research article high-throughput sequencing reveals...

Research ArticleHigh-Throughput Sequencing Reveals Diverse Sets of ConservedNonconserved and Species-Specific miRNAs in Jute

Md Tariqul Islam Ahlan Sabah Ferdous Rifat Ara NajninSuprovath Kumar Sarker and Haseena Khan

Molecular Biology Laboratory Department of Biochemistry and Molecular Biology University of Dhaka Dhaka 1000 Bangladesh

Correspondence should be addressed to Haseena Khan haseenaduacbd

Received 11 November 2014 Revised 13 February 2015 Accepted 23 February 2015

Academic Editor Mohamed Salem

Copyright copy 2015 Md Tariqul Islam et al This is an open access article distributed under the Creative Commons AttributionLicense which permits unrestricted use distribution and reproduction in any medium provided the original work is properlycited

MicroRNAs play a pivotal role in regulating a broad range of biological processes acting by cleaving mRNAs or by translationalrepression A group of plant microRNAs are evolutionarily conserved however others are expressed in a species-specific mannerJute is an agroeconomically important fibre crop nonetheless no practical information is available for microRNAs in jute to dateIn this study Illumina sequencing revealed a total of 227 knownmicroRNAs and 17 potential novel microRNA candidates in jute ofwhich 164 belong to 23 conserved families and the remaining 63 belong to 58 nonconserved families Among a total of 81 identifiedmicroRNA families 116 potential target genes were predicted for 39 families and 11 targets were predicted for 4 among the 17identified novel microRNAs For understanding better the functions of microRNAs target genes were analyzed by Gene Ontologyand their pathways illustrated by KEGG pathway analyses The presence of microRNAs identified in jute was validated by stem-loop RT-PCR followed by end point PCR and qPCR for randomly selected 20 known and novelmicroRNAsThis study exhaustivelyidentifies microRNAs and their target genes in jute which will ultimately pave the way for understanding their role in this crop andother crops

1 Introduction

Regulation of gene expression is one of the most enigmaticfacets of molecular genetics that results in intricate appear-ance of a biological entity Scientists have been attemptingto elucidate the regulatory mechanisms of gene expressionfor long and the radical discovery of regulatory functionof endogenous small noncoding RNAs is overwhelming thescientific community with their ever increasing potentials [1]Small noncoding RNAs of 18ndash40 nucleotides (nt) in size havebeen proved to play a vital role in a remarkably wide rangeof biological processes including cell proliferation devel-opmental timing and patterning chromatin modificationgenome rearrangement and stress response in plants andanimals [2] Small RNAs regulate a variety of biological pro-cesses in plants by interfering with messenger RNA (mRNA)translation directing mRNA cleavage or promoting theformation of compact transcriptionally inactive chromatin

[3] Several distinct classes of small RNAs have been reportedso far including microRNAs (miRNAs) [4] small interferingRNAs (siRNAs) [5] repeat-associated small interfering RNAs(ra-siRNAs) [6] Piwi interacting RNAs (piRNAs) [7] naturalantisense transcript derived small interfering RNAs (nat-siRNAs) [8] transacting small interfering RNAs (ta-siRNAs)[9] heterochromatic small interfering RNAs (hc-siRNAs)[10] secondary transitive small interfering RNAs primarysmall interfering RNAs competing endogenous RNAs (ceR-NAs) and long small interfering RNAs [11ndash13] It has onlybeen a few years since it was appreciated that microRNAsprovide an unanticipated level of gene regulation in bothplants and metazoans [11]

miRNAs are well differentiated due to some of theirparticular characteristics [12] they are derived from distinctgenomic loci and processed from transcripts that can formlocal RNA hairpin structures and usually miRNA sequencesare nearly always conserved in related organisms [13 14]

Hindawi Publishing CorporationInternational Journal of GenomicsVolume 2015 Article ID 125048 14 pageshttpdxdoiorg1011552015125048

2 International Journal of Genomics

Most miRNAs are transcribed by RNA polymerase II whichfolds into a stable usually imperfect hairpin structure [13]pri-miRNA transcript is cleaved to pre-miRNA by RNaseIII-type Dicer-like 1 (DCL1) protein [15] to produce a distinctivesim21 nt double-stranded RNA This duplex is exported intothe cytoplasm by HASTY and methylated at the 31015840 end byHEN1 [16] A cytoplasmic helicase unwinds the translocatedduplex into a single-strandedmaturemiRNA which is finallyincorporated into RNA-induced silencing complex (RISC)[5 17 18] AmaturemiRNA sequence can range from 19 to 24nucleotides (nt) in length and act as a regulatory molecule inposttranscriptional gene silencing by base pairing with targetmRNAs [12] Within the RISC complex miRNAs functionin the direct cleavage of 31015840 untranslated region of protein-coding genes or translational repression depending on itsperfect or imperfect match with the targets [19] The samemature miRNA can also be present as several length variantsthese populations of miRNA variants are called isomiRNAswhich are isoforms of microRNAs caused by an imprecise oralternative cleavage of Dicer during pre-miRNA processing[20]

Several miRNAs have been identified in plants and theyhave been characterized in a wide variety of metabolic andbiological processes with important functions [12] The firstplant miRNAs were described in Arabidopsis thaliana [21]currently the latest miRBase release (v20 June 2013) contains24521microRNA loci from 206 species processed to produce30424 mature microRNA products [22] Earlier miRNAshave been identified through either bioinformatics analysis orsequencing [23] various methods have been used to identifymiRNAs in rice [24] wheat [25] tomato [26] andmaize [27]Besides the miRNAs that are highly conserved in differentspecies there are species-specific miRNAs originating fromrecently evolved miRNA genes [28 29] The expression ofthese species-specific miRNAs is often low and can thereforebe difficult to detect by traditional methods [30] In recenttimes high-throughput sequencing platforms are showingsignificant promise for small RNA discovery and genome-wide transcriptome analysis at single-base pair resolution[23 31] Sequencing techniques such as the Solexa PlatformSOLiD and 454Technology aswell as othermassively parallelsequencing strategies have been successfully applied in orderto identify miRNAs in many plant species such as rice [32]alfalfa [33] grape [34] tomato [35] orange [36] soybean [37]peanut [38] poplar [39] and black gram [40] In comparisonwith microarray deep sequencing has several advantagesthe major one being its application in comprehensive iden-tification and profiling of small previously unknown RNApopulations [23] Nevertheless analyses of these data are notperfect especially in the absence of native genome sequence[40]

Jute (Corchorus olitorius and Corchorus capsularis) is abast fibre like flax and hemp Cultivation of this environmen-tally friendly as well as the most affordable fibre producingplant is concentrated around the Ganges Delta region ofBangladesh and India where the warm wet climate duringthe monsoon season provides ideal growing conditions Interms of usage production and global requirement jute issecond only to cotton [41] Jute plants are easy to grow have

a high yield per acre and unlike cotton have little need forpesticides and fertilizers They are also known to enrich thesoil [42] As these plants grow fast they are often used incrop rotation The leaves and roots left after harvest enrichthe soil with micronutrients maintaining soil fertility Whenused as a geotextile it puts nutrients back in the soil whenit decomposes This rain-fed crop during its growth helps toclean the air by assimilating three times more CO

2than an

average tree converting the CO2into oxygen

Despite its great agronomic importance research on juteat the molecular level is insignificant [43] Genome sequenceof jute is not available in the public database So far only 1210sequences are found in the GenBank [43] with no depositsof any miRNA sequences in miRBase database Within thiscontext the current study has employed the deep sequencingstrategy in an attempt to effectively identify conserved andnovel jute miRNAs Quantitative real-time PCR (qRT-PCR)has been performed to determine the expression of thesemiRNAs For mapping the identified miRNAs genome ofVitis vinifera was used as reference because of sequencehomology of this species with jute [44]

2 Methods and Materials

21 Plant Materials Preparation and Small RNA Library Con-struction Seeds of farmer popular O-9897 variety of tossajute (Corchorus olitorius) were collected from BangladeshJute Research Institute (BJRI) They were surface sterilizedwith 70 ethanol subsequently washed in distilledwater andallowed to germinate on sterile petri dishes containing 3MMmoist filter paper (Whatman) at 30 plusmn 1∘C and 65 relativehumidity Seeds were allowed to grow for 4 days underthe specified conditions On the fourth day of germinationseedlings were collected and immediately snap-frozen inliquid nitrogen and stored at minus80∘C for subsequent use

RNA was isolated from collected seedlings using TRI-zol reagent (Invitrogen USA) by following the manufac-turerrsquos instructions Later RNA samples were sent to Bei-jing Genome Institute (BGI Shenzhen China) for deepsequencing of small RNAby IlluminaHiseq high-throughputsequencing platform In short the sRNAs pool of 18ndash30 nt inlength were fractionated from total RNA After ligation with51015840 and 31015840 adaptors the short RNAs so obtained were reverse-transcribed to cDNA according to the Illumina protocolTheresulting small RNA library was then sequenced followingSBS method (sequencing by synthesis) by Illumina Hiseqhigh-throughput sequencing

22 Prediction of Known miRNA in Jute Raw data obtainedfrom Illumina Hiseq high-throughput sequencing was at firstfiltered by removing contaminants which include low qualityreads reads with 51015840 primer contaminants reads without 31015840primer reads without the insert tag reads with poly A andreads shorter than 18 nt After cleaning the final reads werethen used for further analyses Clean reads fully matchingother RNAs including mRNA rRNA tRNA snRNA

International Journal of Genomics 3

snoRNA and repeat RNA were excluded by using BLASTn-short alignment (blast2226+ ftpftpncbinihgovblastex-ecutablesblast+2226) and ali-gning against Sanger RNAfamily database (Rfam 110 ftpftpsangeracukpubdata-basesRfam) The remaining unique sequences were furtheraligned against miRBase-v20 [22] allowing up to 3 mis-matches to identify known miRNAs present in C olitoriusMature miRNAs present within a genome encoding identicalor nearly identical sequenceswere then grouped together intoa family

23 Novel miRNA Identification Prediction of novel miRNAwas done using prediction software Mireap (httpsource-forgenetprojectsmireap) developed by BGI by taking intoconsideration secondary structure cleavage position of Dicerprotein and minimum free energy of the unannotated smallRNA tags Strategic conditions for selecting unique miRNAare as follows (i) the tags which are to be used to predictnovel miRNA should be from unannotated tags which canmatch reference genome (Vitis vinifera) from the tags whichalign to introns as well as antisense exons (ii) genes whosesequences satisfy the above standards and their secondarystructures which allow hairpin miRNAs to fold within themand the presence of mature miRNAs in one arm of thehairpin precursors are considered as candidate genes formiRNA (iii) the possible candidate mature miRNA strandcontains 2-nucleotide 31015840 overhang (iv) hairpin precursors ofthe candidate miRNAs are devoid of large internal loops orbulges (v) secondary structures of the hairpins are stablewith theminimum folding energy (MFE) lower than or equalto minus20 kcalmol

24 Target Gene Prediction The rules used for target pre-diction in plants are based on those suggested by Allen etal [9] and by Schwab et al [45] These are (i) presenceof maximum 4 mismatches between small RNA and target(G-U bases count as 05 mismatches) (ii) not more than 2contiguous mismatches in the miRNAtarget duplex (iii) noend-to-end mismatches at the 51015840 of miRNA from 2 to 12positions of the miRNAtarget duplex (iv) no mismatches inpositions 10-11 of miRNAtarget duplex (v) a maximum of25 mismatches in positions 1ndash12 of the miRNAtarget duplexfrom 51015840 region of miRNA and (vi) minimum free energy(MFE) of the miRNAtarget duplex which should be ge 74of the MFE of the miRNA bound to its perfect complementThe targets of miRNAs were further validated by a well-recognized miRNA-target prediction tool psRNA Target[46] In addition to potential target prediction for known andnovel miRNAs pathways which include the correspondingtarget genes as well as the biological function of such genesare taken into consideration by using the grape genomeas a reference Biological functions are recommended byusing GO (level 3) (httpwwwgeneontologyorg) GeneOntology (GO) is an international standard classificationsystem for gene function which provides a set of controlledvocabulary to comprehensively describe the property ofgenes and gene products [47] There are 3 ontologies inGO biological process cellular component and molecular

function containing lists of biological functions that illustrateeach gene and its product (httpwwwgeneontologyorg)Each category defines precise participation of a given genewithin an organism As for pathway identification KEGG(httpwwwgenomejpkegg) [48] database was used toculminate the target genes within the systematic biologicalpathways KEGG analyses reveal the main pathways withwhich the target gene candidates are involved [49]

25 Validation of the Presence of Jute miRNAs To verify theidentified known and potential novel miRNA candidates injute stem-loop reverse transcription-PCR was performed[50]

Stem-loop primers were designed according to themethod described by Chen et al [51] This primer bindsto specific miRNA at the 31015840 region owing to the precisionconferred by the primer with the exact reverse complementof six nucleotides from the 31015840 end of each particular miRNAsequence which is reverse-transcribed by the RT enzymeTwo thousand nanograms of total RNAwere used to performthe RT reaction with Superscript III First Strand Synthe-sis System (Invitrogen USA) according to the protocol ofVarkonyi-Gasic et al [50] which has been further stan-dardized for jute For a reaction volume of 20 120583L 05120583L of10mM dNTPs was at first taken together with an appropriateamount of RNA and an adjusted amount of DEPC-treatedH2O followed by heating the mixture for five minutes at 65∘C

and then immediately transferring the same on ice Whilekeeping on ice for approximately 2 minutes 4 120583L of 5X FSbuffer 2 120583L of 01M DTT 12 120583L of 1 120583M stem-loop primer025 120583L of M-MLV Superscript III RT (200U120583L) and 01 120583LRNaseOUT (40U120583L) were added to the reaction mix TheRT reactionwas carried out in a thermal cycler (MastercyclerEppendorf Germany) followed by a pulse RT cycle startingfrom incubation at 16∘C for 30 minutes then 60 cycles of30 sec at 30∘ 30 sec at 42∘C and 1 sec at 50∘C This stepwas followed by another incubation step of 5mins at 85∘C toinactivate the RT enzyme

End point PCR was then conducted with miRNA specificforward primer and a universal reverse primer to checkthe presence of the specific miRNAs PCR products wereelectrophoresed on 3 agarose gel in 1X TAE and stainedwith ethidium bromide before visualization under a tran-silluminator We further conducted quantitative real-timePCR for confirming the expression of some selected knownand novel miRNAs using a 32-well plate Roche LightCyclerNano System and the Roche SYBR Green Master I (RocheDiagnostics Germany) Briefly equal amount of cDNA wastaken in a reaction volume of 75120583L in triplicate with01875 120583L of each primer (forward and universal reverse) and375 120583L of SYBR Green Master I Thermo cycling conditionswere set at an initial polymerase activation step for 600seconds at 95∘C followed by 45 cycles of 5 sec at 95∘C fortemplate denaturation 10 sec at 60∘C for annealing and 1 secat 72∘C for extension and fluorescence measurement Later adissociation protocol with a gradient from 50∘C to 95∘C wasused for each primer pair to verify the specificity of the RT-qPCR reaction and the absence of primer dimers


Table 1 Summary of data cleaning

Type Count Percent ()Total reads 16912862High quality 16822412 10031015840 adapter null 12978 008Insert null 1934 00151015840 adapter contaminants 86857 052Smaller than 18 nt 74711 044Poly A 1608 001Clean reads 16644324 9894

01020304050

15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33

Freq

uenc

e (

)

Length (nt)

Figure 1 Length distribution of small RNAs found in jute (violetbar indicates the percentage of total tags)

3 Results

31 Deep Sequencing of Jute Small RNAs In order to iden-tify microRNAs in jute RNA was isolated from the totaltissue of four-day seedlings and subjected to Illumina Hiseqhigh-throughput sequencing by synthesis (SBS) technologyAmong a total of 16912862 raw reads 16822412 high qualityreads were filtered through a series of data cleaning processesThe details of tag cleaning are summarized in Table 1 whichshows that a total of 16644324 clean reads were obtained byremoving 31015840 adapter null insert null 51015840 adapter contami-nants sequences smaller than 18 nt and poly A

This comprises about 99 of the high quality readsDistribution of these clean reads that contain a pool ofsmall RNAs ranging from 18 to 30 nucleotides is shown inFigure 1 However the sizes of small RNAs were not foundto be uniform majority (9269) of the sRNAs are 20ndash24 nt in size with 21 nt being the most abundant (4219)followed by 24 nt (2295) and 20 nt (1425) respectivelyThese sequences were then aligned to Rfam 110 [52] andGenbank database (BLASTn) to identify common sRNAsother than miRNAs as well as to remove mRNAs (seesupplementary file-1 in Supplementary Material availableonline at httpdxdoiorg1011552015125048) The remain-ing sequences were matched against miRBase-20 database[53] for the prediction of miRNAs revealing 33433 uniqueand 8994892 redundant reads which were finally used toidentify known miRNAs The novel miRNAs in jute wereidentified from unannotated tags by using Mireap softwaredeveloped by BGI (described in Section 2)

32 Identification of Known miRNAs in Jute In the absenceof the complete genome sequence and with practically no

information on miRNA of jute in miRBase clean reads werealigned to the miRNA precursormature miRNA of all plantsin miRBase allowing up to three mismatches or free gaps[54] to identify known miRNAs The expression of miRNAis generated by summing the count of tags which can align tothe temporary miRNA database generated by choosing themost expressive miRNA of each mature miRNA family

A total of 227 known miRNAs were identified in thisstudy of which 164 belong to 23 conserved and 63 to 58nonconserved families These nonconserved families werefurther categorized into 18 defined and 40 undefined familiesConservancy of miRNA families found in jute showed highhomology with their respective homologs in other modelplants (Figure 2) However the number of family membersof conserved miRNAs was highly variable with miR156being the largest family consisting of 26 members whereasmiR403 miR394 miR827 miR477 and miR2111 were thesmallest among the families comprising only one membermiR166 andmiR169 were the second largest with each having18 members and miR171 was the third largest family with 14members (Figure 3) Most of the conserved families containboth 5p and 3p mature miRNA sequences attaching a highconfidence to the data set [54]Highly variable reads numberswere also found among the families even in members ofthe same family indicating different expression levels ofthese miRNAs Among them col-miR157a had the highestlevel of expression having 5531609 counts and the othermiRNAs like col-miR156a col-miR166a and col-miR167halso had relatively high reads numbers counting more than150000 Several conserved miRNAs (like miR171 miR398and miR159) and as expected most of the nonconservedmiRNAs had relatively low copy numbers Interestingly amiRNA named col-miR3954 from an undefined family hadvery high level of expression having 868222 reads thirdhighest of all miRNAs found in jute miRNAs from eachfamily with highest reads number are shown in Table 2 Highexpression frequency of miRNAs derived from the 31015840 armof some pre-miRNAs like col-miR166h-3p col-miR166g-3p col-miR166j-3p col-miR165a-3p col-miR396b-3p col-miR396e-3p and so forth compared to their corresponding51015840 arm-miRNAs supports the observations of functionalactivity of both arms of pre-miRNA hairpins [55 56] Detailsof the miRNAs found in jute are summarized in supplemen-tary file-2

33 Identification of Novel miRNAs ThemiRNA hairpins aremostly located in intergenic regions introns or reverse repeatsequence of coding sequences [57] Thus tags belonging tothese regions were used to predict novel miRNAs Char-acteristic hairpin structure of miRNA precursor was usedto predict novel miRNA with prediction software Mireap(httpsourceforgenetprojectsmireap) by exploring thesecondary structure the Dicer cleavage site and the mini-mum free energy of the unannotated small RNA tags whichcould be mapped to the reference Vitis vinifera genome Pre-dicted secondary structures were further validated by Mfold(supplementary file-3) [58] and novel miRNAs were identi-fied based on the selection criteria described in Section 2 17potential novel miRNAs have been identified in this study of

International Journal of Genomics 5Ta

ble2miRNAs

from

each

family

with

theh

ighestfre

quency

injutewith

theirh

omologsinotherp

lants

Jutefamily

JutemiRNA

Leng

thof

smallR

NA

sequ

ence

Cou

ntof

small

RNA

sequ

ences

SmallR

NAsequ

ence

Hom

olog

(besto

ne)

Matches

number

Mism

atches

number

Gaps

number

Con

served

miR156

col-m

iR157a

21553160

9UUGAC

AGAAG

AUAG

AGAG

CAC

ath-miR157a

210

0col-m

iR156a

201724997

UGAC

AGAAG

AGAG

UGAG

CAC

ath-miR156a

200

0miR166

col-m

iR166a

21215636

UCG

GAC

CAGGCU

UCA

UUCC

CCath-miR166a

210

0miR167

col-m

iR167h

22154973

UGAAG

CUGCC

AGCA

UGAU

CUUA

mdm

-miR167h

220

0miR396

col-m

iR396b

-3p

2118695

GCU

CAAG

AAAG

CUGUGGGAG

Agm

a-miR396b

-3p

210

0miR168

col-m

iR168a

2116590

UCG

CUUGGUGCA

GGUCG

GGAA

ath-miR168a

210

0miR164

col-m

iR164a

217491

UGGAG

AAG

CAGGGCA

CGUGCA

ath-miR164a

210

0miR169

col-m

iR169b

212528

CAGCC

AAG

GAU

GAC

UUGCC

GG

ath-miR169b

210

0miR390

col-m

iR390a

212952

AAG

CUCA

GGAG

GGAU

AGCG

CCath-miR390a

210

0mir160

col-m

iR160a-3p

211448

GCG

UAUGAG

GAG

CCAAG

CAUA

gma-miR160a-3p

210

0miR159

col-m

iR159a

21484

UUUGGAU

UGAAG

GGAG

CUCU

Aath-miR159a

210

0miR171

col-m

iR171b

21558

UGAU

UGAG

CCGUGCC

AAU

AUC

osa-miR171b

210

0miR403

col-m

iR403

21282

UUA

GAU

UCA

CGCA

CAAAC

UCG

ath-miR403

210

0miR398

col-m

iR398

21262

GGAG

CGAC

AUGAG

AUCA

CAUG

hbr-miR398

201

0miR482

col-m

iR482b

222206

UCU

UACC

UACU

CCAC

CCAU

GCC

ghr-miR482b

211

0miR40

8col-m

iR40

821

129

AUGCA

CUGCC

UCU

UCC

CUGGC

ath-miR40

821

00

miR397

col-m

iR397a

21106

UCA

UUGAG

UGCA

GCG

UUGAU

Gath-miR397a

210

0miIR

530

col-m

iR530a

2181

UGCA

UUUGCA

CCUGCA

CCUUU

csi-m

iR530a

201

0miR393

col-m

iR393b-3p

2161

AUCA

UGCG

AUCC

CUUCG

GAAU

stu-m

iR393-3p

201

0miR394

col-m

iR394a

2016

UUGGCA

UUCU

GUCC

ACCU

CCath-miR394a

200

0miR827

col-m

iR827a

2122

UUA

GAU

GAC

CAUCA

ACAAAC

Agh

r-miR827a

210

0miR477

col-m

iR477i

212

ACUCU

CCCU

CAAG

GGCU

UCC

Gmes-m

iR477i

210

0miR2111

col-m

iR2111a

2115

UAAU

CUGCA

UCC

UGAG

GUUUG

ptc-miR2111a

210

0miR172

col-m

iR172a

211480

AGAAU

CUUGAU

GAU

GCU

GCA

Uath-miR172a

210

0Non

conserved

miR2275

col-m

iR2275a-3p

2254

UUA

AGUUUUCU

CCAAU

AUCU

CAzm

a-miR2275a-3p

201

2miR2118

col-m

iR2118a-3p

2236

UUGCC

GAAU

CCGCC

CAUUCC

GU

gma-miR2118a-3p

192

1miR528

col-m

iR528-5p

2117

UGGAAG

GGGCA

UGCA

GAG

GAG

osa-miR528-5p

210

0miR1310

col-m

iR1310

2169

AGGCA

UCG

GGGGCG

CAAC

GCC

han-miR1310

210

1miR7696

col-m

iR7696a-3p

216

UCU

GAAU

CAUGAG

AAC

UUGAG

mtr-

miR7696a-3p

191

2miR6224

col-m

iR6224a-3p

214

CUGAU

AAU

AUAG

GAC

GGAG

GG

sbi-m

iR6224a-3p

191

2miR64

62col-m

iR64

62c-5p

2128

AAG

GGAC

AAAAAG

GCU

AUAAG

ptc-miR64

62c-5p

200

3miR4243

col-m

iR4243

213

UUGAAC

UUGUA

CGAU

UUCG

ACath-miR4243

191

2miR5745

col-m

iR5745b

2116

UUUA

AUUUA

UAUA

CAUCU

CAC

mtr-

miR5745b

200

2miR902

col-m

iR902j-5p

241

AUAU

GUUA

CGCA

GAU

UCU

UCA

UUU

ppt-m

iR902j-5p

210

3miR2873

col-m

iR2873b

2110

UUGUGGCU

GAG

AUUUGGUA

UG

osa-miR2873b

191

2miR2950

col-m

iR2950

212465

UGGUGUGCA

GGGGGUGGAAU

Agh

r-miR2950

210

0miR5067

col-m

iR5049c

243837

GGAC

AAU

UAUUGUGGGAC

GGAG

GG

hvu-miR5049c

212

1miR818

col-m

iR1436

23920

AGAU

AAU

AUGGGAC

GGAG

GGAG

Uosa-miR1436

201

2miR44

14col-m

iR44

14a-3p

2111

AUCC

AAC

GAU

GCA

GGAG

CUGC

mtr-

miR44

14a-3p

201

0


Table2Con

tinued

Jutefamily

JutemiRNA

Leng

thof

smallR

NA

sequ

ence

Cou

ntof

small

RNA

sequ

ences

SmallR

NAsequ

ence

Hom

olog

(besto

ne)

Matches

number

Mism

atches

number

Gaps

number

miR1509

col-m

iR7122a

22488

UUGGAC

AGAG

AAAU

CACG

GUCG

mdm

-miR7122a

202

0miR158

col-m

iR158a

2034

UCC

CAAAU

GUA

GAC

AAAG

CAath-miR158a

200

0miR161

col-m

iR1612

212

UCA

AUGCA

UUGAAAG

UGAC

UAath-miR1612

210

0Und

efined

col-m

iR5162

244

AAAAU

GAC

CAAAAU

ACCC

CUAAAU

osa-miR5162

221

2Und

efined

col-m

iR6248

201

UAAU

UGAG

GAU

GGAG

GGAG

Uosa-miR6248

182

1Und

efined

col-m

iR7767-3p

221

UAGGAU

CAGGCA

GCU

UGAAG

GU

bdi-m

iR7767-3p

192

1Und

efined

col-m

iR5997

211

UGAAAC

UCA

AGUA

GCU

AAAAG

ath-miR5997

200

2Und

efined

col-m

iR5057

231

AAAC

UUUCA

GAU

GCA

UUUUGAC

Abd

i-miR5057

201

2Und

efined

col-m

iR6172

211

UGAG

ACCU

GUUUA

AGUUA

GAA

hbr-miR6172

191

2Und

efined

col-m

iR6279

203

UAAC

AAG

AAU

UCC

AGAC

ACA

ppe-miR6279

182

1Und

efined

col-m

iR6220-3p

231

AGAC

UUA

UAAU

UUGGGAC

GGAG

Asbi-m

iR6220-3p

212

1Und

efined

col-m

iR64

4321

1UGUA

UGAU

CAUGAU

GCU

GGAG

ptc-miR64

4319

12

Und

efined

col-m

iR156h

2017

UGAC

AGAAG

AGAG

AGAG

CAU

vvi-m

iR156h

200

0Und

efined

col-m

iR3954

22868222

UUGGAC

AGAG

UAAU

CACG

GUCG

csi-m

iR3954

192

1Und

efined

col-m

iR167i

201

UCA

UGCU

GGCA

GCU

UCA

CUU

gma-miR167i

200

3Und

efined

col-m

iR6300

1944

00GUCG

UUGUA

GUA

UAGUGGU

gma-miR6300

180

1Und

efined

col-m

iR169p

216

UAGCC

AAG

GAC

AAC

UUGCC

GG

osa-miR169p

210

1Und

efined

col-m

iR894

205406

GUUUCA

CGUCG

GGUUCA

CCA

ppt-m

iR894

190

2Und

efined

col-m

iR472a

22218

UUUUCC

CUAC

UCC

UCC

CAUCC

Cptc-miR472a

211

0Und

efined

col-m

iR5059

21212

CGGUCC

UGGGCA

GCA

ACAC

CAbd

i-miR5059

191

1Und

efined

col-m

iR2916

22312

GGGGGCU

CGAAG

ACGAU

CAGAU

peu-miR2916

202

1Und

efined

col-m

iR5072

2190

CGUUCC

CCAG

CGGAG

UCG

CCA

osa-miR5072

210

1Und

efined

col-m

iR477h

224

ACUCU

CCCU

CAAG

GGCU

UCC

AGmes-m

iR477h

210

1Und

efined

col-m

iR6478

21164

CCGAC

CUUA

GCU

CAGUUGGUA

ptc-miR6478

201

0Und

efined

col-m

iR5205b

24306

CUUA

UAAU

UAGGGAC

AGAG

GGAG

Umtr-

miR5205b

231

0Und

efined

col-m

iR7505

2131

UUCA

GAAAC

CAUCC

CCUCC

UU

ghr-miR7505

201

0Und

efined

col-m

iR5077

20378

GAU

UCA

CGUCG

GGUUCA

CCA

osa-miR5077

181

1Und

efined

col-m

iR5054

20904

GUUCC

CCAC

AGUCG

GCG

CCA

bdi-m

iR5054

171

2Und

efined

col-m

iR845c

2428

AGGCU

CUGAU

ACCA

AUUGAC

GUA

Gvvi-m

iR845c

210

3Und

efined

col-m

iR916

2228

CGAAG

GUCG

UCG

GUUCG

AAU

CCcre-miR916

192

1Und

efined

col-m

iR161-5

p1

2111

UUGAAAG

UGAC

UACA

UCG

GGG

aly-miR161-5

p1

210

0Und

efined

col-m

iR1863

2456

AGCU

CUGAU

ACCA

UGUUA

AGCA

UC

pab-miR1863

211

2Und

efined

col-m

iR7490

2441

AGUCU

GAU

AAAC

UCC

ACUGAC

GGU

ghr-miR7490

221

2Und

efined

col-m

iR3946

2113

UUGAG

AGAAG

AGAG

AGAG

CAC

csi-m

iR3946

210

3Und

efined

col-m

iR7728-5p

195

UUCG

GAU

UGAG

UGGAU

UUU

bdi-m

iR7728-5p

181

2Und

efined

col-m

iR1862f

211

AAG

GGGUUGGUUUA

CUUUUGG

osa-miR1862f

182

1Und

efined

col-m

iR6171

2111

ACUA

UGGAU

UGCU

GAAG

GUUU

hbr-miR6171

191

2Und

efined

col-m

iR5021

2131

UAAG

AAG

AAU

AAG

AAG

AAU

AA

ath-miR5021

182

1Und

efined

col-m

iR5244

216

UAUCU

GAU

GAU

GAU

UGUUGGU

mtr-

miR5244

192

0Und

efined

col-m

iR5049-3p

2330

AAG

UAAU

AUGGAAC

GGAG

GGAG

Ubd

i-miR5049-3p

212

1Und

efined

col-m

iR5629

2341

UUA

GGGUA

GUUA

ACGGGUA

GUUA

ath-miR5629

211

1


Corchorus olitoriusPrunus persicaLinum usitatissimum Carica papayaSolanum tuberosumManihot esculentaTheobroma cacaoRicinus communisCitrus sinensis Aquilegia caerulea

Solanum lycopersicumVitis viniferaBrassica napusPopulus trichocarpaGlycine maxSorghum bicolorZea maysOryza sativaArabidopsis thalianaArabidopsis lyrata

miR1509miR1310miR902

miR827miR818

miR7696

miR6462

miR6224

miR5745

miR530

miR528

miR5067

miR482

miR477

miR4414

miR4243

miR408

miR403

miR398miR397

miR396miR394 miR393miR390

miR2950miR2873

miR2275

miR2118

miR2111

miR172

miR171

miR169

miR168

miR167

miR166

miR164

miR161

miR160

miR159

miR158miR156

Figure 2 Conservancy of miRNAs identified in jute is presented as circular heat map among different model plants Each color represents adifferent plant species and white color represents absence of miRNA miRNA that was found in at least 9 plants was considered as conserved

which 9miRNAswere derived from 31015840 armof the pre-miRNAsequences and 8 from the 51015840 arm (Table 3) Average lengthof the pre-miRNAs sequences ranged from 78 to 349 ntsimilar to those found in maize [59] and rice [24] minimumfolding energy (MFE) for jute miRNAs was observed to bewithin a range from minus21 to minus1053 kcalmol similar to therange observed in cucumber [60] (supplementary file-4)Expression of novel miRNA was determined by summingthe count of such miRNAs which have no more than 3mismatches on either the 51015840 or 31015840 ends and with no mismatchin the middle Novel miRNAs usually have lower levels ofexpression than the conserved miRNAs as evident fromfindings of several plant species like soybean Brassica napusmaize Arabidopsis and wheat [59 61ndash64]

34 Target Gene Prediction for Identified miRNAs For aprecise elucidation of the role of miRNAs target identifi-cation and determination of their biological functions areof vital importance With a plethora of experimentationit is now evident that cleavage or translational repressionsite of most known plant miRNAs is located in the CDS(coding sequence) region of their target mRNA with perfector nearly perfect sequence complementarity [65] making itfeasible to identify plant miRNA targets [4 21 66] In thisstudy target genes of miRNAs were identified by BLASTnagainst the genome sequence of Vitis vinifera followingmethods described by Allen et al and Schwab et al [9 45]Among a total of 79 identified miRNA (both conservedand nonconserved) families 116 potential target genes were


Table 3 Potential novel miRNAs found in jute

miRNA name Number ofreads Mature miRNA sequence Mature

miRNA lengthMFE

(kcalmol)col-miRN1-5p 1448 GUGGGCGUGCCGGAGUGGUUA 21 minus289col-miRN2-3p 219 AGAGGGACUAUGGCCGCUUA 20 minus535col-miRN3-3p 17 UCGGUUUUGAAUUAGAGACGU 21 minus85col-miRN4-3p 14 UGAUGAUUGUGAAGAAGAUGA 21 minus6634col-miRN5-3p 32 AGAGGCUCGGUGAAAUAGACAU 22 minus2462col-miRN6-5p 11 UUCGUCCCCGGCAACGGCGCCA 22 minus666col-miRN7-5p 7 UUUUUUAAUUUUUUAUUUAUC 21 minus21col-miRN8-5p 20 GUUGAUCAAGUUGUGGAUGGC 21 minus7932col-miRN9-3p 2 AAACUUCGAAUUGGGAGGGC 20 minus893col-miRN10-3p 3 UGAAUGAUUUCGGACCAGGCU 21 minus483col-miRN11-3p 2 GUAAGAAGGGGUAGAGAAAAU 21 minus349col-miRN12-3p 5 AAGAUAGAGAGCACAGAUGAU 21 minus511col-miRN13-5p 3 GGCGCUGCCUACUCACUCGGACA 23 minus4077col-miRN14-3p 7 GUGAGGCUGGUUUCACAGAGCA 22 minus391col-miRN15-5p 6 GAGUGCAGCCAAGGAUGACUU 21 minus649col-miRN16-5p 4 UCAAGGUGGAGAUUGUUAGGA 21 934col-miRN17-5p 6 UUAUACGAUGUGGGAUAUUAC 21 minus1053

Table 4 Target genes for jute specific miRNAs

miRNA name Targetsnumber Target accession Annotation Location Free energy

col-miRN1 1 GSVIVT01015521001 Pentatricopeptide repeat-containing proteinmitochondrial 2244 2264 minus4730 [10000]

col-miRN4 2 GSVIVT01020089001 Thioredoxin H 16 36 minus2550 [7774]GSVIVT01021522001 Protease degS 67 87 minus2450 [7447]

col-miRN7 6

GSVIVT01000651001 Conserved gene of unknown function 178 198 minus1330 [7600]GSVIVT01000655001 NB-ARC domain containing protein 1291 1311 minus1330 [7600]GSVIVT01000657001 NB-ARC domain containing protein 1246 1266 minus1320 [7586]GSVIVT01021549001 Conserved gene of unknown function 702 722 minus1290 [7500]GSVIVT01035288001 Casein kinase 1464 1484 minus1420 [8114]GSVIVT01000656001 NB-ARC domain containing protein 1300 1320 minus1330 [7600]

col-miRN8 2 GSVIVT01033994001 26S proteasome regulatory particlenon-ATPase subunit 8 835 855 minus3070 [7852]

GSVIVT01037657001 Aconitase 30 043 024 minus2930 [7711]

predicted for 39 families (supplementary file-5) A totalof 46 genes from this prediction overlapped with targetsidentified by psRNA Target which found 99 target genes for19 miRNA families (supplementary file-9) Highest number(16) of targets was identified for miR397 family all of whichare laccase an enzyme involved in plant cell wall lignification[67] miR3946 had the second highest number of targets with11 genesMost of the other families targeted only a single geneFor the novel jute miRNAs a total of 11 targets were predictedfor 4 among the 17 identified miRNAs (Table 4 details insupplementary file-6) with a maximum number of targetgenes (6) recognized for col-miRN7 Most of col-miRN7targets are NB-ARC domain containing protein which is

a resistance (119877) protein involved in pathogen recognitionand subsequent activation of innate immune responses [68]To better understand the functions of miRNAs target geneswere analyzed by Gene Ontology (GO) level 3 to divulge theregulatory network of miRNAs and target genes [69] Suchanalysis demonstrates that for jute 133 predicted target genes(both for known and novel miRNAs) can be classified into 20having biological 5 cellular and 5 molecular functions Samegene was found to be involved in multiple processes with thereverse being also true (Figure 4 and supplementary file-7)As illustrated byKEGGpathway analysis (supplementary file-8) [70] the predicted target genes of jute miRNAs were foundto be involved in 42 different pathways


05

1015202530

Num

ber o

f fam

ilies

miR156

miR166

miR169

miR171

miR396

miR159

miR172

miR167

miR160

miR164

miR482

miR393

miR390

miR408

miR168

miR398

miR397

miR530

miR394

miR827

miR477

miR2111

miR403

Figure 3 Number of family members of conserved miRNAs arerepresented as bar diagram

05

10152025303540

Biol

ogic

al ad

hesio

nBi

olog

ical

regu

latio

nC

ellu

lar c

ompo

nent

org

aniz

atio

n or

bio

gene

sisC

ellu

lar p

roce

ssD

evelo

pmen

tal p

roce

ssEs

tabl

ishm

ent o

f loc

aliz

atio

nG

row

thLo

caliz

atio

nM

etab

olic

pro

cess

Mul

tiorg

anism

pro

cess

Mul

ticel

lula

r org

anism

al p

roce

ssRe

gula

tion

of b

iolo

gica

l pro

cess

Repr

oduc

tion

Repr

oduc

tive p

roce

ssRe

spon

se to

stim

ulus

Sign

alin

gSi

ngle

-org

anism

pro

cess

Cel

lC

ell p

art

Mem

bran

eM

embr

ane p

art

Org

anel

leA

ntio

xida

nt ac

tivity

Bind

ing

Cata

lytic

activ

ityN

ucle

ic ac

id b

indi

ng tr

ansc

riptio

n fa

ctor

activ

ityTr

ansp

orte

r act

ivity

Num

ber o

f gen

es

Biological processesCell Molecular

functionscomponents

Figure 4 GO (level 3) annotation of predicted targets Violet barindicates the number of targets involved in each process

35 Validation of the Presence of Known and Novel miR-NAs in Jute Some of the miRNAs identified through deepsequencing were verified by the standard stem-loop RT-PCRmethod [50] followed by end point PCR and qRT-PCRThe stem-loop primers were designed with a 31015840 specificityfor a particular miRNA which hybridizes to the same andis reverse-transcribed by the RT enzyme These primersincrease the sensitivity of the reactions such that this methodcan significantly distinguish two miRNAs with only onesingle nucleotide change [51] The RT product is then sub-jected to end point and qRT-PCR Forward primers wereprecisely designed from the first 15 bases of eachmiRNAwith51015840 extension of random GC rich sequence to increase themelting temperature as mentioned by Varkonyi-Gasic et alin 2007 while the reverse primer is a universal sequence thatis designed from the 51015840 region of the stem-loop RT primer[71] A set of 11 randomly selected conserved miRNAs as wellas 9 novel miRNAs were used for verification In this studythe stem-loop primer used was 50 bp long together with 51015840

(forward primer) and 31015840 extensions and the end point PCRproduct size ranged from 60 to 70 bp Amplification of theproduct gave a sharp band for each of the selected knownand novel miRNAs (shown in Figure 5) cDNAs were furtheramplified by qRT-PCR in technical triplicates from whichlog 2 values of Cq were calculated for each of the miRNAsand average of these values was compared with the log 2 valueof read counts obtained from deep sequencing Most of theqRT-PCR results acceded with the sequencing data howeverin some cases discrepancy was observed (Figure 6)

4 Discussion

Widespread discovery of miRNAs and their critical role ingene regulation has made it ever important to recognizethem in different species Identification of miRNAs and theirtargets is the basis for understanding their physiologicalfunctions [60]

While a large amount of miRNAs are reported anddeposited in databases from different plants miRNA asso-ciated research in jute is still to be instigated Without thegenome sequence of jute at hand identification of miRNAand their targets in jute by deep sequencing of small RNAs hasbeen the greatest challenge of the current study Use of closelyrelated speciesrsquo genomes as proxy references can facilitatemiRNA identification in nonmodel species like jute for whichgenome sequence is not available [72]Wehave used the grapegenome as the background because of sequence similaritybetween these two species

sRNAs with known function are commonly 20ndash24 nt insize [34] Analyses of size distribution patterns of the readsshow that the most abundant sRNAs in jute are 21 nt in sizewhich is about 4219 consistent with recent identificationof sRNAs in different plant [34 62 64]

Sequencing frequencies for miRNAs in a library can beused as an index for estimating the relative abundance ofmiRNAs [73] Numerous small RNA sequences engenderedfrom Illumina Hiseq high-throughput sequencing platformshow the presence of different miRNA families and are evenable to differentiate between distinct members of a givenfamily miR156 family which is highly conserved across thespecies [74]was found to be the largest family in jute seedlingswith the highest expression of col-miR157a followed by col-miR156a Two other members of the same family namelycol-miR156c and col-miR156k also show significant levelsof expression During shoot development miR156 regulatesthe transition of plants from juvenile to adult phase bytargeting SPL genes [75] In Arabidopsis miR156 is stronglyexpressed during seedling development and shows weakexpression in mature tissues [76]This could explain the rela-tive abundance of the members of miR156 family since RNAused in sequencing was extracted from jute seedlings Deepsequencing technology allows distinguishing and measuringmiRNA sequences with only a few nucleotide changes [38]Members of different families exhibit considerably dissimilarexpression levels For example the abundance of miR156family varied from 1 read (col-miR156p) to 5531609 reads(col-miR157a) This was also the case for some other miRNA


156 168 159 166 167 171 319 396 397 398 408

sim70bp

1kb+

(a)

N1 N2 N3 N4 N5 N6 N7 N9N8

sim70bp

1kb+

(b)

Figure 5 Agarose gel electrophoresis of known and novel miRNAs identified in jute (a) Amplicons for known miRNAs 156 miR156 159miR159 166 miR166 167 miR167 168 miR168 171 miR171 319 miR319 396 miR396 397 miR397 398 miR398 and 408 miR408 (b)Amplicons for novel miRNAs N1 col-miRN1 N2 colmiRN2 N3 colmiRN3 N4 colmiRN4 N5 colmiRN5 N6 colmiRN6 N7 colmiRN7N8 colmiRN8 and N9 colmiRN9

05

10152025

col-m

iR156

aco

l-miR159

aco

l-miR166

aco

l-miR167

aco

l-miR168

a-5

pco

l-miR171

aco

l-miR319

a-3

pco

l-miR396

a-5

pco

l-miR397

aco

l-miR398

col-m

iR408

aco

l-miR

N1

-5p

col-m

iRN2

-3p

col-m

IRN3

-3p

col-m

iRN4

-3p

col-m

iRN5

-3p

col-m

iRN6

-5p

col-m

iRN7

-5p

col-m

iRN8

-5p

col-m

iRN9

-3p

Log2

frequ

ency

Log2 of reads countLog2 of cq

Figure 6 Comparative expression analysis of different selectedmiRNAs found by deep sequencing and qRT-PCR Read counts ofdeep sequencing and cq values of qRT-PCR were converted intolog 2 value for a better representation Here the green bars representlog 2 values of sequencing frequency and orange bars represent thelog 2 values of cq produced by qRT-PCR Black regions on top of theorange bars represent errors calculated as standard deviation

families such as col-miR166 (from 3 to 215636 reads) and col-miR167 (from 12 to 154973 reads) Presence of a prevailingmember in a miRNA family may indicate the dominant roleof thismember during the growth phase at which the sampleswere collected It is also to be noted thatmost of the conservedmiRNA families consist of more than one member whereasnonconserved miRNAs identified in this study are mostlyrepresented by a single MIR (miRNA) gene

It has been hypothesized thatMIR genes originate by geneduplication events followed by random mutation processesto evolve in multiples of imperfectly paired hairpins [77 78]Consequently ancient evolutionarily conserved miRNAs arerepresented by multiple MIR genes whereas nonconservedmiRNAs (believed to be evolutionarily recent) generallyoriginate from a single locus [79] It is plausible that the con-served miRNAs are responsible for control of basic cellularand developmental pathways common to most eukaryoteswhereas nonconserved miRNAs are involved in regulation ofspecies-specific pathways and functions [80]

Species-specific miRNAs are believed to have recentlyevolved and in general expressed at levels lower than those

of strictly conserved miRNAs [34 77] Data acquired fromsequencing frequencies of conserved and nonconservedmiR-NAs fits well with this extrapolation where the nonconservedand species-specific miRNAs show residual accumulation inthe tested tissue However one miR-3954 a single member ofan undefined family appears to be expressed in significantlyhigh levels Its only homolog deposited in miRBase v20 is inC sinensis [81] showing high frequency of readsThough notdeposited in miRBase it has been reported in X sorbifolia[82]

17 new jute specific miRNAs identified in this study showa size anticipated for sRNAs derived from DCL1 process-ing although sequence variants that possess shortened orextended 51015840 or 31015840 ends were also found Ten among theseventeen new col-miRNAs are 21 nt in size consistent withcanonical DCL1 products [79] However length variation wasalso found Two col-miR2 and col-miR9 are 20 nt in sizethree col-miR5 col-miR6 and col-miR14 are 22 nt long col-miR13 was found to be 23 nt in size which can probably beexplained by the fact that diverse miRNA families are alsoindependently processed by DCL3 to generate a new class ofbona fide (23ndash25 nt) miRNAs with no canonical size calledlong miRNAs [83]

A total of 20 miRNAs of both conserved and species-specific origin were corroborated by stem-loop RT-PCR andtheir expression pattern was assessed by qPCR to validatethe data obtained from deep sequencing Discrepancies inthe expression pattern of some miRNAs found by deepsequencing and qPCR can be attributed to practical differ-ences between the sensitivity and specificity of these twotechniques [84] The sensitivity and large dynamic range ofnext generation sequencing (NGS) along with its consis-tent prediction of fold changes when compared with gold-standard qPCR support its use for discovery-oriented andexploratory miRNA profiling experiments [84 85]

To evaluate and outline a putative function for a miRNAin plants target identification is necessary [73] We havepredicted target genes for known and potential new miRNAsidentified in this study using the genome of Vitis vinifera asa reference Most of the target genes for conserved miRNAfamilies predicted in jute have already been confirmed inmodel plants as target genes are commonly conserved [7880] miR156157-Squamosa promoter-binding protein [86]


miR166-Homeodomain Leucine Zipper protein III (HD-ZIP III) [87] miR167-auxin response factor (ARF) [88]miR164-NAC domain protein [89] miR172-transcriptionfactor APETALA2 [90] miR159-MYB transcription factor[91] miR171-GRAS family transcription factor [92] miR394-F-box family protein [93] and miR395-ATP sulfurylase [94]well characterized miRNA-target pairs in other plants havebeen found in jute However a number of widely studiedmiRNA-target pairs such as miR398-copper superoxide dis-mutase [95] miR399-E2 ubiquitin conjugating protein [96]and mir162-Dicer-like 1(DCL1) [97] were not found in thisstudy This could possibly be due to the fact that the jutegenome sequence is not available to be used as a refer-ence However conserved miRNAs with their nonconservedtargets including miR167-peroxidase29 miR396-eukaryotictranslation initiation factor 2c miR168-NAC domain con-taining protein miR164-growth regulating factor 1 miR390-AP domain containing transcription factor miR160-MYBtranscription factor and miR393-GTP-binding protein alphasubunit were also found to be present in jute allowingpresumption of nonconserved targets for conserved miR-NAs Highest number of target genes were identified formiR397 which is laccase a well-studied enzyme encodedby multigene families in poplar Arabidopsis rice and Liri-odendron tulipifera [98] reported to be involved in ligninbiosynthesis of plants [99ndash101] High lignin content of jutefibre limits its use in making fine fabrics [102] Toughnessof this biopolymer also poses a major obstacle to pulpingforage digestibility and biofuel production [103] It has beenreported that transgenic P trichocarpa plants overexpressingPtr-miR397a result in a reduction of Klason lignin content[104] supporting the idea that use of miR397 would be anattractivemeans for reducing lignin-related problems Futureexperiments including in-depth studies of miR397-laccasepair may help in producing quality products from jute

5 Conclusion

This is the first report on jute miRNA identification This setof experimentations for identification of miRNAs and theirpotential targets can initiate further study on understandingthe mechanisms of regulation of jute miRNA

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper

Authorsrsquo Contribution

Md Tariqul Islam and Ahlan Sabah Ferdous contributedequally

Acknowledgments

The authors thank the Ministry of Science and TechnologyGovernment of Bangladesh forfunding this project andMd Moniruzzaman from LalTeer Livestock for shipment

of samples for sequencing The authors acknowledge ArifMohammad Tonmoy for his help and also appreciate thetechnical help fromMd Kamal Hossain

References

[1] J Jiang Y Yang and J Cao ldquoIdentification of microRNAspotentially involved in male sterility of Brassica campestrisssp chinensis using microRNA array and quantitative RT-PCRassaysrdquo Cellular and Molecular Biology Letters vol 18 no 3 pp416ndash432 2013

[2] F Xie C N Stewart F A Taki Q He H Liu and B ZhangldquoHigh-throughput deep sequencing shows that microRNAsplay important roles in switchgrass responses to drought andsalinity stressrdquo Plant Biotechnology Journal vol 12 no 3 pp354ndash366 2014

[3] B Khraiwesh G Pugalenthi and N V Fedoroff ldquoIdentificationand analysis of red sea mangrove (Avicennia marina) microR-NAs by high-throughput sequencing and their association withstress responsesrdquo PLoS ONE vol 8 no 4 Article ID e607742013

[4] B J Reinhart E GWeinstein MW Rhoades B Bartel and DP Bartel ldquoMicroRNAs in plantsrdquo Genes amp Development vol 16no 13 pp 1616ndash1626 2002

[5] S M Hammond E Bernstein D Beach and G J HannonldquoAn RNA-directed nuclease mediates post-transcriptional genesilencing in Drosophila cellsrdquo Nature vol 404 no 6775 pp293ndash296 2000

[6] A Djikeng H Shi C Tschudi and E Ullu ldquoRNA interferencein Trypanosoma brucei cloning of small interfering RNAs pro-vides evidence for retroposon-derived 24-26-nucleotide RNAsrdquoRNA vol 7 no 11 pp 1522ndash1530 2001

[7] A A Aravin G J Hannon and J Brennecke ldquoThe Piwi-piRNApathway provides an adaptive defense in the transposon armsracerdquo Science vol 318 no 5851 pp 761ndash764 2007

[8] V N Kim ldquoSorting out small RNAsrdquo Cell vol 133 no 1 pp25ndash26 2008

[9] E Allen Z Xie A M Gustafson and J C CarringtonldquomicroRNA-directed phasing during trans-acting siRNA bio-genesis in plantsrdquo Cell vol 121 no 2 pp 207ndash221 2005

[10] B J Reinhart and D P Bartel ldquoSmall RNAs correspond tocentromere heterochromatic repeatsrdquo Science vol 297 no 5588p 1831 2002

[11] D V Dugas and B Bartel ldquoMicroRNA regulation of geneexpression in plantsrdquo Current Opinion in Plant Biology vol 7no 5 pp 512ndash520 2004

[12] F R Kulcheski L F V de Oliveira L G Molina et alldquoIdentification of novel soybeanmicroRNAs involved in abioticand biotic stressesrdquo BMC Genomics vol 12 article 307 2011

[13] D P Bartel ldquoMicroRNAs genomics biogenesis mechanismand functionrdquo Cell vol 116 no 2 pp 281ndash297 2004

[14] V Ambros R C Lee A Lavanway P TWilliams andD JewellldquoMicroRNAs and other tiny endogenous RNAs in C elegansrdquoCurrent Biology vol 13 no 10 pp 807ndash818 2003

[15] G Tang B J Reinhart D P Bartel and P D Zamore ldquoAbiochemical framework for RNA silencing in plantsrdquo Genes ampDevelopment vol 17 no 1 pp 49ndash63 2003

[16] X Chen ldquomicroRNA biogenesis and function in plantsrdquo FEBSLetters vol 579 no 26 pp 5923ndash5931 2005

[17] Y Kurihara and YWatanabe ldquoArabidopsis micro-RNA biogen-esis through Dicer-like 1 protein functionsrdquo Proceedings of the


National Academy of Sciences of the United States of Americavol 101 no 34 pp 12753ndash12758 2004

[18] V N Kim ldquoMicroRNA biogenesis coordinated cropping anddicingrdquo Nature Reviews Molecular Cell Biology vol 6 no 5 pp376ndash385 2005

[19] P Brodersen L Sakvarelidze-Achard M Bruun-Rasmussen etal ldquoWidespread translational inhibition by plant miRNAs andsiRNAsrdquo Science vol 320 no 5880 pp 1185ndash1190 2008

[20] L Guo and Z Lu ldquoGlobal expression analysis of miRNA genecluster and family based on isomiRs from deep sequencingdatardquo Computational Biology and Chemistry vol 34 no 3 pp165ndash171 2010

[21] W Park J Li R Song J Messing and X Chen ldquoCARPELFACTORY a Dicer homolog and HEN1 a novel protein actin microRNA metabolism in Arabidopsis thalianardquo CurrentBiology vol 12 no 17 pp 1484ndash1495 2002

[22] A Kozomara and S Griffiths-Jones ldquoMiRBase annotating highconfidence microRNAs using deep sequencing datardquo NucleicAcids Research vol 42 no 1 pp D68ndashD73 2014

[23] H Li Y Dong H Yin et al ldquoCharacterization of the stressassociated microRNAs in Glycine max by deep sequencingrdquoBMC Plant Biology vol 11 article 170 2011

[24] Q-H Zhu A Spriggs L Matthew et al ldquoA diverse set ofmicroRNAs and microRNA-like small RNAs in developing ricegrainsrdquo Genome Research vol 18 no 9 pp 1456ndash1465 2008

[25] W Jin N Li B Zhang et al ldquoIdentification and verificationof microRNA in wheat (Triticum aestivum)rdquo Journal of PlantResearch vol 121 no 3 pp 351ndash355 2008

[26] R L R Pilcher S Moxon N Pakseresht et al ldquoIdentification ofnovel small RNAs in tomato (Solanum lycopersicum)rdquo Plantavol 226 no 3 pp 709ndash717 2007

[27] D Ding L Zhang H Wang Z Liu Z Zhang and Y ZhengldquoDifferential expression of miRNAs in response to salt stress inmaize rootsrdquo Annals of Botany vol 103 no 1 pp 29ndash38 2009

[28] J T Cuperus N Fahlgren and J C Carrington ldquoEvolution andfunctional diversification ofMIRNA genesrdquoThe Plant Cell vol23 no 2 pp 431ndash442 2011

[29] R Rajagopalan H Vaucheret J Trejo and D P Bartel ldquoAdiverse and evolutionarily fluid set of microRNAs in Arabidop-sis thalianardquo Genes amp Development vol 20 no 24 pp 3407ndash3425 2006

[30] J Zhu W Li W Yang L Qi and S Han ldquoIdentificationof microRNAs in Caragana intermedia by high-throughputsequencing and expression analysis of 12 microRNAs and theirtargets under salt stressrdquo Plant Cell Reports vol 32 no 9 pp1339ndash1349 2013

[31] K P McCormick M R Willmann and B C Meyers ldquoExper-imental design preprocessing normalization and differentialexpression analysis of small RNA sequencing experimentsrdquoSilence vol 2 no 1 article 2 2011

[32] R Sunkar X Zhou Y Zheng W Zhang and J-K ZhuldquoIdentification of novel and candidate miRNAs in rice by highthroughput sequencingrdquo BMC Plant Biology vol 8 article 252008

[33] G Szittya S Moxon D M Santos et al ldquoHigh-throughputsequencing of Medicago truncatula short RNAs identifies eightnew miRNA familiesrdquo BMC Genomics vol 9 article 593 2008

[34] V Pantaleo G Szittya S Moxon et al ldquoIdentification ofgrapevine microRNAs and their targets using high-throughputsequencing and degradome analysisrdquoThe Plant Journal vol 62no 6 pp 960ndash976 2010

[35] S Moxon R Jing G Szittya et al ldquoDeep sequencing of tomatoshort RNAs identifies microRNAs targeting genes involved infruit ripeningrdquo Genome Research vol 18 no 10 pp 1602ndash16092008

[36] C Song C Wang C Zhang et al ldquoDeep sequencing discoveryof novel and conserved microRNAs in trifoliate orange (Citrustrifoliata)rdquo BMC Genomics vol 11 no 1 article 431 2010

[37] Q-X Song Y-F Liu X-Y Hu et al ldquoIdentification of miRNAsand their target genes in developing soybean seeds by deepsequencingrdquo BMC Plant Biology vol 11 article 5 2011

[38] C-Z Zhao H Xia T P Frazier et al ldquoDeep sequencingidentifies novel and conserved microRNAs in peanuts (Arachishypogaea L)rdquo BMC Plant Biology vol 10 article 3 2010

[39] D Klevebring N R Street N Fahlgren et al ldquoGenome-wideprofiling of Populus small RNAsrdquoBMCGenomics vol 10 article620 2009

[40] S Paul A Kundu and A Pal ldquoIdentification and expressionprofiling of Vigna mungo microRNAs from leaf small RNAtranscriptome by deep sequencingrdquo Journal of Integrative PlantBiology vol 56 no 1 pp 15ndash23 2014

[41] A Roy A Bandyopadhyay A K Mahapatra et al ldquoEvaluationof genetic diversity in jute (Corchorus species) using STMSISSR and RAPD markersrdquo Plant Breeding vol 125 no 3 pp292ndash297 2006

[42] M K Sinha S Mitra T Ramasubramanian and B S Mahapa-tra ldquoCrop diversification for profitability in jute and allied fibrecropsrdquo Indian Journal of Agronomy vol 54 no 2 pp 221ndash2252009

[43] S Ahmed M D Shafiuddin M S Azam M S Islam AGhosh and H Khan ldquoIdentification and characterization ofjute LTR retrotransposons their abundance heterogeneity andtranscriptional activityrdquo Mobile Genetic Elements vol 1 no 1pp 18ndash28 2011

[44] R Samira M M Moosa M M Alam S I Keka and HKhan ldquolsquoIn silicorsquo analysis of jute SSR library and experimentalverification of assemblyrdquo Plant OMICS vol 3 no 2 pp 57ndash652010

[45] R Schwab J F Palatnik M Riester C Schommer M Schmidand D Weigel ldquoSpecific effects of microRNAs on the planttranscriptomerdquo Developmental Cell vol 8 no 4 pp 517ndash5272005

[46] X Dai and P X Zhao ldquopsRNATarget a plant small RNA targetanalysis serverrdquoNucleic Acids Research vol 39 no 2 ppW155ndashW159 2011

[47] M Ashburner C A Ball J A Blake et al ldquoGene ontology toolfor the unification of biologyrdquoNature Genetics vol 25 no 1 pp25ndash29 2000

[48] M Kanehisa M Araki S Goto et al ldquoKEGG for linkinggenomes to life and the environmentrdquo Nucleic Acids Researchvol 36 no 1 pp D480ndashD484 2008

[49] M Kanehisa S Goto M Hattori et al ldquoFrom genomics tochemical genomics new developments in KEGGrdquoNucleic AcidsResearch vol 34 pp D354ndashD357 2006

[50] E Varkonyi-Gasic R Wu M Wood E F Walton and RP Hellens ldquoProtocol a highly sensitive RT-PCR method fordetection and quantification of microRNAsrdquo Plant Methodsvol 3 no 1 article 12 2007

[51] C Chen D A Ridzon A J Broomer et al ldquoReal-timequantification of microRNAs by stem-loop RT-PCRrdquo NucleicAcids Research vol 33 no 20 p e179 2005


[52] S W Burge J Daub R Eberhardt et al ldquoRfam 110 10 years ofRNA familiesrdquo Nucleic Acids Research vol 41 pp D226ndashD2322012

[53] A Kozomara and S Griffiths-Jones ldquomiRBase integratingmicroRNA annotation and deep-sequencing datardquo NucleicAcids Research vol 39 no 1 Article ID gkq1027 pp D152ndashD1572011

[54] B CMeyersM J Axtell B Bartel et al ldquoCriteria for annotationof plant microRNAsrdquo The Plant Cell vol 20 no 12 pp 3186ndash3190 2008

[55] K Okamura M D Phillips D M Tyler H Duan Y-T Chouand E C Lai ldquoThe regulatory activity of microRNAlowast specieshas substantial influence on microRNA and 31015840UTR evolutionrdquoNature Structural amp Molecular Biology vol 15 no 4 pp 354ndash363 2008

[56] S Yang JrM D Phillips D Betel et al ldquoWidespread regulatoryactivity of vertebrate microRNAlowast speciesrdquo RNA vol 17 no 2pp 312ndash326 2011

[57] P Nelson M Kiriakidou A Sharma E Maniataki and ZMourelatos ldquoThe microRNA world small is mightyrdquo Trends inBiochemical Sciences vol 28 no 10 pp 534ndash540 2003

[58] M Zuker ldquoMfold web server for nucleic acid folding andhybridization predictionrdquoNucleic Acids Research vol 31 no 13pp 3406ndash3415 2003

[59] D Li L Wang X Liu et al ldquoDeep sequencing of maize smallRNAs reveals a diverse set of microRNA in dry and imbibedseedsrdquo PLoS ONE vol 8 no 1 Article ID e55107 2013

[60] W Mao Z Li X Xia Y Li and J Yu ldquoA combined approachof high-throughput sequencing and degradome analysis revealstissue specific expression of microRNAs and their targets incucumberrdquo PLoS ONE vol 7 no 3 Article ID e33040 2012

[61] Q-Y Zeng C-Y Yang Q-B Ma X-P Li W-W Dong and HNian ldquoIdentification of wild soybean miRNAs and their targetgenes responsive to aluminum stressrdquo BMC Plant Biology vol12 article 182 2012

[62] M Y Xu Y Dong Q X Zhang et al ldquoIdentification of miRNAsand their targets from Brassica napus by high-throughputsequencing and degradome analysisrdquo BMC Genomics vol 13no 1 article 421 2012

[63] N Fahlgren M D Howell K D Kasschau et al ldquoHigh-throughput sequencing ofArabidopsismicroRNAs evidence forfrequent birth and death of MIRNA genesrdquo PLoS ONE vol 2no 2 article e219 2007

[64] Y Yao G Guo Z Ni et al ldquoCloning and characterizationof microRNAs from wheat (Triticum aestivum L)rdquo GenomeBiology vol 8 no 6 article R96 2007

[65] X-J Wang J L Reyes N-H Chua and T Gaasterland ldquoPre-diction and identification of Arabidopsis thaliana microRNAsand their mRNA targetsrdquo Genome Biology vol 5 no 9 p R652004

[66] C Llave K D Kasschau M A Rector and J C CarringtonldquoEndogenous and silencing-associated small RNAs in plantsrdquoThe Plant Cell vol 14 no 7 pp 1605ndash1619 2002

[67] D M OrsquoMalley R Whetten W Bao C-L Chen and R RSederoff ldquoThe role of of laccase in lignificationrdquo The PlantJournal vol 4 no 5 pp 751ndash757 1993

[68] G van Ooijen G Mayr M M A Kasiem M Albrecht B J CCornelissen and F L W Takken ldquoStructure-function analysisof the NB-ARC domain of plant disease resistance proteinsrdquoJournal of Experimental Botany vol 59 no 6 pp 1383ndash13972008

[69] Gene Ontology Consortium ldquoThe Gene Ontology (GO)database and informatics resourcerdquo Nucleic Acids Research vol32 pp D258ndashD261 2004

[70] E Altermann and T R Klaenhammer ldquoPathwayVoyager path-way mapping using the Kyoto Encyclopedia of Genes andGenomes (KEGG) databaserdquo BMC Genomics vol 6 article 602005

[71] V Benes and M Castoldi ldquoExpression profiling of microRNAusing real-time quantitative PCR how to use it and what isavailablerdquoMethods vol 50 no 4 pp 244ndash249 2010

[72] K Etebari and S Asgari ldquoAccuracy of microRNA discoverypipelines in non-model organisms using closely related speciesgenomesrdquo PLoS ONE vol 9 no 1 Article ID e84747 2014

[73] J-Z Zhang X-Y Ai W-W Guo S-A Peng X-X Deng andC-G Hu ldquoIdentification of miRNAs and their target genesusing deep sequencing and degradome analysis in trifoliateorange [Poncirus trifoliate (L) Raf]rdquo Molecular Biotechnologyvol 51 no 1 pp 44ndash57 2012

[74] M W Jones-Rhoades D P Bartel and B Bartel ldquoMicroRNAsand their regulatory roles in plantsrdquo Annual Review of PlantBiology vol 57 pp 19ndash53 2006

[75] G Wu and R S Poethig ldquoTemporal regulation of shootdevelopment in Arabidopsis thaliana by miRr156 and its targetSPL3rdquo Development vol 133 no 18 pp 3539ndash3547 2006

[76] M J Axtell and D P Bartel ldquoAntiquity of microRNAs and theirtargets in land plantsrdquo The Plant Cell vol 17 no 6 pp 1658ndash1673 2005

[77] E Allen Z Xie A M Gustafson G-H Sung J W Spataforaand J C Carrington ldquoEvolution ofmicroRNAgenes by invertedduplication of target gene sequences in Arabidopsis thalianardquoNature Genetics vol 36 no 12 pp 1282ndash1290 2004

[78] M J Axtell and J L Bowman ldquoEvolution of plant microRNAsand their targetsrdquo Trends in Plant Science vol 13 no 7 pp 343ndash349 2008

[79] G Martınez J Forment C Llave V Pallas and G GomezldquoHigh-throughput sequencing characterization and detectionof new and conserved cucumber miRNAsrdquo PLoS ONE vol 6no 5 Article ID e19523 2011

[80] E A Glazov P A Cottee W C Barris R J Moore B PDalrymple and M L Tizard ldquoA microRNA catalog of thedeveloping chicken embryo identified by a deep sequencingapproachrdquo Genome Research vol 18 no 6 pp 957ndash964 2008

[81] S-J Kou X-M Wu Z Liu Y-L Liu Q Xu and W-W GuoldquoSelection and validation of suitable reference genes for miRNAexpression normalization by quantitative RT-PCR in citrussomatic embryogenic and adult tissuesrdquo Plant Cell Reports vol31 no 12 pp 2151ndash2163 2012

[82] Y Ao Y Wang L Chen T Wang H Yu and Z ZhangldquoIdentification and comparative profiling of microRNAs inwild-type Xanthoceras sorbifolia and its double flower mutantrdquoGenes amp Genomics vol 34 no 5 pp 561ndash568 2012

[83] F Vazquez T Blevins J Ailhas T Boller and F Meins Jr ldquoEvo-lution of Arabidopsis MIR genes generates novel microRNAclassesrdquo Nucleic Acids Research vol 36 no 20 pp 6429ndash64382008

[84] A Git H Dvinge M Salmon-Divon et al ldquoSystematic com-parison of microarray profiling real-time PCR and next-generation sequencing technologies for measuring differentialmicroRNA expressionrdquo RNA vol 16 no 5 pp 991ndash1006 2010

[85] S Tam R de Borja M-S Tsao and J D McPherson ldquoRobustglobal microRNA expression profiling using next-generation


sequencing technologiesrdquo Laboratory Investigation vol 94 no3 pp 350ndash358 2014

[86] K Xie C Wu and L Xiong ldquoGenomic organization differ-ential expression and interaction of SQUAMOSA promoter-binding-like transcription factors and microRNA156 in ricerdquoPlant Physiology vol 142 no 1 pp 280ndash293 2006

[87] H Zhu F Hu R Wang et al ldquoArabidopsis argonaute10 specif-ically sequesters miR166165 to regulate shoot apical meristemdevelopmentrdquo Cell vol 145 no 2 pp 242ndash256 2011

[88] M-F Wu Q Tian and J W Reed ldquoArabidopis microRNA 167controls patterns of ARF6 and ARF8 expression and regulatesboth female and male reproductionrdquo Development vol 133 no21 pp 4211ndash4218 2006

[89] H K Jin R W Hye J Kim et al ldquoTrifurcate feed-forwardregulation of age-dependent cell death involving miR164 inArabidopsisrdquo Science vol 323 no 5917 pp 1053ndash1057 2009

[90] M J Aukerman and H Sakai ldquoRegulation of flowering timeand floral organ identity by a microRNA and its APETALA2-like target genesrdquo The Plant Cell vol 15 no 11 pp 2730ndash27412003

[91] J L Reyes and N-H Chua ldquoABA induction of miR159 controlstranscript levels of two MYB factors during Arabidopsis seedgerminationrdquo The Plant Journal vol 49 no 4 pp 592ndash6062007

[92] B Zhang X Pan G P Cobb and T A Anderson ldquoPlantmicroRNA a small regulatory molecule with big impactrdquoDevelopmental Biology vol 289 no 1 pp 3ndash16 2006

[93] J B Song S Q Huang T Dalmay and Z M Yang ldquoRegulationof leaf morphology by MicroRNA394 and its target LEAFCURLING RESPONSIVENESSrdquo Plant and Cell Physiology vol53 no 7 pp 1283ndash1294 2012

[94] C G Kawashima C AMatthewman S Huang et al ldquoInterplayof SLIM1 andmiR395 in the regulation of sulfate assimilation inArabidopsisrdquo Plant Journal vol 66 no 5 pp 863ndash876 2011

[95] D V Dugas and B Bartel ldquoSucrose induction of ArabidopsismiR398 represses two CuZn superoxide dismutasesrdquo PlantMolecular Biology vol 67 no 4 pp 403ndash417 2008

[96] K Aung S-I Lin C-C Wu Y-T Huang C-L Su and T-J Chiou ldquopho2 a phosphate overaccumulator is caused bya nonsense mutation in a microRNA399 target generdquo PlantPhysiology vol 141 no 3 pp 1000ndash1011 2006

[97] Z Xie K D Kasschau and J C Carrington ldquoNegative feedbackregulation of Dicer-Like1 in Arabidopsis by microRNA-guidedmRNAdegradationrdquoCurrent Biology vol 13 no 9 pp 784ndash7892003

[98] P Ranocha M Chabannes S Chamayou et al ldquoLaccase down-regulation causes alterations in phenolic metabolism and cellwall structure in poplarrdquoPlant Physiology vol 129 no 1 pp 145ndash155 2002

[99] A Driouich A-C Laine B Vian and L Paye ldquoCharacteriza-tion and localization of laccase forms in stem and cell culturesof sycamorerdquoThe Plant Journal vol 2 no 1 pp 13ndash24 1992

[100] R Sterjiades J F D Dean and K-E L Eriksson ldquoLaccase fromsycamore maple (Acer pseudoplatanus) polymerizes monolig-nolsrdquo Plant Physiology vol 99 no 3 pp 1162ndash1168 1992

[101] W Bao D M Orsquomalley R Whetten and R R Sederoff ldquoAlaccase associated with lignification in loblolly pine xylemrdquoScience vol 260 no 5108 pp 672ndash674 1993

[102] G Sengupta and P Palit ldquoCharacterization of a lignifiedsecondary phloem fibre-deficient mutant of jute (Corchoruscapsularis)rdquo Annals of Botany vol 93 no 2 pp 211ndash220 2004

[103] F Chen and R A Dixon ldquoLignin modification improves fer-mentable sugar yields for biofuel productionrdquo Nature Biotech-nology vol 25 no 7 pp 759ndash761 2007

[104] S Lu Q Li H Wei et al ldquoPtr-miR397a is a negative regulatorof laccase genes affecting lignin content in Populus trichocarpardquoProceedings of the National Academy of Sciences of the UnitedStates of America vol 110 no 26 pp 10848ndash10853 2013

Submit your manuscripts athttpwwwhindawicom

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Anatomy Research International

PeptidesInternational Journal of


Hindawi Publishing Corporation httpwwwhindawicom

International Journal of

Volume 2014

Zoology


Molecular Biology International

GenomicsInternational Journal of


The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014


BioinformaticsAdvances in

Marine BiologyJournal of



Signal TransductionJournal of


BioMed Research International

Evolutionary BiologyInternational Journal of



Biochemistry Research International

ArchaeaHindawi Publishing Corporationhttpwwwhindawicom Volume 2014


Genetics Research International


Advances in

Virolog y

Hindawi Publishing Corporationhttpwwwhindawicom

Nucleic AcidsJournal of

Volume 2014

Stem CellsInternational



Enzyme Research



Microbiology


Most miRNAs are transcribed by RNA polymerase II whichfolds into a stable usually imperfect hairpin structure [13]pri-miRNA transcript is cleaved to pre-miRNA by RNaseIII-type Dicer-like 1 (DCL1) protein [15] to produce a distinctivesim21 nt double-stranded RNA This duplex is exported intothe cytoplasm by HASTY and methylated at the 31015840 end byHEN1 [16] A cytoplasmic helicase unwinds the translocatedduplex into a single-strandedmaturemiRNA which is finallyincorporated into RNA-induced silencing complex (RISC)[5 17 18] AmaturemiRNA sequence can range from 19 to 24nucleotides (nt) in length and act as a regulatory molecule inposttranscriptional gene silencing by base pairing with targetmRNAs [12] Within the RISC complex miRNAs functionin the direct cleavage of 31015840 untranslated region of protein-coding genes or translational repression depending on itsperfect or imperfect match with the targets [19] The samemature miRNA can also be present as several length variantsthese populations of miRNA variants are called isomiRNAswhich are isoforms of microRNAs caused by an imprecise oralternative cleavage of Dicer during pre-miRNA processing[20]

Several miRNAs have been identified in plants and theyhave been characterized in a wide variety of metabolic andbiological processes with important functions [12] The firstplant miRNAs were described in Arabidopsis thaliana [21]currently the latest miRBase release (v20 June 2013) contains24521microRNA loci from 206 species processed to produce30424 mature microRNA products [22] Earlier miRNAshave been identified through either bioinformatics analysis orsequencing [23] various methods have been used to identifymiRNAs in rice [24] wheat [25] tomato [26] andmaize [27]Besides the miRNAs that are highly conserved in differentspecies there are species-specific miRNAs originating fromrecently evolved miRNA genes [28 29] The expression ofthese species-specific miRNAs is often low and can thereforebe difficult to detect by traditional methods [30] In recenttimes high-throughput sequencing platforms are showingsignificant promise for small RNA discovery and genome-wide transcriptome analysis at single-base pair resolution[23 31] Sequencing techniques such as the Solexa PlatformSOLiD and 454Technology aswell as othermassively parallelsequencing strategies have been successfully applied in orderto identify miRNAs in many plant species such as rice [32]alfalfa [33] grape [34] tomato [35] orange [36] soybean [37]peanut [38] poplar [39] and black gram [40] In comparisonwith microarray deep sequencing has several advantagesthe major one being its application in comprehensive iden-tification and profiling of small previously unknown RNApopulations [23] Nevertheless analyses of these data are notperfect especially in the absence of native genome sequence[40]

Jute (Corchorus olitorius and Corchorus capsularis) is abast fibre like flax and hemp Cultivation of this environmen-tally friendly as well as the most affordable fibre producingplant is concentrated around the Ganges Delta region ofBangladesh and India where the warm wet climate duringthe monsoon season provides ideal growing conditions Interms of usage production and global requirement jute issecond only to cotton [41] Jute plants are easy to grow have

a high yield per acre and unlike cotton have little need forpesticides and fertilizers They are also known to enrich thesoil [42] As these plants grow fast they are often used incrop rotation The leaves and roots left after harvest enrichthe soil with micronutrients maintaining soil fertility Whenused as a geotextile it puts nutrients back in the soil whenit decomposes This rain-fed crop during its growth helps toclean the air by assimilating three times more CO

2than an

average tree converting the CO2into oxygen

Despite its great agronomic importance research on juteat the molecular level is insignificant [43] Genome sequenceof jute is not available in the public database So far only 1210sequences are found in the GenBank [43] with no depositsof any miRNA sequences in miRBase database Within thiscontext the current study has employed the deep sequencingstrategy in an attempt to effectively identify conserved andnovel jute miRNAs Quantitative real-time PCR (qRT-PCR)has been performed to determine the expression of thesemiRNAs For mapping the identified miRNAs genome ofVitis vinifera was used as reference because of sequencehomology of this species with jute [44]

2 Methods and Materials

21 Plant Materials Preparation and Small RNA Library Con-struction Seeds of farmer popular O-9897 variety of tossajute (Corchorus olitorius) were collected from BangladeshJute Research Institute (BJRI) They were surface sterilizedwith 70 ethanol subsequently washed in distilledwater andallowed to germinate on sterile petri dishes containing 3MMmoist filter paper (Whatman) at 30 plusmn 1∘C and 65 relativehumidity Seeds were allowed to grow for 4 days underthe specified conditions On the fourth day of germinationseedlings were collected and immediately snap-frozen inliquid nitrogen and stored at minus80∘C for subsequent use

RNA was isolated from collected seedlings using TRI-zol reagent (Invitrogen USA) by following the manufac-turerrsquos instructions Later RNA samples were sent to Bei-jing Genome Institute (BGI Shenzhen China) for deepsequencing of small RNAby IlluminaHiseq high-throughputsequencing platform In short the sRNAs pool of 18ndash30 nt inlength were fractionated from total RNA After ligation with51015840 and 31015840 adaptors the short RNAs so obtained were reverse-transcribed to cDNA according to the Illumina protocolTheresulting small RNA library was then sequenced followingSBS method (sequencing by synthesis) by Illumina Hiseqhigh-throughput sequencing

22 Prediction of Known miRNA in Jute Raw data obtainedfrom Illumina Hiseq high-throughput sequencing was at firstfiltered by removing contaminants which include low qualityreads reads with 51015840 primer contaminants reads without 31015840primer reads without the insert tag reads with poly A andreads shorter than 18 nt After cleaning the final reads werethen used for further analyses Clean reads fully matchingother RNAs including mRNA rRNA tRNA snRNA













01020304050

15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33

Freq

uenc

e (

)

Length (nt)


3 Results








ble2miRNAs

from

each

family

with

theh

ighestfre

quency

injutewith

theirh

omologsinotherp

lants

Jutefamily

JutemiRNA

Leng

thof

smallR

NA

sequ

ence

Cou

ntof

small

RNA

sequ

ences

SmallR

NAsequ

ence

Hom

olog

(besto

ne)

Matches

number

Mism

atches

number

Gaps

number

Con

served

miR156

col-m

iR157a

21553160

9UUGAC

AGAAG

AUAG

AGAG

CAC

ath-miR157a

210

0col-m

iR156a

201724997

UGAC

AGAAG

AGAG

UGAG

CAC

ath-miR156a

200

0miR166

col-m

iR166a

21215636

UCG

GAC

CAGGCU

UCA

UUCC

CCath-miR166a

210

0miR167

col-m

iR167h

22154973

UGAAG

CUGCC

AGCA

UGAU

CUUA

mdm

-miR167h

220

0miR396

col-m

iR396b

-3p

2118695

GCU

CAAG

AAAG

CUGUGGGAG

Agm

a-miR396b

-3p

210

0miR168

col-m

iR168a

2116590

UCG

CUUGGUGCA

GGUCG

GGAA

ath-miR168a

210

0miR164

col-m

iR164a

217491

UGGAG

AAG

CAGGGCA

CGUGCA

ath-miR164a

210

0miR169

col-m

iR169b

212528

CAGCC

AAG

GAU

GAC

UUGCC

GG

ath-miR169b

210

0miR390

col-m

iR390a

212952

AAG

CUCA

GGAG

GGAU

AGCG

CCath-miR390a

210

0mir160

col-m

iR160a-3p

211448

GCG

UAUGAG

GAG

CCAAG

CAUA

gma-miR160a-3p

210

0miR159

col-m

iR159a

21484

UUUGGAU

UGAAG

GGAG

CUCU

Aath-miR159a

210

0miR171

col-m

iR171b

21558

UGAU

UGAG

CCGUGCC

AAU

AUC

osa-miR171b

210

0miR403

col-m

iR403

21282

UUA

GAU

UCA

CGCA

CAAAC

UCG

ath-miR403

210

0miR398

col-m

iR398

21262

GGAG

CGAC

AUGAG

AUCA

CAUG

hbr-miR398

201

0miR482

col-m

iR482b

222206

UCU

UACC

UACU

CCAC

CCAU

GCC

ghr-miR482b

211

0miR40

8col-m

iR40

821

129

AUGCA

CUGCC

UCU

UCC

CUGGC

ath-miR40

821

00

miR397

col-m

iR397a

21106

UCA

UUGAG

UGCA

GCG

UUGAU

Gath-miR397a

210

0miIR

530

col-m

iR530a

2181

UGCA

UUUGCA

CCUGCA

CCUUU

csi-m

iR530a

201

0miR393

col-m

iR393b-3p

2161

AUCA

UGCG

AUCC

CUUCG

GAAU

stu-m

iR393-3p

201

0miR394

col-m

iR394a

2016

UUGGCA

UUCU

GUCC

ACCU

CCath-miR394a

200

0miR827

col-m

iR827a

2122

UUA

GAU

GAC

CAUCA

ACAAAC

Agh

r-miR827a

210

0miR477

col-m

iR477i

212

ACUCU

CCCU

CAAG

GGCU

UCC

Gmes-m

iR477i

210

0miR2111

col-m

iR2111a

2115

UAAU

CUGCA

UCC

UGAG

GUUUG

ptc-miR2111a

210

0miR172

col-m

iR172a

211480

AGAAU

CUUGAU

GAU

GCU

GCA

Uath-miR172a

210

0Non

conserved

miR2275

col-m

iR2275a-3p

2254

UUA

AGUUUUCU

CCAAU

AUCU

CAzm

a-miR2275a-3p

201

2miR2118

col-m

iR2118a-3p

2236

UUGCC

GAAU

CCGCC

CAUUCC

GU

gma-miR2118a-3p

192

1miR528

col-m

iR528-5p

2117

UGGAAG

GGGCA

UGCA

GAG

GAG

osa-miR528-5p

210

0miR1310

col-m

iR1310

2169

AGGCA

UCG

GGGGCG

CAAC

GCC

han-miR1310

210

1miR7696

col-m

iR7696a-3p

216

UCU

GAAU

CAUGAG

AAC

UUGAG

mtr-

miR7696a-3p

191

2miR6224

col-m

iR6224a-3p

214

CUGAU

AAU

AUAG

GAC

GGAG

GG

sbi-m

iR6224a-3p

191

2miR64

62col-m

iR64

62c-5p

2128

AAG

GGAC

AAAAAG

GCU

AUAAG

ptc-miR64

62c-5p

200

3miR4243

col-m

iR4243

213

UUGAAC

UUGUA

CGAU

UUCG

ACath-miR4243

191

2miR5745

col-m

iR5745b

2116

UUUA

AUUUA

UAUA

CAUCU

CAC

mtr-

miR5745b

200

2miR902

col-m

iR902j-5p

241

AUAU

GUUA

CGCA

GAU

UCU

UCA

UUU

ppt-m

iR902j-5p

210

3miR2873

col-m

iR2873b

2110

UUGUGGCU

GAG

AUUUGGUA

UG

osa-miR2873b

191

2miR2950

col-m

iR2950

212465

UGGUGUGCA

GGGGGUGGAAU

Agh

r-miR2950

210

0miR5067

col-m

iR5049c

243837

GGAC

AAU

UAUUGUGGGAC

GGAG

GG

hvu-miR5049c

212

1miR818

col-m

iR1436

23920

AGAU

AAU

AUGGGAC

GGAG

GGAG

Uosa-miR1436

201

2miR44

14col-m

iR44

14a-3p

2111

AUCC

AAC

GAU

GCA

GGAG

CUGC

mtr-

miR44

14a-3p

201

0


Table2Con

tinued

Jutefamily

JutemiRNA

Leng

thof

smallR

NA

sequ

ence

Cou

ntof

small

RNA

sequ

ences

SmallR

NAsequ

ence

Hom

olog

(besto

ne)

Matches

number

Mism

atches

number

Gaps

number

miR1509

col-m

iR7122a

22488

UUGGAC

AGAG

AAAU

CACG

GUCG

mdm

-miR7122a

202

0miR158

col-m

iR158a

2034

UCC

CAAAU

GUA

GAC

AAAG

CAath-miR158a

200

0miR161

col-m

iR1612

212

UCA

AUGCA

UUGAAAG

UGAC

UAath-miR1612

210

0Und

efined

col-m

iR5162

244

AAAAU

GAC

CAAAAU

ACCC

CUAAAU

osa-miR5162

221

2Und

efined

col-m

iR6248

201

UAAU

UGAG

GAU

GGAG

GGAG

Uosa-miR6248

182

1Und

efined

col-m

iR7767-3p

221

UAGGAU

CAGGCA

GCU

UGAAG

GU

bdi-m

iR7767-3p

192

1Und

efined

col-m

iR5997

211

UGAAAC

UCA

AGUA

GCU

AAAAG

ath-miR5997

200

2Und

efined

col-m

iR5057

231

AAAC

UUUCA

GAU

GCA

UUUUGAC

Abd

i-miR5057

201

2Und

efined

col-m

iR6172

211

UGAG

ACCU

GUUUA

AGUUA

GAA

hbr-miR6172

191

2Und

efined

col-m

iR6279

203

UAAC

AAG

AAU

UCC

AGAC

ACA

ppe-miR6279

182

1Und

efined

col-m

iR6220-3p

231

AGAC

UUA

UAAU

UUGGGAC

GGAG

Asbi-m

iR6220-3p

212

1Und

efined

col-m

iR64

4321

1UGUA

UGAU

CAUGAU

GCU

GGAG

ptc-miR64

4319

12

Und

efined

col-m

iR156h

2017

UGAC

AGAAG

AGAG

AGAG

CAU

vvi-m

iR156h

200

0Und

efined

col-m

iR3954

22868222

UUGGAC

AGAG

UAAU

CACG

GUCG

csi-m

iR3954

192

1Und

efined

col-m

iR167i

201

UCA

UGCU

GGCA

GCU

UCA

CUU

gma-miR167i

200

3Und

efined

col-m

iR6300

1944

00GUCG

UUGUA

GUA

UAGUGGU

gma-miR6300

180

1Und

efined

col-m

iR169p

216

UAGCC

AAG

GAC

AAC

UUGCC

GG

osa-miR169p

210

1Und

efined

col-m

iR894

205406

GUUUCA

CGUCG

GGUUCA

CCA

ppt-m

iR894

190

2Und

efined

col-m

iR472a

22218

UUUUCC

CUAC

UCC

UCC

CAUCC

Cptc-miR472a

211

0Und

efined

col-m

iR5059

21212

CGGUCC

UGGGCA

GCA

ACAC

CAbd

i-miR5059

191

1Und

efined

col-m

iR2916

22312

GGGGGCU

CGAAG

ACGAU

CAGAU

peu-miR2916

202

1Und

efined

col-m

iR5072

2190

CGUUCC

CCAG

CGGAG

UCG

CCA

osa-miR5072

210

1Und

efined

col-m

iR477h

224

ACUCU

CCCU

CAAG

GGCU

UCC

AGmes-m

iR477h

210

1Und

efined

col-m

iR6478

21164

CCGAC

CUUA

GCU

CAGUUGGUA

ptc-miR6478

201

0Und

efined

col-m

iR5205b

24306

CUUA

UAAU

UAGGGAC

AGAG

GGAG

Umtr-

miR5205b

231

0Und

efined

col-m

iR7505

2131

UUCA

GAAAC

CAUCC

CCUCC

UU

ghr-miR7505

201

0Und

efined

col-m

iR5077

20378

GAU

UCA

CGUCG

GGUUCA

CCA

osa-miR5077

181

1Und

efined

col-m

iR5054

20904

GUUCC

CCAC

AGUCG

GCG

CCA

bdi-m

iR5054

171

2Und

efined

col-m

iR845c

2428

AGGCU

CUGAU

ACCA

AUUGAC

GUA

Gvvi-m

iR845c

210

3Und

efined

col-m

iR916

2228

CGAAG

GUCG

UCG

GUUCG

AAU

CCcre-miR916

192

1Und

efined

col-m

iR161-5

p1

2111

UUGAAAG

UGAC

UACA

UCG

GGG

aly-miR161-5

p1

210

0Und

efined

col-m

iR1863

2456

AGCU

CUGAU

ACCA

UGUUA

AGCA

UC

pab-miR1863

211

2Und

efined

col-m

iR7490

2441

AGUCU

GAU

AAAC

UCC

ACUGAC

GGU

ghr-miR7490

221

2Und

efined

col-m

iR3946

2113

UUGAG

AGAAG

AGAG

AGAG

CAC

csi-m

iR3946

210

3Und

efined

col-m

iR7728-5p

195

UUCG

GAU

UGAG

UGGAU

UUU

bdi-m

iR7728-5p

181

2Und

efined

col-m

iR1862f

211

AAG

GGGUUGGUUUA

CUUUUGG

osa-miR1862f

182

1Und

efined

col-m

iR6171

2111

ACUA

UGGAU

UGCU

GAAG

GUUU

hbr-miR6171

191

2Und

efined

col-m

iR5021

2131

UAAG

AAG

AAU

AAG

AAG

AAU

AA

ath-miR5021

182

1Und

efined

col-m

iR5244

216

UAUCU

GAU

GAU

GAU

UGUUGGU

mtr-

miR5244

192

0Und

efined

col-m

iR5049-3p

2330

AAG

UAAU

AUGGAAC

GGAG

GGAG

Ubd

i-miR5049-3p

212

1Und

efined

col-m

iR5629

2341

UUA

GGGUA

GUUA

ACGGGUA

GUUA

ath-miR5629

211

1





miR827miR818

miR7696

miR6462

miR6224

miR5745

miR530

miR528

miR5067

miR482

miR477

miR4414

miR4243

miR408

miR403

miR398miR397


miR2950miR2873

miR2275

miR2118

miR2111

miR172

miR171

miR169

miR168

miR167

miR166

miR164

miR161

miR160

miR159

miR158miR156







miRNA lengthMFE






col-miRN7 6







05

1015202530

Num

ber o

f fam

ilies

miR156

miR166

miR169

miR171

miR396

miR159

miR172

miR167

miR160

miR164

miR482

miR393

miR390

miR408

miR168

miR398

miR397

miR530

miR394

miR827

miR477

miR2111

miR403


05

10152025303540

Biol

ogic

al ad

hesio

nBi

olog

ical

regu

latio

nC

ellu

lar c

ompo

nent

org

aniz

atio

n or

bio

gene

sisC

ellu

lar p

roce

ssD

evelo

pmen

tal p

roce

ssEs

tabl

ishm

ent o

f loc

aliz

atio

nG

row

thLo

caliz

atio

nM

etab

olic

pro

cess

Mul

tiorg

anism

pro

cess

Mul

ticel

lula

r org

anism

al p

roce

ssRe

gula

tion

of b

iolo

gica

l pro

cess

Repr

oduc

tion

Repr

oduc

tive p

roce

ssRe

spon

se to

stim

ulus

Sign

alin

gSi

ngle

-org

anism

pro

cess

Cel

lC

ell p

art

Mem

bran

eM

embr

ane p

art

Org

anel

leA

ntio

xida

nt ac

tivity

Bind

ing

Cata

lytic

activ

ityN

ucle

ic ac

id b

indi

ng tr

ansc

riptio

n fa

ctor

activ

ityTr

ansp

orte

r act

ivity

Num

ber o

f gen

es


functionscomponents




4 Discussion






156 168 159 166 167 171 319 396 397 398 408

sim70bp

1kb+

(a)

N1 N2 N3 N4 N5 N6 N7 N9N8

sim70bp

1kb+

(b)


05

10152025

col-m

iR156

aco

l-miR159

aco

l-miR166

aco

l-miR167

aco

l-miR168

a-5

pco

l-miR171

aco

l-miR319

a-3

pco

l-miR396

a-5

pco

l-miR397

aco

l-miR398

col-m

iR408

aco

l-miR

N1

-5p

col-m

iRN2

-3p

col-m

IRN3

-3p

col-m

iRN4

-3p

col-m

iRN5

-3p

col-m

iRN6

-5p

col-m

iRN7

-5p

col-m

iRN8

-5p

col-m

iRN9

-3p

Log2

frequ

ency












5 Conclusion






Acknowledgments



References





















































































































Volume 2014

Zoology






















Advances in

Virolog y



Volume 2014




Enzyme Research



Microbiology













01020304050

15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33

Freq

uenc

e (

)

Length (nt)


3 Results








ble2miRNAs

from

each

family

with

theh

ighestfre

quency

injutewith

theirh

omologsinotherp

lants

Jutefamily

JutemiRNA

Leng

thof

smallR

NA

sequ

ence

Cou

ntof

small

RNA

sequ

ences

SmallR

NAsequ

ence

Hom

olog

(besto

ne)

Matches

number

Mism

atches

number

Gaps

number

Con

served

miR156

col-m

iR157a

21553160

9UUGAC

AGAAG

AUAG

AGAG

CAC

ath-miR157a

210

0col-m

iR156a

201724997

UGAC

AGAAG

AGAG

UGAG

CAC

ath-miR156a

200

0miR166

col-m

iR166a

21215636

UCG

GAC

CAGGCU

UCA

UUCC

CCath-miR166a

210

0miR167

col-m

iR167h

22154973

UGAAG

CUGCC

AGCA

UGAU

CUUA

mdm

-miR167h

220

0miR396

col-m

iR396b

-3p

2118695

GCU

CAAG

AAAG

CUGUGGGAG

Agm

a-miR396b

-3p

210

0miR168

col-m

iR168a

2116590

UCG

CUUGGUGCA

GGUCG

GGAA

ath-miR168a

210

0miR164

col-m

iR164a

217491

UGGAG

AAG

CAGGGCA

CGUGCA

ath-miR164a

210

0miR169

col-m

iR169b

212528

CAGCC

AAG

GAU

GAC

UUGCC

GG

ath-miR169b

210

0miR390

col-m

iR390a

212952

AAG

CUCA

GGAG

GGAU

AGCG

CCath-miR390a

210

0mir160

col-m

iR160a-3p

211448

GCG

UAUGAG

GAG

CCAAG

CAUA

gma-miR160a-3p

210

0miR159

col-m

iR159a

21484

UUUGGAU

UGAAG

GGAG

CUCU

Aath-miR159a

210

0miR171

col-m

iR171b

21558

UGAU

UGAG

CCGUGCC

AAU

AUC

osa-miR171b

210

0miR403

col-m

iR403

21282

UUA

GAU

UCA

CGCA

CAAAC

UCG

ath-miR403

210

0miR398

col-m

iR398

21262

GGAG

CGAC

AUGAG

AUCA

CAUG

hbr-miR398

201

0miR482

col-m

iR482b

222206

UCU

UACC

UACU

CCAC

CCAU

GCC

ghr-miR482b

211

0miR40

8col-m

iR40

821

129

AUGCA

CUGCC

UCU

UCC

CUGGC

ath-miR40

821

00

miR397

col-m

iR397a

21106

UCA

UUGAG

UGCA

GCG

UUGAU

Gath-miR397a

210

0miIR

530

col-m

iR530a

2181

UGCA

UUUGCA

CCUGCA

CCUUU

csi-m

iR530a

201

0miR393

col-m

iR393b-3p

2161

AUCA

UGCG

AUCC

CUUCG

GAAU

stu-m

iR393-3p

201

0miR394

col-m

iR394a

2016

UUGGCA

UUCU

GUCC

ACCU

CCath-miR394a

200

0miR827

col-m

iR827a

2122

UUA

GAU

GAC

CAUCA

ACAAAC

Agh

r-miR827a

210

0miR477

col-m

iR477i

212

ACUCU

CCCU

CAAG

GGCU

UCC

Gmes-m

iR477i

210

0miR2111

col-m

iR2111a

2115

UAAU

CUGCA

UCC

UGAG

GUUUG

ptc-miR2111a

210

0miR172

col-m

iR172a

211480

AGAAU

CUUGAU

GAU

GCU

GCA

Uath-miR172a

210

0Non

conserved

miR2275

col-m

iR2275a-3p

2254

UUA

AGUUUUCU

CCAAU

AUCU

CAzm

a-miR2275a-3p

201

2miR2118

col-m

iR2118a-3p

2236

UUGCC

GAAU

CCGCC

CAUUCC

GU

gma-miR2118a-3p

192

1miR528

col-m

iR528-5p

2117

UGGAAG

GGGCA

UGCA

GAG

GAG

osa-miR528-5p

210

0miR1310

col-m

iR1310

2169

AGGCA

UCG

GGGGCG

CAAC

GCC

han-miR1310

210

1miR7696

col-m

iR7696a-3p

216

UCU

GAAU

CAUGAG

AAC

UUGAG

mtr-

miR7696a-3p

191

2miR6224

col-m

iR6224a-3p

214

CUGAU

AAU

AUAG

GAC

GGAG

GG

sbi-m

iR6224a-3p

191

2miR64

62col-m

iR64

62c-5p

2128

AAG

GGAC

AAAAAG

GCU

AUAAG

ptc-miR64

62c-5p

200

3miR4243

col-m

iR4243

213

UUGAAC

UUGUA

CGAU

UUCG

ACath-miR4243

191

2miR5745

col-m

iR5745b

2116

UUUA

AUUUA

UAUA

CAUCU

CAC

mtr-

miR5745b

200

2miR902

col-m

iR902j-5p

241

AUAU

GUUA

CGCA

GAU

UCU

UCA

UUU

ppt-m

iR902j-5p

210

3miR2873

col-m

iR2873b

2110

UUGUGGCU

GAG

AUUUGGUA

UG

osa-miR2873b

191

2miR2950

col-m

iR2950

212465

UGGUGUGCA

GGGGGUGGAAU

Agh

r-miR2950

210

0miR5067

col-m

iR5049c

243837

GGAC

AAU

UAUUGUGGGAC

GGAG

GG

hvu-miR5049c

212

1miR818

col-m

iR1436

23920

AGAU

AAU

AUGGGAC

GGAG

GGAG

Uosa-miR1436

201

2miR44

14col-m

iR44

14a-3p

2111

AUCC

AAC

GAU

GCA

GGAG

CUGC

mtr-

miR44

14a-3p

201

0


Table2Con

tinued

Jutefamily

JutemiRNA

Leng

thof

smallR

NA

sequ

ence

Cou

ntof

small

RNA

sequ

ences

SmallR

NAsequ

ence

Hom

olog

(besto

ne)

Matches

number

Mism

atches

number

Gaps

number

miR1509

col-m

iR7122a

22488

UUGGAC

AGAG

AAAU

CACG

GUCG

mdm

-miR7122a

202

0miR158

col-m

iR158a

2034

UCC

CAAAU

GUA

GAC

AAAG

CAath-miR158a

200

0miR161

col-m

iR1612

212

UCA

AUGCA

UUGAAAG

UGAC

UAath-miR1612

210

0Und

efined

col-m

iR5162

244

AAAAU

GAC

CAAAAU

ACCC

CUAAAU

osa-miR5162

221

2Und

efined

col-m

iR6248

201

UAAU

UGAG

GAU

GGAG

GGAG

Uosa-miR6248

182

1Und

efined

col-m

iR7767-3p

221

UAGGAU

CAGGCA

GCU

UGAAG

GU

bdi-m

iR7767-3p

192

1Und

efined

col-m

iR5997

211

UGAAAC

UCA

AGUA

GCU

AAAAG

ath-miR5997

200

2Und

efined

col-m

iR5057

231

AAAC

UUUCA

GAU

GCA

UUUUGAC

Abd

i-miR5057

201

2Und

efined

col-m

iR6172

211

UGAG

ACCU

GUUUA

AGUUA

GAA

hbr-miR6172

191

2Und

efined

col-m

iR6279

203

UAAC

AAG

AAU

UCC

AGAC

ACA

ppe-miR6279

182

1Und

efined

col-m

iR6220-3p

231

AGAC

UUA

UAAU

UUGGGAC

GGAG

Asbi-m

iR6220-3p

212

1Und

efined

col-m

iR64

4321

1UGUA

UGAU

CAUGAU

GCU

GGAG

ptc-miR64

4319

12

Und

efined

col-m

iR156h

2017

UGAC

AGAAG

AGAG

AGAG

CAU

vvi-m

iR156h

200

0Und

efined

col-m

iR3954

22868222

UUGGAC

AGAG

UAAU

CACG

GUCG

csi-m

iR3954

192

1Und

efined

col-m

iR167i

201

UCA

UGCU

GGCA

GCU

UCA

CUU

gma-miR167i

200

3Und

efined

col-m

iR6300

1944

00GUCG

UUGUA

GUA

UAGUGGU

gma-miR6300

180

1Und

efined

col-m

iR169p

216

UAGCC

AAG

GAC

AAC

UUGCC

GG

osa-miR169p

210

1Und

efined

col-m

iR894

205406

GUUUCA

CGUCG

GGUUCA

CCA

ppt-m

iR894

190

2Und

efined

col-m

iR472a

22218

UUUUCC

CUAC

UCC

UCC

CAUCC

Cptc-miR472a

211

0Und

efined

col-m

iR5059

21212

CGGUCC

UGGGCA

GCA

ACAC

CAbd

i-miR5059

191

1Und

efined

col-m

iR2916

22312

GGGGGCU

CGAAG

ACGAU

CAGAU

peu-miR2916

202

1Und

efined

col-m

iR5072

2190

CGUUCC

CCAG

CGGAG

UCG

CCA

osa-miR5072

210

1Und

efined

col-m

iR477h

224

ACUCU

CCCU

CAAG

GGCU

UCC

AGmes-m

iR477h

210

1Und

efined

col-m

iR6478

21164

CCGAC

CUUA

GCU

CAGUUGGUA

ptc-miR6478

201

0Und

efined

col-m

iR5205b

24306

CUUA

UAAU

UAGGGAC

AGAG

GGAG

Umtr-

miR5205b

231

0Und

efined

col-m

iR7505

2131

UUCA

GAAAC

CAUCC

CCUCC

UU

ghr-miR7505

201

0Und

efined

col-m

iR5077

20378

GAU

UCA

CGUCG

GGUUCA

CCA

osa-miR5077

181

1Und

efined

col-m

iR5054

20904

GUUCC

CCAC

AGUCG

GCG

CCA

bdi-m

iR5054

171

2Und

efined

col-m

iR845c

2428

AGGCU

CUGAU

ACCA

AUUGAC

GUA

Gvvi-m

iR845c

210

3Und

efined

col-m

iR916

2228

CGAAG

GUCG

UCG

GUUCG

AAU

CCcre-miR916

192

1Und

efined

col-m

iR161-5

p1

2111

UUGAAAG

UGAC

UACA

UCG

GGG

aly-miR161-5

p1

210

0Und

efined

col-m

iR1863

2456

AGCU

CUGAU

ACCA

UGUUA

AGCA

UC

pab-miR1863

211

2Und

efined

col-m

iR7490

2441

AGUCU

GAU

AAAC

UCC

ACUGAC

GGU

ghr-miR7490

221

2Und

efined

col-m

iR3946

2113

UUGAG

AGAAG

AGAG

AGAG

CAC

csi-m

iR3946

210

3Und

efined

col-m

iR7728-5p

195

UUCG

GAU

UGAG

UGGAU

UUU

bdi-m

iR7728-5p

181

2Und

efined

col-m

iR1862f

211

AAG

GGGUUGGUUUA

CUUUUGG

osa-miR1862f

182

1Und

efined

col-m

iR6171

2111

ACUA

UGGAU

UGCU

GAAG

GUUU

hbr-miR6171

191

2Und

efined

col-m

iR5021

2131

UAAG

AAG

AAU

AAG

AAG

AAU

AA

ath-miR5021

182

1Und

efined

col-m

iR5244

216

UAUCU

GAU

GAU

GAU

UGUUGGU

mtr-

miR5244

192

0Und

efined

col-m

iR5049-3p

2330

AAG

UAAU

AUGGAAC

GGAG

GGAG

Ubd

i-miR5049-3p

212

1Und

efined

col-m

iR5629

2341

UUA

GGGUA

GUUA

ACGGGUA

GUUA

ath-miR5629

211

1





miR827miR818

miR7696

miR6462

miR6224

miR5745

miR530

miR528

miR5067

miR482

miR477

miR4414

miR4243

miR408

miR403

miR398miR397


miR2950miR2873

miR2275

miR2118

miR2111

miR172

miR171

miR169

miR168

miR167

miR166

miR164

miR161

miR160

miR159

miR158miR156







miRNA lengthMFE






col-miRN7 6







05

1015202530

Num

ber o

f fam

ilies

miR156

miR166

miR169

miR171

miR396

miR159

miR172

miR167

miR160

miR164

miR482

miR393

miR390

miR408

miR168

miR398

miR397

miR530

miR394

miR827

miR477

miR2111

miR403


05

10152025303540

Biol

ogic

al ad

hesio

nBi

olog

ical

regu

latio

nC

ellu

lar c

ompo

nent

org

aniz

atio

n or

bio

gene

sisC

ellu

lar p

roce

ssD

evelo

pmen

tal p

roce

ssEs

tabl

ishm

ent o

f loc

aliz

atio

nG

row

thLo

caliz

atio

nM

etab

olic

pro

cess

Mul

tiorg

anism

pro

cess

Mul

ticel

lula

r org

anism

al p

roce

ssRe

gula

tion

of b

iolo

gica

l pro

cess

Repr

oduc

tion

Repr

oduc

tive p

roce

ssRe

spon

se to

stim

ulus

Sign

alin

gSi

ngle

-org

anism

pro

cess

Cel

lC

ell p

art

Mem

bran

eM

embr

ane p

art

Org

anel

leA

ntio

xida

nt ac

tivity

Bind

ing

Cata

lytic

activ

ityN

ucle

ic ac

id b

indi

ng tr

ansc

riptio

n fa

ctor

activ

ityTr

ansp

orte

r act

ivity

Num

ber o

f gen

es


functionscomponents




4 Discussion






156 168 159 166 167 171 319 396 397 398 408

sim70bp

1kb+

(a)

N1 N2 N3 N4 N5 N6 N7 N9N8

sim70bp

1kb+

(b)


05

10152025

col-m

iR156

aco

l-miR159

aco

l-miR166

aco

l-miR167

aco

l-miR168

a-5

pco

l-miR171

aco

l-miR319

a-3

pco

l-miR396

a-5

pco

l-miR397

aco

l-miR398

col-m

iR408

aco

l-miR

N1

-5p

col-m

iRN2

-3p

col-m

IRN3

-3p

col-m

iRN4

-3p

col-m

iRN5

-3p

col-m

iRN6

-5p

col-m

iRN7

-5p

col-m

iRN8

-5p

col-m

iRN9

-3p

Log2

frequ

ency












5 Conclusion






Acknowledgments



References





















































































































Volume 2014

Zoology






















Advances in

Virolog y



Volume 2014




Enzyme Research



Microbiology


ble2miRNAs

from

each

family

with

theh

ighestfre

quency

injutewith

theirh

omologsinotherp

lants

Jutefamily

JutemiRNA

Leng

thof

smallR

NA

sequ

ence

Cou

ntof

small

RNA

sequ

ences

SmallR

NAsequ

ence

Hom

olog

(besto

ne)

Matches

number

Mism

atches

number

Gaps

number

Con

served

miR156

col-m

iR157a

21553160

9UUGAC

AGAAG

AUAG

AGAG

CAC

ath-miR157a

210

0col-m

iR156a

201724997

UGAC

AGAAG

AGAG

UGAG

CAC

ath-miR156a

200

0miR166

col-m

iR166a

21215636

UCG

GAC

CAGGCU

UCA

UUCC

CCath-miR166a

210

0miR167

col-m

iR167h

22154973

UGAAG

CUGCC

AGCA

UGAU

CUUA

mdm

-miR167h

220

0miR396

col-m

iR396b

-3p

2118695

GCU

CAAG

AAAG

CUGUGGGAG

Agm

a-miR396b

-3p

210

0miR168

col-m

iR168a

2116590

UCG

CUUGGUGCA

GGUCG

GGAA

ath-miR168a

210

0miR164

col-m

iR164a

217491

UGGAG

AAG

CAGGGCA

CGUGCA

ath-miR164a

210

0miR169

col-m

iR169b

212528

CAGCC

AAG

GAU

GAC

UUGCC

GG

ath-miR169b

210

0miR390

col-m

iR390a

212952

AAG

CUCA

GGAG

GGAU

AGCG

CCath-miR390a

210

0mir160

col-m

iR160a-3p

211448

GCG

UAUGAG

GAG

CCAAG

CAUA

gma-miR160a-3p

210

0miR159

col-m

iR159a

21484

UUUGGAU

UGAAG

GGAG

CUCU

Aath-miR159a

210

0miR171

col-m

iR171b

21558

UGAU

UGAG

CCGUGCC

AAU

AUC

osa-miR171b

210

0miR403

col-m

iR403

21282

UUA

GAU

UCA

CGCA

CAAAC

UCG

ath-miR403

210

0miR398

col-m

iR398

21262

GGAG

CGAC

AUGAG

AUCA

CAUG

hbr-miR398

201

0miR482

col-m

iR482b

222206

UCU

UACC

UACU

CCAC

CCAU

GCC

ghr-miR482b

211

0miR40

8col-m

iR40

821

129

AUGCA

CUGCC

UCU

UCC

CUGGC

ath-miR40

821

00

miR397

col-m

iR397a

21106

UCA

UUGAG

UGCA

GCG

UUGAU

Gath-miR397a

210

0miIR

530

col-m

iR530a

2181

UGCA

UUUGCA

CCUGCA

CCUUU

csi-m

iR530a

201

0miR393

col-m

iR393b-3p

2161

AUCA

UGCG

AUCC

CUUCG

GAAU

stu-m

iR393-3p

201

0miR394

col-m

iR394a

2016

UUGGCA

UUCU

GUCC

ACCU

CCath-miR394a

200

0miR827

col-m

iR827a

2122

UUA

GAU

GAC

CAUCA

ACAAAC

Agh

r-miR827a

210

0miR477

col-m

iR477i

212

ACUCU

CCCU

CAAG

GGCU

UCC

Gmes-m

iR477i

210

0miR2111

col-m

iR2111a

2115

UAAU

CUGCA

UCC

UGAG

GUUUG

ptc-miR2111a

210

0miR172

col-m

iR172a

211480

AGAAU

CUUGAU

GAU

GCU

GCA

Uath-miR172a

210

0Non

conserved

miR2275

col-m

iR2275a-3p

2254

UUA

AGUUUUCU

CCAAU

AUCU

CAzm

a-miR2275a-3p

201

2miR2118

col-m

iR2118a-3p

2236

UUGCC

GAAU

CCGCC

CAUUCC

GU

gma-miR2118a-3p

192

1miR528

col-m

iR528-5p

2117

UGGAAG

GGGCA

UGCA

GAG

GAG

osa-miR528-5p

210

0miR1310

col-m

iR1310

2169

AGGCA

UCG

GGGGCG

CAAC

GCC

han-miR1310

210

1miR7696

col-m

iR7696a-3p

216

UCU

GAAU

CAUGAG

AAC

UUGAG

mtr-

miR7696a-3p

191

2miR6224

col-m

iR6224a-3p

214

CUGAU

AAU

AUAG

GAC

GGAG

GG

sbi-m

iR6224a-3p

191

2miR64

62col-m

iR64

62c-5p

2128

AAG

GGAC

AAAAAG

GCU

AUAAG

ptc-miR64

62c-5p

200

3miR4243

col-m

iR4243

213

UUGAAC

UUGUA

CGAU

UUCG

ACath-miR4243

191

2miR5745

col-m

iR5745b

2116

UUUA

AUUUA

UAUA

CAUCU

CAC

mtr-

miR5745b

200

2miR902

col-m

iR902j-5p

241

AUAU

GUUA

CGCA

GAU

UCU

UCA

UUU

ppt-m

iR902j-5p

210

3miR2873

col-m

iR2873b

2110

UUGUGGCU

GAG

AUUUGGUA

UG

osa-miR2873b

191

2miR2950

col-m

iR2950

212465

UGGUGUGCA

GGGGGUGGAAU

Agh

r-miR2950

210

0miR5067

col-m

iR5049c

243837

GGAC

AAU

UAUUGUGGGAC

GGAG

GG

hvu-miR5049c

212

1miR818

col-m

iR1436

23920

AGAU

AAU

AUGGGAC

GGAG

GGAG

Uosa-miR1436

201

2miR44

14col-m

iR44

14a-3p

2111

AUCC

AAC

GAU

GCA

GGAG

CUGC

mtr-

miR44

14a-3p

201

0


Table2Con

tinued

Jutefamily

JutemiRNA

Leng

thof

smallR

NA

sequ

ence

Cou

ntof

small

RNA

sequ

ences

SmallR

NAsequ

ence

Hom

olog

(besto

ne)

Matches

number

Mism

atches

number

Gaps

number

miR1509

col-m

iR7122a

22488

UUGGAC

AGAG

AAAU

CACG

GUCG

mdm

-miR7122a

202

0miR158

col-m

iR158a

2034

UCC

CAAAU

GUA

GAC

AAAG

CAath-miR158a

200

0miR161

col-m

iR1612

212

UCA

AUGCA

UUGAAAG

UGAC

UAath-miR1612

210

0Und

efined

col-m

iR5162

244

AAAAU

GAC

CAAAAU

ACCC

CUAAAU

osa-miR5162

221

2Und

efined

col-m

iR6248

201

UAAU

UGAG

GAU

GGAG

GGAG

Uosa-miR6248

182

1Und

efined

col-m

iR7767-3p

221

UAGGAU

CAGGCA

GCU

UGAAG

GU

bdi-m

iR7767-3p

192

1Und

efined

col-m

iR5997

211

UGAAAC

UCA

AGUA

GCU

AAAAG

ath-miR5997

200

2Und

efined

col-m

iR5057

231

AAAC

UUUCA

GAU

GCA

UUUUGAC

Abd

i-miR5057

201

2Und

efined

col-m

iR6172

211

UGAG

ACCU

GUUUA

AGUUA

GAA

hbr-miR6172

191

2Und

efined

col-m

iR6279

203

UAAC

AAG

AAU

UCC

AGAC

ACA

ppe-miR6279

182

1Und

efined

col-m

iR6220-3p

231

AGAC

UUA

UAAU

UUGGGAC

GGAG

Asbi-m

iR6220-3p

212

1Und

efined

col-m

iR64

4321

1UGUA

UGAU

CAUGAU

GCU

GGAG

ptc-miR64

4319

12

Und

efined

col-m

iR156h

2017

UGAC

AGAAG

AGAG

AGAG

CAU

vvi-m

iR156h

200

0Und

efined

col-m

iR3954

22868222

UUGGAC

AGAG

UAAU

CACG

GUCG

csi-m

iR3954

192

1Und

efined

col-m

iR167i

201

UCA

UGCU

GGCA

GCU

UCA

CUU

gma-miR167i

200

3Und

efined

col-m

iR6300

1944

00GUCG

UUGUA

GUA

UAGUGGU

gma-miR6300

180

1Und

efined

col-m

iR169p

216

UAGCC

AAG

GAC

AAC

UUGCC

GG

osa-miR169p

210

1Und

efined

col-m

iR894

205406

GUUUCA

CGUCG

GGUUCA

CCA

ppt-m

iR894

190

2Und

efined

col-m

iR472a

22218

UUUUCC

CUAC

UCC

UCC

CAUCC

Cptc-miR472a

211

0Und

efined

col-m

iR5059

21212

CGGUCC

UGGGCA

GCA

ACAC

CAbd

i-miR5059

191

1Und

efined

col-m

iR2916

22312

GGGGGCU

CGAAG

ACGAU

CAGAU

peu-miR2916

202

1Und

efined

col-m

iR5072

2190

CGUUCC

CCAG

CGGAG

UCG

CCA

osa-miR5072

210

1Und

efined

col-m

iR477h

224

ACUCU

CCCU

CAAG

GGCU

UCC

AGmes-m

iR477h

210

1Und

efined

col-m

iR6478

21164

CCGAC

CUUA

GCU

CAGUUGGUA

ptc-miR6478

201

0Und

efined

col-m

iR5205b

24306

CUUA

UAAU

UAGGGAC

AGAG

GGAG

Umtr-

miR5205b

231

0Und

efined

col-m

iR7505

2131

UUCA

GAAAC

CAUCC

CCUCC

UU

ghr-miR7505

201

0Und

efined

col-m

iR5077

20378

GAU

UCA

CGUCG

GGUUCA

CCA

osa-miR5077

181

1Und

efined

col-m

iR5054

20904

GUUCC

CCAC

AGUCG

GCG

CCA

bdi-m

iR5054

171

2Und

efined

col-m

iR845c

2428

AGGCU

CUGAU

ACCA

AUUGAC

GUA

Gvvi-m

iR845c

210

3Und

efined

col-m

iR916

2228

CGAAG

GUCG

UCG

GUUCG

AAU

CCcre-miR916

192

1Und

efined

col-m

iR161-5

p1

2111

UUGAAAG

UGAC

UACA

UCG

GGG

aly-miR161-5

p1

210

0Und

efined

col-m

iR1863

2456

AGCU

CUGAU

ACCA

UGUUA

AGCA

UC

pab-miR1863

211

2Und

efined

col-m

iR7490

2441

AGUCU

GAU

AAAC

UCC

ACUGAC

GGU

ghr-miR7490

221

2Und

efined

col-m

iR3946

2113

UUGAG

AGAAG

AGAG

AGAG

CAC

csi-m

iR3946

210

3Und

efined

col-m

iR7728-5p

195

UUCG

GAU

UGAG

UGGAU

UUU

bdi-m

iR7728-5p

181

2Und

efined

col-m

iR1862f

211

AAG

GGGUUGGUUUA

CUUUUGG

osa-miR1862f

182

1Und

efined

col-m

iR6171

2111

ACUA

UGGAU

UGCU

GAAG

GUUU

hbr-miR6171

191

2Und

efined

col-m

iR5021

2131

UAAG

AAG

AAU

AAG

AAG

AAU

AA

ath-miR5021

182

1Und

efined

col-m

iR5244

216

UAUCU

GAU

GAU

GAU

UGUUGGU

mtr-

miR5244

192

0Und

efined

col-m

iR5049-3p

2330

AAG

UAAU

AUGGAAC

GGAG

GGAG

Ubd

i-miR5049-3p

212

1Und

efined

col-m

iR5629

2341

UUA

GGGUA

GUUA

ACGGGUA

GUUA

ath-miR5629

211

1





miR827miR818

miR7696

miR6462

miR6224

miR5745

miR530

miR528

miR5067

miR482

miR477

miR4414

miR4243

miR408

miR403

miR398miR397


miR2950miR2873

miR2275

miR2118

miR2111

miR172

miR171

miR169

miR168

miR167

miR166

miR164

miR161

miR160

miR159

miR158miR156







miRNA lengthMFE






col-miRN7 6







05

1015202530

Num

ber o

f fam

ilies

miR156

miR166

miR169

miR171

miR396

miR159

miR172

miR167

miR160

miR164

miR482

miR393

miR390

miR408

miR168

miR398

miR397

miR530

miR394

miR827

miR477

miR2111

miR403


05

10152025303540

Biol

ogic

al ad

hesio

nBi

olog

ical

regu

latio

nC

ellu

lar c

ompo

nent

org

aniz

atio

n or

bio

gene

sisC

ellu

lar p

roce

ssD

evelo

pmen

tal p

roce

ssEs

tabl

ishm

ent o

f loc

aliz

atio

nG

row

thLo

caliz

atio

nM

etab

olic

pro

cess

Mul

tiorg

anism

pro

cess

Mul

ticel

lula

r org

anism

al p

roce

ssRe

gula

tion

of b

iolo

gica

l pro

cess

Repr

oduc

tion

Repr

oduc

tive p

roce

ssRe

spon

se to

stim

ulus

Sign

alin

gSi

ngle

-org

anism

pro

cess

Cel

lC

ell p

art

Mem

bran

eM

embr

ane p

art

Org

anel

leA

ntio

xida

nt ac

tivity

Bind

ing

Cata

lytic

activ

ityN

ucle

ic ac

id b

indi

ng tr

ansc

riptio

n fa

ctor

activ

ityTr

ansp

orte

r act

ivity

Num

ber o

f gen

es


functionscomponents




4 Discussion






156 168 159 166 167 171 319 396 397 398 408

sim70bp

1kb+

(a)

N1 N2 N3 N4 N5 N6 N7 N9N8

sim70bp

1kb+

(b)


05

10152025

col-m

iR156

aco

l-miR159

aco

l-miR166

aco

l-miR167

aco

l-miR168

a-5

pco

l-miR171

aco

l-miR319

a-3

pco

l-miR396

a-5

pco

l-miR397

aco

l-miR398

col-m

iR408

aco

l-miR

N1

-5p

col-m

iRN2

-3p

col-m

IRN3

-3p

col-m

iRN4

-3p

col-m

iRN5

-3p

col-m

iRN6

-5p

col-m

iRN7

-5p

col-m

iRN8

-5p

col-m

iRN9

-3p

Log2

frequ

ency












5 Conclusion






Acknowledgments



References





















































































































Volume 2014

Zoology






















Advances in

Virolog y



Volume 2014




Enzyme Research



Microbiology


Table2Con

tinued

Jutefamily

JutemiRNA

Leng

thof

smallR

NA

sequ

ence

Cou

ntof

small

RNA

sequ

ences

SmallR

NAsequ

ence

Hom

olog

(besto

ne)

Matches

number

Mism

atches

number

Gaps

number

miR1509

col-m

iR7122a

22488

UUGGAC

AGAG

AAAU

CACG

GUCG

mdm

-miR7122a

202

0miR158

col-m

iR158a

2034

UCC

CAAAU

GUA

GAC

AAAG

CAath-miR158a

200

0miR161

col-m

iR1612

212

UCA

AUGCA

UUGAAAG

UGAC

UAath-miR1612

210

0Und

efined

col-m

iR5162

244

AAAAU

GAC

CAAAAU

ACCC

CUAAAU

osa-miR5162

221

2Und

efined

col-m

iR6248

201

UAAU

UGAG

GAU

GGAG

GGAG

Uosa-miR6248

182

1Und

efined

col-m

iR7767-3p

221

UAGGAU

CAGGCA

GCU

UGAAG

GU

bdi-m

iR7767-3p

192

1Und

efined

col-m

iR5997

211

UGAAAC

UCA

AGUA

GCU

AAAAG

ath-miR5997

200

2Und

efined

col-m

iR5057

231

AAAC

UUUCA

GAU

GCA

UUUUGAC

Abd

i-miR5057

201

2Und

efined

col-m

iR6172

211

UGAG

ACCU

GUUUA

AGUUA

GAA

hbr-miR6172

191

2Und

efined

col-m

iR6279

203

UAAC

AAG

AAU

UCC

AGAC

ACA

ppe-miR6279

182

1Und

efined

col-m

iR6220-3p

231

AGAC

UUA

UAAU

UUGGGAC

GGAG

Asbi-m

iR6220-3p

212

1Und

efined

col-m

iR64

4321

1UGUA

UGAU

CAUGAU

GCU

GGAG

ptc-miR64

4319

12

Und

efined

col-m

iR156h

2017

UGAC

AGAAG

AGAG

AGAG

CAU

vvi-m

iR156h

200

0Und

efined

col-m

iR3954

22868222

UUGGAC

AGAG

UAAU

CACG

GUCG

csi-m

iR3954

192

1Und

efined

col-m

iR167i

201

UCA

UGCU

GGCA

GCU

UCA

CUU

gma-miR167i

200

3Und

efined

col-m

iR6300

1944

00GUCG

UUGUA

GUA

UAGUGGU

gma-miR6300

180

1Und

efined

col-m

iR169p

216

UAGCC

AAG

GAC

AAC

UUGCC

GG

osa-miR169p

210

1Und

efined

col-m

iR894

205406

GUUUCA

CGUCG

GGUUCA

CCA

ppt-m

iR894

190

2Und

efined

col-m

iR472a

22218

UUUUCC

CUAC

UCC

UCC

CAUCC

Cptc-miR472a

211

0Und

efined

col-m

iR5059

21212

CGGUCC

UGGGCA

GCA

ACAC

CAbd

i-miR5059

191

1Und

efined

col-m

iR2916

22312

GGGGGCU

CGAAG

ACGAU

CAGAU

peu-miR2916

202

1Und

efined

col-m

iR5072

2190

CGUUCC

CCAG

CGGAG

UCG

CCA

osa-miR5072

210

1Und

efined

col-m

iR477h

224

ACUCU

CCCU

CAAG

GGCU

UCC

AGmes-m

iR477h

210

1Und

efined

col-m

iR6478

21164

CCGAC

CUUA

GCU

CAGUUGGUA

ptc-miR6478

201

0Und

efined

col-m

iR5205b

24306

CUUA

UAAU

UAGGGAC

AGAG

GGAG

Umtr-

miR5205b

231

0Und

efined

col-m

iR7505

2131

UUCA

GAAAC

CAUCC

CCUCC

UU

ghr-miR7505

201

0Und

efined

col-m

iR5077

20378

GAU

UCA

CGUCG

GGUUCA

CCA

osa-miR5077

181

1Und

efined

col-m

iR5054

20904

GUUCC

CCAC

AGUCG

GCG

CCA

bdi-m

iR5054

171

2Und

efined

col-m

iR845c

2428

AGGCU

CUGAU

ACCA

AUUGAC

GUA

Gvvi-m

iR845c

210

3Und

efined

col-m

iR916

2228

CGAAG

GUCG

UCG

GUUCG

AAU

CCcre-miR916

192

1Und

efined

col-m

iR161-5

p1

2111

UUGAAAG

UGAC

UACA

UCG

GGG

aly-miR161-5

p1

210

0Und

efined

col-m

iR1863

2456

AGCU

CUGAU

ACCA

UGUUA

AGCA

UC

pab-miR1863

211

2Und

efined

col-m

iR7490

2441

AGUCU

GAU

AAAC

UCC

ACUGAC

GGU

ghr-miR7490

221

2Und

efined

col-m

iR3946

2113

UUGAG

AGAAG

AGAG

AGAG

CAC

csi-m

iR3946

210

3Und

efined

col-m

iR7728-5p

195

UUCG

GAU

UGAG

UGGAU

UUU

bdi-m

iR7728-5p

181

2Und

efined

col-m

iR1862f

211

AAG

GGGUUGGUUUA

CUUUUGG

osa-miR1862f

182

1Und

efined

col-m

iR6171

2111

ACUA

UGGAU

UGCU

GAAG

GUUU

hbr-miR6171

191

2Und

efined

col-m

iR5021

2131

UAAG

AAG

AAU

AAG

AAG

AAU

AA

ath-miR5021

182

1Und

efined

col-m

iR5244

216

UAUCU

GAU

GAU

GAU

UGUUGGU

mtr-

miR5244

192

0Und

efined

col-m

iR5049-3p

2330

AAG

UAAU

AUGGAAC

GGAG

GGAG

Ubd

i-miR5049-3p

212

1Und

efined

col-m

iR5629

2341

UUA

GGGUA

GUUA

ACGGGUA

GUUA

ath-miR5629

211

1





miR827miR818

miR7696

miR6462

miR6224

miR5745

miR530

miR528

miR5067

miR482

miR477

miR4414

miR4243

miR408

miR403

miR398miR397


miR2950miR2873

miR2275

miR2118

miR2111

miR172

miR171

miR169

miR168

miR167

miR166

miR164

miR161

miR160

miR159

miR158miR156







miRNA lengthMFE






col-miRN7 6







05

1015202530

Num

ber o

f fam

ilies

miR156

miR166

miR169

miR171

miR396

miR159

miR172

miR167

miR160

miR164

miR482

miR393

miR390

miR408

miR168

miR398

miR397

miR530

miR394

miR827

miR477

miR2111

miR403


05

10152025303540

Biol

ogic

al ad

hesio

nBi

olog

ical

regu

latio

nC

ellu

lar c

ompo

nent

org

aniz

atio

n or

bio

gene

sisC

ellu

lar p

roce

ssD

evelo

pmen

tal p

roce

ssEs

tabl

ishm

ent o

f loc

aliz

atio

nG

row

thLo

caliz

atio

nM

etab

olic

pro

cess

Mul

tiorg

anism

pro

cess

Mul

ticel

lula

r org

anism

al p

roce

ssRe

gula

tion

of b

iolo

gica

l pro

cess

Repr

oduc

tion

Repr

oduc

tive p

roce

ssRe

spon

se to

stim

ulus

Sign

alin

gSi

ngle

-org

anism

pro

cess

Cel

lC

ell p

art

Mem

bran

eM

embr

ane p

art

Org

anel

leA

ntio

xida

nt ac

tivity

Bind

ing

Cata

lytic

activ

ityN

ucle

ic ac

id b

indi

ng tr

ansc

riptio

n fa

ctor

activ

ityTr

ansp

orte

r act

ivity

Num

ber o

f gen

es


functionscomponents




4 Discussion






156 168 159 166 167 171 319 396 397 398 408

sim70bp

1kb+

(a)

N1 N2 N3 N4 N5 N6 N7 N9N8

sim70bp

1kb+

(b)


05

10152025

col-m

iR156

aco

l-miR159

aco

l-miR166

aco

l-miR167

aco

l-miR168

a-5

pco

l-miR171

aco

l-miR319

a-3

pco

l-miR396

a-5

pco

l-miR397

aco

l-miR398

col-m

iR408

aco

l-miR

N1

-5p

col-m

iRN2

-3p

col-m

IRN3

-3p

col-m

iRN4

-3p

col-m

iRN5

-3p

col-m

iRN6

-5p

col-m

iRN7

-5p

col-m

iRN8

-5p

col-m

iRN9

-3p

Log2

frequ

ency












5 Conclusion






Acknowledgments



References





















































































































Volume 2014

Zoology






















Advances in

Virolog y



Volume 2014




Enzyme Research



Microbiology





miR827miR818

miR7696

miR6462

miR6224

miR5745

miR530

miR528

miR5067

miR482

miR477

miR4414

miR4243

miR408

miR403

miR398miR397


miR2950miR2873

miR2275

miR2118

miR2111

miR172

miR171

miR169

miR168

miR167

miR166

miR164

miR161

miR160

miR159

miR158miR156







miRNA lengthMFE






col-miRN7 6







05

1015202530

Num

ber o

f fam

ilies

miR156

miR166

miR169

miR171

miR396

miR159

miR172

miR167

miR160

miR164

miR482

miR393

miR390

miR408

miR168

miR398

miR397

miR530

miR394

miR827

miR477

miR2111

miR403


05

10152025303540

Biol

ogic

al ad

hesio

nBi

olog

ical

regu

latio

nC

ellu

lar c

ompo

nent

org

aniz

atio

n or

bio

gene

sisC

ellu

lar p

roce

ssD

evelo

pmen

tal p

roce

ssEs

tabl

ishm

ent o

f loc

aliz

atio

nG

row

thLo

caliz

atio

nM

etab

olic

pro

cess

Mul

tiorg

anism

pro

cess

Mul

ticel

lula

r org

anism

al p

roce

ssRe

gula

tion

of b

iolo

gica

l pro

cess

Repr

oduc

tion

Repr

oduc

tive p

roce

ssRe

spon

se to

stim

ulus

Sign

alin

gSi

ngle

-org

anism

pro

cess

Cel

lC

ell p

art

Mem

bran

eM

embr

ane p

art

Org

anel

leA

ntio

xida

nt ac

tivity

Bind

ing

Cata

lytic

activ

ityN

ucle

ic ac

id b

indi

ng tr

ansc

riptio

n fa

ctor

activ

ityTr

ansp

orte

r act

ivity

Num

ber o

f gen

es


functionscomponents




4 Discussion






156 168 159 166 167 171 319 396 397 398 408

sim70bp

1kb+

(a)

N1 N2 N3 N4 N5 N6 N7 N9N8

sim70bp

1kb+

(b)


05

10152025

col-m

iR156

aco

l-miR159

aco

l-miR166

aco

l-miR167

aco

l-miR168

a-5

pco

l-miR171

aco

l-miR319

a-3

pco

l-miR396

a-5

pco

l-miR397

aco

l-miR398

col-m

iR408

aco

l-miR

N1

-5p

col-m

iRN2

-3p

col-m

IRN3

-3p

col-m

iRN4

-3p

col-m

iRN5

-3p

col-m

iRN6

-5p

col-m

iRN7

-5p

col-m

iRN8

-5p

col-m

iRN9

-3p

Log2

frequ

ency












5 Conclusion






Acknowledgments



References





















































































































Volume 2014

Zoology






















Advances in

Virolog y



Volume 2014




Enzyme Research



Microbiology




miRNA lengthMFE






col-miRN7 6







05

1015202530

Num

ber o

f fam

ilies

miR156

miR166

miR169

miR171

miR396

miR159

miR172

miR167

miR160

miR164

miR482

miR393

miR390

miR408

miR168

miR398

miR397

miR530

miR394

miR827

miR477

miR2111

miR403


05

10152025303540

Biol

ogic

al ad

hesio

nBi

olog

ical

regu

latio

nC

ellu

lar c

ompo

nent

org

aniz

atio

n or

bio

gene

sisC

ellu

lar p

roce

ssD

evelo

pmen

tal p

roce

ssEs

tabl

ishm

ent o

f loc

aliz

atio

nG

row

thLo

caliz

atio

nM

etab

olic

pro

cess

Mul

tiorg

anism

pro

cess

Mul

ticel

lula

r org

anism

al p

roce

ssRe

gula

tion

of b

iolo

gica

l pro

cess

Repr

oduc

tion

Repr

oduc

tive p

roce

ssRe

spon

se to

stim

ulus

Sign

alin

gSi

ngle

-org

anism

pro

cess

Cel

lC

ell p

art

Mem

bran

eM

embr

ane p

art

Org

anel

leA

ntio

xida

nt ac

tivity

Bind

ing

Cata

lytic

activ

ityN

ucle

ic ac

id b

indi

ng tr

ansc

riptio

n fa

ctor

activ

ityTr

ansp

orte

r act

ivity

Num

ber o

f gen

es


functionscomponents




4 Discussion






156 168 159 166 167 171 319 396 397 398 408

sim70bp

1kb+

(a)

N1 N2 N3 N4 N5 N6 N7 N9N8

sim70bp

1kb+

(b)


05

10152025

col-m

iR156

aco

l-miR159

aco

l-miR166

aco

l-miR167

aco

l-miR168

a-5

pco

l-miR171

aco

l-miR319

a-3

pco

l-miR396

a-5

pco

l-miR397

aco

l-miR398

col-m

iR408

aco

l-miR

N1

-5p

col-m

iRN2

-3p

col-m

IRN3

-3p

col-m

iRN4

-3p

col-m

iRN5

-3p

col-m

iRN6

-5p

col-m

iRN7

-5p

col-m

iRN8

-5p

col-m

iRN9

-3p

Log2

frequ

ency












5 Conclusion






Acknowledgments



References





















































































































Volume 2014

Zoology






















Advances in

Virolog y



Volume 2014




Enzyme Research



Microbiology


05

1015202530

Num

ber o

f fam

ilies

miR156

miR166

miR169

miR171

miR396

miR159

miR172

miR167

miR160

miR164

miR482

miR393

miR390

miR408

miR168

miR398

miR397

miR530

miR394

miR827

miR477

miR2111

miR403


05

10152025303540

Biol

ogic

al ad

hesio

nBi

olog

ical

regu

latio

nC

ellu

lar c

ompo

nent

org

aniz

atio

n or

bio

gene

sisC

ellu

lar p

roce

ssD

evelo

pmen

tal p

roce

ssEs

tabl

ishm

ent o

f loc

aliz

atio

nG

row

thLo

caliz

atio

nM

etab

olic

pro

cess

Mul

tiorg

anism

pro

cess

Mul

ticel

lula

r org

anism

al p

roce

ssRe

gula

tion

of b

iolo

gica

l pro

cess

Repr

oduc

tion

Repr

oduc

tive p

roce

ssRe

spon

se to

stim

ulus

Sign

alin

gSi

ngle

-org

anism

pro

cess

Cel

lC

ell p

art

Mem

bran

eM

embr

ane p

art

Org

anel

leA

ntio

xida

nt ac

tivity

Bind

ing

Cata

lytic

activ

ityN

ucle

ic ac

id b

indi

ng tr

ansc

riptio

n fa

ctor

activ

ityTr

ansp

orte

r act

ivity

Num

ber o

f gen

es


functionscomponents




4 Discussion






156 168 159 166 167 171 319 396 397 398 408

sim70bp

1kb+

(a)

N1 N2 N3 N4 N5 N6 N7 N9N8

sim70bp

1kb+

(b)


05

10152025

col-m

iR156

aco

l-miR159

aco

l-miR166

aco

l-miR167

aco

l-miR168

a-5

pco

l-miR171

aco

l-miR319

a-3

pco

l-miR396

a-5

pco

l-miR397

aco

l-miR398

col-m

iR408

aco

l-miR

N1

-5p

col-m

iRN2

-3p

col-m

IRN3

-3p

col-m

iRN4

-3p

col-m

iRN5

-3p

col-m

iRN6

-5p

col-m

iRN7

-5p

col-m

iRN8

-5p

col-m

iRN9

-3p

Log2

frequ

ency












5 Conclusion






Acknowledgments



References





















































































































Volume 2014

Zoology






















Advances in

Virolog y



Volume 2014




Enzyme Research



Microbiology


156 168 159 166 167 171 319 396 397 398 408

sim70bp

1kb+

(a)

N1 N2 N3 N4 N5 N6 N7 N9N8

sim70bp

1kb+

(b)


05

10152025

col-m

iR156

aco

l-miR159

aco

l-miR166

aco

l-miR167

aco

l-miR168

a-5

pco

l-miR171

aco

l-miR319

a-3

pco

l-miR396

a-5

pco

l-miR397

aco

l-miR398

col-m

iR408

aco

l-miR

N1

-5p

col-m

iRN2

-3p

col-m

IRN3

-3p

col-m

iRN4

-3p

col-m

iRN5

-3p

col-m

iRN6

-5p

col-m

iRN7

-5p

col-m

iRN8

-5p

col-m

iRN9

-3p

Log2

frequ

ency












5 Conclusion






Acknowledgments



References





















































































































Volume 2014

Zoology






















Advances in

Virolog y



Volume 2014




Enzyme Research



Microbiology



5 Conclusion






Acknowledgments



References





















































































































Volume 2014

Zoology






















Advances in

Virolog y



Volume 2014




Enzyme Research



Microbiology




































































































Volume 2014

Zoology






















Advances in

Virolog y



Volume 2014




Enzyme Research



Microbiology

research article high-throughput sequencing reveals...

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