Open Access

Exogenous auxin regulates multi-metabolic network and embryo development, controlling seed secondary dormancy and germination in Nicotiana tabacum L.

  • Zhenhua Li1, 2,
  • Jie Zhang2,
  • Yiling Liu3,
  • Jiehong Zhao2,
  • Junjie Fu4,
  • Xueliang Ren2,
  • Guoying Wang4 and
  • Jianhua Wang1Email author
BMC Plant BiologyBMC series – open, inclusive and trusted201616:41

https://doi.org/10.1186/s12870-016-0724-5

Received: 15 October 2015

Accepted: 28 January 2016

Published: 9 February 2016

Abstract

Background

Auxin was recognized as a secondary dormancy phytohormone, controlling seed dormancy and germination. However, the exogenous auxin-controlled seed dormancy and germination remain unclear in physiological process and gene network.

Results

Tobacco seeds soaked in 1000 mg/l auxin solution showed markedly decreased germination compared with that in low concentration of auxin solutions and ddH2O. Using an electron microscope, observations were made on the seeds which did not unfold properly in comparison to those submerged in ddH2O. The radicle traits measured by WinRHIZO, were found to be also weaker than the other treatment groups. Quantified by ELISA, there was no significant difference found in β-1,3glucanase activity and abscisic acid (ABA) content between the seeds imbibed in gradient concentration of auxin solution and those soaked in ddH2O. However, gibberellic acid (GA) and auxin contents were significantly higher at the time of exogenous auxin imbibition and were gradually reduced at germination. RNA sequencing (RNA-seq), revealed that the transcriptome of auxin-responsive dormancy seeds were more similar to that of the imbibed seeds when compared with primary dormancy seeds by principal component analysis. The results of gene differential expression analysis revealed that auxin-controlled seed secondary dormancy was associated with flavonol biosynthetic process, gibberellin metabolic process, adenylyl-sulfate reductase activity, thioredoxin activity, glutamate synthase (NADH) activity and chromatin regulation. In addition, auxin-responsive germination responded to ABA, auxin, jasmonic acid (JA) and salicylic acid (SA) mediated signaling pathway (red, far red and blue light), glutathione and methionine (Met) metabolism.

Conclusions

In this study, exogenous auxin-mediated seed secondary dormancy is an environmental model that prevents seed germination in an unfavorable condition. Seeds of which could not imbibe normally, and radicles of which also could not develop normally and emerge. To complete the germination, seeds of which would stimulate more GA synthesis to antagonize the stimulation of exogenous auxin. Exogenous auxin regulates multi-metabolic networks controlling seed secondary dormancy and germination, of which the most important thing was that we found the auxin-responsive seed secondary dormancy refers to epigenetic regulation and germination to enhance Met pathway. Therefore, this study uncovers a previously unrecognized transcriptional regulatory networks and physiological development process of seed dormancy and germination with superfluous auxin signal activate.

Keywords

Auxin Seed dormancy Germination Wateruptake Embryo development Endosperm burst Hormone Nicotiana tabacum RNA-seq

Background

The transition from dormancy to germination in seeds is a key physiological process during the life-cycle of some plants. Water uptake, seed dormancy released, embryo expansion, and radical breakthrough of seed envelopes is considered as the completion of the seed germination [1]. Plant hormone, as a signaler, is also important for seed dormancy and germination [2]. GA and ABA are recognized as the key internal factors, with GA promoting and ABA inhibiting seed germination and dormancy [3]. Recent studies support the fact that the ABA/GA ratio regulates the metabolic transition required for dormancy release and germination [46]. On this basis, it is inferred that other hormones such as ethylene [7, 8] and cytokinin [9, 10] also influence germination through cross-talk mechanisms.

Auxin, as a versatile trigger taking part in many plant developmental processes [11], also plays a critical role in root development, such as shaping the embryonic root pole, determining the root meristem size and controlling root cell elongation [12]. However, the biological function of auxin in seed dormancy and germination is yet to be explored. Recently, a previously unrecognized regulatory factor of seed dormancy, auxin, was identified as a secondary dormancy hormone. It works with ABA signaling to control seed dormancy and germination [13].

Numerous genes involved in dormancy and germination regulation have already been confirmed. ABA receptors (PYR, PYL/RCAR), protein phosphatase 2C (ABI1, ABI2, HAB1, AHG3), protein kinase (SnRK2.2, 2.3, 2.6) and other dormancy hormone regulators were reviewed recently [14]. PIL5/PIF1 has been identified as an important upstream component, which through transcriptional control of biosynthetic genes, reciprocally regulates levels of both ABA and GA [12], and PIL5 was found to target promoters of various hormonal signaling genes including ARF18, IAA16, CRF2, and JAZ1 [15]. Very recently, it was reported that auxin acts upstream of the major regulator of seed dormancy, by recruiting the auxin response factors ARF 10 and 16 to control the expression of ABI3 during seed germination [13].

However, the mechanisms for the auxin regulation of seed germination process and the genetic response to exogenous auxin stimulation on a transcriptomic scale remained unknown. The aim of this study is to analyze the differential physiological process and genes expression of the auxin-controlled seed dormancy and germination using Nicotiana tabacum L as the model plant. This is the first study that exogenous auxin-controlled seed dormancy and germination on a transcriptomic scale and physiological development process also would be taken into consideration.

Results

Seed dormancy depends on exogenous auxin levels

Keeping in mind auxin control of seed dormancy in Arabidopsis [13], it was presumed that the exogenous high concentration of auxin might promote seed secondary dormancy in tobacco. We found that tobacco seeds soaked in 1000 mg/l indole-3-acetic acid (IAA) solution showed markedly decreased germination compared with those soaked in 0, 10 and 100 mg/l IAA solution and even unsoaked seeds (Fig. 1).
Fig. 1

A graphical representation of exogenous auxin levels controlling seed dormancy. Germination of seeds imbibed in supplementation IAA solution or ddH2O 24 h or untreated and then germinated on filter paper beds 156 h. Subscript 10, 100, 1000 indicated the concentration gradients

Exogenous auxin regulates the emergence of germinated seed radicle

The effect of exogenous auxin on seed germination including water uptake, radicle emergence, endosperm burst and cotyledons unfolding assay were analyzed. The result showed that vacuoles of seeds imbibed in 1000 mg/l IAA solution could not properly unfold compared with that in ddH2O (Fig. 2a and b). Also the radicle traits, which included the radicle weight, length and surface area, were significantly weaker (Fig. 3a-c), but there was no significant difference in β-1,3glucanase activity (Fig. 4). The radicle of all the seeds did not emerge even when approximately half of the cotyledons unfolded in the germination process.
Fig. 2

An electron micrograph showing (a) seed secondary dormancy, vacuole of the seeds not fully expanded, and many follicles bubble were found in cells of the seeds that treated with IAA (1000 mg · L−1) 24 h, (b) seed germinating, vacuole of seeds treated with ddH2O 24 h and vacuole of which completely expanded

Fig. 3

Radicle weight (a), length (b) and surface area (c) of tobacco seed imbibed in supplementation IAA solution or ddH2O 24 h or untreated and then germinated on filter paper beds 156 h. Different letters indicate significant differences according to Duncan test (means ± SD, p < 0.05). Subscript 10, 100, 1000 indicate the concentration gradients

Fig. 4

β-1, 3glucanase activity (means ± SD) of tobacco seed imbibed in supplementation IAA solution or ddH2O 24 h or untreated and then germinated on filter paper beds 144 h. Subscript 10, 100, 1000 indicate the concentration gradients

Gibberellin level was regulated by exogenous auxin and not abscisic acid

The effect of exogenous IAA on content of endogenous hormones including ABA, GA, and IAA were examined. The dynamic changes in ABA, GA1+3 and IAA in three germination stages were shown in Fig. 5. The result indicated that there was no significant difference in ABA content between seeds imbibed in gradient concentration of auxin solution and those soaked in ddH2O, in all three germination stages (Fig. 5a-c). However, the GA1+3 (Fig. 5d-f) and IAA (Fig. 5g-i) contents were significantly higher, especially in the first stage.
Fig. 5

Endogenous ABA (a-c), GA1+3 (d-f) and IAA (g-i) hormones’ content of tobacco seed imbibed in supplementation IAA solution or ddH2O 24 h or untreated and then germinated on filter paper beds 144 h. Subscript 10, 100, 1000 indicate the concentration gradients

Transcriptome analysis of exogenous auxin controlled seed dormancy and germination

Figure 1 shows the phenotype of 72 and 156 h germinating tobacco seeds and Fig. 6 illustrates the process flux of the RNA-seq experiment. As shown, three replications of 0 or 1000 mg/l IAA imbibed seeds that germinated after 0, 72 or 156 h (for seeds status see Table 1) were respectively collected, mixed and then used for total RNA isolation. Afterwards, paired-end libraries were prepared and sequenced as described in the ‘Methods’. The quality of the data and the generated sequences were checked using the Fast QC software and Phred measure Score, respectively. The percentage of high-quality fragments was >80 % in all cases (20 units or more in Phred values which correspond to a sequencing error rate of 1 %). The mapped data generated was shown in Table 1. There were seven samples in total. An average of about 37 million high-quality paired-end reads (2 × 100 bp) for all RNA-seq samples were generated. We got approximately 263 million reads pairs, which are more than 52.6 billion bases. For each RNA-seq sample, 72.61–91.43 % (Table 1) of reads were mapped to the genome of N.tabacumK326 reference genome [16] with TopHat software [17]. Following this, we used the Cufflinks program [18] to reassemble the mapped reads into a set of transcripts for each sample. Then cuffmerge module in cufflinks was used to merge the transcripts from each sample to generate a unique transcript set, also named as unigenes. After removing the transcripts with length < 200 bp, a total of 107,403 unigenes were detected. These unigenes had an average length of 1757 bp and N50 value of 2105 bp, of which the lengths ranged from 200 bp to 14,848 bp. There were 80,494 (74.94 %) of the unigenes with length ≥ 1000 bp.
Fig. 6

Flow chart of the RNA-seq experimental procedure

Table 1

Number of reads sequenced and mapped with Tophat. The number of unique mapping reads plus multimapping reads equals the total number of alignments. CK, H2O and IAA stand for imbibed tobacco seeds and control respectively; Numbers 0, 72 and 156 stand for germinated time

Sample

Seed category

Total reads

Total mapped reads

Unique mapping reads

Reads mapped in proper pairs

Untreated-0

Dormancy

39,344,236

28,566,421(72.61 %)

24,229,292(61.58 %)

25,845,450

 H2O-0

Imbibition

39,795,012

35,183,360(88.41 %)

21,537,407(66.58 %)

29,258,962

 IAA-0

Dormancy

48,297,176

38,392,739(79.49 %)

32,439,112(67.17 %)

34,779,672

Untreated-72

Germination

33,792,314

30,897,092(91.43 %)

26,584,380(78.67 %)

24,978,136

 H2O-72

Germination

35,593,768

31,962,893(89.80 %)

27,456,500(77.14 %)

26,621,694

 IAA-72

Dormancy

32,459,006

28,789,591(88.70 %)

25,040,225(77.14 %)

23,209,710

 IAA-156

Germination

33,769,804

29,877,097(88.47 %)

25,821,822(76.46 %)

24,613,498

For unigenes’ functional annotation, we utilized a blastx search against the NCBI NR database, with an E-value of 1E-05 as a cut-off. The blastx search result showed that about 91,840 (85.18 %) unigenes which had significant hits in the NR database was utilized. The distribution of the unigenes best blastx hit E-value is shown in Additional file 1: Figure S1. Most of the unigenes had high similarity with NR database sequences. They include 70,439 (65.58 %) unigenes with E-value ≤ 1.0E-100, and 91,839 (85.51 %) ungenes with E-value ≤ 1.0E-5. The blastx best-hit of the 91,839 unigenes showed that the first two species with the highest hits were Solanum lycopericum (38,302, 41.71 %) and Solanum tuberosum (37,890, 41.26 %), which were the most important model organisms in Solanaceae. The distribution of best hits species is shown in Additional file 2: Figure S2. For unigenes functional classification, a blastx search against the EuKaryotic Orthologous Groups (KOG) database was done, and it showed that 60,497 unigenes matched with 25 KOG clusters. As shown in Additional file 3: Figure S3, KOG classification showed that the largest category was ‘general function prediction only’ which was same as other studies; the following category was ‘posttranslational modification, protein turnover, chaperones’. For gene ontology (GO) annotation, Blast2GO suite was used to retrieve GO terms based on the blastx search result of NCBI NR database. Among the 91,839 annotated unigenes, there were 76,969 unigenes that were annotated with at least one GO term. As a result, 62,074 unigenes were grouped into Biological Process (BP), 61,316 into Molecular Function (MF) group and 56,760 into Cellular Component (CC) group. The unigene percentage of each GO term in the three groups is shown in Additional file 4: Figure S4. Finally, KAAS tool was used to identify pathways for the unigenes. There were 23,261 (21.66 %) unigenes assigned to 2100 kyoto encyclopedia of genes and genomes (KEGG) orthologs, which were classified into 327 KEGG pathways.

To quantify the unigenes expression in each RNA-seq sample, we used bowtie to map the clean RNA-seq reads to all unigenes sequences, and then used eXpress software to calculate fragments per kilobase of exon per million fragments mapped (FPKM) for unigenes in each sample. To analyze the similarity of gene express patterns among these different RNA-seq samples, we firstly filtered out the unigenes without any reads mapped in all samples, and then used principal component analysis (PCA) to analyze the unigenes FPKM values of all the 7 samples. PCA plot of principal components 1 and 2 showed that the spatial distribution of H2O-0 and IAA-0, H2O-72 and IAA-156 points was more concentrated, suggesting that these samples were more similar (Fig. 7).
Fig. 7

A principal component analysis (PCA) chart to explore the relationship between samples using the unigene expression quantity. The more similar the samples, the spatial distribution of different colors points more concentrated

Auxin-responsive dormancy seeds and primary dormancy seeds differ in their gene expression profiles

The differential expression analysis was performed by comparing untreated seeds (Primary dormancy) and auxin-imbibed seeds (Secondary dormancy) with H2O-imbibed seeds (No dormancy), separately. At a significant level of p < 0.05 and fold change ≥ 2, we identified 1958 up- and 2917 down-regulated unigenes between untreated seeds and H2O-imbibed seeds (Additional file 5: Figure S5A). At the same condition, we also identified 2506 up- and 2634 down-regulated unigenes between auxin-imbibed seeds and H2O-imbibed seeds (Additional file 5: Figure S5B). To determine the unigenes with differential expression pattern between untreated seeds and auxin-imbibed seeds relative to H2O-imbibed seeds, the H2O-imbibed seeds were taken as a control and then the unigene counts of the nine expression patterns were calculated.

As shown in Fig. 8, the Percentage FC and Unigene FC columns were calculated based on the unigene expression fold change, in which unigene with fold change < 0.5 was treated as down -regulated, and fold change > 2.0 was treated as up-regulated; the rest were treated as unchanged. The pie chart was drawn with the Percentage FC values. The Unigene P column was calculated based on the p-values of gene differential expression analysis, in which unigene with p-value < 0.05 and fold change < 0.5 was treated as down-regulated, and that with p-value < 0.05 and fold change > 2.0 was treated as up-regulated; the rest were treated as unchanged. In the nine expression patterns, we treated the III/IV/VI/VII patterns as the differential expression pattern between untreated seeds and auxin-imbibed seeds relative to H2O-imbibed seeds. The III/VII pattern had complete differential regulating tendency relative to H2O-imbibed seeds. In the IV/VI pattern, unigenes presented differential expression between auxin-imbibed seeds and H2O-imbibed seeds, but remained unchanged between untreated seeds and H2O-imbibed seeds. Consequently, unigenes in these four expression patterns which could also be considered as the major causal factors that led to the difference in mechanism between primary dormancy and auxin-induced secondary dormancy, and this could be used to do functional analysis.
Fig. 8

A pie chart distribution of unigenes whose expression is altered during seed dormancy. The pie chart was drawn with the percentage of fold change values. Unigenes whose expression level was significantly up-regulated or down-regulated by more than 2-fold or p-value < 0.05 during dormancy were grouped according to their expression behavior in the two dormancy states of untreated seeds (primary dormancy) and auxin-imbibed seeds (secondary dormancy) relative to H2O-imbibed seeds (non-dormancy). Arrows facing up or down represent up-regulated or down-regulated genes, respectively

Table 2

Representative significant enriched GO terms of the differential expressed unigenes

Seed status

Category

GO term

Refence set

Query set

P-value (FDR)

Representative gene ID

Encoded protein

Dormancy

BP

Para-aminobenzoic acid metabolic process

130

19

2.20E-04

TCONS_00105446

glucosyltransferase

Oxalate catabolic process

6

4

2.99E-03

TCONS_00017169

4-coumarate--CoA ligase-like 10-like

N-acylethanolamine metabolic process

34

9

6.41E-04

TCONS_00047595

fatty acid amide hydrolase-like

Glutamate biosynthetic process

25

7

2.99E-03

TCONS_00068711

glutamate synthase 1

Gibberellin metabolic process

127

13

3.21E-02

TCONS_00065700

gibberellin 2-oxidase 2,3,5

Flavonol biosynthetic process

109

13

1.15E-02

TCONS_00051510

immediate-early salicylate-induced glucosyltransferase

Cutin biosynthetic process

47

9

3.95E-03

TCONS_00032450

CYP77A19

Auxin mediated signaling pathway

548

43

8.41E-04

TCONS_00056392,TCONS_00049526,TCONS_00102987,TCONS_00043746,TCONS_00029963,TCONS_00082867

NTGP3, Nt-iaa4.5 deduced protein, IAA9, ARF1, IAA13, LAX2

MF

Adenylyl-sulfate reductase activity

5

4

1.43E-03

TCONS_00030231

APS reductase

Carbon-nitrogen ligase activity, with glutamine as amido-N-donor

200

19

1.85E-02

TCONS_00077280

amidase-like protein

Glutamate synthase (NADH) activity

22

8

3.01E-04

TCONS_00068708

glutamate synthase 1

Indole-3-acetic acid amido synthetase activity

42

8

1.43E-02

TCONS_00011340

Nt-gh3 deduced protein

Isoflavone 2′-hydroxylase activity

21

5

4.94E-02

TCONS_00066756

cytochrome P450

Oxalate-CoA ligase activity

6

4

3.69E-03

TCONS_00017169

4-coumarate--CoA ligase-like 10-like

Phosphoadenylyl-sulfate reductase (thioredoxin) activity

5

4

1.43E-03

TCONS_00030231

APS reductase

Germiantion

BP

ABA mediated signaling pathway

547

35

3.19E-03

TCONS_00022716, TCONS_00055623, TCONS_00066091

bZIP, LEB5, calcium-dependent protein kinase 8

Auxin mediated signaling pathway

548

34

5.43E-03

TCONS_00033126, TCONS_00075562, TCONS_00084884

auxin efflux facilitator PIN3b, Nt-iaa28 deduced protein, germin like protein

Cinnamic acid biosynthetic process

16

7

2.95E-05

TCONS_00069919

phenylalanine ammonia-lyase 4

Cysteine biosynthetic process

547

34

5.31E-03

TCONS_00016976, TCONS_00018745, TCONS_00017791

serine acetyltransferase 7, chloroplast pigment-binding protein CP24, ZIP

Ethylene metabolic process

247

20

4.37E-03

TCONS_00086037, TCONS_00008535, TCONS_00106286

ethylene forming enzyme,WRKY transcription factor NtEIG-D48, Avr9/Cf-9 rapidly elicited protein 74

JA mediated signaling pathway

592

38

1.90E-03

TCONS_00016976, TCONS_00057641,TCONS_00052052, TCONS_00055412, TCONS_00081296

serine acetyltransferase 7, BOP3, WRKY DNA-binding protein, jasmonate ZIM-domain protein10, MAP kinase kinase

L-phenylalanine catabolic process

50

7

1.79E-02

TCONS_00069919

phenylalanine ammonia-lyase 4

Response to blue light

372

25

9.11E-03

TCONS_00051968

chloroplast FtsZ-like protein

Response to far red light

324

24

4.19E-03

TCONS_00033254

chlorophyll a/b-binding protein

Response to red light

285

26

1.38E-04

TCONS_00049275

alpha-expansin precursor

SA mediated signaling pathway

732

42

5.65E-03

TCONS_00081296, TCONS_00055623, TCONS_00016976

MAP kinase kinase, LEB5, serine acetyltransferase 7

MF

Phenylalanine ammonia-lyase activity

15

7

1.13E-05

TCONS_00069919

phenylalanine ammonia-lyase 4

Serine-type endopeptidase inhibitor activity

34

10

4.64E-06

TCONS_00053724, TCONS_00009793

trypsin proteinase inhibitor precursor, cyclin-T1-3-like

UDP-glucosyltransferase activity

581

39

4.20E-04

TCONS_00002352, TCONS_00039739, TCONS_00066391

glucosyltransferase, UDP-glucose, SA glucosyltransferase, flavonoid 3-O-glucosyltransferase

CC

Chloroplast thylakoid membrane

1211

91

5.07E-14

TCONS_00032434, TCONS_00018745, TCONS_00051968

plastid transketolase, chloroplast pigment-binding protein CP24, chloroplast FtsZ-like protein

Photosystem I reaction center

28

9

1.81E-06

TCONS_00002104, TCONS_00102030, TCONS_00067457

PSI-H precursor, photosystem I subunit XI, PSI-H precursor

Photosystem II reaction center

6

4

1.91E-04

TCONS_00065835, TCONS_00027279

photosystem II protein T, photosystem II reaction center PSB28 protein

Table 3

Significant enriched KEGG pathways of the difference express unigene

Seed status

KEGG ID

Refence set

Query set

P-value (FDR)

KEGG pathway

Dormancy

ko00062

12

54

2.68E-04

Fatty acid elongation in mitochondria

ko00910

15

105

2.13E-03

Nitrogen metabolism

ko04330

14

119

2.30E-02

Notch signaling pathway

ko04075

62

1029

4.07E-02

Plant hormone signal transduction

Germination

ko00195

28

154

3.18E-12

Photosynthesis

ko00980

25

131

1.80E-11

Metabolism of xenobiotics by cytochrome P450

ko00940

39

370

1.55E-09

Phenylpropanoid biosynthesis

ko00480

32

270

3.96E-09

Glutathione metabolism

ko00196

14

78

4.20E-06

Photosynthesis - antenna proteins

ko00360

29

315

6.65E-06

Phenylalanine metabolism

ko04626

39

547

4.11E-05

Plant-pathogen interaction

ko00941

10

65

8.04E-04

Flavonoid biosynthesis

ko04976

9

63

3.31E-03

Bile secretion

ko00592

12

123

1.01E-02

alpha-Linolenic acid metabolism

ko00945

8

60

1.06E-02

Stilbenoid, diarylheptanoid and gingerol biosynthesis

ko00965

2

2

1.90E-02

Betalain biosynthesis

ko00052

17

256

5.00E-02

Galactose metabolism

The analyses for GO and KEGG pathway enrichment of genes in up-regulated or down-regulated auxin-responsive seeds were performed and it was found that these unigenes also showed different expression trend in primary dormancy seeds (p-value < 0.05, 3962; patternsIII+IV+VI+VII). There were significant enrichment of GO terms related to auxin mediated signaling pathway (flavonol biosynthetic process, gibberellin metabolic process), adenylyl-sulfate reductase activity, phosphoadenylyl-sulfate reductase (thioredoxin) activity, and glutamate synthase (NADH) activity (Table 2 and Additional file 6: Figure S6). KEGG pathway enrichment analysis shown the differential express unigenes were significant enriched in plant hormone signal transduction (Additional file 7: Figure S7) fatty acid elongation in mitochondria, and so on (Table 3).

Auxin-responsive germinating seeds and conventional germinating seeds differ in their gene expression profiles

Using the same method as the dormancy experiment, a differential analysis between conventional germinated seeds (H2O-72) and auxin-responsive germinated seeds (IAA-156) relative to auxin-responsive dormancy seeds (IAA-72) was conducted. Firstly, at a significant level of P < 0.05 and fold change ≥ 2, we identified 3526 up- and 2073 down-regulated unigenes between untreated seeds and H2O-imbibed seeds (Additional file 5: Figure S5C). At the same condition, we also identified 4458 up- and 1616 down-regulated unigenes between auxin-imbibed seeds and H2O-imbibed seeds (Additional file 5: Figure S5D). The transcriptome comparison analysis of two germinated states seeds of conventional germinated seeds (H2O-72) and auxin-responsive germinated seeds (IAA-156) in comparison with auxin-responsive dormancy seeds (IAA-72) was performed. The unigenes were further classified into 9 expression patterns (Fig. 9). Like the different expression analysis in the dormancy seeds above, only unigenes in III/IV/VI/VII patterns were analyzed to identify the genes with differential expression between sample IAA-156 and sample H2O-72. These genes could also be treated as the major causal factors that led to the difference in mechanism between auxin-responsive germinated seeds and conventional germinated seeds.
Fig. 9

A pie chart distribution of unigenes whose expression is altered during seed germination. The pie chart was drawn with the percentage of fold change values. Unigenes whose expression level was significantly up-regulated or down-regulated by more than 2-fold or p-value < 0.05 during seed germination were grouped according to their expression behavior in the two germination states of H2O-72 seeds (normal germination) and IAA-156 seeds (auxin-imbibed germination) relative to IAA-72 seeds (secondary dormancy). Arrows facing up or down represent up-regulated or down-regulated genes, respectively

The GO and KEGG pathway enrichment of genes in the up-regulated or down-regulated auxin-responsive germinated seeds showed that these genes had different expression trend compared with conventional germinated seeds (p-value < 0.05, 3048; patternsIII+IV+VI+VII). The enrichment of GO terms were associated with ABA, auxin, JA and SA-mediated signaling pathway, response to red, far red and blue light, serine-type endopeptidase inhibitor activity, phenylalanine ammonia-lyase activity, UDP-glucosyltransferase activity, and photosynthesis, etc. (Table 2 and Additional file 8: Figure S8). The KEGG enriched pathway were associated with glutathione metabolism, flavonoid biosynthesis (Additional file 9: Figure S9), and phenylpropanoid biosynthesis (Table 3).
Table 4

Fold changes of significant differential expressed unigenes revealed in auxin-responsive seed dormancy and germination regulation by RNA-seq and their verification by RT-PCR

Gene

Encoded protein

RNA-seq

RT-PCR

Untreated-0 vs. H2O-0

IAA-0 vs. H2O-0

H2O-72 vs. IAA-72

IAA-156 vs. IAA-72

Untreated-0 vs. H2O-0

IAA-0 vs. H2O-0

H2O-72 vs. IAA-72

IAA-156 vs. IAA-72

ABA and GA crosstalk

         

 TCONS_00064877

AHG3(Protein phosphatase 2C)

0.318

0.3407

 TCONS_00038628

GA3ox1

0.072

6.848

0.0146

1.6385

 TCONS_00082895

GA2ox2

13.934

5.5919

 TCONS_00084330

CYP707A2

0.008

 

0.0273

ABA and auxin crosstalk

         

 TCONS_00033126

PIN4

10.190

5.358

3.9632

7.2267

Met pathway

         

 TCONS_00038414

Cysteine synthase

0.094

2.415

0.0386

2.8547

 TCONS_00035466

AdoMet:Met S-methyltransferase

0.105

0.5236

 TCONS_00000319

S-adenosylmethionine synthas

5.156

7.679

1.7983

4.4588

 TCONS_00049344

Met synthase

4.748

5.275

1.9543

3.8106

 TCONS_00052600

Serine acetyltransferase

19.437

Epigenetic regulators

     

 TCONS_00072327

EFS (Histone H3 methyltransferase)

20.418

0.3253

 TCONS_00057450

HUB1(C3HC4 RING finger)

6.917

0.7614

Genetic expression difference of auxin-responsive seed dormancy and germination in the acquainted core metabolism pathways

The crosstalk of ABA and GA [12], and interaction of auxin and ABA [13] were the most important pathways controlling seed dormancy and germination. Other important dormancy regulators could be divided into four groups involved in seed maturation, hormonal action, dormancy and chromatin regulation [14]. To study the changes of these important genes and signal pathways, we utilized a blastx search against the NCBI NR database, the homolog unigenes of which in tobacco were identified. Express patterns of these unigenes’ were obtained from differential expression analyses, and the result showed that EFS, HUB1 and AHG3 in auxin-responsive seed dormancy were significantly up-regulated and down-regulated (Table 4).

Met metabolism is a housekeeping mechanism in all organisms, and also is central to seed germination [19]. As the methods above, unigenes in methionine metabolism was studied. Met synthase and serine acetyltransferase gene were significantly unregulated both in auxin-responsive germinated seeds and conventional germinated seeds (Table 4). Cysteine (Cys) synthase gene was up-regulated in auxin-responsive seed dormancy seeds and down-regulated in primary dormancy seeds (Table 4).

Validation of auxin-responsive genes by quantitative real-time PCR

To validate RNA-seq results, quantitative real-time reverse transcription-PCR (qRT-PCR) was used to conduct the expression analysis of randomly assigned nineteen auxin-responsive genes in dormancy and germination. Table 4 and Additional file 10: Table S1 show the comparison between the qRT-PCR and RNA-seq analysis, showing that all the auxin-responsive genes tested and previously identified by RNA-seq were confirmed by qRT-PCR. The results showed a significant positive correlation between the two quantitative approaches of gene expression (Pearson correlation: p = 5.9E-3, r = 0.65; Spearman correlation: p = 5.2E-5, ρ = 0.84), indicating that the RNA-seq expression analysis performed is highly reliable.

Discussion

Seed dormancy and germination are complex biological processes which are affected by both developmental and environmental factors. Auxin was recognized as a secondary dormancy hormone that controls seed dormancy and germination in Arabidopsis [13]. In this study, we found that tobacco seeds imbibed in a high concentration of exogenous auxin solution could promote seed dormancy and inhibit germination assayed by both restraining radicle protrusion and cotyledon greening. However, the microscopic scanning results implied that the seeds soaked in auxin solution were germinating as many follicles bubbles were found in cells whose vacuoles did not expand completely despite their treatment with ddH2O. The transcriptome PCA results also indicated that auxin-induced seeds are more similar to the seeds treated with ddH2O when compared to the primary dormant seeds. Seed dormancy has been defined as the incapacity of a viable seed to germinate under favorable conditions [1, 20]. So, this exogenous auxin-mediated seed dormancy can be referred to as an environmental model that prevents seed germination in an unfavorable condition.

Dormancy or germination depends on the balance between the resistance strength of the surrounding tissues and the growth force of the elongating radicle [14]. In this study, we found that exogenous auxin completely restrained radicle emergence, but not refrained endosperm rupture judged by the activity of β-1,3glucanase, a specific enzyme that was necessary for endosperm rupture during tobacco seed germination [2123]. As recognized, radicle cell elongation was necessary for seed germination and was generally accepted to be sufficient for the completion of radicle protrusion, while cell division was not essential [24]. Thus, auxin level may also be the prerequisite for radicle development and emergence during seed germination. The seeds of triple tir1afb2afb3 and the quadruple mutant tir1afb1afb2afb3 [25] in Arabidopsis failed to develop a hypocotyl and root meristem. Therefore, high concentration of exogenous auxin in this study might also inhibit hypocotyl and root meristem development.

A recent study carried out by Liu et al. 2013 on Arabidopsis, revealed that auxin and ABA in seed dormancy are interdependent. Auxin acted upstream of the major regulator of seed dormancy by activating the ABA response, but the ABA biosynthesis was not stimulated [13]. This study also revealed, that seeds imbibed in superfluous exogenous auxin did not show increase in ABA level. GA and IAA levels significantly increased during the imbibition stage, and both of them progressively decreased in the subsequent germination stage. These findings suggest that seed in order to release form the dormant state, more GA synthesis is required to antagonize the application of the auxin. The GA pathway was shown to have been subjected to regulation by auxin, and the auxin promotes Arabidopsis root growth by modulating gibberellin response [26]. GAs, although required for the completion of germination, are not directly involved in many processes taking place during germination, which occurred at a stage coinciding with or very close to radicle emergence [19]. So, the exogenous auxin application might significantly promoted dormancy by activating the ABA response during seed dormancy, and also inhibited the radicle development and emergence by modulating gibberellin response during seed germination.

The induction of seed dormancy is controlled by a diverse group of regulators, which can be divided into four groups that may be involved in: i. seed maturation, ii. hormonal action, iii. dormancy and iv. chromatin regulation [14]. In present study, we found that a hormonal regulator AHG3 was significantly down-regulated. AHG3/AtPP2CA functions as a negative regulator in the ABA-signaling pathway, suggesting that it plays a major role in ABA signaling in seed germination and early growth of Arabidopsis [27]. Moreover, expression levels of two epigenetic regulators EFS and HUB1 were significantly up-regulated in this study. The EFS gene has been selected as a phase transition regulator during seed germination in a transcriptional network modelling study, and the mutant efs seeds also show a variety of seed phenotypes including precocious germination [28]. The RDO4/HUB1 gene was initially identified on the basis of its reduced dormancy phenotype [29].

Met metabolism is metabolism central for seed germination [19]. During seed germination of Arabidopsis [3032], rice [33, 34], and peas [35], Met synthase or adometsynthetase accumulation increased. In Arabidopsis, studies have shown that the accumulation level of Met synthase strongly increased prior to radicle emergence, but no further increase was observed during radicle emergence [3032]. In this study, Met synthase and adometsynthetase gene were significantly up-regulated (refer to auxin-responsive germination). Serine acetyltransferase is a crucial enzyme in Cys synthesis metabolism that was significantly up-regulated in auxin-responsive germinated seeds. Cys is a precursor of Met biosynthesis [36] and constitutes a building block contributing to protein structure through the formation or reduction of disulfide bonds as catalyzed by Trxs. It is well documented that these enzymes affect a myriad of proteins during germination [37]. Cys is also the precursor of the major antioxidant molecule glutathione (GSH), which is involved in several processes playing a role in germination. The GSH-ascorbate cycle [38] or the formation of S-nitroso glutathione (GSNO), or a storage form of NO plays a pivotal role in seed physiology [39]. Above all, auxin-responsive germination refers to an enhanced met pathway in the transcriptome.

Conclusions

Unlike controlling of seed dormancy by exogenous ABA in a microscale, this exogenous auxin-mediated seed dormancy is more likely to be an environmental model that prevents seed germination in an unfavorable condition. Compared to the cotyledon, the radicle was more sensitive to exogenous auxin stimulation. Radicles of seeds that imbibed in 1 g/L exogenous auxin solution could not develop normally and emerge. In response to exogenous auxin stimulation, seeds would stimulate more GA synthesis to antagonize the effect of auxin. As the auxin level decreased, seeds recovered from the dormancy status to a germination status. Principal component analysis revealed that the transcriptome of auxin-responsive dormancy seeds was more similar to that of imbibed seeds when compared to primary dormancy seeds. And the transcriptome of auxin-responsive germinated seeds was more similar to that of conventional germinated seeds when compared to auxin-responsive dormancy seeds. To obtain the signaling pathways induced by auxin, the unigenes of showed differential expression between untreated seeds and auxin-imbibed seeds relative to H2O-imbibed seeds were chosen, was used to do gene function analysis. Auxin-responsive dormancy was associated with flavonol biosynthetic process, gibberellin metabolic process, adenylyl-sulfate reductase activity, thioredoxin activity, glutamate synthase (NADH) activity and chromatin regulation. Auxin-responsive germination responded to ABA, auxin, JA and SA mediated signaling pathway (red, far red and blue light), glutathione and methionine metabolism, of which most importantly we found that the auxin-responsive secondary seed dormancy refers to epigenetic regulation and germination to enhance Met pathway. Our study, thus, uncovers a previously unrecognized transcriptional regulatory networks and physiological development processes of seed dormancy and germination with superfluous auxin signal activate.

Methods

Seed imbibition; germination and radicle traits measurement

Seeds of tobacco (Nicotianatabacum L.)Nanjiang3 were obtained from Guizhou Academy of Tobacco Science. Seeds were surface sterilized with 1 % CuSO4 solution for 30 min and then 0.5 % ZnSO4 solution for 15 min on a shaker and then washed three times with double distilled water for two minutes each. Sterile seeds were imbibed in a supplementation hormone solution of (0, 10, 100, 1000) mg/l IAA for 24 h in a 12 h light/12 h dark cycle at 25 °C ± 1 °C, with untreated seeds as control. The samples were washed three times with distilled water. Then, the seeds in each treatment were sown on the surface of paper bed in 90-mm-diameter plastic petri dishes and incubated in a 12 h light/12 h dark cycle at 25 °C ± 1 °C. Germination was defined as visible radicle emergence to seed length. After 156 h, ten radicles, randomly sampled from germinated seeds, were weighed on a 10−3 g balance, and radicle length and surface area measured with WinRHIZO [40].

Extraction, purification and quantification of the phytohormones and β-1,3glucanase activity in seeds

The 0, 36, 72, 108 and, 144 h geminating seeds were collected for β-1,3glucanase activity quantification and 0, 72 and, 144 h geminating seeds for phytohormones ABA, GA1+3 and IAA quantification. The method for extraction, purification, and quantification of phytohormones was modified from the description of Wang [41]. ELISA kits used for estimation of the hormonal levels came from China Agricultural University (Beijing, China). The procedures for proteins extraction were modified from the Leubner-Metzger described [21]. ELISA kits used for the estimation of the β-1,3glucanase activity came from R&D Systems parent company (Minneapolis, America).

Scanning the vacuole of imbibed seeds by electron microscope

Among the imbibed samples, 0 and 1000 mg/L IAA treated samples were used for subcellular structure observation. Approximately half of the seeds were fixed in FAA (Formalin-Acetic - Alcohol) buffer and exhausted with an aspirator pump. Subsequently, serial transverse sections from the paraffin-embedded tissue were sequentially stained with safranin and fast green. Finally, these sections were observed with a transmission electron microscope (JEOL 1230, JEOL Ltd, and Japan).

RNA extraction and next generation sequencing

The total RNA from the tobacco seeds was extracted using total RNA purification kit (LC Science, TRK-1001) according to the manufacturer’s instructions. The integrity and quality of the total RNA were checked using NanoDrop 2000 Spectrophotometer (Thermo Scientific, USA) and formaldehyde agarose gel electrophoresis. RNA was only used when the Abs260 nm/Abs280 nm ratio was >1.8. Constructing database standards were as follows: RIN value ≥ 7.5, RNA content ≥ 15 μg and, concentration ≥ 300 ng/μl.

mRNA were enriched from 5ug qualified total RNA using Invitrogen Dynabeads mRNA Ditect kit, and then mRNA were fragmented on block at 95 °C for 2mins followed by the addition of stop solution to end the reaction. After purification by Qiagen kit, the RNA fragments were used to first strand cDNA synthesis by SMARTscript II reverse transcriptase. Afterward, SMARTeroligos and dNTPs were added to synthesize double cDNA. After gel purification of cDNA, purified products were used as template to generate sequencing library. We used qPCR to check library quality and calculate library concentration. Libraries were sequenced with Illumina HiSeq 2000 platform, each sample yielding 10Gb data from the final library fragments using V3 reagent. Base calling was performed by CASAVA 1.8 software (Illumina).

Transcriptome assembly with reference genome and functional classification

The RNA-Seq reads generated by the Illumina Genome Analyzer were initially processed to remove the adapter sequences and low-quality bases at the 3′ end. After preprocessing the RNA-Seq data, the reads were mapped to the K326 genome using a spliced aligner called Tophat [42] that can be used to identify novel splicing events and generate novel transcripts. Tophat with default parameters which allow up to two mismatches and report up to 40 alignments for reads mapping at multiple positions was run. The sam files generated by Tophat were provided as input to the software Cufflinks [18], which assembled the alignments in the sam file into transcripts. Then, Cufflinks were run with parameters to construct a minimum set of transcripts that best describes the RNA-Seq reads. Subsequently all libraries were assembled by Cufflinks. Cuffmerge [18] was used to merge these assemblies to generate a unique transcript sets, we called them as unigenes. Later, these unigenes were used to estimate express abundance (FPKM) by Cufflinks.

For unigenes function annotation, homology search with blastx algorithm was performed. Firstly, each transcript with length ≥ 200 bp was searched against NCBI NR database (ftp://ftp.ncbi.nih.gov/blast/db) and KOG database (ftp://ftp.ncbi.nih.gov/pub/COG/KOG/kyva) using blastx. The best similar hit with an E-value < 1.0e-5 was chosen to generate transcript annotation information. Secondly, each transcript with length ≥ 200 bp was annotated with GO database (http://www.geneontology.org/) with Blast2GO [43] that was based on the blast algorithm to obtain the Biological Process (BP), Cellular Component (CC) and Molecular Function (MF) GO terms information of annotated transcripts. Finally, all transcripts were searched against KEGG database with KAAS tool [44], and multiple plant organisms were chosen to get the KEGG best homologous ortholog IDs with the default parameters.

Gene differential expression and gene enrichment analyses

For unigenes expression analysis, preprocessed RNA-seq reads were mapped to unique transcripts with Bowtie2, and then the unigene reads counts were obtained by eXpress, which can correct multiple mapped reads. Then, differential express transcripts between two treatments without replicate were detected by R DESeq package [45], which normalized the library size based on library reads counts and detected the DE genes based on the negative binomial distribution. nbinomTest ()function was used for no-replicate analysis. Differential express transcripts p-value was corrected by Benjamini and Hochberg FDR correction.

Over-representation of GO terms of differential express unigenes were identified by BiNGO plugin [46] in Cytoscape software with a hypergeometric test after Benjamini and Hochberg FDR correction at a significance level of p-value < 0.05 based on our custom tobacco transcripts GO annotated datasets.

Over-representation of KEGG pathways of differential express unigenes were identified with GSEAKEGGHyperGParams() function in R GOstats package [47], which was based on the hypergeometric test. P-values were corrected by Benjamini and Hochberg FDR method, then chose a significance level of p < 0.05. The KEGG native diagrams were obtained using keggview.native() function in R Pathview package [48].

Real-time quantitative PCR

Quantification was performed with a two-step reaction process: reverse transcription (RT) and PCR. Each RT reaction consisted of 0.5 μg RNA, 2 μl of PrimerScript Buffer, 0.5 μl of oligo dT, 0.5 μl of random 6mers and 0.5 μl of PrimerScript RT Enzyme Mix I (TaKaRa, Japan), in a total volume of 10 μl. Reactions were performed in a GeneAmp® PCR System 9700 (Applied Biosystems, USA) for 15 min at 37 °C, followed by heat inactivation of RT for 5 s at 85 °C. The 10 μl RT reaction mix was then diluted 10 times in nuclease-free water and held at −20 °C.

Real-time PCR was performed using LightCycler® 480 II Real-time PCR Instrument (Roche, Swiss) with 10 μl PCR reaction mixture that included 1 μl of cDNA, 5 μl of 2 × LightCycler® 480 SYBR Green I Master (Roche, Swiss), 0.2 μl of forward primer, 0.2 μl of reverse primer and 3.6 μl of nuclease-free water. Reactions were incubated in a 384-well optical plate (Roche, Swiss) at 95 °C for 10 min, followed by 40 cycles of 95 °C for 10 s, and 60 °C for 30 s. Each sample was run in triplicate for analysis. At the end of the PCR cycles, melting curve analysis was performed to validate the specific generation of the expected PCR product. The primer sequences were designed in the laboratory and synthesized by Generay Biotech (Generay, PRC) based on the mRNA sequences obtained from the NCBI database (Additional file 11: Table S2). The expression levels of mRNAs were normalized to L25 and were calculated using the 2-ΔΔCt method [49].

Statistics

The results are expressed as means ± standard deviation (SD) calculated from at least three replications per treatment. ANOVA for radicle traits, β-1,3glucanase activity and plant hormone levels were performed using the Ducan’s test (P < 0.05 error level). Statistical analyses were performed using SPSS software Ver.16.0, and plotting using Origin software Ver.8.5.

Availability of supporting data

RNA-seq read data has been deposited in the NCBI SRA database under accession number SRP068795.

Declarations

Acknowledgments

This work was financially supported by special funds from molecular genetics key laboratory of China National Tobacco Corporation, youth fund from the Guizhou Provincial Tobacco Company of China National Tobacco Corporation (201526) and Key projects from the Guizhou Provincial Tobacco Company of China National Tobacco Corporation (201321).

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. 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.

Authors’ Affiliations

(1)
College of Agriculture and Biotechnology, China Agricultural University
(2)
Molecular Genetics Key Laboratory of China Tobacco, Guizhou Academy of Tobacco Science
(3)
Institute of Tobacco, Guizhou University
(4)
Institute of Crop Sciences, Chinese Academy of Agricultural Sciences

References

  1. Bewley JD. Seed germination and dormancy. Plant Cell. 1997;9(7):1055–66.PubMed CentralView ArticlePubMedGoogle Scholar
  2. Kucera B, Cohn MA, Leubner-Metzger G. Plant hormone interactions during seed dormancy release and germination. Seed Sci Res. 2005;15(04):281–307.View ArticleGoogle Scholar
  3. Razem FA, Baron K, Hill RD. Turning on gibberellin and abscisic acid signaling. Curr Opin Plant Biol. 2006;9(5):454–9.View ArticlePubMedGoogle Scholar
  4. Yamaguchi S. Gibberellin metabolism and its regulation. Annu Rev Plant Biol. 2008;59:225–51.View ArticlePubMedGoogle Scholar
  5. Morris K, Linkies A, Muller K, Oracz K, Wang X, Lynn JR, et al. Regulation of seed germination in the close Arabidopsis relative Lepidium sativum: a global tissue-specific transcript analysis. Plant Physiol. 2011;155(4):1851–70.PubMed CentralView ArticlePubMedGoogle Scholar
  6. Nambara E, Okamoto M, Tatematsu K, Yano R, Seo M, Kamiya Y. Abscisic acid and the control of seed dormancy and germination. Seed Sci Res. 2010;20(02):55–67.View ArticleGoogle Scholar
  7. Linkies A, Muller K, Morris K, Tureckova V, Wenk M, Cadman CS, et al. Ethylene interacts with abscisic acid to regulate endosperm rupture during germination: a comparative approach using Lepidium sativum and Arabidopsis thaliana. Plant Cell. 2009;21(12):3803–22.PubMed CentralView ArticlePubMedGoogle Scholar
  8. Subbiah V, Reddy KJ. Interactions between ethylene, abscisic acid and cytokinin during germination and seedling establishment in Arabidopsis. J Biosci. 2010;35(3):451–8.View ArticlePubMedGoogle Scholar
  9. Chiwocha SD, Cutler AJ, Abrams SR, Ambrose SJ, Yang J, Ross AR, et al. The etr1-2 mutation in Arabidopsis thaliana affects the abscisic acid, auxin, cytokinin and gibberellin metabolic pathways during maintenance of seed dormancy, moist-chilling and germination. Plant J. 2005;42(1):35–48.View ArticlePubMedGoogle Scholar
  10. Belin C, Megies C, Hauserova E, Lopez-Molina L. Abscisic acid represses growth of the Arabidopsis embryonic axis after germination by enhancing auxin signaling. Plant Cell. 2009;21(8):2253–68.PubMed CentralView ArticlePubMedGoogle Scholar
  11. Vanneste S, Friml J. Auxin: a trigger for change in plant development. Cell. 2009;136(6):1005–16.View ArticlePubMedGoogle Scholar
  12. Vanstraelen M, Benkova E. Hormonal interactions in the regulation of plant development. Annu Rev Cell Dev Biol. 2012;28:463–87.View ArticlePubMedGoogle Scholar
  13. Liu X, Zhang H, Zhao Y, Feng Z, Li Q, Yang HQ, et al. Auxin controls seed dormancy through stimulation of abscisic acid signaling by inducing ARF-mediated ABI3 activation in Arabidopsis. Proc Natl Acad Sci U S A. 2013;110(38):15485–90.PubMed CentralView ArticlePubMedGoogle Scholar
  14. Graeber K, Nakabayashi K, Miatton E, Leubner-Metzger G, Soppe WJ. Molecular mechanisms of seed dormancy. Plant Cell Environ. 2012;35(10):1769–86.View ArticlePubMedGoogle Scholar
  15. Oh E, Kang H, Yamaguchi S, Park J, Lee D, Kamiya Y, et al. Genome-wide analysis of genes targeted by PHYTOCHROME INTERACTING FACTOR 3-LIKE5 during seed germination in Arabidopsis. Plant Cell. 2009;21(2):403–19.PubMed CentralView ArticlePubMedGoogle Scholar
  16. Sierro N, Battey JN, Ouadi S, Bakaher N, Bovet L, Willig A, et al. The tobacco genome sequence and its comparison with those of tomato and potato. Nat Commun. 2014;5:3833.PubMed CentralView ArticlePubMedGoogle Scholar
  17. Trapnell C, Pachter L, Salzberg SL. TopHat: discovering splice junctions with RNA-Seq. Bioinformatics. 2009;25(9):1105–11.PubMed CentralView ArticlePubMedGoogle Scholar
  18. Trapnell C, Williams BA, Pertea G, Mortazavi A, Kwan G, van Baren MJ, et al. Transcript assembly and quantification by RNA-Seq reveals unannotated transcripts and isoform switching during cell differentiation. Nat Biotechnol. 2010;28(5):511–5.PubMed CentralView ArticlePubMedGoogle Scholar
  19. Rajjou L, Duval M, Gallardo K, Catusse J, Bally J, Job C, et al. Seed germination and vigor. Annu Rev Plant Biol. 2012;63:507–33.View ArticlePubMedGoogle Scholar
  20. Finch-Savage WE, Leubner-Metzger G. Seed dormancy and the control of germination. New Phytol. 2006;171(3):501–23.View ArticlePubMedGoogle Scholar
  21. Leubner-Metzger G, Frundt C, Vogeli-Lange R, Meins Jr F. Class I β-1,3-Glucanases in the endosperm of tobacco during germination. Plant Physiol. 1995;109:751–9.PubMed CentralPubMedGoogle Scholar
  22. Leubner-Metzger G, Fründt C, Meins Jr F. Effects of gibberellins, darkness and osmotica on endosperm rupture and class I β-1,3-glucanase induction in tobacco seed germination. Planta. 1996;199:282–8.View ArticleGoogle Scholar
  23. Leubner-Metzger G, Petruzzelli L, Waldvogel R, Vogeli-Lange R, Meins F. Ethylene-responsive element binding protein (EREBP) expression and the transcriptional regulation of class I β-1,3-glucanase during tobacco seed germination. Plant Mol Biol. 1998;38:785–95.View ArticlePubMedGoogle Scholar
  24. Barroco RM, Van Poucke K, Bergervoet JH, De Veylder L, Groot SP, Inze D, et al. The role of the cell cycle machinery in resumption of postembryonic development. Plant Physiol. 2005;137(1):127–40.PubMed CentralView ArticlePubMedGoogle Scholar
  25. Mai YX, Wang L, Yang HQ. A gain-of-function mutation in IAA7/AXR2 confers late flowering under short-day light in Arabidopsis. J Integr Plant Biol. 2011;53:480–92.View ArticlePubMedGoogle Scholar
  26. Fu X, Harberd NP. Auxin promotes Arabidopsis root growth by modulating gibberellin response. Nature. 2003;421(6924):740–3.View ArticlePubMedGoogle Scholar
  27. Yoshida T, Nishimura N, Kitahata N, Kuromori T, Ito T, Asami T, et al. ABA-hypersensitive germination3 encodes a protein phosphatase 2C (AtPP2CA) that strongly regulates abscisic acid signaling during germination among Arabidopsis protein phosphatase 2Cs. Plant Physiol. 2006;140(1):115–26.PubMed CentralView ArticlePubMedGoogle Scholar
  28. Bassel GW, Lan H, Glaab E, Gibbs DJ, Gerjets T, Krasnogor N, et al. Genome-wide network model capturing seed germination reveals coordinated regulation of plant cellular phase transitions. Proc Natl Acad Sci U S A. 2011;108(23):9709–14.PubMed CentralView ArticlePubMedGoogle Scholar
  29. Liu Y, Koornneef M, Soppe WJ. The absence of histone H2B monoubiquitination in the Arabidopsis hub1 (rdo4) mutant reveals a role for chromatin remodeling in seed dormancy. Plant Cell. 2007;19(2):433–44.PubMed CentralView ArticlePubMedGoogle Scholar
  30. Gallardo K, Job C, Groot SP, Puype M, Demol H, Vandekerckhove J, et al. Proteomic analysis of Arabidopsis seed germination and priming. Plant Physiol. 2001;126:835–48.PubMed CentralView ArticlePubMedGoogle Scholar
  31. Gallardo K, Job C, Groot SP, Puype M, Demol H, Vandekerckhove J, et al. Importance of methionine biosynthesis for Arabidopsis seed germination and seedling growth. Physiol Plant. 2002;116:238–47.View ArticlePubMedGoogle Scholar
  32. Gallardo K, Job C, Groot SP, Puype M, Demol H, Vandekerckhove J, et al. Proteomics of Arabidopsis seed germination. A comparative study of wild-type and gibberellin-deficient seeds. Plant Physiol. 2002;129:823–37.PubMed CentralView ArticlePubMedGoogle Scholar
  33. Kim ST, Kang SY, Wang Y, Kim SG, Hwang du H, Kang KY. Analysis of embryonic proteome modulation by GA and ABA from germinating rice seeds. Proteomics. 2008;8:3577–87.View ArticlePubMedGoogle Scholar
  34. Kim ST, Wang Y, Kang SY, Kim SG, Rakwal R, Kim YC, et al. Developing rice embryo proteomics reveals essential role for embryonic proteins in regulation of seed germination. J Proteome Res. 2009;8:3598–605.View ArticlePubMedGoogle Scholar
  35. Wang WQ, Moller IM, Song SQ. Proteomic analysis of embryonic axis of Pisum sativum seeds during germination and identification of proteins associated with loss of desiccation tolerance. J Proteomics. 2012;77:68–86.View ArticlePubMedGoogle Scholar
  36. Ravanel S, Gakiere B, Job D, Douce R. The specific features of methionine biosynthesis and metabolism in plants. Proc Natl Acad Sci U S A. 1998;95(13):7805–12.PubMed CentralView ArticlePubMedGoogle Scholar
  37. Buchanan BB, Balmer Y. Redox regulation: a broadening horizon. Annu Rev Plant Biol. 2005;56:187–220.View ArticlePubMedGoogle Scholar
  38. Bonsager BC, Shahpiri A, Finnie C, Svensson B. Proteomic and activity profiles of ascorbate-glutathione cycle enzymes in germinating barley embryo. Phytochemistry. 2010;71(14–15):1650–6.View ArticlePubMedGoogle Scholar
  39. Bethke PC, Libourel IG, Jones RL. Nitric oxide reduces seed dormancy in Arabidopsis. J Exp Bot. 2006;57(3):517–26.View ArticlePubMedGoogle Scholar
  40. Li ZH, Ren XL, Long MJ, Kong DJ, Wang ZH, Liu YL. Capsule colour quantification-based evaluation of seed dryness and vigour during natural and artificial drying in Nicotiana tabacum. L. Seed Sci Technol. 2015;43:208–17.View ArticleGoogle Scholar
  41. Wang Y, Li B, Du M, Eneji AE, Wang B, Duan L, et al. Mechanism of phytohormone involvement in feedback regulation of cotton leaf senescence induced by potassium deficiency. J Exp Bot. 2012;63(16):5887–901.PubMed CentralView ArticlePubMedGoogle Scholar
  42. Kim D, Pertea G, Trapnell C, Pimentel H, Kelley R, Salzberg SL. TopHat2: accurate alignment of transcriptomes in the presence of insertions, deletions and gene fusions. Genome Biol. 2013;14(4):R36.PubMed CentralView ArticlePubMedGoogle Scholar
  43. Gotz S, Garcia-Gomez JM, Terol J, Williams TD, Nagaraj SH, Nueda MJ, et al. High-throughput functional annotation and data mining with the Blast2GO suite. Nucleic Acids Res. 2008;36(10):3420–35.PubMed CentralView ArticlePubMedGoogle Scholar
  44. Moriya Y, Itoh M, Okuda S, Yoshizawa AC, Kanehisa M. KAAS: an automatic genome annotation and pathway reconstruction server. Nucleic Acids Res. 2007;35(Web Server issue):W182–5.PubMed CentralView ArticlePubMedGoogle Scholar
  45. Anders S, Huber W. Differential expression analysis for sequence count data. Genome Biol. 2010;11(10):R106.PubMed CentralView ArticlePubMedGoogle Scholar
  46. Maere S, Heymans K, Kuiper M. BiNGO: a Cytoscape plugin to assess overrepresentation of gene ontology categories in biological networks. Bioinformatics. 2005;21(16):3448–9.View ArticlePubMedGoogle Scholar
  47. Falcon S, Gentleman R. Using GOstats to test gene lists for GO term association. Bioinformatics. 2007;23(2):257–8.View ArticlePubMedGoogle Scholar
  48. Luo W, Brouwer C. Pathview: an R/Bioconductor package for pathway-based data integration and visualization. Bioinformatics. 2013;29(14):1830–1.PubMed CentralView ArticlePubMedGoogle Scholar
  49. Livak KJ, Schmittgen TD. Analysis of relative gene expression data using real-time quantitative PCR and the 2(−Delta Delta C (T)) Method. Methods. 2001;25(4):402–8.View ArticlePubMedGoogle Scholar

Copyright

© Li et al. 2016

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