EST-SSR markers development and application in an important medicinal plant, Schisandra chinensis (Schisandraceae)

Abstract

Schisandra chinensis, classed as a climbing woody vine, is representative of the Schisandraceae family regarded as a significant plant in Chinese herbal medicine. However, the application of molecular breeding is constrained by the fact that the number of genetic markers is small for this species. In this study, transcriptome sequencing of S. chinensis was performed using the Illumina HiSeq platform to construct a library of expressed sequence tag-simple sequence repeat (EST-SSR) markers. A total of 59,786 unigenes were obtained on the basis of 8.57 Gbp clean data. A total of 3460 putative SSR sites were detected with a frequency of 5.79%. The predominant type of repeat markers was dinucleotide (64.54%), followed by trinucleotide (23.87%), hexanucleotide (0.90%), tetranucleotide (0.12%) and pentanucleotide (0.40%). Besides, 50 pairs of EST-SSR primers were randomly selected for verification, among which 14 pairs (28%) showed polymorphism in 42 different types of S. chinensis accessions. The mean values of Na, Ne, PIC, Ho, He and SI were 2.71, 1.7642, 0.4295, 0.6016, 0.3934 and 0.6078, respectively. All of the 42 accessions were successfully identified and formed four major clusters, indicating that the EST-SSR markers are applicable for genetic diversity analysis and identification in S. chinensis. According to the result, the transcriptome data are an effective resource for developing SSR markers. These markers can provide a basis for the identification of S. chinensis accessions, genetic diversity analysis, the conservation and construction of genetic linkage maps as part of selective breeding and the conservation efforts for this valuable plant.

Keywords:

• Expressed sequenced tag (EST)
• Schisandra chinensis
• simple sequence repeat (SSR)
• genetic diversity analysis

Introduction

Schisandra chinensis (Turcz.) Baill. (Schisandraceae) is regarded as an essential plant in respect of Chinese herbal medicine [1,2]. The fruit of S. chinensis possesses multiple beneficial therapeutic and physiological properties, including adaptogenic, hepatoprotective, anticancer, antioxidant and anti-inflammatory effects. The abundance of Schisandra species has declined significantly in recent years due to habitat loss and excessive economic exploitation. S. chinensis has been listed as a ‘Category III’ protected species in the Chinese National Key Protected Wild Plants [3,4]. Most of the studies on S. chinensis centered on its pharmacological properties, while there is still little attention brought to its mechanism on the molecular level.

DNA molecular markers can be used to analyze the genetic diversity of germplasm resources. However, previous studies have applied only a few types of markers in Schisandra, including inter simple sequence repeats (ISSRs) [5,6], simple sequence repeats (SSRs) [7,8], amplified fragment length polymorphisms (AFLPs) [9,10] and randomly amplified polymorphic DNA (RAPD) [11]. Adopting the FIASCO method, Yan et al. [8] achieved a success in developing and screening 9 SSR polymorphic primers, with the expected heterozygosity (He) reaching 0.528 on average. Based on Bayes cluster analysis, ten natural populations of S. sphenanthera were divided into two groups [8]. By analyzing the genetic structure of S. sphenanthera and S. chinensis, Sun et al. [6] inidcated that the He value of S. sphenanthera was 0.2782, Shannon’s Information (SI) index was 0.4280, the He value of S. chinensis was 0.2894 and the SI index was 0.4396. In comparison with the traditional method applied for the development of SSR markers, transcriptome sequencing can provide a large number of putative SSR loci with significantly less efforts and costs required. Herein, to increase the collection of available markers, through transcriptome sequencing, we report a large number of identified ESR-SSRs, which provide ample genome resource for further studies about the species.

Materials and methods

Sample collection and total RNA extraction

The plant materials were obtained from the germplasm resource garden of Jilin Agriculture University (125°24′15″E, 43°48′5″N; Changchun, Jilin Province, China) in July, 2019. The information on 42 accessions is shown in Table 1. ‘Yanhong’ and ‘Jinwuwei’ were examined and approved by Jilin Provincial Variety Examination and Approval Committee in 2012 and 2016, respectively. Young leaves (0.5–1.0 g) were collected and ground into powder after freeze drying in liquid nitrogen. Total RNA was extracted using a modified version of the cetyltrimethylammonium bromide (CTAB) method [12]. RNA was visualized by 1.5% agarose gel electrophoresis.

Table 1. Schisandra chinensis accessions analyzed in this work.

No.	Name	Origin	No.	Name	Origin	No.	Name	Origin
1	Yanhong	Jilin	15	Changbai	Jilin	29	19-3-4	Jilin
2	BaiGuo	Jilin	16	84-7-2	Jilin	30	2012-7	Jilin
3	Zaohong	Jilin	17	158-11-6	Jilin	31	27-2-6	Jilin
4	Jinwuwei	Jilin	18	18-10-2	Jilin	32	A18-8-5	Liaoning
5	35-6-1	Jilin	19	8-1-1	Jilin	33	20-1-4	Jilin
6	168-1-6	Jilin	20	17-11-3	Jilin	34	19-3-5	Jilin
7	10-S8-N2	Jilin	21	130-9-6	Jilin	35	A71	Jilin
8	162-1-4	Jilin	22	2012-5	Liaoning	36	18-10-2	Jilin
9	17-N1-N1	Liaoning	23	20-28-1	Liaoning	37	94-9-2	Jilin
10	12-(-2)-1	Jilin	24	11-2-3	Liaoning	38	25-3-2	Jilin
11	25-6-10	Liaoning	25	14-3-1-5	Jilin	39	13-5-2	Jilin
12	50-5	Liaoning	26	106-43	Jilin	40	171-1-4	Jilin
13	137-3-3	Jilin	27	156-5-2	Heilongjiang	41	235-5-6	Jilin
14	99-8-7	Jilin	28	82-5-6	Jilin	42	11N1S1	Heilongjiang

Sequencing, assembly and functional annotation

RNA was extracted using the CTAB method before the reverse-transcription into cDNA, which was sequenced by Illumina (San Diego, CA, USA) high-throughput deep sequencing platform in 2018. The Trinity program [12] was involved to assemble the high quality reads. The unigenes annotation was performed on the basis of COG, GO, KEGG, KOG, Pfam, Swissprot, NR and eggNOG databases.

SSR site identification and primer design based on transcriptome data

SSR loci of unigenes were analyzed using MISA software (https://omictools.com/misa-tool). The minimum number of di-, tri-, tetra-, penta- and hexanucleotide repeats was 6, 5, 5, 5 and 5, respectively. Primer 3 (http://bioinfo.ut.ee/primer3-0.4.0/) was adopted to design primers with the following characteristics: (1) a length varying between 18 and 23 bp; (2) an annealing temperature ranging from 55 °C to 65 °C, with a difference of less than 2 °C between forward and reverse primers; (3) an amplification product sized between 80 and 300 bp; and (4) a GC concentration that varies from 40% to 60%. In total, 50 EST-SSR primers were randomly selected and synthesized by Shenggong Biological Engineering (Shanghai, China).

Polymerase chain reaction (PCR) amplification and data analysis

The 50 EST-SSR primers were tested to identify those with both stability and capability to detect polymorphisms. The PCR reaction, with a total volume of 16 µL, contained 8 µL of 2× Ex Taq Master Mix, 0.8 µL of each of primer, 5.4 µL of ultrapure water, and approximately 20 ng of DNA template. PCR amplification was conducted as previously described [6] with a T100^TM thermal cycler (Bio-Rad, USA). The products were separated using a 5% polyacrylamide gel. The bands were visualized by means of silver staining. A clear band was assigned a value of 1 while a weak or no band at the same position was given a value of 0.

Data analysis

Trinity version r20131110 [12] software was used to assemble the transcriptome data. The parameters of S. chinensis genetic diversity (Na, Ne, Ho, He, PIC and SI) were analyzed using Popgene version 1.32 software [13]. Final dendrograms were constructed by NTSYS-PC software [14] based on the unweighted pair group method with arithmetic mean (UPGMA).

Results and discussion

RNA-Seq and functional annotation

A total of 8.57 Gbp clean data were obtained with 92.51% Q30 bases. The raw data of RNA-seq were deposited in Sequence Read Archives Database (http://www.ncbi.nlm.nih.gov/bioproject/609148) under the accession number PRJNA609148.

A total of 59,786 unigenes were assembled using the Trinity method and were treated as the background data required for the development of EST-SSR markers. The functional annotation of unigenes is presented in Table 2.

Table 2. Functional annotation of S. chinensis unigenes.

Database	Unigene	Percentage
COG	7740	12.95%
GO	15625	26.13%
KEGG	9637	16.12%
KOG	14849	24.84%
Pfam	17203	28.77%
Swissprot	17998	30.10%
eggNOG	24329	40.69%
NR	26350	44.07%
All_Annotated	26827	44.87%

The number of hits against Nelumbo nucifera at 5059 hits (19.2%) was the highest, followed by Macleaya cordata at 2835 hits (10.76%), Amborella trichopoda at 2818 hits (10.69%), Vitis vinifera at 1358 hits (5.15%) and Elaeis guineensis at 932 hits (3.54%) (Figure 1).

Figure 1. Distribution of the Blast hits in the NR database.

SSR site distribution in S. chinensis

We searched 59,786 unigene sequences in the transcriptome data and detected 3460 SSR sites in 3062 sequences. There were 352 unigene sequences containing two or more EST-SSR sites. The SSR frequency was 5.79%. This value was affected by not only the SSR search threshold but also a large number of single nucleotide repeats. In order to facilitate comparisons with other species, we analyzed the results in two groups: one including and the other excluding mononucleotide repeats. In the former context, the SSR frequency in S. chinensis was 10.46%, which is higher than Allium cepa (5.57%) [15] and Phoebe nanmu (9.90%) [16] but lower than Elaeis guineensis (11.26%) [17], Miscanthus (14.44%) [18] and Solanum melongena (18.32%) [19]. Without considering mononucleotide repeats, the SSR distribution frequency was 5.79%, which is higher than corn (Zea mays) (1.5%), barley (Hordeum vulgare) (3.4%) and rice (Oryza sativa) (4.7%) [20], cucumber (Cucumis sativus) (4.03%) [21], Chinese yew (Taxus chinensis) (2.24%) [22] and Korean pine (Pinus koraiensis)(4. 24%) [23]; similar to peanut (Arachis hypogaea) (6.63%) [24], pepper (Capsicum annuum) (7.83%) [25] and dal (Cajanus cajan) (7.6%) [26]; and lower than thorn pear (Rosa roxburghii) (20.37%) [27], oak (Quercus austrocochinchinensis) (27.61%) [28] and precocious trifoliate orange (Citrus reticulata) (26.88%) [29]. It is speculated that these differences indicate the actual variations in SSR abundance across various species if the impact of the amount and source of EST data was ignored [27]. Thus, transcriptome SSRs are abundant in Schisandra, making these an ideal marker for genetic mapping.

The types of EST-SSR detected in the transcriptome varied and their frequencies differed significantly (Table 3). Di-, and trinucleotides were the most common, accounting for 64.54% and 23.87%, respectively. Tetra-, penta- and hexanucleotides were rare, only accounting for 1.42%.

Table 3. Type, number and frequency of expressed sequence tag-simple sequence repeat markers in Schisandra chinensis.

Repeat type	Repeat number							Total	Percentage
	5	6	7	8	9	10	>10
Di		404	314	369	590	447	109	2233	64.54%
Tri	472	224	110	19			1	826	23.87%
Tetra	22	6	2			1		31	0.90%
Penta	4							4	0.12%
Hexa	8	2	2	1			1	14	0.40%
Compound								352	10.17%
Total	506	636	428	389	590	448	111	3460	100%
Percentage	8.57%	10.78%	7.25%	6.59%	10.00%	22.91%	33.90%

More than two times higher frequency of the dinucleotides compared to the trinucleotides conformed to the trend as observed in peanut (Arachis hypogaea) [24], precocious trifoliate orange (Citrus reticulata) [29], Korean pine (Picea neoveitchii) [30] and litchi (Litchi chinensis) [31], despite some evidence suggesting that trinucleotides are the most common SSR type [17,19,22,32,33]. This difference is potentially attributed to the characteristics and quantity of EST-SSR and the EST resources in plants.

Characteristics of EST-SSRs

An analysis was conducted of di-, tri-, tetra-, penta- and hexanucleotides. Due to the potential of poor sequencing quality caused by homopolymerization, mononucleotides were excluded [34]. In total, 82 types of motif were identified, with 8, 30, 25, 5 and 14 di-, tri-, tetra-, penta- and hexanucleotide repeats, respectively (complementary sequences were considered one type of motif) (Table 4). The most highly represented EST-SSR type was dinucleotide (64.54%); TC/GA was the most common motif (48.46%) followed by CT/AG (39.52%), with other motif types comprising merely 12.02% of all EST-SSR dincleotides. TC/GA was revealed as the most common dinucleotide repeat unit in S. chinensis, which is identical to pigeonpea (Cajanus cajan) and tree rhododendron (Rhododendron arboreum) [26,35] but distinct from barley (Hordeum vulgare), wheat (Triticum aestivum), corn (Zea mays), sorghum (Sorghum bicolor), rice (Oryza sativa) [20], eggplant (Solanum melongena) [19], peanut (Arachis hypogaea) [24], sugarcane (Saccharum officinarum) [36], grass (Miscanthus) [18], daylily (Hemerocallis citrina) [37], Chinese gansui (Euphorbia kansui) [38], thorn pear (Rosa roxburghii) [27], and Chinese yew (Taxus chinensis) [22]. There were 30 types of trinucleotide repeat motifs among S. chinensis ESTs. More specifically, the most frequent ones include GAA/TTC and AGA/TCT, accounting for 16.59% (846) and 13.49% (688) of the total, respectively. GAA/TTC was the most abundant trinucleotide repeat motif, as reported for pansy [39].

Table 4. Distribution of EST-SSR motifs in the transcriptome of S. chinensis.

Motif	Repeat number	Motif	Repeat number
GT/AC	520	CTC/GAG	153
TC/GA	9969	ATT/AAT	126
AG/CT	8131	AGC/GCT	261
CA/TG	833	CCG/CGG	55
AT	624	CGT/ACG	36
TA	471	ATG/CAT	149
CG	18	TCC/GGA	91
GC	6	ATC/GAT	195
Dinucleotide	20572	GTT/AAC	60
TGC/GCA	210	GAA/TTC	846
AAG/CTT	517	TGA/TCA	225
ACT/AGT	10	GCG/CGC	39
GGC/GCC	33	TGT/ACA	56
TAG/CTA	5	AGA/TCT	688
TCG/CGA	43	CAG/CTG	239
GAC/GTC	51	CCT/AGG	80
TAA/TTA	96	TGG/CCA	234
TAC/GTA	29	Trinucleotide	5100
CAA/TTG	89	Tetranucleotide	206
TAT/ATA	123	Pentanucleotide	27
GTG/CAC	210	Hexanucleotide	6
ACC/GGT	151

The frequency of different motifs in the EST datasets varied, with 20572 (79.39%) dinucleotides, 5100 (19.68%) trinucleotides, 206 (0.81%) tetranucleotides, 27 (0.1%) pentanucleotides and 6 (0.02%) hexanucleotides (Figure 2(a)). The number of motif repeats ranged from 5 to 12, with six as the most-seen number of repeats, as shown in Figure 2(b).

Figure 2. Frequency distribution of putative EST-SSRs identified from S. chinensis ESTs, according to motif type (a) and number of repeats (b).

Development of S. chinensis EST-SSR primer pairs and detection of polymorphisms

To obtain high quality SSRs that could detect polymorphisms, we randomly selected 50 primer pairs to evaluate polymorphisms among four accessions of S. chinensis (Yanhong, Zaohong, Jinwuwei and 12-(-2)-1). Among the 50 EST-SSR primer pairs tested, 40 were successfully amplified, whereas 14 produced stable and polymorphic bands of the expected size (Table 5), with a polymorphic amplification efficiency of 28%, which is comparable to Chinese bajitian (Morinda officinalis) (24%) [40], higher than pigeonpea (Cajanus cajan) (12.9%) [26] but lower than onion (Allium cepa) (60%) [15], thorn pear (Rosa roxburghii) (54.76%) [27] and Chinese yew (Taxus chinensis) (53.23%) [22]. A total of 38 alleles were detected by 7 pairs of primers, with an average of 2.71. The polymorphism information content (PIC) ranged from 0.2604 to 0.5817, with an average of 0.4295. The He value for diversity ranged from 0.0235 to 0.4997, and the highest SI index was found for SSC0035 with 1.0842, the lowest for SSC0062 (Table 6).

Table 5. Information of 14 SSRs used for assessment of genetic diversity among 42 S. chinensis accessions.

No.	SSR name	Repeat motif	Forward primer sequence (5′→3′)	Tm (°C)	Reverse primer sequence (5′→3′)	Tm (°C)	Expected siz e (bp)
1	SSC00061	(TCT)6	GGCAAGCAGACACAGTCAAA	60.03	GTAGTGGAGGAGCGAAGACG	60.01	253
2	SSC00055	(CAG)6	AAGAAAGCCAGAACACGTCC	59.33	GCTTTTGTGACTTGGGGTGT	60.01	241
3	SSC00094	(AGA)6	TGTAAACTTTGAAGTCCAACCG	59.17	TTGCTTTCTGAAGCACGAGA	59.87	188
4	SSC00095	(ATT)6	CTGTCCCGCTTCTCTTTGAG	60.13	GTGGCCCGAGGTACTAACAA	59.99	123
5	SSC00082	(CAT)7	ATTACTACCACAGCCACCGC	60.02	GATGATCAGGTGTGGTCCCT	60.07	267
6	SSC00098	(GCG)7	CTCTCTCGCTTCATTCACCC	59.95	TCATCACTGTTCGATTCCCA	60.05	144
7	SSC00096	(TGGGCC)6	ACCATCTCCACTTTCGCAAC	60.03	ATCTGGAACTGTGATTGGGC	59.98	216
8	SSC00097	(CAT)7	CAAGCTTTCTTTCCCTCGTG	60.05	GATGATCAGGTGTGGTCCCT	60.02	267
9	SSC00035	(CAT)6	CAACTGGCTGGGCTGATATT	59.96	TGTTCGATTTGGTTGTTGGA	59.45	253
10	SSC00019	(ATC)7	GTGGAATTTCGATTCAGGGA	59.88	GGGAATTGGTCAATTGGGTA	59.86	186
11	SSC00041	(GTG)5	TAGTATGGGCTTGGAGGTGG	60.04	AATTTACTGCATTCGCTCGC	60.02	102
12	SSC00036	(CCA)6	ACTGCCATTCGCATTACTCC	59.63	TACGGATGGGAAGGTGAGAG	59.32	199
13	SSC00028	(CAT)5	TGAGGTCCCCATGAAGAAAG	59.84	CCGTTGGATGAAAGGAGTGT	59.86	137
14	SSC00062	(GTC)5	CACTTCAGAAATCTCGGCGT	60.40	CCAGCATGTCCAATCTTTCA	59.65	152

Table 6. Estimation of genetic diversity based on 14 SSRs among 42 S. chinensis.

No.	SSR name	Allele number	PIC	Effective allele number	Ho	He	SI	Amplicon range (bp)
1	SSC00061	2	0.2604	1.2654	0.7877	0.2098	0.3650	242–253
2	SSC00055	2	0.3741	1.9955	0.4951	0.4989	0.6920	240–255
3	SSC00094	4	0.5094	1.7890	0.5536	0.4410	0.8044	100–115
4	SSC00095	4	0.3749	1.9989	0.4943	0.4997	0.6929	192–203
5	SSC00082	3	0.3702	1.9192	0.5148	0.4790	0.6720	235–246
6	SSC00098	3	0.3456	1.6897	0.5869	0.4082	0.5983	270–283
7	SSC00096	2	0.5504	1.6156	0.6143	0.3810	0.5689	137–152
8	SSC00097	2	0.5701	1.9888	0.4965	0.4972	0.6903	128–139
9	SSC00035	3	0.5817	2.9132	0.3337	0.6567	1.0842	218–280
10	SSC00019	3	0.4635	1.9765	0.4998	0.4941	0.8562	140–155
11	SSC00041	2	0.3736	1.9836	0.4965	0.4959	0.6890	201–200
12	SSC00036	2	0.5817	1.2195	0.8177	0.1800	0.3251	181–195
13	SSC00028	3	0.3710	1.0241	0.9762	0.0235	0.4068	150–162
14	SSC00062	3	0.2865	1.3197	0.7546	0.2423	0.0646	188–202
	Mean	2.71	0.4295	1.7642	0.6016	0.3934	0.6078

Note: PIC, Polymorphism information content; He, expected heterozygosity; Ho, observed heterozygosity; SI, Shannon’s Information index.

Discrimination between different S. chinensis genotypes using EST-SSR primer pairs

In the genetic diversity analysis, the 14 EST-SSR primer pairs identified as described above could be used to differentiate between the 42 S. chinensis accessions. Using NTSYS-pc software to analyze genotype data, the accessions were classified into four groups at a similarity index of 0.63 (Figure 3). A dendrogram revealed clear distinctions between the accessions, reflecting a high genetic diversity that can be exploited for S. chinensis identification based on a DNA fingerprint. The relatedness of the 42 accessions was supported by similarity coefficients ranging between 0.61 and 0.97. Group I, which comprised 28 varieties mostly originating in Jilin, was the largest group with four subgroups and a similarity coefficient of 0.682. Group II included four varieties; most were from Heilongjiang, with one accession from Jilin. ‘18-10-3’and ‘162-1-4’ did not cluster with any of the groups and were designated as group IV, and the remaining accessions constituted group III. All 42 accessions were distinguishable based on the 14 EST-SSR markers and their clustering pattern was concordant with their distribution, indicating that EST-SSR data obtained by transcriptome analysis can reveal the genetic relatedness of S. chinensis germplasm resources.

Figure 3. Dendrogram of S. chinensis germplasms generated using the unweighted pair group method with arithmetic mean.

To date, there are as few as nine EST-SSR markers identified for S. chinensis. In this study, the large number of SSR loci and polymorphic markers identified on the basis of transcriptome data are effective in facilitating the identification of accessions and the construction of genetic linkage maps in S. chinensis as part of broader efforts for the selective breeding and the conservation of this valuable plant.

Conclusions

In this study, specific SSR markers were developed based on the transcriptome sequencing data of S. chinensis, and the distribution of SSR markers was analyzed. Using these markers, we successfully analyzed the genetic diversity and identified different accessions of S. chinensis. The results demonstrated that transcriptome sequencing is an effective method to identify molecular markers. Our work may lay a foundation for genetic diversity, genetic mapping and marker-assisted selection in S. chinensis. It may facilitate S. chinensis breeding, as well as studies with other Schisandra plants with economic and medicinal value.

Disclosure statement

The authors declare that they have no conflict of interest.

Availability of data and materials

The raw data of RNA-seq are deposited in Sequence Read Archives Database (http://www.ncbi.nlm.nih.gov/bioproject/609148) under accession number PRJNA609148. Other datasets supporting the conclusions of this article are included within the article (and its additional file).

Additional information

Funding

This work was supported by National Key R&D Program of China (2019 YFC1710701); the Research project in Jilin Province Science and Technology Department (grant number 20180201008YY); National Natural Science Fund of China (grant number 31870673).