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Identification of tRNA nucleoside modification genes critical for stress response and development in rice and Arabidopsis

BMC Plant BiologyBMC series – open, inclusive and trusted201717:261

https://doi.org/10.1186/s12870-017-1206-0

Received: 20 July 2017

Accepted: 6 December 2017

Published: 21 December 2017

The Correction to this article has been published in BMC Plant Biology 2018 18:37

Abstract

Background

Modification of nucleosides on transfer RNA (tRNA) is important either for correct mRNA decoding process or for tRNA structural stabilization. Nucleoside methylations catalyzed by MTase (methyltransferase) are the most common type among all tRNA nucleoside modifications. Although tRNA modified nucleosides and modification enzymes have been extensively studied in prokaryotic systems, similar research remains preliminary in higher plants, especially in crop species, such as rice (Oryza sativa). Rice is a monocot model plant as well as an important cereal crop, and stress tolerance and yield are of great importance for rice breeding.

Results

In this study, we investigated how the composition and abundance of tRNA modified nucleosides could change in response to drought, salt and cold stress, as well as in different tissues during the whole growth season in two model plants–O. sativa and Arabidopsis thaliana. Twenty two and 20 MTase candidate genes were identified in rice and Arabidopsis, respectively, by protein sequence homology and conserved domain analysis. Four methylated nucleosides, Am, Cm, m1A and m7G, were found to be very important in stress response both in rice and Arabidopsis. Additionally, three nucleosides,Gm, m5U and m5C, were involved in plant development. Hierarchical clustering analysis revealed consistency on Am, Cm, m1A and m7G MTase candidate genes, and the abundance of the corresponding nucleoside under stress conditions. The same is true for Gm, m5U and m5C modifications and corresponding methylation genes in different tissues during different developmental stages.

Conclusions

We identified candidate genes for various tRNA modified nucleosides in rice and Arabidopsis, especially on MTases for methylated nucleosides. Based on bioinformatics analysis, nucleoside abundance assessments and gene expression profiling, we propose four methylated nucleosides (Am, Cm, m1A and m7G) that are critical for stress response in rice and Arabidopsis, and three methylated nucleosides (Gm, m5U and m5C) that might be important during development.

Keywords

tRNAModified nucleosideMethyltransferaseStressDevelopment

Background

As indispensable participants in protein synthesis, tRNAs are highly modified in both prokaryotes and eukaryotes. The genes that encode tRNA modification enzymes constitute far more than the tRNA coding genes, which further highlights the importance of tRNA modification [1, 2]. Besides the canonical functions in protein synthesis, emerging evidence emphasized critical role for tRNA nucleoside modification in regulation of cellular response to stimuli and developmental signals [27]. Previous studies in bacteria, yeast and animal systems illustrated various tRNA modified nucleosides affecting bacterial virulence, yeast exocytosis, C.elegans embryo development and human mitochondrial diseases such as MELAS and MERRF [713].

However, we understand quite poorly about the function of tRNA nucleoside modifications on either development or stress response in higher plants. Plants are particularly prone to environmental changes such as drought, cold and high salinity stresses. Research of tRNA nucleoside modification changes upon various stresses or during development is scarce in higher plants. In Arabidopsis, a few components of the Elongator complex (ELP1–6, KTI11–14) were shown to regulate cell proliferation, anthocyanin biosynthesis, drought stress tolerance and immune response [1418]. These genes participated in ncm5U (5-carbamoylmethyluridine) modification at position 34 on certain tRNA species [1921]. In addition to the elp mutants, certain Arabidopsis mutants of tRNA nucleoside modification genes also showed mild phenotypes, such as slow growth of smo2 [22] and reduced respiration rate and less fresh weight of seedlings in tad1 [23]. It has been long postulated that modified nucleosides on tRNA molecules may function as “biosensor” for environmental and physiological changes [24, 25], as a fast module to regulate gene expression at translational level. In agreement with this hypothesis, the abundance of tRNA modified nucleosides do change in response to various stresses [26]. The mutants of AtTRM4B, m5C (5-methylcytidine) methylation modification gene, had shorter primary roots and increased sensitivity to oxidative stress [27]. Our recent study showed that Am nucleoside (2’-O-methyladenosine) was induced by salt stress in a variety of plants including Rice, Poplar, Arabidopsis and Brachypodium [28]. Overexpression of OsTRM13, the corresponding gene for Am and Cm modification at position 4, improved salt stress tolerance in rice [28].

Among the hundreds of modified nucleosides present on tRNA molecules, methylation is the most ubiquitous and abundant type [2931]. Nucleoside methylation are catalyzed by methyltransferases (MTases) [30, 31]. tRNA MTases in S. cerevisiae are mostly AdoMet-dependent methyltransferase, either in RFM superfamily or SPOUT superfamily [3236]. Another method of classification of AdoMet-dependent MTases was suggested by Schubert HL et al. by using the catalytic domain as criteria for function annotation [37]. MTases for tRNA nucleoside methylations in S. cerevisiae were considered as good references for the study of tRNA MTases in higher plants. Although a few tRNA MTase in Arabidopsis have been reported [22, 27, 38], little is known in cereal crops such as rice. The PlantRNA database (http://plantrna.ibmp.cnrs.fr/plantrna/) provides decent amount of information on tRNA genomic sequences and processing enzymes (such as the 5′ /3′ processing and intron-splicing enzymes), but not information for the exact location of modified nucleosides in tRNA sequences, either in Arabidopsis or in rice. As for the function of tRNA nucleoside modification enzymes, very few were supported with experimental data in Arabidopsis [22, 23, 38, 39], and none in O. sativa.

The detection and quantification of tRNA modified nucleosides provide a basis for studying the function of modifying enzymes. In comparison with the HPLC method used before for nucleoside quantification, Liquid chromatography-coupled tandem quadrupole mass spectrometry (LC-MS/MS) is a powerful tool with higher sensitivity for modified nucleosides quantification [6, 40]. In this study, LC-MS/MS was used to quantify changes of tRNA modified nucleosides under stress conditions as well as in different tissues along plant development in rice and Arabidopsis. 25 known tRNA nucleosides can be clearly separated and detected (Additional file 5: Figure S1), among which 12 were methylated nucleosides catalyzed by different TRM enzymes as MTases or associated partners (Additional file 5: Figure S2). With protein sequence homology, we identified candidate genes for a subset of methylated nucleosides. Hierarchical clustering was performed on abundance of modified nucleoside and transcript level of modification candidate genes from developmental or stress dataset. The results indicated that, besides Am nucleoside, other methylated nucleosides such as Cm, m1A (1-methyladenosine), and m7G (7-methylguanosine) might participate in regulation of stress response; whereas Gm (2’-O-methylguanosine), m5U (5-methyluridine) and m5C (5-methylcytidine) most likely participated in regulation of pant development.

Results

Identification of tRNA MTase candidate genes in rice and Arabidopsis

O. sativa and A. thaliana were selected for the monocot or the dicot model organism. tRNA MTase candidate genes were identified based on protein sequence homology with yeast tRNA MTases. 13 Trm proteins involved in methylated nucleosides in S. cerevisiae were used as query sequences, for blastp search of the rice and Arabidopsis candidates (Table 1, Additional file 4). Figure S2 (Additional file 5: Figure S2) showed the name of the yeast TRM genes, name and structure of the corresponding nucleosides, and the location of these methylated nucleosides on tRNA molecules. Trm1 for N2,N2-dimethylguanosine (m2 2G) modification; Trm9 for the last step of 5-methyloxy carbonyl-methyluridine (mcm5U) and 5-methyl-amino-methyluridine (mnm5U); Trm3 and Trm7 for 2’-O-methylguanosine (Gm) and 2’-O-methylcytosine (Cm) respectively; Trm13 for 2’-O-methyladenosine (Am); Trm2 for 5-methyluridine (m5U), Trm11 and Trm112 form a complex for 2-methylguanosine (m2G); Trm5 and Trm10 for 1-methylguanosine (m1G) at position 37 and position 9, respectively; Trm8 and Trm82 from a complex for 7-methylguanosine (m7G); Trm6 and Trm61 for 1-methyladenosine (m1A); Trm4 for 5-methylcytidine (m5C), and Trm140/ABP140 for 3-methylcytidine (m3C) modification at position 32 of yeast tRNA [41] We did not quantify m3C in this study, since we only got one unique peak (Additional file 5: Figure S1) under 258/126 m/s (Q1/Q3) which overlapped with the m5C nucleoside standard. Trm6-Trm61 is a two-subunit complex responsible for m1A58 in tRNAi Met, tRNAAsn GUU, tRNAArg ACU and a few other isoacceptors [42, 43]. However, TRM61 is a direct MTase with conserved AdoMet-binding domain. This binding domain was not found in TRM6 protein, indicating TRM6 is accessory protein that may play a role in maintaining the stability of the complex [44, 45]. Similarly, TRM82 is a noncatalytic subunit of the heterodimeric complex TRM8-TRM82, which catalyzes m7G formation at position 46 [46]. TRM112 is a 15-KDa zinc-finger protein that assisted TRM9 and TRM11 for mcm5U and m2G methylation, respectively [47, 48].
Table 1

Arabidopsis and rice candidate genes for tRNA nucleoside methylation

Yeast Protein

Modification

Arabidopsis Candidate Gene

E-value

Rice Candidate Gene*

E-value

Note

Trm1

m2 2G

At3g02320 (AtTRM1a)

1.0E-74

LOC_Os03g57280 (OsTRM1a)

1.1E-62

 
  

At5g15810 (AtTRM1b)

2.0E-73

LOC_Os10g21360 (OsTRM1b)

3.8E-62

 
  

At3g56330 (AtTRM1c)

2.0E-21

LOC_Os05g25870 (OsTRM1c)

3.1E-07

 

Trm2

m5U

At3g21300 (AtTRM2a)

1.0E-23

LOC_Os01g09750 (OsTRM2a)

9.9E-24

 
  

At2g28450 (AtTRM2b)

9.0E-09

LOC_Os04g01480 (OsTRM2b)

3.5E-10

 

Trm3

Gm

At4g17610 (AtTRM3)

7.0E-35

LOC_Os03g01110 (OsTRM3)

9.3E-29

 

Trm4

m5C

At4g40000 (AtTRM4a)

e-101

LOC_Os09g29630 (OsTRM4a)

1.2E-100

 
  

At2g22400 (AtTRM4b)

2.0E-97

LOC_Os08g37780 (OsTRM4b)

9.8E-95

 
  

At5g55920 (AtTRM4c)

1.0E-21

LOC_Os02g49270 (OsTRM4c)

6.0E-24

 
  

At4g26600 (AtTRM4d)

2.0E-19

LOC_Os09g37860 (OsTRM4d)

4.7E-23

 
  

At3g13180 (AtTRM4e)

4.0E-14

LOC_Os08g27824 (OsTRM4e)

1.1E-10

 
  

At1g06560 (AtTRM4f)

9.0E-10

LOC_Os02g21510 (OsTRM4f)

4.5E-10

 
  

At5g66180 (AtTRM4g)

3.0E-08

LOC_Os02g12600 (OsTRM4g)

1.5E-06

 
  

At5g26180 (AtTRM4h)

2.0E-08

   

Trm5

m1G

At3g56120 (AtTRM5a)

3.0E-58

LOC_Os01g29409 (OsTRM5a)

3.7E-60

 
  

At4g27340 (AtTRM5b)

4.0E-53

LOC_Os02g39370 (OsTRM5b)

2.4E-41

 
  

At4g04670 (AtTRM5c)

4.0E-06

   

Trm6

m1A

At2g45730 (AtTRM6)

4.0E-03

LOC_Os04g02150 (OsTRM6)

8.3E-18

not MTase

Trm7

Cm

At5g01230 (AtTRM7a)

4.0E-79

LOC_Os06g49140 (OsTRM7a)

1.5E-74

 
  

At4g25730 (AtTRM7b)

1.0E-28

LOC_Os05g49230 (OsTRM7b)

2.3E-34

 
  

At5g13830 (AtTRM7c)

8.0E-20

LOC_Os09g27270 (OsTRM7c)

7.4E-17

 
    

LOC_Os03g60750 (OsTRM7d)

2.8E-15

 

Trm8

m7G

At5g24840 (AtTRM8a)

8.0E-76

LOC_Os06g12990 (OsTRM8a)

4.1E-65

 
  

At5g17660 (AtTRM8b)

6.0E-08

LOC_Os01g35170 (OsTRM8b)

3.1E-06

 

Trm9

mcm5 U

At1g36310 (AtTRM9)

2.0E-34

LOC_Os02g51490 (OsTRM9)

9.3E-42

 

Trm10

m1G

At5g47680 (AtTRM10)

1.0E-29

LOC_Os02g49360 (OsTRM10)

1.5E-28

 

Trm11

m2G

At3g26410 (AtTRM11)

2.0E-53

LOC_Os02g35060 (OsTRM11)

2.0E-54

 

Trm13

Am

At4g01880 (AtTRM13)

5.0E-24

LOC_Os03g61750 (OsTRM13)

1.6E-09

 

Trm61

m1A

At5g14600 (AtTRM61)

7.0E-47

LOC_Os04g25360 (OsTRM61a)

2.8E-44

 
    

LOC_Os04g25990 (OsTRM61b)

1.5E-43

 
    

LOC_Os05g07830 (OsTRM61c)

1.2E-15

 

Trm82

m7G

At1g03110 (AtTRM82)

6.0E-11

LOC_Os03g53530 (OsTRM82)

2.2E-09

not MTase

Trm112

m2G

At1g78190 (AtTRM112a)

2.0E-11

LOC_Os07g43020 (OsTRM112)

2.0E-12

not MTase

  

At1g22270 (AtTRM112b)

3.0E-07

   

Trm140

m3C

At2g26200 (AtTRM140a)

1E-48

LOC_Os03g04940 (OsTRM140a)

3.4E-35

 
  

At1g54650 (AtTRM140b)

2E-28

LOC_Os07g23169 (OsTRM140b)

1.8E-25

 
As shown in Table 1, 33 candidate genes were identified in both O. sativa and A. thaliana, respectively, with a blastp cutoff value at 1.0E-06 (Table 1). A further analysis by PFAM database confirmed the presence of conserved domain of the TRM genes, in both rice and Arabidopsis candidate genes (Table 2). Twenty two candidate genes were selected from rice and 20 from Arabidopsis, after a manual screen based on the domain structure similarity between the query sequences and the candidate genes (Table 2).
Table 2

Pfam analysis of MTase candidate genes in rice and Arabidopsis

Gene

Source

Accession

Description

Position

Gene

Source

Accession

Description

Position

(m2 2G)Trm1

Pfam

PF02005

m22G tRNA meth_tr

33–490

(mcm5U)Trm9

Pfam

PF08241

Methyltransferase domain

50–141

AT3G02320

pfam

PF02005

m22G tRNA meth_tr

11–466

AT1G36310

pfam

PF08241

Methyltransferase type 11

112–202

AT5G15810

pfam

PF02005

m22G tRNA meth_tr

109–564

LOC_Os02g51490

HMMPfam

PF08241.5

Methyltransf_11

106–196

LOC_Os10g21360

pfam

PF02005.9

TRM

58–438

     

LOC_Os03g57280

pfam

PF02005.9

TRM

19–476

(m1G)Trm10

Pfam

PF01746

tRNA (Guanine-1)-meth_tr

104–276

     

AT5G47680

pfam

PF01746

tRNA (guanine-N1-)-meth_tr

128–293

(m5U)Trm2

Pfam

PF01938

(Uracil-5)-meth_tr

164–227

LOC_Os02g49360

 

PF01746.14

tRNA_m1G_MT

128–293

AT3G21300

pfam

PF05958

(Uracil-5)-meth_tr

354–552

     

LOC_Os01g09750

HMMPfam

PF05958.4

tRNA_U5-meth_tr

366–554

(m2G)Trm11

Pfam

PF01170

Putative RNA methylase family UPF0020

184–297

     

AT3G26410

pfam

PF01170

Putative RNA methylase

193–315

(Gm)Trm3

Pfam

PF00588

tRNA/rRNA meth_tr, SpoU

1286–1428

LOC_Os02g35060

pfam

PF01170.11

UPF0020

193–315

AT4G17610

pfam

PF00588

tRNA/rRNA meth_tr, SpoU

1700–1842

     

LOC_Os03g01110

HMMPfam

PF00588.12

SpoU_methylase

1575–1716

(Am)Trm13

Pfam

PF11722

CCCH zinc finger in TRM13 protein

18–47

      

Pfam

PF05253

U11-48 K-like CHHC zinc finger

71–97

(m5C)Trm4

Pfam

PF01189

NOL1/NOP2/sun family

254–581

 

Pfam

PF05206

Methyltransferase TRM13

179–473

At4g40000

pfam

PF01189

NOL1/NOP2/sun family

155–350

AT4G01880

pfam

PF05206

Methyltransferase TRM13

167–445

At2g22400

pfam

PF01189

NOL1/NOP2/sun family

163–361

 

pfam

PF05253

U11-48 K-like CHHC zinc finger domain

42–66

LOC_Os09g29630

HMMPfam

PF01189.10

Nol1_Nop2_Fmu

168–364

 

pfam

PF11722

Zinc finger, CCCH-type, TRM13

7–36

LOC_Os08g37780

HMMPfam

PF01189.10

Nol1_Nop2_Fmu

185–388

LOC_Os03g61750

pfam

PF11722.1

zf-TRM13_CCCH

20–49

      

pfam

PF05253.5

zf-U11-48 K

61–86

(m1G)Trm5

Pfam

PF02475

tRNA transferase Trm5/Tyw2

177–436

 

pfam

PF05206.7

TRM13

181–247

AT3G56120

pfam

PF02475

tRNA transferase Trm5/Tyw2

116–411

     

AT4G27340

pfam

PF02475

tRNA transferase Trm5/Tyw2

343–542

(m1A)Trm61

Pfam

PF08704

tRNA meth_tr complex GCD14 subunit

72–362

LOC_Os01g29409

HMMPfam

PF02475.9

Met_10

309–505

AT5G14600

pfam

PF08704

tRNA meth_tr complex GCD14 subunit

9–313

LOC_Os02g39370

HMMPfam

PF02475.9

Met_10

156–442

LOC_Os04g25360

HMMPfam

PF08704.3

GCD14

14–321

     

LOC_Os04g25990

pfam

PF08704.3

GCD14

14–320

(Cm)Trm7

Pfam

PF01728

FtsJ-like meth_tr

21–207

     

AT5G01230

pfam

PF01728

Ribosomal RNA meth_tr RrmJ/FtsJ

21–209

(m3C)Trm140

Pfam

PF08242

Methyltransferase domain

439–543

AT4G25730

pfam

PF01728

Ribosomal RNA meth_tr RrmJ/FtsJ

22–200

AT2G26200

pfam

PF08242

Methyltransferase type 12

79–180

AT5G13830

pfam

PF01728

Ribosomal RNA meth_tr RrmJ/FtsJ

19–223

AT1G54650

pfam

PF08242

Methyltransferase type 12

87–214

LOC_Os06g49140

HMMPfam

PF01728.12

FtsJ

21–209

LOC_Os03g04940

pfam

PF08242.5

Methyltransf_12

63–163

LOC_Os05g49230

HMMPfam

PF01728.12

FtsJ

22–201

 

pfam

PF10294.2

Methyltransf_16

326–485

LOC_Os09g27270

HMMPfam

PF01728.12

FtsJ

22–142

LOC_Os07g23169

pfam

PF08242.5

Methyltransf_12

96–229

LOC_Os03g60750

HMMPfam

PF01728.12

FtsJ

20–231

     

(m7G)Trm8

Pfam

PF02390

Putative meth_tr

74–279

     

AT5G24840

pfam

PF02390

tRNA (guanine-N-7) meth_tr

48–246

     

AT5G17660

pfam

PF02390

tRNA (guanine-N-7) meth_tr

115–305

     

LOC_Os06g12990

HMMPfam

PF02390.10

Methyltransf_4

58–254

     

LOC_Os01g35170

HMMPfam

PF02390.10

Methyltransf_4

2–183

     

The tRNA nucleoside MTase candidate genes show an uneven distribution both in Arabidopsis and rice genomes

The chromosomal location of the rice or Arabidopsis tRNA nucleoside MTase candidate genes were shown in Fig. 1. Chromosome sizes and the position of each gene can be estimated by the scale on the left. The chromosomal distribution patterns showed that some chromosomes and chromosomal regions had a relatively high distribution of MTase genes. For example, the 22 rice TRM candidate genes were mapped to 10 out of 12 rice chromosomes and 54.5% of them were anchored on chr1, chr2 and chr3, whereas one only on chr.5, chr.7, chr.8 and chr.10, respectively, and no MTase gene was located on chr.11 or chr.12 (Fig. 1a). LOC_Os04g25360 and LOC_Os04g25990 located on chr.4 (marked out by the wireframe) were tandem duplicated gene pairs homologous to Trm61 (Fig. 1a). In Arabidopsis, TRM candidate genes were found to be located more frequently on chr.4 and chr.5 (12 of 20), especially within a ca.10 Mb segment region on chr.5 (Fig. 1b). On the contrary, only two TRM candidates were mapped to chr.1 or chr.2 (Fig. 1b). No tandem duplicated gene pairs were found among Arabidopsis MTase candidate genes.
Figure 1
Fig. 1

Physical map of tRNA nucleoside methyltransferase candidate genes on rice (a) or Arabidopsis (b) genomes. a, Chromosome location of 22 rice MTases candidate genes. b, Chromosome location of 20 Arabidopsis MTases candidate genes. Chromosome size are indicated by relative lengths. Tandemly duplicated genes are indicated by boxes

Phylogenetic and conserved motif analysis of MTase in rice and Arabidopsis

Multiple sequence alignment was employed to construct a phylogenic tree of the tRNA nucleoside MTase candidates in rice and Arabidopsis, together with the 13 Trm query proteins in yeast (Fig. 2).
Figure 2
Fig. 2

Circular neighbor-joining (N-J) tree of rice and Arabidopsis MTase candidate genes. Supporting values from bootstrap analysis were shown for each branch. The three groups of Trm proteins clustered together were annotated with red lines for group I, blue lines for group II and green lines for group III, respectively

As shown in Fig. 2, MTases that modify analogous substrates were closely clustered: the three MTase groups related to cytidine modification (Trm4p, Trm140p for m5C and m3C respectively, and Trm7p for Cm modification) were clustered in group I; also found in group I was Trm9p which participated in the last step of mcm5U methylation. However, Sequence-structure-function analysis of tRNA m5C methyl-transferase Trm4p and RNA m5U methyltransferase revealed that RNA:m5C MTases shared a number of common features with the RNA:m5U MTases [49], suggesting a tentative evolution route of the two groups of 5-methylpyrimidine MTases. On the contrary, group II and group III MTases were responsible for methylpurine modifications: Trm3p, Trm8p and Trm11p corresponding to Gm, m7G and m2G in group II, and Trm5p, Trm10p and Trm1p corresponding to m2 2G and m1G methylations in group III. In between group II and III we found Trm61p and Trm13p relatives for Am and m1A methylations (Fig. 2).

Conserved motif analysis by MEME program [50] revealed the presence of conserved residues within the catalytic domain of group I, group II and group III MTases (Fig. 3). All four methyl-pyrimidine MTases (Trm4p, Trm7p, Trm9p, Trm140) exhibited a striking conservation of a Glycine (G) residue, as well as a consensus “VLD(L/M)CAA(P/N)” motif as its neighbor (Fig. 3a, Additional file 5: Figure S3). The strong conservation suggested that the Glycine residue and its surrounding motif most likely are involved in a structure that is required for substrate binding and/or catalysis. Similarly, a conserved pattern, the GxE/D motif was found in group II, from the Trm3p, Trm8p and Trm11p homologs (Fig. 3b). Previously, a crystal structure of the Trm8p revealed that E126 (as part of the conserved motif) is involved in a bidentate hydrogen bond with the ribose hydroxyl group [46]. Finally, a conserved DLD motif was found from Trm1p and Trm10p homologs from group III (Fig. 3c). In supporting of the functional relevance for this DLD motif, D211 from Trm1p of S. cerevisiae and D132 from Trmp1 of Aquifex aeolicus have been shown as the catalytic center for m2 2G methylation [51, 52].
Figure 3
Fig. 3

Conserved motif analysis of group I (a), group II (b) and group III (c) MTase candidate genes. X axis indicated position for each residue within the identified motifs, Y axis indicated bit score values. The size of the residue letter represented the degree of conservation within the group of proteins analyzed. The table below each graph illustrated the protein sequence for each member, with the name of the protein, starting position of the conserved motif and the whole motif sequence

Am, cm, m1A and m7G methylated nucleosides respond to stress treatment in rice and Arabidopsis

Hierarchical clustering analysis about tRNA nucleoside methylated modification and the candidate genes expression under stress tolerance was constructed (Fig. 4 and Fig. 5, Additional file 6). The amounts of methylated nucleosides under biotic and abiotic stress was quantified by LC-MS/MS method, in total 15 methylated nucleosides were quantified (marked in red color, Additional file 5: Figure S1). The gene expression profiles (Additional files 2 and 3) corresponding to tRNA methylation candidate genes were obtained from GEO DataSet (https://www.ncbi.nlm.nih.gov/gds/). Hierarchical clustering analyses revealed 4 methylated nucleosides (Cm, Am, m1A and m7G) with consistent changes on nucleoside level and the candidate methylation genes under stress tolerance (black wireframe, Fig. 4 and Fig. 5 Additional file 6). An obviously decrease of m1A and m7G nucleosides was observed under cold stress or salt stress, the level of Cm nucleoside was found to be decreasing under drought stress, whereas the level of Am nucleoside increased dramatically under salt stress in both rice and Arabidopsis (Fig. 4, Fig. 5, Fig. 7a, and b). In a recent study, we have shown that abscisic acid (ABA) treatment also induced a significant increase of Am nucleosides in rice seedlings [28].
Figure 4
Fig. 4

Hierarchical clustering analysis between tRNA nucleoside modification and the Arabidopsis candidate genes expression under stress conditions. Heat map was generated using raw data of nucleosides abundance or MTase candidate genes expression level under stress conditions, respectively, horizontally normalized and logarithmically transformed. LN2 value was presented in color key, which corresponded with ratio of change on either nucleoside level of the gene expression level under various stress conditions. A hierarchy-clustering was shown on the left, showing similar patterns between nucleosides and MTase candidate genes. Solid boxes indicated nucleosides and corresponding genes clustered together

Figure 5
Fig. 5

Hierarchical clustering analysis between tRNA nucleoside modification and the rice candidate genes expression under stress conditions. Heat map was generated using raw data of nucleosides abundance or MTase candidate genes expression level under stress conditions, respectively, horizontally normalized and logarithmically transformed. LN2 value was presented in color key, which corresponded with ratio of change on either nucleoside level of the gene expression level under various stress conditions. A hierarchy-clustering was shown on the left, showing similar patterns between nucleosides and MTase candidate genes. Solid boxes indicated nucleosides and corresponding genes clustered together

Three nucleosides gm, m5U and m5C are important in plant development

Nine different tissues in rice and six representative tissues of Arabidopsis were used to investigate tRNA nucleosides levels during the whole development period. Similar as in the stress dataset, the expression profile of methylated nucleoside candidate genes were obtained from the CREP database (http://crep.ncpgr.cn) for rice genes, and the TileViz database (http://jsp.Weigelworld.Org/tilevi-z/tileviz.jsp) for Arabidopsis genes (Additional file 1). A heat map was constructed based on the expression data and the levels of tRNA nucleosides in different tissues under various stages of development (Fig. 6, Additional file 6). Interestingly, three nucleosides Gm, m5U and m5C were clustered together with their corresponding candidate genes (Trm3p for Gm, Trm2p for m5U and Trm4p for m5C, respectively), both in rice (Fig. 6a) and in Arabidopsis (Fig. 6b). Many nucleoside modification genes in rice were found to be highly expressed in callus sample, and generally low levels in stamen tissues (Fig. 6A). In Arabidopsis, a high expression level of tRNA nucleoside modification candidate genes was found in root samples (Fig. 6b), a good consistency between m5C nucleoside and the corresponding candidate genes AtTRM4a (At4g40000) and AtTRM4b (At2g22400) were found in roots (Fig. 6b). The high level of m5C nucleoside and its corresponding methylation genes suggested a possible role in root development in Arabidopsis, which is consistent with recent findings of short root phenotype in attrm4b mutant [27].
Figure 6
Fig. 6

Hierarchical clustering analysis between tRNA nucleoside methylated modification and candidate genes expression level during development stage. Heatmap profiles about the abundance of methylated nucleosides and the expression level of the rice (a) or Arabidopsis (b) MTase candidate genes from developmental dataset. Heat map was generated from raw data of nucleoside levels and gene expression levels, normalized horizontally. LN2 values was shown above in color key. Solid boxes indicated nucleosides and the corresponding genes clustered into the same group. In panel B, green boxes indicated m5C nucleoside and the corresponding candidate genes in Arabidopsis. Solid boxes indicated nucleosides and corresponding genes clustered together

Figure 8 summarized methylated nucleosides associated with stress tolerance or development, with corresponding MTase candidate genes illustrated in yellow circles (Os_ for rice genes, At_ for Arabidopsis genes, Table 1). As mentioned above, Am, Cm, m1A and m7G nucleosides were regulated by stress (marked by green circle), in particular the Am nucleoside for salt stress and ABA treatment. The abundance of these nucleosides under stress conditions were clustered together (indicated by green lines in Fig. 8) with the expression level of the MTase candidate genes, i.e. TRM13, TRM7, TRM61 and TRM8 homologs in both rice and Arabidopsis. Another five nucleosides, m5U, Gm, m2G, Um and m2 2G, also changed under stress conditions but showed no consistency with the expression level of the MTase candidate genes (gray circle, green dotted lines in Fig. 8). As for development, we found that three nucleosides Gm, m5C and m5U that might be important to plant development, these three nucleosides were clustered together with their MTase candidate genes (red circle, red solid lines in Fig. 8). m5C nucleoside abundance was high in young tissues, especially in roots. The abundance of Gm nucleoside increased in old leaves (Fig. 7c and d), indicating its potential role in leave senescence. Several other nucleosides such as m2G, m1A, m1G, ncm5U also showed tissue/organ specificity during development, but no consistency was found with the expression of their corresponding MTase candidate genes (gray circle, red dotted lines in Fig. 8).
Figure 7
Fig. 7

Selected methylated nucleosides that were potentially important for stress or development. (a and b) Quantification of Cm, m1A, Am, m7G nucleosides under stress conditions in Arabidopsis or rice. (c and d) Quantification of m5C, m5U and Gm nucleosides in different tissues during development

Figure 8
Fig. 8

A model displaying the relationships within tRNA nucleoside methylation and stress/development. Green and red solid lines indicated nucleoside abundance and expression level of the corresponding MTase genes under stress or during development which could be clustered together, respectively. Green and red dashed lines showed nucleosides that changes under stress or during development, but shows no consistency with MTase gene expression

Discussion

In this study, we investigated the profile of tRNA modified nucleosides in different tissues and under various abiotic stress conditions in both rice and Arabidopsis seedlings. Rice is an important cereal crop and a monocot model plant. We identified 22 rice tRNA MTase candidate genes and 20 Arabidopsis genes by protein sequence homology to S. cerevisiea. Analysis of conserved motifs from the candidate MTases showed several types of conserved motifs including residues that might be involved in catalytic activity (Fig. 3). Also from motif analysis, three groups of MTases responsible for cytidine methylations, Trm4p (for m5C), Trm140(for m3C) and Trm7p (for Cm modification), were clustered together. A high conserved Glycine residue was identified from these groups of MTases (Fig. 3a), possibly indicating a role for Gly in structure required for substrate binding. In supporting of this, an isosteric mutation of K179 in Trm4p (neighbor to the conserved G177) was completely inactive [50]. G177 and K179 in Trm4p are located in motif I, which is regarded as AdoMet-binding site rather than the catalytic center. Likewise, G55 from Trm7p is also located in motif I predicted as AdoMet- and ribose-binding sites, while another conserved residue predicted by the motif analysis, D49 (Fig. 3a), is associated with binding to ribose and phosphate group of the nucleotide to be methylated [53]. The conserved G in Trm140p (G549) was also reported critical for AdoMet-binding. As for the second conserved D residue, point mutation of D547 in Trm140p resulted in decreased activity in m3C methylation [41]. Taken together, the high conserved domain in group I (Fig. 3a) most likely constitute for an AdoMet-binding site and indispensable for catalytic activity.

With protein sequence homology, we identified candidate genes for a subset of modified nucleosides from rice and Arabidopsis genomes. However, in half of the branches (Fig. 2) more than one candidate genes were present. This could be anticipated because gene duplication event is rather common in plant kingdom, additionally tissue-specific and subcellular organelles may demand for different set-up of tRNA nucleoside modification machinery. With hierarchical clustering analysis between gene expression and abundance of modified nucleosides in tissues and stress conditions, we found that not every candidate gene can cluster together with the modified nucleosides level. This could be explained in the following ways: 1) the unequal preference between redundant candidate genes, i.e. one of the redundant candidate genes might bear the primary modification activity whereas the other might be inactive. An example of this is the Trm4 homologs in Arabidopsis: AtTRM4a was shown to be inactive while AtTRM4b participated in the methylation at tRNA positions C48, C49, and C50 [27]. This is consistent with our result from hierarchical clustering analysis, that AtTRM4b(At2g22400) expression and the corresponding modified nucleosides m5C were clustered together under development (Fig. 6). 2) Insignificant or irregular changes in tRNA modified nucleosides and the expression of corresponding candidate genes. In other word, these nucleosides may hardly be regulated by drought, cold or salt stress.

From hierarchical clustering, we propose that certain methylated nucleosides, namely Am (2′-methyladenosine), Cm (2’-O-methylcytidine), m1A (1-methyladenosine), and m7G(7-methylguanosine) were involved in plant stress responses, while Gm(2’-O-methylguanosine), m5U (5-methyluridine), m5C (5-methylcytidine) in plant development. With the corresponding MTase genes identified in rice and Arabidopsis, it is possible to verify the function of these candidate genes in regulation of certain type of abiotic stress, or in general physiology for plant growth and development. Actually, our preliminary result of several Arabidopsis candidate genes suggested these candidate genes do have a role in stress response or root growth, our recent finding of OsTRM13 in salt stress tolerance in rice also suggests that the function of tRNA nucleoside modification and modification genes is yet to be illustrated.

Conclusion

We showed in this study that both physiological conditions and environmental stimuli led to changes in tRNA modified nucleosides, these changes were accompanied by regulation on the expression of corresponding modification genes. By quantification of both the level of methylated nucleosides and the candidate MTase genes, under drought, cold and high salinity stresses in rice and Arabidopsis, we found four methylated nucleosides (Am, Cm, m1A, and m7G) critical for stress response and similarly three nucleosides (Gm, m5U and m5C) for plant development. All results showed good consistency in rice and Arabidopsis. This highlighted future work for transgenic manipulation and functional study of the corresponding modification enzymes. Phylogeny and motif analysis also suggested conserved residues within each group of MTases, those residues may be important for catalytic activity which awaits to be tested by future work.

Methods

Plant material and growth conditions

Nipponbare rice (O. sativa cv. Japonica) seeds were germinated in sterilized water for 2 days and then grown hydroponically in a climate chamber with a 16 h-light /8 h-dark cycle at 28 °C. At 3-leaves stage (2–3 weeks after germination), seedlings were transferred to the field located at HuaZhong Agricultural University, Wuhan, HuBei Province (latitude N31°, longitude E115°, average altitude 27 m). The growth season starts from April–May and ends around August–September.

Arabidopsis in Colombian-0 background was used in this study. The sterilized seeds were sowed on 1/2 MS medium and grown in a culture room at 22 °C after vernalization, with 16 h light/8 h dark photo period at 4 °C. 10 days old seedlings were transplanted in soil, growing in a growth chamber with similar conditions.

Sampling of tissues during the whole growth season

Mature rice seeds were sterilized with 70% ethanol followed by 2.5% sodium hydrochloride, washed and soaked in distilled water for 2 days. Plumule and radicle were sampled after seed germination in the dark for 48 h. Seedlings were grown hydroponically in the climate chamber with the settings abovementioned. The following tissue samples were taken during the cultivation in the climate chamber: 3d–seedling and 3d–root taken 3 days after germination, 3-leaf seedling and corresponding root taken 2 weeks after germination. Samples of leaf, stem and root during the shooting stage (about 70 days after sowing), heading stage (about 90 days after sowing) and flowering stage (85–95 days after sowing) were taken after transferring seedling to the field. In addition, panicle, spikelet and anther samples were also taken during flowering stage. A callus sample was taken from MS medium after induction and two rounds of sub-culturing. All samples were taken with three biological duplicates, flash frozen and stored in −80 °C for further use.

For Arabidopsis sampling, roots were sampled 9–10 days after seed germination. Other samples were taken through the whole development stage as following: apex (seed germination for 1-2 day), seedling (germination for 7 day), young leaf (4-leaves stage), old leaf (rosette leaves in flowering stage), stem (base stems in flowering stage). All samples were taken with three biological replicates, flash frozen and stored in −80 °C for further use.

Stress treatment

For rice stress treatment, 9-d-old seedlings from climate chamber were used as starting materials. Cold stress was applied by putting rice seedlings into pre-equilibrated 4 °C cold water, samples were taken 0 d, 1 d, 3 d, 5 d, and 7 d after the treatment. A control set was taken with normal growth conditions. Drought (air dry) stress was applied by transferring seedlings onto 3MM filter paper under room temperature; samples were taken at the same time points as above. For high salinity stress, distilled water was changed into 200 mM NaCl for hydroponic cultivation and samples taken 0d, 1d, 3d, 5d, and 7d after salt stress. Samples were taken in triplicates, each sample with 15–20 seedlings.

Twenty one days old Arabidopsis Col.0 seedlings were used as starting materials for stress treatment. Drought stress was applied by water withholding and samples were taken at 0 d, 3 d, 7 d after the treatment. Cold stress and salt stress were applied in similar ways as for rice seedlings described above, a control set was taken with normal growth conditions. All samples were taken in triplicates, each sample with 5–10 seedlings.

tRNA isolation and nucleoside analysis by LC-MS/MS

Small RNAs (< 200 bp) were extracted using microRNA Extraction Kit (Omega Bio-tek Inc.), digested into nucleosides and analyzed by LC-MS/MS with an LC-20A HPLC system and a diode array UV detector (190-400 nm). Details for LC-MS/MS analysis was described previously [28]. The abundance of each nucleoside under stress conditions was normalized to that in control set, the ratio (fold of change) of each nucleoside was calculated and used for heatmap generation.

Database search for rice and Arabidopsis tRNA nucleoside modification candidate genes and bioinformatic analysis

The protein sequences of known tRNA nucleoside MTases from S. cerevisiae were used as query sequences, for retrieval of rice gene homologs with Blastp search tool on RGAP database (http://rice.plantbiology.msu.edu/index.shtml), or for Arabidopsis gene on TAIR database (http://www.arabidopsis.org/). A cut-off value was set as 1.0E-6 for initial identification of candidate genes. Protein sequences were manually verified by protein domain analysis on pfam (http://pfam.xfam.org/). The logos and conserved motifs were identified by MEME online searching engine (http://meme-suite.org/tools/meme) with parameters setup as the following: motif site distribution, any number of repetitions; maximum number of motifs, 5; motif width, from 8 to 50. Conserved motifs were verified on ESPript 3.0 (http://espript.ibcp.fr/ESPript/cgi-bin/ESPript.cgi) with an ALN file constructed by ClustalX 2.0.

All verified MTase genes were mapped to the O. sativa or A. thaliana genome chromosomes respectively with tool@Oryabase (http://viewer.shigen.info/ory-zavw/maptool/Map-Tool.do) for rice and Chromosome Map Tool (http://www.arabidopsis.org/jsp/ChromosomeMap/tool.jsp) for Arabidopsis, in addition to information from the RGAP and TAIR database. Non-rooted Neighborhood Joining tree of each family of MTases was conducted with MEGA4.0 software [54], bootstrap analysis was performed with 1000 iterations.

Gene expression analysis of MTase candidate genes

Microarray data of MTase candidate genes under drought, salt, cold stress and ABA (ABA treatment only for rice) treatment were downloaded from GEO (Gene Expression Omnibus, http://www.ncbi.nlm.nih.gov/gds/), data series GSE6901, GSE37940, GSE26280 and GSE58603 for rice stress, and data series GSE72050, GSE80099, GSE53308, GSE16765, GSE71271 and GSE3326 for Arabidopsis stress. CREP database http://crep.ncpgr.cn provided the expression data for rice MTase genes of the whole development stage, the developmental datasets for Arabidopsis MTases were downloaded from TileViz (http://jsp.Weigelworld.Org/tilevi-z/tileviz.jsp).

Hierarchical clustering analysis was performed with gene expression and abundance of modified nucleosides from developmental or stress datasets. The heat map construction used heatmap.2, a software written by R language using Euclidean distance as the distance metric for agglomerative clustering. The absolute expression value from different tissues and under different stress conditions were first normalized by control experiment, the ratios (fold of change) of each candidate gene was calculated and used for heatmap generation.

Notes

Abbreviations

ac4C: 

N4-acetylcytidine

Am: 

2’-O-methyladenosine

Cm: 

2’-O-methylcytidine

D: 

Dihydrouridine

Gm: 

2’-O-methylguanosine

I: 

Inosine

m1A: 

1-methyladenosine

m1G: 

1-methylguanosine

m1I: 

1-methylinosine

m2 2G: 

N2, N2-dimethylguanosine

m2A: 

2-methyladenosine

m2G: 

N2-methylguanosine

m3C: 

3-methylcytidine

m5C: 

5-methylcytidine

m5U: 

5-methyluridine

m6A: 

N6-methyladenosine

m6t6A: 

N6-methyl-N6-threonylcarbamoyladenosine

m7G: 

7-methylguanosine

mcm5U: 

5-methoxycarbonylmethyluridine

ncm5U: 

5-carbamoylmethyluridine

t6A: 

N6-threonylcarbamoyladenosine

Um: 

2’-O-methyluridine

Ψ: 

Pseudouridine

Declarations

Acknowledgements

We are grateful for Gunilla Jager (Dept. of Molecular Biology, Umea University, Sweden) for the help of HPLC analysis of rice tRNA nucleoside modifications under stress conditions. We thank Prof. Glenn Bjork (Umea University) for the advice and fruitful discussions. Thanks to Dr. Dongqin Li (National Key Laboratory of Crop Genetic Breeding and Improvement, HuaZhong Agriculture University) for the LC-MS analysis. We are very grateful for Prof. Staffan Persson (University of Melbourne) for the editing of the whole manuscript.

Funding

This study was supported by the National Natural Science Foundation of China (31,100,268 to Peng Chen, 31,270,658 to Bo Zheng); the Fundamental Research Funds for the Central Universities (2662015PY168), Natural Science Foundation of Hubei Province (2016CFB438). These funders supported the experimental study, data collection and analysis. No funder participated in data interpretation and writing of the manuscript.

Availability of data and materials

The data sets supporting the results of this article are included within the article and its additional files. Sequence data used in this manuscript can be found in the RGAP database (http://rice.plantbiology.msu.edu/index.shtml) for rice gene, or in TAIR database (http://www.arabidopsis.org/) for Arabidopsis gene. The neighbor-joining tree in Fig. 2 was deposited in TreeBASE (http://treebase.org) under the following URL: http://purl.org/phylo/treebase/phylows/study/TB2:S21714.

Authors’s contributions

PC and BZ conceived the project and designed the research plan. YW, CP and ZL performed the sampling of plant material, nucleoside and gene expression analysis. XL and ZH participated in all bioinformatic analysis involved in this study. YW and PC drafted the manuscript, BZ reviewed and revised it critically. All authors have read and approved the final version of the manuscript.

Ethics approval and consent to participate

Nipponbare rice (Oryza sativa japonica) and Arabidopsis in Colombian-0 seeds were maintained in this lab. The cultivation and collection of plant material complied with institutional guidelines in accordance with legislation from Faculty of Plant Science and Technology, Huazhong Agricultural University.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Publisher’s Note

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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)
Biomass and Bioenergy Research Centre, Huazhong Agricultural University, Wuhan, China
(2)
College of Plant Science and Technology, Huazhong Agricultural University, Wuhan, China
(3)
Key Laboratory of Horticultural Plant Biology of Ministry of Education, Huazhong Agricultural University, Wuhan, China
(4)
College of Horticulture and Forestry Sciences, Huazhong Agricultural University, Wuhan, China
(5)
College of Life Sciences, Shanxi Agricultural University, Taigu, China

References

  1. Björk GR, Durand JM, Hagervall TG, Leipuviene R, Lundgren HK, Nilsson K, Chen P, Qian Q, Urbonavicius J. Transfer RNA modification: influence on translational frameshifting and metabolism. FEBS Lett. 1999;452(1–2):47–51.View ArticlePubMedGoogle Scholar
  2. El Yacoubi B, Bailly M, de Crécy-Lagard V. Biosynthesis and function of posttranscriptional modifications of transfer RNAs. Annu Rev Genet. 2012;46:69–95.View ArticlePubMedGoogle Scholar
  3. Raina M, Ibba M. tRNAs as regulators of biological processes. Front Genet. 2014;5:171.View ArticlePubMedPubMed CentralGoogle Scholar
  4. Phizicky EM, Hopper AK. tRNA biology charges to the front. Genes Dev. 2010;24(17):1832–60.View ArticlePubMedPubMed CentralGoogle Scholar
  5. Thompson DM, Parker R. Stressing out over tRNA cleavage. Cell. 2009;138(2):215–9.View ArticlePubMedGoogle Scholar
  6. Chan CT, Dyavaiah M, DeMott MS, Taghizadeh K, Dedon PC, Begley TJ. A quantitative systems approach reveals dynamic control of tRNA modifications during cellular stress. PLoS Genet. 2010;6(12):e1001247.View ArticlePubMedPubMed CentralGoogle Scholar
  7. Emilsson V, Näslund AK, Kurland CG. Thiolation of transfer RNA in Escherichia coli varies with growth rate. Nucleic Acids Res. 1992;20(17):4499–505.View ArticlePubMedPubMed CentralGoogle Scholar
  8. Wolf J, Gerber AP, Keller W. tadA, an essential tRNA-specific adenosine deaminase from Escherichia coli. EMBO J. 2002;21(14):3841–51.View ArticlePubMedPubMed CentralGoogle Scholar
  9. Soma A, Ikeuchi Y, Kanemasa S, Kobayashi K, Ogasawara N, Ote T, Kato J, Watanabe K, Sekine Y, Suzuki T. An RNA-modifying enzyme that governs both the codon and amino acid specificities of isoleucine tRNA. Mol Cell. 2003;12(3):689–98.View ArticlePubMedGoogle Scholar
  10. Butler AR, White JH, Folawiyo Y, Edlin A, Gardiner D, Stark MJ. Two Saccharomyces cerevisiae genes which control sensitivity to G1 arrest induced by Kluyveromyces lactis toxin. Mol Cell Biol. 1994;14(9):6306–16.View ArticlePubMedPubMed CentralGoogle Scholar
  11. Lu J, Huang B, Esberg A, Johansson MJ, Byström AS. The Kluyveromyces lactis gamma-toxin targets tRNA anticodons. RNA. 2005;11(11):1648–54.View ArticlePubMedPubMed CentralGoogle Scholar
  12. Chen C, Tuck S, Byström AS. Defects in tRNA modification associated with neurological and developmental dysfunctions in Caenorhabditis elegans Elongator mutants. PLoS Genet. 2009;5(7):e1000561.View ArticlePubMedPubMed CentralGoogle Scholar
  13. Suzuki T, Nagao A, Suzuki T. Human mitochondrial tRNAs: biogenesis, function, structural aspects, and diseases. Annu Rev Genet. 2011;45:299–329.View ArticlePubMedGoogle Scholar
  14. Nelissen H, Fleury D, Bruno L, Robles P, De Veylder L, Traas J, Micol JL, Van Montagu M, Inzé D, Van Lijsebettens M. The elongata mutants identify a functional Elongator complex in plants with a role in cell proliferation during organ growth. Proc Natl Acad Sci U S A. 2005;102(21):7754–9.View ArticlePubMedPubMed CentralGoogle Scholar
  15. Chen Z, Zhang H, Jablonowski D, Zhou X, Ren X, Hong X, Schaffrath R, Zhu JK, Gong Z. Mutations in ABO1/ELO2, a subunit of holo-Elongator, increase abscisic acid sensitivity and drought tolerance in Arabidopsis thaliana. Mol Cell Biol. 2006;26(18):6902–12.View ArticlePubMedPubMed CentralGoogle Scholar
  16. Zhou X, Hua D, Chen Z, Zhou Z, Gong Z. Elongator mediates ABA responses, oxidative stress resistance and anthocyanin biosynthesis in Arabidopsis. Plant J. 2009;60(1):79–90.View ArticlePubMedGoogle Scholar
  17. DeFraia CT, Zhang X, Mou Z. Elongator subunit 2 is an accelerator of immune responses in Arabidopsis thaliana. Plant J. 2010;64(3):511–23.View ArticlePubMedGoogle Scholar
  18. Xu D, Huang W, Li Y, Wang H, Huang H, Cui X. Elongator complex is critical for cell cycle progression and leaf patterning in Arabidopsis. Plant J. 2012;69(5):792–808.View ArticlePubMedGoogle Scholar
  19. Huang B, Johansson MJ, Byström AS. An early step in wobble uridine tRNA modification requires the Elongator complex. RNA. 2005;11(4):424–36.View ArticlePubMedPubMed CentralGoogle Scholar
  20. Versées W, De Groeve S, Van Lijsebettens M. Elongator, a conserved multitasking complex? Mol Microbiol. 2010;76(5):1065–9.View ArticlePubMedGoogle Scholar
  21. Esberg A, Huang B, Johansson MJ, Byström AS. Elevated levels of two tRNA species bypass the requirement for elongator complex in transcription and exocytosis. Mol Cell. 2006;24(1):139–48.View ArticlePubMedGoogle Scholar
  22. Hu Z, Qin Z, Wang M, Xu C, Feng G, Liu J, Meng Z, Hu Y. The Arabidopsis SMO2, a homologue of yeast TRM112, modulates progression of cell division during organ growth. Plant J. 2010;61(4):600–10.View ArticlePubMedGoogle Scholar
  23. Zhou W, Karcher D, Bock R. Importance of adenosine-to-inosine editing adjacent to the anticodon in an Arabidopsis alanine tRNA under environmental stress. Nucleic Acids Res. 2013;41(5):3362–72.View ArticlePubMedPubMed CentralGoogle Scholar
  24. Björk GR, Ericson JU, Gustafsson CE, Hagervall TG, Jönsson YH, Wikström PM. Transfer RNA modification. Annu Rev Biochem. 1987;56:263–87.View ArticlePubMedGoogle Scholar
  25. Gustilo EM, Vendeix FA, Agris PF. tRNA's modifications bring order to gene expression. Curr Opin Microbiol. 2008;11(2):134–40.View ArticlePubMedPubMed CentralGoogle Scholar
  26. Chan CT, Pang YL, Deng W, Babu IR, Dyavaiah M, Begley TJ, Dedon PC. Reprogramming of tRNA modifications controls the oxidative stress response by codon-biased translation of proteins. Nat Commun. 2012;3:937.View ArticlePubMedPubMed CentralGoogle Scholar
  27. David R, Burgess A, Parker B, Li J, Pulsford K, Sibbritt T, Preiss T, Searle IR. Transcriptome-wide mapping of RNA 5-methylcytosine in Arabidopsis mRNAs and noncoding RNAs. Plant Cell. 2017;29(3):445–60.View ArticlePubMedGoogle Scholar
  28. Wang Y, Li D, Gao J, Li X, Zhang R, Jin X, Hu Z, Zheng B, Persson S, Chen P. The 2'-O-methyladenosine nucleoside modification gene OsTRM13 positively regulates salt stress tolerance in rice. J Exp Bot. 2017;68(7):1479–91.View ArticlePubMedPubMed CentralGoogle Scholar
  29. Cantara WA, Crain PF, Rozenski J, McCloskey JA, Harris KA, Zhang X, Vendeix FA, Fabris D, Agris PF. The RNA Modification Database, RNAMDB: 2011 update. Nucleic Acids Res. 2011;39:D195–201.View ArticlePubMedGoogle Scholar
  30. Hori H. Methylated nucleosides in tRNA and tRNA methyltransferases. Front Genet. 2014;5:144.View ArticlePubMedPubMed CentralGoogle Scholar
  31. Motorin Y, Helm M. RNA nucleotide methylation. Wiley Interdiscip Rev RNA. 2011;2(5):611–31.View ArticlePubMedGoogle Scholar
  32. Anantharaman V, Koonin EV, Aravind L. SPOUT: a class of methyltransferases that includes spoU and trmD RNA methylase superfamilies, and novel superfamilies of predicted prokaryotic RNA methylases. J Mol Microbiol Biotechnol. 2002;4(1):71–5.PubMedGoogle Scholar
  33. Liu RJ, Zhou M, Fang ZP, Wang M, Zhou XL, Wang ED. The tRNA recognition mechanism of the minimalist SPOUT methyltransferase, TrmL. Nucleic Acids Res. 2013;41(16):7828–42.View ArticlePubMedPubMed CentralGoogle Scholar
  34. Pioszak AA, Murayama K, Nakagawa N, Ebihara A, Kuramitsu S, Shirouzu M, Yokoyama S. Structures of a putative RNA 5-methyluridine methyltransferase, Thermus thermophilus TTHA1280, and its complex with S-adenosyl-L-homocysteine. Acta Crystallogr Sect F Struct Biol Cryst Commun. 2005;61(Pt 10):867–74.View ArticlePubMedPubMed CentralGoogle Scholar
  35. Urbonavicius J, Skouloubris S, Myllykallio H, Grosjean H. Identification of a novel gene encoding a flavin-dependent tRNA:m5U methyltransferase in bacteria--evolutionary implications. Nucleic Acids Res. 2005;33(13):3955–64.View ArticlePubMedPubMed CentralGoogle Scholar
  36. Atta M, Mulliez E, Arragain S, Forouhar F, Hunt JF, Fontecave M. S-Adenosylmethionine-dependent radical-based modification of biological macromolecules. Curr Opin Struct Biol. 2010;20(6):684–92.View ArticlePubMedGoogle Scholar
  37. Schubert HL, Blumenthal RM, Cheng X. Many paths to methyltransfer: a chronicle of convergence. Trends Biochem Sci. 2003;28(6):329–35.View ArticlePubMedPubMed CentralGoogle Scholar
  38. Leihne V, Kirpekar F, Vågbø CB, van den Born E, Krokan HE, Grini PE, Meza TJ, Falnes PØ. Roles of Trm9- and ALKBH8-like proteins in the formation of modified wobble uridines in Arabidopsis tRNA. Nucleic Acids Res. 2011;39(17):7688–701.View ArticlePubMedPubMed CentralGoogle Scholar
  39. Chen P, Jäger G, Zheng B. Transfer RNA modifications and genes for modifying enzymes in Arabidopsis thaliana. BMC Plant Biol. 2010;10:201.View ArticlePubMedPubMed CentralGoogle Scholar
  40. Meng Z, Limbach PA. Mass spectrometry of RNA: linking the genome to the proteome. Brief Funct Genomic Proteomic. 2006;5(1):87–95.View ArticlePubMedPubMed CentralGoogle Scholar
  41. Noma A, Yi S, Katoh T, Takai Y, Suzuki T, Suzuki T. Actin-binding protein ABP140 is a methyltransferase for 3-methylcytidine at position 32 of tRNAs in Saccharomyces Cerevisiae. RNA. 2011;17(6):1111–9.View ArticlePubMedPubMed CentralGoogle Scholar
  42. Roovers M, Wouters J, Bujnicki JM, Tricot C, Stalon V, Grosjean H, Droogmans L. A primordial RNA modification enzyme: the case of tRNA (m1A) methyltransferase. Nucleic Acids Res. 2004;32(2):465–76.View ArticlePubMedPubMed CentralGoogle Scholar
  43. Guelorget A, Roovers M, Guérineau V, Barbey C, Li X, Golinelli-Pimpaneau B. Insights into the hyperthermostability and unusual region-specificity of archaeal Pyrococcus abyssi tRNA m1A57/58 methyltransferase. Nucleic Acids Res. 2010;38(18):6206–18.View ArticlePubMedPubMed CentralGoogle Scholar
  44. Calvo O, Cuesta R, Anderson J, Gutiérrez N, García-Barrio MT, Hinnebusch AG, Tamame M. GCD14p, a repressor of GCN4 translation, cooperates with Gcd10p and Lhp1p in the maturation of initiator methionyl-tRNA in Saccharomyces cerevisiae. Mol Cell Biol. 1999;19(6):4167–81.View ArticlePubMedPubMed CentralGoogle Scholar
  45. Ozanick SG, Bujnicki JM, Sem DS, Anderson JT. Conserved amino acids in each subunit of the heteroligomeric tRNA m1A58 Mtase from Saccharomyces cerevisiae contribute to tRNA binding. Nucleic Acids Res. 2007;35(20):6808–19.View ArticlePubMedPubMed CentralGoogle Scholar
  46. Leulliot N, Chaillet M, Durand D, Ulryck N, Blondeau K, van Tilbeurgh H. Structure of the yeast tRNA m7G methylation complex. Structure. 2008;16(1):52–61.View ArticlePubMedGoogle Scholar
  47. Mazauric MH, Dirick L, Purushothaman SK, Björk GR, Lapeyre B. Trm112p is a 15-kDa zinc finger protein essential for the activity of two tRNA and one protein methyltransferases in yeast. J Biol Chem. 2010;285(24):18505–15.View ArticlePubMedPubMed CentralGoogle Scholar
  48. Purushothaman SK, Bujnicki JM, Grosjean H, Lapeyre B. Trm11p and Trm112p are both required for the formation of 2-methylguanosine at position 10 in yeast tRNA. Mol Cell Biol. 2005;25(11):4359–70.View ArticlePubMedPubMed CentralGoogle Scholar
  49. Bujnicki JM, Feder M, Ayres CL, Redman KL. Sequence-structure-function studies of tRNA:m5C methyltransferase Trm4p and its relationship to DNA:m5C and RNA:m5U methyltransferases. Nucleic Acids Res. 2004;32(8):2453–63.View ArticlePubMedPubMed CentralGoogle Scholar
  50. Bailey TL, Boden M, Buske FA, Frith M, Grant CE, Clementi L, Ren J, Li WW, Noble WS. MEME SUITE: tools for motif discovery and searching. Nucleic Acids Res. 2009;37:W202–8.View ArticlePubMedPubMed CentralGoogle Scholar
  51. Awai T, Kimura S, Tomikawa C, Ochi A, Ihsanawati, Bessho Y, Yokoyama S, Ohno S, Nishikawa K, Yokogawa T, Suzuki T, Hori H. Aquifex aeolicus tRNA (N2, N2-guanine)-dimethyltransferase (Trm1) catalyzes transfer of methyl groups not only to guanine 26 but also to guanine 27 in tRNA. J Biol Chem. 2009;284(31):20467–78.View ArticlePubMedPubMed CentralGoogle Scholar
  52. Awai T, Ochi A, Ihsanawati ST, Hirata A, Bessho Y, Yokoyama S, Hori H. Substrate tRNA recognition mechanism of a multisite-specific tRNA methyltransferase, Aquifex aeolicus Trm1, based on the X-ray crystal structure. J Biol Chem. 2011;286(40):35236–46.View ArticlePubMedPubMed CentralGoogle Scholar
  53. Pintard L, Lecointe F, Bujnicki JM, Bonnerot C, Grosjean H, Lapeyre B. Trm7p catalyses the formation of two 2'-O-methylriboses in yeast tRNA anticodon loop. EMBO J. 2002;21(7):1811–20.View ArticlePubMedPubMed CentralGoogle Scholar
  54. Tamura K, Dudley J, Nei M, Kumar S. MEGA4: molecular evolutionary genetics analysis (MEGA) software version 4.0. Mol Biol Evol. 2007;24(8):1596–9.View ArticlePubMedGoogle Scholar

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