research article transcriptome sequencing in a tibetan...

Research ArticleTranscriptome Sequencing in a Tibetan Barley Landrace withHigh Resistance to Powdery Mildew

Xing-Quan Zeng1 Xiao-Mei Luo2 Yu-Lin Wang1 Qi-Jun Xu1 Li-Jun Bai2

Hong-Jun Yuan1 and Nyima Tashi1

1Barley Improvement and Yak Breeding Key Laboratory Tibet Academy of Agricultural and Animal Husbandry SciencesLhasa Tibet 850002 China2College of Forestry Sichuan Agricultural University Yaan Sichuan 625014 China

Correspondence should be addressed to Nyima Tashi nyima tashi163com

Received 20 October 2014 Revised 1 December 2014 Accepted 1 December 2014 Published 22 December 2014

Academic Editor ChangHui Shen

Copyright copy 2014 Xing-Quan Zeng 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

Hulless barley is an important cereal crop worldwide especially in Tibet of China However this crop is usually susceptible topowdery mildew caused by Blumeria graminis f sp hordei In this study we aimed to understand the functions and pathways ofgenes involved in the disease resistance by transcriptome sequencing of a Tibetan barley landrace with high resistance to powderymildew A total of 831 significant differentially expressed genes were found in the infected seedlings covering 19 functions Eitherldquocellrdquo ldquocell partrdquo and ldquoextracellular regionrdquo in the cellular component category or ldquobindingrdquo and ldquocatalyticrdquo in the category ofmolecular function as well as ldquometabolic processrdquo and ldquocellular processrdquo in the biological process category together demonstratedthat these functionsmay be involved in the resistance to powderymildewof the hulless barley In addition 330KEGGpathwayswerefound using BLASTx with an E-value cut-off of lt10minus5 Among them three pathways namely ldquophotosynthesisrdquo ldquoplant-pathogeninteractionrdquo and ldquophotosynthesis-antenna proteinsrdquo had significant matches in the database Significant expressions of the threepathways were detected at 24 h 48 h and 96 h after infection respectively These results indicated a complex process of barleyresponse to powdery mildew infection

1 Introduction

Hulless barley (Hordeum vulgare L var nudum) is a diploid(2119899 = 7119909 = 14)monocot and belongs to the family of PoaceaeHulless barley is also a form of domesticated barley with aneasier-to-remove hull Hulless barley is an important cerealcrop worldwide especially for beer brewing and poultry feed[1] This crop is often attacked by barley powdery mildewfungus (Blumeria graminis f sp hordei) which is one of themost destructive pathogens of barley Powderymildew causesconsiderable damage and severe loss of grain yield [2] It iscrucial to collect genetic resources resistant to this disease andfurther identify underlying genes of resistance to powderyresources In barley a great number of landraces have beencultivated across theworld and present large genetic variationin many desirable traits including disease resistance Indeedmost of the genes for resistance to powdery mildew incurrently used cultivars were found in barley landraces [3ndash7]

A few resistance genes against powdery mildew have beenstudied in barley such asmla [8]mlo [9]mlg [10]mlhb [11]and mlf [12] Nevertheless many resistance genes have losttheir effectiveness as new races of the pathogen have evolvedHence discovering new candidate genes in barley genomesequence is of particular importance To date the resistancemechanisms for powdery mildew at physiological and genelevels remain unknown so comprehensive transcriptomicsequencing of barley varieties with the disease resistance mayimprove our understanding of plant reaction to pathogeninfection

In the past few years it has been widely demonstratedthat high-throughput next generation sequencing technologymakes it possible to carry out genome-wide studies oftranscriptomes in a cost-efficient way to explore genes andexpression profiling of model and nonmodel organisms [13ndash15] Transcriptome sequencing and characterization usingIllumina II sequencing technology have been successfully

Hindawi Publishing Corporatione Scientific World JournalVolume 2014 Article ID 594579 9 pageshttpdxdoiorg1011552014594579

2 The Scientific World Journal

used to interrogate transcriptomes ofmany organisms such asyeast [16 17] sweet potato [18] rice [19] taxus [20] migrato-ry locust [21] and giant panda [22] Despite its obviouspotential Illumina second generation sequencing has notbeen applied to barley variety for powdery mildew resistanceanalysis

The present study was undertaken to provide a broadsurvey of genes associated with barley resistance to powderymildew by transcriptome analysis using Illumina technologyThe main goals of this work were as follows (1) to discovernew genes related to powdery mildew resistance (2) tocharacterize the gene expression profiles during pathogeninfection processes and (3) to reveal the functions andpathways of the genes involved in the disease resistancemechanism

2 Materials and Methods

21 Plant Materials Pathogen Infection and RNA ExtractionHulless barley cultivar ldquoGan Nong Da 7rdquo displaying highresistance to powdery mildew (unpublished work) was usedin this study Barley seedswere sown in the greenhouseThreeweeks later the seedlings were infected by powdery mildew(isolated from the field infected barley) and then kept in darkat 18∘C for 24 hours and finally kept in light for 14 hoursevery day Barley leaves were harvested at six growth stagesafter infection 0 h 24 h 48 h 72 h 96 h and 120 h respec-tively (see Supplementary Figure 1 in Supplementary Mate-rial available online at httpdxdoiorg1011552014594579)More information about the samples can be found out inSupplementary Table 1 For Illumina sequencing the totalRNA of each of the samples was isolated using an RNAisoPlus (TaKaRa Japan) protocol and then further purified withRNase-free DNase I (TaKaRa Japan)

22 cDNA Library Construction and Sequencing BrieflySera-Mag Magnetic Oligo (dT) Beads (Illumina San DiegoCA) were used to isolate poly (A) mRNA after the totalRNAwas collected from the leaves Fragmentation buffer wasadded for interrupting mRNA into short fragments Thenby using these short fragments as templates random hex-amer (N6) primers (Illumina San Diego CA) were used tosynthesize the first-strand cDNA The second-strand cDNAwas synthesized in the buffer containing dNTPs RNase Hand DNA polymerase I Paired end library was constructedby the Genomic Sample Prep kit (Illumina San Diego CA)according to manufacturerrsquos instructions Short fragmentswere purified with QiaQuick PCR extraction kit (QiagenValencia CA) and resolved with EB buffer for end repairand adding poly (A) After that the short fragments wereconnected with the sequencing adapters For amplificationwith PCR we selected suitable fragments (200 plusmn 25 bp) astemplates based on the result of agarose gel electrophoresisAt last the library was sequenced using Illumina GenomeAnalyzer IIX (Illumina San Diego CA)

23 Mapping Reads to Reference Genome The referencegenome was downloaded from the Barley Genome Database(http15046168145gbrowse new) Sequencing-received

raw image datawas transformed byBaseCalling into rawdataor raw reads Raw sequences were transformed into cleantags by removing reads with adaptor contamination reads oflow quality (reads containing 119873s gt 10) and the reads withmore than 50119876 le 5 basesThen the saturation analysis wasperformed to check whether the number of detected genesincreased along with sequencing amount (total tag number)The distribution of clean tag expressions was used to evaluatethe normality of the whole data After that the remainingreads were aligned to the reference genome using softwareprogram TopHat 209 (Johns Hopkins University seehttpccbjhuedusoftwaretophatindexshtml) followingthe procedure tophat-p4-library-type fr-unstranded-G gff

24 Normalized Gene Expression Level by RNA-Seq Theexpression levels of genes based on RNA-Seq was normalizedby the number of reads per kilo base of exon region in a geneper million mapped reads (RPKM) [23]

RPKM = 106

lowast 119877

(119873 lowast 119871) 103

(1)

where RPKM is the reads per kilo base transcript per millionreads 119877 is the number of mappable reads to a gene119873 is thetotal mapped reads in the experiment and 119871 is the sum of theexons in base pairs

RPKM is able to avoid the difference from gene lengthand total sequence data effect on gene expressionThe cut-offvalue for determining the background expression level wasat 95 confidence interval for all RPKM values of each geneThe results from this formula were directly used to comparethe difference in the gene expressions among the samples atdifferent time sequences

25 Evaluation of DGE (Differentially Expressed Genes)Libraries For screening of DGEs between different samplesa rigorous algorithm was developed based on the previousmethod [24] 119875 value corresponds to differential gene expres-sion test The threshold of 119875 value in multiple tests wasdetermined through manipulating the false discovery rate(FDR) value We use FDR le 005 as the threshold to judgethe significance of DGEs

Gene ontology (GO) terms were analyzed by the softwareBlast2GO v 234 [25] using the default parameters Thisprogram was used to obtain the number of each gene term(GOannotation) and then hypergeometric tests were appliedto detect GO enrichment analysis of functional significancein DEGs The calculating formula is

119875 = 1 minus

119898minus1

sum

119894=0

(119898minus1

119894

) (119873minus119872

119899minus119894

)

(119873

119899

)

(2)

where119873 is number of genes with annotation 119899 is the numberof differently expressed genes in119873119872 is the number of genesthat are annotated to the certain GO term and 119898 is thenumber of DEGs in119872

TheKyoto Encyclopedia of Genes andGenomes (KEGG)the major public pathway-related database was used inthe pathway enrichment analysis to identify significantly

The Scientific World Journal 3

Table 1 RNA-sequencing data filtering analysis

Library Alowast B C D E F Average TotalOriginal reads number (G) 717 640 688 779 714 751 715 4290Modified reads number (G) 666 592 638 724 661 700 664 3983Modified Q30 bases rate () 9622 9621 9627 9619 962 9641 9625 mdashMapped rate () 8634 8621 8699 8682 8689 8655 8663 mdashMultimap rate () 1282 982 1403 1259 1281 1413 127 mdashlowastAndashF the samples collected at 0 h 24 h 48 h 72 h 96 h and 120 h after infection

enriched metabolic pathways or signal transduction path-ways in DEGs compared with the whole transcriptome back-groundThe calculating formula is the same as that in the GOanalysis119873 is the number of all genes with KEGG annotation119899 is the number of DEGs in119873119872 is the number of all genesannotated to the specific pathways and 119898 is the number ofDEGs in119872 The119876 value of a test measures the proportion offalse positives incurred (ie false discovery rate) when thatparticular test is called significant (httpgenomicsprincetonedustoreylabqvalue) Pathways with 119876 value le005 aresignificantly enriched in DEGs

3 Results

31 Summary of RNA-Sequencing Data Sets To obtain adynamic view of the gene expression profiles of barley pow-dery mildew resistance at different infection progress stagessix cDNA samples were prepared from barley leaves at 0 h24 h 48 h 72 h 96 h and 120 h after infection And then thesesamples were subjected to the Illumina sequencing platformIn total we acquired more than 4290G raw reads over sixtime points (Table 1) After cleaning the reads with the pro-portion of119873 over 10 over half of proportion of base quality119876 less than 5 bases and the adapter polluted reads approxi-mately 3980G clean reads were collected with 9625 of the119876 30 bases (base quality over 30) The average data of eachsample was approximately 664G in size The following dataanalysis procedures were based on the modified reads

32 Evaluation of the Sequencing Data Quality To assessthe quality and coverage of the sequencing data meanquality distribution and base distribution were analyzedSequencing error rate is not only related to base quality butalso influenced by sequencer reagent sample and so forthEach base sequencing error can be judged by 119876phred (Phredscore) which is given by a model of prediction base judgingerror probability during Base Calling The sequencing basemean quality distributions of six samples were similar to eachother For example the mean quality distribution of SampleA (the sample at 0 h after infection namely TR130348) wasillustrated in Supplementary Figure 2 The base position inreads is aligned as the 119909-axis and the mean 119876phred as the 119910-axis High proportion of 119876 30 reads indicted high-qualitysequence

Base distributions of all sampleswere also similar and thatin Sample A as an example was illustrated in SupplementaryFigure 3 The base position in reads is aligned as the 119909-axis and the percentage of ATGC base as the 119910-axis In

603

314

Mapping reads coverage of TR130348

Exon mappingIntron mappingIntergene mapping

83

Figure 1 Mapping reads (exon intron and intergene) coverage ofA (C0 TR130348)

general the equal proportions of bases between T and A andbetweenG andCwere found indicating no preference duringsequencingTheGC percentage of each sample accounted forapproximately 54 of the total

33 Mapping Reads Coverage The mapping results werelisted in Table 1 Each of the samples had the mapped readrates greater than 86 which indicates that most sequencingdata are consistent with the reference genome of barley

Based on the mapped reads the proportion of exonmapping intron mapping and intergene mapping of sampleA at 0 h since infection 5 were illustrated in Figure 1 Thehighest exon mapping (603) was found in Sample A whilethe lowest (521) was found in Sample F (C120 TR130353)The intron mapping coverage ranged from 83 (A) to108 (B C24 TR130349) The average of intergene mappingwas 352 There was no affinity with reference genomeannotation

In order to detect the depth of bases exon gene wasdivided into 100 parts The relative positions of genes arealigned as119909-axis and the number of reads is aligned as119910-axisThe line charts of all samples were similar to each other andSample A was illustrated in Supplementary Figure 4 Therewas a little preference of gene exon to the base depth

34 Gene Expressions Gene saturation of each sample wasalso similar and Sample A was illustrated in Supplemen-tary Figure 5 Comparisons of gene expressions in eachsubsample to the whole sample showed less than 15 ofthe difference between them indicating fine expressiongenes in the current size of sequencing data The results


Condition

Genes

ABC

DEF

minus25 00 25

Den

sity

00

01

02

03

04

log 10 (fpkm)

Figure 2 Distributed density of gene global expression of eachsample

represented an accurate dataset to detect highly expressedgenes The distribution density of gene global expressionsof each sample was illustrated in Figure 2 which exhibitssimilar expressed gene distributions among these samplesCuffdiff software (httpcufflinkscbcbumdeduindexhtml)was used to compare the gene expressions between samplepairs Differently expressed genes were identified based ongenes with 119902 lt 005 (119902 is the corrected 119875 value) Theresults were listed in SupplementaryTable 2 TotalDEGs fromeach sample were clustered in Supplementary Figure 6 Thefirst subgroup contained only A the second one included Band C (C48 TR130350) and the last one covered the restsamples of D (C72 TR130351) E (C96 TR130352) and FEuclidean distance was used to estimate the distance of geneexpression between sample pairs The clusters of A and Bwere illustrated in Figure 3 In the histogram the red colorindicates upregulation and the green color downregulationCompared with Sample A gene expressions of B and Cwere significantly different There were similar distributionsbetween A and D between A and E and between A and F

35 Functional Classification by GO GO is an internationalstandardized gene functional classification system whichoffers a dynamic-updated controlled vocabulary and a strictlydefined concept to comprehensively describe the propertiesof genes and their products in any organism GO hasthree ontologies molecular function cellular componentand biological process In total 39197 reads with BLASTxmatches to known proteins were assigned to gene ontologyclasses with 2654 functional terms Of them assignments tothe biological process made up the majority (1344 5064)followed by molecular function (1060 3994) and cellularcomponent (250 942) These functional classifications

by GO were summarized in Table 2 Comparison of GOclassification between A and B was presented in Figure 4

A total of 831 significant DEGs were found by CufflinkThe assigned functions of these genes covered a broad rangeof GO categories Under the cellular component categorycell cell part and extracellular region including ldquothylakoidpartrdquo ldquophotosystemrdquo and ldquophotosystem IIrdquo were prominentlyrepresented indicating that some powdery mildew-relatedmetabolic activities of photosynthesis occurred in the leafof the Tibetan barley landrace Interestingly many geneswere assigned to ldquooxygen evolving complexrdquo It was alsonoteworthy that a large number of genes were involved inldquoextrinsic to membranerdquo Under the category of molecularfunction binding and catalysis including ldquoADP bindingrdquo andldquoauxiliary transport proteinrdquo represented the majorities ofthe category Among the genes assigned to auxiliary trans-port protein ldquoendonuclease activityrdquo represented the mostabundant classification followed by ldquoribonuclease activityrdquoldquoendoribonuclease activityrdquo and ldquoribonuclease T2 activityrdquoFor the biological process category many genes were classi-fied into themetabolic process and cellular process includingldquophotosynthesis light harvestingrdquo whereas only a few geneswere assigned to ldquodefense responserdquo ldquoresponse to stressrdquo andldquogeneration of precursor metabolites and energyrdquo

36 Functional Classification by KEGG KEGG is a publicdatabase recording the networks of molecular interactions inthe cells and variants of them specific to particular organismsPathway-based analysis helps to further understand thebiological functions and interactions of genes First based oncomparison with the KEGG database using BLASTx with an119864-value cut-off of lt10minus5 330 KEGG pathways were detectedAmong them three pathways that is ldquophotosynthesisrdquoldquoplant-pathogen interactionrdquo and ldquophotosynthesis-antennaproteinsrdquo had significant matches in the database As shownin Table 2 the ldquophotosynthesisrdquo pathway became distinct atthe stage of 24 h after infection the ldquoplant-pathogen inter-actionrdquo pathway also differed significantly at the time andthe ldquophotosynthesis-antenna proteinsrdquo and ldquophotosynthesisrdquopathway was remarkable 96 h after infection These resultsindicated a dynamic and complex process of barley responseto powdery mildew

4 Discussion

41 Illumina Paired End Sequencing and Assembly In thisstudy the mRNA of the barley plants infected with powderymildew pathogen was sequenced using Illumina GenomeAnalyzer with Sera-Mag Magnetic Oligo (dT) Beads A clearbioinformatic map of mRNA involved in multiple biologicalprocesses was produced As a result 429G data was collectedfrom six samples over infection time After filtering theaverage data size of each sample was 664G and the readsnumber was 6638M whichmet the requirements for furtheranalysis Saturability analysis indicated a qualified coverageof most genes based on our data size In addition the cleanreads of119876 30 occupied over 95 of the total suggesting high-quality sequencing


TR130348 TR130349

minus3 minus1 0 1 2 3Value

0

20

Color keyand histogram

Cou

nt

Figure 3 Euclidean distance was used to establish the distance of expression between A (C0 TR130348) and B (C24 TR130349)

TopHat package was used to blast the transcriptome datato the reference genome It has been found that 86 of thereads were mapped to the reference genome Multiblastedreads were greater than 10 which might suggest thatthey were repeatable in this species Further analysis of themapping reads showed that the average of intergenemappingreads was more than 30 which might be due to inadequateannotation of the genome as reported by Luo et al [26]

42 Functional Annotation of DEGs On the basis of extensiveexamination of the DEGs between samples 831 significantDEGs were found across nineteen functionsThese functionswere related to cell cell part and extracellular region in thecellular component category binding and catalytic in the cat-egory of molecular function and metabolic process and cel-lular process in the biological process categoryThis indicatedthat these functions were likely involved in powdery mildew-resistant hulless barley Hulbert et al [27] summarised thatthe powdery mildew resistance genes carry motifs foundin other receptor and signal transduction proteins such asnucleotide-binding site domains and kinase domains Activeoxygen in some species has been found to play a numberof critical roles in defence responses during plant-pathogeninteractions [28ndash30] Warren et al [31] reported that itfunctioned in defense response signaling of an Arabidopsis

mutation since it interfered with resistance conferred byseveral other nucleotide-binding site genesThe cellular com-ponents and processes reflect where resistance genes interactwith their corresponding elicitors The cell membrane andextracellular leucine-rich repeats indicated the associationbetween transmembrane domain and the correspondingkinase [32ndash34] The observed interaction with intracellularresistance genes products should stimulate researches intohow these diverse organisms deliver elicitors into plant cells

Furthermore KEGG was used to annotate the DEGsby enrichment analysis and revealed the significant path-ways involved in the disease resistance Three pathwaysoccurred in different stages the infection firstly actedon ldquophotosynthesisrdquo of leaves and then caused ldquopathogenrecognition interactionrdquo and defense response signaling andfinally affected ldquophotosynthesis-antenna proteinsrdquoThis eventsequence exhibited a dynamic process of barley responding topowderymildewOnce the recognition of pathogen occurredthe defense responses were triggeredThese are often charac-terized as a hypersensitive response which involves the deathof the first cell or cells infected and the local accumulation ofantimicrobial compounds [35]

KEGG analysis revealed that resistance gene action wascoupled to a complex series of biochemical defense path-ways It is therefore more likely that resistance genes may


Table 2 Functional classification by GO and KEGG

Category 119876-value FunctionA B cellular component

GO0044464 003867023 Cell partGO0005576 305119864 minus 06 Extracellular regionGO0044436 002673204 Thylakoid partGO0009521 002559572 PhotosystemGO0009523 001277032 Photosystem IIGO0009654 000933201 Oxygen evolving complexGO0019898 000908508 Extrinsic to membrane

B E cellular componentGO0005576 004652511 Extracellular region

A C molecular functionGO0004519 001846397 Endonuclease activityGO0004540 000563478 Ribonuclease activityGO0004521 000325892 Endoribonuclease activity

GO0016894 210119864 minus 05Endonuclease activity active with either ribo- or deoxyribonucleic acids and

producing 31015840-phosphomonoestersGO0016892 210119864 minus 05 Endoribonuclease activity producing 31015840-phosphomonoestersGO0033897 210119864 minus 05 Ribonuclease T2 activity

A E molecular function

GO0016894 004079433 Endonuclease activity active with either ribo- or deoxyribonucleic acids andproducing 31015840-phosphomonoesters

GO0016892 004079433 Endoribonuclease activity producing 31015840-phosphomonoestersGO0033897 004079433 Ribonuclease T2 activity

C E molecular functionGO0043531 001381725 ADP binding

B E biological processGO0006091 001070069 Generation of precursor metabolites and energyGO0009765 488119864 minus 05 Photosynthesis light harvesting

B F biological processGO0009765 000971227 Photosynthesis light harvesting

C E biological processGO0006952 000970112 Defense responseGO0006950 000970112 Response to stress

A B keggmap00195 00422721 Photosynthesis

A C keggmap04626 000085699 Plant-pathogen interaction

B E keggmap00196 656119864 minus 05 Photosynthesis-antenna proteins

B F keggmap00196 000126333 Photosynthesis-antenna proteins

C E keggmap04626 000751478 Plant-pathogen interactionmap00196 004943251 Photosynthesis-antenna proteins


Cellular componentBiological process Molecular function

Ana

tom

ical

stru

ctur

e for

mat

ion

Biol

ogic

al ad

hesio

nBi

olog

ical

regu

latio

nC

ell k

illin

gC

ellul

ar co

mpo

nent

bio

gene

sisC

ellu

lar c

ompo

nent

org

aniz

atio

nC

ellu

lar p

roce

ssD

eath

Dev

elopm

enta

l pro

cess

Esta

blish

men

t of l

ocal

izat

ion

Gro

wth

Imm

une s

yste

m p

roce

ssLo

caliz

atio

nLo

com

otio

nM

etab

olic

pro

cess

Mul

tiorg

anism

pro

cess

Mul

ticel

lula

r org

anism

al p

roce

ssPi

gmen

tatio

nRe

prod

uctio

nRe

prod

uctiv

e pro

cess

Resp

onse

to st

imul

usRh

ythm

ic p

roce

ssVi

ral r

epro

duct

ion

Cel

lC

ell p

art

Enve

lope

Extr

acel

lula

r reg

ion

Extr

acel

lula

r reg

ion

part

Mac

rom

olec

ular

com

plex

Mem

bran

e-en

close

d lu

men

Org

anel

leO

rgan

elle

par

tSy

mpl

ast

Syna

pse

Syna

pse p

art

Virio

nVi

rion

part

Ant

ioxi

dant

0

076

76

Num

ber o

f gen

es

001

01

1

10

100

Cmp1

Gen

es (

)

Comparison of GO classification

Auxi

liary

tran

spor

t pro

tein

Bind

ing

Cata

lytic

Chem

oattr

acta

ntCh

emor

epel

lent

Elec

tron

carr

ier

Enzy

me r

egul

ator

Met

allo

chap

eron

eM

olec

ular

tran

sduc

erN

utrie

nt re

serv

oir

Prot

easo

me r

egul

ator

Prot

ein

tag

Stru

ctur

al m

olec

ule

Tran

scrip

tion

regu

lator

Tran

slatio

n re

gulat

orTr

ansp

orte

r

Figure 4 Histogram presentation of gene ontology classification between A (C0 TR130348) and B (C24 TR130349) The results aresummarized in three main categories biological process cellular component and molecular functionThe right 119910-axis indicates the numberof genes in a category The left 119910-axis indicates the percentage of a specific category of genes in that main category

function together in recognizing pathogen elicitors possiblyas coreceptors The similarity in structure of the tomato Cfproteins [36] to the rice Xa21 protein [37] implies that thetransmembrane domain genes may also include a kinasein their defense-signaling pathway Mla resistance proteincontaining recognition complexes may be activated byRAR1SGT1 (two conserved-interacting proteins in mutantsof barley Rar1) [38] Mlo resistance genes were triggered bya rapid formation of enlarged cell wall appositions belowthe fungusrsquos encounter sites and of a physical and chemicalbarrier that the infection peg can rarely penetrate [9] Mloallele encodes a putative membrane protein which may be anegative regulator of certain defense responses [39] whereasRor (required for mlo-specified resistance) genes act as posi-tive regulators of a non-race-specific resistance response [40]Barley lines that are homozygous for the nonfunctional allelesshow spontaneous defense responses like cell wall appositionsin the epidermal cells and even some cell death [41] Piffanelliet al [42] inferred that the CIS- (cytokine-induced SH2-containing protein-) dependent perturbation of transcriptionmachinery assembly by transcriptional interference inMlo-11plants is a likely mechanism leading to disease resistance

5 Conclusions

This work presents a first report of the transcriptomesequencing of the Tibetan barley landrace with powderymildew resistance and brings a major genomic resource forbarley resistance to this disease A large number of genesin the hulless barley were characterized by DEG analysis

using Illumina sequencing technology The transcriptomeand DEG analyses also provided us with a genome-wideview of the transcriptional mechanisms to improve genomeannotation and enabled us to understand some relatedbiological progress of hulless barley disease resistance Thedata in this study is consistent with those using multipleapproaches including QTL mapping and FISH indicatingthe reliability of the results from the mRNA-Seq and DEGanalysis Therefore further work is needed to find additionallinked DNA markers for these DEGs It is necessary todevelop new reliable PCR-based markers tightly linked tothe resistance genes and this will greatly facilitate genetransfer into currently used varieties

Conflict of Interests

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

Authorsrsquo Contribution

Xing-Quan Zeng and Xiao-Mei Luo contributed equally tothis work

Acknowledgments

This work was supported by Special Funds for PreliminaryResearch of 973 Plan (2012CB723006) China National Sci-entific and Technological Support Plan (2012BAD03B01)


and Specific Financial Funds in Tibet Autonomous Region(2011XZCZZX001)

References

[1] R S Bhatty ldquo120573-glucan and flour yield of hull-less barleyrdquoCerealChemistry vol 76 no 2 pp 314ndash315 1999

[2] B A McDonald and C Linde ldquoThe population genetics ofplant pathogens and breeding strategies for durable resistancerdquoEuphytica vol 124 no 2 pp 163ndash180 2002

[3] G Fischbeck and A Jahoor ldquoThe transfer of genes for mildewresistance from Hordeum spontaneumrdquo in Integrated Con-trol of Cereal Mildews Virulence Patterns and Their ChangeJ H Joslashrgensen Ed pp 247ndash255 Risoslash National Labora-tory Roskilde Denmark 1991 httpagrisfaoorgagris-searchsearchdorecordID=DK9420942

[4] J H Joslashrgensen and P M Wolfe ldquoGenetics of powdery mildewresistance in barleyrdquo Critical Reviews in Plant Sciences vol 13no 1 pp 97ndash119 1994

[5] J Helms Joslashrgensen and H P Jensen ldquoPowdery mildew resis-tance in barley landrace material I Screening for resistancerdquoEuphytica vol 97 no 2 pp 227ndash233 1997

[6] C Silvar H Dhif E Igartua et al ldquoIdentification of quantitativetrait loci for resistance to powdery mildew in a Spanish barleylandracerdquoMolecular Breeding vol 25 no 4 pp 581ndash592 2010

[7] C Silvar A M Casas D Kopahnke et al ldquoScreening theSpanish barley core collection for disease resistancerdquo PlantBreeding vol 129 no 1 pp 45ndash52 2010

[8] F Wei K Gobelman-Werner S M Morroll et al ldquoThe Mla(powdery mildew) resistance cluster is associated with threeNBS-LRR gene families and suppressed recombination withina 240-kb DNA interval on chromosome 5S (1HS) of barleyrdquoGenetics vol 153 no 4 pp 1929ndash1948 1999

[9] I H Joslashrgensen ldquoDiscovery characterization and exploitationofMlo powdery mildew resistance in barleyrdquo Euphytica vol 63no 1-2 pp 141ndash152 1992

[10] I Falak and D E Falk ldquoDoubled haploids as a tool for studyingresistance to powdery mildew (Erysiphe graminis f sp hordei)rdquoBarley Newsletter vol 36 article 208 1993

[11] R A Pickering A M Hill M Michel and G M Timmerman-Vaughan ldquoThe transfer of a powdery mildew resistance genefrom Hordeum bulbosum L to barley (H vulgare L) chromo-some 2 (2I)rdquoTheoretical and Applied Genetics vol 91 no 8 pp1288ndash1292 1995

[12] M Schonfeld A Ragni G Fischbeck and A Jahoor ldquoRFLPmapping of three new loci for resistance genes to powderymildew (Erysiphe graminis f sp hordei) in barleyrdquo Theoreticaland Applied Genetics vol 93 no 1-2 pp 48ndash56 1996

[13] A Barakat D S Diloreto Y Zhang et al ldquoComparison ofthe transcriptomes of American chestnut (Castanea dentata)and Chinese chestnut (Castanea mollissima) in response to thechestnut blight infectionrdquo BMC Plant Biology vol 9 article 512009

[14] J WangWWang R Li et al ldquoThe diploid genome sequence ofan Asian individualrdquoNature vol 456 no 7218 pp 60ndash65 2008

[15] T L Parchman K S Geist J A Grahnen C W Benkmanand C A Buerkle ldquoTranscriptome sequencing in an ecologi-cally important tree species assembly annotation and markerdiscoveryrdquo BioMed Central Genomics vol 11 no 1 article 1802010

[16] U Nagalakshmi Z Wang K Waern et al ldquoThe transcriptionallandscape of the yeast genome defined by RNA sequencingrdquoScience vol 320 no 5881 pp 1344ndash1349 2008

[17] B T Wilhelm S Marguerat S Watt et al ldquoDynamic repertoireof a eukaryotic transcriptome surveyed at single-nucleotideresolutionrdquo Nature vol 453 no 7199 pp 1239ndash1243 2008

[18] Z Wang B Fang J Chen et al ldquoDe novo assembly and char-acterization of root transcriptome using Illumina paired-endsequencing and development of cSSR markers in sweet potato(Ipomoea batatas)rdquo BMC Genomics vol 11 no 1 article 7262010

[19] G Zhang G Guo X Hu et al ldquoDeep RNA sequencing atsingle base-pair resolution reveals high complexity of the ricetranscriptomerdquo Genome Research vol 20 no 5 pp 646ndash6542010

[20] D C Hao G Ge P Xiao Y Zhang and L Yang ldquoThe firstinsight into the tissue specific taxus transcriptome via illuminasecond generation sequencingrdquo PLoS ONE vol 6 no 6 ArticleID e21220 2011

[21] S Chen P Yang F Jiang Y Wei Z Ma and L Kang ldquoDe Novoanalysis of transcriptome dynamics in the migratory locustduring the development of phase traitsrdquo PLoS ONE vol 5 no12 Article ID e15633 2010

[22] L J Collins P J Biggs C Voelckel and S Joly ldquoAn approachto transcriptome analysis of non-model organisms using short-read sequencesrdquo Genome Informatics vol 21 pp 3ndash14 2008

[23] A Mortazavi B A Williams K McCue L Schaeffer and BWold ldquoMapping and quantifying mammalian transcriptomesby RNA-Seqrdquo Nature Methods vol 5 no 7 pp 621ndash628 2008

[24] S Audic and J-M Claverie ldquoThe significance of digital geneexpression profilesrdquo Genome Research vol 7 no 10 pp 986ndash995 1997

[25] A Conesa S Gotz J M Garcıa-Gomez J Terol M Talonand M Robles ldquoBlast2GO a universal tool for annotationvisualization and analysis in functional genomics researchrdquoBioinformatics vol 21 no 18 pp 3674ndash3676 2005

[26] X Luo C P Wight Y Zhou and N A Tinker ldquoCharacteri-zation of chromosome-specific genomic DNA from hexaploidoatrdquo Genome vol 55 no 4 pp 265ndash268 2012

[27] S H Hulbert C A Webb S M Smith and Q Sun ldquoResistancegene complexes evolution and utilizationrdquo Annual Review ofPhytopathology vol 39 pp 285ndash312 2001

[28] M W Sutherland ldquoThe generation of oxygen radicals duringhost plant responses to infectionrdquo Physiological and MolecularPlant Pathology vol 39 no 2 pp 79ndash93 1991

[29] D D Tzeng and J E DeVay ldquoRole of oxygen radicals in plantdisease developmentrdquo in Advance in Plant Pathology J HAndrews and I C Tommerup Eds vol 10 pp 1ndash34 AcademicPress New York NY USA 1993

[30] C J Baker and E W Orlandi ldquoActive oxygen in plant patho-genesisrdquo Annual Review of Phytopathology vol 33 pp 299ndash3211995

[31] S G Warren R E Brandt and P O Hinton ldquoEffect of surfaceroughness on bidirectional reflectance of Antarctic snowrdquoJournal of Geophysical Research E Planets vol 103 no 11 pp25789ndash25807 1998

[32] G F van denAckerveken J A L vanKan and P J GM deWitldquoMolecular analysis of the avirulence gene avr9 of the fungaltomato pathogenCladosporium fulvum fully supports the gene-for-gene hypothesisrdquo Plant Journal vol 2 no 3 pp 359ndash3661992


[33] M H A Joosten T J Cozijnsen and P J de Wit ldquoHost resist-ance to a fungal tomato pathogen lost by a single base-pairchange in an avirulence generdquo Nature vol 367 no 6461 pp384ndash386 1994

[34] M A Botella J E Parker L N Frost et al ldquoThree genes of theArabidopsis RPP1 complex resistance locus recognize distinctPeronospora parasitica avirulence determinantsrdquo Plant Cell vol10 no 11 pp 1847ndash1860 1998

[35] J D G Jones and J L Dangl ldquoThe plant immune systemrdquoNature vol 444 no 7117 pp 323ndash329 2006

[36] M S Dixon D A Jones J S Keddie C M Thomas K Harri-son and J D G Jones ldquoThe tomato Cf -2 disease resistancelocus comprises two functional genes encoding leucine-richrepeat proteinsrdquo Cell vol 84 no 3 pp 451ndash459 1996

[37] W-Y Song L-Y Pi G-L Wang J Gardner T Holsten and PC Ronald ldquoEvolution of the rice Xa21 disease resistance genefamilyrdquoThe Plant Cell vol 9 no 8 pp 1279ndash1287 1997

[38] Q-H Shen F Zhou S Bieri T Haizel K Shirasu andP Schulze-Lefert ldquoRecognition specificity and RAR1SGT1dependence in barley Mla disease resistance genes to thepowdery mildew fungusrdquoThe Plant Cell vol 15 no 3 pp 732ndash744 2003

[39] R Buschges K Hollricher R Panstruga et al ldquoThe barleyMlogene a novel control element of plant pathogen resistancerdquoCellvol 88 no 5 pp 695ndash705 1997

[40] A Freialdenhoven C Peterhansel J Kurth F Kreuzaler and PSchulze-Lefert ldquoIdentification of genes required for the func-tion of non-race-specific mlo resistance to powdery mildew inbarleyrdquo Plant Cell vol 8 no 1 pp 5ndash14 1996

[41] M Wolter K Hollricher F Salamini and P Schulze-LefertldquoThe mlo resistance alleles to powdery mildew infection inbarley trigger a developmentally controlled defence mimicphenotyperdquo Molecular and General Genetics vol 239 no 1-2pp 122ndash128 1993

[42] P Piffanelli L Ramsay R Waugh et al ldquoA barley cultivation-associated polymorphism conveys resistance to powderymildewrdquo Nature vol 430 no 7002 pp 887ndash891 2004

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


used to interrogate transcriptomes ofmany organisms such asyeast [16 17] sweet potato [18] rice [19] taxus [20] migrato-ry locust [21] and giant panda [22] Despite its obviouspotential Illumina second generation sequencing has notbeen applied to barley variety for powdery mildew resistanceanalysis

The present study was undertaken to provide a broadsurvey of genes associated with barley resistance to powderymildew by transcriptome analysis using Illumina technologyThe main goals of this work were as follows (1) to discovernew genes related to powdery mildew resistance (2) tocharacterize the gene expression profiles during pathogeninfection processes and (3) to reveal the functions andpathways of the genes involved in the disease resistancemechanism

2 Materials and Methods

21 Plant Materials Pathogen Infection and RNA ExtractionHulless barley cultivar ldquoGan Nong Da 7rdquo displaying highresistance to powdery mildew (unpublished work) was usedin this study Barley seedswere sown in the greenhouseThreeweeks later the seedlings were infected by powdery mildew(isolated from the field infected barley) and then kept in darkat 18∘C for 24 hours and finally kept in light for 14 hoursevery day Barley leaves were harvested at six growth stagesafter infection 0 h 24 h 48 h 72 h 96 h and 120 h respec-tively (see Supplementary Figure 1 in Supplementary Mate-rial available online at httpdxdoiorg1011552014594579)More information about the samples can be found out inSupplementary Table 1 For Illumina sequencing the totalRNA of each of the samples was isolated using an RNAisoPlus (TaKaRa Japan) protocol and then further purified withRNase-free DNase I (TaKaRa Japan)

22 cDNA Library Construction and Sequencing BrieflySera-Mag Magnetic Oligo (dT) Beads (Illumina San DiegoCA) were used to isolate poly (A) mRNA after the totalRNAwas collected from the leaves Fragmentation buffer wasadded for interrupting mRNA into short fragments Thenby using these short fragments as templates random hex-amer (N6) primers (Illumina San Diego CA) were used tosynthesize the first-strand cDNA The second-strand cDNAwas synthesized in the buffer containing dNTPs RNase Hand DNA polymerase I Paired end library was constructedby the Genomic Sample Prep kit (Illumina San Diego CA)according to manufacturerrsquos instructions Short fragmentswere purified with QiaQuick PCR extraction kit (QiagenValencia CA) and resolved with EB buffer for end repairand adding poly (A) After that the short fragments wereconnected with the sequencing adapters For amplificationwith PCR we selected suitable fragments (200 plusmn 25 bp) astemplates based on the result of agarose gel electrophoresisAt last the library was sequenced using Illumina GenomeAnalyzer IIX (Illumina San Diego CA)

23 Mapping Reads to Reference Genome The referencegenome was downloaded from the Barley Genome Database(http15046168145gbrowse new) Sequencing-received

raw image datawas transformed byBaseCalling into rawdataor raw reads Raw sequences were transformed into cleantags by removing reads with adaptor contamination reads oflow quality (reads containing 119873s gt 10) and the reads withmore than 50119876 le 5 basesThen the saturation analysis wasperformed to check whether the number of detected genesincreased along with sequencing amount (total tag number)The distribution of clean tag expressions was used to evaluatethe normality of the whole data After that the remainingreads were aligned to the reference genome using softwareprogram TopHat 209 (Johns Hopkins University seehttpccbjhuedusoftwaretophatindexshtml) followingthe procedure tophat-p4-library-type fr-unstranded-G gff

24 Normalized Gene Expression Level by RNA-Seq Theexpression levels of genes based on RNA-Seq was normalizedby the number of reads per kilo base of exon region in a geneper million mapped reads (RPKM) [23]

RPKM = 106

lowast 119877

(119873 lowast 119871) 103

(1)

where RPKM is the reads per kilo base transcript per millionreads 119877 is the number of mappable reads to a gene119873 is thetotal mapped reads in the experiment and 119871 is the sum of theexons in base pairs

RPKM is able to avoid the difference from gene lengthand total sequence data effect on gene expressionThe cut-offvalue for determining the background expression level wasat 95 confidence interval for all RPKM values of each geneThe results from this formula were directly used to comparethe difference in the gene expressions among the samples atdifferent time sequences

25 Evaluation of DGE (Differentially Expressed Genes)Libraries For screening of DGEs between different samplesa rigorous algorithm was developed based on the previousmethod [24] 119875 value corresponds to differential gene expres-sion test The threshold of 119875 value in multiple tests wasdetermined through manipulating the false discovery rate(FDR) value We use FDR le 005 as the threshold to judgethe significance of DGEs

Gene ontology (GO) terms were analyzed by the softwareBlast2GO v 234 [25] using the default parameters Thisprogram was used to obtain the number of each gene term(GOannotation) and then hypergeometric tests were appliedto detect GO enrichment analysis of functional significancein DEGs The calculating formula is

119875 = 1 minus

119898minus1

sum

119894=0

(119898minus1

119894

) (119873minus119872

119899minus119894

)

(119873

119899

)

(2)

where119873 is number of genes with annotation 119899 is the numberof differently expressed genes in119873119872 is the number of genesthat are annotated to the certain GO term and 119898 is thenumber of DEGs in119872

TheKyoto Encyclopedia of Genes andGenomes (KEGG)the major public pathway-related database was used inthe pathway enrichment analysis to identify significantly





3 Results




603

314



83








Condition

Genes

ABC

DEF

minus25 00 25

Den

sity

00

01

02

03

04

log 10 (fpkm)







4 Discussion



TR130348 TR130349


0

20


Cou

nt





























Ana

tom

ical

stru

ctur

e for

mat

ion

Biol

ogic

al ad

hesio

nBi

olog

ical

regu

latio

nC

ell k

illin

gC

ellul

ar co

mpo

nent

bio

gene

sisC

ellu

lar c

ompo

nent

org

aniz

atio

nC

ellu

lar p

roce

ssD

eath

Dev

elopm

enta

l pro

cess

Esta

blish

men

t of l

ocal

izat

ion

Gro

wth

Imm

une s

yste

m p

roce

ssLo

caliz

atio

nLo

com

otio

nM

etab

olic

pro

cess

Mul

tiorg

anism

pro

cess

Mul

ticel

lula

r org

anism

al p

roce

ssPi

gmen

tatio

nRe

prod

uctio

nRe

prod

uctiv

e pro

cess

Resp

onse

to st

imul

usRh

ythm

ic p

roce

ssVi

ral r

epro

duct

ion

Cel

lC

ell p

art

Enve

lope

Extr

acel

lula

r reg

ion

Extr

acel

lula

r reg

ion

part

Mac

rom

olec

ular

com

plex

Mem

bran

e-en

close

d lu

men

Org

anel

leO

rgan

elle

par

tSy

mpl

ast

Syna

pse

Syna

pse p

art

Virio

nVi

rion

part

Ant

ioxi

dant

0

076

76

Num

ber o

f gen

es

001

01

1

10

100

Cmp1

Gen

es (

)


Auxi

liary

tran

spor

t pro

tein

Bind

ing

Cata

lytic

Chem

oattr

acta

ntCh

emor

epel

lent

Elec

tron

carr

ier

Enzy

me r

egul

ator

Met

allo

chap

eron

eM

olec

ular

tran

sduc

erN

utrie

nt re

serv

oir

Prot

easo

me r

egul

ator

Prot

ein

tag

Stru

ctur

al m

olec

ule

Tran

scrip

tion

regu

lator

Tran

slatio

n re

gulat

orTr

ansp

orte

r



5 Conclusions







Acknowledgments




References



















































Volume 2014

Zoology






















Advances in

Virolog y



Volume 2014




Enzyme Research



Microbiology





3 Results




603

314



83








Condition

Genes

ABC

DEF

minus25 00 25

Den

sity

00

01

02

03

04

log 10 (fpkm)







4 Discussion



TR130348 TR130349


0

20


Cou

nt





























Ana

tom

ical

stru

ctur

e for

mat

ion

Biol

ogic

al ad

hesio

nBi

olog

ical

regu

latio

nC

ell k

illin

gC

ellul

ar co

mpo

nent

bio

gene

sisC

ellu

lar c

ompo

nent

org

aniz

atio

nC

ellu

lar p

roce

ssD

eath

Dev

elopm

enta

l pro

cess

Esta

blish

men

t of l

ocal

izat

ion

Gro

wth

Imm

une s

yste

m p

roce

ssLo

caliz

atio

nLo

com

otio

nM

etab

olic

pro

cess

Mul

tiorg

anism

pro

cess

Mul

ticel

lula

r org

anism

al p

roce

ssPi

gmen

tatio

nRe

prod

uctio

nRe

prod

uctiv

e pro

cess

Resp

onse

to st

imul

usRh

ythm

ic p

roce

ssVi

ral r

epro

duct

ion

Cel

lC

ell p

art

Enve

lope

Extr

acel

lula

r reg

ion

Extr

acel

lula

r reg

ion

part

Mac

rom

olec

ular

com

plex

Mem

bran

e-en

close

d lu

men

Org

anel

leO

rgan

elle

par

tSy

mpl

ast

Syna

pse

Syna

pse p

art

Virio

nVi

rion

part

Ant

ioxi

dant

0

076

76

Num

ber o

f gen

es

001

01

1

10

100

Cmp1

Gen

es (

)


Auxi

liary

tran

spor

t pro

tein

Bind

ing

Cata

lytic

Chem

oattr

acta

ntCh

emor

epel

lent

Elec

tron

carr

ier

Enzy

me r

egul

ator

Met

allo

chap

eron

eM

olec

ular

tran

sduc

erN

utrie

nt re

serv

oir

Prot

easo

me r

egul

ator

Prot

ein

tag

Stru

ctur

al m

olec

ule

Tran

scrip

tion

regu

lator

Tran

slatio

n re

gulat

orTr

ansp

orte

r



5 Conclusions







Acknowledgments




References



















































Volume 2014

Zoology






















Advances in

Virolog y



Volume 2014




Enzyme Research



Microbiology


Condition

Genes

ABC

DEF

minus25 00 25

Den

sity

00

01

02

03

04

log 10 (fpkm)







4 Discussion



TR130348 TR130349


0

20


Cou

nt





























Ana

tom

ical

stru

ctur

e for

mat

ion

Biol

ogic

al ad

hesio

nBi

olog

ical

regu

latio

nC

ell k

illin

gC

ellul

ar co

mpo

nent

bio

gene

sisC

ellu

lar c

ompo

nent

org

aniz

atio

nC

ellu

lar p

roce

ssD

eath

Dev

elopm

enta

l pro

cess

Esta

blish

men

t of l

ocal

izat

ion

Gro

wth

Imm

une s

yste

m p

roce

ssLo

caliz

atio

nLo

com

otio

nM

etab

olic

pro

cess

Mul

tiorg

anism

pro

cess

Mul

ticel

lula

r org

anism

al p

roce

ssPi

gmen

tatio

nRe

prod

uctio

nRe

prod

uctiv

e pro

cess

Resp

onse

to st

imul

usRh

ythm

ic p

roce

ssVi

ral r

epro

duct

ion

Cel

lC

ell p

art

Enve

lope

Extr

acel

lula

r reg

ion

Extr

acel

lula

r reg

ion

part

Mac

rom

olec

ular

com

plex

Mem

bran

e-en

close

d lu

men

Org

anel

leO

rgan

elle

par

tSy

mpl

ast

Syna

pse

Syna

pse p

art

Virio

nVi

rion

part

Ant

ioxi

dant

0

076

76

Num

ber o

f gen

es

001

01

1

10

100

Cmp1

Gen

es (

)


Auxi

liary

tran

spor

t pro

tein

Bind

ing

Cata

lytic

Chem

oattr

acta

ntCh

emor

epel

lent

Elec

tron

carr

ier

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me r

egul

ator

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allo

chap

eron

eM

olec

ular

tran

sduc

erN

utrie

nt re

serv

oir

Prot

easo

me r

egul

ator

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ein

tag

Stru

ctur

al m

olec

ule

Tran

scrip

tion

regu

lator

Tran

slatio

n re

gulat

orTr

ansp

orte

r



5 Conclusions







Acknowledgments




References



















































Volume 2014

Zoology






















Advances in

Virolog y



Volume 2014




Enzyme Research



Microbiology


TR130348 TR130349


0

20


Cou

nt





























Ana

tom

ical

stru

ctur

e for

mat

ion

Biol

ogic

al ad

hesio

nBi

olog

ical

regu

latio

nC

ell k

illin

gC

ellul

ar co

mpo

nent

bio

gene

sisC

ellu

lar c

ompo

nent

org

aniz

atio

nC

ellu

lar p

roce

ssD

eath

Dev

elopm

enta

l pro

cess

Esta

blish

men

t of l

ocal

izat

ion

Gro

wth

Imm

une s

yste

m p

roce

ssLo

caliz

atio

nLo

com

otio

nM

etab

olic

pro

cess

Mul

tiorg

anism

pro

cess

Mul

ticel

lula

r org

anism

al p

roce

ssPi

gmen

tatio

nRe

prod

uctio

nRe

prod

uctiv

e pro

cess

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onse

to st

imul

usRh

ythm

ic p

roce

ssVi

ral r

epro

duct

ion

Cel

lC

ell p

art

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lope

Extr

acel

lula

r reg

ion

Extr

acel

lula

r reg

ion

part

Mac

rom

olec

ular

com

plex

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bran

e-en

close

d lu

men

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anel

leO

rgan

elle

par

tSy

mpl

ast

Syna

pse

Syna

pse p

art

Virio

nVi

rion

part

Ant

ioxi

dant

0

076

76

Num

ber o

f gen

es

001

01

1

10

100

Cmp1

Gen

es (

)


Auxi

liary

tran

spor

t pro

tein

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ing

Cata

lytic

Chem

oattr

acta

ntCh

emor

epel

lent

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tron

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allo

chap

eron

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olec

ular

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sduc

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utrie

nt re

serv

oir

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easo

me r

egul

ator

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ein

tag

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ctur

al m

olec

ule

Tran

scrip

tion

regu

lator

Tran

slatio

n re

gulat

orTr

ansp

orte

r



5 Conclusions







Acknowledgments




References



















































Volume 2014

Zoology






















Advances in

Virolog y



Volume 2014




Enzyme Research



Microbiology























Ana

tom

ical

stru

ctur

e for

mat

ion

Biol

ogic

al ad

hesio

nBi

olog

ical

regu

latio

nC

ell k

illin

gC

ellul

ar co

mpo

nent

bio

gene

sisC

ellu

lar c

ompo

nent

org

aniz

atio

nC

ellu

lar p

roce

ssD

eath

Dev

elopm

enta

l pro

cess

Esta

blish

men

t of l

ocal

izat

ion

Gro

wth

Imm

une s

yste

m p

roce

ssLo

caliz

atio

nLo

com

otio

nM

etab

olic

pro

cess

Mul

tiorg

anism

pro

cess

Mul

ticel

lula

r org

anism

al p

roce

ssPi

gmen

tatio

nRe

prod

uctio

nRe

prod

uctiv

e pro

cess

Resp

onse

to st

imul

usRh

ythm

ic p

roce

ssVi

ral r

epro

duct

ion

Cel

lC

ell p

art

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lope

Extr

acel

lula

r reg

ion

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acel

lula

r reg

ion

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Mac

rom

olec

ular

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plex

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bran

e-en

close

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anel

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tSy

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pse

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pse p

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rion

part

Ant

ioxi

dant

0

076

76

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ber o

f gen

es

001

01

1

10

100

Cmp1

Gen

es (

)


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liary

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tein

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ntCh

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allo

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ular

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nt re

serv

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ein

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ctur

al m

olec

ule

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scrip

tion

regu

lator

Tran

slatio

n re

gulat

orTr

ansp

orte

r



5 Conclusions







Acknowledgments




References



















































Volume 2014

Zoology






















Advances in

Virolog y



Volume 2014




Enzyme Research



Microbiology



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 transcriptome sequencing in a tibetan...

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