Exploiting genetic variation in nitrogen use efficiency

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Hawkesford, M. J. and Griffiths, S. 2019. Exploiting genetic variation in

nitrogen use efficiency. Current Opinion in Plant Biology. 49, pp. 35-42.

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Exploiting

genetic

variation

in

nitrogen

use

efficiency

for

cereal

crop

improvement

Malcolm

J

Hawkesford

and

Simon

Griffiths

Cerealsarethemostimportantsourcesofcaloriesandnutrition forthehumanpopulation,andareanessentialanimalfeed.

Foodsecuritydependsonadequateproductionanddemands

arepredictedtoriseastheglobalpopulationrises.Theneedfor increasedyieldswillhavetobecoupledtotheefficientuseof resourcesincludingfertiliserssuchasnitrogentounderpinthe sustainabilityoffoodproduction.Althoughoptimally

performingcropswithhighyieldsrequireabalancedmineral nutrition,nitrogenfundamentallydrivesgrowthandyieldaswell asrequirementsforothernutrients.Itisestimatedthatglobally only33%ofappliednitrogenfertiliserisrecoveredinthe harvestedgrain,indicativeofahugewasteofresourceand potentialmajorpollutantandisthusamajortargetforcrop improvement.Bothagronomyandbreedingwillcontributeto improvednitrogenuseefficiency(NUE)andanimportant componentofthelatterisharnessinggermplasmvariation.This reviewwillconsiderthekeytraitsinvolvedinNUE,thepotential toexploitgeneticvariationforthesespecifictraits,andthe approachestobeutilised.

Addresses 1

RothamstedResearch,Harpenden,AL52JQ,UK

2_{JohnInnesCentre,Norwich,NR47UH,UK}

Correspondingauthor:Hawkesford,MalcolmJ (malcolm.hawkesford@rothamsted.ac.uk)

CurrentOpinioninPlantBiology2019,49:35–42

ThisreviewcomesfromathemedissueonPhysiologyand metabolism

EditedbyElizabethAAinsworthandElizabeteCarmoSilva

https://doi.org/10.1016/j.pbi.2019.05.003

1369-5266/ã2019TheAuthors.PublishedbyElsevierLtd.Thisisan openaccessarticleundertheCCBYlicense(http://creativecommons. org/licenses/by/4.0/).

Introduction

Cereals including rice, wheat and maize are the most importantsourcesofcaloriesandnutritionforthehuman population,and inaddition theyareanessentialanimal feedstuff.Foodsecuritydependsonadequateproduction anddemandsarepredictedtoriseinthecomingdecades as the global population rises. The efficient use of resourcesincludingfertiliserssuchasnitrogenunderpins sustainability.Althoughcropswithhighyieldsrequirea balanced mineral nutrition, nitrogen fundamentally drives growth and yield and requirements for other

nutrients. One estimate [1]suggests that globallyonly 33% of applied nitrogen fertiliser is recovered in the harvestedgrain.Thisrepresentsahugewasteofresource andapotentialmajorpollutantthroughbothleachingto watercoursesandfromgreenhousegasemissions,andis thusamajortargetforcropimprovement.More optimis-tically, as yields are a major target for crop breeding programmes, nitrogen use efficiency (NUE) will also increase in parallelbydefinition. Indeed in the United Kingdominrecentyears,wheatyieldshavecontinuedto risemodestly,whilstN-inputshaveremainedconstantat thenationallevel,demonstratingimprovednitrogenuse efficiency [2].

What

is

nitrogen

use

efficiency?

The most fundamental and variable trait influencing NUE is yield; however, the optimum use of nitrogen for crop production may beconsidered in termsof not onlyyieldbutalsoquality.NUEasayieldefficiencytrait isusuallydefinedasyieldperunitof availableN andis the product of the terms defining uptake efficiency (NUpE) and utilisation efficiency (NUtE), the latter beingtheeffectivegrainyieldproducedfortheamount of N taken up (see Box 1 and Moll et al. [3]). One consequence ofthisis thathighNUEcropswill havea highyieldbutpotentiallyalowNcontentinthebiomass andinthegrain.However,additionallyNUEforquality mustbeconsidered,whichrequiresoptimumproduction of proteinthegrainandreliesbothonefficient crop N-uptakeandsubsequenteffectivepartitioningofnitrogen fromvegetativetissuestothegrain.Highgrainproteinis oftenachievedthroughagronomicinterventionofhighor additional Napplications,often lateinthegrowing sea-son, resultingin alowergrainyieldNUE.

Akeymeasureofnitrogenuseefficiencyisfertiliser recov-ery efficiency (FRE) which indicates directly how well applied fertiliseris usedand removed by theharvested componentofthecrop.Itisthismeasurewhichhasbeen calculatedtobeaslowas33%inglobalterms[1].

AsummaryoftraitsisgiveninBox1andanoverviewof theinteractions between thecomponent traits and key physiologicalprocessescontributingtoNUEisshownin Figure1.

Key

traits

Akeytraitforcropnitrogenuseefficiencyistheabilityof thecroptotakeupnitrogen:thisisafunctionoftheroot structure,architectureandfunction.Subsequentto cap-ture, nitrogen is first utilised to produce an effective canopy. Parameters relating to light capture and

photosynthesis will determine yield potential and con-siderable variation exists and between within any crop species,forexamplewheat[6].Secondlythecanopyisan essential resource reserve, including of nitrogen which maybe subsequently utilised for grain filling and the importance of individual canopy fractions have been quantified[7].Canopy heightandflowering timeaffect nitrogenuseefficiency[8,9].Thisislikelytobeduetothe abovegroundbiomassaffectingtheachievablegrainyield given favourable harvest index (HI) but may include impactsonrootproliferationmediatedbyrhtgenes and hence effectiveness of theroots in nitrogen acquisition [10].

Yieldandquality parametersareusuallynegatively cor-related;however, atrait termedgrainprotein deviation (GPD) refers to a grain protein content (GPC) greater thanexpectedforanyparticularyieldandisaparticularly desirabletraitwhichmaybelinkedtoanthesisdateand post anthesis N-uptake [11,12] or to grain-specific pro-cessesreflectedbyintrinsicgraingeneexpressionprofiles [13]. GPD may be affected by partitioning, as a large fractionofgrainNcomesfromremobilisationfrom vege-tativetissuesandisquantifiedthenitrogenharvestindex (NHI;proportion ofN ingrainas afractionof thetotal plant N). Factors influencing nitrogen remobilisation including rates of senescence and transcription factors suchasNAM-B1,whichinfluenceratesofnutrient remo-bilisation[14,15,16,17].Whilstmostmodernhexaploid wheats lackthis functional allele, it is present in some Scandinavian populations [18]. Early senescence may enhance N re-use but will have a negative impact of canopyphotosynthesisandpotentialyield.Whilstcanopy reservesofresourcesincludingNareimportantforgrain fillingandshowconsiderablegeneticvariation[7,19],the senescence of thecanopy limitsfurther photosynthesis and reserve accumulation, and ultimately yield. Hence thekineticsofcanopymaturation,ahighlycontrolledand regulated process [20], impacts on both final yield and remobilisationefficiency.

36 Physiologyandmetabolism

Box1 DefinitionsofselectedNUEparametersreferredtointhisarticleforcerealcrops

Abbreviation Trait Definition Unit

NUE Nitrogenuseefficiency Yield(grain)perunittotalavailablenitrogen(fertiliserandmineralN);itis theproductofNUpENUtE[3]

kgyield/kgN

NUpE Nitrogenuptakeefficiency Nitrogentakenupbyentireabovegroundbiomassasafractionoftotal nitrogenavailabletothecrop

kg/kg

NUtE Nitrogenutilisationefficiency Yieldsasafunctionoftheamountofnitrogentakenup kg/kg GPC Grainproteincontent Thegrainprotein(content);oftentheNcontent(%concentration)a

standardfactortoconverttoprotein(e.g.5.7)

%

GPD Grainproteindeviation ActualgrainNconcentrationcomparedtothatexpectedforagivenyield, assumingalinearnegativerelationship,theresidualofanindividualpoint fromaregressionofgrainproteinconcentrationongrainyield[58]

%

NHI Nitrogenharvestindex ThefractionofNinthegraincomparedtototalNtakenup,usuallyat harvest.

Fraction

FRE Fertiliserrecoveryefficiency GrainNfromfertiliserasafractionofthatappliedasfertiliser:((Nremoved ingrain)–(Nfromsoil+rain))/fertiliserNapplied[1]

%

Figure1

NUpE

YIELD

Photosynthesis

Grain N

NUtE

Remobilisation

NHI

NUE = NUpE x NUtE

Current Opinion in Plant Biology

Other indicatorsof nitrogenuse efficiency include high yieldatlowN,particularlyimportantinsomesubsistence situationswherefertilisersmaynotbereadilyavailable. Alternatively, a measure may be responsiveness to applied N, with a desirable trait beinga proportionally greater increase with adefined application of N. All of theseindicatorsofefficient useofnitrogen arecomplex traitsinvolvingbiochemistry,phenology,architectureand responses totheenvironment.

How

much

genetic

variation

is

there?

There is variation in key NUE traits amongst modern varieties [19,21,22,23].However,itisclearthatamuch greater potential for variation must exist in a wider germplasm base [24]. The key issue with landraces and relatives isthatwhilst biomassmaybehigh,yields andHIinparticularareoftenverylowandthetraditional measuresofNUEarelessuseful.However,traitssuchas totalNuptake,Nuptakeatlowavailabilityandbiomass potentialareallgoodpointersfor usefulNUEtraits.

The most important architectural influence is stature (height)asinfluenced bydwarfinggenes[8].The intro-ductionofdwarfinggenesnotonlyimprovesHIandNHI but also decreases susceptibility to lodging at higher nitrogen applications.Apotentialnegative consequence ofrhtgeneswhichwhilstdecreasingheightmayalsohave other pleiotropic consequences such as decreased root proliferation [8,10,25].

Variationinrootarchitectureand functionwillcontributeto theefficiencyofuptake.Rootproliferationisvery depen-dentuponcanopyformationandnitrogenstatus[26].

Anumberofstudieshavedissectedroottraitsas Quanti-tativeTraitLoci(QTL)[10,27],identifyingthevariation in rootproliferation,length,lateralprofusionandspread or angleof roots. Manyof these studies are laboratory-basedduetothedifficultiesofmeasurementsinthefield; this,however,isbeggingtoberesolvedwithfieldstudies utilising shovelomics [28], root cores or electrophysio-logicalorpenetrometermethodsforassessingrootactivity usingtheproxyofsoildrying[29,30].

Mechanismsofnitrateuptakebyrootsalsocontributeto uptake efficiency. Large families of genes for nitrate transporters exist in wheat, involved in initial uptake and in internaltranslocation processes[31] Variation in expression orfunctioning willimpact onnitrateuptake. Specific individualtransporter geneshavemajoreffects onNUEinrice,forexample,indicaandjaponicaricemay bedifferentiatedbyallelesofalowaffinitynitrate trans-porter, NRT1.1.B (OsNPF6.5)[32].HigherN-uptake andyields andhenceNUEin indicaseemto be specifi-callydependentonthissingleallele.Inaddition,another nitratetransporter,OsNRT2.3,involvedinpHsensingin the phloem and which is involved in the regulation of

nitrateuptake,showsnatural variationwithintheindica subspecies[33].

Strategies

for

the

identification

of

genes

controlling

NUE

Figure2showsaproposedschemefortheidentificationof genescontrollingNUEandtheirdeploymentinbreeding. Asalreadydiscussed,NUEisahighlycomplexpolygenic trait.Consequently,theidentificationofindividualgenetic effects requiresquantitative geneticsapproaches andthe initialdescriptionofsucheffectsisusuallyasQTL.Thepast twenty years has seen a widening of the repertoire in statisticalmethodsandpopulationtypesforthe identifica-tionofQTL.Theoptimalapproachverymuchdependson thespecificNUErelatedquestionbeingasked.Istheaimto describe genetic mechanisms and trait variation that is already beingusedinbreedingprogrammesoristheaim to identify new genes/alleles and mechanisms in more diverse germplasm? All the approaches described carry uniquestrengthsandweaknesses.

Associationgenetics

Associationgeneticscanbebasedonpanelsofgenotypes verywelladaptedtotheresearcherstargetenvironment, sample multiple alleles, and provide very high genetic resolution basedonhistorical recombination eventsand havebeenappliedinmanystudiesofNUE,forexample, inwheat[34].However,statisticalpowerisrelativelylow in thesematerials,aparticularproblemwithNUEtraits whichtendtoberelativelysubtlegeneticeffects display-ing low heritability. This problem can be tackled by increasing panel size but this leads to very large and expensive experiments with many NUE traits being expensivetomeasure(e.g.grindingtissues,CHN analy-sis).Moreover,associationgeneticsreliesonareasonable balance of alleles at each locus studied, low frequency alleles(typicallylessthan 10%)areeliminatedfromthe analysis.Thisisaparticularproblemifrareallelesarethe targetaswouldtypicallybethecasewhensearchingfor variation inlandrace collections and soon. An essential element of successful association studies is the proper considerationofgeneticstructure.Forexample,groupsof germplasmwithinapanelmaybegeneticallydistinctdue to similar pedigree history within each. A NUE trait might be more highly expressed in one group. In this case loci with allele frequency differences between groups will result in false trait marker associations (TMAs) and,equallypossible, falsenegatives.

QTLmappingusingbiparentalpopulations

locusand(exceptinthecaseofsegregationdistortion)the populationiscomprised50%ofeachallelicclass. Numer-ousNUEQTLhavebeenidentifiedusingthisapproach forexamplein rice[35].

Multiparentpopulations

Overthelastdecadeattemptshavebeenmadetocombine thebenefitsofassociationandbiparentalmappingthrough theuseof multiparentpopulations,mostnotablynested associationmapping(NAM)popularisedinmaize[36]and multi parent advanced generation intercross (MAGIC) developedin wheat [37].These allow the simultaneous analysis of multiple alleles and the mapping resolution affordedbyrecombinationcapturedduringtheformation ofthepopulationaswellashistoricalrecombination.The problemof artefactual QTLcaused by structureis also removedbecausetheallelesunderlyingputativeTMAsare segregatinginthemultiparentpopulation.Thebenefitsof thesenewpopulationtypescoupledwithgamechanging advancesinappliedgenomicsmeanthatmolecularmarker datapointcostandabilitytoaligntoareferencegenomeis

nowpossibleinmaizericeandwheat.Workexemplifying thischangeinthelatestofourstudiesspeciestoachieve postgenomicstatus includeshigh densitymarker arrays developed by Winfield et al. [38] and, at last, a whole genomesequence assembly[39].Thishasled toa step changeinthe scaleofpopulationdevelopmentwiththe aim ofidentifyingnewandusefulgeneticvariationforcomplex traitssuchas NUE, andfor example,Wingen et al.[40] producedapubliclyavailableNAMpopulationwhichnow represents more than 90 landrace parents and over 10000recombinantinbredlines.

Backcrosspopulations

Backcrossingusuallyinvolvesadonorparentwhich car-ries characteristics of interest and a recurrent parent whichisbackcrossedwiththeprogenyoftheinitialcross sothatthegenomesoftheprogenybecomeincreasingly (50%)likethatoftherecurrentparent.Aftertherequisite numberof backcrosses,the progeny is then brought to geneticfixationeitherbysingleseeddescentordoubled haploidy.SoeachindividualofaBC3(3rdgenerationof 38 Physiologyandmetabolism

Figure2

2.NUE/component QTL

Beneficial allele validation using NILs

3. Desirable increasing allele/haplotype

5. Marker validation in pre-breeding

6. Variety development by marker assisted selection

Introgression into elite genepool 1. Genetic dissection of NUE

• Association panels

• NAM

• Biparental

• Backcross pop

• NIL library

4. Marker development and

trait introgression for pre-breeding

Decreasing phenology

variation

+

Current Opinion in Plant Biology

backcrossing)populationwillbeonaverage87.5% recur-rent parent with 12.5%random segments of the donor parent. After fixation for example by SSD, the donor genomecontribution willthenbeamere 4.25%.These progeniescanbegenotypedineachgenerationand seg-ments selected to tile the entire genome and for a chromosome segment substitution library (CSSL).The populationsproduceddisplayrestrictedphenotypic vari-ance,withmostindividualsalmostidenticaltothe recur-rentparent.However,linescarryingdonorsegmentsthat carryQTLinfluencingNUEonlyneedbecomparedwith thephenotypeoftherecurrentparenttoachieveahighly accurateandpreciseestimationofthegeneticeffectfrom that QTL. Soleimani et al. [41] used this approach to dissect phosphorususe inbarley.

Nearisogeniclines(NILs)

Empiricalselectionforagronomicperformance,including grainyieldhasbeenagoodproxyforNUEinwheat[42], rice[43],andmaize[44]suggestingthatmanytraitsunder selectionareconstitutiveandconferbenefitatarangeof nitrogen availabilities. In these cases, precise genetic stocksdevelopedtostudy-specificQTLinfluencingyield and yieldcomponents suchasthosedeveloped by Sim-mondsetal.[45]inwheat,representapowerfulresource for the study of NUE. Chief amongst these are Near Isogenic Lines (NILs) which are produced using the backcrossingapproachdescribedabovebutasingle frag-mentofdonorchromosome(geneticforeground)is main-tainedin thefaceofbackcrossingbyactive selectionof heterozygotes atthat locusin eachgenerationeither by phenotypic selection where the trait is controlled by a major gene at that locus or, more typically, by marker assistedselection(MAS)usingmappedmarkersthatflank the gene of interest or are even within it. NILs are a classicoutputofadvancedQTLstudiesinwhichaQTL is validated whenthe NIL is shownto differ from the recurrent parent in a similar way to the QTL in the original discovery population, that is same direction of effectandsimilarmagnitude.Thesematerialsprovidean immenselyvaluableresourceforNUEstudies.TheQTL fortheoriginaltraitofinterestisproventoberobust.Only twolinesneedtobestudies,theNILandtherecurrent parent. This means that multi-level factorial interven-tionsarefeasibleanddeepphysiologicalanalysiscanbe conducted.AnincreasingpoolofNILresourcesarenow availableandtheirspecificuseinNUEstudieshasbeen carried outinwheatfor examplebyKowalskietal. [46] andwhole librariesofNILsrepresentingallmajor agro-nomicQTLidentifiedsofarfromwellstudiesreference populationssuchasAvalonCadenza[47]surelypresent arichseam ofdiscoveryforfutureNUEresearch.

The

impact

of

phenology

on

meaningful

gene

discovery

Thewordphenologywascoinedby19thcenturyEnglish naturalists recording the timing of key natural history

events within each season such as the appearance of blossom on trees or frog spawn in the local pond [48]. Inreferencetocropsitdescribesthetimingof develop-mentaltransitionssuchasthetransitionfromvegetative toreproductivegrowth,theonsetofstemextension,the emergenceoftheinflorescence,anthesis,senescence,and maturity. Phenology is genetically determined with a number of environmental cues modifying the crop response. Optimisation ofthe crop phenological profile isthemajordriverofcropadaptation.So,itcomesaslittle surprisethatphenologyisshowntocorrelatewithNUEis almosteverystudyinwhichitismeasuredandQTLfor phenology traits often collocate with NUE and it is components,mostlikelythroughpleiotropy.Thisraises averyimportantquestionforNUEgenediscovery stud-ies.Forexample,ifamajorphenologyQTLsuchasPpd-1 controlling photoperiod sensitivity in wheat, or Hd1 in rice, and so on is segregating and the allele which is associated with poor adaptation to that environment is also the low allele for NUE in that population has anythingusefulbeenlearntaboutNUEinthatscenario? Thesamecanbesaidaboutmajorgenescontrollingcrop height.Inmostcasestheanswerisno,andresearchersdo not pursue these effects. The segregation of the effect stillcausesaproblemthough,becauseititselfitincreases the noise to signal ratio for other NUE loci (often of smallereffect)segregatinginthesamepopulationwhich areofgreaterinterestbutmightnotbedetectedatallin thisscenario.

Thepopulationsdescribedaboveweredescribedinorder of decreasingphenologyvariance.Inwheatfor example manyassociationpanelsmightexhibitarangeof flower-ing timesup to one month whereas aNIL will usually havethesamephenologicalprofileastherecurrentparent (unless the foreground selection was for a phenology QTL). All the better if the recurrent parent is well adapted to the growing environment. This means that anyeffectdetectedcanbeattributedtoNUEperse,and notasarelativelysimpleandlowvaluesecondary conse-quenceofimprovedadaptation.Thisisnottosaythatthe finetuningofphenologydoesnotplayanimportantrole in themaximisationofNUE.Withingenotypesthatare equally well adapted improvements in NUE can be achieved by fine tuning phenological patterns such as therateof floretabortion[49].

narrowphenologicalwindowforanygivenenvironment, thusminimisingtheseconfoundingeffectsintheprimary phaseof NUEQTLdetection.

Prospects

for

crop

improvement

Themajortargetforbreedersandgrowersishighyield. Specifically, in the case of wheat, a high final protein content is desirable for bread-making quality. For all cereal crops and agronomic systems, the key priorityis efficientcaptureofNbytherootsystems,toimproveon thelowworldwideefficiency[1].Appropriateagronomy will contribute greatly to this; however, genetic approacheshavenot fully targetedroot traitsand there is likely scope for improvement. An efficient canopy, targeting both structural and photosynthetic traits will

improveyieldandNUE asdefinedas nitrogen require-ment; however, this may be atthe expense of quality. Possiblythemostimportanttargetwillbetoimprovethe N use efficiency at higher N inputs, particularly by ensuringefficiency of useof thehigherN inputsinthe grain.

A hugely useful resource is the wide genetic variation availableto cerealbreedersand researchers. Significant butlimitedvariationexistsin moderngermplasmpools; however, a huge opportunity exists to exploit more diversegermplasmcollections suchas the Watkins col-lection[50]andidentifyefficiencyalleleswhichmayhave beenlosttothemoderngermplasmpool.Screeningand exploitingsuchmaterialrequireamajorcommitmentto largescaletrialsatcontrastinglocationsandin multiple 40 Physiologyandmetabolism

Figure3

Current Opinion in Plant Biology

years,aswellastheexpertisetophenotypeforphenology, architecture and nutrient use efficiency parameters. A typical trial of bi-parental wheat populations illustrates the diversityof formand theimpact of nitrogen inputs (Figure 3). The critical challenge is having the right phenotypic screening strategies which can be applied with high throughput attheappropriate scale.The use of optical sensors [51] and crop indices such NDVI (normaliseddifferencevegetationindex)[52]tomeasure canopydevelopmentand canopynutritionalstatus have beenwidelyemployed,bothwithground-based observa-tionsusingspectrometersandhand-heldcontactdevices suchasSPADmeters[53]orusingaerialimagery[54,55]. The most recent developments include automated mobile [56] and fixed [57] platforms for high temporal and spatialanalysis ofsuchparameters.

Conflict

of

interest

statement

Nothing declared.

Acknowledgement

The authors acknowledge the Biotechnology and Biological Sciences ResearchCounciloftheUnitedKingdomforfundingoftheDesigning FutureWheatprogramme(BB/P016855/1)andtheUnitedKingdom DepartmentforEnvironment,FoodandRuralAffairsforfundingofthe Wheat Genetic Improvement Network (CH1090).

References

and

recommended

reading

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