Dynamic Cytosine DNA Methylation Patterns Associated with mRNA

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Omics Technologies Applied to Agriculture and Food

Dynamic cytosine DNA methylation patterns associated with mRNA and siRNA expression profiles in alternate bearing apple trees Sheng Fan, Xiuhua Gao, Cai Gao, Yang Yang, Xinzheng Zhu, Wei Feng, Ruimin Li, Muhammad Mobeen Tahir, Dong Zhang, Mingyu Han, and Na An J. Agric. Food Chem., Just Accepted Manuscript • DOI: 10.1021/acs.jafc.9b00871 • Publication Date (Web): 22 Apr 2019 Downloaded from http://pubs.acs.org on April 23, 2019

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Journal of Agricultural and Food Chemistry

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Dynamic Cytosine DNA Methylation Patterns Associated with mRNA

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and siRNA Expression Profiles in Alternate Bearing Apple Trees

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Sheng Fan1, Xiuhua Gao1, Cai Gao1, Yang Yang3, Xinzheng Zhu3, Wei

4

Feng3, Ruimin Li1, Muhammad Mobeen Tahir1, Dong Zhang1, Mingyu

5

Han1*, Na An1,2*

6 7 8 9 10 11

1

College of Horticulture, Northwest A&F University, Yangling 712100,

Shannxi, China 2

College of Life Science, Northwest A&F University, Yangling 712100,

Shaanxi, China 3

Innovation Experimental College, Northwest A&F University, Yangling

712100, Shaanxi, China

12 13 14 15 16 17 18 19 20 21 22

ACS Paragon Plus Environment


23

Sheng Fan: [email protected]

24

Xiuhua Gao: [email protected]

25

Cai Gao: [email protected]

26

Yang Yang: [email protected]

27

Xinzheng Zhu: [email protected]

28

Wei Feng: [email protected]

29

Ruimin Li: [email protected]

30

Muhammad Mobeen Tahir: [email protected]

31

Dong Zhang:[email protected]

32

Mingyu Han: [email protected]

33

Na An: [email protected]

34 35 36

*

Corresponding author

37

E-mail: [email protected];

38

Tel.: 86-029- 87082543

39

Fax: 86-029- 87082543

40

E-mail: [email protected]

41

Tel.: 86-029- 87082543

42

Fax: 86-029- 87082543

43 44


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ABSTRACT: Cytosine DNA methylation plays important roles in plants;

46

it can mediate gene expression to affect plant growth and development.

47

However, little is known about the potential involvement of cytosine

48

DNA methylation in apple, as well as in response to alternate bearing.

49

Here, we performed whole-genome bisulfate sequencing to investigate

50

genomic CG, CHG, and CHH methylation patterns, together with their

51

global mRNA accumulation, and small RNA expression in ‘Fuji’ apple

52

trees. Results showed that ‘Fuji’ apple trees had a higher CHH

53

methylation than Arabidopsis. Moreover, genomic methylation analysis

54

revealed that CG and CHG methylation was robust maintained at the

55

early stage of flower induction. Additionally, differentially methylated

56

regions (DMRs), including hypermethylated and hypomethylated DMRs,

57

were also characterized in AB apple trees. Intriguingly, the DMRs were

58

enriched in hormones, redox state, and starch and sucrose metabolism,

59

which affect flowering. Further global gene expression evaluation based

60

on methylome analysis revealed that a negative correlation between gene

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body methylation and gene expression. Subsequent small RNA analyses

62

showed that 24-nucleotide small interfering RNAs were were activated

63

and maintained in non-CG methylated apple trees. Our whole-genome

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DNA methylation analysis, and RNA and small RNA expression profile

65

construction provide valuable information future studies.

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KEYWORDS: Malus domestica, alternate bearing, flower induction,



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methylomes, expression profile

68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88


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INTRODUCTION

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DNA methylation, which is a form of epigenetic modification, occurs

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when a methyl group connects to the 5′ carbon of cytosine under the

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function of DNA methyltransferase (DNMT). In plants, the DNA

93

methylation levels in heterochromatin regions such as centromeres and

94

centrosomes are very high, whereas the levels in the promoter region are

95

a bit lower. DNA methylation usually occurs in symmetrical sequences,

96

such as CG and CHG (where H=A, T, or C), and the majority of GC

97

sequences in the genome are methylated. However, asymmetrical

98

sequences such as CHH are also sometimes methylated.1

99 100

In higher plants, there are three main kinds of DNA transferases:

101

methyltransferase 1 (MET1), domains rearranged methyltransferase

102

(DRM), and chromomethylase (CMT).2 MET1 mainly functions in GC

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sequences, whereas CMT3 mainly functions in CHG sequences.3-5

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However, DNA methylation maintenance in CHH sequences is usually

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controlled by DRM2.6-7 Moreover, for some sites in CHH sequences,

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DNA methylation maintenance is dominated by CMT3 and DRM2.8 In

107

higher plants, the two most common DNA methylation modification

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mechanisms include DNA methylation, which is primarily controlled by

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MET1 and CMT, and de novo DNA methylation, which is mainly

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controlled by RNA-directed DNA methylation (RdDM). RdDM is more



111

complex, and includes canonical RdDM and non-canonical RdDM

112

pathways in plants.9 and requires additional key factors, such as RNA

113

polymerase V (Pol V), Pol II, Argonaute 4 (AGO4), AGO2, Defective in

114

RNA-directed and methylation 1 (DRD1), and RDM1.9-11 The third DNA

115

methylation modification mechanism in higher plants is demethylation.

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DNA glycosylase is involved in this process, and demeter (DME),

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demeter-like 2/3 (DML2/3), and repressor of silencing (ROS) are the only

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glycosylases that have been discovered that could function in

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demethylation.12-14

120 121

DNA methylation levels vary by plant species, age, and tissues.

122

Analyzing DNA methylation in the Arabidopsis genome revealed that the

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percentage of DNA methylation was 24% in GC sequences compared

124

with 6.7% in CHG sequences and 1.7% in CHH sequences.15 Additionally,

125

DNA methylation patterns differ among organs.16-18 DNA methylation

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plays important roles in plants, including maintenance of genome stability,

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resisting biotic or biotic stress, reproductive process, genomic imprinting,

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embryo formation, fruit development, and flower development.19-23 It was

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also involved in fruit ripening.24 For example, DNA methylation in Zea

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mays was significantly reduced after cold treatment.25 DNA methylation

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was also found to be important in heavy metal ion resistance. Other

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studies revealed that decline in DNA methylation could help plants


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defend against bacterial infection.26 Moreover, DNA methylation could

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regulate flowering in plants. Studies have also shown that DNA

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methylation could change the expression of FLC, which controls floral

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induction, and therefore regulates flowering in Arabidopsis.27-28 Another

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study identified 71 histone methyltransferases and 44 histone

138

demethylases in the apple genome that showed different expression

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patterns in response to flower induction; however, the influence of

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methylation levels are still unknown.29 Overall, DNA methylation plays

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important roles in plant growth and development. However, the limited

142

research has only focused on some model plants or resistant researches in

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annual plants. DNA methylation in regulating other processes, such as

144

flower induction in apple or other fruit trees, is still unknown.

145 146

Flower induction is a complex process that is controlled by many factors.

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Six pathways have been identified in the Arabidopsis model, including

148

autonomous,

149

vernalization pathways.30 Meanwhile, a series of genes were involved in

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the epigenetic regulation. For example, the H3K27m3 levels of MADS

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Affecting Flowering 4/5 (MAF4/5) can be affected by RING1A.31 The

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Early Flowering MYB protein and JMJ30 (H3K36me2 demethylase) can

153

also affect H3K36me2 at FT to influence flowering.32 Apples, which are

154

delicious table fruits, are popular all over the world. Apple flowering

photoperiod,

gibberellins,

age,


thermosensory,

and


155

includes floral induction, floral initiation, floral differentiation, and

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anthesis. Among all the stage, flower induction was the most important.

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At this stage, exogenous hormones and flowering genes were active to

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determine bud fate. Flower induction lasted for 40 to 60 days depended

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on environmental differences and varieties. ‘Fuji’ is a main cultivated

160

variety and represents 79% of planted apples in China. However, ‘Fuji’

161

apples have difficult flowering and undergo alternate bearing (AB). ‘Fuji’

162

flower induction was from 30 days after full blossom (DAFB) to 70

163

DAFB, and characterized as early stage, middle stage and last stage.

164 165

AB means that, in a given year, a crop produced more fruit (ON year)

166

than in the second year, when the crop produced less or no fruit (OFF

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year).33-34 AB often occurs in woody plants, such as apple, citrus, and

168

olive trees.33-35 And many factors regulate AB. One point believed that

169

AB is controlled by the level of phytohormones, such as gibberellins and

170

cytokinins. However, uneven distribution of nutrition in fruit trees can

171

also lead to AB. In an ON year, the bud gets less nutrition, which inhibits

172

flowering. In an OFF year, the bud gets more nutrition, which is

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beneficial to flower formation. Although AB and flower induction have

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been investigated for several decades,34-37 there are stills many unknown.

175 176

Recently, increasing evidence has shown that DNA methylation plays


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important roles in regulating plant growth and development. Moreover,

178

with the development of high-throughput sequencing, the transcriptome,

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miRNAs, and proteome have been used to elucidate the potential AB and

180

flower induction mechanisms in apple, citrus, and other economically

181

important fruit trees.38-39 However, little is known about whether

182

epigenome variants are responsible for flower induction and AB in trees.

183

It is also considerable that how DNA methylation was occurred in the

184

main cultivated ‘Fuji’ apple trees compared with other model annual

185

plants.

186 187

Herein, we analyzed the cytosine DNA methylation patterns of buds from

188

ON and OFF trees at different flower induction stages, including the early

189

stage (ES), middle stage (MS), and late stage (LS). Additional mRNA and

190

miRNA expression profiles were also used. Our single-base methylome

191

analysis will provide valuable information regarding methylation

192

differences in response to flower induction in AB trees. This

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comprehensive investigation of DNA methylation, and gene and miRNA

194

expression will reveal novel insight into and enrich biological theories of

195

flower induction in apple and other fruit trees.

196 197

MATERIALS AND METHODS

198

Plant Material and Sample Collection



199

A total of 30 7-year-old Fuji/M9 trees were used, and they were planted at

200

the base of Baoji Haisheng Modern Agriculture Co., Ltd (Nanzhai Town,

201

Qianyang County, Shaanxi, 34°39′N, 107°10′E) in 2017. 15 of the trees

202

were characterized by more flowers and fruits, and were considered ON

203

trees; the other 15 were characterized by fewer flowers and fruits, and

204

were considered OFF trees, as previously described.34 Terminal buds

205

from ON and OFF trees were collected at the ES, MS, and LS on 30 days

206

after full blossom (DAFB), 50 DAFB, and 70 DAFB on clear mornings

207

from local phenological period.29, 39-40 Buds from different stages were

208

characterized as ON1 and OFF1, ON2 and OFF2, and ON3 and OFF3;

209

they were brought into the lab with liquid nitrogen and stored at −80°C

210

for further use.

211 212

Genomic DNA Extraction and Bisulfite Library Construction

213

Genomic DNA was extracted with the Plant Total DNA Isolation Kit Plus

214

(FOREGENE, Chengdu, China) according to the manufacturer’s

215

instructions. Genomic DNA was then checked by a NanoPhotometer®

216

spectrophotometer (IMPLEN, CA, USA) for purity and a Qubit® 2.0

217

Fluorometer (Life Technologies, CA, USA) for library construction.

218 219

After checking, a total of 5.2 μg genomic DNA and 26 ng lambda DNA

220

were interrupted into 200–300-bp fragments by sonication according to


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end repair and adenylation. Cytosine-methylated barcodes were bound to

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the DNA fragments and then treated with bisulfite twice with the EZ

223

DNA Methylation-Gold™ Kit (Zymo Research, CA, USA). After

224

treatment, unmethylated cytosine changed to uracil, whereas methylated

225

cytosine remained. PCR was then conducted. Finally, the library

226

concentration was assayed by a Qubit® 2.0 Fluorometer (Life

227

Technologies, CA, USA), and the insert size was analyzed by the Agilent

228

Bioanalyzer 2100 system. They were all performed by Novogene (Beijing,

229

China).

230 231

BS-Seq Data Processing and Genome Mapping Analysis

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The quality-checked libraries were then sequenced on an Illumina HiSeq

233

2500 system (Novogene, Beijing, China). They were sequenced by

234

synthesis, with four kinds of dNTPs, DNA polymerase, and splice

235

primers added. Image acquisition and base calling were conducted by

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fluorescence signal and using the Illumina CASAVA pipeline. All raw

237

reads were analyzed with FastQC v0.11.5 and then trimmed with

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Trimmomatic v0.36 to remove the low-quality reads. After trimming all

239

the filtering steps, the clean data were checked with FastQC and then

240

used for genome mapping.

241 242

The recently published apple genome (GDDH13 v1.1), which was



243

downloaded from https://iris.angers.inra.fr/gddh13/, was used as a

244

reference genome to process the clean data with Bismark v0.12.5.41-42

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Both sequence results and the reference genome were converted with C to

246

T, G to A in a directional manner. After the bisulfide-converted apple

247

genome was prepared, it was indexed with bowtie2.43 Reads that were

248

produced from a unique best alignment were then compared with the

249

normal genomic sequence. The methylated sites of all cytosine positions

250

will be defined and inferred.

251 252

Assessment of Methylation Levels and Differentially Methylated

253

Regions and TEs

254

Methylation level (ML) was defined as fraction of methylated Cs and

255

calculated by ML(C)=reads (mC)/ (reads (mC)+reads(C)). Additionally,

256

the corrected ML was then calculated as ML=(ML−r)/(1−r), of which r

257

was defined as the bisulfite non-conversion rate, as described in a

258

previous study.44 The DMRs were analyzed with DSS. The gene body

259

(from TSS to TES) and promoter regions (2-kb up-stream of the TSS or

260

down-stream of TES) had overlapping DMRs. At least three methylated

261

cytosine sites were considered with threshold=1e-05, remove bases with

262

more than 99.9 percentile coverage to minimize errors. Those putative

263

DMRs in gene body or flanking regions were prepared for further use.

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RepeatMasker (http://www.repeatmasker.org/) was used to screen and


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annotate all TEs in the apple genome. TEs, including LTRs, LINEs, and

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Helitrons, were obtained.

267 268

Whole-genome and Small Library Preparation and Sequencing

269

Total RNA was extracted with the Total RNA Isolation Kit Plus

270

(FOREGENE, Chengdu, China) of sample the same as methylation

271

sequencing. After checking, a total of 3 μg RNA was used. Ribosomal

272

RNA was removed with an Epicentre Ribo-zero™ rRNA Remove Kit

273

(Epicentre, WI, USA). Ethanol precipitation was used to clean up the

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rRNA free residue. Sequencing libraries were generated using the

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rRNA-depleted RNA with the NEBNext® Ultra™ Directional RNA

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Library Prep Kit for Illumina® (NEB, MA, USA) following the

277

manufacturer’s recommendations, with three biological replicates.

278

Additional products were purified (AMPure XP system), and library

279

quality was assessed on the Agilent Bioanalyzer 2100 system. Clustering

280

of the index-coded samples was performed on a cBot Cluster Generation

281

System (TruSeq PE Cluster Kit v3-cBot-HS, Illumina, CA, USA)

282

according to the manufacturer’s instructions. Finally, the libraries were

283

sequenced on an Illumina HiSeq 4000 platform with 150-bp paired-end

284

reads.

285 286

The same samples were used for small RNA library construction and



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sequencing with three biological replicates. The small RNA library was

288

prepared as described in a previous study.39

289 290

Quantification Analysis of Gene and miRNA Expression Profiles

291

First, all raw data were processed through in-house Perl script and

292

trimmed with low reads, such as containing adapter, poly-N. Further

293

clean data were checked for Q20 and Q30 for quality assessment.

294

Additionally, the available genome was downloaded and built with

295

bowtie2 v2.2.8, and paired-end clean reads were aligned with HISAT2

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v2.0.4.43 The mapped reads were further analyzed by String Tie v1.3.1.

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For coding gene expression, FPKM was used to assess their expressions

298

with Cuffdiff v2.1.1.45 miRNA expression was evaluated by TMT

299

(transcript per million). For DEGs and miRNAs, p-adjustON2 and ON1>ON3 in

403

the ON trees (Figure 4j and 4l), and OFF1>OFF2 and OFF1>OFF3 in the

404

OFF trees (Figure 4m and 4o).

405 406

These distinct methylation patterns among the three different stages

407

revealed that flower induction was heavily controlled at the ES, which

408

showed the highest CG and CHG methylation; this could contribute to

409

why ‘Fuji’ apple trees have more difficulty flowering than any other

410

cultivated varieties. Moreover, compared with the methylation levels in

411

ON and OFF trees, the CG, CHG, and CHH was not quite remarkable in

412

the ES (Figure 4g), but they showed differences in the MS and LS, and

413

were characterized by ON2>OFF2 and ON3>OFF3 for all genomic

414

regions except repeat regions (Figure 4h–i).

415 416

DNA Methylation Distributions among Different TEs in AB Apple

417

Trees

418

The CG, CHG, and CHH methylation levels of genes and transposons



419

greatly differed in ON and OFF trees at different development stages

420

(Figure 5a–c). TEs in each context were all hypermethylated compared

421

with genes at all stages. Additionally, TE methylation increased across

422

development stages, and the TE methylation levels were characterized as

423

ON3>ON2>ON1 and OFF3>OFF2>OFF1 for all contexts (Figure 5a–c).

424 425

We also analyzed the differential methylation patterns of gene bodies and

426

their 2-kb up- and down-stream regions between ON and OFF trees at

427

different stages (Figure 5d). In general, the methylation levels of CG,

428

CHG, and CHH were extremely low at the transcriptional start site (TSS)

429

and transcriptional end site (TES), and the CG, CHG, and CHH

430

methylation levels were also higher in the flanking regions than in the

431

gene bodies (Figure 5d). We then compared CG, CHG, and CHH

432

methylation levels in detail for both ON and OFF trees, and different

433

stages (Figure S4). Firstly, when compared between ON and OFF trees

434

(Figure S4a–c), similar to genomic distribution, small methylation

435

differences were found in the gene bodies and flanking regions of ON1

436

and ON2 (Figure S4a); however, there were greater changes in the MS

437

and LS (Figure S4b–c). ON trees always showed a preferential in terms

438

of CG, CHG, and CHH, which indicated that methylation levels in ON

439

trees were heavily maintained in the gene body, 2-kb up- and

440

down-stream regions (Figure S4b–c).


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We then compared methylation levels during flower induction stages

443

among ES, MS and LS. They all showed reduced CG and CHG

444

methylation along the time points, which was characterized as ON1>ON2

445

and ON1>ON3 in ON trees (Figure S4d and f), and OFF1>OFF2 and

446

OFF1>OFF3 in OFF trees (Figure S4g and i). These results indicated that

447

the methylation levels of buds in the ES were highest in the gene body

448

and their 2-kb up- and down-stream regions. However, the CHH content

449

was not similar and showed a fluctuant trend at different time points.

450 451

Moreover, we analyzed the methylation levels in different transposon

452

families, including LTR, LINE, and Helitron (Figure 5e–g). Generally,

453

these different TE families all showed similar patterns: there were higher

454

methylation levels in the gene body regions than the flanking regions in

455

the CG, CHG, and CHH contexts. However, their methylation trends

456

differed in the gene body and their 2-kb up- and down-stream regions. We

457

noticed that there were few methylcytosine differences between LTRs and

458

LINEs in the gene bodies, but there were more differences in the flanking

459

regions (Figure 5e–f). Obvious differences were noticed among samples

460

in Helitron methylation among the genomic regions including the gene

461

body and its flanking regions (Figure 5g).

462



463

Overall, our genomic methylation analysis revealed that AB trees had a

464

distinct preference and characterization in the gene bodies and other

465

genomic regions. CG and CHG methylation was consistently higher in

466

ON compared with OFF trees at all the three time points. Moreover, buds

467

in the ES had the highest methylation levels compared with those in the

468

MS and LS.

469 470

Identification, Distribution, and Functional Annotations of DMRs in

471

the Apple Genome

472

We analyzed differentially methylated regions (DMRs) in the three

473

contexts (CG, CHG, and CHH) between ON and OFF trees (Figure 6),

474

and different time points in ON (Figure S5) and OFF trees (Figure S6).

475

The results showed that these DMRs were heavily enriched within the

476

apple genome, including gene, promoter, and other regions, for AB apple

477

trees of different development stages (Figure 6a–c). A total of 1125 and

478

2407 DMRs were identified in both gene and promoter regions between

479

ON1 and OFF1 (Figure 6d, Table S3), 1450 and 2515 DMRs were found

480

in gene and promoter regions between ON2 and OFF2 (Figure 6e), and

481

1290 and 2404 between ON3 and OFF3 (Figure 6f). We then used violin

482

and heatmap to visualize the distribution of methylation levels of

483

different contexts (Figure 6g–j). These DMRs were enriched in GC and

484

CHH contexts, whereas CHH showed fewer differences between ON1


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485

and OFF2 (Figure 6h and j). These trends were consistent for ON2 and

486

OFF2, and ON3 and OFF3 (Figure 6g–j). These findings revealed that

487

DMRs were heavily maintained in CG and CHG contexts, whereas CHH

488

showed a reduced mechanism in response to AB.

489 490

We also analyzed the hyper and hypo DMRs of the three contexts in

491

anchoring areas, including promoter, TSS, 5′UTR, exon, intron, 3′UTR,

492

TES, repeat, and other regions, of ON and OFF trees (Figure 6k–m). The

493

DMRs were mainly enriched in repeat, promoter, exon, and intron regions

494

between ON and OFF trees. Moreover, the number of DMRs in CG, CHG,

495

and CHH contexts also greatly differed between ON1 and OFF1 (Figure

496

6k), ON2 and OFF2 (Figure 6l), and ON3 and OFF3 (Figure 6m). As

497

shown in Table S3, various kinds of genes showed promoter, 5′UTR,

498

3′UTR, or exon differences. We listed some key genes, including

499

transcription

500

MD07G1073200, and MD01G1095100), MYB (e.g., MD04G1008300,

501

MD04G1008300, and MD04G1008300), and TCP (e.g., MD02G1196100,

502

MD13G1047200, and MD14G1213400); flowering-related genes, such as

503

MADS-box

504

MD10G1264500),

505

(MD14G1154900),

506

(MD14G1156400); and hormone-related genes, such as gibberellin-

factors

(e.g.,

such

as

NAC

MD01G1038600, CONSTANS-LIKE and

B-box

(e.g.,

MD07G1073200,

MD14G1066200,

and

(MD16G1148500),

SPL

(MD15G1248300),


NFY


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507

(MD15G1116300, MD10G1314500, and MD06G1073300), auxin- (e.g.,

508

MD13G1222200, MD03G1116000, and MD07G1156400), jasmonic

509

acid- (MD16G1127400 and MD15G1023600), histone modification-

510

(MD03G1137100,

511

sugar-related

512

MD11G1293300).

MD02G1057400,

genes

and

(MD15G1193400,

MD03G1058300),

and

MD15G1433200,

and

513 514

GO and KEGG analyses were also performed to describe the potential

515

biological processes associated with these DMRs between ON and OFF

516

trees. GO results showed that DMRs of different methylation contexts

517

between ON1 and OFF1, ON2 and OFF2, and ON3 and OFF3 were

518

mainly classified into three major categories, including biological process,

519

cellular component, and molecular function (Figure S7a–c). GO revealed

520

that these DMRs participate in various developmental processes.

521

Additionally, KEGG enrichment analysis was also performed to identify

522

the potential roles of the DMRs in ON and OFF trees (Figure S8). The

523

CG-related DMRs were mainly enriched in RNA degradation,

524

plant–pathogen interactions, flavonoid biosynthesis, and phenylpropanoid

525

biosynthesis (Figure S8a, d, and g); CHG-related DMRs were mainly

526

enriched in secondary metabolites, protein process, and endocytosis

527

(Figure S8b, e, and h); and CHH-related DMRs were also mainly

528

enriched in secondary metabolites (Figure S8c, f, and i). Additionally,


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529

other biological processes including nitrogen metabolism, brassinosteroid

530

biosynthesis, plant circadian rhythm, and starch and sucrose metabolism

531

were also partially enriched.

532 533

The DMR distributions were then analyzed at different development

534

stages. DMRs and between different time points were first characterized

535

for ON2 and ON1, ON3 and ON1, and ON3 and ON2 (Figure S5a–c). A

536

total of 1081 and 3132 DMRs between ON2 and ON1 (Figure S5d), 1181

537

and 2430 DMRs between ON3 and ON2 (Figure S5e), and 1137 and 3779

538

DMRs between ON3 and ON1 were identified between gene and

539

promoter regions, respectively (Figure S5f). The results also showed

540

diverse methylation levels in CG, CHG, and CHH contexts (Figure

541

S5g–j). Further analysis revealed that the hyper and hypo DMRs were

542

highly maintained in promoter, exon, intron, and repeat regions, and CHH

543

methylation was higher than CG and CHG methylation (Figure S5k–m).

544 545

We also analyzed the DMRs in the OFF trees similar to how development

546

stages were analyzed in the ON trees. These results also showed diverse

547

methylation characterization and distribution in OFF trees (Figure S6a). A

548

total of 1500 and 2956, 1399 and 2805, and 1303 and 3278 DMRs in

549

gene and promoter regions, respectively, were surfaced between OFF2

550

and OFF1, OFF3 and OFF2, and OFF3 and OFF1 (Figure S6d–f).



551 552

Violin and heat map plots were then employed to show the different

553

distributions of CG, CHG, and CHH contexts in OFF trees (Figure S6g–j).

554

The hyper and hypo DMRs in OFF trees were also mainly enriched in

555

promoter, exon, intron, and repeat regions (Figure S6k–m). DMR

556

distributions were similar for ON and OFF trees (Figure S5k–m), which

557

indicated that DMRs showed similar characterizations across apple

558

development for both ON and OFF trees.

559 560

To elucidate the potential biological processes of the DMRs, KEGG

561

enrichment was then employed for DMRs along different development

562

stages (Figure S9-S10). Results showed that CG, CHG, and CHH DMRs

563

participated in different biological processes, including phenylpropanoid

564

biosynthesis, flavonoid biosynthesis, and secondary metabolites. Other

565

pathways including starch and sucrose metabolism, zeatin biosynthesis,

566

peroxisome, nitrogen metabolism et al. processes.

567 568

Association Analysis of Gene Expression and DNA Methylation

569

To understand the effect of DNA methylation on gene expression in apple

570

flower development, we further performed an association analysis of

571

mRNA levels along with associated CG, CHG, and CHH methylation

572

contexts. Global gene expression profiles were employed based on the


Page 26 of 73

Page 27 of 73


573

same samples from methylation sequencing from ON tree and OFF tree.

574

Gene expression profiles were classified into four categories based on

575

Fragments Per Kilobase of transcript per Million mapped reads (FPKM)

576

value as previous study.17 No expression was determined for FPKM < 1.

577

For genes whose FPKM values were more than 1, they were further

578

divided into low expression (1≤FPKMLS (Figure S12f and i). This

624

finding indicated that the methylation levels of those DEGs in AB were

625

highly maintained in ON trees at the MS and LS. DEGs were most highly

626

methylated in the ES rather than the MS and LS during apple flower

627

induction. A previous study showed that higher methylation in the

628

promoter inhibited gene expression, whereas lower promoter methylation

629

levels could promote gene expression. We selected five candidate genes

630

including TIFY, SPL, MYB, and NAC between ON1 and OFF1. Results

631

showed that the DMRs with lower methylation levels in the promoter

632

were more highly expressed (Figure 8b).

633 634

Association Analysis of Small RNA Expression and DNA Methylation

635

It was previously reported that small RNAs also play important roles in

636

DNA methylation and is involved in RdDM. Therefore, we performed

637

small RNA sequencing of 18 of the samples from ON and OFF trees at

638

the ES, MS, and LS, with three biological replicates.



639 640

After filtration and further analysis, 24-nt small RNAs were the most

641

abundant small RNAs (Figure S13). To investigate which kinds of small

642

RNAs contributed to DNA methylation, we analyzed the effect of those

643

different 21–24-nt siRNA bases (A, T, C, and G) on the methylation

644

levels of cytosine in their sense strand (mC) and antisense strand (mC*).

645

Actually, the abundance of guanine was quietly associated with its

646

antisense strand small RNA sequences, whereas the abundance of

647

cytosine was associated with its sense strand. Consequently, we analyzed

648

all their corrections of C and mC, and G and mC* in ON and OFF trees

649

during flower induction. As shown in Figure 9a–d, 24-nt small RNAs in

650

ON1 buds showed the highest abundance of mC and mC* relative to C

651

and G, respectively. These results indicated that the 24-nt small RNAs

652

were strongly associated with DNA methylation in apple buds.

653 654

Because of the important role of 24-nt siRNAs, additional research

655

mainly focused on these siRNAs. We firstly investigated the methylation

656

levels of 24-nt siRNAs in CG, CHG, and CHH between mapped and

657

unmapped regions. First, the CHH methylation levels were significantly

658

lower in the mapped than unmapped regions in both ON and OFF trees,

659

whereas CG and CHG methylation levels were not consistent (Figure

660

9a–f). CG and CHH methylation levels were higher in the mapped than


Page 30 of 73

Page 31 of 73


661

unmapped regions in the ES (ON1 and OFF2), but they gradually reduced

662

in the MS and LS (ON2 and ON3, respectively) (Figure 9f and g), or

663

showed a performance in unmapped regions in the MS or LS (OFF2 and

664

OFF3) (Figure 9i and g).

665 666

We also analyzed 24-nt siRNA methylation abundance in the gene body

667

and associated 2-kb up- and down-stream flanking regions. Results

668

showed that the 24-nt siRNA methylation levels were highly maintained

669

in the flanking regions than gene body (Figure 9k). Moreover, 24-nt

670

siRNAs were less methylated in ON trees compared with OFF trees

671

(Figure 9k). Similar to the distributions in the gene regions, the 24-nt

672

siRNAs were also more methylated in the flanking regions than in the TE

673

regions; however, the 24-nt siRNA methylation levels were significantly

674

higher in the TE regions compared with the gene regions (Figure 9l). We

675

also found that the 24-nt siRNA methylation levels were highly enriched

676

in the CG and CHG regions (Figure S14).

677 678

We also investigated 24-nt siRNA abundance relative to CHH

679

methylation. The results showed that, in the hyper regions, 24-nt siRNA

680

abundance was reduced; in the hypo regions, the 24-nt siRNA abundance

681

was heavily enriched compared with ON and OFF trees (Figure 9m–o).

682



683

DISCUSSION

684

With the development of high-throughput sequencing, whole-genome

685

bisulfate sequencing (WGBS) has become an important method for

686

uncovering novel regulatory mechanisms of various biological processes,

687

including seed development,17,

688

development,49 fruit ripening, 50 abiotic stress,51 disease defense,52 and

689

other processes in various plants. However, little is known about its

690

potential involvement in regulating flower induction.

47

root development,48 floral organ

691 692

Flower induction is a critical stage in apple that integrates various

693

endogenous signals to control bud fate.39,

694

phenomenon in perennial fruit trees and some other plants that results

695

from incongruent flower induction and is not observed in the model

696

Arabidopsis. AB can always induce huge economic losses for people.

697

Research on AB has been conducted on apple, avocado, mango, pistachio,

698

citrus and other fruit trees.33-34,36,38,54 But there were still remained and

699

less epigenetic researches were performed.

53

Moreover, AB is also a

700 701

Herein, we first performed single-base WGBS and described mRNA and

702

small RNA expression profiles of buds from ON and OFF trees in

703

cultivated ‘Fuji’ trees at three key flower induction stages. We aimed to

704

draw the apple methylome landscape to understand the different


Page 32 of 73

Page 33 of 73


705

methylation changes between ON and OFF trees at different flower

706

induction stages, and the different methylation changes associated with

707

mRNAs and small RNAs. Our methylome map provides valuable

708

epigenetic information regarding apple flower induction.

709 710

Apple Methylation Variants

711

A recent study revealed that there were 71 histone methyltransferases, 44

712

histone demethylases, 57 histone acetylases, and 26 histone deacetylases

713

identified in apple, which showed different expression profiles in

714

response to flower induction.29 Those findings indicated that flower

715

induction is potentially related to DNA methylation. In general, apple

716

showed higher CHH proportions of the total mC among the three contexts

717

(CG, CHG and CHH), which was similar to the findings for other woody

718

trees, such as ash, popular, and birch,52, 55-56 but different from results on

719

annual plants such as Arabidopsis and rice, which showed higher CG

720

proportions (Figure 3).51. It was also reported that CG methylation was

721

highly enriched in angiosperms.57-60

722 723

In this study, the apple methylome showed nearly 57.7%–61.2% CG

724

methylation, 40.3%–43.3% CHG methylation, and 6.9%–11.5% CHH

725

methylation; this methylation distribution was consistent with that of

726

most plants. A previous study revealed that leaves of the ‘Qinguan’ and



Page 34 of 73

727

‘Honeycrisp’ apple varieties showed nearly 53.6%, 37.7%, and 8.5% CG,

728

CHG, and CHH methylation, respectively.51 Here, we found that the ‘Fuji’

729

methylation levels were slightly different. Previous study has revealed

730

that

731

polymorphisms

732

insertion/deletions (INDELs) have been identified between ‘Qinguan’ and

733

‘Fuji’ genome, and they showed different phenotypic traits. Their

734

different genomic features and variations were contributed to explain the

735

different methylation levels between these different varieties.57, 61

lots

of

genomic (SNPs),

variations structural

including

single

variations

nucleotide

(SVs),

and

736 737

We also investigated the genome DNA methylation features of ON and

738

OFF trees across flower stages (Figure 2). Interestingly, change in total

739

methylated cytosine (CG, CHG, and CHH) frequencies between ON and

740

OFF trees differed over time. For example, ON trees showed lower

741

methylated cytosine levels than OFF trees in the ES, but they were then

742

decreased and showed higher levels in the MS and LS (Figure 2a–c); this

743

indicated that methylation has complex involvement in AB at different

744

development stages. Other genomic methylation features showed that all

745

CG, CHG, and CHH methylation mainly occurred in TE-enriched regions,

746

whereas enriched gene regions always showed reduced TE density and

747

methylation levels (Figure 2d–f). Additionally, these genomic features

748

were consistent with the findings of previous studies.59-60 We also noticed


Page 35 of 73


749

that that the majority of CG and CHG were highly methylated, which was

750

similar to previous findings on castor bean and cassava (Figure 3k–p),62

751

but slightly different from results on Arabidopsis.63 Moreover, their

752

methylation were also widely distributed in different genomic regions,

753

including promoter, 5′UTR, exon, intron, 3′UTR, and repeat regions

754

(Figure 4); this finding is consistent with that on other plant species.52

755

Overall, these results indicated that methylation features were partially

756

conserved; however, apple genomic methylation still showed some

757

distinct characterizations.

758 759

The CG, CHG, and CHH methylation patterns in gene and TE regions

760

showed distinct features in apple trees (Figure 5a–c) Additionally, the

761

three contexts in TEs were highly methylated compared with those in

762

gene regions, which is similar to previous findings in the model plants

763

Arabidopsis,21 and rice.60

764 765

Genomic Methylation Features in AB Apple Trees

766

DNA methylation is dynamic, and differs across tissues and time

767

points.44,64 Here, we found that DNA methylation patterns differed

768

between ON and OFF trees, and different development stages. We further

769

analyzed the genomic DNA features of AB apple trees in detail. We found

770

that methylation levels differed between the gene body and 2-kb up- and



771

down-stream regions (Figure S4). For example, these regions were all

772

more highly methylated in ON and OFF trees at the ES than the MS or

773

LS, which indicates that methylation levels were strongly maintained at

774

the beginning of flower induction; genes in this stage were also less

775

expressed, which could help explain why flowering in ‘Fuji’ apple trees

776

compared with other varieties.36,39 Similar as their genomic features in the

777

promoter, 5′UTR, 3′UTR, intron, and repeat regions, their further

778

methylation levels in gene body and its up or down stream regions were

779

similar. They showed higher methylation levels in ON trees in CG and

780

CHH contexts (Figure 5d, S4).

781 782

We also analyzed the methylation patterns in different TE families,

783

including LTR, LINE, and Helitron, in the AB apple trees (Figure 5e–g).

784

Generally, these three TE methylation patterns exhibited similar trends in

785

apple, which showed higher levels in gene body regions than flanking

786

regions; these findings are consistent with those of previous studies on

787

soybean.48 Additionally, the different TE methylation levels between ON

788

and OFF trees indicated that they were also response to flower induction

789

in AB trees.

790 791

After analyzing the different DNA methylation distribution patterns, we

792

then focused on the DMRs between ON and OFF trees, and differences


Page 36 of 73

Page 37 of 73


793

across flower induction stages. DMRs between ON and OFF trees, and

794

different stages in ON and OFF trees were widely distributed among

795

different chromosome regions (Figure 6, S5–6). To further characterize

796

the potential biological processes of the DMRs, GO and KEGG

797

enrichment analysis were performed. The results showed that the DMRs

798

were involved in various processes, including hormone processes,

799

nitrogen metabolism, starch and sucrose metabolism, and peroxisome

800

(Figure S8). Previous studies revealed that sugar, hormone, and redox

801

state played important roles in regulating AB or flower induction.36-37 In

802

Citrus, primary metabolism and oxidoreductase activity differ between

803

ON and OFF crops, and they are critical for floral induction.37 Here, we

804

found that most DMRs were also enriched in primary metabolism, which

805

indicated that they have important roles in regulating AB.

806 807

Dynamic DNA methylation Patterns and Gene Expression in

808

Response to AB

809

Our detailed comparisons between ON and OFF trees revealed numerous

810

interesting DMRs that participate in flowering processes and showed

811

different methylation levels between ON1 and OFF1 (Figure 6, Table S3).

812

Previous studies showed that sugar and hormones participate in apple

813

flower induction.39-40 Interestingly, we found several DMRs that were

814

annotated as sugar transport-, gibberellin-, auxin-, and jasmonic-related



Page 38 of 73

815

proteins, and all showed different methylation levels (Table S3); this

816

indicated that these DMRs were also responsible for flower induction. We

817

also found that some epigenetic genes, such as histone-lysine

818

N-methyltransferase

819

(MD02G1057400) also showed CHH and CG methylation differences in

820

their promoter regions, and the AGO protein (MD03G1137100) showed

821

CHH methylation differences between ON and OFF trees. These different

822

methylation levels were shown to be associated with mRNA expression

823

profiles in a previous study.39

(MD04G1052400)

and

methyltransferase

824 825

DNA methylation was always associated with gene expression, neither

826

marginally or totally.65 To further analyze the relationship between DNA

827

methylation and gene expression in apple, we used genomic RNA-seq

828

data of samples from AB trees. Genes that were not expressed showed

829

higher methylation levels in both ON and OFF trees (Figure 7a–f). Some

830

differences were also found in the gene body regions, although most

831

moderately expressed genes showed higher methylation levels in CG

832

context (Figure 7a–f). These results showed that one of the functions of

833

DNA methylation was to inhibit gene expression.

834 835

We also characterized the effect of DMRs on gene expression in ON and

836

OFF trees. For example, less significant gene expression differences were


Page 39 of 73


837

found regardless of if the DMRs occurred in 5′ or 3′ regions in CG, CHG,

838

or CHH contexts (Figure 7g–i); this indicates that DMRs were weakly

839

associated with gene expression, which is similar to previous findings on

840

castor bean.17

841 842

We then focused on the significant DEGs and their 2-kb up- and

843

down-stream regions. Overall, ON trees showed a higher methylation

844

levels, especially in the ES and MS, except for CHH methylation in the

845

ES (Figure S12b–c). Furthermore, we also compared methylation levels

846

at different development stages; the results showed that genes in the ES

847

were highly methylated in both ON and OFF trees (Figure S12d–i). These

848

results indicated that genes were heavily methylated in ON trees during

849

the ES, which could partially explain why flowering is difficult for ‘Fuji’

850

apple trees.

851 852

Small RNAs were reported to be involved in de novo DNA methylation,

853

which is controlled by RdDM.6-7 Here, we first investigated the

854

relationship between small RNA and DNA methylation. The results

855

showed that 24-nt siRNAs showed the most abundant distributions

856

(Figure S13), which was similar to the findings of a previous study.39

857

Interestingly, we found that the 24-nt siRNAs showed great percentage in

858

the mapped than unmapped regions (Figure 9e–j). The reduced non-CG



859

percentage in the 24-nt siRNA mapping regions in ON trees was highly

860

associated with the RdDM pathway. These findings indicated that the

861

RdDM pathway was activated in apple. Moreover, the distribution of

862

24-nt siRNAs was similar in gene regions and TE regions (Figure 8k–l),

863

and similar to the 24-nt siRNA distributions observed in castor.17 We

864

found that the 24-nt siRNAs were highly associated with the distribution

865

and patterns of non-CG methylation. Further analysis showed that some

866

key genes that were related to the RdDM pathway also had different

867

expression profiles, which indicated that the RdDM pathway was

868

activated in apple flower induction. Although other factors may also

869

participate in the establishment and maintenance of CHH methylation in

870

apple trees, because of the limited available information on small

871

RNA-mediated methylation in plants, we could not find any other

872

research to support this. Therefore, future research should address this

873

issue.

874 875

Overall, our results showed that DNA methylation played important roles

876

in regulating flower induction and AB. And these findings can enhance

877

future research on apple and other fruit trees. As AB was always a serious

878

problem, the data herein may be a good resource for further survey and

879

research.

880


Page 40 of 73

Page 41 of 73


881

AUTHOR INFORMATION

882

Corresponding Authors

883

* Tel: 86-029- 87082543; E-mail: [email protected]

884

* Tel: 86-029- 87082543; E-mail: [email protected]

885

ORCID

886

Mingyu Han: 0000-0001-5459-9782

887

Na An: 0000-0002-7855-4447

888

Author Contributions

889

S.F. M.H. and N.A. conceived the original screening and research plans;

890

S.F. C.G. Y.Y. X.Z. W.F. and X.G. supervised the experiments; S.F. R.L.

891

D.Z. analyzed the data. S.F. wrote the article. M.H. and N.A. revised the

892

manuscript.

893

Funding

894

This work was supported by National Key Research and Development

895

Program of China (2018YFD1000101), China Apple Research System

896

(CARS-27), National Natural Science Foundation of China (31672101),

897

Shaanxi key research and development plan (2017ZDXM-NY-019), Tang

898

Scholar by Cyrus Tang Foundation and Northwest A&F University,

899

Yangling Science Plan Project (2018NY-08), Yangling Subsidiary Center

900

Project of the National Apple Improvement Center and Collaborative

901

Innovation of the Center for Shaanxi Fruit Industry Development.

902

Notes



903

The authors declare that they have no competing interests.

904

ABBREVIATION USED

905

AB, alternate bearing; ES, early stage; GO, Gene Ontology;

906

KEGG, Kyoto Encyclopedia of Genes and Genomes; LS, late stage;

907

MS, middle stage

908 909 910 911 912 913 914 915 916 917 918 919 920 921 922 923 924


Page 42 of 73

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925

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1189

FIGURE LEGENDS

1190

Figure 1 Overview of alternate bearing (AB) apple trees. (a) Visual

1191

simulation of the AB phenotype. Total average fruit number per tree in

1192

AB apple trees in 2017 (b) and 2018 (c). Total average fruit weight per

1193

tree of AB apple trees in 2017 (d) and 2018 (e).

1194 1195

Figure 2 Genomic DNA methylation features in AB apple trees. (a–c) CG,

1196

CHG, and CHH methylation levels between ON and OFF trees during

1197

flower induction. (d–f) Circos plots of mCG, mCHG, and mCHH

1198

locations, and gene and transposon density in different chromosomes. The

1199

methylation order was ON1, OFF1, ON2, OFF2, ON3, and OFF3 (outer

1200

to inner). Methylation frequencies are shown for each context in ON and

1201

OFF trees for CG (g), CHG (h), and CHH (i).

1202 1203

Figure 3 DNA methylation levels of each context (CG, CHG, and CHH).

1204

mCs relative proportions in ‘Fuji’ ON trees (a), ‘Fuji’ OFF trees (b),

1205

‘Qinguan’ apple trees (c), ‘Honeycrisp’ apple trees (d), tomato (e),

1206

Arabidopsis (f), rice (g), poplar (h), ash (i), and birch (j). (k–p) Average

1207

cytosine methylation levels in TE in ON1 (k), ON2 (l), ON3 (m), OFF1

1208

(n), OFF2 (o), and OFF3 (p).

1209 1210

Figure 4 DNA methylation distributions in different genomic regions of



1211

AB apple trees. Dendrogram clustering analysis of methylation levels are

1212

shown for different samples based on principal component analysis in CG

1213

(a), CHG (b), and CHH (c). Heatmap analysis of methylation patterns in

1214

the apple genome is shown for CG (d), CHG (e), and CHH (f).

1215

Comparative analysis of DNA methylation patterns in different genomic

1216

regions at different development stages in AB apple trees, followed by

1217

comparison between ON and OFF trees (g–i), different development

1218

stages in ON trees (j–l), and different development stages in OFF trees

1219

(m–o).

1220 1221

Figure 5 DNA methylation patterns of genes and TEs in AB apple trees.

1222

DNA methylation patterns are shown for genes and transposons in CG (a),

1223

CHG (b), and CHH (c). (d) DNA methylation patterns in the gene body

1224

and 2-kb up- and down-stream regions of AB apple trees. DNA

1225

methylation patterns are shown for different TE families in AB apple

1226

trees, and are characterized as LTRs (e), LINEs (f), and Helitrons (g).

1227 1228

Figure 6 Analysis of differentially methylated regions (DMRs) in AB

1229

apple trees. Circos plots of hyper and hypo DMRs between ON1 and

1230

OFF1 (a), ON2 and OFF2 (b), ON3 and OFF3 (c). Venn diagrams of

1231

DMR genes and DMR promoter genes between ON and OFF trees in the

1232

ES (d), MS (e), and LS (f). Violin comparisons of DMRs in each context


Page 56 of 73

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1233

between ON and OFF trees in the ES (g), MS (h), and LS (i). (j) Heatmap

1234

clusters of DMRs between different comparisons. Distribution of hyper

1235

and hypo DMRs in each context (CG, CHG, and CHH) in different

1236

genomic regions between ON1 and OFF1 (k), ON2 and OFF2 (l), and

1237

ON3 and OFF3 (m).

1238 1239

Figure 7 Association analyses of DNA methylation and mRNA

1240

expression in AB apple trees. (a–f) Effect of DNA methylation levels and

1241

global

1242

hypomethylation in 5′ and 3′ regions on gene expression in AB apple

1243

trees.

gene

expression

on

AB

apple trees.

(g–i) Effect

of

1244 1245

Figure 8 Relationship between DNA methylation and gene expression. (a)

1246

IGV snapshots of DNA methylation patterns in ON and OFF trees. (b)

1247

DNA methylation levels (the upper) and expression patterns (the under)

1248

of the five candidate genes.

1249 1250

Figure 9 Association analyses of DNA methylation and small mRNA

1251

expression in AB apple trees. (a–d) Nucleotide distributions and

1252

abundance of the 21- to 24-nt sRNAs. mC and mC* represent the sense

1253

and antisense strands, respectively. (e–j) Methylation levels in the 24-nt

1254

mapped and unmapped regions in AB apple tree. (k) Distributions of the



1255

24-nt sRNAs in the gene body and 2-kb up- and down-stream. (l)

1256

Distributions of the 24-nt small RNAs in the TE regions, and 2-kb up-

1257

and down-stream. (m–o) Abundance of the 24-nt small RNAs in the CHH

1258

hypermethylated and hypomethylated regions.

1259 1260 1261 1262 1263 1264 1265 1266 1267 1268 1269 1270 1271 1272 1273 1274 1275 1276


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1277

Supplementary Materials

1278

Figure S1 Total view of AB apple trees. Phenotypes of ON (a) and OFF

1279

trees (b) at full blossom. Magnification of the ON (c) and OFF trees (tree).

1280

Buds from ON (e) and OFF trees (f).

1281 1282

Figure S2 Read distribution and coverage in different chromosomes of

1283

samples. The left Y-axis represents mean sequence depth in each

1284

chromosome associated with the green column in the X-axis. The right

1285

Y-axis represents proportion of covered bases associated with the red line

1286

in the X-axis. ON1 (a), OFF1 (b), ON2 (c), OFF2 (d), ON3 (e), and OFF3

1287

(f).

1288 1289

Figure S3 Proportion of different mC contexts (CG, CHG, and CHH) in

1290

each apple chromosome. ON1 (a), OFF1 (b), ON2 (c), OFF2 (d), ON3 (e),

1291

and OFF3 (f).

1292 1293

Figure S4 Detailed comparisons of the DNA methylation patterns in the

1294

gene body and 2-kb up- and down-stream regions of ON1 and OFF1 (a),

1295

ON2 and OFF2 (b), ON3 and OFF3 (c), ON2 and ON1 (d), ON3 and

1296

ON2 (e), ON3 and ON1 (f), OFF2 and OFF1 (g), OFF3 and OFF2 (h),

1297

and OFF3 and OFF1 (i).

1298



1299

Figure S5 Analysis of differentially methylated regions (DMRs) in ON

1300

trees. Circos plots of hyper and hypo DMRs between ON2 and ON1 (a),

1301

ON3 and ON2 (b), and ON3 and ON1 (c). Venn diagrams of DMR genes

1302

and DMR promoter genes between ON2 and ON1 (d), ON3 and ON2 (e),

1303

and ON3 and ON1 (f). Violin comparisons of DMRs in each context

1304

between ON2 and ON1 (g), ON3 and ON2 (h), and ON3 and ON1 (i). (j)

1305

Heatmap clusters of DMRs between different comparisons. Distribution

1306

of hyper and hypo DMRs in each context (CG, CHG, and CHH) in

1307

different genomic regions between ON2 and ON1 (k), ON3 and ON2 (l),

1308

and ON3 and ON1 (m).

1309 1310

Figure S6 Analysis of differentially methylated regions (DMRs) in OFF

1311

trees. Circos plots of hyper and hypo DMRs between OFF2 and OFF1 (a),

1312

OFF3 and OFF2 (b), and OFF3 and OFF1 (c). Venn diagrams of DMR

1313

genes and DMR promoter genes between OFF2 and OFF1 (d), OFF3 and

1314

OFF2 (e), and OFF3 and OFF1 (f). Violin comparisons of DMRs in each

1315

context between OFF2 and OFF1 (g), OFF3 and OFF2 (h), and OFF3 and

1316

OFF1 (i). (j) Heatmap clusters of DMRs between different comparisons.

1317

Distribution of hyper and hypo DMRs in each context (CG, CHG, and

1318

CHH) in different genomic regions between OFF2 and OFF1 (k), OFF3

1319

and OFF2 (l), and OFF3 and OFF1 (m).

1320


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1321

Figure S7 GO analysis of the CG, CHG, and CHH DMRs between ON

1322

and OFF trees, followed by ON1 and OFF1 (a), ON 2 and OFF2 (b), and

1323

ON3 and OFF3 (c).

1324 1325

Figure S8 KEGG enrichment of the CG, CHG, and CHH DMRs between

1326

ON and OFF trees. KEGG enrichment of DMRs between ON1 and OFF1

1327

in CG (a), CHG (b), and CHH (c) contexts. KEGG enrichment of DMRs

1328

between ON2 and OFF2 in CG (d), CHG (e), and CHH (f) contexts.

1329

KEGG enrichment of DMRs between ON3 and OFF3 in CG (d), CHG (e),

1330

and CHH (f) contexts.

1331 1332

Figure S9 KEGG enrichment of the CG, CHG, and CHH DMRs between

1333

ON trees at different development stages. KEGG enrichment of DMRs

1334

between ON2 and ON1 in CG (a), CHG (b), and CHH (c) contexts.

1335

KEGG enrichment of DMRs between ON3 and ON2 in CG (d), CHG (e),

1336

and CHH (f) contexts. KEGG enrichment of DMRs between ON3 and

1337

ON1 in CG (d), CHG (e), and CHH (f) contexts.

1338 1339

Figure S10 KEGG enrichment of the CG, CHG, and CHH DMRs

1340

between OFF trees at different development stages. KEGG enrichment of

1341

DMRs between OFF2 and OFF1 in CG (a), CHG (b), and CHH (c)

1342

contexts. KEGG enrichment of DMRs between OFF3 and OFF1 in CG



1343

(d), CHG (e), and CHH (f) contexts. KEGG enrichment of DMRs

1344

between OFF3 and OFF2 in CG (d), CHG (e), and CHH (f) contexts.

1345 1346

Figure S11 Effect of hypomethylation in 5′ and 3′ regions on gene

1347

expression between different comparisons. Effect of hypomethylation in 5′

1348

and 3′ regions on gene expression in ON trees at different development

1349

stages between ON2 and ON1 (a), ON3 and ON2 (b), and ON3 and ON1

1350

(c). Effect of hypomethylation in 5′ and 3′ regions on gene expression in

1351

OFF trees at different development stages between OFF2 and OFF1 (d),

1352

OFF3 and OFF2 (e), and OFF3 and OFF1 (f).

1353 1354

Figure S12 Relationships between methylation levels and differentially

1355

expressed genes between different comparisons of ON and OFF trees.

1356

Comparisons between ON and OFF trees: ON1 and OFF1 (a), ON2 and

1357

OFF2 (b), and ON3 and OFF3 (c). Comparisons between ON trees at

1358

different development stages: ON1 and ON2 (d), ON2 and ON3 (e), and

1359

ON1 and ON3 (f). Comparisons between OFF trees at different

1360

development stages: OFF1 and OFF2 (g), OFF2 and OFF3 (h), and OFF1

1361

and OFF3 (i).

1362 1363

Figure S13 Small RNA length distributions in ON (a) and OFF (b) trees.

1364


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1365

Figure S14 Methylation levels of the small RNAs in the TE regions of

1366

the CG, CHG, and CHH contexts in AB apple trees.

1367 1368 1369 1370

Table S1 Primer list used to analyze gene expression.

1371

Table S2 Quality assessment of the sequence data.

1372

Table S3 Differentially methylated regions between ON1 and OFF1.

1373 1374 1375 1376 1377 1378 1379 1380 1381 1382 1383 1384 1385 1386 1387 1388 1389 1390 1391 1392 1393 1394 1395 1396 1397 1398



1399

Figure 1

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Figure 2

1428 1429 1430 1431 1432 1433 1434 1435 1436 1437 1438 1439 1440 1441 1442 1443 1444 1445 1446 1447



1448

Figure 3

1449 1450 1451 1452 1453 1454 1455 1456 1457 1458 1459 1460 1461 1462 1463 1464 1465 1466 1467


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1468


Figure 4

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1490

Figure 5

1491 1492 1493 1494 1495 1496 1497 1498 1499 1500 1501 1502 1503 1504 1505 1506 1507 1508 1509


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1510


Figure 6

1511 1512 1513 1514 1515 1516 1517 1518 1519 1520 1521 1522 1523 1524 1525 1526



1527

Figure 7

1528 1529 1530 1531 1532 1533 1534 1535 1536 1537 1538 1539 1540 1541 1542 1543 1544 1545 1546 1547


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Page 71 of 73

1548


Figure 8

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1571

Figure 9

1572 1573 1574 1575 1576 1577 1578 1579 1580 1581 1582 1583 1584 1585 1586


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Page 73 of 73

1587


TOC graphic

1588


Dynamic Cytosine DNA Methylation Patterns Associated with mRNA

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