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Methods in Molecular Biology 2467 Nourollah Ahmadi Jérôme Bartholomé Editors Genomic Prediction of Complex Traits Methods and Protocols M M B ETHODS IN OLECULAR IO LO GY SeriesEditor JohnM.Walker School of Lifeand MedicalSciences University ofHertfordshire Hatfield, Hertfordshire, UK Forfurther volumes: http://www.springer.com/series/7651 For over 35 years, biological scientists have come to rely on the research protocols and methodologiesinthecriticallyacclaimedMethodsinMolecularBiologyseries.Theserieswas thefirsttointroducethestep-by-stepprotocolsapproachthathasbecomethestandardinall biomedicalprotocolpublishing.Eachprotocolisprovidedinreadily-reproduciblestep-by- step fashion, opening with an introductory overview, a list of the materials and reagents neededtocompletetheexperiment,andfollowedbyadetailedprocedurethatissupported with a helpful notes section offering tips and tricks of the trade as well as troubleshooting advice. These hallmark features were introduced by series editor Dr. John Walker and constitutethekeyingredientineachandeveryvolumeoftheMethodsinMolecularBiology series. Tested and trusted, comprehensive and reliable, all protocols from the series are indexedinPubMed. Genomic Prediction of Complex Traits Methods and Protocols Edited by Nourollah Ahmadi and Jérôme Bartholomé CIRAD, UMR AGAP Institut, Montpellier, France Editors NourollahAhmadi Je´roˆmeBartholome´ CIRAD CIRAD UMRAGAPInstitut UMRAGAPInstitut Montpellier,France Montpellier,France ISSN1064-3745 ISSN1940-6029 (electronic) MethodsinMolecularBiology ISBN978-1-0716-2204-9 ISBN978-1-0716-2205-6 (eBook) https://doi.org/10.1007/978-1-0716-2205-6 ©TheEditor(s)(ifapplicable)andTheAuthor(s),underexclusivelicensetoSpringerScience+BusinessMedia,LLC,part ofSpringerNature2022,CorrectedPublication2022 Chapters 3, 9, 13, 14 and 21 are licensed under the terms of the Creative Commons Attribution 4.0 International License(http://creativecommons.org/licenses/by/4.0/).Forfurtherdetailsseelicenseinformationinthechapters. Thisworkissubjecttocopyright.AllrightsaresolelyandexclusivelylicensedbythePublisher,whetherthewholeorpart of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting,reproductionon microfilmsorinanyotherphysicalway,andtransmissionorinformation storageand retrieval,electronicadaptation, computersoftware,orbysimilar ordissimilar methodologynow knownorhereafter developed. Theuseofgeneraldescriptivenames,registerednames,trademarks,servicemarks,etc.inthispublicationdoesnotimply, evenintheabsenceofaspecificstatement,thatsuchnamesareexemptfromtherelevantprotectivelawsandregulations andthereforefreeforgeneraluse. Thepublisher,theauthorsandtheeditorsaresafetoassumethattheadviceandinformationinthisbookarebelievedto betrueandaccurateatthedateofpublication.Neitherthepublishernortheauthorsortheeditorsgiveawarranty, expressedorimplied,withrespecttothematerialcontainedhereinorforanyerrorsoromissionsthatmayhavebeen made.Thepublisherremainsneutralwithregardtojurisdictionalclaimsinpublishedmapsandinstitutionalaffiliations. ThisHumanaimprintispublishedbytheregisteredcompanySpringerScience+BusinessMedia,LLCpartofSpringer Nature. Theregisteredcompanyaddressis:1NewYorkPlaza,NewYork,NY10004,U.S.A. Preface Over the last three decades, steady progresses within the fields of molecular genetics and quantitativegeneticshaveledtotwomajorbreakthroughsingenetics,geneticmappingand genomicpredictionofcomplextraitsofimperfectlyknownbiologicalbases,withimmense potential impact in the applied fields of human health and agriculture. The prospect of predicting human disease risks, and complex traits of agronomic interest with reasonably high precision, although they are difficult to evaluate or/and subject to numerous regula- tionsandinteractions,hasstimulatedpublicandprivateresearch.Theaimsincludedrefining the theoretical bases of genomic prediction, extending its areas of application, fine-tuning the experimental designs for specific cases on different species of interest, and developing dedicated tools. Excitement over the development of methods for genomic prediction has notescapedtheonearoundmachinelearningandartificialintelligencetechnologies.Results fromvarioussimulationworksandempiricalapplicationsindicatethatthequalityofpredic- tion depends on the interplay between a large number of factors, including relatedness between the reference and the candidate populations, trait architecture, optimal marker density, prediction methods, and, in the case of traits of agronomic interest, the overall organization of the plant and animal breeding programs. As the concepts and methods of genomic prediction of complex traits mature and are about to become the mainstream approachindealingwithanincreasingnumberofhealthissuesandobjectivesofanimaland plantbreeding,itisverytimelytoassemblethemethodologicalachievementsofthefieldina volumeoftheseriesMethodsinMolecularBiology. Thisvolumeiscomposedoffivesections.Thefirstsection(Chapter1)isareminderof the evolution of the conceptual frameworks for genotype-phenotype relationship analysis and molecular genetics approaches intending to predict phenotypic variations. The second section (Chapters 2–4), passing through the principles of genomic prediction of complex traitsandtheoverviewoffactorsthataffectitsreliability,providesanextensivereviewofthe characteristicsofthemostinfluentialfactors,andmethodstooptimizethosecharacteristics. The third section (Chapters 5–10) describes single trait and single environment genomic predictionmethodsandtheassociatedassumptionsonthevarianceofmarkereffectandon thearchitectureofthetargettraitandpresentsanoverviewofmajorcomputerpackagesfor genomicprediction.Then,movingon,presentgenomicpredictionapproachesdealingwith morecomplexbiologicalcontexts,suchasnonadditivegeneticeffects,effectsofgenotypeby environment interaction, and correlation between phenotypic traits, are described and the associate computer packages presented. The fourth section (Chapters 11–14) provides examples of incorporation into genomic prediction models, of new knowledge coming out of molecular genetics and ecophysiology—such as trait-specific genetic information and “omics” data, and the coupling of genomic models with crop growth models. The lastsection(Chapters15–22)isdedicatedtolessonslearnedfromanumberofapplications of genomic prediction in the fields of human health, animal breeding, and plant breeding and to methods for analysis of the economic effectiveness of genomic selection relative to conventionalbreedingapproaches. v vi Preface Astheobjectiveofthevolumeistoprovideareferenceresourceforstudents,teachers, practitioners,andfor furthermethodologicalresearch,thechaptersaredesignedtoinclude practicalexamples,whilereportingthelateststateofknowledgeinthefield. Montpellier,France NourollahAhmadi Je´roˆmeBartholome´ Contents Preface ..................................................................... v Contributors................................................................. ix 1 GeneticBasesofComplexTraits:FromQuantitativeTrait LocitoPrediction....................................................... 1 NourollahAhmadi 2 GenomicPredictionofComplexTraits,Principles,Overview ofFactorsAffectingtheReliabilityofGenomicPrediction, andAlgebraoftheReliability............................................. 45 Jean-MichelElsen 3 BuildingaCalibrationSetforGenomicPrediction,Characteristics toBeConsidered,andOptimizationApproaches ........................... 77 SimonRio,AlainCharcosset,TristanMary-Huard, LaurenceMoreau,andRenaudRincent 4 Genotyping,theUsefulnessofImputationtoIncreaseSNPDensity, andImputationMethodsandTools....................................... 113 FlorencePhocas 5 OverviewofGenomicPredictionMethodsandtheAssociated AssumptionsontheVarianceofMarkerEffect, andontheArchitectureoftheTargetTrait ................................ 139 Re´kaHoward,DiegoJarquin,andJoseĆrossa 6 OverviewofMajorComputerPackagesforGenomicPrediction ofComplexTraits....................................................... 157 GiovannyCovarrubias-Pazaran 7 Genome-EnabledPredictionMethodsBased onMachineLearning.................................................... 189 EdgarL.Reinoso-Pelaéz,DanielGianola,andOscarGonza´lez-Recio 8 GenomicPredictionMethodsAccountingforNonadditive GeneticEffects ......................................................... 219 LuisVarona,AndresLegarra,MiguelA.Toro, andZulmaG.Vitezica 9 GenomeandEnvironmentBasedPredictionModels andMethodsofComplexTraitsIncorporating Genotype(cid:1)EnvironmentInteraction..................................... 245 JoseĆrossa,OsvalAntonioMontesinos-L(cid:1)opez,PaulinoPe´rez-Rodrı´guez, GermanoCosta-Neto,RobertoFritsche-Neto,RodomiroOrtiz, JohannesW.R.Martini,MortenLillemo,AbelardoMontesinos-L(cid:1)opez, DiegoJarquin,FlavioBreseghello,JaimeCuevas,andRenaudRincent 10 AccountingforCorrelationBetweenTraits inGenomicPrediction .................................................. 285 OsvalAntonioMontesinos-L(cid:1)opez,AbelardoMontesinos-L(cid:1)opez, BrandonA.Mosqueda-Gonzalez,JoseĆricelioMontesinos-L(cid:1)opez, andJoseĆrossa vii viii Contents 11 IncorporationofTrait-SpecificGeneticInformationintoGenomic PredictionModels ...................................................... 329 ShaoleiShi,ZheZhang,BingjieLi,ShengliZhang, andLingzhaoFang 12 IncorporatingOmicsDatainGenomicPrediction .......................... 341 JohannesW.R.Martini,NingGao,andJoseĆrossa 13 IntegrationofCropGrowthModelsandGenomicPrediction................ 359 AkioOnogi 14 PhenomicSelection:ANewandEfficientAlternative toGenomicSelection ................................................... 397 PaulineRobert,CharlotteBrault, RenaudRincent,andVincentSegura 15 FromGenotypetoPhenotype:PolygenicPrediction ofComplexHumanTraits ............................................... 421 TimothyG.Raben,LouisLello,ErikWiden,andStephenD.H.Hsu 16 GenomicPredictionofComplexTraitsinAnimalBreeding withLongBreedingHistory,theDairyCattleCase......................... 447 JoelIraWeller 17 GenomicSelectioninAquacultureSpecies................................. 469 FrançoisAllalandNguyenHongNguyen 18 GenomicPredictionofComplexTraitsinPerennialPlants: ACaseforForestTrees.................................................. 493 FikretIsik 19 GenomicPredictionofComplexTraitsinForagePlantsSpecies: PerennialGrassesCase................................................... 521 PhilippeBarre,TorbenAsp,StephenByrne,MichaelCasler, MartyFaville,OddArneRognli,IsabelRoldan-Ruiz, LeifSkøt,andMarcGhesquie`re 20 GenomicPredictionofComplexTraitsinanAllogamousAnnualCrop: TheCaseofMaizeSingle-CrossHybrids .................................. 543 IsadoraCristinaMartinsOliveira,ArthurBernardeli, Jose´HenriqueSolerGuilhen,andMariaMartaPastina 21 GenomicPrediction:ProgressandPerspectives forRiceImprovement................................................... 569 Je´roˆmeBartholome´,ParthibanThathapalliPrakash, andJoshuaN.Cobb 22 AnalyzingtheEconomicEffectivenessofGenomicSelection RelativetoConventionalBreedingApproaches............................. 619 AlineFugeray-Scarbel,SarahBen-Sadoun, SophieBouchet,andSte´phaneLemarie´ Correctionto:GenomicPredictionMethodsAccountingforNonadditive GeneticEffects.............................................................. C1 Index ...................................................................... 645 Contributors NOUROLLAHAHMADI • CIRAD,UMRAGAPInstitut,Montpellier,France FRANÇOISALLAL • MARBEC,Universite´deMontpellier,CNRS,Ifremer,IRD,Palavas-les- Flots,France TORBENASP • Center forQuantitativeGeneticsandGenomics,AarhusUniversity,Slagelse, Denmark PHILIPPEBARRE • INRAE,URP3F,Lusignan,France JE´ROˆMEBARTHOLOME´ • CIRAD,UMRAGAPInstitut,Montpellier,France SARAH BEN-SADOUN • INRAE-UCAUMR1095,GeneticsDiversityandEcophysiologyof Cereals,Clermont-Ferrand,France ARTHURBERNARDELI • DepartmentofAgronomy,UniversidadeFederaldeViçosa, Viçosa-MG,Brazil SOPHIE BOUCHET • INRAE-UCAUMR1095,GeneticsDiversityandEcophysiologyof Cereals,Clermont-Ferrand,France CHARLOTTEBRAULT • UMRAGAPInstitut,UnivMontpellier,CIRAD,INRAE,Institut Agro,Montpellier,France;InstitutFrançaisdelaVigneetduVin,Montpellier,France; UMTGeno-Vigne®,IFV-INRAE-InstitutAgro,Montpellier,France FLAVIO BRESEGHELLO • EmbrapaArrozeFeijaõ,SantoAntoˆniodeGoia´s,GO,Brazil STEPHENBYRNE • Teagasc,CropScienceDepartment,OakPark,Carlow,Ireland MICHAELCASLER • U.S.DairyForageResearchCenter,USDA-ARS,Madison,WI,USA ALAINCHARCOSSET • GQE—LeMoulon,INRAE,UniversityParis-Sud,CNRS, AgroParisTech,Universite´Paris-Saclay,Gif-sur-Yvette,France JOSHUA N.COBB • RiceTecInc,Alvin,TX,USA GERMANOCOSTA-NETO • DepartamentodeGene´tica,EscolaSuperiordeAgricultura“Luiz deQueiroz”(ESALQ/USP),SaõPaulo,Brazil GIOVANNY COVARRUBIAS-PAZARAN • CentroInternacionaldeMejoramientodeMaizyTrigo (CIMMYT),Texcoco,Mexico;ExcellenceinBreedingPlatform(EiB),Texcoco,Mexico JOSE´ CROSSA • ColegiodePostgraduados,Montecillos,Mexico;BiometricsandStatisticsUnit, InternationalMaizeandWheatImprovementCenter(CIMMYT),CarreteraMexico- Veracruz,Mexico JAIME CUEVAS • UniversidaddeQuintanaRoo,Chetumal,QuintanaRoo,Mexico JEAN-MICHELELSEN • GenPhySE,Universite´deToulouse,INRAE,ENVT,CastanetTolosan, France LINGZHAOFANG • MRCHumanGeneticsUnitattheInstituteofGeneticsandCancer,The UniversityofEdinburgh,Edinburgh,UK MARTYFAVILLE • AgResearchLtd,GrasslandsResearchCentre,PalmerstonNorth,New Zealand ROBERTOFRITSCHE-NETO • DepartamentodeGene´tica,EscolaSuperiordeAgricultura “LuizdeQueiroz”(ESALQ/USP),SaõPaulo,Brazil ALINE FUGERAY-SCARBEL • Univ.GrenobleAlpes,INRAE,CNRS,GrenobleINP,GAEL, Grenoble,France NINGGAO • SchoolofLifeSciences,SunYat-SenUniversity,Guangzhou,China MARCGHESQUIE`RE • INRAE,URP3F,Lusignan,France ix