Wheat seed storage proteins: Advances in molecular genetics, diversity and breeding applications

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Journal of Cereal Science xxx (2014) 1e14

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Journal of Cereal Science

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Review

Wheat seed storage proteins: Advances in molecular genetics,diversity and breeding applications

Awais Rasheed a,b, Xianchun Xia a, Yueming Yan c, Rudi Appels d, Tariq Mahmood b,Zhonghu He a,e,*

a Institute of Crop Science, National Wheat Improvement Center, Chinese Academy of Agricultural Sciences (CAAS), 12 Zhongguancun South Street,Beijing 100081, ChinabDepartment of Plant Sciences, Quaid-i-Azam University, Islamabad 45320, PakistancCollege of Life Science, Capital Normal University, Beijing 100048, ChinadVeterinary and Life Sciences, Murdoch University, Perth, WA 6150, Australiae International Maize and Wheat Improvement Center (CIMMYT) China Office, c/o CAAS, 12 Zhongguancun South Street, Beijing 100081, China

a r t i c l e i n f o

Article history:Received 12 November 2013Received in revised form28 January 2014Accepted 29 January 2014Available online xxx

Keywords:GluteninsGliadinsBreadmaking qualityCoeliac disease

Abbreviations: HMW-GS, high molecular weightlow molecular weight glutenin subunit; SDS-PAGE, sacrylamide gel electrophoresis; HPCE, high performaRP-HPLC, Reversed-phase high-performance liquid cdimensional electrophoresis; MALDI-TOF-MS, matriionization time-of-flight mass spectrometry; RP-UPLformance liquid chromatography; AS-PCR, allele-specotide polymorphisms; NILs, Near-isogenic lines; GMCD, coeliac diseases; WDEIA, wheat-dependent exIWGSC, the international wheat genome sequencingwide association studies.* Corresponding author. Institute of Crop Science, N

Center, Chinese Academy of Agricultural Sciences (CAStreet, Beijing 100081, China. Tel./fax: þ86 10 821085

E-mail address: [email protected] (Z. He).

http://dx.doi.org/10.1016/j.jcs.2014.01.0200733-5210/� 2014 Elsevier Ltd. All rights reserved.

Please cite this article in press as: Rasheedapplications, Journal of Cereal Science (2014

a b s t r a c t

Wheat seed storage proteins, especially glutenins and gliadins, have unique functional properties givingrise to a wide array of food products for human consumption. The wheat seed storage proteins, however,are also the most common cause of food-related allergies and intolerances, and it has become cruciallyimportant to understand their composition, variation and functional properties and interface thisknowledge with the grain handling industry as well as the breeders. This review focuses on advances inunderstanding the genetics and function of storage proteins and their application in wheat breedingprograms. These include: (1) The development and validation of high-throughput molecular markersystems for defining the composition and variation of low molecular weight glutenin subunits (LMW-GS)genes and a summary of the more than 30 gene-specific markers for rapid screening in wheat breedingprograms; (2) The identification of more than 100 alleles of storage proteins in wild species providecandidate genes for future quality improvement; (3) The documentation of quality effects of individualLMW-GS and HMW-GS for improving end-use quality; and (4) The analysis of a-gliadin genes onchromosomes 6A and 6D with non-toxic epitopes as potential targets to develop less toxic cultivars forpeople with celiac disease. Genomic and proteomic technologies that will continue to provide new toolsfor understanding variation and function of seed storage proteins in wheat are discussed.

� 2014 Elsevier Ltd. All rights reserved.

glutenin subunit; LMW-GS,odium dodecyl sulfate poly-nce capillary electrophoresis;hromatography; 2-DE, two-x-assisted laser desorption/C, reversed-phase ultra per-ific PCR; SNPs, single nucle-P, glutenin macro polymers;ercise induced anaphylaxis;consortium; GWAS, genome

ational Wheat ImprovementAS), 12 Zhongguancun South47.

, A., et al., Wheat seed storag), http://dx.doi.org/10.1016/j.

1. Introduction

Bread wheat (Triticum aestivum L.) is one of the most importantfood crops, with current annual global production of over 680million tonnes providing approximately one-fifth of the totalcalorific input of the world population. Meeting the multitude ofquality demands for a wide range of products in various countrieshas to be combined with the needs of an increase in population,constraints of land and water availability, and global climaticchanges. The improvements in wheat grain quality has to accom-pany high yield potential, resistance to biotic and abiotic stresses,and broad adaptation, particularly in environments undergoing thelargest effect of climate change. In the most rapidly growing mar-kets of South Asia and China, grain quality improvement hasbecome much more important largely due to rapidly increasingincomes and food diversity. The traditional quality aspects of wheatalso need to evolve as new processing technologies are established,

e proteins: Advances in molecular genetics, diversity and breedingjcs.2014.01.020

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A. Rasheed et al. / Journal of Cereal Science xxx (2014) 1e142

and as concerns on health issues increase significantly. The inte-gration of various disciplines such as functional genomics, prote-omics, bioinformatics, genetic transformation, breeding andexploitation of new genetic resources, is rapidly promoting ourunderstanding of the genetic and biochemical bases of quality traitsin wheat. Ongoing activities for quality improvement are alsocapturing information from other crops andmodel organisms, suchas rice and Arabidopsis, in order to define genes that underpin theunique quality attributes. The large datasets generated from theseresponses need to be incorporated into breeding programs inconjunctionwith high-throughput screening technology in order toefficiently combine traits for wheat cultivars with improved quality.

Wheat seed storage proteins are important quality de-terminants because they are responsible for dough elasticity andextensibility, and thus for determining the processing qualities inthe production of a range of end-products. Biochemical and mo-lecular studies in the past three decades have provided the basis forunderstanding the genetics, structure and composition of storageproteins (Ma et al., 2009). The development and utilization offunctional markers or gene-specific markers for high molecularweight glutenin subunit (HMW-GS), lowmolecular weight gluteninsubunit (LMW-GS), and gliadin alleles have dramatically improvedthe selection efficiency of breeding materials with desirable genes(Liu et al., 2012). However, most LMW-GS and gliadin genescomprise complex populations of genes (Anderson et al., 2013)with high allelic variation, and thus their contributions to qualitiesstill need to be resolved.

Wheat storage proteins also confer dietary intolerances, such ascoeliac diseases (CD) and various allergies (baker’s asthma andwheat-dependent exercise induced anaphylaxis (WDEIA)). Under-standing the mechanisms of such diseases from gluten structuresand searching for genetic variants conferring reduced intoleranceshave therefore become crucially important objectives for wheatbreeding programs, particularly in developed countries. Juhászet al. (2012a) proposed a method to define epitope toxicity inwheat proteins, especially the prolamins, by combining databaseresources, computational tools and proteomic diagnostics. How-ever, much effort is still needed to integrate this information intoapplied wheat breeding programs.

Previously, Gianibelli et al. (2001) and Shewry et al. (2003a)reviewed the genetics, biochemistry and molecular characteriza-tion of glutenin and gliadins in bread wheat, and D’Ovidio andMasci (2004) analyzed in detail the structure, function and ge-netics of low molecular weight glutenins. Bonomi et al. (2013)reviewed the structural features of water-insoluble gluten pro-teins and highlighted the modifications in gluten structure duringvarious processing stages. Similarly, Ribeiro et al. (2013) reviewedthe impact of proteomics on the study of gluten proteins and use oftransgenesis to improve the quality of gluten. The objectives of thispaper are to review the recent advances in defining the nature andproperties of wheat storage proteins, focusing on molecular ge-netics, proteomics, and practical breeding aspects, as well assummarize progress in understanding the health issues of storageproteins.

2. Genetics, molecular characterization and diversity ofstorage proteins

2.1. HMW-GS

2.1.1. Genetics and polymorphismHMW-GS accounts for around 12% of the total seed storage

protein corresponding to about 1.0e1.7% of the flour dry weight. Inthe last 20 years, the functional and structural aspects of HMW-GSin relation to dough strength have been defined. HMW-GS genes

Please cite this article in press as: Rasheed, A., et al., Wheat seed storagapplications, Journal of Cereal Science (2014), http://dx.doi.org/10.1016/j.

located at Glu-1 loci on the long arms of homoeologous group 1chromosomes are named as Glu-A1, Glu-B1 and Glu-D1, respectively(Payne et al., 1980). Each locus produces two subunits of differentsize, called x-type and y-type subunits (e.g., 1Ax and 1Ay), withcomparatively higher and lower molecular weights, respectively.All bread wheat cultivars express 1Bx, 1Dx, and 1Dy subunits whilesome cultivars express 1By and 1Ax subunits as well. Due to wheatdomestication syndrome, the gene encoding the 1Ay subunit usu-ally remains silent in bread and durum wheats. HMW-GS has a lotof allelic variation among wheat germplasm. The Glu-A1 locus hasthree common allelic variants in bread wheat; however, more than21 alleles have been documented in different bread wheat anddurum genotypes. More than 69 alleles at Glu-B1 and 29 alleles atGlu-D1 have been reported in bread wheat (McIntosh et al., 2013).The AACC glutenin allele database contains the glutenin composi-tions of over 8500 wheat genotypes from around the world (http://www.aaccnet.org/initiatives/definitions/Pages/Gluten.aspx). Therecent versions of the database also predict the quality of genotypein terms of dough strength (Rmax) and extensibility based on bothHMW-GS and LMW-GS alleles (Bekes and Wrigley, 2013).

Genetic diversity in the Triticeae gene pool can provide muchinformation in understanding the variation of HMW-GS, and canalso be an important source of genes for quality improvement.Several A-genome wild species and wild tetraploid species (Triti-cum dicoccoides and Triticum turgidum subsp. dicoccon) express theGlu-Ay gene (Waines and Payne, 1987), and a Swedish bread wheatcultivar was also found to express a Glu-Ay gene (Margiotta et al.,1996). This could be very useful for expanding the narrow allelicdiversity at the Glu-A1 locus in both bread wheat and durumwheatwhere only a limited number of x-type and virtually no y-typesubunits are expressed, despite the presence and expression ofnovel allelic variants in Triticum urartu and Triticum monococcum(Gutierrez et al., 2011). Durum and bread wheat genotypes withfour and six subunits, respectively, were also developed byreplacing the silenced subunit of Glu-A1 with expressed ones, andthey show an incremental increase in polymeric glutenin quantity,expressed as better dough strength (Alvarez et al., 2009). There areextensive studies on identification and characterization of allelicvariation for Glu-Dt1 loci from Ae. tauschii and D-genome synthetichexaploids since variation at this locus plays a more significant rolein determining dough and end-use product qualities (Xu et al.,2010; Rehman et al., 2008). Niu et al. (2011) analyzed HMW-GSin Thinopyrum bessarabicum, Th. intermedium, Lophopyrum elonga-tum, Aegilops markgrafii and their addition lines in breadwheat. Thegenes coding for HMW-GS were identified from several genera ofthe Triticeae, including Hordeum, Secale, Taeniatherum, Thinopyrum,Aegilops, Crithopsis, and Dasypyrum. Recently, a superior dough andbreadmaking quality allele from Ae. longissima was identified byanalysis of a Chinese Spring substitution line, CS-1SI(1B) (Wanget al., 2013). These novel HMW-GS alleles may serve as new ge-netic resources for quality improvement if the potentially positivecontributions to processing quality can be confirmed.

2.1.2. Molecular characterization and structural featuresThe complete coding sequences of 10 HMW-GS alleles including

Ax1, Ax2*, the silent Ay subunit, Bx7, Bx14, Bx17, By9, Dx2, Dx5, Dy10,and Dy12 are known (Forde et al., 1985; Halford et al., 1987, 1992).This has facilitated structure prediction and design of primers tosequence the other alleles used in breeding programs. The x- and y-type subunits share the same structure, signal peptide, N-terminalregion, repetitive region and C-terminal region, but x-type subunitsare characterized by the presence of a unique tri-peptide motif(GQQ), whereas in y-type subunits, the second proline is replacedby a leucine in the GYYPTSPQQ repeat motif (i.e., GYYPTSLQQ).Moreover, the majority of x-type subunits possess four conserved


http://www.aaccnet.org/initiatives/definitions/Pages/Gluten.aspx

http://www.aaccnet.org/initiatives/definitions/Pages/Gluten.aspx

A. Rasheed et al. / Journal of Cereal Science xxx (2014) 1e14 3

cysteine residues, while y-type subunits usually have sevencysteine residues. It is likely that in HMW-GS, differences in thenumber of cysteine residues are associated with variation in bread-making quality. For example, Dx5 associated with superior bread-making quality, has an extra cysteine residue located at the N-ter-minal part of its repetitive domain (Lafiandra et al., 1993). Similarly,an extra cysteine residue occurs in the middle of the domain of theAx2*B subunit, a variant of Ax2*, that shows positive effects ongluten properties (Juhász et al., 2001). In contrast, fewer cysteineresidues are present in the N-terminal domains of Bx14 and Bx20that have negative effects on dough strength (Shewry et al., 2003b).Over-expression of a Bx7 (Bx7OE) subunit resulted in increaseddough resistance compared to normal Bx7 gene. It may possibly bedue to the insertion of 18 bp in the central repetitive domainwithout affecting number of cysteine residues (Butow et al., 2003).

Several alleles from Ae. tauschii and D-genome synthetic hexa-ploids were characterized at the molecular level, including 1Dx1.5t

(Lu et al., 2005a),1Dx2.1t (Lu et al., 2005b), andDx3t andDx4t (Wanget al., 2012a). Compared with the 1Dx5 subunit, 1Dx3t has a sixamino acid insertion at 146e151 whereas 1Dx4t has a nine aminoacid deletion compared with the 1Dx3t subunit. Wang et al. (2012a)also predicted that the secondary structure of the 1Dx3t subunit hasa significantly higher a-helix and b-strand contents, indicating itmight have positive effects on dough quality. Feng et al. (2011)isolated and characterized a novel chimeric HMW-GS, Dx5/, fromwheat line W985. This subunit has six helices and one strand,including four helices in the repetitive domain capable ofenhancing the dough properties, and possibly having a high po-tential for quality improvement. In summary, molecular charac-terization of HMW-GS genes and deduced amino acid structureshelp to predict the protein structure and any potential value inimproving dough properties.

2.1.3. Proteomic and molecular diagnosisSodium dodecyl sulfate poly-acrylamide gel electrophoresis

(SDS-PAGE) has beenwidely used for HMW-GS diagnosis. However,limitations involving co-migration of some subunits, and difficultyin detecting differences in expression levels, led to inaccurateidentification of alleles that differ in functional properties. In orderto overcome these problems, more powerful separation techniqueshave been used for HMW-GS separation. For example, high per-formance capillary electrophoresis (HPCE), a method with variouselectrophoretic modes, is capable of rapid separation of HMW-GSwith high resolution from small samples. HPCE was used to iden-tify new allelic variants of HMW-GS in bread wheat and relatedspecies (Li et al., 2006; Gao et al., 2010). Reversed-phase high-performance liquid chromatography (RP-HPLC), that separatesproteins based on surface hydrophobicities, provides automatedseparation, and also allows quantitative analysis of wheat proteins(Gao et al., 2010). Along with the development of wheat proteomicsover the past 20 years, two-dimensional electrophoresis (2-DE) andvarious mass spectrometry techniques, such as matrix-assistedlaser desorption/ionization time-of-flight mass spectrometry(MALDI-TOF-MS), were developed, and these permit high resolu-tion and accurate molecular mass determinations of differentprotein components and HMW-GS with similar molecular sizes(Zhang et al., 2008a).

Gao et al. (2010) performed a comparative analysis for HMW-GSidentification by SDS-PAGE, RP-HPLC, HPCE and MALDI-TOF-MS.Overestimation of molecular mass and low resolution was themain limitation of SDS-PAGE; however, it is still the simplest andcheapest technique suitable for large-scale and high-throughputHMW-GS screening for wheat genotypes in breeding programs,especially when the glutenin composition is clear. MALDI-TOF-MShas several technical advantages including high throughput, high


resolution, and accuracy (Zhang et al., 2008a). RP-HPLC and HPCEare considered to be intermediate between MALDI-TOF-MS andSDS-PAGE. They also show significant advantages in resolving someHMW-GS, such as Bx14þBy15 and Bx20 that cannot be easilydiscriminated by SDS-PAGE. HPCE is used only for specific studieswhen stringent characterization of novel alleles is required. Bothtechniques demonstrated higher resolution and reproducibilitythan SDS-PAGE, but lower detection power than MALDI-TOF-MS.Moreover, there are no significant differences in throughput sam-ple; 100 samples can easily be handled per day with all thesetechniques. Thus, SDS-PAGE is still the most widely used method,but is rapidly being replaced by PCR methods in routine breedingprograms as DNA is available at any stages of crop development.MALDI-TOF-MS is an efficient and accurate method, and HPLC andRP-HPLC serve as complementary methods that can be used tocharacterize novel alleles.

Advances in molecular biology have enabled protein-basedlimitations of HMW glutenin allele resolution to overcome by theuse of specific PCRmarkers. Development of these markers is basedon DNA polymorphisms among the glutenin subunit genes andonce available they can be considered as perfect or functionalmarkers for HMW-GS alleles. The major advantages are high-throughput capability for assessing different alleles in breedingmaterials, and genotyping can be performed during the vegetativegrowth stages (Liu et al., 2008). Allele-specific PCR (AS-PCR)markers are available for the three most common x-type subunitsat the Glu-1 locus i.e., 1Ax2*, 1Ax1 and 1Ax Null (Ma et al., 2003; Liuet al., 2008). At Glu-B1, allele specific markers are available for x-type subunits Bx7, Bx14, Bx17 (Xu et al., 2008), Bx6 (Schwarz et al.,2004), Bx7OE (Ragupathy et al., 2008; Butow et al., 2003), and y-type subunits By8, By16 and By18 (Lei et al., 2006). At Glu-D1,markers are available to identify 1Dx2, 1Dx5, 1Dy10 and 1Dy12 (Liuet al., 2008). AS-PCR provides a fast and efficient tool for screeningdesirable HMW-GS for maintenance and improvement of qualityparameters in breeding programs. However, these markers are notreplacements for other detection techniques such as SDS-PAGE,especially in regard to related wild species because these PCRmethods are redundant when unknown subunits are present. It isimportant to validate the presence of specific alleles with diag-nostic molecular and biochemical techniques when characterizingwild species and their derivatives.

2.2. LMW-GS

2.2.1. Genetics and polymorphismLMW-GS represents about 60% of total glutenins and about one

third of the storage proteins. The genes encoding LMW-GS, namedGlu-A3, Glu-B3 and Glu-D3, are located on the short arms of group 1chromosomes (Sreeramulu and Singh,1997). In addition, three newloci Glu-2, Glu-4 and Glu-5 (McIntosh et al., 2013) located onchromosomes 1B, 1D and 7D, respectively, have also been reported.Biochemical classification revealed three classes of LMW-GS; B, Cand D types based on SDS-PAGEmobility (Jackson et al., 1983), withthe B type LMW-GS further divided into three classes, LMW-m,LMW-s and LMW-i based on the first amino acid residue thatmay be methionine, serine and isoleucine, respectively (Muccilliet al., 2010). Genes at the Glu-A3 locus encode mainly LMWi typesubunits (Zhang et al., 2004).

In early studies, 20 LMW-GS alleles were identified in 222 breadwheat cultivars from 32 countries (Gupta and Shephard, 1990),including six alleles at Glu-A3, nine at Glu-B3 and five at Glu-D3locus. McIntosh et al. (2013) list 17, 26 and 11 alleles at the Glu-3loci. However, this does not include allelic variants reported inwheat wild relatives within the Triticeae. Allelic richness at Glu-A3is relatively low, whereas Glu-B3 shows the highest levels of



polymorphism. There is a close genetic linkage between gliadinsencoded byGli-1 loci and LMW-GS encoded byGlu-3 loci (Gianibelliet al., 2001). This linkage helps in diagnosis of several Glu-B3 andGlu-D3 alleles in wheat genotypes. Several gliadins are reliablemarkers for diagnosing LMW-GS alleles due to their easy detection(Jackson et al., 1996).

Many genes encoding LMW-GS have been isolated and analyzedin cultivated and wild species of the Triticeae. Ae. tauschii, animportant species for genetic studies of LMW-GS (Rehman et al.,2008), exhibits greater variation than wheat in the codingsequence of LMW-GS. Other species studied in detail includeT. monococcum, T. urartu (Tranquilli et al., 2002), T. turgidum var.dicoccoides (Ciaffi et al., 1993) and var. polonicum (AABB) (Liu andShepherd, 1996), Ae. umbellulata, Ae. comosa, Ae. markgrafii andAe. speltoides (Li et al., 2010). The variability found for LMW-GSgenes in wild relatives indicates a large potential for improvingdough properties in wheat. Other studies of Glu-3 genes haveextended to more distant relatives, including Elytrigia (Gupta andShephard, 1990), Dasypyrum (Blanco et al., 1991), Hordeum(Atienza et al., 2002), polyploid Aegilops spp. (Li et al., 2008a),Agropyron elongatum (Luo et al., 2005), Crithopsis delileana (Guoet al., 2008), Hordeum chilense, and Hordeum brevisubulatum(Piston et al., 2005). Comparative analyses of nucleotide sequencesof LMW-GS revealed some important differences among species.For example, Hordeum chilense and A. elongatum lack the N-ter-minal regions in the predicted mature proteins (Piston et al., 2005).The potential of LMW-GS from wild species to improve the pro-cessing quality over that of desirable alleles available in currentelite wheat germplasm can now be achieved by facilitating theirtransfer into bread wheat.

2.2.2. Genomic organization and complexities of LMW-GSUnlike the two copies of genes in HMW-GS, the exact gene copy

numbers of LMW-GS genes remain unknown, which is a majorbottleneck to distinguishing most of the members in bread wheat.Copy numbers of LMW-GS genes were estimated to range from 10e20 to 30e40 (Ikeda et al., 2002; D’Ovidio and Masci, 2004; Huangand Cloutier, 2008; Dong et al., 2010; Zhang et al., 2011a, b). Inthe past 10 years, significant progress has been made in under-standing the structural complexities of LMW-GS by analyzingorthologous sequences in a wide array of wheat genetic resources.BAC library resources, in particular, provided impetus for identi-fying and cloning multi-gene families of LMW-GS (Wicker et al.,2003; Johal et al., 2004; Gao et al., 2007; Huang and Cloutier,2008; Dong et al., 2010). Complete ORF sequences for LMW-GSgenes in four wheat cultivars, i.e., Norin 61 (Ikeda et al., 2002,2006), Glenlea (Huang and Cloutier, 2008), Xiaoyan 54 (Donget al., 2010), and Chinese Spring (Zhang et al., 2011b), and theircomparative analyses successfully discriminated members of theLMW-GS gene family. Ikeda et al. (2002) isolated LMW-GS genesfrom Norin 61, and classified them into 12 groups on the basis ofsequences from N-, C-terminal domains and deduced amino acidssequences. Huang and Cloutier (2008) screened a BAC library tostudy the genomic organization of LMW-GS and identified 82positive BAC clones from Glenlea, and 12 unique active LMW-GSgenes were identified and all contained eight cysteine residues.Dong et al. (2010) dissected the LMW-GS genes in Xiaoyan 54 usingBAC library screening, expression profiling, and proteomics anal-ysis. Of 14 unique LMW-GS genes, 11 active genes were identified,three at Glu-A3, two at Glu-B3 and six at Glu-D3. Recently, Zhanget al. (2013a) reported that at least 15 LMW-GS genes were pre-sent in individual accessions from Chinese core collections, 4e6 ofwhich were located at Glu-A3, 3e5 at Glu-B3, and 8 at the Glu-D3loci. Expression and sequence analysis confirmed the presence of9e13 active LMW-GS genes in each accession. Thus, it is reasonable


to say that the number of active LMW-GS genes in bread wheat isless than 15. A consistent finding among these studies was that Glu-D3 locus contains a higher number of active genes than the otherloci, but the diversity of LMW-GS genes at Glu-D3 was the lowest(Zhang et al., 2013a).

BAC clones derived from the durum wheat cultivar Langdonrevealed that five gliadin and gliadin-like genes (pseudo or inactivegliadin genes) and two typical LMW-GS genes were present in a265 kb BAC contig derived from the short arm of chromosome 1AS,and eight gliadin genes and one typical LMW-GS gene were foundin a 140 kb genomic DNA fragment derived from chromosome 1BS(Gao et al., 2007). The gliadin genes are more clustered than LMW-glutenin genes which are separated from each other bymuch largerdistances (Anderson et al., 2013). The dispersion of LMW-gluteningenes is the result of both insertion of large blocks of repetitiveDNA owing to the rapid amplification of retrotransposons and eventhe presence of genetic loci between them. Moreover, small geneclusters were found in the contigs of each prolamin family. Thesesmall clusters were scattered with the longer DNA stretchesgenerally preventing assembly of complete contigs of LMW-GSgenes.

2.2.3. Molecular characterization and structural featuresSeveral hundreds of LMW-GS gene sequences have been

deposited in GenBank and used to predict primary protein struc-tures. This has provided a basis for designing gene- or locus-specificprimers for subsequent isolation and cloning. LMW-GS genes at theGlu-B3 and Glu-D3 loci in bread wheat were identified using gene-specific primers, and molecular markers were subsequentlydeveloped for specific haplotypes (Zhao et al., 2006, 2007a, b).Subsequently, a LMW-GS genemarker systemwas developed basedon conserved sequences and length polymorphisms among theLMW-GS genes and was used to characterize a core collection ofChinese wheats (Zhang et al., 2011a, 2013a). More than 15 genes,including 9 to 13 active genes, were successfully separated fromeach accession, greatly enhancing our understanding of the mo-lecular structure of LMW-GS. However, very few breeding pro-grams have the facilities (a 3730 DNA analyzer) to survey theirgermplasm using the marker system, and it will be very difficult toestablish associations between these genes and dough quality aswell as end-use product quality. At a more applied level, sevenallele-specific markers were designed based on single nucleotidepolymorphisms (SNPs) among allelic variants at the Glu-A3 locus(Wang et al., 2010), and 10 allele-specific markers were designed atthe Glu-B3 locus (Wang et al., 2009). These markers were validatedand successfully used to characterize LMW-GS composition inChinese and CIMMYT wheat accessions, and the results were inagreement with those from SDS-PAGE (Jin et al., 2011; Liu et al.,2010). The Glu-D3 locus displayed less variation and only sixactive LMW-GS genes were present in all bread wheat cultivars(Zhao et al., 2006, 2007a). These six active LMW-GS genes wereextremely conserved among accession in the Chinese core collec-tion (Zhang et al., 2013a). No gene-specific molecular markers havebeen developed to detect allelic variation at the Glu-D3 locus.

LMW-GS gene sequences are intronless, similar to other prola-min genes. More than 200 nucleotide sequences and cDNA clonesfrom LMW-GS genes have been reported in wheat and wild species(An et al., 2006; Ikeda et al., 2002; Long et al., 2005; Zhao et al.,2006, 2007a, b). In most of these cases, only a few LMW-GSgenes were isolated from a cultivar due to the complex composi-tion of genes. Collectively, more than 100 LMW-GS genes have beencharacterized and sequenced from bread wheat, including severalpartial and pseudo genes (Cloutier et al., 2001; Zhang et al., 2004).Sequence analysis suggested that the deduced proteins contain asignal peptide, a central repetitive region rich in proline and



glutamine, and N and C terminal non-repetitive domains, similar toother prolamins (Colot et al., 1989). The N-terminal amino acidsequence of LMW-s type subunits generally start with SHIPGL-, andLMW-m subunits are more variable starting with METSHIPGL-,METSRIPGL- or METSCIPGL- (Masci et al., 1993). LMW-i type sub-units actually lack an N-terminal region and start directly with therepetitive domain ISQQQQ- being the deduced N-terminalsequence. Besides those three types of subunits, a new LMW-l typesubunit was identified in Aegilops species with the first amino acidresidue being leucine (Wang et al., 2011).

2.2.4. Proteomic and molecular diagnosisSDS-PAGE is considered one of the simplest techniques to

identify LMW-GS; however, few laboratories in the world have theexpertise to conduct it for large numbers of samples in breedingprograms. More recently, reversed-phase ultra performance liquidchromatography (RP-UPLC) has been developed to separate LMW-GS in a more effective way (Yu et al., 2013). In this system, smalldiameter columns such as 1.7 mm columns, can be used and highcolumn performance (100,000e300,000) can be undertaken.Compared with the fastest high-performance liquid chromatog-raphy analysis currently available, RP-UPLC analysis is nine timesfaster in speed, two times higher in resolution, and three timeshigher in sensitivity, and thus provides a powerful tool for rapidseparation and characterization of LMW-GS.

SDS-PAGE, 2-DE, MALDI-TOF-MS and PCR based markers weredeveloped to detect the Glu-3 allelic variation. Liu et al. (2010)compared the four techniques to assess their suitability for use inbreeding programs. They indicated that PCR-based markers are thesimplest, most accurate, lowest cost technique and therefore rec-ommended it for the identification of Glu-A3 and Glu-B3 alleles inbreeding programs. MALDI-TOF-MS showed great potential inseparation of LMW-GS, but much more effort is needed before itcan be used routinely in breeding program. Considering the Glu-D3locus, it should be noted that its effect on quality variation amongwheat cultivars is very small compared to the Glu-A3 and Glu-B3loci (Zhang et al., 2012). A total of 17 allele-specific markers for Glu-A3 and Glu-B3 loci have been reported and used, and multiplex PCRprotocols have been developed to reduce costs of screening inpractical breeding programs (Wang et al., 2009, 2010). Applicationof functional markers for identification of LMW-GS in various typesof wheat germplasm has also been reported by others (Jin et al.,2011; Ram et al., 2011).

A combination of different techniques was required to identifycertain alleles of LMW-GS and these combinations are especiallyuseful when characterizing new alleles from genetic resource ma-terials. As more alleles are reported at Glu-A3 and Glu-B3 in breadwheat, more molecular markers will be needed to distinguish themin breeding germplasm. Liu et al. (2010) recommended a standardset of 30 cultivars to represent all known LMW-GS allelic variants infuture studies. Among them, Chinese Spring, Opata 85, Seri 82 andPavon 76were recommended as a core set for use in SDS-PAGE gels.Use of the standard cultivar set was recommended to promote andfacilitate information sharing on LMW-GS, ultimately enhancinguniversal quality improvement efforts in wheat.

In addition to HMW-GS and LMW-GS, gliadins account for 40e50% of total wheat seed storage proteins and have impacts both onprocessing and nutritional quality, but their effects on processingquality is less significant than the HMW- and LMW-GS. Gliadins canbe separated into a-/b-, g-, and u-gliadins in acid-PAGE based ondifferences in mobility, while a- and b-gliadins are structurally verysimilar (Kasarda et al., 1984). All u- and many g-gliadins areencoded by Gli-1 loci on the short arms of group 1 chromosomes,and all a-, many b-, and some g-gliadins are encoded by Gli-2 locion the short arms of homoeologous group 6 chromosomes. In the


wheat gene catalogue, 23, 24 and 15 alleles are listed for Gli-A1, Gli-B1 and Gli-D1 in bread wheat and durum wheat, respectively.Similarly, among Gli-2 loci, Gli-A2 encodes 36 alleles, Gli-B2 en-codes 47 alleles, and Gli-D1 encodes 31 alleles. The main factorspreventing the participation of gliadins in polymeric gluteninstructure is lack of free cysteines and the ability to form inter-molecular SeS linkages, hence they have small effect on process-ing quality. Qi et al. (2009) analyzed 170 g-gliadin genes from breadwheat and closely related species and found a wide range of aminoacid compositions in g-gliadins, and those g-gliadins from sub-groups SG-10 and SG-12 and g-gliadins with a short repetitivedomain were considered more nutritional. However, comparedwith glutenins, there has been little progress during the last 10years in understanding the structure and function of gliadins.Therefore, no further details will be presented here, although as-sociations of gliadins with health issues will be discussed in afollowing section of this paper.

3. Integrated genomics, functional analysis and evolution ofwheat storage proteins

3.1. Genomic resources and databases to understand prolamin-omics

Recent progress in understanding the genomic organization andin resolving the structural complexities of prolamins are largely dueto the establishment of genomics resources and database such asbacterial artificial chromosome (BAC) libraries, availability ofsaturated physical maps, and expressed sequence tags (ESTs)(Feuillet et al., 2012). The choice of database to be searched iscritical, particularly in organisms where a completely annotatedgenome sequence is not available. In addition, new sequences areconstantly being added to gene and protein databases. In the pastfew years, several hundred new glutenin and gliadin gene se-quences were added at the National Center for Biotechnology In-formation (NCBI) non-redundant database.

A large number of EST collections derived from developing seedcDNA libraries have allowed identification of new classes of pro-lamin genes and novel seed storage proteins (Anderson et al., 2001,2012). The use of large insert BAC libraries permits study of thecomplex structural organization of prolamin gene families (Guet al., 2004; Johal et al., 2004). Characterization of wheat BACclones using an a-gliadin gene probe revealed that positive BACclones carried one to five copies of the a-gliadin gene per BAC (Guet al., 2004). In contrast, when the BAC clones were used to char-acterize LMW-GS genes, no single BAC clone was found to carrymore than one copy of the LMW-glutenin gene. Several BACs wereneeded to provide all seven copies of an LMW-GS gene in Ae. tau-schii, the D genome donor of bread wheat (Johal et al., 2004). Thecultivar Glenlea BAC library (Nilmalgoda et al., 2003) is an impor-tant source for gene discovery, providing the template for genomeorganization studies of LMW-GS. Eighty two positive clones wereidentified to have LMW-GS genes, of which 12 were unique and 7were pseudogenes (Huang and Cloutier, 2008). The genomic or-ganization of several LMW-GS and gliadin genes was similarlystudied using the BAC library database of durum wheat cultivarLangdon (Gao et al., 2007). The EST databases from bread wheatcultivar Butte 6 also provided substantial information for under-standing the structural complexities of a-gliadins (Altenbach et al.,2010a) and g-gliadins (Altenbach et al., 2010b; Anderson et al.,2013). Now, the available whole genome shotgun draft sequencesof T. urartu (Ling et al., 2013) and Ae. tauschii (Jia et al., 2013) willaccelerate deeper and more systematic studies to meet futurechallenges in understanding wheat processing qualities. Databaseenhancement by inclusion of cultivar-specific prolamin gene



sequences maximizes the number and quality of peptide identifi-cations and increases sequence coverage of storage proteins byproteomic diagnosis. This approach makes it possible to distinguishclosely related proteins, to associate individual proteins with se-quences of specific genes, and to evaluate proteomic data in abiological context to better address their effect on flour quality.

3.2. Gene cloning and functional analysis

Integrated approaches in the modern genomics era have facili-tated cloning and functional analysis of new genes for HMW-GS(Butow et al., 2003; Li et al., 2008a; Zhang et al., 2008b), LMW-GS (Jiang et al., 2008; Li et al., 2008b, c), and gliadin (Wang et al.,2012b; Zhu et al., 2010) genes. The strategy for cloning and func-tional analysis of genes encoding storage protein is presented inFig. 1. The initial step is usually the identification of the new storageprotein that requires validation by multiple proteomic diagnosticplatforms. The aforementioned genomic databases provide tem-plates to design primers to isolate full-length open reading frames(ORF) of the encoding genes, which are then analyzed throughsequencing and functional investigations. Functional analysis of theencoding genes indicates that storage proteins evolve by unequalcrossing over and slip-mismatching (Zhang et al., 2008b). Trans-lation of nucleotide fragments into deduced peptides helps indemonstrating the structural basis of differences between subunits.Similarly, expression of fragments in E. coli is useful for predictionof possible mechanisms of duplication and deletion of large frag-ments (Zhang et al., 2008b).

3.3. Phylogeny and evolutionary studies in wheat storage proteins

It is thought that tandem gene duplication in globulins gave riseto the prolamins (Xu and Messing, 2009). The ancestral prolamingene in wheat progenitors gave rise to the HMW-GS, whichconstitute the group III prolamins and are unique to the subfamily

New allele/Putative new

allele

IVthe

Step 3: Functional analysis ofthe gene using bioinformatics,genomic resources & in vitro

expression analysis

I. Sequencecomparison withavailable sequences

II. Validation ofchromosomallocalization

III. Analysis ofdeduced amino

acids

IV. IdentificationSNPs and InDels

V. Phylogeny andevolutionary analysis

Step 4: Combination of all thisinformation to designate new

allele

VI. In vitro expressionanalysis

Functional analysis

Fig. 1. Strategy for cloning and functional ana


Pooideae. During evolution of the grasses, prolamin genes werecopied and inserted either in tandem or dispersed to differentchromosomal locations, which in turn gave rise to further ampli-fications. Donor copies were either maintained or lost by unequalcrossing over (Xu et al., 2012). Genome-wide dispersal gave rise tonew groups of prolamins, the largest of which is group II, includingthe LMW-GS, a-, g-, and u-gliadins inwheat and the b- and u-zeinsin maize. Group I represents the youngest prolamins that includethe a- and u-zeins in sorghum and maize that are unique to thePanicoideae (Zhang et al., 2013b).

Within the wheat seed prolamins, two evolutionary linesresulted in the major prolamin classes (Xu and Messing, 2009),with both lines originating separately within the super family ofrelated seed proteins. The LMW-GS and gliadins, which shareenough similarities to establish a common origin, emerged fromone line. Phylogenetic analysis showed that a-, g-, and b-gliadinsfrom barley, and LMW-GS genes from wheat were closely related,and they differentiated at a relatively late stage. In contrast, u-gli-adins and HMW-GS genes are separated by a much larger geneticdistance compared to other storage protein genes, indicating thatdifferentiation of these two kinds of genes occurred very early(approximately 74 million years ago, MYA) (Zhu et al., 2010).Among LMW-GS, LMW-m type genes could be considered to be themost primitive forms than other LMW-GS genes, and LMW-s andLMW-i type genes were variant forms among the LMW-GS genefamilies (D’Ovidio and Masci, 2004).

The second evolutionary line of wheat prolamins contains onlythe HMW-GS, and likely arose as a tandem duplication of a globulingene, with one of the resulting genes evolving into an HMW-GS(Kong et al., 2004). A subsequent tandem duplication of a chro-mosome fragment containing an ancestral HMW-glutenin andglobulin genes resulted in the x- and y-type HMW-GS. The twoHMW-glutenin genes remained as two conserved genes, whereasthe gliadins and LMW-glutenin genes radiated into large multi-gene families with highly variable copy numbers of member. All

Differential expression

RP-HPLC

SDS-PAGE

MALDI-TOF

2D-PAGE

Step 1: The new allele should showdifferential expression on one of thefollowing proteomic platforms

MolecularCharacterization

I. Primer designbased on availablesequence of related

gene family

II. Amplification ofcomplete ORF ofthe required gene

III. Cloning of thedesired product byligation to selected

vectors

. Sequencing ofcloned segment

Step 2: Molecularcharacterization of the gene bycloning followed by sequencingof

lysis of novel glutenin and gliadin genes.



HMW-GS genes encoded by Glu-1 loci from different Triticumspecies are homologous, and x-type alleles show greater variationthan the y-type alleles. Therefore, both x- and y-type subunit genescould have diverged from an ancestral sequence prior to separationof the wheat genomes, and the discrepancy is probably due torelatively rapid variation of the x-type genes. Network analysis ofGlu-D1-1 HMW-GS from Ae. tauschii demonstrated common an-cestors of the other Glu-D-1-1 alleles in an associated star-likephylogeny, suggesting that there were at least four independentorigins of bread wheat (Zhang et al., 2008b). In addition to unequalhomologous recombination, duplication and deletion of largefragments occurring in Glu-D-1-1 and Glu-3 alleles were attributedto illegitimate recombination (Zhang et al., 2008b; Li et al.,2008a,b,c; Wang et al., 2011). The time of the duplication event ofx- and y-type subunits could extend to 17 MYA, suggesting thatduring the origin of cultivated wheat the A and B genomes did notevolve simultaneously, and that they might have been introgressedinto hexaploid at different times and rates (Blatter et al., 2004). Byanalyzing haplotype variation at the Glu-D1 locus, Dong et al.(2013) established that the Glu-D1d allele was likely alreadydifferentiated in ancestral hexaploid wheat and Triticum speltaaround 10,000 years ago and was subsequently transmitted anddomesticated.

4. Quantifying prolamin allelic effects on processing qualities

The quality effects of HMW-GS and LMW-GS have been wellstudied to facilitate incorporation of desirable quality genes intobread wheat germplasm. Usually two types of populations havebeen used to study the effects of glutenin alleles on dough prop-erties and end-use qualities: viz., mapping populations developedfrom biparental crosses of parents having different glutenin alleles(recombinant inbred lines and doubled haploid lines), and non-structured populations, general collections of cultivars, biotypesfrom a cultivar, and breeding lines. Near-isogenic lines (NILs)differing by single glutenin alleles in a common genetic backgroundwere developed and they proved to be the best genetic stocks tostudy effects of single alleles on quality. In some recent studies, anarray of NILs derived in cultivar Aroona were used to determinequality effects (Jin et al., 2012; Zhang et al., 2012). Similarly, glu-tenin identification platforms that aremore sophisticated and high-throughput (AS-PCR markers and MALDI-TOF) greatly improvedsuch studied (Liu et al., 2010).

4.1. Individual allelic effects and interactions of glutenin onprocessing quality

The allelic effects of HMW-GS on dough properties and bread-making quality are well investigated because the alleles are rela-tively easy to identify. It is generally agreed that Glu-D1 has moreprofound effects on processing quality than Glu-A1 and Glu-B1(Zhang et al., 2009). Among HMW-GS, x-type subunits are muchmore important than y-type subunits and their contributions aremuch larger (Wieser and Kieffer, 2001). The presence and amountof subunit Dx5 is particularly significant due to its special disulfidestructure.

Previously, Payne (1987) proved that the subunits Ax1 or Ax2* atGlu-A1, Bx7 þ By8, Bx17 þ By18, and Bx13 þ By16 at Glu-B1, andDx5 þ Dy10 at Glu-D1 were desirable subunits for bread-makingquality. Several groups later confirmed this in different germ-plasm pools (Brönneke et al., 2000; He et al., 2005). Recently, ionbeam-induced mutants of bread wheat cultivar Xiaoyan 81 wereused to understand the effect of mutations at Glu-1 loci on glutenfunctionality (Yang et al., 2014). Based on the glutenin macropolymers (GMP) contents and elastic and viscous moduli, the Glu-1


loci can be ranked as Glu-D1 > Glu-B1 > Glu-A1. According to thecontributions of individual glutenin subunits to dough strength andpan breadmaking quality, different glutenin subunits at each of thethree loci were ranked as: 1 > 2* > N at Glu-A1,7 þ 8 � 13 þ 16 > 17 þ 18 ¼ 7 þ 9 at Glu-B1, and5 þ 10 > 2 þ 12 > 4 þ 12 at Glu-D1 (He et al., 2005; Wrigley et al.,2009). However, much more work is needed to understand theassociations between HMW-GS and qualities of Chinese/Asianproducts, such as steamed bread and noodles. Jin et al. (2012) foundthat variation in subunits at Glu-A1 had a significant effect on theshape of steamed bread, while Glu-B1 made significant contribu-tion to stress relaxation of steamed bread.

LMW-GS also contributes significantly to dough strength andextensibility. At Glu-A3, the ranking of alleles for dough strength isGlu-A3d > Glu-A3b > Glu-A3c > Glu-A3f > Glu-A3a > Glu-A3e,whereas ranking for dough extensibility is slightly different, viz.,Glu-A3c > Glu-A3b � Glu-A3f > Glu-A3e (Zhang et al., 2012). Thereare controversies regarding different kinds of populations or col-lections. For example, Cane et al. (2008) reported that Glu-A3e wascorrelated with inferior dough resistance and extensibility,whereas Zheng et al. (2009) found that Glu-A3e was a favorableallele for dough-mixing properties. The contribution of Glu-A3 wasthe highest among all LMW-GS loci, especially Glu-A3fwhich had astrong positive effect on end-use quality against the backgrounds ofall HMW-GS combinations. He et al. (2005) reported that Glu-A3dwas slightly better than others for dry white Chinese noodlequality, and Glu-B3j associated with the 1B/1R translocation, hadstrong negative effects on all quality traits. At Glu-B3, alleles wereranked Glu-B3b ¼ Glu-B3d ¼ Glu-B3g > Glu-B3h > Glu-B3a > Glu-B3c for dough strength, whereas ranking for dough extensibilitywas Glu-B3i > Glu-B3f ¼ Glu-B3g > Glu-B3h > Glu-B3a � Glu-B3b> Glu-B3d (Zhang et al., 2012). At Glu-D3, the effect of alleles onmost traits were not reported; alleles were ranked Glu-D3d ¼ f > Glu-D3e > Glu-D3a ¼ Glu-D3c ¼ Glu-D3bwith respect todough strength (Cornish, 2007; Zhang et al., 2012). It is generallyagreed that the effects of Glu-D3 alleles on processing qualities areless significant in comparison with those at Glu-A3 and Glu-B3.

4.2. Effects of gliadins on processing quality

The complex genetic structure, linkage with LMW-GS and in-heritance in blocks (not individual alleles) are the main bottlenecksto dissecting the functional properties of individual gliadin genes inwheat. Cysteine residues in gliadins facilitate interchain cross linkswith glutenins that influence flour characteristics. Moreover,certain proteins with amino acid sequences very similar to gliadins,contain an extra cysteine residue that enables them to be incor-porated into the glutenin polymer group (D’Ovidio and Masci,2004). These proteins are structurally similar to gliadins, butfunctionally similar to LMW-glutenin subunits. It has been hy-pothesized that these proteins serve as chain terminators of theglutenin polymer thereby limiting its size and influencing thequality of the flour. Gliadin proteins contribute little to resistanceand extension in dough and are mainly related to dough cohe-siveness (Uthayakumaran et al., 2000). The gliadin fractionreportedly contributes to viscosity properties. Pistón et al. (2011)analyzed transgenic lines with g-gliadins silenced by RNAi tech-nology. Mixograph testing revealed that silencing increased thecontents of other gluten proteins and quality parameters werethereby slightly affected. Similar findings were obtained when g-gliadins were silenced in three different cultivars, and it wasconcluded that reduction in g-gliadins had no direct effect onmixing and bread-making properties, and the compensatory effectson the synthesis of the other prolamins may result in strongerdough with improved over-mixing resistance.



4.3. Quality effects of “interaction and relative proportion” ofdifferent gluten fractions

Both HMW- and LMW-GS are important factors in determiningdough properties and end use quality; it is likely that HMW-GS aremore important for dough strength, and LMW-GS more importantfor dough extensibility. Actually, interactions between gluteninsand gliadins, and between HMW-GS and LMW-GS are consideredas important variables (Bekes et al., 2006). Therefore, it is not asimple matter of recommending a desirable combination of HMW-GS and LMW-GS for quality improvement although selection ofdesirable subunits/alleles will generally benefit breeding efforts forquality improvement. On a qualitative basis, ranking of gluteninfractions have been well described by Jin et al. (2012) and Zhanget al. (2012). Based on data collected from global publications,Bekes et al. (2006) reported that for dough strength, the interactionamong glutenin fractions can be ranked as HMW-HMW > HMW-LMW > LMWeLMW, while for gluten extensibility, HMW-LMW > LMW-LMW > HMW-HMW. Similarly, the contribution ofindividual loci for gluten strength was ranked as Glu-D1 > Glu-B1 > Glu-A1 > Glu-A3 ¼ Glu-B3 > Glu-D3, whereas for glutenextensibility, the ranking was Glu-A3 > Glu-B3 � Glu-D3 > Glu-A1 ¼ Glu-B1 ¼ Glu-D1. Overall, the contributions of protein allelescan be summarized in a pictorial model modified from Ikeda andTakata (2013) in Fig. 2 by plotting the gluten strength effect of in-dividual glutenin alleles in breeding implications.

In quantitative terms, the relative proportion of gluten fractions(glutenins and gliadins) and their sub-fractions (x- and y-typeHMW-GS) are important determinants of bread-making quality.There is still a debate as to the role of the various protein classes onbread-making parameters such as dough properties, loaf volume,and crumb characteristics. For example, gliadin proteins were re-ported to be closely related to loaf volume in some studies (Khatkaret al., 2002), but in other studies gliadin proteins had no significanteffects on loaf volume, and glutenin proteins were the majorcomponents responsible for loaf volume (Uthayakumaran et al.,2002). Zhang et al. (2007b) also found that gliadin/glutenin ratiosshowed significant and negative associations with dough proper-ties and Chinese steamed bread quality. Alteration of this ratio hada complex effect on the dough extensibility, indicating the differentrheological properties of glutenins and gliadins (Uthayakumaranet al., 2000).

HMW-GS/LMW-GS weight ratios vary between 0.18 and 0.74,suggesting the amount of LMW-GS (55e85%) may vary from onlyslightly higher to an almost six fold that of HMW-GS (15e45%) (seereview from Veraverbeke and Delcour, 2002). HMW-GS/LMW-GS

Fig. 2. Breeding implications of glutenin alleles for specific wheat-based products; Y-AXIS represents Glu-1 alleles and X-AXIS represents Glu-3 allele effects on doughstrength at different grain protein levels (modified from Ikeda and Takata 2013).


ratios determined dough extensibility (Zhang et al., 2007a) andwere correlated with farinograph development time and stability(Zhang et al., 2007b). Synthetic dough comprising homopolymersof HMW-GSwere found to be stronger than that those composed ofLMW-GS homopolymers (Beasley et al., 2002). The mixing time,peak resistance, maximum resistance to extension, and loaf heightincreasedwith increases in HMW/LMWratio, whereas resistance tobreakdown and extensibility decreased with the incorporation ofglutenin subunits (Uthayakumaran et al., 2000). The contribution ofdifferent glutenin subunits to the molecular properties of dough isdirectly related to the polymeric structure of the glutenin protein.Both variations in structure and in relative amounts of HMW-GScorrelated strongly with dough strength, whereas alteration inLMW-GS and gliadin composition affected dough extensibility.

5. Health related aspects of storage proteins

Wheat protein is one of the most extensively utilized proteins inthe human diet, and it is also one of the most common causes offood-related allergens and intolerances. The terms wheat-relatedintolerance (sensitivity) and wheat allergy are often used inter-changeably. Wheat allergy refers to the negative reaction wheresymptoms appear rapidly following exposure to macro-moleculessuch as proteins. Several recent reviews address different aspectsof the role of storage proteins in allergies and their clinical andpharmaceutical applications. Tatham and Shewry (2008) reviewedthe cereal proteins responsible for dietary and respiratory allergiesin relation to their structural and biological properties. Sapone et al.(2012) summarized the current knowledge about themain forms ofgluten reactions which may be allergic and autoimmune (coeliacdisease, dermatitis herpetiformis, and gluten ataxia). They alsooutlined the pathological, clinical and epidemiological differencesand proposed new nomenclature and classifications for glutenrelated disorders. Mamone et al. (2011) presented an in-depth re-view on the proteomics of allergens in wheat storage proteins andtheir derived products. Juhász et al. (2012a) proposed a method toidentify the “epitope toxicity” by analyzing the number andcomposition of epitopes on a single protein. The use of knowledgeabout the composition and level of epitopes present in a cultivar isrestricted due to the absence of an efficient prediction methodol-ogy. In this regard, the “epitope toxicity” value obtained by utilizingwheat proteome data is a significant measure and can be applied towheat improvement and food industry for development of gluten-free or less toxic products. Moreover, the published genome ofBrachypodium distachyon, a diploid wild grass with low prolamincontent, can be effectively utilized to study allergen potential ofprolamin and non-prolamin proteins (Juhász et al., 2012b). Giventhe recent publication of these reviews, we will only provide anoverview of toxic prolamin-related epitopes in different wheatgenetic resources. A summary of prolamin-related toxic epitopes inwheat is given in Table 1. Allelic variation for toxic prolamin epi-topes is also reviewed in order to develop strategies to addressthese disorders in wheat.

5.1. Coeliac disease

Coeliac disease (CD) is the most important disease resultingfrom gluten intolerance. It is an intestinal T cell-mediated diseasecaused by an uncontrolled immune response to gluten, whichcontains several peptides that constitute the main toxic componentin CD (van deWal et al., 1998). It causes a medium to severe chronicinflammatory condition that is characterized by injury to the liningof the small-intestine on exposure to the gluten. CD affects 0.5e2.0% of the human population (Rewers, 2005). In CD patients, CD4þT cells are present in the lamina propria that secrete interferon-


Table 1Allergen domains in wheat seed storage proteins.

Protein Epitopesequence

Toxic Genomeassigned

Allergy Reference

HMW-GSDQ8-glut-H1 QGYYPTSPQ CD van de Wal et al., 1998

CD Kooy-Winkelaar et al., 2011Peptide-1 QQPGQ A, B, D WDEIA Matsuo et al., 2005Pedtide-2 QQPGQGQQ A, B, D WDEIA Matsuo et al., 2005Peptide-3 QQSGQGQ A, B, D WDEIA Matsuo et al., 2005

LMW-GSGlutenin-17 PFSEQEQPV CD Stepniak et al., 2005; Vader et al., 2003Glutenin-156 FSQQQESPF CD Stepniak et al., 2005; Vader et al., 2003

a-GliadinsGlia-a QGSFQPSQQ Yes A, B, D, S, U, M, C, N CD van Herpen et al., 2006Glia-a2 PQPQLPYPQ Yes M, U, C, N CD Li et al., 2012

D CD van Herpen et al., 2006Glia-a9 PFPQPQLPY Yes A, B, D CD Xie et al., 2010Glia-a20 FRPQQPYPQ Yes A CD Vaccino et al., 2009Glia-g1 DQ2-g-I PQQSFPEQQ CD Sjöström et al., 1998Glia-g2 DQ2-g-II, g30 I QPEQPAQL CD Qiao et al., 2005Glia-g3 DQ2-g-III QQPEQPYPQ CD Arentz-Hansen et al., 2002Glia-g4a DQ2-g-IV SQPEQEFPQ CD Arentz-Hansen et al., 2002Glia-g4b DQ2-g-VIIc PQPEQEFPQ CD Qiao et al., 2005Glia-g4c DQ2-g-VIIa QQPEQPFPQ CD Arentz-Hansen et al., 2002Glia-g4d DQ2-g-VIIb PQPEQPFCQ CD Qiao, unpublishedGlia-g5 DQ2-g-VI QQPFPEQPQ CD Arentz-Hansen et al., 2002

u5-GliadinQQIPQQQ WDEIA Matsuo et al., 2004QQFPQQQ WDEIA Matsuo et al. 2004QQSPEQQ WDEIA Matsuo et al., 2004QQSPQQQ WDEIA Matsuo et al. 2004QQLPQQQ WDEIA Matsuo et al., 2004QQYPQQQ WDEIA Matsuo et al. 2004PYPP WDEIA Matsuo et al., 2004QQFHQQQ WDEIA Matsuo et al., 2005QSPEQQQ WDEIA Matsuo et al., 2005YQQYPQQ WDEIA Matsuo et al., 2005QQPPQQ WDEIA Matsuo et al., 2005QQQLPQQQ WDEIA Battais et al., 2005QQQFPQQQ WDEIA Battais et al., 2005


gamma upon recognition of gluten-derived peptides bound to HLA-DQ2 or HLA-DQ8 molecules present on antigen presenting cells.Strikingly, most of the gluten peptides implicated in CD requiremodification by the enzyme transglutaminase before they can bindto the disease-predisposing HLA-DQ molecules and trigger T cellresponses (Koning, 2003). In addition to the adaptive CD4þ T cellresponse to gluten, CD is characterized by upregulation of IL-15, anintraepithelial T cell infiltrate expressing the NKG2D receptor, andthe overexpression of a ligand for NKG2D (MICA) (Meresse et al.,2004).

A variety of studies have been conducted to identify the glutenpeptides responsible for CD. These peptides have been identified ina-, u-, and g-gliadins (van de Wal et al., 1998; Arentz-Hansen et al.,2002; van Herpen et al., 2006) as well as in HMW and LMW glu-tenins (Kooy-Winkelaar et al., 2011; Bodd et al., 2012). The a-glia-dins are considered to be the most relevant components of glutenscausing CD (Vader et al., 2003; van Herpen et al., 2006; Vaccinoet al., 2009). Alpha-gliadin genes on chromosome 6A in breadwheat almost invariably contain epitopes glia-a9 and glia-a20, butnot the intact epitopes glia-a or glia-a2. Genes on chromosome 6Bdo not contain any of the four T cell epitopes, and genes on chro-mosome 6D contain all of these T cell epitopes in variable combi-nations (van Herpen et al., 2006). Therefore, a-gliadins produced bychromosomes 6A and 6D could be themajor targets for reducing CDthrough genetic improvement of wheat.

The identification of gluten peptides involved in CD is not yetcomplete. A large variation was observed for the amounts of CD4 T


cell stimulatory peptides present in a- and g-gliadins and gluteninsamong diploid, tetraploid, and hexaploid wheat accessions(Molberg et al., 2005; Spaenij-Dekking et al., 2005; Mitea et al.,2010). If such differences are genetically determined, this wouldprovide strategies for selection and breeding of wheat cultivarssuitable for consumption by CD patients. van Herpen et al. (2006)analyzed several wheat species with A-, B- and D-genomes andshowed that epitopes are distributed non-randomly. Completesequence analysis of toxic epitopes in T. monococcum led to theconclusion that it is very difficult to breed wheats lacking toxicepitopes in their storage proteins (Vaccino et al., 2009). In fact, itseems hardly feasible to create new genotypes lacking all 17harmful peptides, present in proteins produced by different loci.Likewise, silencing of the genes giving rise to immunostimulatorysequences via targeted mutagenesis (Vader et al., 2003) also ap-pears somewhat unrealistic.

The number of T cell-stimulatory epitopes (glia- a2/a9) found inAe. tauschii were more comparable to A and B genome species (Xieet al., 2010). A number of a-gliadin genes from Ss (Ae. speltoides) andB genome species did not contain any of the 4T cell stimulatoryepitopes (Spaenij-Dekking et al., 2005). Additionally, large varia-tions in glutamine residues in the two polyglutamine domains arealso present in a-gliadin genes from Ae. tauschii, suggesting a usefulresource for reducing gliadin toxicity levels in wheat breedingprograms. Ongoing work onwheat genetic resources and genomicsaims to identify specific variations that might be helpful in devel-oping functional markers for incorporation of less toxic epitopes



(Xie et al., 2010). Li et al. (2012, 2013) identified specific SNPs andInDels in the four T-cell stimulatory toxic epitopes and the twopoly-glutamine domains which could be used as effective molec-ular markers for screening a-gliadin genes with no toxic epitopes.These variations could be of importance for consideration in thetransfer of potentially valuable genes from Aegilops species to breadwheat.

5.2. Baker’s asthma

Baker’s asthma is an occupational hypersensitivity disease thatresults from the inhalation of flour and dust during grain process-ing. It has been recognized since Roman times when slaves whohandled flour and dough were required to wear masks, and wasdescribed by Ramazzini in about 1700. Bakers’ asthma is nowrecognized as one of the most common types of occupationalasthma. For example, it is recognized as the second most commontype by the UK Health and Safety Executive (www.hse.gov.uk/asthma/bakers.htm). Earlier studies indicated that multiple aller-gens were present, with the water-soluble albumins being partic-ularly reactive with the IgE fractions from patients’ sera and it isnowwell established that grain a-amylase inhibitors (CM proteins)are the major proteins responsible for baker’s asthma as reviewedby Tatham and Shewry (2008). A few reports suggest that wheatprolamin is partially responsible for this disease (Mittag et al.,2004). Sandiford et al. (1997) used immunoblotting to identifyIgE against a range of wheat gluten proteins. All of the patients’ seratested, showed IgE binding to a-gliadins, 21 of 24 to fast u-gliadin,18 of 24 to b-gliadin, 12 of 24 to g-gliadin and 15 of 24 to slow u-gliadin. Competitive binding studies with salt-soluble proteins alsoshowed reduced binding to purified a- and g-gliadins (but not to b-or u-gliadins), indicating the presence of common epitopes.Western blotting of fractions from total gliadins, glutenins and al-bumins-1-globulins showed reactions with IgE in 15 patients withbaker’s asthma. Nine sera reacted with albumins-1-globulins, twowith gliadins and seven with glutenins (Mittag et al., 2004).Therefore, more focused studies will be needed to dissect the role ofwheat glutenins and gliadins from the other proteins to betterdevise wheat improvement strategies, following the same route asfor CD.

5.3. Wheat-dependent exercise-induced anaphylaxis

Wheat-dependent exercise-induced anaphylaxis (WDEIA) is aform of allergic reaction jointly induced by the ingestion of acausative food and subsequent physical exercise. The first case ofexercise-induced anaphylaxis (EIA) was reported by Sheffer andAusten (1980). Wheat is the most widely reported food to beassociated with EIA. Patients with WDEIA display a range of clinicalsymptoms from generalized urticaria to severe allergic reactionsincluding anaphylaxis.

a-gliadin protein detected by immunoblotting had the majorallergen domain (Palosuo et al., 1999), but Morita et al. (2003)subsequently established that u5-gliadins (Tri a 19) were the ma-jor allergen in WDEIA. Later, synthetic peptides were used toidentify seven important epitopes (Table 1) within the primarysequence of u5-gliadin (Matsuo et al., 2004, 2005). Four (QQIPQQQ,QQFPQQQ, QQSPEQQ and QQSPQQQ) of seven epitopes weredominant. Due to the non-availability of full-length sequences, theysearched a wheat EST library for u5-gliadin-like sequences andidentified four sequences with GenBank accession numbersBE590637, BQ608902, BQ895830 and BQ245835. Later, Matsuoet al. (2005) identified four further IgE-binding epitope se-quences, QQFHQQQ, QSPEQQQ, YQQYPQQ and QQPPQQ, in threepatients with WDEIA using a recombinant u-gliadin. Mutational


analysis of the QQIPQQQ and QQFPQQQ peptides indicated that theamino acids at positions Gln 1, Pro 4, Gln 5, Gln 6 and Gln 7 werecritical for IgE binding. A similar finding was reported by Battaiset al. (2005) on two immune-dominant epitopes (QQQLPQQQ andQQQFPQQQ) on u5-gliadin.

Another important finding was identification of allergen do-mains in HMW-GS that also reacted with IgE from patients withWDEIA (Morita et al., 2003). This was confirmed by Matsuo et al.(2005) through establishment of the IgE-binding epitopes ofwheat HMW-GS using synthetic peptides. They also identifiedthree epitopes (QQPGQ, QQPGQGQQ and QQSGQGQ) from the re-petitive domain. Genome-level studies on the variability of theseallergens in wheat and related species are still needed in order tobridge a significant gap in our current knowledge-base.

6. Future challenges

Improvement of processing qualities for various products andreduction of the adverse health effect of storage proteins arebecoming more important. We need to develop more sophisticatedtools and to upgrade the resolution of current technologies in orderto move forward. Although progress has been made in this context,HMW-GS at Glu-1 and LMW-GS at Glu-3 explain only about 60% ofthe variability in dough properties and end-use qualities. Therefore,the identification of other major QTLs or loci is needed for a betterunderstanding of wheat processing qualities. For example, thepresence of a further class of storage proteins, named Avenin-likeproteins identified by Kan et al. (2006), could also contribute tothe functional properties of wheat flour. The international wheatgenome sequencing consortium (IWGSC) efforts and genome wideassociation studies (GWAS) with modern marker technologies suchas genotyping by sequencing and SNPs will be crucially important.Completion of the wheat DNA sequencing project will greatlyenhance our capacities in gene discovery, gene cloning and markerdevelopment. Similarly, research efforts on classes of storage pro-teins such as lunasin (Mitchell et al., 2013) and triticin (Shailajaet al., 2002) need to be extended to validate their effects and todetermine how they might be manipulated for grain qualityimprovement. For processing quality, quality consistency over lo-cations and seasons is equally important to quality performance perse. It is expected that proteomics will play a leading role in un-derstanding quality consistency and variation in differentenvironments.

Apart from recent achievements on certain aspects related towheat storage proteins, there are many challenging tasks that needto be covered for a better understanding and achievement ofapplied outputs. The first task is to resolve remaining problems onthe identification of ambiguous glutenin alleles. Different diag-nostic techniques, difficulties in sharing standard germplasm, dif-ferences in growing conditions to evaluate quality contributions byspecific alleles and linkage/epistatic effects are the main problemsin this regard. A proposal is underway to form an InternationalGluten Working Group to resolve such problems. Liu et al. (2010)provide an excellent example of what can be achieved throughcollaboration by providing a common platform for resolving LMW-GS related issues. Such types of integrated activity with more co-ordination will be helpful in addressing other difficulties. Geneticresources also need to be improved to facilitate the dissection ofquality effects of individual glutenin and gliadin alleles. TheAroona-derived NILs and durum cultivar Langdon derived D-genome synthetic hexaploids (Xu et al., 2010) have proven to be theideal genetic resources for studies targeting the properties ofparticular protein alleles.

Studies on T cell stimulatory epitopes in all types of glutenproteins are relatively new, and given that the role of the innate


http://www.hse.gov.uk/asthma/bakers.htm

http://www.hse.gov.uk/asthma/bakers.htm


immune system is only beginning to be understood, it may bepremature to start breeding non-toxic wheat cultivars or cultivarsexpressing lower levels of toxic polypeptides. However, there is aneed to develop functional markers for the most toxic epitopes, asthese can be exploited in selection for less toxic epitopes in wheatbreeding programs.

Acknowledgments

The authors are grateful to Prof. R. A. McIntosh at Plant BreedingInstitute, University of Sydney, and Dr. Xiaofei Zhang at Universityof Minnesota, for critical reviews of this manuscript. This study wassupported by International Collaboration Projects from the Minis-try of Science and Technology (2013DFG30530) and China Agri-culture Research System (CARS-3-1-3). We also acknowledge theHigher Education Commission (HEC) in Pakistan for providing anoverseas fellowship to the first author under the InternationalResearch Support Initiative Program (IRSIP).

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