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Plant
Science
jo u r n al h om ep ag e :w w w . e l s e v i e r . c o m / l o c a t e / p l a n t s c i
Construction
of
a
versatile
SNP
array
for
pyramiding
useful
genes
of
rice
Yusuke
Kurokawa
a,1,
Tomonori
Noda
a,1,
Yoshiyuki
Yamagata
c,d,e,
Rosalyn
Angeles-Shim
a,b,c,
Hidehiko
Sunohara
f,
Kanako
Uehara
a,
Tomoyuki
Furuta
a,
Keisuke
Nagai
a,
Kshirod
Kumar
Jena
b,
Hideshi
Yasui
d,e,
Atsushi
Yoshimura
d,e,
Motoyuki
Ashikari
a,c,d,
Kazuyuki
Doi
c,d,f,∗aBioscienceandBiotechnologyCenter,NagoyaUniversity,Furo-cho,Chikusa,Nagoya,Aichi464-8601,Japan bNovelGeneResourcesLaboratory,InternationalRiceResearchInstitute,DAPOBox7777,MetroManila,Philippines cWonderRiceInitiativeforFoodSecurityandHealth(WISH)project,JapanInternationalCooperationAgency(JICA),Japan
dScienceandTechnologyResearchPartnershipforSustainableDevelopment(SATREPS)project,JapanScienceandTechnologyAgency(JST)andJapan
InternationalCooperationAgency(JICA),Japan
ePlantBreedingLaboratory,KyushuUniversity,6-10-1Hakozaki,Higashi,Fukuoka812-8581,Japan
fGraduateSchoolofBioagriculturalSciences,NagoyaUniversity,Furo-cho,Chikusa,Nagoya,Aichi464-8601,Japan
a
r
t
i
c
l
e
i
n
f
o
Articlehistory:
Received4June2015
Receivedinrevisedform4September2015 Accepted7September2015
Availableonline10September2015
Keywords: MAS Ricebreeding QTL SNP Genepyramiding
a
b
s
t
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t
DNAmarker-assistedselection(MAS)hasbecome anindispensablecomponentof breeding.Single nucleotidepolymorphisms(SNP)arethemostfrequentpolymorphisminthericegenome.However, SNPmarkersarenotreadilyemployedinMASbecauseoflimitationsingenotypingplatforms.Herethe authorsreportaGoldenGateSNParraythattargetsspecificgenescontrollingyield-relatedtraitsand bioticstressresistanceinrice.Asafirststep,theSNPgenotypesweresurveyedin31parental vari-etiesusingtheAffymetrixRice44KSNPmicroarray.Thehaplotypeinformationfor16targetgeneswas thenconvertedtotheGoldenGateplatformwith143-plexmarkers.Haplotypesforthe14usefulallele areuniqueandcandiscriminateamongallothervarieties.Thegenotypingconsistencybetweenthe AffymetrixmicroarrayandtheGoldenGatearraywas92.8%,andtheaccuracyoftheGoldenGatearray wasconfirmedin3F2segregatingpopulations.Theconceptofthehaplotype-basedselectionbyusing theconstructedSNParraywasproofed.
©2015TheAuthors.PublishedbyElsevierIrelandLtd.ThisisanopenaccessarticleundertheCCBY license(http://creativecommons.org/licenses/by/4.0/).
1. Introduction
By 2050,theworld populationisexpected tosurpass 9 bil-lion.Toaddressthemonumentalchallengeoffeeding9billion,a 70%increaseinglobalagriculturalproductionhastobereached [[1], http://faostat.fao.org/default.aspx]. Rice is one of themost importantfoodcrops,providing upto76%ofthecaloricintake inSoutheastAsiaandupto23%ofthecaloricneedsworldwide [2,3].Increasingriceproduction,therefore,wouldplayakeyrole
Abbreviations:QTL,quantitativetraitloci;SNP,singlenucleotidepolymorphism; MAS,marker-assistedselection;SSR,simplesequencerepeat;BX,BeadXpress;OPA, oligopoolassay;InDel,insertion/deletion.
∗ Correspondingauthorat:GraduateSchoolofBioagriculturalSciences,Nagoya
University,Furo-cho,Chikusa,Nagoya464-8601,Japan.
E-mailaddress:[email protected](K.Doi).
1 Theseauthorsequallycontributedtothisstudy.
ineffortstosecuretheworldfoodsupply.Superiorricevarieties withhighyield,goodeatingquality,pestanddiseaseresistanceand othergoodagronomiccharacteristicshavebeendevelopedby tra-ditionalbreeding.However,thereisstillacontinuingdemandfor newvarietiesthatwouldfurtherimprovericeproduction.Tothis end,genepyramidinghasbeenanefficientbreedingstrategythat allowsincorporationofmultiplesgenesofagronomicimportance intoasinglevariety[4].
Currently,a numberofusefulgenesorquantitativetraitloci (QTLs)thatarerelatedtoagronomicaltraitshavebeenidentified. Genescontrollingyield-relatedtraitssuchaspanicleorseedshape [5,6],aswellasbioticstressresistancegenesthatcanbeusedto rationallymanagericepestsanddiseases[7–9]havebeen identi-fiedandcloned.DNAmarkersarenowavailabletopreciselyselect usefulallelesforthesetraitsandpyramidtheminrice.
With the development of DNA techniques, marker-assisted
selection(MAS)hasbecomeanindispensablecomponentof breed-ing.MASnotonlyeliminatedtheextensivetraitevaluationinvolved http://dx.doi.org/10.1016/j.plantsci.2015.09.008
Table1
Ricevarietiesusedinthisstudy.
ID Variety Descriptiona Targetgene(s)b
1 ADR52 Brownplanthopperresistance bph25,Bph26
2 ARC10313 Greenriceleafhopperresistance Grh2,Grh4
3 Asominori Greenriceleafhopperresistance Ovc
4 ASU Coldtolerance/recipient
5 Azucena Droughttolerance/recipient
6 Basmati217 Goodeatingquality/recipient
7 Basmati370 Goodeatingquality/recipient
8 DV85 Greenriceleafhopperresistance,bacterialblightresistance Grh2,Grh4,Xa7
9 Fukuhibiki Highyield/recipient
10 IR24 BackgroundofIRBB21andIRBB4/5/13/21
11 IRBB21 Bacterialblightresistance Xa21
12 IRBB4/5/13/21 Bacterialblightresistance Xa21,Xa4
13 Kandang18 Vietnamesecultivar/recipient
14 KinandangPatong Droughttolerance(deeproot)/recipient
15 Kinmaze Japanesecultivar/recipient
16 Koshihikari Japanesecultivar/recipient
17 Kuchum Coldtolerance/recipient
18 LO1050 Coldtolerance/recipient
19 Mizuhochikara Highbiomass,Japanesecultivar/recipient
20 Nipponbare Varietyofricereferencegenome
21 PakheDhan Coldtolerance/recipient
22 Sensho Blastresistance pi21
23 Silewah Coldtolerance/recipient
24 ST12 Highyield Gn1ac,WFP,APO1c
25 ST6 Highyield,Newplanttype Gn1ac
26 T65BPH25/26 Brownplanthopperresistance bph25,Bph26
27 T65GRH2/4/6 Greenriceleafhopperresistance Grh2,Grh4,Grh6
28 Taichung65 Taiwanesecultivar/recipient
29 TAL214 Goodeatingquality/recipient
30 TSC3 Brownplanthopperresistance(unidentified)
31 V103S Vietnamesecultivar/recipient
aOnlygenestargetedinthisstudywereindicated.ReferencesareshowninTable2.
b “/recipient”indicatethevarietieswhichwillbepotentiallyusedasrecipientsorgeneticbackgrounds. c AllelewereconfirmedbysequencingandQTLanalysis(datanotshown)
ingenepyramidingbutalsoreducedthebreedingdurationfora variety.DNAmarkerssuchasrestrictionfragmentlength polymor-phism(RFLP),simplesequencerepeat(SSR),andsinglenucleotide
polymorphism(SNP)havebeenusedinMAS,withSSRsbeingthe
mostcommonmarkerof choicedue totheirabundancein the
genome,robustness,reproducibility,andlow cost.SNPs,onthe otherhand,havenot beenusedasextensivelyin breeding pro-gramsbecause ofthedifficultyin theirdetection.Thus far,the applicationofSNPsinmarker-aidedbreedinghasentailed labori-ousandcomplicatedtechniquessuchasallele-specificPCR[10,11] orrestriction-enzymebasedmethodslikecleavedamplified poly-morphicsequence(CAPS)[12].
Inspiteofthis,theutilizationofSNPsasmolecularmarkersfor breedingisbecomingarealpossibility.SNPsmakeupthelargest
amountofDNApolymorphismintheeukaryoticgenomeandhence
canbeusedmorerationallyinmarker-basedbreeding[13–15].In rice,1.7millionSNPshavebeendetectedbycomparativeanalysis ofthedraftgenomicsequencesofcv.Nipponbare(japonica)and 93-11(indica)[16,17].Avastamountofinformationon160,000 high-qualityriceSNPsisalsonowavailableinOryzaSNP[18]and innewerdatabasesthatserveasrepositoriesforthevastamount ofinformationgeneratedfromthe3000ricegenomesproject[19]. AsforSNPdetection,modernSNPgenotypingtechniquesare enablingautomated,multi-lociallelecallinginmanysamplesat atime[13].Inrecentyears,therehasbeenashiftfromtheuse ofthemicroarrayplatformtowardstheuseofIllumina’sGolden GatetechnologyforSNPdetection[20–23].TheGoldenGate tech-nologyisbasedonallele-specificextensionandligation,andcan genotype1536SNPson96samplesinitsoriginalformat[24].This givestheadvantageofanefficient,high-throughputmarkersystem withlowercostperdatapointunlikethemicroarray-basedmethod,
whichmightbeadvantageousindetectingalargenumber(more
than40,000)ofSNPs,butistooexpensiveforbreedingpurposes.
Thehighly automatedGolden Gate-basedmethodalsorequires
onlyaminimumquantityofDNA,allowingselectionintheseedling stagebeforetransplanting.Moreimportantly,theGoldenGate sys-temofferstheadvantageofhaplotype-basedselectionbecauseit cansimultaneouslydetectappropriatenumbersofmultipleSNPs forMAS(48-1536ormoreSNPs).
Inthepresentstudy,wedevelopedaMASsystembasedonSNPs. Asafirststep,thewholegenomeSNPinformationfor31ricelines thatwereselectedfortheauthors’breedingprojectwascollected usingtheAffymetrix’sSNPmicroarray[14,25].TheSNPswithinthe genomicregionsthatarelinkedto16targetgeneswerethen con-vertedtoIllumina’sGoldenGateVeracodeoligopoolassay(OPA). ThequalityofSNPdetectionandtheapplicationoftheSNParray
forhaplotype-basedMASwereconfirmedusing24parentallines
outofthe31varieties,andearlybreedingpopulations.
2. Materialsandmethods
2.1. Plantmaterialsandtargetgenes
Thirty-one rice varieties that were selected for the authors’ breeding project, Wonder Rice Initiative for Food Security and Health(WISH)wereusedinthisstudy.WISHisabreeding pro-gramthataimstoimprovetheyieldandbioticstressresistance ofexistingricevarietiesthatarepreferentiallygrownbyfarmers fortheirinherentadaptationtoawiderangeofenvironments.The 31varietiescontainthedonorsof16targetgenesandpotential recipientvarieties,whichareleadingvarieties,high-biomass vari-eties,orvarietieswithabioticstresstolerances,and1varietywith unidentifiedinsectresistancegene(s)(Table1).
A total of 16 target genes controlling yield-related traits and pest resistanceare listedin Table2.The map positions of
Table2
TargetgenesforSNPselection.
Gene Trait ID(IRGSP)or mapped position
Chromo-some
Position References Numberofloci incustomOPA
Gn1a/OsCKX2 Highyield Os01g0197700 1 5,270,449–5,275,585 [26] 12
GW2 Seedshape Os02g0244100 2 8,120,821–8,121,387 [27] 2
Grh4 Greenrice leafhopper Resistance Tightlylinked toXNpb144 3 14,904,428–15,106,953a [28] 10
GS3 Seedshape Os03g0407400 3 16,729,501–16,735,109 [29,30] 1
Grh6 Greenrice leafhopper Resistance RM8213-C60248 4 4,290,544–4,647,693a [31] 10
pi21 Blastresistance Os04g0401000 4 19,835,206–19,836,892 [32] 1
qSW5 Seedshape Os05g0187500 5 5,360,574–5,360,727 [33] 10
bph25 Brownplant hopper resistance Tightlylinked toRM6273and RM6775 6 382,564–1,594,975a [34] 22
Ovc Ovicidalgene
toplant hoppers
Tightlylinked toR1954
6 4,737,177–5,036,025a [35] 10
APO1 Highyield Os06g0665400 6 27,480,082–27,481,450 [36] 10
Xa7 Bacterialleaf
blight resistance
RM20576 -RM340
6 28,796,789–29,000,232a [37,38] 7
WFP/OsSPL14 Highyield Os08g0509600 8 25,274,541–25,278,696 [39] 10
Xa21 Bacterialleaf
blight resistance Os11g0559200 11 20,802,978–20,806,262 [40] 9 Grh2 Greenrice leafhopper Resistance Tightlylinked toG1465 11 23,231,248–23,607,373a [28] 9
Xa4 Bacterialleaf
blight resistance R1506-S12886 11 27,822,819–28,130,150a [41] 8 Bph26 Brownplant hopper resistance Tightlylinked toRM5479 12 22,607,871–23,340,348a [34] 13
aForthegenesthatarenotcloed,theregionscoveredbytheSNPmarkersareshown.
sequenceasreference[IRGSP1,http://http://rapdb.dna.affrc.go.jp]. Thegenomicpositionsofthegenesthatarenotyetclonedwere determinedbasedonavailablepublicinformationordataobtained bytheauthors.AllelesforGW2andGS3werediscriminatedbyusing PCR-basedmethod.Allofthe31varietiescarrysmallalleleofGW2, and7varietiescarrylong-alleleofGS3.FunctionalallelesofqSW5
wereknowninnotallvarieties.Forreducingredundancy,GW2,GS3
andqSW5arenotindicatedinTable1.
2.2. DNAmicroarrayanalysis(Rice44kSNPgenotypingarray)
RicegenomicDNAwasextractedfromyoung,greenleaftissue usingtheDNeasyPlantMiniKit(QIAGEN).Hybridizationand sig-nalgenerationusingtheGeneChipRice44kSNPGenotypingArray (Affymetrix)wereconductedfollowingthemethodsof[25]. Fluo-rescenceintensitywasdetectedusingtheGeneChipScanner3000 7G.“.CEL”filescontainingsignalintensitieswereobtained.
The genotypes of the 31 varieties were called using the
ALCHEMYprogram[42]followingthemethodsof[25].
2.3. DeterminationofSNPmarkersforcustomGoldenGateassay
ToselecttheSNPmarkers tobeconverted intoGoldenGate assay,graphicalgenotypesbasedonthemicroarraydatawerefirst madevisibleusingtheFlapjackprogram[43].Thehaplotype (pat-ternofSNPs)informationfromapproximately200kbupstreamand downstreamregionsofthetargetgeneswasthencollected.SNPs withlowquality,i.e.lowcallratewereremovedandhaplotypes thatwereasuniqueaspossibletotheusefulallelesofthetarget
geneswerevisuallyselected,takingintoconsiderationthedistance tothegenepositionsandbalanceoftheminorallelefrequencies. Uptoatotalof22SNPlociwerechosenforeachtargetgene.
ThepositionsoftheselectedSNPsiteswerecorrectedbasedon thereferencesequenceavailableatIRGSP1[http://rapdb.dna.affrc. go.jp/]andflankingsequencesonthemicroarray(17+17bases)for eachSNPsiteswereverifiedusingtheinformationavailablefrom the RiceDiversity projectwebsite [http://ricediversity.org/data/ sets/44kgwas/]. Additionalflanking sequences(200+200 bases)
wereobtainedfromthereferenceNipponbaregenomeandwere
used fordesigning theGoldenGate OPA. Functional nucleotide
polymorphism(FNPs)forthegenes,GW2(2SNPs),GS3(1SNP)and
pi21(1insersion/deletion(InDel)),weredirectlyusedtodesignthe OPA.
Theassaydesigntool(ADT)providedbyIlluminawasusedto
design thecustom OPA.A totalof 143SNPs comprisethefinal
versionofthecustomOPA.
2.4. GoldenGateassay
ToverifytheprecisenessofthecustomOPA,the24varieties whichcoveredallofthe16genesandLG10,thedonorofGW2,
weregenotypedwiththeGoldenGateassayusing theIllumina
BeadXpressinstrumentfollowingthemanufacturer’sinstruction. ThesameDNAsamplesusedinthemicroarrayanalysiswereused.
GenotypeswerecalledusingtheGenomeStudioGenotyping
Mod-uleversion1.8.4(Illumina).SNPswithlowdispersioningenotype clusters(GC10lessthan0.5)wereremoved.
2.5. VerificationofthefeasibilityofcustomGoldenGateOPA usingsegregatingpopulations
ToconfirmthefeasibilityofthecustomGoldenGateOPA,3F2 populationsfromthecrossesST12xIRBB4/5/13/21,T65BPH25/26
xST12andST6xT65GRH2/4/6wereused.DNAsof 12,15 and
15plants, respectively,fromeach ofthe3F2 populationswere
extractedand genotypedusingthecustomSNParray.Usingthe
sameDNAsamples,genotypesattheGN1indel(primerpair:5
-CCTTGTCCCTTCTACAATGG-3and5-
AGTTGAGCATGAGGAGCACT-3)andRM5493([44],primerpair:5-GCGGTAACAAACCAACCAACC -3and5-AAAGCAGGACACAGTCACACAGG-3)lociofallsamples
weredeterminedby PCRand electrophoresis ofPCR amplicons
on4%agarosegel.GN1indelis locatedat5275477- 5275606bp
withinthecodingregionofGrainNumber1a(Gn1a)onrice
chromo-some1,whereasRM5493isapproximately750kbpdownstreamof
theWealthyFarmer’sPanicle(WFP)locusonchromosome8.
Con-cordancebetweenthegenotypesofsamplesgeneratedusingthe
customSNParrayand thetwo PCRmarkerswere comparedto
verifytheaccuracyoftheSNParray. 3. Results
3.1. SNPsurveyusingmicroarray
WholegenomeSNPanalysisofthe31parentalvarietiesthat werepreviouslyselectedfortheauthors’breedingprogramwas
conductedusingtheRice44kSNPGenotypingArraywhich can
detect1SNPper5kbgenomicDNA[14,25](Table1,Supplementary information1).BecausetheAffymetrix’sgenuineBRLMM-P
(Beye-sianRobustLinearModelwithMahalanobiswithperfectmatch)
basecallerprogramwasnotapplicableforriceandnotappropriate forthissmallpopulationsize,theauthorsemployedtheALCHEMY program[25,42].Usingthesameparameters(callrate>70%,minor allelefrequency>1%)fortheinformatics,acomparablenumberof high-qualitySNPs(34,985)wereobtainedinthisstudy(vs36,901 in[25]).
3.2. SelectionofSNPs
Linkage disequilibrium (LD) of SNPs within the subspecies
groupsofOryzasativahasbeenreportedtobegreaterthan500kbin
templatejaponica,150kbintropicaljaponica,and75kbpinindica [45].Thericegenomeisapproximately389Mb[46]andlinkage mapstypicallycontainapproximately1500cm[47,48].Therefore,
1cm(onerecombination per100meiosisper chromosomes)in
riceisconsideredtobeapproximately260kb.Basedonthis
con-sideration,theauthorsdefined the200kb regionupstreamand
downstreamofthetarget geneasthehaplotypeblocktoallow
selectionfortargetalleleswithsufficientprecision.Forexample,a totalof10SNPmarkersrepresentingthehaplotypeoftheWFP-ST12
allelewereselected(Fig.1).Inthesamemanner,theSNPmarkers for4otherclonedgenes,Gn1a(12SNPs),qSW5(10SNPs),APO1
(10SNPs)andXa21(9SNPs)wereselectedbygraphical genotyp-ing.Becausethecausalmutations(SNPsorinsetion/deletions)for
GW2,GS3,andpi21arealreadyknown[27,29,30,32],thesesites weredirectlyusedtodesignthecustomarray.Forgenesthatare notyetcloned,linkagemapinformationwasused.Forexample,
OvcislocatedneartheRFLPmarkerR1954onricechromosome6 [35].Therefore,thehaplotypesurroundingR1954(±200kb)was usedforthecustomarray.SNPsitesoftheremaininggeneswere consideredbasedonpubliclyavailableliteratureand additional
mappinginformationobtainedbytheauthors(datanotshown).
Usinglinkage,theaccuracyofSNPselection(markerswithin5cm) wasestimatedtobehigherthan95%.
3.3. CustomOPAdesign
SelectedSNPsfromthehaplotypeblocksofeachofthe16 tar-getgeneswereregardedasfirststepcandidatesforSNPmarkers.
ADTscoringwasconductedusingthefirststepcandidate
mark-ersandmarkerswithlowADTscore(<=0.5)werereplacedwith otherpossibleSNPs.Atotalof143sitesincluding142SNPsand1
InDelwereconvertedtoGoldenGatecustomOPA(IlluminaOPA
ID:VC0014297-OPA,Table2,Supplementaryinformation2).
3.4. ComparisonofmicroarrayandGoldenGategenotypes
IntheSNPmicroarrayanalysis,genotypecallsusingALCHEMY gaveanoutputinan[AA,AB,BB]format.TheAAindicatesanallele thatisidenticalwiththatofthereferenceNipponbaregenome. Inthepresentstudyhowever,thedataobtainedfromNipponbare containedBB.Thismaybeduetodiversitywithinthevariety prob-ablybecausethesamplewasmaintainedatNagoyaUniversity.The genotypecallsusingtheGenomeStudiosoftwarewereconverted to[AA,AB,BB]format(Supplementaryinformation3)beforethe
resultsfrommicroarray andGolden Gatearray werecompared
(Fig.2andSupplementaryinformation4).
Thecallrateoftheparentvarieties bythecustomOPA was
98.5%(Supplementaryinformation3).Thecomparisonof
haplo-types obtainedfor the WFPgene is shown in Fig.2. In the 24
varietiestested,and whenconsidering139SNPsdesignedfrom
theAffymetrixSNPmicroarray,therateofgenotypeconcordance
betweenSNPmicroarrayandGoldenGatearraywas95.2%
(Sup-plementary information 4).Thisreduced rate isbecause ofthe presenceoflow(ormedium)qualitySNPsinthecustomOPA,23 outofthe139SNPscontainedmissingdatagreaterthan10%(>2 missingdata)amongthe24varieties.ThisisremarkableintheSNPs coveringXa4gene,7outofthe8SNPsshowedconsistencyinless than16outofthe24varieties.IftheSNPsforXa4wereremoved,
theconsistencywasimprovedto97.6%.The2FNPsforGW2and
oneFNPforGS3waspreciselydetectedandcorrespondedto geno-typesobtainedbasedonPCR(datanotshown).TheFNPforpi21
(21bpInDel[32])wasnotsuccessfulinthecustomOPA.Onthe whole,theresultsindicatethatgenotypedataobtainedfromthe customGoldenGateOPAisconsistentwiththatofSNPmicroarray.
ThecustomOPAenabledhaplotype-basedorFNP-basedMASina
total14genesoutofthe16targetgenes(exceptingforpi21and
Xa4).
3.5. SNPgenotypingusingF2populations
BecauseGn1aandWFPsignificantlychangethepanicleshape [24,37]andsuitableforhaplotype-basedselectionbecausecausal mutationsarenot known,threeF2 populationsthat segregated
these 2 geneswere picked up and used for the verification of
theSNParrayin actualsegregating populations.Thegenotypes of the3 F2 populations weresummarized in Fig.3.The 4SNP
markers,id1004195toid1004310,co-segregatedwithGN1indel.
Oneoutof the15F2 plants fromT65BPH25/26xST12showed
recombinationbetweenid1004146andid1004198.One
recombi-nationwasobservedbetweenid1004230 andid1004310 inthe
ST6x IRBB4/5/13/21 F2 population. Threeout of the 27 plants
(ST12 x IRBB4/5/13/21 and T65BPH25/26 x ST12 crosses taken
together)possessedrecombinationbetweenthelikelyWFP
geno-typesandRM5493,and1recombinationwasobservedwithinthe
SNPmarkersid8006925and id8006944.We thusconcludethat
theSNPmarkersdetectedusingthecustomOPAshowedagood
co-segregationtoPCR-basedmarkersandsufficientfortheuseof MAS.
Fig.1.HaplotypesencompassingWFPgeneobtainedusingAffymetrixmicroarrayandSNPsfordesigningcustomSNParray.Schematicphysicalmapofricechromosome 8(top)andhaplotypesoftheregioncontainingWFPlocus(bottom)wereshown.CodingsequenceofWFPisfrom25,274,541bpto25,278,696bp.GenotypesfromSNPs ud8001656toid8006986wereconsideredascandidatesforSNPmarkersforWFP.TheSNPsiteswithasterisksatthebottomwereconvertedtoGoldenGatecustomOPA. GenotypesAA,BB,and–indicatethesamealleleasNipponbare,alternativealleleandmissingdata,respectively.GenotypeswithbluebackgroundareidenticaltoST12,the donorofWFP,andyellowarealternativegenotypes.(Forinterpretationofthereferencestocolorinthisfigurelegend,thereaderisreferredtothewebversionofthisarticle.)
4. Discussion
MASisacommontechniqueusedinricebreedingprograms.To
thisday,PCR-basedmarkersystemsarethemostcommonlyused
forMAS.However,thePCR-basedmarkers,incombinationwith
electrophoresishavethedisadvantageoflowthroughput.Only sev-eralmarkersatmost,couldbedetectedinonePCRreactionand conventionalelectrophoresislane.Thislimitstheapplicationofthe markersystemfor“foreground”selectiononlyofafewtargetgenes. Thepracticaluseofmultiplexmarkerhaslongbeenawaited,but itsrealizationhasbeenpreventedbythelackoftechnologythat wouldcutbothcostsandprocessingtime.Recently,“breeders”SNP arrayshavebeendevelopedforrice[20,21,22,23].Thesearraysare designedtocoverawiderangeofcrosscombinationsinrice how-ever,theyareonlysuitablefor“background”selectionandarenot targetedforspecificgenes.
Unlike thepreviouslyreported arrays [20,21,22,23],theSNP arraydeveloped inthis studycontains aSNPsettargeting spe-cificgenesofinterest,andfirstprovideaplatformforforeground
MASformultiplegenes.The95.2%matchbetweenthegenotypic
dataobtainedusingmicroarrayandthecustomGoldenGatearray iscomparablewiththepreviouslyreported82%match[14].SNP genotypingusingsegregatingF2populationsconfirmedthe accu-racyofthecustomarray.Theapproachusedinthepresentstudy canbeusedandappliedtofuturebreedingprojectsthatrequirea newsetofSNPs.Thesequencediversityofriceisbeingintensively analyzedbyvariousprojects(e.g.[19]).Therefore,thebasicSNP informationthatissimilartothosegeneratedinthisstudyusing microarraywillbeavailablethroughpublicdatabasesinthefuture.
EliminationofadditionalexperimentationforSNPdiscoverywill allowfasterdesignandfabricationofcustomarrays.
Inthisstudy,functionalnucleotidepolymorphisms(FNPs)for
GW2,GS3andpi21weredirectlyincludedinthecustomarray.The FNPsforGW2andGS3canbedetectedinthecustomarray. How-ever,FNPsformostofthetargetgenes,evenintheclonedgenes, havenotbeenidentifiedasinthecaseofWFP.WFPwascloned asagenecontrollingthenumberofprimarybranchesperpanicle, buttheFNPresponsibleforincreasednumberofprimary branch-ingremainsunknown[39].Inthiscase,itisdifficulttofindaDNA markerthatwouldsegregatewiththeusefulallele.Thehaplotype selectionapproachisusefulinsuchacasebecausetheusefulallele canbemonitoredusingasetofSNPmarkersencompassingthe tar-getloci.MultiplexedSNPmarkersareconsideredtobesuitablefor thispurpose,enablingaversatileSNParrayworkinvariouscross combinations.
TheSNParrayconstructedinthepresentstudyisusefulin con-structingasetofNILsthataresuitablefortraitevaluationbecause theSNPscanbeusedtoselectusefulallelesina widerangeof geneticbackgrounds.ThetightlylinkedsetofSNPscanalsobeused fordissecting“linkagedrag”.Inthepresentstudy,some recom-binantswithinthehaplotyperegionsweredetected(Fig.3).This indicatesthatthehaplotypesaroundthetargetgenescanbe uti-lizedforthefinegeneticdissectionofregionsnearthetargetgenes. Atypicalcaseofalinkagebetweenausefulgeneandaharmful genewasreportedin[32].Ifalargesegregatingpopulationis avail-able,theSNParraycanbereadilyusedtoconstructanNILwith
averysmallintrogressedchromosomesegmentfromthedonor
Fig.2.ComparisonofgenotypesobtainedfromAffymetrixmicroarrayandBeadXpress.SchematicphysicalmaparoundWFPlocusshowingthelocationoftheSNPmarkers (top)andcomparisonofgenotypesbetweenthosedetectedwithAffymetrixSNPmicroarray(Affy)andGoldenGatewithBeadXpress(BX)(bottom)wereshown.Genotypes AA,BB,and–indicatethesamealleleasNipponbare,alternativealleleandmissingdata,respectively.GenotypeswithbluebackgroundareidenticaltoST12,thedonorof
WFP,andyellowarealternativegenotypes.(Forinterpretationofthereferencestocolorinthisfigurelegend,thereaderisreferredtothewebversionofthisarticle.)
Thesimultaneousdetectionofusefulallelespotentiallyallows adramaticdecreaseinlaborandtimerequiredtodeveloppyramid
lines.DevelopmentofDNAmarkershasallowedgenepyramiding
(e.g.[31,34,35,49]).Intheinitialconceptofgenepyramiding, near-isogeniclines(NILs)foreachofthetargetgenesmustbegenerated beforetheconstructionofpyramidinglines[4].Thisrequiresthe laborious,repeatedselectionsandcrossingstogenerateNILs. Addi-tionaleffortisalsonecessarytocombinemultiplegenesintoone line.TheSNParrayinthisstudyhasthepotentialtocutthetime requiredtopyramidmultiplegenesintoasinglevarietyby direct-crossingofgenedonorsandMASintheprogeny.Forexample,a multi-parentadvancedgenerationinter-cross(MAGIC)population [50,51]canbedevelopedusingrelativelysimple waysof cross-ing.FromaMAGICpopulation,candidatelineswithmultipleuseful genescanbeselectedusingtheSNParray.Thelowfrequencyofthe desirablegenotypecanbeovercomebytheuseofalarge popula-tion.Inaddition,thismethodofdirectpyramidingofusefulgenes willalsocontributeinincreasingthegeneticdiversityinbreeding materials.
However,costforSNPdetectionisstillexpensiveformostof thericebreeders.CurrentlytheBeadXpressplatformcanprocess upto96samplesatatimeandthecostisstillexpensiveforuse inabreedingproject.Theselimitationsarepotentiallyproblematic whenhandlingalargesegregatingpopulation.Thedisadvantage oftheGoldenGatesystemisinitshighinitialcostandlow flexi-bility.Althoughthecostfor1genotypepersampleiscomparable toPCR-basedmethods(datanotshown),theonepurchaseofOPA becomesquiteexpensive(∼$10,000)andnotacceptableformost ofthelocalbreeders.However,thepotentialofSNPmarkersfor
automatedandsimultaneousdetectionmustbeadvantageousand
willbeexpanded.Itisexpectedthatabovelimitationwillbecleared bytheuseofnext-generationsequencers(NGS).However,the
tar-getedSNPdetectionwithNGSstill needsa complicatedsample
preparationmethod[52].Ontheotherhand,oneoftheNGS-based genotypingmethods,genotypingbysequencing(GBS)isbecoming common(e.g.[53]).GBSenablesmultiplexinginbothsamplesand markers(upto768samplesandhundredstothousandsofmarkers in1NGSrun)butisnotsuitablefortargetingusefulSNPs.Itisstill necessaryforgeneticistsandbreederstochooseasuitable genotyp-ingplatformintheirbreedingproject.WideuseoftheGoldenGate arraymightbelimitedbecauseofthecostproblem,sotheSNParray willbeusedformonitoringwhetherthenewlydevelopedlines pos-sessessomeofusefulalleleornot,whichisinformativeforfurther
genepyramidingandMAS.
Toenhancericeproductionbynewvarieties,developmentof actualplantmaterialssuchasNILsisrequiredtoverifytheeffects ofyield-improvinggenes.Itshouldbeconsideredthattheeffect
of yield-enhancinggenes suchas Gn1a[26],WFP [39] or APO1
[36],arenotconfirmedyetinothergeneticbackgroundandactual farmer’s field. Therefore, these potential yield-improvinggenes shouldbetestedinvariousgeneticbackgrounds.The“NewPlant Type”approach[54]wasbasedontheconceptofincreasingthe
“sink size”, and the aforementioned yield enhancinggenes are
consideredtobeassociatedwithsinksize.Furthermore,a gene for increasingrice “source” ability have beenrecentlyreported [55]. Currently, scientistshave a good technologyfor MAS, but effortsonactualmaterialdevelopmentarelimited.Thebreeding projectWonderRiceInitiativeforFoodSecurityandHealth(WISH) waslaunchedbytheauthors’group,asanefforttoprovide pre-varietiestoricescientistsandbreedersworldwide.Inthisproject,
Fig.3.Confirmationofco-segregationbetweenSNPmarkersasdetectedusingBeadXpressandPCR-basedmarkers.GenotypesofindividualF2plantsobtainedfrom
T65BPH25/26xST12,ST6xT65GRH2/4/6andST12xIRBB4/5/13/21,andparentswereshownontheright.LocationsofGn1aandWFPandDNAmarkersareshownas physicalmapsontheleft.GenotypesAA,BB,and–inidicatethesamealleleasNipponbare,alternativealleleandmissingdata,respectively.Genotypeswithbluebackground areidenticaltoST12orST6,yellowarealternativeallele,andgreenareheterozygous.(Forinterpretationofthereferencestocolorinthisfigurelegend,thereaderisreferred tothewebversionofthisarticle.)
theauthorsenvisionincorporatingmultipleusefulgenes(Table2) torecipient varieties (Table1) and generatingpre-varieties for distribution.The anticipated pre-varieties contain two types of materials:(1)breedingmaterialswithuniformbackgrounds(i.e. setsofNILs/pyramidlineswithmultiplebackgrounds)thatprovide moreconveniencetoricebreedersbecausetheycanevaluatethe effectofincorporatedgenesontheirownbreedingsites,(2)single linewithmanyusefulgenes(i.e.highly-pyramidedlines)thatwill beconvenientlyusedbecausemultiplegenescanbeincorporated totargetvarietieswithasinglecross,and(3)theSNPinformation forusefulgeneswillbeavailable.TheversatileSNParray devel-opedinthisstudywilllargelycontributeinfacilitatingthebreeding activity.BothplantmaterialsandSNParrayswillbemadeavailable tohelpimprovevarietiesthatareadaptedtovariousregionsinthe world.
Acknowledgments
ThisworkwassupportedinpartbytheSATREPSprojects
“Devel-opmentof cropgenotypesfor midlandsand mountainareas of
northVietnam”and“Improvementinproductivityandyield
stabil-ityofriceunderKenya’sbioticandabioticstressconditionsthrough
tailor-madebreedinganddevelopmentofcultivationmethods”,
and NationalBio-Resource ProjectforRice.Theauthorsexpress theirheartfeltgratitudetoProfessorsMakotoMatsuoka,Hidemi
Kitano, Mr. Nobuhiko Hanazato and JICA staffs for supporting
the WISHproject. The authorsthank Drs. Chi-Wei Tung,Mark
“Koni”WrightandSusanMcCouchfortheirkindinstructioninSNP microarrayanalysis.
AppendixA. Supplementarydata
Supplementarydataassociatedwiththisarticlecanbefound,in theonlineversion,athttp://dx.doi.org/10.1016/j.plantsci.2015.09. 008.
References
[1]H.C.J.Godfray,J.R.Beddington,I.R.Crute,L.Haddad,D.Lawrence,J.F.Muir,J. Pretty,S.Robinson,S.M.Thomas,C.Toulmin,Foodsecurity:thechallengeof feeding9billionpeople,Science327(2010)812–818.
[3]R.Huang,L.Jiang,J.Zheng,T.Wang,H.Wang,Y.Huang,Z.Hong,Geneticbasis ofricegrainshape:somanygenes,solittleknown,TrendsPlantSci.18(2013) 218–226.
[4]M.Ashikari,M.Matsuoka,Identification,isolationandpyramidingof quantitativetraitlociforricebreeding,TrendsPlantSci.11(2006)344–350. [5]K.Miura,M.Ashikari,M.Matsuoka,TheroleofQTLsinthebreedingof
high-yieldingrice,TrendsPlantSci.16(2011)319–326.
[6]M.Ikeda,K.Miura,K.Aya,H.Kitano,M.Matsuoka,Genesofferingthe potentialfordesigningyield-relatedtraitsinrice,Curr.Opin.PlantBiol.16 (2013)213–220.
[7]X.Wang,S.Lee,J.Wang,J.Ma,T.Bianco,Y.Jia,Currentadvancesongenetic resistancetoriceblastdisease,in:W.Yan,J.Bao(Eds.),Rice—Germplasm, GeneticsandImprovement,InTech,Rijeka,2014,pp.195–217.
[8]M.A.Khan,M.Naeem,M.Iqbal,Breedingapproachedforbacterialleafblight resistanceinrice(OryzasativaL.),currentstatusandfuturedirection,Eur.J. PlantPathol.139(2014)27–37.
[9]G.He,B.Du,R.Chen,Insectresistance,in:Q.Zhang,R.A.Wing(Eds.),Genetics andGenomicofRice,Springer,NewYork,2013,pp.177–192.
[10]C.R.Newton,A.Graham,L.E.Heptinstall,S.J.Powell,C.Summers,N.Kalsheker, J.C.Smith,A.F.Markham,AnalysisofanypointmutationinDNA.The amplificationrefractorymutationsystem(ARMS),Nucl.AcidsRes.17(1989) 2503–2516.
[11]K.Hayashi,N.Hashimoto,M.Daigen,I.Ashikawa,DevelopmentofPCR-based SNPmarkersforriceblastresistancegenesatthePizlocus,Theor.Appl. Genet.108(2004)1212–1220.
[12]A.Konieczny,F.M.Ausubel,AprocedureformappingArabidopsismutations usingco-dominantecotype-specificPCR-basedmarkers,PlantJ.4(1993) 403–410.
[13]S.R.McCouch,K.Zhao,M.Wright,C.W.Tung,K.Ebana,M.Thomson,A. Reynolds,D.Wang,G.DeClearck,M.L.Ali,A.McClung,G.Eizenga,C. Bustamante,Developmentofgenome-wideSNPassaysforrice,Breed.Sci.60 (2010)524–535.
[14]C.W.Tung,K.Zhao,M.H.Wright,M.L.Ali,J.Jung,J.Kimball,W.Tyagi,M.J. Thomson,K.McNally,H.Leung,H.Kim,S.N.Ahn,A.Reynolds,B.Scheffler,G. Eizenga,A.McClung,C.Bustamante,S.R.McCouch,Developmentofaresearch platformfordissectingphenotype-genotypeassociationsinrice(Oryzaspp.), Rice3(2010)205–217.
[15]X.Huang,X.Wei,T.Sang,Q.Zhao,Q.Feng,Y.Zhao,C.Li,C.Zhu,T.Lu,Z.Zhang, M.Li,D.Fan,Y.Guo,A.Wang,L.Wang,L.Deng,W.Li,Y.Lu,Q.Weng,K.Liu,T. Huang,T.Zhou,Y.Jing,W.Li,Z.Lin,E.S.Buckler,Q.Qian,Q.F.Zhang,J.Li,B. Han,Genome-wideassociationstudiesof14agronomictraitsinrice landraces,Nat.Genet.42(2010)961–967.
[16]F.A.Feltus,J.Wan,S.R.Schulze,J.C.Estill,N.Jiang,A.H.Paterson,ASNP resourceforricegeneticsandbreedingbasedonsubspeciesindicaand
japonicagenomealignments,GenomeRes.14(2004)1812–1819.
[17]Y.J.Shen,H.Jiang,J.P.Jin,Z.B.Zhang,B.Xi,Y.Y.He,G.Wang,C.Wang,L.Qian, X.Li,Q.B.Yu,H.J.Liu,D.H.Chen,J.H.Gao,H.Huang,T.L.Shi,Z.N.Yang, Developmentofgenome-wideDNApolymorphismdatabaseformap-based cloningofricegenes,PlantPhysiol.135(2004)1198–1205.
[18]K.L.McNally,K.L.Childs,R.Bohnert,R.M.Davidson,K.Zhao,V.J.Ulat,G.Zeller, R.M.Clark,D.R.Hoen,T.E.Hoen,T.E.Bureau,R.Stokowski,D.G.Ballinger,K.A. Frazer,D.R.Cox,B.Padhukasahasram,C.D.Bustamante,D.Weigel,D.J.Mackill, R.M.Bruskiewich,G.Ratsch,C.R.Buell,H.Leung,J.E.Leach,GenomewideSNP variationrevealsrelationshipsamonglandracesandmodernvarietiesofrice, Proc.Nat.Acad.Sci.U.S.A.106(2009)12273–12278.
[19]The3000ricegenomesproject,The3000ricegenomesproject,GigaScience3 (2014)7.
[20]H.HeH.Chen,W.ChenY.Zou,X.LiuR.Yu,Y.M.GaoY.Yang,L.M.FanJ.L.Xu, Y.Li,X.W.DengZ.K.Li,Developmentandapplicationofasetof
breeder-friendlySNPmarkersforgeneticanalysesandmolecularbreedingof rice(OryzasativaL.),Theor.Appl.Genet.123(2011)869–879.
[21]M.J.Thomson,K.Zhao,M.Wright,K.L.McNally,J.Rey,C.W.Tung,A.Reynolds, B.Scheffler,G.Eizenga,A.McClung,H.Kim,A.M.Ismail,M.D.Ocampo,C. Mojica,M.Y.Reveche,C.J.Dilla-Ermita,R.Mauleon,H.Leung,C.Bustamante, S.R.McCouch,High-throughputsinglenucleotidepolymorphismgenotyping forbreedingapplicationsinriceusingtheBeadXpressplatform,Mol.Breed. 29(2012)875–886.
[22]H.Chen,W.Xie,H.He,H.Yu,W.Chen,J.Li,R.Yu,Y.Yao,W.Zhang,Y.He,X. Tang,F.Zhou,X.WangDeng,Q.Zhang,Ahigh-densitySNPgenotypingarray forricebiologyandmolecularbreeding,Mol.Plant7(2014)541–553. [23]H.Yu,W.Xie,J.Li,F.Zhou,Q.Zhang,Awhole-genomeSNParray(RICE6K)for
genomicbreedinginrice,PlantBiotech.J.12(2014)28–37.
[24]R.Shen,J.B.Fan,D.Campbell,W.Chang,J.Chen,D.Doucet,J.Yeakley,M. Bibikova,G.E.Wickham,C.McBride,F.Steemers,F.Garcia,B.G.Kermani,K. Gunderson,A.Oliphant,high-throughputSNPgenotypingonuniversalbead arrays,Mutat.Res.573(2005)70–82.
[25]K.Zhao,C.W.Tung,G.C.Eizenga,M.H.Wright,M.L.Ali,A.H.Price,G.J.Norton, M.R.Islam,A.Reynolds,J.Mezey,A.M.McClung,Genome-wideassociation mappingrevealsarichgeneticarchitectureofcomplextraitsinOryzasativa, Nat.Commun.2(2011)467.
[26]M.Ashikari,H.Sakakibara,S.Lin,T.Yamamoto,T.Takashi,A.Nishimura,E.R. Angeles,Q.Qian,H.Kitano,M.Matsuoka,Cytokininoxidaseregulatesrice grainproduction,Science309(2005)741–745.
[27]X.J.Song,W.Huang,M.Shi,M.Z.Zhu,H.X.Lin,AQTLforricegrainwidthand weightencodesapreviouslyunknownRING-typeE3ubiquitinligase,Nat. Genet.39(2007)623–630.
[28]S.Yazawa,H.Yasui,A.Yoshimura,N.Iwata,RFLPmappingofgenesfor resistancetogreenriceleafhopper(NephotettixcincticepsUhler)inrice cultivarDV85usingnearisogeniclines,Sci.Bull.Fac.Agric.KyushuUniv.52 (1998)169–175.
[29]C.Fan,Y.Xing,H.Mao,T.Lu,B.Han,C.Xu,X.Li,Q.Zhang,GS3,aMajorQTLfor grainlengthandweightandminorQTLforgrainwidthandthicknessinrice, encodesaputativetransmembraneprotein,Theor.Appl.Genet.112(2006) 1164–1171.
[30]N.Takano-Kai,H.Jiang,T.Kubo,M.Sweeney,T.Matsumoto,H.Kanamori,B. Padhukasahasram,C.Bustamante,A.Yoshimura,K.Doi,S.McCouch, EvolutionaryhistoryofGS3,ageneconferringgrainlengthinrice,Genetics 182(2009)1134–1323.
[31]D.Fujita,A.Yoshimura,H.Yasui,Developmentofnear-isogeniclinesand pyramidedlinescarryingresistancegenestogreenriceleafhopper (NephotettixcincticepsUhler)withtheTaichung65geneticbackgroundinrice (OryzasativaL.),BreedingSci60(2010)18–27.
[32]S.Fukuoka,N.Saka,H.Koga,K.Ono,T.Shimizu,K.Ebana,N.Hayashi,A. Takahashi,H.Hirochika,K.Okuno,M.Yano,Lossoffunctionofa
proline-containingproteinconfersdurablediseaseresistanceinrice,Science 325(2009)998–1001.
[33]T.Shomura,K.Izawa,T.Ebana,H.Ebitani,S.Kanegae,M.Y.Konishi,ano, Deletioninageneassociatedwithgrainsizeincreasedyieldsduringrice domestication,Nat.Genet.40(2008)1023–1028.
[34]D.Myint,M.Fujita,T.Matsumura,A.Sonoda,H.YoshimuraYasui,Mapping andpyramidingoftwomajorgenesforresistancetothebrownplanthopper (Nilaparvatalugens[Stål])inthericecultivarADR52,Theor.Appl.Genet.124 (2011)495–504.
[35]M.Yamasaki,A.Yoshimura,H.Yasui,Geneticbasisofovicidalresponseto whitebackedplanthopper(SogatellafurciferaHorváth)inrice(OryzasativaL.), Mol.Breed.12(2003)133–143.
[36]T.Terao,K.Nagata,K.Morino,T.Hirose,Agenecontrollingthenumberof primaryrachisbranchesalsocontrolsthevascularbundleformationand henceisresponsibletoincreasetheharvestindexandgrainyieldinrice, Theor.Appl.Genet.120(2010)875–893.
[37]B.W.Porter,J.M.Chittoor,M.Yano,T.Sasaki,F.F.White,developmentand mappingofmarkerslinkedtothericebacterialblightresistancegeneXa7, CropSci.43(2003)1484–1492.
[38]Y.Zhang,J.Wang,J.Pan,Z.Gu,X.Chen,Y.Jin,F.Liu,H.Zhang,B.Ma, Identificationandmolecularmappingofthericebacterialblightresistance geneallelictoXa7fromaneliterestorerlineZhenhui084,Eur.J.PlantPathol. 125(2009)235–244.
[39]K.Miura,M.Ikeda,A.Matsubara,X.J.Song,M.Ito,K.Asano,M.Matsuoka,H. Kitano,M.Ashikari,OsSPL14promotespaniclebranchingandhighergrain productivityinrice,Nat.Genet.42(2010)545–549.
[40]W.Y.Song,G.L.Wang,L.L.Chen,H.S.Kim,L.Y.Pi,T.Holsten,J.Gardner,B. Wang,W.X.Zhai,L.H.Zhu,C.Fauquet,P.Ronald,Areceptorkinase-like proteinencodedbythericediseaseresistancegene,Xa21,Science270(1995) 1804–1806.
[41]X.Sun,Z.Yang,S.Wang,Q.Zhang,Identificationofa47-kbDNAfragment containingXa4,alocusforbacterialblightresistanceinrice,Theor.Appl. Genet.106(2003)683–687.
[42]M.H.Wright,C.W.Tung,K.Zhao,A.Reynolds,S.R.McCouch,C.D.Bustamante, ALCHEMY:areliablemethodforautomatedSNPgenotypecallingforsmall batchsizesandhighlyhomozygouspopulations,Bioinformatics26(2010) 2952–2960.
[43]I.Milne,P.Shaw,G.Stephen,M.Bayer,L.Cardle,W.T.B.Thomas,A.J.Flavell,D. Marshall,Flapjack—graphicalgenotypevisualization,Bioinformatics26 (2010)3133–3134.
[44]S.R.McCouch,L.Teytelman,Y.Xu,K.B.Lobos,K.Clare,M.Walton,B.Fu,R. Maghirang,Z.Li,Q.Zhang,I.Kono,M.Yano,R.Fjellstrom,G.DeClerck,D. Schneider,S.Cartinhour,D.Ware,L.Stein,Developmentandmappingof2240 newSSRmarkersforrice(OryzasativaL.),DNARes.9(2002)199–207. [45]K.A.Mather,A.L.Caicedo,N.R.Polato,K.M.Olsen,S.R.McCouch,M.D.
Purugganan,Theextentoflinkagedisequilibriuminrice(OryzasativaL.), Genetics177(2007)2223–2232.
[46]TheInternationalRiceGenomeSequencingProject,Themap-basedsequence ofthericegenome,Nature436(2005)793-800.
[47]M.A.Causse,T.M.Fulton,Y.G.Cho,S.N.Ahn,J.Chunwongse,K.Wu,J.Xiao,Z. Yu,P.C.Ronald,S.E.Harrington,Saturatedmolecularmapofthericegenome basedonaninterspecificbackcrosspopulation,Genetics138(1994) 1251–1274.
[48]Y.Harushima,M.Yano,A.Shomura,M.Sato,T.Shimano,Y.Kuboki,T. Yamamoto,S.Y.Lin,B.A.Antonio,A.Parco,H.Kajiya,N.Huang,K.Yamamoto, Y.Nagamura,N.Kurata,G.S.Khush,T.Sasaki,Ahigh-densityricegenetic linkagemapwith2275MarkersUsingasingleF2population,Genetics148 (1998)479–494.
[49]N.Huang,E.R.Angeles,J.Domingo,G.Magpantay,S.Singh,G.Zhang,N. Kumaravadivel,J.Bennett,G.S.Khush,Pyramidingofbacterialblight resistancegenesinrice:marker-assistedselectionusingRFLPandPCR,Theor. Appl.Genet95(1997)313–320.
[50]P.X.Kover,W.Valdar,J.Trakalo,N.Scarcelli,I.M.Ehrenreich,M.D. Purugganan,C.Durrant,R.Mott,Amultiparentadvancedgeneration inter-crosstofine-mapquantitativetraitsinArabidopsisthaliana,PLoS Genet.5(2009)e1000551.
[51]N.Bandillo,C.Raghavan,P.A.Muyco,M.A.L.Sevilla,I.T.Lobina,C.J.D.Ermita, C.W.Tung,S.McCouch,M.Thomson,R.Mauleon,R.K.Singh,G.Gregorio,E.
Redona,H.Leung,Multi-parentadvancedgenerationinter-cross(MAGIC) populationsinrice:progressandpotentialforgeneticsresearchandbreeding, Rice6(2013)11.
[52]J.W.Davey,P.A.Hohenlohe,P.D.Etter,J.Q.Boone,J.M.Catchen,M.L.Blaxter, Genome-widegeneticmarkerdiscoveryandgenotypingusing
next-generationsequencing,Nat.Rev.Genet.12(2011) 499–510.
[53]J.Spindel,M.Wright,C.Chen,J.Cobb,J.Gage,S.Harrington,M.Lorieux,N. Ahmadi,S.McCouch,Bridgingthegenotypinggap:usinggenotypingby sequencing(GBS)toaddhigh-densitySNPmarkersandnewvalueto
traditionalbi-parentalmappingandbreedingpopulations,Theor.Appl. Genet.126(2013)2699–2716.
[54]G.S.Khush,Greenrevolution:thewayforward,Nat.Rev,Genet.2(2001) 815–822.
[55]T.Takai,S.Adachi,F.Taguchi-Shiobara,Y.Sanoh-Arai,N.Iwasawa,S. Yoshinaga,S.Hirose,Y.Taniguchi,U.Yamanouchi,J.Wu,T.Matsumoto,K. sugimoto,K.Kondo,T.Ikka,T.Ando,I.Kono,S.Ito,A.Shomura,T.Ookawa,T. Hirasawa,AnaturalvariantofNAL1,selectedinhigh-yieldricebreeding programs,pleiotropicallyincreasesphotosynthesisrate,Sci.Rep.3(2013), 2149.