漆小泉植物代谢组学及其应用课件

CenterforSignalTransduction&Metabolomics漆小泉中国科学院植物研究所植物分子生理重点实验室植物代谢组学及其应用CenterforSignalTransductionCenterforSignalTransduction&MetabolomicsCenterforSignalTransductionAlkaloidsAminesCyanogenicglycosidesGlucosinolatesMonoterpenesSesquiterpenesNon-proteinaminoacidsDiterpenesTriterpenes,steroidsFlavonoidsPolyketidesPolyacetylenes,fattyacids,waxes植物合成二十多万种不同的化合物

（主要为次生代谢物）AlkaloidsAminesCyanogenicglycCenterforSignalTransduction&Metabolomics植物次生代谢物合成的模式BackboneEarlystepFinalproductP450s,GTs,etcCenterforSignalTransductionCenterforSignalTransduction&Metabolomics植物产生次生代谢物适应不良自然环境PollinationandseeddispersalScentsColoursFlavoursChemicaldefencePestsPathogensAllelopathyCenterforSignalTransductionCenterforSignalTransduction&Metabolomics次生代谢与植物发育有着不可分割的联系SpearmintGlandulartrichomesThymeTrichomes–monoterpenesandsesquiterpenesLemonSecretorycavityCenterforSignalTransductionCenterforSignalTransduction&Metabolomics次生代谢物是很多中药的主要成分TraditionalChineseMedicinesNaturalproductsasdrugsCenterforSignalTransduction人体需要的特殊营养物质主要来源于植物异黄酮(植物雌激素)维生素E叶酸b-胡萝卜素人体需要的特殊营养物质主要来源于植物异黄酮维生素E叶酸bCenterforSignalTransduction&Metabolomics维生素A缺乏导致眼睛疾病。我国儿童VA缺乏率达9.3%维生素C缺乏导致坏血病维生素缺乏导致人体多种疾病的发生维生素E缺乏导致皮肤病、早衰等叶酸缺乏导致新生儿神经系统疾病、贫血等CenterforSignalTransduction生长发育适应不良环境人体必需营养成分药用化合物b-胡萝卜素GA1BrStrigolactone植物萜类代谢物具有重要功能和作用生长发育适应不良环境人体必需营养成分药用化合物b-胡萝卜素GCenterforSignalTransduction&MetabolomicsFromWink,M.Phytochemistry64:3(2003)QuinolizidinealkaloidsSteroidalalkaloidsMono-andsesqui-terpenes次生代谢多样性的特点——特定的种属合成并积累特异的代谢物CenterforSignalTransductionArabidopsis–ModelplantCropsYeast-ModelunicellulareukaryoteChineseherbsandotherplantspecies(>250,000)Referencespecies基因组、代谢组学研究加快代谢途径的解析Arabidopsis–CropsYeast-ChinCenterforSignalTransduction&MetabolomicsMetabolomicsisanew“omics”.Thenamemetabolomicswascoinedinthe1990s:ThefirstpaperusingthewordmetabolomeisOliver,S.G.,Winson,M.K.,Kell,D.B.&Baganz,F.(1998).Systematicfunctionalanalysisoftheyeastgenome.TrendsBiotechnol.16(9):373-8Thenameisgiventothevarietyoftechniquesusedtorecognisepatternsinthechemicalspresentinbiologicalsamplesinordertodeciphertheirsignificance.

代谢组学（Metabolomics）CenterforSignalTransductionCenterforSignalTransduction&MetabolomicsMetabolomicsistheanalysisofthetotalpopulationofmetabolitesinagivensample,cellortissueandtheintegrationofthedatainthecontextoffunctionalgenomicsgenomicstranscriptomicsproteomicsmetabolomicsCombiningallthe“omics”datawillprovideaclearerunderstandingofcellbiology.代谢组学（Metabolomics）CenterforSignalTransductionTraitsDNARNAProteinsMetabolitesNH2OHOOHOHOHOHOHOOHPhenomicsGenomicsTranscriptomicsProteomics

Metabolomics

从组学到分子系统生物学From漆小泉等《植物代谢组学-方法与应用》2011年TraitsDNARNAProteinsMetaboliteCenterforSignalTransduction&MetabolomicsMetabolomicsresearchisparticularlyimportantintheplantfieldbecausecollectivelyproduceahugevarietyofchemicalcompounds,farmorethananimalsandevenmicroorganism.Otherareasofimpact:environmentalgenomicsfoodquality,diagnosticsinterorganismsignallingbioactivecompounds植物代谢组学更具有挑战性CenterforSignalTransductionCenterforSignalTransduction&MetabolomicsNosinglemethodcanbeusedtodetectthewholepopulationofmetabolitesThechoiceofinitialextractionsolventimmediatelylimitstheclassesofmetabolitesextractedbaseduponpolarityNospectroscopymethod,currentlyavailable,isideallysuitedtothedetectionofeverymetabolite.AvarietyofanalyticalmethodsshouldbeusedandthedataintegratedinordertogaininformationonasmanymetabolitesaspossibleDatagainedfromavarietyofmethodsneedstobeintegrated.Metabolomics:theneedtointegratedatafromseveralplatformstoincreasecoverageMetaboliteidentityHighthroughputGlobalmetabolitefingerprintFT-IRFT-NMRESI-MSFT-MSCE-MSGC-MSLC-MSCenterforSignalTransductionCenterforSignalTransduction&MetabolomicsMassSpectrometryEquipmentAvailableinTheNationalCentreforPlantandMicrobialMetabolomics,UKThermoFinniganLCQLC-MSWatersGC-MSAccuratemassGC-MSAgilentGC-MSThermoFinniganGCQGC-MSThermoFinniganMaT95XPWatersQ-TOFWatersMaldi-TOFLecoPegasusTOFFastScanningGC-MS(boughtunderMeT-RO)FromMikeBealeCenterforSignalTransductionCenterforSignalTransduction&Metabolomics600MHzNMRMagnetBACSsamplechangerBrukerEsquire3000MassspectrometerBNMIinterfaceDADdetectorHPLCSparkIISPEUnit2XFOXYFractionCollectors600MHzHyphenatedLC-SPE-NMR-MSsystemTheNationalCentreforPlantandMicrobialMetabolomics,UKFromMikeBealeCenterforSignalTransductionGC-TOF/MSUPLC-Q-TOF/MSGC-QQQ/MS段礼新博士(Res.Assistant)漆小泉(TeamLeader)薛震(Tech.Assistant)韩彬博士(Tech.Assistant)样品前处理数据分析IB-CASaimstoestablishanadvanceplantmetabolomicsplatformandnetworkinChinaGC-TOF/MSUPLC-Q-TOF/MSGC-QQQ/M海量质谱数据分析软件的开发开发了Pmass质谱分析软件，用分布式并行的方式加速了GC-MS数据的峰对齐和定量速度。使用目前广泛使用的GC-MS数据分析软件XCMS处理1200个样本需要时近90天，而使用Pmass软件只需2-3天。(杨辉华，任洪军，李灵巧，段礼新，郭拓，杜玲玲，漆小泉（2013）基于Sector/Sphere平台的GC-MS多样本并行对齐算法实现.《计算机应用》33(1):inPress,与桂林电子科技大学的合作研究）水稻代谢物化合物库及质谱数据库的建立通用化合物纯品：230种植物甾醇及萜醇：116种质谱数据库：230+116+>200=>900种IB-CASaimstoestablishanadvanceplantmetabolomicsplatformandnetworkinChina海量质谱数据分析软件的开发水稻代谢物化合物库及质谱数据库的建Rawdataprocession(MStopeaks)Biologicalannotation(pathwayandnetwork)Multivariateanalysis

(findfeatureandmarkers)DeconvolutionDataformatconvertAlignmentQuantitativeSmoothingDenoisngPeakdetectionCalibrationbyISandweightPCA:principlecomponentsanalysisPLS-DA:partialleastsquares-discriminateanalysis

OPLS-DA:OrthogonalPLS-DAHCA:hierarchicalclusteranalysis

CA:correlationanalysisANOVA:analysisofvarianceT-testPeakidentificationPathwayanalysisMetabolicnetworkIntegratewithother“–omic”dataNormalizationMetabolomicsdataanalysisworkflowRawdataprocessionBDatapre-processionTOF/MSRawdataDeconvolutionAlignmentDatamatrixQuantitativeDatacalibrationDatapre-processionTOF/MSRawdMultivariateanalysisNon-supervisedSupervisedPCAHCAPLS-DAOPLS-DAPrincipleofPCAScoreplotLoadingplotvMultivariateanalysisNon-superPathwayandnetworkanalysisThemainmetabolicmapMetabolicnetworkPathwayandnetworkanalysisThMetabolomicsdatabasesMetaCyc:genes,proteins,compounds,reactionandpathways.Compounds(MassandNMR)databaseMetabolomicsdatabasesMetaCyc:漆小泉植物代谢组学及其应用ppt课件植物代谢组学的应用基因功能解析代谢途径及代谢网络调控机理植物与生物逆境和非生物逆境互作研究作物的产量作物营养成分及品质等基因功能解析植物代谢组学的应用鉴别标识化合物代谢途径的构建代谢调控网络的构建鉴别标识化合物CenterforSignalTransduction&Metabolomics中药种类繁多，资源丰富，来源复杂，品种混杂严重。2000年版药典收载的534种中药材，即有143种为多基源(二基源以上),占收载总数的27%。中药材基源品种的真伪，关系到该味中药的确切疗效和疗效的重现性，进而直接影响到中药制剂的质量，是实现中药现代化的首要问题。长期的医疗实践发现即使是同种药材，由于产地不同、野生与栽培以及生长年限不同都表现出质量和疗效上的差异，这些问题为中药材鉴别方法提出了新的挑战。中药黄芪的鉴别CenterforSignalTransduction中药黄芪的鉴别材料选取膜荚黄芪：Astragalusmembranaceus(Fisch.)Bunge蒙古黄芪：Astragalusmemeranaceus(Fisch.)Bge.var.mongholicus(Bge.)Hsiao肖培根等（1965）认为蒙古黄芪是膜荚黄芪的变种。CenterforSignalTransduction&Metabolomics分析手段ＤＮＡ分子标记技术：ＡＦＬＰ代谢组学分析技术：ＧＣ-ＴＯＦ/MS编号品种地理位置种植方式１膜荚黄芪吉林四平种植２膜荚黄芪吉林通化种植３膜荚黄芪甘肃魏源野生４膜荚黄芪甘肃漳县野生５蒙古黄芪甘肃陇西种植６蒙古黄芪山西浑源种植７蒙古黄芪甘肃漳县种植８蒙古黄芪山西应县野生材料来源中药黄芪的鉴别材料选取CenterforSignalTCenterforSignalTransduction&MetabolomicsClusterofgenetic（Ａ）andmetabolicfingerprinting（Ｂ）蒙古黄芪膜荚黄芪（甘肃）膜荚黄芪（吉林）蒙古黄芪膜荚黄芪中药黄芪的鉴别CenterforSignalTransductionCenterforSignalTransduction&Metabolomics中药黄芪的鉴别OPLS分析CenterforSignalTransductionCenterforSignalTransduction&Metabolomics区分膜荚黄芪和蒙古黄芪标识物的选取(OPLS)V-plotLoadingplot中药黄芪的鉴别CenterforSignalTransduction初步鉴定出21个标识物indexrt(min)VIPnamechinesenameMW-UROC-AUCp24927.37211.41691Galactose半乳糖3.70E-099.97E-01p5410.18121.94196Malonicacid丙二酸2.88E-091.00E+00p39239.08291.68164Maltose麦芽糖2.30E-089.70E-01p11215.22621.49712L-ThreonineL-苏氨酸

6.72E-079.18E-01o70344.05671.59318Stigmasterol豆甾醇7.38E-089.53E-01p38238.48291.99751Sucrose蔗糖7.70E-099.55E-01o57435.01171.337081-Monohexadecanoylglycerol1-单棕榈酸甘油酯6.90E-058.35E-01o34320.76921.72885Azelaicacid壬二酸1.30E-070.944444o42825.82331.91289Hexadecanoicacid棕榈酸(16酸)5.42E-080.955729o47228.80921.53552linoleicacid亚油酸3.49E-068.90E-01o10910.29671.60082OctanoicaciD辛酸（8碳酸）6.04E-070.920139p17721.05291.43659L-GlutamicacidL-谷氨酸6.95E-068.78E-01o10810.27581.46575Ethanolamine乙醇胺1.14E-060.909722o47428.92831.479789-(Z)-Octadecenoicacid9-顺-十八烯酸1.04E-070.947917o23314.88581.414414-Amino-Butanoicacidγ－氨基丁酸4.87E-070.923611o33319.97671.64515L-Glycerol-3-phosphate3-磷酸-甘油酯3.70E-090.996528o15711.99671.6474L-Homoserine高丝氨酸2.91E-080.967014p22825.41541.54198Ornithine瓜氨酸2.03E-079.38E-01o12410.85751.34682L-Proline脯氨酸2.30E-080.970486p23025.54461.81697Citricacid柠檬酸1.42E-089.77E-01o29317.91921.49245L-Asparagine天冬酰胺3.70E-090.996528中药黄芪的鉴别初步鉴定出21个标识物indexrt(min)VIPnameCenterforSignalTransduction&Metabolomics产地和种植方式的差别（ＰＣＡ）膜荚黄芪：产地和种植方式叠加效果蒙古黄芪：产地因素>种植方式因素中药黄芪的鉴别Duan

etal(2012)MolPlant5:376

CenterforSignalTransductionCenterforSignalTransduction&Metabolomics代谢途径分析代谢物含量比值较高代谢物含量比值较低膜荚黄芪/蒙古黄芪萜类,甾类,胡萝卜素芳香化合物,木质素,黄酮胆碱,喹啉脂肪簇氨基酸生物碱Glc1PUDP-Glc多糖脂肪酸多胺生物碱中药黄芪的鉴别Duan

etal(2012)MolPlant5:376

CenterforSignalTransductionCenterforSignalTransduction&Metabolomics代谢组学技术能够快速区分两种黄芪，能综合反映生长环境与基因相互作用的影响。利用OPLS模型鉴定了21个代谢差异物质。由于只使用了GC-TOF/MS分析平台，不能检测到黄芪的有效成分，如黄酮类、三萜苷类、多糖类等代谢物。应使用多平台整合分析手段。中药黄芪的鉴别CenterforSignalTransduction.DiterpenequinonesknownastanshinonesandphenolicacidderivativessuchassalvianolicacidarethemainbioactivecomponentsofS.miltiorrhiza.

Morethan100compoundshaveisolatedfromDanshen,whilehalfofthemarediterpenes.Theyhavebeenfoundtohaveavarietyofpharmaceuticalactivities,includingantibacterial,antiinflammatory,andanticancerproperties.解析丹参二萜代谢途径.DiterpenequinonesknownastCPS1istheonlyclassIIdiTPSInvolvedinTanshinonesBiosyntheticPathwayinRootCui

etal,unpublisheddata解析丹参二萜代谢途径CPS1istheonlyclassIIdiTPQuantificationoffiveknownmajorcompoundsinCKand

CPS1-RNAi

linesCui

etal,unpublisheddata解析丹参二萜代谢途径QuantificationoffiveknownmIdentificationofmetabolitesdownstreamofSmCPS1catalyticstepintanshinonespathwayCui

etal,unpublisheddata解析丹参二萜代谢途径Identificationofmetabolites84383CKirSmCPS1DataanalyzedbyMPP(hairyroot)解析丹参二萜代谢途径84383CKDataanalyzedbyMPP(h漆小泉植物代谢组学及其应用ppt课件5x10012+ESIEIC(371.2345)???Frag=130.0Vck49.d5x10012+ESIEIC(325.2526)???Frag=130.0Vcps13.d???????(??)1.522.533.544.555.566.577.588.599.51010.51111.51212.51313.5145x1000.511.522.53+???(9.264??)ck49.d313.1810371.2344780.5551227.1076647.3355??????(m/z)751001251501752002252502753003253503754004254504755005255505756006256506757007257507758008258508759009259509755x1000.511.522.53+???(9.264??)ck49.d313.1810335.1631371.2344330.2075358.2389299.0688277.0866??????(m/z)2702752802852902953003053103153203253303353403453503553603653703753803853903955x10012+ESIEIC(371.2345)???6x1000.250.50.751+ESIEIC(277.0868)9.108min

116x1000.250.50.751+ESIEIC(281.1178)8.545min

116x1000.250.50.751+ESIEIC(279.1027)

Frag=130.0VPK-1-10-plant.d11min12345678910111213148.178min9.712minTrijuarone1,2-dihydrotanshinonedihydrotanshinoneItanshinoneI6x1000.250.50.751+ESIEIC(277.6x1000.20.40.60.81+277.0871(9.108min)299.0683277.0871575.1483335.16266x1000.250.50.7511.251.51.75+279.1016(9.737min)301.0836279.1016579.1776261.0917233.0965324.1598205.10126x1000.250.50.7511.251.5+281.1174(8.545min)583.2088303.0993235.1118263.1070207.1173m/z)1802002202402602803003203403603804004204404604805005205405605806006202M+Na2M+Na2M+NaM+HM+HM+H6x1000.20.40.60.81+277.08716x1000.20.40.60.81+277.0871(9.108min)299.0683277.0871335.1626322.1445249.09166x1000.250.50.7511.251.51.75+279.1016(9.737min)301.0836279.1016261.0917233.0965324.1598205.1012190.07766x1000.250.50.7511.251.5+281.1174(8.545min)303.0993281.1174235.1118263.1070207.1173192.0930319.0725m/z)180190200210220230240250260270280290300310320330340350360M+HM+NaM+HM+NaM+NaM+HM-H2OM-H2O-18.0099-27.9952-27.9953-15.0236-CH3-CO-CO-18.0104-27.9952-27.9945-15.0243-CH3-CO-CO-18.0099M-H2O6x1000.20.40.60.81+277.0871(9SmCPS1wastheonlyclassIIditerpenecyclaseinvovledintanshinonesbiosynthesisintherootofDanshen.PeridermistheplacewheretanshinoneswerebiosynthesizedandaccumulatedTanshinonebiosynthesisisacomplexnetworkandit

islikelythattanshinoneIcanbesynthesizedthroughdifferentpathways解析丹参二萜代谢途径解析丹参二萜代谢途径漆小泉植物代谢组学及其应用ppt课件CenterforSignalTransduction&MetabolomicsApplicationsofMetabolomicsanalysisNatureGenetics(2006)Volume38number7July,P842-849CenterforSignalTransductionCenterforSignalTransduction&MetabolomicsApplicationsofMetabolomicsanalysisKeurentjesetal.200614ArabidopsisecotypesandRILsUntargetedmetabolomicsanalysis(LC-QTOFMS)CenterforSignalTransductionCenterforSignalTransduction&MetabolomicsApplicationsofMetabolomicsanalysisKeurentjesetal.2006CenterforSignalTransductionCenterforSignalTransduction&MetabolomicsKeurentjesetal.2006FrequencydistributionofthenumberofsignificantQTLsdetectedateachmarkerpositionatfoursignificancelevel.NumberofmassesdetectedintheRIpopulationanditsparents.NotdetectedintheparentsDetectedinbothparentsCenterforSignalTransductionCenterforSignalTransduction&MetabolomicsKeurentjesetal.2006ApplicationsofMetabolomicsanalysisBeforesidechainmodificationAftersidechainmodificationCenterforSignalTransductionCenterforSignalTransduction&MetabolomicsApplicationsofMetabolomicsanalysisKeurentjesetal.2006Largegeneticvariationsformasspeaksinthe14accessions(only13.4%ofmasspeakswaredetectedincommoninall14accession)75%ofthe2000masspeakscanbeexplainedbyQTLsintheRIpopulation.Many(one-third)metabolitesareproducedasaresultoftherecombinationofthegenomesofthetwoparents,sincetheyareabsentinbothparents.CenterforSignalTransductionConclusionInsummary,authorsintegratedhigh-throughputmetabolomicsandgenotypingdatafromalargepopulationcohortforelucidatingthebiochemicalidentitiesofunknownmetabolites.Tothisend,authorsappliedmetabolomicsgenome-wideassociationstudiesandGaussiangraphicalmodelinginordertolinktheseunknownmetaboliteswithknownmetabolicclassesandbiologicalprocesses.Itistobenotedthatthemethoddoesnotspecificallyrequiregenotypingdata.Evenmetabolomicsmeasurementsalone,analyzedthroughtheGGMs,mayprovidesufficientinformationfortheclassificationandevenpreciseidentityprediction.Onelimitationofthisapproachistherequirementforassociationswithfunctionallydescribedlociorknownmetabolites.ConclusionInsummary,authors水稻种子低温萌发的代谢组分析DNAmarkers珍汕97x明恢63120RILsSSDPhenotypesMetabolitespQTLsmQTLsMetabolicnetwork/pathwayscontrolledbyQTLsco-locationcorrelation15℃,

10days15℃,

10days水稻种子低温萌发的代谢组分析DNAmarkers珍汕97萌发率分布图RIL15

MH63RIL78ZS97RIL163水稻种子低温萌发的代谢组分析萌发率分布图RIL15水稻种子低温萌发的代谢组分析珍汕97x明恢63

RI群体的高密度SNP连锁图谱Xieetal(2010)PNAS107:10578Yu

et

al

(2011)PloSOne

6:e175951839

markers水稻种子低温萌发的代谢组分析珍汕97x明恢63RI群体的高Bin690Bin6923.1Bin6951.9Bin7002.8Bin7021.3Bin72313.3Bin73012.7Bin74311.2Bin76011.9Bin77010.9Bin78710.6Bin79216.8RM264.1Bin8083.7Bin8187.4RM311.7Chr5胚根QTLs胚芽鞘QTLs水稻种子低温萌发的代谢组分析低温萌发速率QTL的定位Bin690Bin6923.1Bin6951.9Bin700C161Bin1410.7Bin2615.0Bin4413.5Bin5216.6Bin6616.7Bin10317.9Bin11914.7Bin13015.2Bin13210.2G39310.5Bin1626.9C23402.1C866.8Bin19419.9Bin19911.7Bin21712.8Bin690Bin6923.1Bin6951.9Bin7002.8Bin7021.3Bin72313.3Bin73012.7Bin74311.2Bin76011.9Bin77010.9Bin78710.6Bin79216.8RM264.1Bin8083.7Bin8187.4RM311.7Bin1391Bin139914.7Bin14139.3Bin142211.0Bin143017.8Bin14619.6Bin147610.3Bin14889.4G40018.9Bin14951.2Bin15032.7Bin15062.9Bin15074.7G1819.7TEL37.3低温胚根长度QTLs低温胚芽鞘长度QTLs常温胚根长度QTLs常温胚芽鞘长度QTLs水稻种子低温萌发的代谢组分析种子萌发速率QTLsChr1Chr5Chr11C161Bin1410.7Bin2615.0Bin4413.0hour2days4days6daysendospermendospermendospermendospermembryoembryoembryoembryoZS97MH63ZS97MH63ZS97MH63ZS97MH63MH63MH63水稻种子低温萌发的代谢组分析亲本低温萌期间代谢谱变化0hour2days4days6daysendosp取样时间：萌发后第4天

萌发温度：15oCendospermembryoZS97MH63MH63100

RILs

x4EmbryoEndospermPolarfractionNon-polarfractionPolarfractionNon-polarfraction1,600samplesGC-Tof/MS水稻种子低温萌发的代谢组分析代谢组分析方法取样时间：萌发后第4天endospermembryoZS9InternalstandardcorrectionQualitycontrolmQTLanalysisforRILsGC-MSofsamplesXCMSIonfeatureAbundancefilteringMetaboliteinteractionnetworkColocalizationanalysisMultiplestatisticanalysisAnovaanalysisCandidategenepredictionMolecularmechanism水稻种子低温萌发的代谢组分析遗传代谢组学分析流程InternalstandardcorrectionmQChr1Chr2Chr3Chr4Chr5Chr6Chr7Chr8Chr9Chr10Chr11Chr12GeneticPosition(cM)Ionfeatures红色代表碎片离子丰度在明恢63中高于珍汕97，绿色相反。水稻种子低温萌发的代谢组分析50-5Lod定位mQTLs—1417个QTLs(碎片离子丰度)32300Xieetal,unpublisheddataChr1Chr2Chr3Ch鉴定出4个数量遗传位点(QTLs)控制种子低温和常温萌发速率。在低温(15℃)萌发第4天时，珍汕97和明恢63之间的代谢谱出现了明显的变化。鉴定出1417个离子碎片数量性状位点。其中，与种子萌发速率表型共定位的有405个。在控制种子淀粉成分位点出现了大量的mQTLs。去卷积分析这些离子碎片将有助于解析这些位点在种子低温萌发速率及营养成分的代谢调控机制及建立代谢调控网络。水稻种子低温萌发的代谢组分析鉴定出4个数量遗传位点(QTLs)控制种子低温和常温萌发速率MethodsMetabolomicsanalysisGaussiangraphicalmodeling(GGM)Genome-wideassociationanalysis(GWAS)IdentificationofunknownmetabolitesbasedonGGMandGWASMethodsMetabolomicsanalysisIGGMsarebasedonpartialcorrelationcoefficients,thatispairwisePearsoncorrelationcoefficientsconditionedagainstthecorrelationwithallothermetabolites.Krumsieketal.BMCSystemBiology.2011,5IdentificationofunknownmetabolitesbasedonGGMandGWASGGMsarebasedonpartialcorrIdentificationof