Transcriptome sequencing, and de novo assembly
Two cDNA libraries were constructed from the total RNA of R. molle flower and root, respectively. The libraries were sequenced using the Illumina HiSeq 2000 platform and approximately 26.58 Gb of clean data (89 million reads) were generated. The quality check showed that the base quality was above Q30 for 92% reads, and raw reads were trimmed prior to assembly. The adapter and low quality reads were trimmed, and the short reads (<50 bp) were also removed. Then, 47,559,180 and 41,387,924 high quality reads were obtained from the flowers and root libraries, respectively, for further analysis. Trinity software and TGI clustering tool (TGICL) were used for the de novo assembly and removed redundant clusters, a total of 100,603 unigenes were generated, with average length of 778 bp, the N50 length of 1,384 bp, and the GC content of 47.7%. 40.88% (41,129) of the assembled unigenes were longer than 500 bp, and 20.96% (20,886) longer than 1000 bp. The length of the most unigenes fell between 200 bp and 2000 bp, as shown in Additional file 4: FigureS1a. Additionally, a total of 76,198 coding sequences (CDS) with average length 515 bp were predicted, including 20,213 (26.5%) complete CDSs. Among all predicted CDSs 18,106 (23.8%) were longer than 200 bp in length (Additional file 4: Figure S1b). The highly qualified sequencing results would be in favor of subsequent functional annotations.
Functional annotation
For comprehensive annotation of assembled unigenes, sequence similarity search was performed against eight public databases. The result indicated that total 57,416 (57.1%) unigenes had significant matches in these public databases, while others were uninformative (e.g. “unknown” “unnamed” or “hypothetical protein”). Maximum annotation (56.2%) was resulted from NR database, while COG had the least number of annotated unigenes (16%). Additionally, 50.2%, 36.9%, 32.8%, 27% , 26.8% and 17.8% unigenes acquired significant hits in the eggNOG, GO (Gene Ontology), Pfam (Protein family), KOG (euKaryotic Orthologous Groups), swissprot and KEGG, respectively (Table1). Moreover, the E-value and identity distribution were calculated to further analyze the BLAST results. Statistical analysis revealed that 45.71% of the mapped sequences displayed apparent homology (< 1.0E-50), while the remaining unigenes had the E-value ranging from 1.0×10−50 to 1.0×10−11 (Additional file 5: Figure S2a). In addition, the identity distribution showed that the majority of the mapped unigenes (73.64%) exhibited a similarity of > 60%, 37.84% unigenes showed similarity between 60–80%, while 13.83% unigenes showed similarity between 50–60%, only 12.54% unigenes were < 50% (Additional file 5:Figure S2b). The higher identity along with high quality E-value proved reliability of the de novo assembly generated in this study. According to Nr annotation result, the top two species with the highest number of best hits were Quercus Suber (8.88% matched unigenes) and Vitis vinifera (5.95% matched unigenes). (Additional file 5: Figure S2c). To facilitate the functional classification of the unigenes, GO annotation was conducted, which provided the ontology of defined terms representing gene product properties. GO annotations were further classified into three major classes as biological process, cellular component and molecular functions. A total of 37,108 sequences were identified based on sequence homology and can be classified into 52 functional groups (Fig. 1). Cellular components category was divided into 15 classes, in which the predominant groups corresponded to the cell (16,736 unigenes, 45.10%) and cell part (16,728 unigenes, 45.07%) followed by membrane (14,451 unigene, 38.9 %), organelle (11,873 unigenes, 31.9%) and membrane part (11,098 unigenes, 29.9%). In the molecular function category, the top two groups were catalytic activity (18,589 unigenes, 50.09%) and binding (17,291 unigenes, 46.59%) which far outnumbered the unigenes corresponding to transporter activity (3,066 unigenes, 8.26%) and structural molecular activity (1,373 unigenes, 3.7 %). In the 22 groups of biological process, the most abundant unigenes belonged to metabolic processes (18,425 unigenes, 49.65 %), indicating rich secondary metabolites accumulated in R. molle, followed by those taking part in cellular processes (17,024 unigenes,48.65%) and single-organism process (12,502 unigenes, 32.73%).
Table 1 Annotation of unigenes against eight different databases
Annotated database
|
Annotated number
|
Percentage of annotated genes (%)
|
Nr
|
56,529
|
56.2%
|
eggNOG
|
50,523
|
50.2%
|
GO
|
37,108
|
36.9%
|
Pfam
|
32,970
|
32.8%
|
KOG
|
27,211
|
27%
|
Swissprot
|
26,983
|
26.8%
|
KEGG
|
17,906
|
17.8%
|
COG
|
16,102
|
16%
|
All annotated
|
57,416
|
57.1%
|
Pathway analysis by Kyoto Encyclopaedia of Genes and Genomes (KEGG)
Genes within the same pathway usually cooperate with each other to exercise their biological functions. Pathway-based analysis aid in understanding those functions and identification of unigenes involved in various biosynthetic pathways. In this study, KEGG pathway analysis was performed with the threshold E-value of <10−5. A total of 17,906 (17.8%) unigenes were significantly matched into the KEGG database which were divided into five primary categories, including cellular process, environmental information processing, genetic information processing, metabolism, and organismal systems comprising 130 pathways (Fig. 2a). In our dataset, the highest numbers of unigenes were grouped into “carbohydrate metabolism (993 unigenes)” followed by “ribosome (881 unigenes)” and “biosynthesis of amino acid (703 unigenes)”. We further explore the unigenes related to secondary metabolism, a total of 11 pathways including 437 unigenes were found to participate in “biosynthesis of other secondary metabolites”, among which the most unigenes were enriched in the beta-Alanine metabolism (118 unigenes) (Fig. 2b), followed by‘Phenylalanine biosynthesis’ (100 unigenes) and ‘flavonoid biosynthesis (53 unigenes). Furthermore, “metabolism of terpenoids and polyketides” subcategory contained 8 pathways including 253 unigenes, the cluster for ‘terpenoid backbone biosynthesis’ representing the largest group (102 unigenes), followed by carotenoid biosynthesis (49 unigenes) and diterpenoid biosynthesis (26 unigenes) (Fig. 2c).
Over view of differentially expressed genes
We performed DEGs analysis of the two transcriptome libraries to discover the unigenes with significant difference in expression. FPKM value was used to measure unigenes expression levels. The overall expression levels of flower unigenes were higher than root unigenes (Fig. 3a). Further analysis revealed that out of 100,603 unigenes generated from the combined assembly of both flower and root transcriptomes, 6,082 unigenes were differentially expressed in flower and root, including 1,120 up-regulated and 4,962 down-regulated unigenes in root vs flower (Fig. 3b), among which 507 unigenes were expressed uniquely in flower. Hierarchical clustering of the 6,082 DEGs showed that the two tissues clustered relatively tight (Fig. 3c), indicating that some DEGs may involved in the same metabolic pathway. Out of 6,082 unigenes, 5,314 were annotated using different databases. For the GO enrichment analysis, the flower-specific up-regulated unigenes were assigned to several ontologies based on sequence homology, including 1,254 for cellular component, 716 for biological process, and 1,133 for molecular function. In the biological process category, the GO terms ‘metabolic process’ (GO:0008152) was most significantly enriched (304 unigenes), indicating the presence of vital metabolic activities in flowers (Fig. 4a). To further understand the involved metabolism pathways of DEGs, the KEGG enrichment analysis was performed. A total of 1,433 unigenes referring to 115 KEGG pathways were identified, the top three most abundant DEGs enrichment pathways were carbon metabolism (78 unigenes, 5.4%), starch and sucrose metabolism (66 unigenes, 4.6%), and biosynthesis of amino acids (61 unigenes, 4.3%), all of them were related to primary metabolism (Fig. 4b). Besides, DEGs were also enriched in biosynthetic pathways of secondary metabolites, a total of 222 DEGs involving 20 biosynthetic pathways were identified, among them 32 DEGs and 6 DEGs were clustered in flavonoid and phenylpropanoid biosynthetic pathways respectively. Moreover the “metabolism of terpenoids and polyketides” subcategory contained 8 pathways including 27 DEGs, and the highest numbers of DEGs (7) were clustered into terpenoid backbone biosynthesis. Furthermore, one DEG in monoterpenoid biosynthesis, four DEGs in sesquiterpenoid and triterpenoid biosynthesis, and six DEGs in diterpenoid biosynthesis (Additional file 6: Table S4) Further research on these genes can offer an improved understanding of terpenoid biosynthetic pathway.
Analysis of the secondary metabolic pathways
Identification of genes involved in terpenoid backbone biosynthesis
Terpenoids are the major secondary metabolites accumulated in R.molle, especially grayanoids which belong to the tetracyclic diterpenoid. The biosynthesis process of terpenoids can be divided into two stages, namely, the synthesis of terpenoid backbone and specific terpene formation and modification. The terpenoid backbone is synthesized from dimethylallyl diphosphate (DMAPP) and isopentenyl diphosphate (IPP), the general C-5 building blocks [39, 40]. In plants both the cytosolic mevalonate (MVA) and the plastids methylerythritol phosphate (MEP) pathway contribute to supplying DMAPP and IPP with cross flow [41, 42]. DMAPP was then sequentially condensed with IPP catalyzed by prenyltransferase leading to the formation of the starting precursors of different classes of terpenes, i.e., geranyl diphosphate (GPP, C-10) for monoterpenes, farnesyl diphosphate (FPP, C-15) for sesquiterpene and geranylgeranyl diphosphate (GGPP, C-20) for diterpenes [39] (Fig. 5a). Based on the KEGG pathway assignment, a total of 102 unigenes for 17 key enzymes related to the biosynthesis of terpenoid backbone were annotated, accounting for 0.57% of all the assembled unigenes with pathway annotation. These unigenes were mainly distributed in the MVA (46 unigenes, 6 enzymes) and MEP (17 unigenes, 6 enzymes) pathways, which may participate in the biosynthesis of IPP, the common building block of terpenoinds. Moreover, several genes (28 unigenes, 3 enzymes) were distributed in the downstream. In most cases, more than one unigenes was annotated as the same enzyme, suggesting that these unigenes might represent different members of the same gene family or the different fragments of a single transcript. Corresponding unigenes were listed in Table 2. Among them, seven DEGs were discovered, three up-regulated unigenes were related to MEP pathway, including one for DXS, one for 2-C-Methyl-D-erythitol 2,4 cyclodiphosphate (MDS) and one for isoprene synthase. Besides, we also found three down-regulated unigenes which were involved in MVA pathway, including two for HMGS, one for PMK (Table 2). These results indicated that the MEP pathway was mainly responsible for synthesizing terpenoids in flowers.
Table 2 Unigenes involved in the terpenoid backbone biosynthesis in R. molle
Enzyme name
|
EC number
|
Unigene number
|
DEGs number
|
AACT
|
2.3.1.9
|
18
|
*
|
HMGS
|
2.3.3.10
|
10
|
2
|
HMGR
|
1.1.1.34
|
12
|
*
|
MK
|
2.7.1.36
|
1
|
*
|
PMK
|
2.7.4.2
|
2
|
1
|
MVD
|
4.1.1.33
|
3
|
*
|
DXS
|
2.2.1.7
|
3
|
1
|
DXR
|
1.1.1.267
|
1
|
*
|
CMS
|
2.7.7.60
|
1
|
*
|
MCS
|
4.6.1.12
|
1
|
1
|
HDS
|
1.17.7.1
|
2
|
*
|
HDR
|
1.17.7.2
|
2
|
*
|
IPPI
|
5.3.3.2
|
4
|
*
|
GPPS
|
2.5.1.1
|
12
|
*
|
FPPS
|
2.5.1.10
|
10
|
*
|
GGPS
ISPS
CHL P
|
2.5.1.1
4.2.3.27
1.3.1.83
|
6
1
3
|
*
1
1
|
* DEGs were not found AACT: acetyl-CoA acetyltransferase HMGS:hydroxymethylglutaryl-CoA synthase HMGR: hydroxymethylglutaryl-CoA reductase MK: mevalonate kinase PMK: phosphomevalonate kinase MVD: mevalonate diphosphate decarboxylase DXS: 1-deoxy-D-xylulose-5-phosphate synthase DXR: 1-deoxy-D-xylulose-5-phosphate reductoisomerase CMS: 2-C-methyl-D-erythritol 4-phosphate cytidylyltransferase MCS: 2-C-methyl-D-erythritol 2,4-cyclodiphosphate synthase
HDS: 4-hydroxy-3-methylbut-2-enyl diphosphate synthase HDR: 4-hydroxy-3-methylbut-2-enyl diphosphate reductase IPPI: isopentenyl diphosphate isomerase GPPS: Geranyl diphosphate synthase FPPS:Farnesyl diphosphate synthase GGPS: Geranylgeranyl diphosphate synthase ISPS:isoprene synthase CHL P:geranylgeranyl reductase
Enzymes involved in grayanoids biosynthesis
Previous investigations have reported that abundant grayanane diterpenes were isolated from the roots and flowers of R. molle [6, 7, 10] which are regarded as the characteristic metabolites of this plant and possess significant analgesic activity. The proposed biosynthetic pathway of grayanoids starts from the common precursor GGPP (20-carbon), which are converted to kaurene by terpene synthases (TPSs) firstly, then finally generate grayanoids. The biosynthesis process from kaurene to grayanane may involve oxidative rearrangement (Fig. 5b). The grayanane backbone undergoes modifications primarily through the activity of cytochromes P450 (CYP) enzymes. To identify TPS and CYP candidates, the custom databases were built based on the publicly available protein sequences, which represented the least populous sequence sets without redundancy. A panel of nine terpene synthases was identified from the transcriptome data according to the sequence homology to the NCBI NR database (Additional file 7: Table S5), in which three unigenes were annotated as linalool synthases involved in monoterpene biosynthesis, and one unigene as germacrene D synthase. Additionally, two copies of copalyl diphosphate synthase and one copy of ent-kaurene synthase were also identified, and details were shown in Table 3. These enzymes can be grouped into four families according to phylogenetic relationships (Fig. 6). Six out of these TPS candidates (RmTPS1-5, RmTPS9) belonged to the TPS-a family, and RmTPS8 was classified into the TPS-e/f family. All the above-mentioned TPSs possessed the features of a class I terpene synthase, and only two class II terpene synthase were discovered in our dataset, which were RmTPS6 and RmTPS7 belonging to the TPS-c family. In angiosperm, the formation of diterpene backbone requires both class I and class II terpene synthase, the specific functions of TPSs need to be further verified.
Table 3 Terpene synthase candidate genes of R. molle
Terpene synthase
|
Gene
|
Unigene ID
|
Annotation
|
Mono-
|
RmTPS3
RmTPS4
|
c135826
c61279
|
linalool synthase
linalool synthase
|
|
RmTPS5
|
c97331
|
linalool synthase
|
Sesqui-
|
RmTPS9
|
c71656
|
germacrene D synthase
|
Di
|
RmTPS6
|
c95076
|
copalyl diphosphate synthase
|
|
RmTPS7
|
c86861
|
copalyl diphosphate synthase
|
|
RmTPS8
|
c92044
|
ent-kaurene synthase
|
*
|
RmTPS1
|
c79171
|
putative terpene synthase 9 [Quercus suber]
|
*
|
RmTPS2
|
c91666
|
putative terpene synthase2 [Camellia sinensis]
|
Cytochrome P450 monooxygenases (CYP) represent the largest superfamily of enzymes (around 1% of the sequenced plant genomes) in plants, but only few CYPs involved in terpenoid metabolism have been characterized, making it challenging to identify CYPs in the specialized terpenoid biosynthetic pathway of R. molle. In this study, the R.molle flower and root transcriptomes were mined against a P450-specific protein database, and a total of 61 candidates were identified (Additional file 7: Table S5). Phylogenetic analysis classified these CYPs candidates into 4 clans, members of the CYP71 clan were the most represented (Fig. 7), this clan harbors the most of CYP families involved in plant secondary metabolism [43, 44]. Terpenoid metabolism in plants is dominated by a few CYP families, among which the CYP71 and CYP76 families are major contributor [44, 45]. We used reported proteins from these two CYP families as probes to investigate our transcriptomes and a total of nine CYP enzymes from CYP71 and CYP76 families were identified (Fig. 8). To further screen the highly probable CYP candidates, the gene expression levels were assessed based on the FPKM values. The results showed that most of the genes were expressed in both flowers and roots, but the expression levels were different. Specifically, Rm89174 was significantly up-regulated in the flower tissue, while Rm66646 and Rm92121 were highly expressed in the root tissue of R. molle (Fig. 9a). The expression levels of unigenes detected in FPKM analysis were further verified through qRT-PCR analysis (Fig. 9b). Generally, expression level measured by qRT-PCR was consistent with RNA-Seq data. The CYP unigenes showed accordant expressions in both qRT-PCR and FPKM analysis, confirming the reliability of the sequencing results. These results provide a reference for future functional characterization of TPS and CYP candidates involved in terpenoid biosynthesis in R. molle. Nevertheless, further research is warranted to uncover the true functions of these unigenes.
Lignan biosynthetic genes
Phenylpropanoids are derived from phenylalanine and comprise a large group of plant natural products with extensive bioactivities, such as hepatoprotection and antioxidation. These compounds are involved in all aspects of plant responses to both biotic and abiotic stimuli [46]. The general phenylpropanoid metabolism derives a large number of secondary metabolites using the few intermediates of the shikimate pathway as basic precursors. The biosynthetic pathway starts with the formation of cinnamic acid from phenylalanine, which results in the formation of cinnamoyl-CoA and p-coumaroyl -CoA. These CoA-activated compounds are the precursor for synthesizing lignans, flavonoids, flavonols as well as numerous other secondary metabolites (Fig. 10). In the present study, we performed KEGG analysis on both R. molle flower and root transcriptomes and the results revealed a total of 232 unigenes were involved in the phenylpropanoid biosynthetic pathway. Ten unigenes were annotated for coding phenylalanine ammonia-lyase (PAL) and three unigenes were annotated to code the trans-cinnamate 4-monooxygenase. Both of the two enzymes play a significant role in the formation of important intermediate cinamic acid. Besides, 18 unigenes were annotated as 4-coumarate-CoA ligase (4CL) and 6 unigenes were annotated to code cinnamoyl-CoA reductase (CCR). Moreover, enzymes at branching points were also identified, and the representative enzymes are listed in Table 4.
Table 4 Representative enzymes in phenylpropanoid biosynthetic pathway in R. molle
Enzyme name
|
Annotation
|
EC number
|
Unigene number
|
PAL
|
phenylalanine ammonia lyase
|
4.3.1.24
|
10
|
4CL
|
4-coumarate--CoA ligase
|
6.2.1.12
|
18
|
CCR
|
cinnamoyl-CoA reductase
|
1.2.1.44
|
6
|
CYP73A
|
trans-cinnamate 4-monooxygenase
|
1.14.14.91
|
3
|
HCT
|
shikimate O-hydroxycinnamoyl
transferase
|
2.3.1.133
|
10
|
CYP98A
|
5-O-(4-coumaroyl)-D-quinate 3'-monooxygenase
|
1.14.14.96
|
4
|
CYP84A
|
ferulate-5-hydroxylase
|
1.14--
|
4
|
COMT
|
caffeic acid 3-O-methyltransferase
|
2.1.1.68
|
12
|
Identification of genes related to flavonoid biosynthesis
Flavonoids are important polyphenolic plant secondary metabolites that can be categorized into flavones, flavonols, flavanone, isoflavones, catechins and chalcones [47]. Appropriate intake of flavonoids can reduce the incidence of cancer, cardio vascular disease, lipid peroxidation and osteoporosis [48]. Previous phytochemical studies have revealed the presence of numerous of flavonoids in flowers of R. molle [3, 12, 13]. Considering the diverse beneficial effects of flavonoids, this study also explored the unigenes related to flavonoid biosynthesis in the transcriptome of R. molle. Coumaroyl-CoA and malonyl-CoA are the common precursors for the biosynthesis of flavonoids, which are derived from phenylpropanoid pathway and carbohydrate metabolism, respectively. The biosynthesis of flavonoids is initiated by chalcone synthase (CHS), which generates chalcone as the important intermediate and the pathway proceeds with several enzymatic steps for forming other classes of flavonoids, like flavanones and dihydroflavonols. In addition, the side branches of the flavonoid pathway lead to synthesis of other flavonoid classes including isoflavones, flavones, and flavonols (Fig. 11). A total of 53 unigenes related to flavonoid biosynthetic pathway were annotated. Starting from the initial committed enzymes for the biosynthesis of flavonoids, chalcone synthase (CHS), chalcone isomerase (CHI) and flavanone hydroxylase (F3H) were identified, all of which continuously catalyzed p-coumaroyl-CoA and malonyl-CoA into the important intermediate dihydrokae- mpferol. Additionally, the flavonoid-3¢-hydroxyase and flavonoid-3¢,5¢-hydroxyase, which are essential for converting dihydrokaempferol into dihydroquercetin and dihydromyricetin were also identified. The main enzymes involved in flavonoid biosynthesis were listed in Table 5.
Table 5 Unigenes involved in the flavonoid biosynthetic pathway in R. molle
Enzyme name
|
Annotation
|
EC number
|
Unigene number
|
CHS
|
chalcone synthase
|
2.3.1.74
|
6
|
CHI
|
chalcone isomerase
|
5.5.1.6
|
3
|
F3H
|
flavanone hydroxylase
|
1.14.11.9
|
7
|
F3’H
|
flavonoid-3’-hydroxylase
|
2.7.1.36
|
2
|
F3’5’H
|
flavonoid-3’5’-hydroxylase
|
1.14.14.81
|
3
|
DFR
|
dihydroflavonol-4-reductase
|
1.1.1.219
|
3
|
ANS
|
anthocyanidin synthase
|
1.14.20.4
|
7
|
FLS
|
flavonol synthase
|
1.14.20.6
|
2
|
Identification of transcription factors
In plant, transcription factors (TFs) often play a key role in regulating gene expression at the transcriptional level, which can also affect the metabolic flux by interacting with the promoter regions of gene. Based on our Blast X search against the known Plant Transcription Factor database, 3376 putative R. molle transcription factor distributed in at least 49 TF families were identified, which represented 3.35% of the total assembled unigenes (Fig. 12). Among them, C2H2 was the most abundant TF family (329 unigenes, 9.7%), followed by zn-clus (179 unigenes, 5.3%), and bZIP (105 unigenes, 3.1%). C2H2 family members are crucial to plant developmental processes including floral organogenesis, initiation of leaves and lateral shoots and seed development [49]. bZIP regulates processes including pathogen defense and stress signaling [50]. The present study also identified 59 and 97 unigenes encoding MYB and MYB related TFs, respectively. MYB TFs regulate the phenylpropanoid biosynthesis in several plant species and mostly include the R2R3-MYB TFs, which have also been shown to regulate the main branch viz. flavonoid metabolic pathway in phenylpropanoid biosynthesis in several plants including Arabidopsis thaliana [51], Prunus persica [52] and Epimedium sagittatum [52]. In addition, 89, 83 and 51 unigenes were also found to be related to bHLH, AP2-ERF and WRKY, respectively. These TFs have various roles throughout the whole life cycle of plant, from the regulation of several developmental processes to the response to environmental stress [53-55]. Moreover, they are especially important to secondary metabolism in plants. For example, bHLH TFs regulate the flavonoid biosynthetic pathway in plants [56, 57]. The AP2/ERF TF family members modulate the biosynthetic genes for terpenoid indole alkaloids in Catharanthus roseus [58]. Further investigation on these TFs may provide a clear profile on the regulatory network for the biosynthesis of secondary metabolites in R. molle.
Identification of SSRs
Simple sequence repeats (SSRs) also termed as microsatellites, are tandem repeats of short DNA motifs with one to six base pairs. They are widely distributed in eukaryotes (e.g. plants, animals and fungi) as well as in some prokaryotes.[59]. SSRs are generally associated with phenotypic variations which have become the most extensively utilized informative molecular markers that favor for a variety of applications, including the genetic breeding of plants, gene mapping and genetic marker-assisted selection [60].To identify SSRs, all the assembled unigenes of both R. molle flower and root were analyzed using MISA. Overall 10,828 SSRs were identified from 7,799 unigene, in which the most abundant SSRs were mono-nucleotide repeat motif (4,868, 44.95%), followed by di-nucleotide repeat motif (3,872, 35.75%) and tri-nucleotide repeat motif (1,292, 11.93%), while hexa-nucleotide SSRs (6, 0.055%) had the lowest abundance. Additionally, there were 66 (6.1%) tetra-nucleotide and 14 (0.13%) penta-nucleotide SSR (Additional files 8: Figure S3). Especially, some SSR motifs were associated with the unigenes which encode enzymes involved in terpene biosynthesis (eg. HMGR, DXS) (Table 6).These SSRs can provide a basis for further analyzing genetic diversity of R. molle and the related species.
Table 6 SSR motifs in unigenes related to terpenoid biosynthesis
Enzyme name
|
Unigene ID
|
Number of SSRs
|
SSR motif
|
Number of repeats
|
HMGR
|
c88044
|
4
|
AAC
|
6
|
T
|
13
|
GA
|
7
|
AAC
|
5
|
MCT
GGPS
|
c86870
|
1
|
TC
|
7
|
c83679
|
1
|
*
|
10
|
DXS
|
c83170
|
1
|
AG
|
7
|
c84061
|
1
|
T
|
2
|
* represent compound repeat type. SSR motif: (T)GATCAGCAGAAAGATGAGG ACTTTGATTCATGGTACTGTAACAGCATCTGACGTTTTGCAGG(A)