Skip to main content
Download PDF

De novo transcriptome assembly, gene annotation, and EST-SSR marker development of an important medicinal and edible crop, Amomum tsaoko (Zingiberaceae)

BMC Plant Biology volume 22, Article number: 467 (2022) Cite this article

Abstract

Background

Amomum tsaoko is a medicinal and food dual-use crop that belongs to the Zingiberaceae family. However, the lack of transcriptomic and genomic information has limited the understanding of the genetic basis of this species. Here, we performed transcriptome sequencing of samples from different A. tsaoko tissues, and identified and characterized the expressed sequence tag-simple sequence repeat (EST-SSR) markers.

Results

A total of 58,278,226 high-quality clean reads were obtained and de novo assembled to generate 146,911 unigenes with an N50 length of 2002 bp. A total of 128,174 unigenes were successfully annotated by searching seven protein databases, and 496 unigenes were identified as annotated as putative terpenoid biosynthesis-related genes. Furthermore, a total of 55,590 EST-SSR loci were detected, and 42,333 primer pairs were successfully designed. We randomly selected 80 primer pairs to validate their polymorphism in A. tsaoko; 18 of these primer pairs produced distinct, clear, and reproducible polymorphisms. A total of 98 bands and 96 polymorphic bands were amplified by 18 pairs of EST-SSR primers for the 72 A. tsaoko accessions. The Shannon's information index (I) ranged from 0.477 (AM208) to 1.701 (AM242) with an average of 1.183, and the polymorphism information content (PIC) ranged from 0.223 (AM208) to 0.779 (AM247) with an average of 0.580, indicating that these markers had a high level of polymorphism. Analysis of molecular variance (AMOVA) indicated relatively low genetic differentiation among the six A. tsaoko populations. Cross-species amplification showed that 14 of the 18 EST-SSR primer pairs have transferability between 11 Zingiberaceae species.

Conclusions

Our study is the first to provide transcriptome data of this important medicinal and edible crop, and these newly developed EST-SSR markers are a very efficient tool for germplasm evaluation, genetic diversity, and molecular marker-assisted selection in A. tsaoko.

Peer Review reports

Background

Amomum tsaoko is a perennial evergreen tufted herb of Zingiberaceae; the whole plant has a spicy taste. The dried fruit (also called Cao-Guo in China) of A. tsaoko is an important crude drug in traditional Chinese medicine (TCM), such as ‘Cao-Guo-Zhi-Mu-Tang,’ ‘Da-Yuan-Yin,’ ‘Cao-Guo-Si-Wei-Tang,’ and ‘Li-Gan-Shi-Liu-Ba-Wei-San,’ which clear dampness, resolve phlegm, warm the spleen, and dispel colds. In addition, A. tsaoko is also a top-grade spice known as one of the “five spices” in food seasoning [1]. In recent years, A. tsaoko has been considered to have a broader utilization value and proven to have biological activities, such as anti-oxidation [2, 3], antibacterial [4], anti-inflammation [5], antidiabetic [6], anti-tumor [7], and anticonvulsant properties [8]. In addition, A. tsaoko is a TCM that has been prescribed for the treatment of COVID-19 [9,10,11,12]. As an aromatic Chinese herbal medicine used for both medicinal and edible purposes, essential oil is the most important active ingredient of A. tsaoko, and its content determines the quality of A. tsaoko (Pharmacopoeia of the People’s Republic of China, 2020). Recent studies have shown that A. tsaoko essential oil has a significant inhibitory effect on COVID-19 [13]. The monoterpene 1,8-cineole was found to be the major constituent (34.6–45.24%) of the essential oil in A. tsaoko, and has well-known antiviral, anti-inflammatory, antimicrobial, and pain-relieving effects [14]. In recent years, the cloning and expression analysis of functional genes involved in terpenoid biosynthesis has become a popular topic of research. He et al. [15] used transcriptome sequencing to identify a number of terpenoid synthesis-related genes in Amomum villosum, including five monoterpene synthase genes AvTPS1–AvTPS5. However, until now, there have been no reports about regulated genes that are involved in the terpenoid biosynthesis of A. tsaoko.

A. tsaoko is a high-altitude medicinal crop that grows in humid forests, narrowly distributed in the southern Yunnan Province of China and northern Laos and Vietnam at high altitudes between 1100 and 1800 m in mountainous regions [16, 17]. Due to excessive harvesting and the destruction of the original habitat of A. tsaoko, wild resources are almost extinct, and it was listed as a “Nearly Endangered Species” on the IUCN Red List in 2012. Genetic diversity evaluation can provide important reference information for the identification and evaluation of germplasm resources and the selection of elite germplasm. Molecular marker technology is an effective tool for analyzing plant genetic diversity, which has the advantages of abundant quantity, high polymorphism, direct expression in the form of DNA, and is not affected by the environment [18, 19]. SSRs, also known as microsatellite DNA, are short, repeated DNA sequences present throughout the genome. It has the advantages of good reproducibility, codominance, abundant polymorphisms, and easy detection [20]. In recent years, SSR markers have been widely used in genetic diversity analysis [21, 22], linkage genetic map construction and QTL identification [23, 24], and marker-assisted breeding [25, 26].

As a TCM and spice, previous studies of A. tsaoko mainly focused on active component extraction, identification of chemical components, and pharmacological effects [27,28,29,30,31,32]; however, molecular studies of A. tsaoko are lacking. This limits the excellent germplasm selection and breeding utilization of A. tsaoko. Some researchers have begun to study the genetic diversity of A. tsaoko at the phenotypic and molecular levels. Zhang et al. [33] analyzed the phenotypic characteristics of A. tsaoko in nine producing areas of China. The results showed that the number of fruit ridges, the number of seeds per fruit, and the vertical diameter of fruit had the greatest variation. Genetic diversity and population genetic differentiation of A. tsaoko from eight different producing areas were analyzed by 12 RAPD markers [34]. More recently, the genetic diversity of 91 A. tsaoko accessions from southwest China was studied by SRAP and ISSR markers [17]. A few reports on SSR development and the genetic diversity of A. tsaoko have recently been published [1, 35], but the number of markers is insufficient to conduct comprehensive genetic studies.

With the rapid development of next-generation sequencing technology and lower sequencing costs, large-scale RNA-seq provides an important information for functional gene mining and molecular marker development in non-model species [36, 37]. Here, we present the first transcriptome of A. tsaoko using the Illumina HiSeqTM 4000 sequencing platform. The obtained transcriptome data advance our understanding of the function categories from the annotated genes on this species, and the development of EST-SSR markers will provide an important basis for germplasm evaluation, genetic diversity analysis, and molecular breeding of A. tsaoko.

Results

Sequencing and de novo assembly

In this study, 59,876,622 raw reads were obtained using the Illumina HiSeq 4000 platform. After strict quality control, 97.33% clean reads (58,278,226) were obtained with 96.28% Q20 and 94.25% Q30 bases. A total of 199,191 transcripts were obtained by de novo assembly of clean reads with Trinity software. After clustering transcripts and removing redundancy, 146,911 unigenes were obtained, with an average length of 1527 bp and an N50 value of 2002 bp (Table 1).

Table 1 Characterization of Amomum tsaoko transcripts
Full size table

The assembled unigenes of A. tsaoko were functionally annotated against seven public databases (Table 2, Fig. 1A). A total of 123,420 unigenes (84.01%) were annotated successfully in the NR database, while 95,786 (65.20%) were annotated in the NT database. At the same time, 21,543 unigenes were annotated in all databases, and 128,174 unigenes (87.24%) were successfully annotated with at least one database. The species distribution showed that 80.4% matched Musa acuminata, and 5.6% matched Elaeis guineensis. The matching degrees of Phoenix dactylifera, Nelumbo nucifera, and Vitis vinifera were 4.5, 0.6, and 0.5%, respectively, and 8.3% for other species (Fig. 1B).

Table 2 Functional annotation of A. tsaoko in seven databases
Full size table
Fig. 1
figure 1

Functional annotation (A) and species distribution (B) of unigenes in Amomum tsaoko

Full size image

Furthermore, for the KOG classification, 36,621 putative unigenes of A. tsaoko were classified into 25 clusters (Fig. 2). Among these categories, ‘general function prediction only’ (5039; 13.76%); ‘posttranslational modification, protein turnover, chaperones’ (4993; 13.63%); and ‘translation, ribosomal structure and biogenesis’ (3332; 9.10%) were the dominant groups, while only a few unigenes were annotated as ‘cell motility’ (35; 0.09%) and ‘extracellular structures’ (26; 0.07%). Furthermore, there were 89,750 unigenes categorized into three main GO categories: biological processes (233,859; 47.53%); cellular components (145,239; 29.52%); and molecular functions (112,917; 22.95%) (Fig. 3). Within the three categories, ‘binding’ (53,980), ‘cellular process’ (52,634), ‘metabolic process’ (49,492), ‘catalytic activity’ (41,468), and ‘single-organism process’ (37,122) were the most prevalent. Following searches against the KEGG database, 53,059 unigenes were classified into five categories, which were distributed in 130 metabolic pathways. The largest category was comprised of ‘metabolism’ (21,001; 53.69%), followed by ‘genetic information processing’ (10,413; 26.62%), ‘cellular processes’ (2887, 7.38%), ‘organismal systems’ (2559, 6.54%), and ‘environmental information processing’ (2255, 5.77%) (Fig. 4). In addition, 96,740 (65.84%) and 89,573 (60.97%) unigenes matched the SwissProt and PFAM databases, respectively.

Fig. 2
figure 2

Eukaryotic clusters of orthologous groups (KOG) classification of unigenes. A total of 36,621 unigenes with NR hits were grouped into 25 functional groups. The y-axis indicates the number of unigenes in a specific functional cluster. The x-axis indicates the function class

Full size image
Fig. 3
figure 3

Gene ontology (GO) classification of unigenes. A total of 89,750 unigenes were categorized into three main categories: biological process, cellular component, and molecular function. The x-axis indicates the subgroups in GO annotation, while the y-axis indicates the percentage of specific categories of genes in each main category

Full size image
Fig. 4
figure 4

Clusters of orthologous groups based on KEGG classification. A Cellular process; B Environmental information processing; C Genetic information processing; D Metabolism; E Organismal systems

Full size image

Importantly, KEGG analysis showed that 496 unigenes were annotated as being directly involved in the metabolism of terpenoids, including the terpenoid backbone (338 unigenes), monoterpenoid (22 unigenes), diterpenoid (81 unigenes), and sesquiterpenoid and triterpenoid (55 unigenes) biosynthesis pathways (Table 3). In the monoterpenoid biosynthesis pathway, two unigenes encoding alpha-terpineol synthase, 15 unigenes encoding neomenthol dehydrogenase, one unigene encoding 1,8-cineole synthase, and four unigenes encoding linalool synthase were significantly enriched. The FPKM values of Cluster-26,586.35631, Cluster-26,586.48848, Cluster-26,586.69915, Cluster-26,586.65004, Cluster-18,694.1, and Cluster-26,586.96889 were greater than 10 (Fig. 5A). Notably, 1,8-cineole synthase (Cluster-24,134.3) was initially identified in this species. Multiple sequence alignment revealed that Cluster-24,134.3 contained the DDXXD motif, which is conserved in angiosperm monoterpene synthases (Fig. 5B). Cluster analysis showed that Cluster-24,134.3 had the highest homology with the monoterpene synthase gene AvTPS2 in Amomum villosum (Fig. 5C).

Table 3 Overview of the terpene biosynthetic pathways
Full size table
Fig. 5
figure 5

Unigene analysis of potential monoterpene metabolic pathway in A. tsaoko. Expression of candidate unigenes related to monoterpene synthesis of A. tsaoko (A). Alignment of amino acid sequences of Cluster-24,134.3 (putative 1,8-cineole synthase unigene) with other TPS proteins from Arabidopsis thaliala (AtTPS-Cin), Salvia officinalis (SoTPS-Cin), and Amomum villosum (AvTPS1-AvTPS4) using DNAMAN 8.0 (B). Phylogenetic tree constructed based on amino acid multiple sequence alignment using MEGA 5.2 with the neighbor-joining method (C), dark blue branches represent genus Amomum species (A. tsaoko and A. villosum), and red branches represent other species (A. thaliala and S. officinalis)

Full size image

Development of EST-SSR markers

SSR loci were identified within the A. tsaoko transcriptome using the MISA software. Among the 146,911 non-redundant unigenes, we identified 55,590 potential SSRs, of which 3794 had a compound formation. There were 10,465 unigenes containing more than one SSR. An average of one SSR site was found every 1.53 kb. The largest fraction of SSRs were mononucleotide SSRs (26, 742, 48.11%), followed by trinucleotide repeats (13,849; 24.91%), dinucleotide repeats (12,716; 22.87%), tetranucleotide repeats (1169; 2.10%), hexanucleotide repeats (566; 1.02%), and pentanucleotide repeats (548; 0.99%) (Fig. 6, Table 4). Among the different SSR repeat-type classes, the most dominant repeat motifs were A/T (25,819; 46.44%), AG/CT (7554; 13.59%), AT/AT (3971; 7.14%), AGG/CCT (3390; 6.10%), AAG/CTT (2709; 4.87%), and CCG/CGG (2330; 4.19%). The remaining motif types accounted for 17.67% of these repeats (Table 4). The tandem repeat numbers of these SSRs ranged from 5 to 86, and 10 tandem repeats (12,910; 23.22%) was the most common number, followed by 5 (7789; 14.01%), 6 (6749; 12.14%), 11 (5655; 10.17%), 12 (3975; 7.15%), and 7 (3792; 6.82%) (Table 5).

Fig. 6
figure 6

Frequency and distribution of EST-SSRs from the transcriptome of A. tsaoko. The most abundant dinucleotide and trinucleotide motifs were AG/CT and AGG/CCT

Full size image
Table 4 Distribution of EST-SSR loci in the transcriptome of A. tsaoko
Full size table
Table 5 The length distribution of EST-SSRs based on the number of nucleotide repeat units
Full size table

Validation of EST-SSR markers

A total of 42,333 primer pairs were successfully designed based on SSR flanking sequences. Four accessions of A. tsaoko were used for primer amplification specificity and efficiency testing. Eighty pairs of primers were randomly selected for synthesis; 64 of the EST-SSRs successfully amplified DNA fragments with the expected band sizes. Eventually, 18 primer pairs yielding the best amplification were chosen to analyze the genetic diversity of 72 A. tsaoko accessions from six cultivated populations (Table 6). SSR amplification profiles of primer pairs AM242, AM272, AM273, and AM278 are shown in Fig. 7. A total of 98 bands were scored, with an average of 5.4 bands per primer and a range of 3 (AM213) to 12 (AM255). The average effective number (Ne) of alleles per locus was 2.961, ranging from 1.311 (AM208) to 4.852 (AM242). The Shannon' information index (I) ranged from 0.477 (AM208) to 1.701 (AM242) with a mean of 1.183. The observed heterozygosity (Ho) ranged from 0.264 (AM208) to 1.000 (AM225) with a mean of 0.594, and the expected heterozygosity (He) ranged from 0.237 (AM208) to 0.794 (AM242) with a mean of 0.613. The value of PIC ranged from 0.223 (AM208) to 0.779 (AM247) with a mean value of 0.580. The HWE analysis showed that six loci (AM224, AM225, AM237, AM247, AM248, and AM278) significantly deviated from HWE (P < 0.05), and the remaining 12 loci (AM203, AM206, AM207, AM208, AM213, AM218, AM223, AM242, AM255, AM272, AM273, and AM279) were in accordance with HWE (Table 7). The frequencies of null alleles were low (< 0.20) for each locus, except AM247.

Table 6 Characterization of 18 EST-SSRs among 72 A. tsaoko accessions
Full size table
Fig. 7
figure 7

Electrophoretic profiles of 48 A. tsaoko accessions using four pairs of EST-SSR primers. Denatured PCR products were separated using an 8% non-denaturing polyacrylamide gel and then stained with 1% silver nitrate

Full size image
Table 7 Allelic diversity of 18 EST-SSR markers used in 72 accessions of A. tsaoko
Full size table

Population genetic diversity

At the population level, the YY population scored higher values in Ne, I, and He, while Na and Ho were higher in the LVC and LC populations, respectively. Notably, the number of private alleles (PAr) in the JP and LVC populations (0.167) was higher than that in the PB, YY, LC, and YX populations. Mean fixation index (F) values ranged from − 0.145 in the YX population to 0.015 in the YY population, with an average of − 0.066 (Table 8). The samples did not cluster according to the six different sampling sites based on the UPGMA cluster and PCoA, and all samples from different populations were not separated from each other (Fig. 8). The studied populations showed relatively low between-population genetic differentiation (Fst average = 0.052; min = 0.029, max = 0.091) and small genetic distance (GD average = 0.155, min = 0.090, max = 0.263) (Table 9). Consistent with these results, AMOVA also showed that 90% molecular variance was found within populations (Table 10).

Table 8 Genetic diversity of A. tsaoko populations based on EST-SSR markers
Full size table
Fig. 8
figure 8

Cluster analysis and principal coordinate analysis (PCoA) based on the genotyping of 72 accessions of A. tsaoko

Full size image
Table 9 Pairwise comparison of FST (above diagonal) and genetic distance (below diagonal) for six A. tsaoko populations
Full size table
Table 10 Analysis of molecular variance (AMOVA) in A. tsaoko from six populations
Full size table

Cross-species transferability

To test the transferability of the novel EST-SSR markers in different Zingiberaceae species, 18 polymorphic EST-SSR markers were tested for amplification in 11 other species. Fourteen primer pairs were successfully amplified, and the transferability rates (TR) ranged from 27.78% (Alpinia coriandriodora) to 77.78% (Alpinia zerumbet and Curcuma phaeocaulis), with an average of 68.18% (Fig. 9A). Furthermore, UPGMA phylogenetic analysis based on transferable SSR markers showed that 12 Zingiberaceae species clustered into two groups (Fig. 9B): the first class (the green shaded area indicating the genera Amomum and Alpinia) and the second class (the red shaded area indicating the genera Kaempferia, Hedychium, and Curcuma).

Fig. 9
figure 9

Cross-species transferability of 14 polymorphic EST-SSR markers in different Zingiberaceae species. The transferability rates of EST-SSR markers in 11 Zingiberaceae species (A). UPGMA phylogenetic analysis of 12 Zingiberaceae species based on transferable SSR markers (B)

Full size image

Discussion

Characterization of the Amomum tsaoko transcriptome

For species without reference genomes, transcriptome sequencing is considered the most effective way of mining functional genes and developing novel molecular markers [38, 39]. The results of this study represent the first report of transcriptome analysis and EST-SSR detection in A. tsaoko. To maximize the transcriptome information gained, mixed samples of five organs, namely roots, stem, leaves, flowers, and fruit, were collected from A. tsaoko for paired-end transcriptome sequencing. A total of 58,278,226 clean and high-quality reads with a 94.25% Q30 level, which ensures the quality of sequencing. In the present study, the N50 sizes of generated unigenes (2002 bp) were obviously longer than those in the Zingiberaceae family, such as A. villosum (N50 = 1381 bp) [15], C. wenyujin (N50 = 1566 bp) [40], Curcuma longa (N50 = 1515 bp) [41], Curcuma alismatifolia (N50 = 1501 bp) [42], Zingiber officinale (N50 = 1077 bp) [43], and Elettaria cardamomum (N50 = 616–664 bp) [44].

Among them, 128,174 unigenes were annotated to 7 major databases, such as GO, KEGG, NR, and KOG, accounting for 87.24% of the total unigenes. These annotated unigenes provide a reference basis for the study of metabolic pathways, gene function classification, plant hormone signal transduction, and quality character analysis of A. tsaoko. In addition, there are 18,737 unigenes unannotated. It is speculated that these unigenes may be specific new genes of A. tsaoko or that the non-coding RNA sequence and public gene database are imperfect [45,46,47]. Based on NR alignment results, most of the unigenes were annotated to Musa acuminata (80.4% similarity), similar to the report in Curcuma alismatifolia (Zingiberaceae family) (80.4% similarity) [42]. Zingiberaceae (A. tsaoko) and Musaceae (Musa acuminata) belong to Zingiberacea, and both are tropical plants, which may explain the large number of homologous genes between them [48]. In addition, 8.3% of the homologous sequences have not been matched, which may because some unigene fragments are too small to match a single data sequence. A. tsaoko can be divided into 3 major categories and 55 subcategories in GO functional classification, mainly focusing on cellular part, catalytic activity, and metabolic process. The same outcome was found in the transcriptomic study of A. villosum from congeneric species [15]. Volatile terpenoids are the active metabolites in the essential oil of A. tsaoko, but the terpene synthases (TPS) responsible for their biosynthesis remain unknown. In our study, the KEGG enrichment analysis found that 496 unigenes were enriched in the metabolic pathways of terpenoids, which will provide a better understanding of terpenoid biosynthesis in A. tsaoko. The DDXXD conserved motifs contained in the amino acid sequence of Cluster-24,134.3 binds catalytic substrates (such as GPP) through complexation with metal ions (such as Mg2+), which is shared by ionization-dependent terpenoid synthases belonging to the monoterpene synthase functional domain [49, 50]. The phylogenetic tree based on amino acid sequences showed that Cluster-24,134.3 had the highest homology with the AvTPS2 identified in A. villosum, which is in the same genus, and was quite different from the 1,8-cineole synthase gene of Arabidopsis and Salvia officinalis. This may be because the phylogeny and lineage differentiation of angiosperm TPS are closely related to the natural plant classification system, and the similarity of TPS from similar species is much higher than that of TPS from different sources with the same function [51]. Follow-up cloning and functional verification of the corresponding genes of Cluster-24,134.3 are necessary.

Frequency and distribution of EST-SSRs

Molecular marker technology has been widely used in various fields of plant sciences, including germplasm resource identification, genetic diversity, new variety breeding, and map construction [18]. Among them, SSRs are known as a marker type widely used at present. Furthermore, SSRs can be divided into two categories: genomic and expressed sequence tags (EST-SSRs). The construction of a transcriptome platform has promoted the development of DNA molecular markers to a great extent. To date, there are only a few reports about molecular markers in A. tsaoko [1, 17, 35]. Recently, 123 SSRs were identified in the A. tsaoko chloroplast genome; the mean density of SSR loci is up to 1/1.33 kb; however, they have not been validated for A. tsaoko [48]. In recent years, the use of transcriptome data to obtain sequences containing microsatellites, and the study of their genetic diversity has been successfully reported [52,53,54]. Excluding mononucleotide repeats, trinucleotides were found to be the most abundant repeats in the present study. This result was consistent with previous studies in other plants, such as Curcuma alismatifolia [42], Vicia amoena [22], and Pseudotaxus chienii [55]. Importantly, the abundance of trinucleotides in coding regions does not change the coding frame and therefore may not affect the functions of the genes [56, 57]. The most abundant dinucleotide SSR motifs were AG/CT (59.41%), a similar finding has been reported in other plant genomes [42, 53, 58, 59]. This may be because alanine (Ala) and leucine (Leu) are the amino acids with the highest frequency in proteins, while the AG/CT dinucleotide motif is present in the codons of Ala and Leu [60]. Moreover, some studies have shown that the CT motif frequently occurs in the 5′ UTRs; this motif plays an important role in regulating nucleic acid metabolism and gene expression in plants [61, 62]. Among trinucleotide repeat motifs, AGG/CCT (24.48%) occurred most commonly, agreeing with the results reported in Zantedeschia rehmannii [63], Phragmites karka [64], Amorphophallus [65], and Aspidistra saxicola [66]. It has been suggested that AGG/CCT interruptions play a protective role in genomic packaging [67, 68].

Validation of EST-SSR markers

In our study, 64 primer pairs (80%) were successfully amplified among the 80 randomly selected EST-SSRs (designated AM201-AM280) across 4 A. tsaoko accessions. Some studies have pointed out that, compared with genomic SSRs, EST-SSRs have a better amplification effect, but the polymorphism rate is relatively low [69, 70]. However, these newly developed EST-SSRs (Na = 5.444; Ho = 0.594; He = 0.613) have higher resolutions than microsatellite markers (Na = 2.000; Ho = 0.250–0.372; He = 0.432–0.456) [35] and genomic SSR markers (Na = 3.913; Ho = 0.468; He = 0.500) [1] in A. tsaoko. This phenomenon has also been reported in poplar [71]. PIC is one of the main indices used to evaluate locus polymorphisms, including high (PIC > 0.5), moderate (0.5 > PIC > 0.25), and low (PIC < 0.25) polymorphism [72]. Among the 72 accessions, the PIC values indicated a good informative level of these EST-SSRs, including 13 highly polymorphic (AM203, AM206, AM223, AM224, AM225, AM237, AM242, AM247, AM248, AM255, AM272, AM273, and AM278), four moderately polymorphic (AM207, AM213, AM218, and AM279), and only one low polymorphic (AM208) markers. EST-SSR markers exhibit much higher polymorphism than RAPD, ISSR, SRAP, and genomic SSR markers for A. tsaoko [1, 17, 34]. HWE analysis showed that 12 primer pairs (AM203, AM206, AM207, AM208, AM213, AM218, AM223, AM242, AM255, AM272, AM273, and AM279) were in accordance with HWE, while the remaining primer sets (AM224, AM225, AM237, AM247, AM248, and AM278) significantly deviated from HWE (P < 0.05). Taken together, the newly developed EST-SSRs are suitable for exploring the genetic diversity and relationships of A. tsaoko. These molecular markers will be effective tools in fingerprinting germplasm collections from different sources to guide germplasm evaluation and conservation in A. tsaoko. We also analyzed the characteristics of SSR loci within the terpenoid metabolism-related unigenes (Table S1). Next, we will develop molecular markers around these SSR loci, which is very important for gene mining and marker-assisted selection breeding for controlling important traits in A. tsaoko.

Genetic diversity of the A. tsaoko population

Genetic diversity is an important indicator of the effective management and utilization of plant germplasm resources. The level of genetic diversity is often correlated with its range of distribution; the wide distribution range of plants usually shows higher levels of genetic diversity compared with narrowly distributed plants [73, 74]. However, while the known distribution of A. tsaoko is narrow, it retains relatively high levels of genetic diversity at the population level (PPB = 98.150%, I = 1.019, Ho = 0.594, and He = 0.560). Similar results have been reported for many other plant species, such as Petunia secreta [75], Nouelia insignis [76], and Calanthe tsoongiana [77]. In our study, Jingping and Lvchun counties, as possible places of origin of A. tsaoko, harbored the highest number of private alleles (PAr = 0.167), which indicates the presence of specific sequences or genes in JP and LVC populations [78]; this was also consistent with our previous findings [17]. The overall mean value of the fixation index was − 0.066, showing an excess of heterozygosity present in the A. tsaoko population; this result is in agreement with a previous study carried out with genomic SSR markers [1]. The pairwise FST analysis (average pairwise FST = 0.052) detected no significant genetic differentiation among six A. tsaoko populations. Correspondingly, the AMOVA results also showed that much more genetic variance exists among individuals within populations. High genetic diversity, excess heterozygotes, and low genetic differentiation are characteristics of outbreeding populations [79]. A. tsaoko is a perennial cross-pollinating plant pollinated by insects (native bumblebee), allowing allele exchange among individuals in the population [17]. In this study, the accessions did not cluster according to different sampling sites by UPGMA cluster, and the PCoA analysis further confirmed low genetic differentiation among populations.

Compared with bulk crops, the molecular markers available for Zingiberaceae are very limited. In our study, the ESR-SSR markers developed in A. tsaoko have high cross-species transferability (with an average transferability of 68.18%) with other Zingiberaceae species, and these markers can accurately classify different species, making them useful for increasing the number of available molecular markers of Zingiberaceae species.

Conclusions

In this study, we reported the first transcriptome sequencing analysis of A. tsaoko using Illumina sequencing technology. The de novo assembly generated a total of 146,911 unigenes with an average length of 1527 bp and an N50 of 2002 bp. In total, 128,174 unigenes were successfully annotated to the NR (84.01%), NT (65.20%), KEGG (36.11%), Swiss-prot (65.84%), PFAM (60.97%), GO (61.09%), and KOG (24.92%) databases. 496 unigenes involved in the terpenoid biosynthesis pathway were identified. Based on the transcriptome assembly, 55,590 potential EST-SSRs were identified and characterized. Seventy-two A. tsaoko accessions using 18 novel polymorphic EST-SSR primers showed rich genetic diversity and low genetic differentiation among populations. The transcriptome data from this study will provide valuable resources for investigating gene functions, and the EST-SSR markers developed will provide a foundation for germplasm identification, genetic diversity assessment, and marker-assisted breeding in A. tsaoko.

Methods

Plant material

The transcriptome sequencing materials were collected from the young roots, stems, leaves, flowers, and fruits of 5-year-old A. tsaoko plants in Caoguoshan Village, Adebo Township, Jinping County, Honghe Prefecture, Yunnan Province, China (22°54′30.34″N, 103°13′16.39″E). To verify EST-SSR markers, young leaves from a total of 72 A. tsaoko accessions were collected from different sites covering the plant’s major distribution areas in China (Fig. 10; Table S2). For cross-species transferability analysis, 12 Zingiberaceae species were used, which consisted of two species in the genus Amomum (A. tsaoko and A. villosum), two species in Kaempferia (K. galangal and K. rotunda), two species in Hedychium (H. flavum and H. coronarium), and three species in Curcuma (C. kwangsiensis, C. caesia, and C. phaeocaulis) (Table S3). No approval or permission was required to collect these samples. All the species were identified by Professor Bingyue Lu (Honghe University). The genomic DNA was extracted from leaf tissues using a modified cetyltrimethylammonium bromide (CTAB) method [80].

Fig. 10
figure 10

Geographic locations of the 6 populations of A. tsaoko included in this study

Full size image

RNA isolation, library preparation, and transcriptome sequencing

Total RNA was extracted from three biological replicates (with two technical replicates per each biological replicate) from mixed samples of the five different organs using the RNeasy extraction kit (QIAGEN, Beijing, China). The integrity and purity of extracted RNA were measured by a NanoDrop spectrophotometer and agarose gel electrophoresis. After total RNA extraction, eukaryotic mRNA was enriched with Oligo (dT) beads. Next, fragmentation buffer was added to break mRNA into short fragments. Then, these mRNA fragments were used to synthesize first-strand cDNA with hexameric random primers. Subsequently, second-strand cDNA was synthesized by adding DNA polymerase I, RNase H, dNTPs, and buffer. The purified double-stranded cDNA was repaired at the end, dA-tailed fragments were added, and it was connected to the sequencing connector. After library inspection, the quality-qualified libraries were sequenced using the Illumina HiSeq platform (Novogene Biotech Co., Ltd., Beijing, China).

De novo assembly and annotation

After sequencing, raw data were filtered, and high-quality clean data were obtained by removing the joint sequence and low-quality reads. High-quality reads were used for de novo assembly using Trinity software [81]. Finally, we obtained sequences that could not be extended on either end, which were considered unigenes. The resulting clean data were deposited in the Sequence Read Archive of National Center for Biotechnology Information (NCBI) (Bioproject no. PRJNA735890; Biosample no. SAMN19601270). The assembled A. tsaoko transcripts were compared with the NCBI non-redundant protein sequences (NR), NCBI non-redundant nucleotide sequences (NT), protein family (PFAM), eukaryotic clusters of orthologous groups (KOG), a manually annotated and reviewed protein sequence (SwissProt), and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases using the BLASTX algorithm (significant thresholds of E-value < 10− 5), and Gene Ontology (GO) annotations were obtained using Blast2GO software (http://www.geneontology.org) based on NR annotations.

Development and characterization of EST-SSRs

Based on the transcriptome sequencing data of A. tsaoko, MISA software (https://webblast.ipk-gatersleben.de/misa/) was used to search the SSR loci of A. tsaoko. The search criteria were as follows: mono- to hexa-nucleotide repeats ≥10, 6, 5, 5, 5, and 5; mono- to hexa-nucleotide repeat types are labeled P1, P2, P3, P4, P5, and P6. Primer3 (http://primer3.sourceforge.net/releases.php) was used to design SSR primers based on the detected sites.

SSR analysis

Eighty pairs of EST-SSR primers were randomly synthesized, and four A. tsaoko germplasm resources with different fruit shapes (round type, oval type, long type, and shuttle type) were selected to verify the effectiveness and polymorphisms of the primers. The primers producing clear bands and obvious polymorphisms were subsequently used for genetic diversity assessments. The PCR reaction system, amplification program, and gel electrophoresis were as previously described [1].

Data analysis

According to the polyacrylamide electrophoresis results, at the same migration location, a band is marked as “1,” no band is marked as “0,” and a missing band is indicated by “-”. Subsequently, 0/1 data were preprocessed using DataFormater software [82], which transformed SSR data into readable input files for NTSYS-pc and PowerMarker. The GenAlEx 6.501 program [83] was employed to calculate genetic diversity parameters, namely the observed number of alleles (Na), the effective number of alleles (Ne), Shannon’s information index (I), expected heterozygosity (He), observed heterozygosity (Ho), number of private alleles (PAr), and fixation index (F), which was used to assess Hardy–Weinberg genetic equilibrium. PowerMarker v3.25 [84] was used to estimate the polymorphism information content (PIC) of each EST-SSR primer pair. We estimated the frequencies of null alleles (FNA) using Micro-checker 2.2.3 [85]. The genetic differentiation between populations was carried out using analysis of molecular variance (AMOVA), pairwise FST, and pairwise Nei’s genetic distance in GenAlEx software. Cluster analysis (unweighted pair group method with arithmetic mean algorithm) and principal coordinate analysis (PCoA) were performed using NTSYS-pc software [86] and GenAlEx v6.5, respectively. Multiple amino acid sequence alignment and phylogenetic analysis was performed using DNAMAN 8.0 and MEGA version 5.2 software. The amino acid sequences of the 1,8-cineole synthase gene of Arabidopsis thaliala (GenBank accession no. NM_113483.5) and Salvia officinalis (GenBank accession no. AF051899.1) were downloaded from the NCBI (http://www.ncbi.nlm.nih.gov/). The amino acid sequences of four monoterpene synthase genes (AvTPS1, AvTPS2, AvTPS3, and AvTPS4) of A. villosum were obtained from the published literature [87].

Availability of data and materials

The original sequencing data generated in the study have been deposited into the National Center for Biotechnology Information (NCBI) Sequence Read Archive (SRA) database (https://www.ncbi.nlm.nih.gov/bioproject/?term=PRJNA735890). The EST sequences in this study have been submitted to GenBank with accession numbers OM468473–OM468552 (https://www.ncbi.nlm.nih.gov/genbank/). Other datasets supporting the conclusions of this article are included within the article.

Abbreviations

EST-SSR:

Expressed sequence tag-simple sequence repeat

AMOVA:

Analysis of molecular variance

TCM:

Traditional Chinese medicine

COVID:

Coronavirus disease

IUCN:

International union for conservation of nature

RFLP:

Restriction fragment length polymorphism

RAPD:

Random amplified polymorphic DNA

ISSR:

Inter-simple sequence repeat

SSR:

Simple sequence repeat

SNP:

Single nucleotide polymorphism

QTL:

Quantitative trait locus

CTAB:

Cetyltrimethylammonium bromide

NR:

NCBI non-redundant protein sequences

NT:

NCBI non-redundant nucleotide sequences

PFAM:

Protein family

KOG:

Eukaryotic clusters of orthologous groups

SwissProt:

A manually annotated and reviewed protein sequence

KEGG:

Kyoto encyclopedia of genes and genomes

GO:

Gene ontology

Na:

Observed number of alleles

Ne:

Effective number of alleles

I:

Shannon’s information index

He:

Expected heterozygosity

Ho:

Observed heterozygosity

PAr:

Number of private alleles

F:

Fixation index

FNA:

Frequencies of null alleles

UPGMA:

Unweighted pair-group method with arithmetic means

PCoA:

Principal coordinate analysis

HWE:

Hardy–Weinberg genetic equilibrium

References

  1. Lu BY, Ma ML, Zhang W, Meng HL, Lei E, Wang TT, et al. Development of 23 novel microsatellite markers of Amomum tsao-ko (Zingiberaceae) based on restriction-site-associated DNA sequencing. Mol Biol Rep. 2021;48(2):1943–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Zhang TT, Lu CL, Jiang JG. Antioxidant and anti-tumour evaluation of compounds identified from fruit of Amomum tsaoko Crevost et Lemaire. J Funct Foods. 2015;18(423–4):31.

    Google Scholar 

  3. Zhang XF, Tang YJ, Guan XX, Lu X, Li J, Chen XL, et al. Flavonoid constituents of Amomum tsao-ko Crevost et Lemarie and their antioxidant and antidiabetic effects in diabetic rats - in vitro and in vivo studies. Food Funct. 2022;13(1):437–50.

    Article  PubMed  Google Scholar 

  4. Guo N, Zang YP, Cui Q, Gai QY, Jiao J, Wang W, et al. The preservative potential of Amomum tsaoko essential oil against E. coil, its antibacterial property and mode of action. Food Control. 2017;75:236–45.

    Article  CAS  Google Scholar 

  5. Hong SS, Lee JE, Jung YW, Park JH, Lee JA, Jeong W, et al. Monoterpenoids from the fruits of Amomum tsao-ko have inhibitory effects on nitric oxide production. Plants (Basel). 2021;10(2):257.

    Article  CAS  Google Scholar 

  6. He XF, Chen JJ, Huang XY, Hu J, Zhang XK, Guo YQ, et al. The antidiabetic potency of Amomum tsao-ko and its active flavanols, as PTP1B selective and alpha-glucosidase dual inhibitors. Ind Crop Prod. 2021;160:112908.

    Article  CAS  Google Scholar 

  7. Chen C, You F, Wu FH, Luo YS, Zheng GH, Xu HL, et al. Antiangiogenesis efficacy of ethanol extract from Amomum tsaoko in ovarian cancer through inducing ER stress to suppress p-STAT3/NF-kB/IL-6 and VEGF loop. Evid-based Compl Alt. 2020;2020:2390125.

    Google Scholar 

  8. Wang KN, Liu YN, Shi Y, Yan MZ, Rengarajan T, Feng X. Amomum tsaoko fruit extract exerts anticonvulsant effects through suppression of oxidative stress and neuroinflammation in a pentylenetetrazol kindling model of epilepsy in mice. Saudi J Biol Sci. 2021;28(8):4247–54.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Zong Y, Ding ML, Jia KK, Ma ST, Ju WZ. Exploring active compounds of Da-Yuan-Yin in treatment of COVID-19 based on network pharmacology and molecular docking method. Chin Tradit Herb Drugs. 2020;51:836–44.

    Google Scholar 

  10. Lee DYW, Li QY, Liu J, Efferth T. Traditional Chinese herbal medicine at the forefront battle against COVID-19: clinical experience and scientific basis. Phytomedicine. 2021;80:153337.

    Article  CAS  PubMed  Google Scholar 

  11. Li XR, Wen ZS, Si MD, Jia YX, Liu HX, Zheng YG, et al. Exploration of Hanshi Zufei prescription for treatment of COVID-19 based on network pharmacology. Chin Herb Med. 2022;14(2):294–302.

    Article  PubMed  PubMed Central  Google Scholar 

  12. Zhu YW, Yan XF, Ye TJ, Hu J, Wang XL, Qiu FJ, et al. Analyzing the potential therapeutic mechanism of Huashi Baidu decoction on severe COVID-19 through integrating network pharmacological methods. J Tradit Complement Med. 2021;11(2):180–7.

    Article  PubMed  PubMed Central  Google Scholar 

  13. Liu JZ, Lyu HC, Fu YJ, Cui Q. Amomum tsao-ko essential oil, a novel anti-COVID-19 omicron spike protein natural products: a computational study. Arab J Chem. 2022;15(7):103916.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Yang SY, Xue YF, Chen DJ, Wang ZT. Amomum tsao-ko Crevost & Lemarié: a comprehensive review on traditional uses, botany, phytochemistry, and pharmacology. Phytochem Rev. 2022;10:1–35.

    Google Scholar 

  15. He XY, Wang H, Yang JF, Deng K, Wang T. RNA sequencing on Amomum villosum Lour. Induced by MeJA identifies the genes of WRKY and terpene synthases involved in terpene biosynthesis. Genome. 2018;61(2):91–102.

    Article  CAS  PubMed  Google Scholar 

  16. de Boer H, Newman M, Poulsen AD, Droop AJ, Fer T, Hien LTT, et al. Convergent morphology in Alpinieae (Zingiberaceae): Recircumscribing Amomum as a monophyletic genus. Taxon. 2018;67(1):6–36.

    Article  Google Scholar 

  17. Ma ML, Wang TT, Lu BY. Assessment of genetic diversity in Amomum tsao-ko Crevost & Lemarie, an important medicine food homologous crop from Southwest China using SRAP and ISSR markers. Genet Resour Crop Ev. 2021;68(6):2655–67.

    Article  Google Scholar 

  18. Agarwal M, Shrivastava N, Padh H. Advances in molecular marker techniques and their applications in plant sciences. Plant Cell Rep. 2008;27(4):617–31.

    Article  CAS  PubMed  Google Scholar 

  19. Ismail NA, Rafii MY, Mahmud TMM, Hanafi MM, Miah G. Molecular markers: a potential resource for ginger genetic diversity studies. Mol Biol Rep. 2016;43(12):1347–58.

    Article  CAS  PubMed  Google Scholar 

  20. Powell W, Machray GC, Provan J. Polymorphism revealed by simple sequence repeats. Trends Plant Sci. 1996;1(7):215–22.

    Article  Google Scholar 

  21. Lu J, Zhang YC, Diao X, Yu K, Dai XW, Qu P, et al. Evaluation of genetic diversity and population structure of Fragaria nilgerrensis using EST-SSR markers. Gene. 2021;796:145791.

    Article  PubMed  Google Scholar 

  22. Wu FF, Zhang SX, Gao Q, Liu F, Wang JL, Wang XG. Genetic diversity and population structure analysis in a large collection of Vicia amoena in China with newly developed SSR markers. BMC Plant Biol. 2021;21(1):544.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Wu HB, He XL, Gong H, Luo SB, Li MZ, Chen JQ, et al. Genetic linkage map construction and QTL analysis of two interspecific reproductive isolation traits in sponge gourd. Front Plant Sci. 2016;7:980.

    Article  PubMed  PubMed Central  Google Scholar 

  24. Lu BY, Yang CY, Xie K, Zhang L, Wu T, Li LF, et al. Quantitative trait loci for grain-quality traits across a rice F2 population and backcross inbred lines. Euphytica. 2013;192(1):25–35.

    Article  Google Scholar 

  25. Bharadwaj C, Tripathi S, Soren KR, Thudi M, Singh RK, Sheoran S, et al. Introgression of “QTL-hotspot” region enhances drought tolerance and grain yield in three elite chickpea cultivars. Plant Genome. 2021;14(1):e20076.

    Article  CAS  PubMed  Google Scholar 

  26. Karunarathna KHT, Mewan KM, Weerasena O, Perera S, Edirisinghe ENU. A functional molecular marker for detecting blister blight disease resistance in tea (Camellia sinensis L.). Plant Cell Rep. 2021;40(2):351–9.

    Article  CAS  PubMed  Google Scholar 

  27. Cui Q, Wang LT, Liu JZ, Wang HM, Guo N, Gu CB, et al. Rapid extraction of Amomum tsao-ko essential oil and determination of its chemical composition, antioxidant and antimicrobial activities. J Chromatogr B. 2017;1061:364–71.

    Article  Google Scholar 

  28. Liu LJ, Zhao YM, Ming J, Chen J, Zhao GH, Chen ZY, et al. Polyphenol extract and essential oil of Amomum tsao-ko equally alleviate hypercholesterolemia and modulate gut microbiota. Food Funct. 2021;12(23):12008–21.

    Article  CAS  PubMed  Google Scholar 

  29. Kim JG, Jang H, Le TPL, Hong HR, Lee MK, Hong JT, et al. Pyranoflavanones and pyranochalcones from the fruits of Amomum tsao-ko. J Nat Prod. 2019;82(7):1886–92.

    Article  CAS  PubMed  Google Scholar 

  30. Wang Y, You CX, Wang CF, Yang K, Chen R, Zhang WJ, et al. Chemical constituents and insecticidal activities of the essential oil from Amomum tsaoko against two stored-product insects. J Oleo Sci. 2014;63(10):1019–26.

    Article  CAS  PubMed  Google Scholar 

  31. He XF, Wang HM, Geng CA, Hu J, Zhang XM, Guo YQ, et al. Amomutsaokols A-K, diarylheptanoids from Amomum tsao-ko and their alpha-glucosidase inhibitory activity. Phytochemistry. 2020;177:112418.

    Article  CAS  PubMed  Google Scholar 

  32. Qin HW, Wang YZ, Yang WZ, Yang SB, Zhang JY. Comparison of metabolites and variety authentication of Amomum tsao-ko and Amomum paratsao-ko using GC-MS and NIR spectroscopy. Sci Rep. 2021;11(1):15200.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Zhang W, Lu BY, Meng HL, Wei X, Yang ZQ, Yang SC. Phenotypic diversity analysis of the fruit of Amomum tsao-ko Crevost et Lemarie, an important medicinal plant in Yunnan, China. Genet Resour Crop Ev. 2019;66(5):1145–54.

    Article  Google Scholar 

  34. Lu BY, Ma ML, Wang TT, Meng HL, Lei E, Zhang W. Genetic diversity and genetic relationships of Amomum tsao-ko based on random amplified polymorphic DNA markers. Int J Agric Biol. 2018;20(9):2032–8.

    Google Scholar 

  35. Yang YW, Yang ZY, Yan MR, Qian ZG, Guan KY. Isolation and characterization of microsatellite markers for Amomum tsaoko (Zingiberaceae), an economically important plant in China. Genet Mol Res. 2014;13(4):8220–4.

    Article  PubMed  Google Scholar 

  36. Guo JD, Huang Z, Sun JL, Cui XM, Liu Y. Research progress and future development trends in medicinal plant transcriptomics. Front Plant Sci. 2021;12:691838.

    Article  PubMed  PubMed Central  Google Scholar 

  37. Madritsch S, Burg A, Sehr EM. Comparing de novo transcriptome assembly tools in di- and autotetraploid non-model plant species. BMC Bioinformatics. 2021;22(1):146.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Unamba CIN, Nag A, Sharma RK. Next generation sequencing technologies: the doorway to the unexplored genomics of non-model plants. Front Plant Sci. 2015;6:1074.

    Article  PubMed  PubMed Central  Google Scholar 

  39. Zalapa JE, Cuevas H, Zhu HY, Steffan S, Senalik D, Zeldin E, et al. Using next-generation sequencing approaches to isolate simple sequence repeat (SSR) loci in the plant sciences. Am J Bot. 2012;99(2):193–208.

    Article  CAS  PubMed  Google Scholar 

  40. Chen R, Wei QH, Liu YH, Wei X, Chen XB, Yin XP, et al. Transcriptome sequencing and functional characterization of new sesquiterpene synthases from Curcuma wenyujin. Arch Biochem Biophys. 2021;709:108986.

    Article  CAS  PubMed  Google Scholar 

  41. Annadurai RS, Neethiraj R, Jayakumar V, Damodaran AC, Rao SN, Katta M, et al. De novo transcriptome assembly (NGS) of Curcuma longa L. rhizome reveals novel transcripts related to anticancer and antimalarial terpenoids. PLoS One. 2013;8(2):e56217.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Taheri S, Abdullah TL, Rafii MY, Harikrishna JA, Werbrouck SPO, Teo CH, et al. De novo assembly of transcriptomes, mining, and development of novel EST-SSR markers in Curcuma alismatifolia (Zingiberaceae family) through Illumina sequencing. Sci Rep. 2019;9:3047.

    Article  PubMed  PubMed Central  Google Scholar 

  43. Jiang YS, Huang MJ, Wisniewski M, Li HL, Zhang MX, Tao X, et al. Transcriptome analysis provides insights into gingerol biosynthesis in ginger (Zingiber officinale). Plant Genome. 2018;11(3):1–11.

    Article  Google Scholar 

  44. Nadiya F, Anjali N, Thomas J, Gangaprasad A, Sabu KK. Transcriptome profiling of Elettaria cardamomum (L.) Maton (small cardamom). Genom Data. 2017;11:102–3.

    Article  CAS  PubMed  Google Scholar 

  45. Liu MY, Qiao GR, Jiang J, Yang HQ, Xie LH, Xie JZ, et al. Transcriptome sequencing and de novo analysis for Ma bamboo (Dendrocalamus latiflorus Munro) using the Illumina platform. PLoS One. 2012;7(10):e46766.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Shi X, Sun HJ, Chen YT, Pan HW, Wang SF. Transcriptome sequencing and expression analysis of cadmium (cd) transport and detoxification related genes in cd-accumulating Salix integra. Front Plant Sci. 2016;7:1577.

    Article  PubMed  PubMed Central  Google Scholar 

  47. Shen SS, Chai XT, Zhou Q, Luo D, Wang YR, Liu ZP. Development of polymorphic EST-SSR markers and characterization of the autotetraploid genome of sainfoin (Onobrychis viciifolia). Peer J. 2019;7:e6542.

    Article  PubMed  PubMed Central  Google Scholar 

  48. Ma ML, Lu BY. The complete chloroplast genome of Amomum tsao-ko. Mitochondrial DNA B. 2020;5(1):848–9.

    Article  Google Scholar 

  49. Oldfield E, Lin FY. Terpene biosynthesis: modularity rules. Angew Chem Int Ed Engl. 2012;51(5):1124–37.

    Article  CAS  PubMed  Google Scholar 

  50. Christianson DW. Structural and chemical biology of Terpenoid Cyclases. Chem Rev. 2017;117(17):11570–648.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Bohlmann J, Meyer-Gauen G, Croteau R. Plant terpenoid synthases: molecular biology and phylogenetic analysis. Proc Natl Acad Sci U S A. 1998;95(8):4126–33.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Ruan XX, Wang Z, Wang T, Su YJ. Characterization and application of EST-SSR markers developed from the transcriptome of Amentotaxus argotaenia (Taxaceae), a relict vulnerable conifer. Front Genet. 2019;10:1014.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Li S, Ji FF, Hou FF, Cui HL, Shi QQ, Xing GM, et al. Characterization of Hemerocallis citrina transcriptome and development of EST-SSR markers for evaluation of genetic diversity and population structure of Hemerocallis collection. Front Plant Sci. 2020;11:686.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Vu DD, Shah SNM, Pham MP, Bui VT, Nguyen MT, Nguyen TPT. De novo assembly and transcriptome characterization of an endemic species of Vietnam, Panax vietnamensis ha et Grushv., including the development of EST-SSR markers for population genetics. BMC Plant Biol. 2020;20(1):358.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Xu RX, Wang Z, Su YJ, Wang T. Characterization and development of microsatellite markers in Pseudotaxus chienii (Taxaceae) based on transcriptome sequencing. Front Genet. 2020;11:574304.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. Bazzo BR, de Carvalho LM, Carazzolle MF, Pereira GAG, Colombo CA. Development of novel EST-SSR markers in the macauba palm (Acrocomia aculeata) using transcriptome sequencing and cross-species transferability in Arecaceae species. BMC Plant Biol. 2018;18(1):276.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. Qi WH, Jiang XM, Yan CC, Zhang WQ, Xiao GS, Yue BS, et al. Distribution patterns and variation analysis of simple sequence repeats in different genomic regions of bovid genomes. Sci Rep. 2018;8:14407.

    Article  PubMed  PubMed Central  Google Scholar 

  58. Zhang Y, Zhang X, Wang YH, Shen SK. De novo assembly of transcriptome and development of novel EST-SSR markers in Rhododendron rex Levl. Through Illumina sequencing. Front. Plant Sci. 2017;8:1664.

    Google Scholar 

  59. Zhang ZY, Xie WG, Zhao YQ, Zhang JC, Wang N, Ntakirutimana F, et al. EST-SSR marker development based on RNA-sequencing of E. sibiricus and its application for phylogenetic relationships analysis of seventeen Elymus species. BMC Plant Biol. 2019;19:235.

    Article  PubMed  PubMed Central  Google Scholar 

  60. Chen LY, Cao YN, Yuan N, Nakamura K, Wang GM, Qiu YX. Characterization of transcriptome and development of novel EST-SSR makers based on next-generation sequencing technology in Neolitsea sericea (Lauraceae) endemic to east Asian land-bridge islands. Mol Breed. 2015;35(9):1–15.

    Article  Google Scholar 

  61. Martienssen RA, Colot V. DNA methylation and epigenetic inheritance in plants and filamentous fungi. Science. 2001;293(5532):1070–4.

    Article  CAS  PubMed  Google Scholar 

  62. Morgante M, Hanafey M, Powell W. Microsatellites are preferentially associated with nonrepetitive DNA in plant genomes. Nat Genet. 2002;30(2):194–200.

    Article  CAS  PubMed  Google Scholar 

  63. Wei Z, Sun ZZ, Cui BB, Zhang QX, Xiong M, Wang X, et al. Transcriptome analysis of colored calla lily (Zantedeschia rehmannii Engl.) by Illumina sequencing: de novo assembly, annotation and EST-SSR marker development. Peer J. 2016;4:e2378.

    Article  PubMed  PubMed Central  Google Scholar 

  64. Nayak SS, Pradhan S, Sahoo D, Parida A. De novo transcriptome assembly and analysis of Phragmites karka, an invasive halophyte, to study the mechanism of salinity stress tolerance. Sci Rep. 2020;10(1):5192.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  65. Zheng XF, Pan C, Diao Y, You YN, Yang CZ, Hu ZL. Development of microsatellite markers by transcriptome sequencing in two species of Amorphophallus (Araceae). BMC Genomics. 2013;14:490.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  66. Huang DN, Zhang YQ, Jin MD, Li HK, Song ZP, Wang YG, et al. Characterization and high cross-species transferability of microsatellite markers from the floral transcriptome of aspidistra saxicola (Asparagaceae). Mol Ecol Resour. 2014;14(3):569–77.

    Article  CAS  PubMed  Google Scholar 

  67. Jarem DA, Huckaby LV, Delaney S. AGG interruptions in (CGG)(n) DNA repeat tracts modulate the structure and thermodynamics of non-B conformations in vitro. Biochemistry. 2010;49(32):6826–37.

    Article  CAS  PubMed  Google Scholar 

  68. Volle CB, Delaney S. AGG/CCT interruptions affect nucleosome formation and positioning of healthy-length CGG/CCG triplet repeats. BMC Biochem. 2013;14:33.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  69. Biswas MK, Bagchi M, Nath UK, Biswas D, Natarajan S, Jesse DMI, et al. Transcriptome wide SSR discovery cross-taxa transferability and development of marker database for studying genetic diversity population structure of Lilium species. Sci Rep. 2020;10(1):18621.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  70. Varshney RK, Graner A, Sorrells ME. Genic microsatellite markers in plants: features and applications. Trends Biotechnol. 2005;23(1):48–55.

    Article  CAS  PubMed  Google Scholar 

  71. Wu QC, Zang FQ, Xie XM, Ma Y, Zheng YQ, Zang DK. Full-length transcriptome sequencing analysis and development of EST-SSR markers for the endangered species Populus wulianensis. Sci Rep. 2020;10(1):16249.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  72. Botstein D, White RL, Skolnick M, Davis RW. Construction of a genetic linkage map in man using restriction fragment length polymorphisms. Am J Hum Genet. 1980;32(3):314–31.

    CAS  PubMed  PubMed Central  Google Scholar 

  73. Hamrick JL, Godt MJW. Effects of life history traits on genetic diversity in plant species. Phil Trans R Soc Lond B. 1996;351(1345):1291–8.

    Article  Google Scholar 

  74. Nybom H. Comparison of different nuclear DNA markers for estimating intraspecific genetic diversity in plants. Mol Ecol. 2004;13(5):1143–55.

    Article  CAS  PubMed  Google Scholar 

  75. Turchetto C, Segatto ALA, Mader G, Rodrigues DM, Bonatto SL, Freitas LB. High levels of genetic diversity and population structure in an endemic and rare species: implications for conservation. Aob Plants. 2016;8:plw002.

    Article  PubMed  PubMed Central  Google Scholar 

  76. Luan SS, Chiang TY, Gong X. High genetic diversity vs. low genetic differentiation in Nouelia insignis (Asteraceae), a narrowly distributed and endemic species in China, revealed by ISSR fingerprinting. Ann Bot. 2006;98(3):583–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  77. Qian X, Wang CX, Tian M. Genetic diversity and population differentiation of Calanthe tsoongiana, a rare and endemic orchid in China. Int J Mol Sci. 2013;14(10):20399–413.

    Article  PubMed  PubMed Central  Google Scholar 

  78. Saboori S, Noormohammadi Z, Sheidai M, Marashi S. SCoT molecular markers and genetic fingerprinting of date palm (Phoenix dactylifera L.) cultivars. Genet Resour Crop Evol. 2020;67(1):73–82.

    Article  CAS  Google Scholar 

  79. Garcia-Arias FL, Osorio-Guarin JA, Zarantes VMN. Association study reveals novel genes related to yield and quality of fruit in cape gooseberry (Physalis peruviana L.). front. Plant Sci. 2018;9:362.

    Google Scholar 

  80. Doyle JJ, Doyle JL. A rapid DNA isolation procedure for small quantities of fresh leaf tissue. Phytochem Bull. 1987;19(1):11–5.

    Google Scholar 

  81. Grabherr MG, Haas BJ, Yassour M, Levin JZ, Thompson DA, Amit I, et al. Full-length transcriptome assembly from RNA-Seq data without a reference genome. Nat Biotechnol. 2011;29(7):644–U130.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  82. Fan WQ, Gai HM, Sun X, Zhang ZF, Ren M. DataFormater, a software for SSR data formatting to develop population genetics analysis. Mol Plant Breed. 2016;14(1):265–70.

    Google Scholar 

  83. Peakall R, Smouse PE. GenAlEx 6.5: genetic analysis in excel. Population genetic software for teaching and research-an update. Bioinformatics. 2012;28(19):2537–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  84. Liu KJ, Muse SV. PowerMarker: an integrated analysis environment for genetic marker analysis. Bioinformatics. 2005;21(9):2128–9.

    Article  CAS  PubMed  Google Scholar 

  85. Van Oosterhout C, Hutchinson WF, Wills DPM, Shipley P. MICRO-CHECKER: software for identifying and correcting genotyping errors in microsatellite data. Mol Ecol Notes. 2004;4(3):535–8.

    Article  Google Scholar 

  86. Rohlf F. NTSYSpc: numerical taxonomy and multivariate system. Version 2.1 Exeter software. New York: Applied Biostatics Inc; 2000.

    Google Scholar 

  87. Wang H, Ma DM, Yang JF, Deng K, Li M, Ji XY, et al. An integrative volatile Terpenoid profiling and transcriptomics analysis for Gene Mining and functional characterization of AvBPPS and AvPS involved in the Monoterpenoid biosynthesis in Amomum villosum. Front Plant Sci. 2018;9:846.

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

We thank Accdon (www.accdon.com) for its linguistic assistance during the preparation of this manuscript.

Funding

This work was funded the Special Basic Cooperative Research Programs of Yunnan Provincial Undergraduate Universities’ Association (No. 202001BA070001–181), the Youth Top-notch Talent Support Program of Yunnan Province (No. YNWR–QNBJ–2020–207) and the National Natural Science Foundation of China (No. 82260735, 31460380).

Author information

Authors and Affiliations

  1. Key Laboratory for Research and Utilization of Characteristic Biological Resources in Southern Yunnan, Honghe University, Mengzi, 661199, China

    Mengli Ma, Hengling Meng, Wei Zhang & Bingyue Lu

  2. College of Biological and Agricultural Sciences, Honghe University, Mengzi, 661199, China

    En Lei, Tiantao Wang, Wei Zhang & Bingyue Lu

Authors
  1. Mengli Ma
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Hengling Meng
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. En Lei
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Tiantao Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Wei Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Bingyue Lu
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

BL conceived and designed the experiments; BL, EL, and TW collected A. tsaoko samples; MM, HM, and WZ performed the experiments; BL, and MM analyzed the data and wrote the manuscript. All authors reviewed and approved the manuscript.

Corresponding author

Correspondence to Bingyue Lu.

Ethics declarations

Ethics approval and consent to participate

Amomum tsaoko is neither wild nor endangered in China, and no specific permission was required for the collection. The study complied with relevant institutional, national, and international guidelines and legislation.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no conflicts of interest.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Additional file 1: Table S1.

Analysis of SSR loci of terpenoid metabolic pathway-related unigenes in A. tsaoko. Table S2. Populations of A. tsaoko from different locations in the study. Table S3. Sampling location information of 12 Zingiberaceae species.

Additional file 2: Fig. S1.

The original image of electrophoretic using AM242, AM272, AM273, and AM278 primer pairs.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Ma, M., Meng, H., Lei, E. et al. De novo transcriptome assembly, gene annotation, and EST-SSR marker development of an important medicinal and edible crop, Amomum tsaoko (Zingiberaceae). BMC Plant Biol 22, 467 (2022). https://doi.org/10.1186/s12870-022-03827-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s12870-022-03827-y

Keywords

BMC Plant Biology

ISSN: 1471-2229

Contact us