriming and null alleles. Null alleles were confirmed by using at least 5 times more template in PCR reactions. Out of 25, 16 primers sets were optimized for the EST-SSR study. PCR products were run on PAGE to test the change in amplicon size. Representative image showing amplification across 25 accessions using three EST SSR markers (GES440, GES452 and GES454) is shown in Fig. 1. The optimized EST-SSR markers were checked for cross species transferability among seven different species of Zingiberaceae: Z. zerumbet, H. spicatum, C. longa, C. amada, C. aeruginosa, C. aromatica and C. angustifolia. GES454, GES466, GES480, GES486 markers were transferable to all the accessions of Zingiber, Curcuma and H. spicatum while GES452, GES456 marker were transferable to all species under study except one (Supplementary Fig. 2a). Percentage transferability of EST-SSR markers was found to be 100% for GES454, GES466, GES480, GES486 (Supplementary Fig. 2b).

Fig. 1.

Fig. 1

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Development of EST-SSR markers in different accessions of Z. officinale collected from various regions of India. a Representative gel image of three EST-SSR markers (out of 25) used in the study. 18S rDNA was used as control. Optimized PCRs were run on PAGE to test for changes in amplicon size. Amplicon size changes up to ± 15 base pairs were taken into consideration, b dendrogram generated using UPGMA analysis depicts phylogenetic relationships amongst different accessions

Discussion

Zingiber officinale is important medicinal spice, with wide range of pharmaceutical properties (Marx et al. 2013; Haniadka et al. 2013). Genetic variability observed in vegetatively propagated crops, such as Z. officinale, may be due to ancestral differences and/or spontaneous mutations (Elias et al. 2000; Jankowicz-Cieslak et al. 2012). Microsatellite expansion/contraction and retrotransposon mobility are amongst the key drivers of spontaneous mutations (Ellegren 2004). Here, we have made a systematic attempt to study the genic (protein coding) sequences of this plant for development of genetic markers. SSRs may be found in non-coding as well as protein coding (genic) DNA (Tóth et al. 2000; Zhao et al. 2014). However, variation in lengths of SSRs present in genic sequences may have profound effects on morphology, chemoprofile, fiber content, etc. Earlier we have reported differences in such parameters amongst the collected accessions of Z. officinale (Khan et al. 2016; Pandotra et al. 2013a, b). EST-SSR markers (genic microsatellites) have been widely used for gene mapping and diversity analysis in many plant species (Kantety et al. 2002; Chen et al. 2006). Earlier, we had developed EST-SSR markers for Ocimum genus and correlated with the essential oil composition (Mahajan et al. 2015).

Abundance and distribution of microsatellites and EST-SSR primer development

In case of ginger, we found that 2.7% unigenes contained non-redundant microsatellites. In general, EST-SSR frequency was found to range between 2.65 and 16.82% for dicotyledonous species (Kumpatla and Mukhopadhyay 2005). While EST SSR frequency in monocots is generally low (1.5–4.7%) in comparison to dicots (Kumpatla and Mukhopadhyay 2005). Among dicots, computational analysis of EST data shows that there are significant differences in types and abundance of SSRs in various plants (Kantety et al. 2002; Kumpatla and Mukhopadhyay 2005). The present study recorded a relatively lower abundance of genic SSRs as compared to other dicot plant species such as grapes, tea, coffee and turmeric (Scott et al. 2000; Poncet et al. 2006; Joshi et al. 2010; Huang et al. 2011; Backiyarani et al. 2013). The frequency of different SSR repeats in Z. officinale revealed that tri-nucleotide repeats were the most plentiful SSRs followed by di-, hexa-, tetra- and penta-nucleotide repeats. In general, genic SSRs with tri-repeats remained most common among the monocot and dicots (Kumpatla and Mukhopadhyay 2005).

Transferability of EST SSR marker within Zingiberaceae

16 optimized EST-SSR markers were found to be cross transferable among seven species (Z zerumbet, H. spicatum, C. longa, C. amada, C. aeruginosa, C. aromatica and C. angustifolia) of Zingiberaceae (Supplementary Fig. 2). Higher levels of transferability of these genic SSRs imitate the conserved nature of coding sequences in the microsatellite flanking region. This result suggested that these transferable genic microsatellite markers could be used for detection of markers associated with specific traits in other Zingiberaceae species and related genera. Similar results were seen among the other species of grapes, and pines (Decroocq et al. 2003; Chagn et al. 2004). In another study, 100% transferability of EST SSR (C. longa) marker was observed but among other species of Curcuma (Siju et al. 2010).

Conclusion

Ginger is a vegetatively propagated plant, however it is found in multiple varieties which display considerable diversity in morphological characters and chemoprofiles. Present study has isolated genic microsatellite markers from this commercially important plant. Since these markers originate from coding gene sequences, they can be utilized not only for studying the genetic diversity but also used for identification of candidate genes for particular traits. Further, many markers were found to exhibit a high degree of cross-genus and cross-species transferability which implies that they will be a precious resource for the comparative mapping by developing conserved ortholog set (COS) markers in evolutionary studies of different members of Zingiberaceae.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary Fig. 1 (1MB, tif)

Annotation of ESTs containing SSRs: (a) Biological process, (b) Molecular function, and (C) Cellular component (TIFF 1031 kb)

Supplementary Fig. 2 (14.2MB, tif)

Cross-species transferability of Zingiber officinale EST-SSR markers (selected on the basis of amplification in different accessions of Z. officinale) in Z. zerumbet, H. spicatum, C. longa, C. amada, C. aeruginosa, C. aromatica and C. ausutifolia was studied. (a) Presence of amplifiable DNA was scored as ‘+’ and absence as ‘-’. (b) Percentage transferabilty of each EST-SSR markers was also calculated. (TIFF 14512 kb)

Supplementary Table 1 (36.4KB, docx)

SSRs mined from EST resource of Zingiber officinale (DOCX 36 kb)

Supplementary Table 2 (27KB, docx)

Characteristics and frequency of different types of EST- SSRs identified in Z. Officinale. (DOCX 27 kb)

Acknowledgements

PA, VM and ShG are supported by CSIR research fellowships. YSB, SuG and SGG acknowledge the financial support for this work from CSIR 12th FYP project ‘BioprosPR’ (BSC0106) and PMSI (BSC0117) of Council of Scientific and Industrial Research (CSIR).

Author contributions

SuG and APG collected and maintained the accessions of Z. officinale. PA performed EST-SSR work. PA and AS carried out cross transferability studies. PA wrote the manuscript. VM and ShG helped in manuscript preparation. SGG designed the study, carried out bioinformatics analysis for discovery of EST-SSR markers and edited the manuscript and Figures. YSB provided critical inputs for the study as well as during preparation of the manuscript. Authors are thankful to Dr. Gandhi Ram and Mr. Pankaj Pandotra for maintaining the accessions in the field.

Compliance with ethical standards

Conflict of interest

All authors declare that they have no conflict of interest.

Footnotes

Electronic supplementary material

The online version of this article (doi:10.1007/s12298-017-0472-5) contains supplementary material, which is available to authorized users.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplementary Fig. 1 (1MB, tif)

Annotation of ESTs containing SSRs: (a) Biological process, (b) Molecular function, and (C) Cellular component (TIFF 1031 kb)

Supplementary Fig. 2 (14.2MB, tif)

Cross-species transferability of Zingiber officinale EST-SSR markers (selected on the basis of amplification in different accessions of Z. officinale) in Z. zerumbet, H. spicatum, C. longa, C. amada, C. aeruginosa, C. aromatica and C. ausutifolia was studied. (a) Presence of amplifiable DNA was scored as ‘+’ and absence as ‘-’. (b) Percentage transferabilty of each EST-SSR markers was also calculated. (TIFF 14512 kb)

Supplementary Table 1 (36.4KB, docx)

SSRs mined from EST resource of Zingiber officinale (DOCX 36 kb)

Supplementary Table 2 (27KB, docx)

Characteristics and frequency of different types of EST- SSRs identified in Z. Officinale. (DOCX 27 kb)

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