A Genetic Framework for Grain Size and Shape Variation in Wheat Author(s): Vasilis C. Gegas, Aida Nazari, Simon Griffiths, James Simmonds, Lesley Fish, Simon Orford, Liz Sayers, John H. Doonan and John W. Snape Source: The Plant Cell, Vol. 22, No. 4 (APRIL 2010), pp. 1046-1056 Published by: American Society of Plant Biologists (ASPB) Stable URL: http://www.jstor.org/stable/25680117 Accessed: 16-12-2015 17:24 UTC REFERENCES Linked references are available on JSTOR for this article: http://www.jstor.org/stable/25680117?seq=1&cid=pdf-reference#references_tab_contents You may need to log in to JSTOR to access the linked references. Your use of the JSTOR archive indicates your acceptance of the Terms & Conditions of Use, available at http://www.jstor.org/page/ info/about/policies/terms.jsp JSTOR is a not-for-profit service that helps scholars, researchers, and students discover, use, and build upon a wide range of content in a trusted digital archive. We use information technology and tools to increase productivity and facilitate new forms of scholarship. For more information about JSTOR, please contact support@jstor.org. American Society of Plant Biologists (ASPB) is collaborating with JSTOR to digitize, preserve and extend access to The Plant Cell. http://www.jstor.org This content downloaded from 204.235.148.92 on Wed, 16 Dec 2015 17:24:15 UTC All use subject to JSTOR Terms and Conditions The PlantCell, Vol. 22:1046-1056, April2010,www.plantcell.org? 2010 AmericanSociety ofPlantBiologists A Genetic Framework forGrain Size and Shape Variation inWheat Vasilis C. Gegas,a bAida Nazari,b>1 Simon Griffiths,8 James Simmonds,3 Lesley Fish,3 Simon Orford,3 Liz Sayers,3 John H. Doonan,b'1 and John W. Snapea 2 a Department of Crop Genetics, John InnesCentre, Norwich NR4 7UH, United Kingdom b Department of Cell and Developmental Biology, John InnesCentre, Norwich NR4 7UH, United Kingdom Grain morphology inwheat [Triticumaestivum) has been selected and manipulated even invery early agrarian societies and remains a major breeding target.We undertook a large-scale quantitative analysis to determine the genetic basis of the phenotypic diversity inwheat grain morphology. A high-throughput method was used to capture grain size and shape variation inmultiple mapping populations, elite varieties, and a broad collection of ancestral wheat species. This analysis reveals that grain size and shape are largely independent traits in both primitivewheat and inmodern varieties. This phenotypic structure was retained across the mapping populations studied, suggesting that these traits are under the control of a limitednumber of discrete genetic components. We identifiedthe underlying genes as quantitative trait loci that are distinct for grain size and shape and are largely shared between the differentmapping populations. Moreover, our results show a significant reduction of phenotypic variation ingrain shape in the modern germplasm pool compared with the ancestral wheat species, probably as a result of a relatively recent bottleneck. Therefore, this study provides the genetic underpinnings of an emerging phenotypic model where wheat domestication has transformed a long thinprimitivegrain to a wider and modern shorter grain. (Triticumturgidumssp dicoccoides; BBAA) to the domesticated INTRODUCTION Wheat epitomizes the effectiveness of artificialselection and breeding inshaping a crop to suit human social and historical as well circumstances as economical incentives. The domesti cation ofwild einkornand emmerwheat around 10,000 years ago the marked from a transition hunter-gatherer society to an agrarianone with considerable effectson theevolutionof human civilization. bread wheat, Moreover, followed or common the emergence of hexaploid, breed and extensive by further selection ing, led to a crop species of significantfinancialand nutritional importance since itprovides one-fifth of the calories consumed by humans today (Dubcovsky and Dvorak, 2007). One of themain components of the domestication syndrome in cereals domesticated (i.e., the species set the that distinguishes an in is increase ancestors) of characters from itswild grain size (Fuller,2007; Brown et al., 2009). Archaeobotanical evidence fromaround the FertileCrescent region indicates that monococ the transitionfromthe diploid wild einkorn (Triticum cum ssp aegilopoides; AmAm) and tetraploid emmer wheat 1 Institute of Biological Science, Current address: University of Malaya, 50603 Kuala Lumpur, Malaysia. 2 to john.snape@bbsrc.ac.uk. Address correspondence for distribution of materials The authors responsible integral to the with the policy described in this article inaccordance findings presented in the Instructions forAuthors (www.plantcell.org) are: John H. Doonan and John W. Snape (john.snape@bsrc. (john.doonan@bbsrc.ac.uk) ac.uk). ^Some figures in this article are displayed and white in the print edition. ^Online version contains Web-only data. www.plantcell.org/cgi/doi/10.1105/tpc.110.074153 in color online but in black (T. monococcum forms ssp monococcum and T. turgidum ssp dicoccum, respectively)was associated with a trend toward largergrains (Feldman, 2001; Fuller,2007). This phenomenon is thought to have occurred relativelyquickly and preceded the transitionto nonshattering/free-threshing (two of themost im portant components of the domestication syndrome) wheat forms (Fuller, 2007). Mainly because of its effect on yield, increasing grain size continues a major to be selection and modern tetraploid(T. turgidumssp durum) and breeding target in aestivum ssp aestivum; BBAADD). hexaploid wheat (Triticum not appear does shape of the wheat domestication Grain nent other cereal species, domestication process such as involved been a major compo with in contrast syndrome, the rice (Oryza sativa), where both for grain strong selection to have size and shape (Kovach et al., 2007), but has been a relatively recent breeding target dictated by the market and industry requirements. Indeed, grain shape (and size), density, and are importantattributes fordetermining themarket uniformity value of wheat grain since they influence the milling perfor mance (i.e., flourquality and yield). Theoretical models predict thatmillingyield could be increased by optimizinggrain shape and size with largeand spherical grains being theoptimum grain morphology (Evers et al., 1990). Several other quality criteria used by the industryare influenced by grain morphology. Specific weight (kilogramsofmass per literbulk grain) is used extensively to grade wheat beforemilling,and itisthoughtto be related to the grain shape or size since these parameters determine theway the individualgrain packs. Grain size was also found to be associated with various characteristics of flour, such as protein content and hydrolyticenzymes activity,which This content downloaded from 204.235.148.92 on Wed, 16 Dec 2015 17:24:15 UTC All use subject to JSTOR Terms and Conditions Genetic Analysis ofWheat GrainMorphology inturndetermine baking quality and end-use suitability (Millar et al., 1997; Evers, 2000). Though genetically and developmental^ important,the phe notypic and genetic variation of wheat grain morphology is surprisinglyunderstudiedmainly due to the difficultyinquanti fyingthistrait.Previous studies used a limitednumberofmetrics thatwere analyzed discretely largelyinsingle mapping popula tions (Giuraand Saulescu, 1996; Campbell et al., 1999; Dholakia et al., 2003; Breseghello and Sorrels, 2007; Sun et al., 2009). This approach identifiesonly pairwise associations between traits and single-traitgenetic effects; therefore,itis limitedinproviding a comprehensivemodel forthephenotypicand genetic structure of the quantitative traits.One approach is to integrate the into a different metrics low dimensional framework (i.e., a few variables that capture most of the traitvariation) and subse the genetic basis of the phenotypic quently use this to identify relationshipbetween grain size and shape. Another problem is that the use of single biparental mapping populations reveals only part of the genetic architectureof the traitsand restrains identificationof background-specific alleles. The inference power of quantitative analysis to determine the genetic archi tectureof a traitcould be enhanced by analyzing, inthe same experiment,multiple populations that representa wider sample of genetic variationpresent (Holland,2007). Therefore, to gain deeper insights intothe genetic basis of grain size and shape several variation, different populations of recombinantdoubled haploids (DH) thatcapture a broad spec trumof thephenotypic variationpresent intheelitewinterwheat germplasm pool fromaccessions varieties were were exploited. Furthermore, grain material of primitivewheat species and modern elite measured to determine the phenotypic structure of the traits and assess the extent of variation retained in domesticated wheat. We show thatgrain size is largely inde pendent of grain shape both in the DH populations and in the wheat species and thatthere isa significantreductionof primitive phenotypic variation ingrain shape inthe breeding germplasm pool probably as a resultof relativelyrecent bottleneck. This phenotypic structure isattributedto a distinctgenetic architec turewhere common genetic components are involved in the control of those traits in different wheat varieties. 1. DH Mapping Table Population Avalon Beaver x Cadenza x Soissons x Rialto Savannah No Lines Environments3 A x C B x S 202 DH CF07, CF08 65 DH CF07, CF08 CF, Church Numerical 76 DH 112 DH x R Sa x Charger Malacca CF06, CF07 CF07 98 DH M x C_100 Farm, Norwich, UK. suffixes show the years CF08 DH of which CF07_ each experiment carried out. was Cadenza thatdifferfor lengthand L7W,and Savannah and Rialto thatdifferforTGW and FFD (see Supplemental Tables 1A, 1C, and 1E online). extensive However, transgressive segregation exists intheDH populations,with linesshowing higherand lower phenotypic values from the parents forall traits (see Supple mental Figures 1 and 2 online). This indicates the polygenic inheritanceof the traitswith both parents contributingincreasing and decreasing traitalleles. The genotypic and environmental effectsboth withinand between differentyears were calculated forall populations and traits.Significantdifferencesamong DH lines(foreach individualpopulation)were foundforall six traits(P < 0.001). Broad sense heritability was moderate to high forall the traits,rangingbetween 0.51 and 0.95 with grain lengthand U\N across all populations (see Sup showing the highest heritability plementalTable 1 online). Phenotypic Structure of Grain Size and Shape Variation Simple linearcorrelation coefficients (Spearman's rho) were calculated between themorphological traitsstudied (see Sup plemental Table 2 online). TGW is highlypositively correlated with grain area, width, and FFD inall populations and years (r> 0.75, P < 0.001) and moderately correlatedwith grain length(r> 0.23, P < 0.001). The only exception isBxS, where TGW is not the L/W significantlycorrelated with grain length. Interestingly, no significant ratio shows in Six morphometric parameters, 1000-grainweight (TGW),grain area, width (W), length (L), L/W ratio,and factor formdensity and reproduciblycapture grain size and (FFD),which efficiently shape variation,were measured ina collection of sixDH mapping populations (Table 1, Figure 1). All the measurements were performedusing a digitalgrainanalyzer assisted by an automatic image analysis suite thatallowed high-throughputdata collec large number of grains and lines. There were no significantdifferencesbetween theparental linesformost of the traits (see Supplemental Table 1 online) with the exception of and Abbreviation Shamrockx Shango S x S Spark x Rialto Sp x R describe Variation and Heritability of Grain Size and Shape DH Populations Beaver Studied or a very weak correlation (see Sup plemental Table 2 online)with eitherof the twomain grain size variables (TGW and grain area), suggesting that the relative proportionsof themain growthaxes of the grain,which largely RESULTS tion from a Populations 1047 Soissons that differ for area and L/W, Avalon and grain shape, is independent of grain size. A principal component analysis (PCA) was performed to identifythe major sources of variation in the morphometric data sets of each DH population (Figure2) and on the popula tion-widedata set (see Supplemental Table 3A online). PCA does thatby identifying orthogonal directions, namely principalcom ponents (PCs), along which the traitvariance ismaximal (Jolliffe, 2002). The substantive importanceof a given variable fora given factorcan be gauged by the relativeweight of the component loadings (Field,2005). Inthisstudy, only variables with loading values of >0.4 were consider important and therefore used for interpretation followingthe criteriaproposed by Stevens (2009) that take intoaccount both the sample size and the percentage of shared variance between the variable and the component (Stevens, 2009). Two significant PCs, PC1 and PC2, were This content downloaded from 204.235.148.92 on Wed, 16 Dec 2015 17:24:15 UTC All use subject to JSTOR Terms and Conditions 1048 Figure The PlantCell 1. Phenotypic Variation inGrain Size and Shape inSix DH Mapping Populations. AxC (A), BxS (B), SxS (C), SaxR (D), SpxR (E), and MxC (F)-Within each panel, the grains at the extremities correspond the order (i.e., leftor right)of the cross, while the two middle grains correspond to extreme DH lines. Bars = 2 mm. [See online article for color version of this figure.] extracted foreach DH population thatcapture 88.7 to 90.9% of the variationapparent inthese populations (see Supplemental Table 3 online). Both PCs showed analogous organization inall six populations (Figure 2), with PC1 (55.6 to 67.1%) and PC2 (23.8 to 30.1%) capturing primarilyvariation ingrain size and grain shape, on PCA Furthermore, respectively. a population size differences, a proportional where increase along both the longitudinal(length)and proximodistal (width)axes positively with an associates increase ingrain area and subsequently grain weight (Figure2C). On the other hand, PC2 captures primarily grain shape differenceswith L7Wratioand grain lengthbeing the main explanatory factors (Figure2C). Genetic Architecture IsConsistent with the Phenotypic Structure forGrain Size and Shape Variation control of distinct genetic components. To address this question, we identifiedthe genetic basis underlyingall six morphometric traits studied. Quantitative trait loci (QTL) analysis was per formed on six DH populations for either two consecutive years (AxC,SxS, and BxS) or for 1 year only (SpxR,MxC, and SaxR). Consistent with the extensive transgressive segregation ap parent in themorphometric data (see Supplemental Figures 1 and 2 online), numerousQTL with dispersed effectsbetween the to 50.2%, 6.6 respectively. In the AxC and BxS populations, where the broad sense heritabilityisvery high forall the traits, most of the QTL are common between for any years given population (see Supplemental Figures 3A and 3C online). The strong positive correlations between the grain size variables (i.e., TGW, area, width, and FFD) and between the grain shape variables (i.e., L/W and length) can be attributed to cosegregat ingQTL with thesame allelic effect. Indeed,QTL forthegrainsize variables cosegregated consistently inall populations and years. The same holds true fortheQTL forgrain lengthand L7W (see Supplemental Text 1 online). These findingsare consistentwith thephenotypicarchitecture of themorphometric traitsstudied, where grain size is largely independentof grain shape inthe individualpopulations as well as The phenotypicmodel forthe grain size and shape parameters (Figure2) suggests that these two traitsare probably under the lines following parentswere identified(see Supplemental Figure 3 and Supple mental Tables 4 to 6 online). Specifically, 54 QTL were identified inAxC, 18QTL inBxS, 10QTL inSpxR, 10QTL inMxC, 12QTL in SaxR, and 13 QTL in SxS. The LOD scores and variation explained by each of these QTL range between 3.0 and 18.1, and wide data set also identifiedtwo PCs, comparable to the ones identifiedfor the individualDH populations, each of which explained 68.7 and 23.3% of the variation, respectively (see Supplemental Table 3A online). Therefore, PC1 describes grain to the parental QTL in the population-wide data set. To further substantiate on the principal analysis was performed components this, (i.e., PC1 and PC2) extracted fromeach DH population (Figure 2). Similarapproaches have been used before forthestudyoforgan morphology inother species (Langlade et al., 2005; Feng et al., 2009). A totalof 25 QTL forPC1 and PC2 were identifiedinthesix DH mapping populations with LOD scores rangingbetween 2.9 and 10.6, and the amount of variation explained was between 9.2 and 36.4% (see Supplemental Table 7 online). The majority of the are located on fivechromosomes, 1A, 3A, 4B, 5A, QTL identified This content downloaded from 204.235.148.92 on Wed, 16 Dec 2015 17:24:15 UTC All use subject to JSTOR Terms and Conditions Genetic Analysis ofWheat Grain Morphology 1049 _J_BxS L/W ^ TGVV^ FFD ^ _AxC ^AF^A^\W^^ -0.60 -0.80 PCI _-| oo> ^ ijj^MbN) | ooo000000 go'_i_i_I jibbob 1 pci -7 -6 -4 ^5 ._ -3 -2v-^^?e^/ 4 5 76 o 04 Figure 2. A Morphometric . 2/ . -3 Model forVariation i! i> . ^ssv ! S XVS o inGrain Morphology in Wheat Mapping 3 Populations. ingrain size is captured by PC1 with both grain length and width having large effects, whereas PC2 describes variation ingrain ingrain length. Component shape largely through changes loading (i.e., correlations between the variables and factor) forPC1 (A) and PC2 (B) for each population are color coded. (A) and (B) Variation (C) Score distribution for PC1 and PC2. Schematic representation of variation in grain size and shape captured by PC1 (x axis) and PC2 (y axis), respectively. and 6A (twocolocated QTL or more). Three QTL forPC2 were detected intheBxS, SpxR, and SaxR on chromosome 1A, each of which 29.2,11.3, explained and 18.5% of the variation ingrain shape, respectively(Figure3; see Supplemental Figure4 online). Meta-analysis identifiedtwo QTL at close proximityto each other, MQTL1 between markers psp3027 and wPt5374 and MQTL2 between GluA1 and s12/m25.6 on the consensus map for 1A (Figure3, Table 2). Significanteffects both forPC1 and PC2 were identifiedinAxC, BxS, and SpxR on chromosome 3A. Specifically, twoQTL forPC2 were detected inAxC and SpxR populations around markers while one QTL forPC1 was bard9 and wmc264, respectively, identifiedinBxS around marker gwm2 (Figure 3). Meta-analysis revealed one meta-QTL that 3A1A 4B s635ACAG-barc19 (Figure3, Table 2). Two spanned the interval QTL forPC1 were detected inBxS and AxC populations on chromosome 4B, around markers s14/m15.6 respectively (Figure3). One meta-QTL was the markers gwm149 and wmc47 on the wheat and wmc349, identifiedbetween consensus map (Figure3, Table 2). QTL both forPC1 and PC2 were identifiedinAxC, SxS, SpxR, and SaxR populations on chromosome 5A (Figure 3). Meta analysis identifiedthreemeta-QTL in the intervalswPt4131 gwm293, wmc492-gwm666, and cfa2185-wmc727 (Figure 3, Table 2). Effects forPC1 were identifiedinAxC, MxC, and SaxR inthemiddle of chromosome 6A, whereas a QTL forPC2 was detected inAxC on the longarm of 6A (Figure3). Two meta-QTL 6A5A ^?^? ^hb^b^h^bhhbhhb?mm.%%%%t%%%%%%%wmi%^m ^^^1%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%* mmm%%%%%%%mm.%%%%^k^m ^^^^^^mhhmhhhhhmhm* BxS ^^^^S^Sf^^^^l ^^BSSSSSES^S^ ^BffiSBSBBBB! fSiBSSSBHHIBBIS SIBiiiBSSEES^^l^^^^^ mxc Figure 3. Genetic Structure Underlying Phenotypic Variation. forgrain size and shape in the DH mapping populations. Schematic representation of colocated QTL identified forPC1 genetic components and PC2 on fivemain chromosomes (i.e., 1A, 3A, 4B, 5A, and 6A) and their corresponding meta-QTL. QTL for each DH population are color coded. in red. The length of each QTL denotes 2-LOD confidence intervals on the wheat consensus Meta-QTL are depicted map (Somers et al., 2004). Common This content downloaded from 204.235.148.92 on Wed, 16 Dec 2015 17:24:15 UTC All use subject to JSTOR Terms and Conditions 1050 The PlantCell 2. Meta-QTL Table Traits3 Identified across All Populations whereas grainwidth is the leastvariable trait(mean ? sd = 3.3 ? and Traits 0.4 mm, PCb Mapping Interval0 Chromosome Chromosome Mapping Interval shape in the primitive wheat 2A wmc819-gwm47 cfd233-wmc41 3A s635ACAG-barc19 3A gwm149-wmc47 2Dgwm349-wmc167 3AwPt1688-barc45 5A wPt4131-gwm293 5A 3AwPt9562-wPt9215 5A wmc492-gwm666 cfa2185-wmc727 PCA identifiedtwo significantPCs thatcollectivelyexplained 99.5% of the totalvariationof the traits inprimitive wheat (Figure 5). For PC1 (55.25%), themain explanatory factorswere IAN and whereas forPC2 (44.2%), grainarea and widthwere grain length, themain explanatory factors (Figures5A and 5B). Therefore,PC1 captured variation ingrain shape primarilythroughchanges in grain length,and PC2 captured variation ingrain size through 6A 6A 79 psp3029-wmd wPt5549-wPt5480 6A 7 7O-wmc 72 7 traits. Only meta identified for the individual morphometric to more than two different populations are shown. that correspond A detailed description of the QTL for the individual traits and their aMeta-QTL QTL can be found inSupplemental Text 1 online. corresponding meta-QTL that corre identified for the individual PCs. Only meta-QTL bMeta-QTL spond to more than two different populations are shown. mapping -0.75, r = 0.45, intervals on the consensus map (Somers et al., 2004). were identified: MQTL8 corresponds to the PC1-specific QTL between psp3029 and wmc179, and MQTL9 corresponds to PC2 QTL between wPt5549 and wPt5480 (Figure3, Table 2). inGrain Size and Shape through Domestication Breeding Wheat domestication led predominantlyto an increase ingrain further intensified by contin a phenomenon that has been it is still unclear how However, breeding of hexaploid wheat. impactedon grain shape and how much of the variation apparent inthewildwheat species still grainsize/shape these processes wheat in the modern address these varieties and breeding germplasm. wheat species origi ancestral questions, natingfromthebroader FertileCrescent regionwere analyzed for variation ingrain size and shape (Figure4). The collection that was analyzed includes all the known species of the genus Triticum based on the most commonly accepted taxonomic and phylogenetic classification for wheat (Feldman, 2001; Golovnina et al., 2007). Moreover, to assess the variation within each species, a comprehensive sampling and analysis of differ ent accessions of each respectively) species was performed, each of which see Supplemental Figure 5 and Supplemental Table 8 online), r= respectively). and Triticum corre ispahanicum varieties where grain shape is considerably variation reduced. Indeed,?70% of the variationcaptured by PC1 inthe DH population data sets is attributed primarilyto grain size differenceswith only?24% attributedtovariation ingrain shape inthewild species, (Figure2) as opposed to?44 and ?55% respectively.Much of the grain shape variation present in the primitivewheat species has been lost inthemodern breeding germplasm probably due to selection formore uniformgrain shape inthe elite varieties. Figures 6A to 6C illustratehow grain dimensions (i.e., lengthand width) and theirrelativeproportions (i.e., LAN) have changed during and domestication breeding. Specifically, grainwidth appeared markedly increased intheDH populations and in the collection of elite varieties examined (mean = 4.08 mm; see Supplemental Table 9 online), whereas there is a much = grain length isdecreased (mean 7.3 mm) compared with the wild species (mean = 3.3 and 8.52 mm, respectively) (see Supplemental Table 8 online). These changes in grain axial dimensions resulted ingrain shape modifications that led from a predominant long and thinprimitivegrain (meanL/w= 2.63) to a much shorter and wider grain in the DH populations and elite varieties (meanuw = 1.78). Moreover, wider spectrum of grain shape phenotypes inthewild species (rangetvw = 2.64, minimum = 1.54, maximum = 4.2) compared with the DH populations and elite varieties (ranges minimum ?1.6, corresponded to a distinct geographical locale or country of origin (http://data.jic.bbsrc.ac.uk/cgi-bin/germplasm/triticeae/). mm2 ? Extensive variation exists forgrain area (mean ? sd=22.8 = 8.5 ? = 18.4 1.1 mm, 3.6, range length (mean ? sd mm2), = = 2.6 ? = 5.6 2.64; 0.6, range range mm), and L/W (mean ? sd IVW (r = 0.67, and spond to the two extreme grain shape phenotypes along PC1, with the latterhaving approximately twofold longer (L/W= 3.4) but almost as wide grains as T. sphaerococcum (L/W= 1.5) (Figure 5C). On the other hand, Triticumurartu and Triticum sinskajae representthe twoextreme phenotypes intermsof grain size along PC2 (Figure 5C), with T. sinskajae having approxi mately twice thegrainsize (?25 mm2 versus 14.6mm2) primarily due to increased grainwidth (?4 mm versus 2.2 mm). Thus, itis evident thatbroad variationboth ingrainsize and shape exists in the primitive wheat species incontrastwith theDH populations and modern To P < 0.001, P < 0.001, inwidth. changes Triticum sphaerococcum wmc6807-psp3071 cos07Tb-wPt5480 6A remains showed 0.67, mile 5A uous grain area Indeed, species. no significantcorrelationwith IAN (r= 0.13, P = 0.335), whereas correlatedwith both area (r= lengthand widthwere significantly psp3027-wPt5374 GluA1-s12/m25.6 5A wPW654-wPt3069 size, from the DH 1A gwm443-cfa2104 5A wmc492-w/77c475 and to the results 1A 4B s14/m15.6-wmc349 Changes Similar 1AwPt-8347-s12/m25.6 3A barc19-cfa2262 cMeta-QTL 1.94 mm). 1A barc263-wPt7030 2D 5A = range populations, grain size appeared largelyindependent fromgrain maximum ?0.4, ?2.0). DISCUSSION We used high-throughputmorphometric analysis to quantify grain size and shape variation and determine its underlying This content downloaded from 204.235.148.92 on Wed, 16 Dec 2015 17:24:15 UTC All use subject to JSTOR Terms and Conditions Genetic T. urartu(Au) aegilopoides paleocolchicum monococcum \-,-' T. monococcum ssp. dicoccoides polonicum Analysis of Wheat 1051 Grain Morphology armeniacum typicum T.militinae (GGAmAm) ?-1 T. timopheevii ssp. (GGAmAm) T.sinskajae(AmAm) (AmAm) carthlicum turanicum speciosum i-,-1 dinurum dicoccum T. ispahanicum (BBAUAU) T. turgidum ssp.(BBAuAu) macha spelta Figure 4. Phenotypic Variation compactum i-,-' sphaerococcum T. aestivum ssp. inGrain Size and Shape T. vavilovii (BBAUAUDD) T. zhukovskyi (GGAA AmAm ) aestivum (BBAUAUDD) inAncestral Wheat Species. of the genus Triticum. Species are organized according to the ploidy level from diploids Representative grains are shown for22 species and subspecies T. sinskajae is given inparentheses. isa mutant free-threshing form of T. monococcum to hexaploids. The genome of each species (Goncharov et al., 2007), T. militinae represents a free-threshing mutant form of T. timopheevii (Feldman, 2001), and 7. vavilovii (BBAUAUDD) and T. zhukovskyi = 3 mm. (BBAAAmAm) are hexaploid hulled wheats. Bar for color version of this online article [See figure.] genetic basis inan extensive collection that includedDH map ping populations, varieties. ancestral wheat species, and commercial Quantitative analyses of themorphometric data revealed that grain size and shape are largely independent traits.This is unlikelyto be the resultof artificialselection during breeding since wheat. are also and shape At the developmental size variables independent level, this phenomenon inprimitive may reflect differential modulation ingrowth (orgrowtharrest)along themain axes of the grain at different developmental stages. In tomato (Solanum lycopersicum),forexample, loci have been identified that affect fruit shape but not size and vice versa (Frary et al., 2000; Tanksley, 2004). Specifically, the fw2.2gene was shown to size but not shape variation (Frary be a major determinantforfruit et al., 2000), whereas theovate (Liuet al., 2002) and sun (vander effect Knaap and Tanksley, 2001) locialter fruitshape with little on size due to asymmetricgrowth inthe longitudinalaxis of the carpels and young fruit, respectively. The notion that certain or graingrowthcould lead developmental constraintsduringfruit to morphological changes is furthercorroborated by recent studies on grain size/shape genes in rice (Fan et al., 2006; Song et al., 2007; Shomura et al., 2008; Takano-Kai et al., 2009). The GS3 locuswas found to have major effectson grain length and weight and smaller effectson grainwidth (Fan et al., 2006), and the longergrains can be attributed to relaxed constraints duringgrainelongation (Takano-Kai et al., 2009). The GW2 gene was shown to alter grain width grain lengthowing to changes and weight and to lesser extend inthewidth of the spikelet hull This content downloaded from 204.235.148.92 on Wed, 16 Dec 2015 17:24:15 UTC All use subject to JSTOR Terms and Conditions 1052 The PlantCell Area_Width L/W Length 0.451-;-!-a-i 0.25" A j 0.05-- I-!_ -\ -0.15- \ X -0.35!\ -0.55- r I X PP1 * 4 ppp6PP<=> -0.75H B,^ T T. sphaerococcum (T. urartu U4 I -2 -3 Figure 5. A Morphometric ingrain shape Variation (55.25%) Model *1 2 . and size .\-.-. 4 ? \ 3 A *_3 Bn ? U inGrain Morphology ? * n > inAncestral Wheat ^ .V. "o < ^5 ro Species. is captured by PC1 and PC2, respectively. (A) and (B) Component loading for PC1 (A) and PC2 (B), as inFigure 2. that correspond (C) Score distribution for PC1 and PC2. Grains of the species is shown inparentheses. explained by each principal component to extreme size or shape (arrows) are shown. Variation phenotypes [See online article for color version of this figure.] (Song et al., 2007). Similarly,theSW5 gene has been reportedto effect grain width by modulating the size of the outer glume et al., 2008). in comparative advances (Shomura Recent wheat and rice genomes have confirmed analysis between extensive synteny 5A and 6A. The rice gw3.1 QTL (Thomson et al., 2003) and itsunderlying lociGS3 (Fan et al., 2006; Takano-Kai et al., 2009) correspond to the very strongwheat QTL forgrain size on chromosome 4B. The GS3 effecton grain size isattrib uted primarilyto alterations ingrain lengthand less so inwidth (Fan et al., 2006). However, the grain weight QTL on wheat chromosome 4B cosegregates consistently only with grain width QTL, suggesting a differentmechanism. Itwas recently reported (Li et al., 2010) that the orthologous gene of GS3 in maize (Zea mays) affects kernel weight but also through a different mechanism to thatdescribed inrice.The GW2 locus on ricechromosome 2 does not correspond toany of the identified wheat QTL. However, several grain weight, width, and length riceQTL correspond to grain size (TGWand grainwidth)wheat QTL on chromosome 6A. Such orthologous relationships be tween differentspecies should remainspeculative untilpositive through gene-specific comparative is analysis provided. The sequence between the two species (Sorrellset al., 2003; Quraishi et al., 2009). This enables us to assess the positional correspondence between QTL identifiedinwheat and known QTL or loci that affectgrainmorphology inrice.Several QTL forgrainweight and length(Thomson et al., 2003; Li et al., 2004) were reportedon rice chromosome 3 and correspond toQTL forrelated traitsidentified inthisstudy.Specifically, riceQTL forgrainweight correspond to TGW and grain width QTL on the syntenic regions of wheat chromosomes confirmation observed ary process and fixed structure phenotypic inwhich grain size over independently and might reflect an evolution shape have the wheat been selected domestication. Our analysis clearly demonstrates thatPC1 and PC2 are under the control of distinctlydifferentgenetic components inall of the studied. Even when the various morpho populations mapping metric traits were considered the QTL for either grain separately, size or grain shape parameters were frequentlycolocated inthe different mapping populations, indicatingthatcommon genetic underlie components the observed variation in grain morphol thereare a number of differences intheQTL ogy. Interestingly, distribution across that share a common even the populations, parent, showing between that populations identifying back ground-specific effects by analyzing multiple populations crucial more in determining apparent when the genetic we consider architecture. the results This is becomes from previous studies, most ofwhich analyzed single populations. In this study, QTL have been identified inmost of the groups, homeologous but those on chromosomes 1A, 3A, 4B, 5A, and 6A have the largestand most consistent (across different populations) effects on grain size and/or shape. Strong QTL for grain lengthand grain shape (PC2) were on chromosome 1A inthreepopulations, BxS, SpxR, identified and SaxR. Effects forgrain lengthon 1A have been previously reported. Grain 1A in a disomic length was population affected negatively by chromosome derived from a cross between long and shortgrain parental lines (Giuraand Saulescu, 1996). A QTL This content downloaded from 204.235.148.92 on Wed, 16 Dec 2015 17:24:15 UTC All use subject to JSTOR Terms and Conditions Genetic ^ 50 I 40 ^ 30? 20 n n I" I J] wk m centromeric IB II 3.25 3.5 3.75 . rw,_fc_, 4 4.25 7.5 8 8.5 effects .(I li n n n . 9 9.5 10 10.5 related ^ ^ |~| _ 2 ^| 2.4 2.2 ^| Var'et'eS ^B 2.8 3 inAncestral inGrain Axial Dimensions and Modern Frequency distributions forgrain width (A), length (B), and U\N (C) in the DH mapping populations, Triticum species, and wheat varieties. [See online article for color version of this figure.] for grain lengthwas identified in a recombinant inbred line population between two Chinese winter elite varieties at an equivalent chromosomal positionon 1Aas theQTL inBxS, SpxR, and SaxR reported inthisstudy (Sun et al., 2009). Homoeologous group 3, especially chromosome 3A, has a strong effect both on grain size and shape across the DH populations studied here, yetQTL forrelated traits (grain length and area) have been reported only inone previously studied population on chromosome 3B (Campbell et al., 1999). The QTL forgrain size and shape on chromosome 3A identifiedin this analysis are of particular interestsince theirmapping intervals coincide with the approximate position of the sphaerococcum locus (Salina et al., 2000). The 3A et al., (Salina referred as dwarfing respec genes), sphaerococcoid grain size Chromosome parameters. in four of the six populations parameters None studied. of but significant associations loci on between 5A were reportedbefore (Breseghello and Sorrells, and grain length 2006). Inthisstudy, strongQTL forgrain size-related traitshave on chromosome 6A inthreeDH populations (AxC, been identified SaxR, and MxC) and intwo previouslydescribed studies (Giura and Saulescu, 1996; Sun et al., 2009). Specifically,QTL forgrain width (Sun et al., 2009) have been detected before at an ap as the grainwidthQTL intheAxC proximatelyequivalent interval 6A was Chromosome populations. also found to have a positive effecton FFD (Giuraand Saulescu, 1996) consistent with the effectsdetected intheAxC and SaxR populations. Therefore, comparison of theQTL described herewith those identifiedinother studies showed thatallelic variation forsome, L/W Figure 6. Changes Wheat. (frequently of this loci on other and SaxR 1.8 on gwm720 above. chromosome, CIZl Triticum ^ and gwm2 the previous studies identifiedQTL for related traits on this 11 70 " 40 jj (Salina respectively 5Awas found to have largeeffectson both grainsize and shape Length (mm) c 3A, tively,thatwere shown to affectgrainweight, among other traits of these grainsize (Flinthamet al., 1997). Therefore,theproximity QTL to Rht-B1 and Rht-D1 might indicate furtherpleiotropic n 1olnlll. Ill 7 and 3B, Strong grain size QTL have been identifiedon chromosomes 4B and 4D intheBxS and AxC populations. However, effectsof chromosome 4B on grain lengthand width have been previously identified only inone population (Giuraand Saulescu, 1996). The AxC and BxS populations segregate fortheRht-B1 and Rht-D1 homoeoalleles I 30- I | & 20- J | C markers mentioned 4.5 50 6.5 3D, 2000). This position corresponds to themapping interval(highest LOD scores) ofQTL forgrain lengthand L/W inAxC and grain width inBxS. QTL forgrain length inSaxR and grainwidth and LVW inMxC were adjacent to the S3 locus mapping interval 701 ~ 1053 et al., 2000). The S3 locuswas shown to be located between the Width (mm) B on chromosomes mapped _=_,_m-,_1L,_i,_WB 0 3 Grain Morphology threegenes S1,S2, and S3 of thesphaerococcoid mutationwere 601 A ofWheat Analysis mutation reduces alteringgrain shape and size. The grain length,thus significantly effects for example, diverse germplasm. on 1A and 6A, appear to occur the majority However, of in frequently them appear unique to thisstudy,most notablyeffectson 3A, 4B, and 5A. Morphometricanalysis shows thatwheat grainevolved froma longand thinprimitivegrain to a much wider and shortermodern grain. Moreover, variation of grain shape appeared significantly reduced not only in themodern elite varieties but also in the mapping populations, suggesting that the naturalgenetic diver sity present inthe ancestral wheat species has been reduced during the development of the modern elite cultivars. One possibility isthatdiversity ingrainshape was reduced as a result of the polyploidyspeciation of T. aestivum. However, hexaploid wheat retained a relatively large percentage of the nucleotide diversityofA and B genomes found inthe tetraploidancestors, suggesting that ploidy differences imposed a weak barrier to gene flow, at least from the tretraploid ancestor, the during emergence of the hexaploid wheat (Dvoraket al., 2006; Haudry et al., 2007). Overrepresentation of grain size and shape QTL in the A and B genomes furthersupports this notion. The data presented here (see Supplemental Table 8 online) indicate that the phenotypic variation for the main grain shape parameters, grain lengthand U\N, has actually increased in the hexaploid species (T. aestivum ssp; rangeL This content downloaded from 204.235.148.92 on Wed, 16 Dec 2015 17:24:15 UTC All use subject to JSTOR Terms and Conditions = 3.1 mm; range^ = 0-91) 1054 The PlantCell compared with that of the tetraploid ones (T. turgidumssp; rangeL = 2.0 mm; = range^ The 0.6). other possible explana tionsare that the reduction ingrain shape variationapparent in themodern germplasm and elite varietiesmight have appeared eitherat veryearly stages of theevolutionof common wheat (ssp or at aestivum) later stages after the emergence of the subspe cies. T. aestivum ssp spelta and ssp macha represent hexaploid hulled wheats (Feldman, 2001) and were very similar to the tetraploid species in terms of grain shape (see Supplemental Table 8 online). It isbelieved thatT. aestivum ssp spelta, at least theAsiatic type,gave riseto nonhulledor free-threshing common wheat (ssp aestivum) (Feldman, 2001). Therefore, the reduced in grain variation in common observed shape wheat have may been the resultof a bottleneck thatoccurred duringthe transition fromthe hulled to free-threshingform.The lowest traitvalue in the hexaploid species is provided by T. aestivum ssp sphaer occocum, which is thought to have emerged fromT. aestivum ssp aestivum as a resultofmutation at theS gene and imposed a significantalteration ingrain shape (Salina et al., 2000). Thus, part of the grain shape diversity found inhexaploid wheat (T. aestivum ssp) has risen relativelyrecentlyand most likelyafter the emergence of common wheat (ssp aestivum). This then that strong suggests as such mutations, the sphaeroccocum, were selected against at the early stages of wheat breeding possibly because of undesirable pleiotropic effects on other traits. Further selection at later stages for certain grain morphol ogy and greater uniformity among the differentvarieties could have limitedthegenetic variation inthegene pool even more and subsequently resulted inthe predominant grain shape found in the modern elite varieties. The present genetic and phenotypic structure supports an model emerging for grain size and shape variation, where grain size has progressively increased throughalterationsboth ingrain width and length,followed at laterstages by modifications in largely through grain shape changes in grain length. Elucidating the genetic basis of variation ingrain size and shape inwheat is to the effort to improve yield potential and process in the current climate where food ing performance, especially is at the epicenter of crop research worldwide. security instrumental METHODS Genetic and Field Trials Resources The DH populations and genetics maps used inthis study were generated as was described previously (Snape et al., 2007; Griffiths et al., 2009) and in Table 1. Specifically, summarized they are as follows: Avalon x (SxS), (AxC), Beaver x Soissons (BxS), Shamrock x Shango x Charger (MxC), and Savannah x Rialto Spark x Rialto (SpxR), Malacca (SaxR). The populations were grown in randomized, replicated field trials Cadenza Farm, Norwich, UK, over two consecutive (AxC and BxS), and 2006 and 2007 (SxS). The populations were grown only in2007 and 2008, at Church (three replicates) 2007 and 2008 years: SpxR, MxC, and SaxR respectively. The lineswere grown in large-yield plots (1x5 m2) following standard agronomic practices. Grain material of primitive wheat acces sions was provided by the John Innes Centre Triticeae Collection. The studied are given inSupplemental of the species accession Table 8 online, and further information can be found at http://data.jic. numbers bbsrc.ac.uk/cgi-bin/germplasm/triticeae/. Morphometric Analysis were measurements Morphometric using the MARVIN performed on 200 to 250 grains/line grain analyzer (GTA; Sensorik). Specifically, TGW, The ratio L/W grain width (W), length (L), and grain area were measured. and the FFD were calculated. FFD describes the differences in grain density and the deviation of a shape from a cylindrical form and * by: grain weight/(grain length grain width) (Giura and Saulescu, Statistical is given 1996). Analysis statistics and normality tests on the quantitative data were performed using GenStat v 11. Analysis of variance was performed to estimate the relative genetic contribution to trait variation for each = population and year. Broad sense heritability was calculated by h2 1 M2/M-i, where M1 and M2 are the mean square values for genotype and genotype x environment (for the two years trials), respectively (Knap Descriptive et al., 1985). Mean values of the three replicates for each year were used to calculate the correlation coefficients correlation and (Pearson's PCA was performed on Spearman's rho) and for the QTL mapping. each population (mean values for each year) and on a population-wide For the extraction of PCs, the correlation (P-W) data set using SPPS12.0. matrix method was used. Only the factors with an eigenvalue >1 according to Kaiser's criterion were retained (Field, 2005). QTL and Meta-QTL Analysis The MapQTL 5.0 software (Van Ooijen, 2004) was used for the analysis of the quantitative data. Single-interval mapping was initiallyused to identify followed by an automatic cofactor selection process (Van Ooijen, 2004). The resulted set of cofactors was then used incomposite-interval threshold LOD value for significant QTL was mapping. A genome-wide QTL set at 3.1 (P < 0.05) by performing 10,000 permutations of the original data. analysis was consensus Meta-QTL The published reference map tions were were was performed using Biomercator software v. 2.1. map (Somers et al., 2004) was used as a upon which the genetic linkage maps of the six popula intervals projected. QTL and 2-LOD confidence together with the genetic linkage maps. Meta-analysis followed by initiallyforeach population and chromosome subsequently projected conducted a population-wide analysis The number of meta-QTL minimized formeta-QTL across all the traits and years. as the model that present was determined the Akaike criterion (Arcade et al., 2004). Author Contributions the experi and designed V.C.G., J.W.S., J.H.D., and S.G. conceived ments. V.C.G. and A.N. performed the experiments. V.C.G. analyzed the data. J.S., L.F., L.S., and S.O. provided technical support. V.C.G., J.W.S., and J.H.D. wrote the article. Supplemental Data The following materials are available in the online version of this article. Supplemental Figure 1. Frequency ric Traits forAxC, BxS, and SxS. Distributions of the Morphomet Supplemental Figure 2. Frequency Distributions of the Morphomet x x Rialto, and Malacca ric Traits for Spark x Rialto, Savannah Charger. Supplemental Figure 3. QTL Identified for the Morphometric eters in the Six Mapping Populations. Supplemental Figure 4. Common in the DH Mapping Size and Shape This content downloaded from 204.235.148.92 on Wed, 16 Dec 2015 17:24:15 UTC All use subject to JSTOR Terms and Conditions Genetic Components Populations. Param for Grain Genetic Figure 5. Morphometric Supplemental Traits for Triticum Species. Table 1. Trait Variation and Heritability in the Parental Supplemental Lines and DH Mapping Populations. 2. Spearman Table Supplemental between Morphometric Traits. Supplemental Rank Correlation 3. Principal Component Table Analysis Coefficients on the Map ping Populations. Table 4. QTL for the Morphometric Traits in the AxC Table Supplemental and BxS Populations. 5. QTL for the Morphometric Traits in the SxS Supplemental Population. for the Morphometric Table 6. QTL Supplemental and SaxR Populations. Traits in the SpxR, for the Principal Components in the AxC, MxC, Supplemental SxS, Table 7. QTL and SaxR BxS, SpxR, MxC, Supplemental Supplemental Varieties. Table 8. Morphometric Data 9. Morphometric Table Text Supplemental Each Homoeologous Populations. 1. Details on Triticum Species. Data of the QTL on 61 Commercial the success Analysis ofWheat of polyploid wheat Grain Morphology under domestication. 1055 Science 316: 1862-1866. 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