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Identification of ethylene responsive miRNAs and their targets from newly harvested banana fruits using high-throughput sequencing ming Dan, meihua Huang, fen Liao, Renyuan Qin, Xiaojun Liang, Ezhen Zhang, Maokang Huang, Zhenyong Huang, and Quanguang HE J. Agric. Food Chem., Just Accepted Manuscript • DOI: 10.1021/acs.jafc.8b01844 • Publication Date (Web): 07 Sep 2018 Downloaded from http://pubs.acs.org on September 8, 2018

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Journal of Agricultural and Food Chemistry

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Identification of ethylene responsive miRNAs and their targets from newly

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harvested banana fruits using high-throughput sequencing

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Ming Dan1, Meihua Huang1.2, Fen Liao1, Renyuan Qin1, Xiaojun Liang1, Ezhen Zhang1, Maokang

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Huang1, Zhenyong Huang, Quanguang He 1 3∗

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Corresponding author: [email protected] Institute of Agro-food Science & Technology, Guangxi Academy of Agricultural Sciences, 174 East Daxue Road, Nanning 530007, China 2 Guangxi Crop Genetic Improvement Laboratory, Nanning 530007, China 3 Guangxi Key Laboratory of Fruits and Vegetables Storage-processing Technology, Nanning 530007, China

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Email of authors: Ming Dan, [email protected];Ezhen Zhang, [email protected]; Fen Liao, [email protected]; Meihua Huang, [email protected]; Renyuan Qin ,[email protected]; Maokang Huang, [email protected]; Xiaojun Liang, [email protected]; Zhenyong Huang ,[email protected]

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Abstract

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The roles of microRNAs(miRNAs) related to ethylene response in banana fruits remain

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unknown because many miRNAs are differentially expressed as the fruit ripens, making the

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identification of ethylene-responsive miRNAs difficult. Using newly harvested banana fruits

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(within five hours after harvest) as material, we found that these fruit did not ripen when treated

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with 5 µL/L of ethylene for 12 h at 22°C. Two miRNA libraries were generated from newly

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harvested banana fruits with and without ethylene treatment and sequenced. In total, 128 known

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miRNAs belonging to 42 miRNA families were obtained, and 12 novel miRNAs were identified.

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Among them, 22 were differentially expressed in response to ethylene treatment, among which 6

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known miRNAs and their putative targets were validated using qRT-PCR. These putative targets

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encoded proteins including GATA, ARF, DLC and AGO,etc. KEGG and GO analyses showed that

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miRNAs differentially expressed in response to ethylene mainly function in the molecular and

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biological processes.

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Keywords: microRNA, banana fruit, newly harvested, ethylene response, high-throughput sequencing

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Introduction

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MicroRNAs (miRNAs) are a class of small RNAs (sRNAs) with lengths of 21-24 nt that regulate

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the expression levels of their target genes mainly via endonucleolytic cleavage or translational

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inhibition

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functions have been examined, revealing important roles in plant growth, development, responses to

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pathogens and abiotic stress 4.

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1-3

.At present, miRNAs from more than fifty plants have been identified, and their

In recent years, high-throughput sequencing has been applied to miRNA screening.

Using deep

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sequencing, 33 known miRNAs were identified in tomatoes, 14 of which showed different

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expression

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immunoprecipitation sequencing (ChIP-seq) confirmed the direct binding of RIN (Ripening

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Inhibitor, an important transcription factor in control of tomato ripening) to the miR172a promoter5.

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Tomato fruit and leaf sRNA databases have also been generated using deep sequencing and 7912

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redundant sequences matching 20 known miRNA families have been found. Validation by northern

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blotting showed that some of these families were fruit-specific, and different accumulation patterns

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were observed during fruit growth and ripening 6. In trifoliate orange fruit and leaf tissues, 42

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highly conserved miRNA families were found from 4,876,395 distinct sequences using Solexa

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sequencing, among which 10 novel miRNAs were predicted and confirmed using q-PCR7.

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Additionally, miRNAs have also been identified from other fruits such as olives8and strawberries9.

pattern

during

fruit

ripening5.

Furthermore,

whole-genome

chromatin

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The banana is the most widely cultivated tropical fruit worldwide. It contributes approximately

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20% of total fruit production worldwide, according to the FAO in 2015. In many tropical and

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subtropical countries, bananas are eaten as part of the daily diet due to their nutritional balance and

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high carbohydrates. The ripening process of banana fruits, which are typical climacteric fruits, has

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been widely studied by many researchers. The known physiological changes that occur during



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banana ripening include chlorophyll degradation, carbohydrate metabolism, aroma synthesis,etc 10-11.

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Many of the genes underlying these marked changes have been proven to be involved in banana

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ripening or abiotic/biotic resistance, including MADS12, MabZIP4/513,

MAPK 14and WRKY15

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Banana miRNAs have also been reported. For instance, 170 and 244 miRNAs were identified

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from cv. Grand Naine (Musa, AAA group) and cv. Rasthali (Musa, AAB group) leaves,

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respectively16. The over expression of mir156 in banana plants results in stunted growth and

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peculiar changes in leaf anatomy16. Fifty-nine salt stress response miRNAs were identified from

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banana roots, and their expression patterns were found to be dose-dependent17. In particular,

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miR169, miR156 and miR2188 were up-regulated in banana leaves when the plants were grown

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under

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showed tissue-specific behaviors. For example, miR167c is greatly abundant in banana flowers but

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is rare in the roots

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identified from banana fruits, and their predicted targets include genes encoding SPL, AP2, EIN3

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(ETHYLENE INSENSITIVE 3), E3 ubiquitin ligase, and β-glucosidase20. However, little is

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currently known about the miRNAs in banana fruits that respond to ethylene .

water-deficient

stress

conditions

18

.

Some

miRNAs

in

bananas

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. It is worth noting that a total of 82 ripening-related miRNAs were also

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Plant responses to ethylene include ripening, senescence, disease resistance, stress tolerance and

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changes in morphology. As a climacteric fruit, bananas are sensitive to ethylene. Abundant changes

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occur at the molecular level when ripening initiates, which can make the identification of specific

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miRNAs that regulate the ethylene responses difficult. Indeed, these responses are not only

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correlated with fruit ripening but also are related to disease resistance , stress tolerance and

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development regulation.

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Climacteric fruits sometimes show ethylene insensitivity that depends on whether they are

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attached to the tree or on growing time. Purple passion fruit, plum and pear were found to ripen


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when they were attached to the tree 21-23 .Tomato fruits did not ripen normally when

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more slowly

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they were picked up at the 20% of the total growth period even when they were treated with

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ethylene gas 24. Our study also found that newly harvested banana fruits exhibit low sensitivity to

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ethylene. The span of this stage may range from 0 to 72 h depending on the growing time of the

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fruit. During this stage, banana fruits hardly ripen after low-level ethylene treatment (e.g., 5 µL/L

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for 12 h), whereas the same concentration effectively ripened the fruit stored longer than 72 h.

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These ethylene-insensitive fruits enabled investigation of the ethylene response at the molecular

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level.

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In this study, we used these low ethylene-sensitivity fruits with or without ethylene treatment to , identify miRNAs related to the ethylene response by a high-throughput sequencing approach.

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Materials and methods

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Plant material and treatments. As shown in the experimental design in Fig. 1,pre-climacteric

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banana (Musa acuminata AAA group, cv. Cavendish) fruits at 70–80% maturation (70–75 days

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after flowering) were obtained from a local plantation near Nanning, Guangxi, China. The fruit

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fingers were separated from the hands. Fingers with visual defects were excluded and fruits with

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uniform in shape, weight, and maturation were selected. The selected fruit fingers were washed

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twice in clean water and air-dried before treatment. These pretreatments were performed within 1 h

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of cutting the spike from the banana tree.

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Next, the fruit fingers were randomly divided into three groups and stored at 22°C. Fruits stored

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for 5 h were designated the first group and then sealed in an atmosphere containing 0 µL/L of

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ethylene for 12 h at 22°C. This group of fruits served as the control (CK). According to our previous

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study, fruits stored for 5 h after harvest do not to start to ripen easily after the application of 5 µL/L



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of ethylene gas for 12 h. Thus, the second group of banana fruits was selected at 5 h of storage and

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sealed in an atmosphere containing 5 µL/L of ethylene for 12 h at 22°C. This group of banana fruits

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was labeled ethylene-unripened (ETU) fruit. To ensure that the ethylene treatment was effective,

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another finger of banana fruits that had been stored for three days at 22°C was placed in the same

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chamber with the ETU fruits and labeled the positive control. The third group of fruits, which were

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stored for 72 h and sealed in an atmosphere containing 5 µL/L of ethylene for 12 h, were labeled the

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ethylene-ripened (ET) fruit(Fig 1). After 12 h of gas treatment, the fruits were placed at 22°C and

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90% RH for 5 days. Samples were obtained at specific selected time points, and the pulp was frozen

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in liquid nitrogen and then stored at -80°C. Ethylene production and the firmness of the fruit were

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measured during the experimental period. All assessments were performed using three biological

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replicates. According to our previous study, the ethylene signaling pathway was activated at 1 h

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after treatment, but fewer physiological changes occurred. At the 24-h time point, the ethylene

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production reached its peak, and the firmness decreased dramatically, indicating that the fruit had

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begun to ripen. For the 60-h time point, the color of the banana fruit turned from green to yellow,

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which is a key point for color shift. Therefore, the pulp of the ETU and CK fruits after 1 h of

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treatment was selected as the high-throughput sequencing samples for ethylene-responsive miRNA

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analysis. Samples were taken at 1, 24 and 60 h to perform the qPCR analysis.

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Determination of changes in firmness. Firmness was measured at four regions of the pulp of six

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individual banana fruits using a texture analyzer Model CT3 (Brookfield Engineering Labs, Inc.

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USA) equipped with a 100 N static load cell. A 6-mm diameter stainless steel probe with a flat end

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was used. The chart speed was 60 mm/min, and the force (N) required for penetration was recorded.

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Determination of ethylene production. Ethylene production rates were measured by placing

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three banana fruits in an airtight container equipped with a rubber stopper for 2 h at 25°C. A 1-mL ACS Paragon Plus Environment

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gas sample was withdrawn from the headspace of the containers using a syringe and injected into a

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gas chromatograph (Model GC-6890N, Agilent Technologies, Santa Clara, CA, United States)

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fitted with a flame ionization detector (FID) and an activated alumina column (200 cm × 0.3 cm),

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with an injector temperature of 120°C, a column temperature of 60°C and a detector temperature of

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160°C. Helium was used as the a carrier gas at a flow rate of 30 mL/min. Three replicates were

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used.

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RNA extraction. Ten grams of frozen tissues was ground in liquid nitrogen using a mortar and

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pestle, and 0.5 g of frozen powder was used for RNA extraction. Total RNA and miRNA were

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isolated using the TaKaRa MiniBEST Plant RNA Extraction Kit

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according to the manufacturer’s instructions.

(TaKaRa, Dalian, China)

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sRNA library construction and sequencing. For construction of the sRNA libraries, small

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RNAs of length ranging from 18 to 40 nt were purified from total RNA using polyacrylamide gel

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electrophoresis (PAGE). Purified sRNAs were then ligated to a 3’ adaptor and a 5’ adaptor with T4

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RNA ligase (Promega, Madison, WI). Next, sRNAs with 5’ and 3’ adaptors were selected and

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reverse transcribed into cDNA using RT-PCR. Finally, the PCR product was purified by PAGE and

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quantified using the Agilent high sensitivity DNA assay on an Agilent Bioanalyzer 2100 system.

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Deep sequencing was performed using an Illumina Hiseq 2000 platform at Beijing Novo Gene

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Genomics Institute, China.

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RAW data analysis. To evaluate the quality of the data, the error rate, Q20, Q30 and GC content



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were calculated. Raw sequence reads containing poly-N, poly-A, T, G or C, or 5’ adaptor

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contaminants, reads lacking the 3’ adaptor and insert tag, and other low quality reads were filtered

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out. Data that satisfied the above quality standards were selected as clean data and processed for

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further downstream analyses. sRNA lengths typically ranged from 18-40 nt, and sequence lengths

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outside this range were excluded.

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Bioinformatics analysis. Small RNA tags were mapped to the reference genomic sequence

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(ftp://ftp.ensemblgenomes.org/pub/release-19/plants/fasta/musa_acuminata/dna/Musa_acuminata.M

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A1.19.dna.toplevel.fa.gz) using Bowtie without mismatch to analyze the expression and distribution

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on the reference. Mapped sRNA tags were matched to miRBase21.0 to search for known miRNAs

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using blastn and E-value cutoff was set to 125. The Software programs miRdeep2 and srna-tools-cli

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were used to obtain potential miRNAs and to draw the secondary structures. miREvo26 and

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miRdeep227were integrated to predict novel miRNAs by exploring their secondary structure. For

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miRNA family analysis, miFam.dat (http://www.miRbase.org/ftp.shtml) was used with known

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miRNAs to search for members in other species. Novel miRNA precursors were submitted to Rfam

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(http:// rfam.sanger.ac.uk/search) to search for Rfam families. The miRNA expression levels were

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estimated by transcript per million (TPM), and differential expression analysis was performed using

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the DEGSeq R package (1.8.3). q-value 1 were set as the threshold

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for significant difference. The value of log10 (TPM+1) was used to generate a heat map by HemI

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1.0, with color from red to blue representing gradual decreases in expression level. An online plant

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sRNA tool (http://plantgrn.noble.org/psRNATarget/) was used to predict the target genes of

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differentially expressed miRNAs. The banana CDS library (Musa acuminata, Banana Genome Hub,

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version 1) was selected for the target search with the default web parameter.Then the target gene


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candidates were performed Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and

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Genomes (KEGG) pathway analysis by GOseq (release 2.12) and KOBAS respectively.

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qPCR analysis of differentially expressed miRNAs. miRNAs were isolated from pulp using the

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Plant miRNA Extraction Kit (TaKaRa BIO INC, JPN). After digestion by DNAse I (TaKaRa,

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Dalian, China), first strand cDNA was synthesized from the miRNAs using the Mir-X miRNA

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First-Strand Synthesis and SYBR qRT-PCR synthesis kit (Clontech, USA).The primers for cDNA

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synthesis and qPCR are listed in the appendix (Supporting Information 1). U6 was used as the

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reference gene. All qPCR experiments used the SYBR Green PCR Master Mix (Bio-Rad). The

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formula 2-∆∆CT was used to calculate the relative expression levels of the candidate target genes.

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Three independent biological replicates were used in the analysis. The LSD method was used to

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perform the significance testing and fold changes with a p-value < 0.05 were considered statistically

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significant.

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qPCR analysis for predicted target genes. Total RNA was isolated from pulp using the Plant

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RNA Extraction Kit (TaKaRa, Dalian, China). After digestion by DNAse I to remove genomic

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DNA, total RNA was synthesized to first strand cDNA using M-MLV cDNA synthesis kit

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(Promega). The primers for qPCR are listed in the appendix (Supporting Information 1). MaRPS2

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(ribosomal protein 2) was used as the reference gene according to a previous study

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experiments used the SYBR Green PCR Master Mix (Bio-Rad). The formula 2-∆∆CT was used to

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calculate the relative expression levels of candidate target genes. Three independent biological

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replicates were used in the analysis. Fisher LSD method was used to perform the significant test and


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. All qPCR


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fold changes with a p-value < 0.05 were considered statistically significant.

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Results

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Effect of ethylene on banana fruits stored for 5 h and 72 h. As shown in Fig. 2, the color in

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the ET fruit changed rapidly, and the skin peeled off easily after ethylene induction. By contrast, for

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the ETU fruits, the peel was difficult to separate, and the fruits did not show any signs of ripening

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although they were exposed to the same ethylene concentration. The positive control fruits indicated

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the effectiveness of ethylene treatment, as observed by the physiological change. The ET fruits were

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induced to ripen by ethylene and showed increasing endogenous ethylene production (Fig. 3A);

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additionally, a rapid decrease in firmness (Fig. 3B) occurred. However, in the ETU fruits, ethylene

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production and changes in firmness similar to those in the control were observed. These

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observations clearly indicated that banana fruits were less insensitive to ethylene treatment when

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they were immediately after they were cut from the tree. After days in storage, the fruits became

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more sensitive, and ripening was easily induced.

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Sequence analysis. Raw data were obtained from two sample libraries using the Illumina

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Hisq2000 platform, yielding 10975203 and 10942315 total reads, respectively. After filtration, more

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than 95% clean data were obtained from the raw data, demonstrating the reliability of the

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sequencing.

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These reads contained 8597259 and 2885798 short RNA sequences with lengths ranging between


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18 and 30 nt in the two banana fruit samples, respectively. The length distribution analysis showed

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that the majority of the sRNAs in each library were between 21 and 24 nt in length for both libraries

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(Fig. 4). The most abundant length in both sRNA libraries was 24 nt.

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length-selected sRNAs (18–30 nt) to the banana genomic database led to successful mapping of

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66.46% and 68.81% of the sequences, respectively. Non-coding sequences, such as rRNAs, tRNAs,

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snRNAs and snoRNAs, were excluded by submitting these data to the Rfam database prior to

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analysis.(table 1)

Mapping these

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Identification of known miRNAs and novel miRNAs in banana fruits. To identify known

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miRNAs, sequences that mapped to the banana genomic database were blasted against miRBase 21

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with all plant species (72 plant species) as match objects. In total, 2207 and 2097 matched

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sequences were found to belong to 40 and 34 miRNA families, respectively (table 2,Supporting

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Information 2). These 42 families contain 128 known miRNAs in the two experimental samples

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(see Supporting Information 3). Half of the miRNAs belonged to were highly conserved families

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that are widely distributed in more than 30 plant species, including miR156, miR396 and miR166,

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which were covered in 52, 45 and 44 plant species in miRBase21, respectively (see Supporting

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Information 2). However, some miRNAs showed conservation only in monocot plants. For example,

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miR528 is found only in Brachypodium distachyon, Zea mays, Sorghum bicolor, Oryza sativa,

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Saccharum sp, and Aegilops tauschii. The top three species matched to the two banana fruit sRNA

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libraries were Oryza sativa, Vitis vinifera and Glycine max, and more than two thousand sequences

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were successfully aligned (see Supporting Information 4).

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The total unique read number showed the abundance of the miRNA families. miR319, miR159,



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and miR396 were the three most abundant miRNA families in banana fruits (see Supporting

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Information 3). However, some miRNA families, such as miR171 and miR169, had few unique

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reads in the two siRNA libraries, demonstrating their low abundance in banana fruits. Sequence

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alignment analyses identified 305 and 265 miR156 sequences in 52 plant species in the two sRNA

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libraries (see Supporting Information 2). This finding confirmed that miR156 was the most

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conserved family in plants. miR396 was the largest family with 14 members in banana fruits. In

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contrast, only one or two members of some families such as miR5179 and miR1511, were detected

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in the two sRNA libraries,suggesting that these miRNAs do not exhibit conserved properties (see

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Supporting Information 3).

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A total of 12 novel miRNA families with lengths of 18 to 24 nt were identified in the two sRNA

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libraries. Each sample contained 9 and 11 novel miRNA families, and seven of the families were

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identified as anti-sense miRNAs (miRNAs*), which was powerful evidence for new miRNA

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prediction. When the sequences were blasted in miRBase 21, no homologs were found with the

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criteria of a score greater than 90 and an E-value less than 1, indicating that these 12 predicted

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miRNAs might be specific to banana. By analyzing the read counts, we found that most of these

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novel miRNAs had very low abundances in the two samples except for mac-miRn1, whose read

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count exceeded one thousand. These findings for mac-miRn1 suggested that it may be a

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banana-specific miRNA that plays an important role in fruit development and ripening (see

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Supporting Information 5).

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Prediction of targets of known and novel miRNAs. For 30 of the 44 known miRNAs, targets

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were successfully predicted in the banana CDS library including transcription factor, Dicer

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endoribonuclease, Auxin response factor, and AP2 domain-containing protein (see Supporting


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Information 6). The other predicted target genes were unannotated, indicating that their functions in

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banana fruits were unknown. The same procedure was performed to predict the targets of the novel

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miRNAs. The blast and computational results showed that the successful prediction and annotation

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of target genes for 8 of the 12 novel miRNAs (see Supporting Information 7). Although the target

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genes for mac-miRn4, mac-miRn6, and mac-miRn7 were predicted, their targets were not annotated,

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suggesting the need for future studies in exploring their unknown functions. Furthermore,

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mac-miRn11 and mac-miRn12 could not be matched with any target sequence under the default

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parameters, which might be due to the incompleteness of the banana genome database.

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Differential expression of known and novel miRNAs in response to ethylene treatment. The

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read numbers of all of the known and novel miRNAs were normalized by transcripts per million

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(TPM), and differential expression analysis was performed using the DEGSeq R package (1.8.3).

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This screening showed 22 miRNAs to be differentially expressed at a threshold of a q-value 1 (see Supporting Information 8). The heat map showed that 12 of the

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miRNAs were up-regulated, and 10 of the miRNAs were down-regulated after ethylene treatment

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(Fig. 5). Moreover, mac-miR535a, mac-miR162a, and mac-miR319a, which had the three highest

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TPM values were down-regulated after ethylene treatment. Whereas mac-miR172a, mac-miR160a,

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and mac-miRn2 were up-regulated, and high TPM values were also detected in these two samples.

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Furthermore, mac-miRn12, mac-miR169a, mac-miR169e, and mac-miRn4 demonstrated very high

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log2 fold change values, but their TPM values were lower than 150(Fig. 6). Considering the TPM

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and log2 fold change values, we selected mac-miR172a,mac-miR319a, mac-miR167a, mac-miR535a,

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mac-miR168a and mac-miR162a as the validation genes for the subsequent qPCR experiments.

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Gene Ontology analysis of predicted targets of the differentially expressed miRNAs.To

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better understand the functions of miRNAs involved in the response of banana to ethylene, the GO

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enrichment of the predicted targets of the differentially expressed miRNAs were analyzed by

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GOSEQ (see Supporting Information 9). The candidate targets were mainly assigned to biological

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processes and molecular function. The biological process ontology contained 20 GO items,

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including regulation of the nitrogen compound metabolic process, regulation of the cellular

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macromolecule biosynthetic process, and the RNA metabolic process. The molecular function

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ontology contained 8 enriched GO terms, including nucleic acid binding and heterocyclic

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compound binding. The most enriched molecular function GO terms were heterocyclic compound

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binding, nucleic acid binding and organic cyclic compound binding, each of which covered more

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than 30 genes for each term(Fig 7).

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KEGG pathway analysis. KEGG is a database resource that elucidates the high-level functions

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and utilities of a biological system, including the organism, cell, and ecosystem, from

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molecular-level information. In our study, RNA transport and metabolic pathways were enriched

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(Fig. 8, Supporting Information 10), indicating that ribosome biogenesis was a major process

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underlying the fruit response to ethylene. When the metabolic process becomes a primary pathway,

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indicating the fruit begins to ripen32.

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Validation of differentially expressed miRNAs and their targets using qRT-PCR. To obtain


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better miRNA expression profiles during the banana fruit response to ethylene, we selected some

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differentially expressed miRNAs and their target genes for validation using qRT-PCR (table 3).

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These selected miRNAs included mac-miR172a, mac-miR535a, mac-miR162a, mac-miR167a,

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mac-miR168a, and mac-miR319a, which were found to show significant differential expression..

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The U6 sRNA was used as the reference gene for the miRNA qRT-PCR, and the RPS2 gene was

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selected as the internal control for the target gene qRT-PCR24(Fig 9).

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According to our target prediction analysis in banana, TOE3, PSS2, HOX9 and SNC1 were

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predicted to be targets of mac-miR172a. In the control fruit, mac-miR172a was dramatically

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increased at 24 h and then decreased at 60 h. All of the targets were significantly down-regulated at

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24 h and then increased again at 60 h. Their expression patterns were complementary to that of

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mac-miR172a. However, after ethylene application, mac-miR172a was highly increased in the 1 h

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ETU sample and then significantly decreased at 24 and 60 h compared to the level in the control

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fruit. The putative target genes, except for TOE3,were significantly decreased in the ETU fruit at 1

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h.

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Auxin response factors (ARFs) are targets of miR167 in Arabidopsis thaliana. In this study,

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ARF17 and ARF6 were predicted as targets of mac-miR167a. According to the qRT-PCR results,

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mac-miR167a was dramatically decreased when the banana fruits were exposed to ethylene. This

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result was consistent with the deep sequencing analysis. A negative correlation was found between

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ARF6 and mac-miR167a in the control and ETU fruits, indicating that this miRNA-target pair might

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be a regulator in the ethylene response. However, ARF17 did not show a reverse expression pattern

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from that of mac-miR167a in the CK or ETU fruits, suggesting that it was not a target of miR167

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under ethylene exposure.

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According to the psRNATarget analysis results, two transcription factors (GAMYB and GATA26)



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were predicted to be targets of mac-miR319a. The expression of mac-miR319a was enhanced at 24

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h and then decreased at 60 h, and the same trend was found in the ETU fruits. The RT-PCR results

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showed that mac-miR319a was down-regulated in the ETU fruits compared with the control fruits.

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Of the two predicted target genes, no significant difference was found in the accumulation of

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GAMYB between the CK and ETU fruits, whereas GATA26 was significantly up-regulated after

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ethylene treatment, demonstrating a negative correlation with the expression pattern with

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mac-miR319a.

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The function of miR535 in plants is unclear. In our experiment, no trend was observed in the

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control or ETU banana fruits, but ethylene significantly down-regulated mac-miR535a

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accumulation. The tricalbin-3 gene (TCB3) and sodium/hydrogen exchanger 6-like (NHE6) gene

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were two putative targets of mac-miR535a; the expression levels of both genes were up-regulated

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by ethylene, and their patterns were negatively correlated with that of mac-miR535a, indicating that

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these genes might be potential targets and might participate in the response to ethylene.

367

The expression of mac-miR162a did not change from 1 h to 60 h in the control banana fruits.

368

Ethylene gradually down-regulated the amount of mac-miR162a, and a 0.6-fold change was

369

observed in the ETU fruit at 60 h. The transcriptional levels of the two predicted targets were

370

determined. DCL1 (endoribonuclease Dicer homolog 1) was significantly increased from 1 h to 60

371

h in both the control and ETU fruits. Moreover, the accumulation of DCL1 in the ETU fruits was

372

dramatically higher than that in the control fruits. Ethylene down-regulated the mac-miR162a

373

transcription levels and up-regulated the DCL1 expression levels. Another predicted target, DPP8

374

(putative dipeptidyl peptidase 8), was found a negative correlation expression pattern only in the

375

control fruits, but had higher expression levels in the ETU fruits than in control fruits.


Page 16 of 35

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376

The expression pattern of mac-miR168a was significantly increased in the CK fruits at 24 h

377

and then decreased at 60 h. A similar pattern was found in the ETU fruits but was not significant.

378

The transcription levels of mac-miR168a in the ETU fruits were lower than those in the control

379

fruits at all time points tested, suggesting that mac-miR168a was down-regulated by ethylene. Two

380

predicted targets of mac-miR168a [AGO1A (protein argonaute 1A) and WEB (WEB family protein)]

381

were up-regulated by ethylene stimulation. indicating that miR168 might regulate AGO1A and WEB

382

in banana fruits after ethylene treatment.

383 384

Discussion

385

Newly harvested banana fruits show low sensitivity to ethylene

386

As a climacteric fruit, the banana is highly sensitive to ethylene. Typically, green banana fruits

387

ripen completely within 5–7 days after exposure to ethylene gas at 20–25℃. Uniform ripening is

388

necessary for both the fresh sale market and product manufacturing. However, some partially green

389

banana fruits are found among the fully ripened group in the market. This dissimilarity in ripening

390

speed is mainly due to their different ethylene sensitivities. Based on our results, the changes of

391

ethylene production and firmness show that newly harvested banana fruits are less sensitive to

392

ethylene. Days in storage may improve banana fruit sensitivity and facilitate the induction of

393

ripening.

394 395

sRNA deep sequencing analysis to assess the response of newly harvested banana fruits to

396

ethylene

397

Deep sequencing of sRNAs has become a highly efficient method for studying miRNA profiles

398

during plant exposure to hormones. miRNAs that respond to ethylene have been explored by ACS Paragon Plus Environment


399

high-throughput sequencing in many plants. In grapevine berries, 162 miRNAs were differentially

400

expressed after ethylene treatment 29, and during rose petal flower opening, among which a total of

401

50 miRNAs were responsive to ethylene

30

402

miRNAs from banana fruits, respectively

20

403

miRNAs from banana fruits. This discrepancy might be due to the difference of fruit development

404

stage, growing environment and postharvest treatment. In our experiment the bananas were unripe,

405

whereas in previous studies the ripe fruits were used. Generally, studies of miRNAs involved in the

406

ethylene response of fruits use ethylene-ripened fruits as the material. Many miRNAs that are

407

differentially expressed during the fruit ripening process are explored.Although this method can

408

effectively identify ripening-related miRNAs, distinguishing the miRNAs that are involved in the

409

ethylene response is difficult. Here, we used newly harvested banana fruits, which did not ripen

410

after low-concentration ethylene treatment, to identify miRNAs that participated in the ethylene

411

response. A systematic analysis identified 22 of the miRNAs were screened as differentially

412

expressed miRNAs involved in the ethylene response. The targets of these differentially expressed

413

miRNAs were predicted using bioinformatics software, and most of the targets functioned in the

414

nucleus or acted as transcription factors.

. A previous study identified 125 known and 26 novel . In this study, we identified 128 known and 12 novel

415

GO analysis showed that the targets were mainly assigned to biological processes and molecular

416

functions. No genes were significantly enriched for the cellular component GO terms, which was in

417

contrasted with the previous findings in ripening banana fruits20. Additionally, differences were

418

found in the molecular function and biological process terms. Changes in cellular components

419

indicate the physiological initiation of the physiology for ripening, and the lack of inclusion of a

420

cellular component in the GO terms suggests that ripening-related genes are not activated even if

421

some changes occur at the molecular level. The remarkably increased number of candidate targets


Page 18 of 35

Page 19 of 35


422

in molecular functions suggested that miRNAs participated in the response of bananas to ethylene

423

via diverse binding functions. Previous research demonstrated that the most highly represented

424

KEGG pathway in normally ripening banana fruits was the metabolic pathway 20. In our experiment,

425

RNA transport and metabolic pathways were enriched. Both the KEGG and GO analyses indicated

426

that the activity at the cell nucleus level was the primary change during ethylene stimulation.

427 428

miRNAs and their predicted targets in response to ethylene in newly harvested banana fruits

429

miRNAs repress their target transcripts by cleavage or translational inhibition. Cleavage is the

430

main method used by plant miRNAs for regulation. We selected 6 of the differentially expressed

431

known miRNAs and their predicted targets for validation. The qRT-PCR results for all of these

432

selected miRNAs were consistent with the deep sequencing analysis results, and some target

433

accumulation showed opposite trends to miRNA expression.

434

miR172 has been proposed to be important in regulating plant phase transitions

31

, floral organ

435

identity and tomato pedicel abscission32. miR172 may also play a role in fruit development and

436

ripening 33,34. The direct binding of RIN to the miR172a promoter has been confirmed in tomatoes 5.

437

We found that mac-miR172a was up-regulated at 1 h in the ETU sample and then significantly

438

decreased at 24 and 60 h; a similar expression pattern was found in the ethylene-ripened banana

439

fruits

440

correspondingly down-regulated at 1 h of ethylene treatment. These results indicated that the three

441

predicted targets might be regulated by mac-miR172a. HOX9 is belongs to HD-ZIP

442

(homeodomain leucine zipper)TF family, which also response to hormone ,abiotic stress and organ

443

development. One of tomato homeobox protein named LeHB-1 had been proved to interact with

444

LeACO1 then involved in the tomato ripening35. The down-regulated HOX9 implied a repression of

20

. The predicted targets of this miRNA are PSS2, HOX9 and SNC1, which were



445

ripening on this experiment. TOE3 has been demonstrated to play a critical role in Arabidopsis

446

floral patterning and can be repressed by miR17236. However, TOE3 did not show reverse

447

transcriptional profiles with mac-miR172a in banana fruits under ethylene conditions. Similar

448

results were found in a previous study, indicating that the TOE3 gene was not targeted by miR172

449

under ethylene or 1-MCP conditions in banana fruits20. These findings show that miRNAs and their

450

targets exhibit opposing expression patterns at specific time points and under specific conditions,

451

indicating that miRNAs participate in plant development via diverse regulatory functions.

452

In Arabidopsis thaliana, miR167 targets ARF6 and ARF8 and regulates gynoecium and stamen

453

development in immature flowers 4. A recent study found that miR167 also targeted IAA-Ala

454

Resistant 3 (IAR3) in Arabidopsis thaliana was under high osmotic stress conditions37. Auxin and

455

ethylene are two important plant hormones, but the crosstalk between the ethylene and auxin

456

pathways is unclear. Ethylene and auxin act synergistically to regulate root growth and

457

development38. Transcriptome profiling analysis revealed a complex auxin-ethylene crosstalk

458

during the tomato ripening process 38. This study also found that the mac-miR167a target ARF6 in

459

banana fruits was down-regulated after ethylene induction, implying that miR167 might mediate the

460

auxin-ethylene interaction. However, the roles in banana fruit ripening need to be further

461

investigated.

462

miR319 has been shown to contribute to the fate of plant leaves and flowers by regulating TCPs

463

(TCP transcription factor family) 4. A recent study revealed that miR319 also plays important roles

464

in cold, salt and drought stress tolerance

465

its target MYB33 in roots but not in shoots42. However, in our experiment, ethylene down-regulated

466

mac-miR319a and up-regulated GATA26,suggesting that GATA26 is a potential target of

467

mac-miR319a in banana fruits.Similar results were found in Medicago truncatula43, suggesting that

39-41

. Ethylene up-regulated miR319b and down-regulated


Page 20 of 35

Page 21 of 35


468

miRNAs have diverse functions in different organs and species. GATA transcription factors are

469

conserved in higher plants44 and are important for flowering, germination and greening.

470

Interestingly, two GATA factors GNC (NITRATE-INDUCIBLE, CARBON-METABOLISM

471

INVOLVED) and GNL (GNC-LIKE) are threshold-dependent regulators that are targeted by the GA

472

and auxin signaling pathways to control plant growth45. Our findings showed that GATA26, which is

473

a potential target of mac-miR319a, could be induced by the exposure of banana fruits to ethylene.

474

Combined analysis indicates that mac-miR167a may target ARF6, which may provide new insights

475

into the plant hormone network regulated by miRNAs.

476

miR535 was down regulated after treatment then TCB3 and NHE6 were all up regulated

477

accordingly.

478

binding, especially in calcium-dependent phospholipid binding. NHE6 was responsible for

479

transmemberance sodium/hydrogen exchanging. These suggested that a enhancment of ion

480

transmemberance transportation may be a physiological response to ethylene, and this may be

481

regulated by miR535.

482

According to UniProtKB database(www.uniprot.org),TCB3 was involved in metal

DCL1 and AGO1 are nucleus component that were responsable for miRNAs formation and

483

mRNA degradation respectively.

Both of them play critical roles in miRNA biogenesis and the

484

regulation of downstream gene expression. miR168 is involved in plant development, viral defense

485

and antibiotic stress by regulating the AGO1 protein, which is a post-transcriptional regulatory

486

protein that binds to RISC and interacting with other miRNAs

487

SlAGO1A and SlAGO1B participated in tomato fruit development 50. In addition, ethylene increased

488

AGO1 expression and decreased DCL1 expression to promote tomato flower abscission

489

observation showed negative expression patterns between mac-miR168a and AGO1, which was in

490

agreement with a previous study showing that ethylene up-regulated AGO1 accumulation 32. In this


46-49

. A previous study showed that

32

. Our


491

work, we found that DCL1 was also increased after ethylene exposure. These findings differ from

492

the results reported for the tomato pedicel. The diverse miRNAs involved in the regulatory

493

mechanism may be due to the different organs and species studied. The increased accumulation of

494

DCL1 and AGO1 implied biological activity of the miRNAs induced by ethylene. Taken together,

495

our findings suggest that DCL1 and AGO1 mediate the regulatory progress by guiding miR162 and

496

miR168 after ethylene induction in banana fruits.

497

In summary, ethylene-responsive miRNAs were identified from two sRNA libraries from newly

498

harvested banana fruits with and without ethylene induction. Some of the miRNAs and their

499

predicted targets were validated by qRT-PCR. The KEGG and GO analyses revealed their potential

500

roles following exposure of banana fruits to ethylene. Here, we show a schematic (Fig 10) based on

501

our result and attempt to illustrate the possible functions of miRNAs during the banana fruits

502

response to ethylene. These results shed light on the functions of miRNAs involved in the ethylene

503

signaling pathway and provide a good reference for deeper exploration of the roles of miRNAs in

504

plants.

505 506 507

Abbreviations used

508

miRNA, MicroRNA; qPCR, quantitative PCR; TF, transcription factor; sRNAs: Small RNAs; nt:

509

Nucleotide; ET: Ethylene ripen fruit; CK: Control fruit ; ETU:Ethylene treated but unripened

510

fruit ;GO: Gene Ontology; KEGG: Kyoto Encyclopedia of Genes and Genomes.

511 512 513

Funding sources


Page 22 of 35

Page 23 of 35


514

This work was supported by the National Natural Science Fund of China (grant no. 31160406，

515

31760599) and Natural Science Fund of Guangxi province(grant no. 2012GXNSFBA053058,

516

2014GXMXFAA118110), Science & Technology project of Nanning(grant no .20142067) and team

517

project of Guangxi academy of agricultural siences(grant no .2015YT88，2017YZ01).

518 519

Supporting Information description

520

Supporting Information1:Primers used in this study (XLS 29.5kb)

521

Supporting Information2:Number of successful matched species and sequences (XLS 13.1Mb)

522

Supporting Information3:List of miRNA family matched in mirbase (XLS 59.5kb)

523

Supporting Information4:Numbers of sequence mathed to species in plant mirBase (XLS 21kb)

524

Supporting Information5:Novel miRNAs (XLS 15.5kb)

525

Supporting Information6:Predicted targets of known miRNAs (XLS 292kb)

526

Supporting Information7:Predicted targets of novel miRNAs (XLS 24kb)

527

Supporting Information8:Result of different analysis (XLS 33.5kb)

528

Supporting Information9:Significant GO terms for target genes of differentially miRNAs (XLS

529

91kb)

530

Supporting Information10:The most enriched pathways that was identified for target genes (XLS

531

15kb)

532

Competing interest

533

The authors declare that they have no competing interest.



534 535 536 537 538 539 540 541 542 543 544 545 546 547 548 549 550 551 552 553 554 555 556 557 558 559 560 561 562 563 564 565 566 567 568 569 570 571 572 573 574 575 576 577 578 579

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672 673 674 675 676 677 678 679 680 681 682 683 684 685 686 687 688 689 690 691 692 693 694 695 696 697 698 699 700 701 702 703 704 705 706 707 708 709 710 711 712 713 714 715 716


Figure graphics and tables

Fig. 1 Graphical representation of the experimental design pathway

Fig. 2 Images of banana fruits showing the progression of ripening CK: Fruits stored for 5 h and then sealed with 0 µL/L of ethylene for 12 h ETU: Fruits stored for 5 h and then sealed with 5 µL/L of ethylene for 12 h ET: Fruits stored for 72 h and then sealed with 5 µL/L of ethylene for 12 h Positive control: sealed with ETU fruits to indicate the effectiveness of ethylene treatment.

717



718 719 720

5 4.5

(A)

4

-1

µL.kg .h

-1

3.5

CK

3 2.5 2

ETU

1.5 1 0.5

ET

0 1h

12h

24h

36h

48h

60h

72h

5d

times after treatment 60

(B)

50

CK

40

N

721 722 723 724 725 726 727 728 729 730 731 732 733 734 735 736 737 738 739 740 741 742 743 744 745 746 747 748

Page 28 of 35

30

ETU 20 10

ET

0 1h

12h

24h

36h

48h

60h

72h

5d

times after treatment

Fig. 3 Ethylene production (A) and firmness (B) of differently treated banana fruits

Table 1 Sequence analysis of short RNAs

Sample

Total reads

CK

10975203

ETU

10942315

Clean data

18-30 nt RNA

Mapped sRNA

6579093 10728476 8597259 (76.53%) (97.75%) 1985634 10553063 2885798 (68.81%) (96.44%)

rRNA

tRNA

snRNA

snoRNA

405135

85852

8931

3818

68020

13601

1300

933

749 750 751 752 753 754 755 756 757


Page 29 of 35

762 763 764 765 766 767 768 769 770 771 772 773 774

775 776 777 778 779 780 781 782 783 784 785 786 787 788 789 790 791 792 793 794 795 796 797 798

40 35

Frequence %

758 759 760 761


CK

30

ETU

25 20 15 10 5 0

18

19

20

21

22

23

24

25

26

27

28

29

30

Length distribution(nt)

Fig. 4 Length distributions of sRNAs in banana fruits

Table 2 Number of matched known miRNA families and novel miRNAs Number of sequences matched known novel total matched know miRNAs miRNA families miRNAs (all plant database) CK 6579093 2207 40 10 ETU 1985634 2097 34 11

Fig. 5 Hierarchical cluster analysis of differentially expressed miRNAs between control (CK) and ethylene-unripened banana fruits (ETU) (CK) fruits stored for 5 h and sealed with 0 µL/L of ethylene, (ETU) fruits stored for 5 h and sealed with 5 µL/L of ethylene. The red color represents high expression levels, and the blue color represents low expression levels. Clustering generated by HemI 2.0 with log10(TPM+1).



mac-miRn2

mac-miRn3

mac-miRn10

mac-miR160a

mac-miR172a

mac-miR164h

mac-miR169e

-6

mac-miR169a

-4

mac-miRn12

-2

mac-miR168d

-8 -10

mac-miRn5

mac-miR319h

mac-miR169d

mac-miR162a

0

mac-miRn4

2

mac-miR319a

4

mac-miR167e

6

mac-miR535a

8

mac-miRn7

8

mac-miR168a

10

mac-miR167a

10

mac-miRn11

799 800 801 802 803 804 805 806 807 808 809 810 811 812 813 814 815 816 817 818 819 820 821 822 823 824 825 826 827 828 829 830 831 832 833 834 835 836 837 838 839 840 841 842 843 844

Page 30 of 35

6 4 2 0 -2 -4 -6 -8

2

log .fold change TPM( ETU/CK)

-10

Fig. 6 22 differential expressed miRNAs presented in log2 (fold change) (ETU/CK) (CK) fruits stored for 5 h and sealed with 0 µL/L of ethylene and (ETU) fruits stored for 5 h and sealed with 5 µL/L of ethylene. All data were normalized against TPM (transcripts per million).

Fig. 7 Enriched GO terms generated from putative targets of the differentially expressed miRNAs


Page 31 of 35

845 846 847 848 849 850 851 852 853 854 855 856 857 858 859 860 861 862 863 864 865 866 867 868 869 870 871 872


Fig. 8. KEGG pathway analysis of putative targets of the differentially expressed miRNAs

Table 3 Selected miRNAs and their targets for qPCR validation miRNA

Predicted targets GSMUA_Achr1T09830_001 GSMUA_Achr7T05560_001

mac-miR172a

Target description AP2-like ethylene-responsive transcription factor TOE3 (TOE3) SNC 1 like protein(SNC1)

GSMUA_Achr5T18530_001

Homeobox-leucine zipper protein HOX9 (HOX9) GSMUA_Achr10T20130_001 Putative Phosphatidylserine synthase 2 (PSS2) GSMUA_Achr11T18520_001 Auxin response factor 17 (ARF17)

mac-miR167a GSMUA_Achr11T25770_001 Auxin response factor 6 (ARF6) GSMUA_Achr7T21560_001

Putative Transcription factor GAMYB (GAMYB) mac-miR319a GSMUA_Achr11T23110_001 Putative GATA transcription factor 26 (GATA26)



Page 32 of 35

Tricalbin-3 (TCB3)

GSMUA_Achr2T03720_001

mac-miR535a GSMUA_Achr10T03540_001 Sodium/hydrogen exchanger 6-like (NHE6) GSMUA_Achr2T19780_001 Putative Dipeptidyl peptidase 8 (DPP8) mac-miR162a GSMUA_Achr8T12350_001 Endoribonuclease Dicer homolog 1 (DLC1) GSMUA_Achr5T18090_001 WEB family protein (WEB) mac-miR168a GSMUA_Achr1T07120_001

4

mac-miR172a HOX9

a

2.5 2

d e a

b

1

bc

b

f d

d

relative expression level


c

3

1.5

a

b

b

3.5

mac-miR172a SNC1

4.5 4

0.5

3.5

c

3 2.5

d

2 1.5

e

a

1 0.5

0

b

b

CK-24h

CK-60h

ETU-1h

ETU-24h

ETU-60h

CK-1h

CK-24h

CK-60h


a

4

4.5

3 2.5

e

d

a

a 1

b

b

0.5

f b

b


c

2

ETU-1h

ETU-24h

ETU-60h

mac-miR172a TOE3

a

4

b

3.5

b

3.5

c

3 2.5

a

d

2 1.5

b

b

e b

1

c

d

0.5

f

0

0 CK-1h

CK-24h

CK-60h

ETU-1h

ETU-24h

CK-1h

ETU-60h

CK-24h


1.8

2.5

b a c

c

0.8

b

0.6

bc

0.4

d

cd d

d

d


1.4

1

CK-60h

ETU-1h

ETU-24h

ETU-60h


mac-miR167a ARF6

a

1.6

1.2

b


mac-miR172a PSS2

4.5

1.5

f

b

b

0

CK-1h


893 894 895 896 897 898 899 900 901 902 903 904 905 906 907

4.5


873 874 875 876 877 878 879 880 881 882 883 884 885 886 887 888 889 890 891 892

Protein Argonaute 1A (AGO1A)

mac-miR167a ARF17

2

a

a

b

b 1.5

b c

c c

1

d

c d

d

0.5

0.2 0

0 CK-1h

CK-24h

CK-60h

ETU-1h

ETU-24h

ETU-60h

CK-1h



CK-24h

CK-60h

ETU-1h


ETU-24h

ETU-60h

Page 33 of 35

mac-miR319a GATA

3

1.6

a b c

2

a d

1.5

d

e

b

b b

1

mac-miR319a GAMYB

a

1.4

a



2.5

c c

0.5

b

1.2

ab b b

c

0.8

c

c

0.6 0.4

0 CK-24h

CK-60h

ETU-1h

ETU-24h

CK-1h

ETU-60h

CK-24h

CK-60h


3

mac-miR535 NHE6

4.5

a


b

b c a d

a a

1

e

b

b

b

0.5

ETU-60h

a b

3.5

c

3 2.5

d

2

e a f

1.5

a

b

a

1

b

b

0.5 0

0 CK-1h

CK-24h

CK-60h

ETU-1h

ETU-24h

CK-1h

ETU-60h

CK-24h

CK-60h


6

2.5

mac-miR162a DLC1


bc c

ab e

a

d b

bc

ab

c

1

a

DPP8

b

2

ETU-24h

ETU-60h

mac-miR162a

a

4 3

ETU-1h


5

a

b

2

a 1.5

ab

c c

b

ab

1

bc

d

c

0.5

0

0 CK-1h

CK-24h

CK-60h

ETU-1h

ETU-24h

ETU-60h

CK-1h

CK-24h

CK-60h


3

d

bc c

0.5 0 CK-1h

CK-24h

CK-60h

ETU-1h

ETU-24h

ETU-60h


d

1

bc

bc

ETU-60h

b c

c d

a

3

b

a b

ETU-24h

mac-miR168a AGO1A

3.5

a

2

ETU-1h


mac-miR168a WEB

2.5

1.5

ETU-24h

mac-miR535 TCB3

4

2 1.5

ETU-1h


2.5


b

0.2

CK-1h


ab

b

1

0


908 909 910 911 912 913 914 915 916 917 918 919 920 921 922 923 924 925 926 927 928 929 930 931 932 933 934 935 936 937 938 939 940 941 942 943 944 945 946 947 948 949 950 951 952 953


2.5

a

2 1.5

d b

e

bc

1

c

bc

bc

f

0.5 0 CK-1h


CK-24h

CK-60h

ETU-1h

ETU-24h


Fig. 9 Quantitative expression analysis of some differentially expressed miRNAs and their target ACS Paragon Plus Environment

ETU-60h


954 955 956 957 958 959 960 961 962 963 964 965 966 967 968 969 970 971 972 973 974 975 976 977 978 979 980 981 982 983 984 985 986 987 988 989 990 991 992 993 994 995 996 997 998 999

genes. Expression levels are presented as fold changes by setting CK-1h as value 1. Each value represents the mean±SD of three replicates. Different capital letters mean significant difference between tissues (p

Identification of Ethylene Responsive miRNAs and ... - ACS Publications

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