Biotechnology Advances 29 (2011) 199–209

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Research review paper

Genomic resources in horticultural crops: Status, utility and challenges

Humira Sonah, Rupesh K. Deshmukh, Vinay P. Singh, Deepak K. Gupta, Nagendra K. Singh, Tilak R. Sharma ⁎National Research Centre on Plant Biotechnology, IARI, Pusa Campus, New Delhi-110012, India

⁎ Corresponding author. Tel.: +91 112584 1787; fax:E-mail address: trsharma@nrcpb.org (T.R. Sharma).

0734-9750/$ – see front matter © 2010 Elsevier Inc. Aldoi:10.1016/j.biotechadv.2010.11.002

a b s t r a c t

a r t i c l e i n f o

Article history:Received 13 February 2010Received in revised form 4 September 2010Accepted 26 September 2010Available online 19 November 2010

Keywords:ESTGenomic resourcesHorticultural cropsPositional cloningQTLSequencing status

A significant review of status and availability of genomic resources in horticultural crops can be utilized for theefficient exploitation of the current research in developing improved varieties and also defining future goals.In this review, we describe the current genomic resources available in major horticultural crops and utility ofthe genomic and genic sequence information for isolating and characterizing novel useful genes and designingnew DNAmarkers. We have found that these genomic resources have been utilized for both basic and appliedresearch; however the progress is relatively slow. Recent advances in automation and high throughputtechniques used in decoding plant genomes play an important role to speed up the genomic research. Withthe establishment of genome and transcriptome sequencing projects for several horticultural crops, hugewealth of sequence information have been generated. These sequence information have been usedextensively for analyzing and understanding genome structures and complexities, comparative andfunctional genomics and to mine useful genes and molecular markers. However, certain limitations presenta number of challenges for the generation and utilization of genomic resources in many important crops.

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Contents

1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1992. Genome sequencing projects in horticultural crops . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2003. Large-insert genomic libraries used in genome sequencing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2014. EST resources in horticultural crops . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2025. Molecular markers in horticultural crops . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2026. Candidate gene identification and positional cloning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2047. The DNA microarray studies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2058. Comparative genomics in horticultural crops . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2069. Harnessing genomic information of model species . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 206

10. Challenges . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 207Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 207Appendix A. Supplementary data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 207References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 207

1. Introduction

Horticulture is one of the important sectors of agriculture whichconsists of fruits, flowers, vegetables, spices, plantation crops,medicinal and aromatic plants. The importance of horticulturalcrops is widely acknowledged in many aspects of innovation,

production, quality maintenance, for uplifting economic condition offarmers, entrepreneurs and in providing nutritional security to thepeople. With the growing population, demand for horticulturalproducts is gradually increasing. Latest genomic technologies can beeffectively used in horticultural crop improvement programmes.Developing genomic resources like whole genome sequences,expressed sequence tags (ESTs), genomic survey sequences (GSS)and high throughput genome sequences (HTGs) are required tomaintain the growth of these crops and associated value added

200 H. Sonah et al. / Biotechnology Advances 29 (2011) 199–209

opportunities. Genomic resources for model horticultural crops areincreasing with great pace, however many of them are still not beingexploited. Many genomic resources like whole genome sequence,large number of ESTs, large-insert genomic libraries, plenty ofmolecular markers and high-density genetic maps are available.These resources have been used for sequencing and annotation,mapping and cloning of genes or quantitative trait loci (QTL), andmarker assisted selection (MAS) in important horticultural crops.However, as compared to cereals and other crops, the progress ofgenomic studies in horticultural crops is relatively slow. Availability ofnext generation sequencing (NGS) technologies like FLX-454, Illu-mina, SOLiD and Helicose have brought hopes to generate genomicresources for many more horticultural crops in few years time.Therefore, the horticulture breeders should equip themselves to makeuse of this extensive genome information in their varietal develop-ment programmes. The objectives of this review were to take stock ofavailability of genomic resources in horticultural crops, compile thisinformation at one place, make sequence information useful forbreeders and to identify potential future challenges which one canface while making proper use of genomic resources.

2. Genome sequencing projects in horticultural crops

Many projects were started for the genome sequencing ofhorticultural crops and few of them are and many more will beavailable in public domain in near future (Table 1). The mostnoticeable projects are Tomato genome sequencing project (www.sgn.cornell.edu/about/tomato), Potato genome sequencing consor-tium, (www.potatogenome.net), Papaya genome sequencing project(www.asgpb.mhpcc.hawaii.edu/papaya/), Grape genome sequencingproject (www.vitaceae.org), Floral genome sequencing project(www.fgp.bio.psu.edu/) and many more. Along with conventionalmethods, these projects are well equipped with advanced sequencingtools, to ensure maximum coverage with high quality sequence andcost efficient methodology. The conventional DNA sequencingmethod referred as di-deoxynucleotide sequencing, or more com-

Table 1Status of sequencing projects in horticultural crops up to August 2010.

Crop Size(Mb)

Chr. Status Centre

Allium cepa 15,000 8 Initiated USDA-ARS and UnAquilegia coerulea 350 – In progress Joint Genome InstiAquilegia formosa 350 7 In progress DOE Joint GenomeBeta vulgaris 760 9 Initiated Hokkaido UniversiBrassica juncea – 18 Initiated Multinational BrasBrassica oleracea 600 9 In progress TIGRBrassica rapa 500 10 In progress Brassica IGF ProjecCapsicum annuum 3000 12 Initiated Korea Research InsCarica papaya 370 9 Draft assembly The Papaya GenomCarya illinoinensis – 16 Initiated University of GeorgCitrus sinensis 380 9 In progress U.S. Citrus GenomiCoffea arabica – 11 Initiated University of CentrCorylus avellana – 11 Initiated Department of HorCucumis sativus 370 7 Draft assembly The Cucumber GenDaucus carota 470 9 Initiated University of CentrKadua centranthoides – – Initiated Lita Annenberg HaLactuca sativa – 9 Initiated Research InstituteMalus×domestica 750 17 In progress IASMA research ceMusa acuminata 600 11 In progress Global Musa GenomPrunus armeniaca – 8 Initiated Instituto ValencianPrunus dulcis – 8 Initiated Beijing Agro-biotecPrunus persica 290 8 Initiated Clemson UniversityRosa multiflora – 7 Initiated Rosaceae InternatiSolanum bulbocastanum – 12 In progress University of CentrSolanum demissum – 12 In progress TIGRSolanum lycopersicum 950 12 Complete International TomaSolanum melongena 1100 12 Initiated Cornell UniversitySolanum tuberosum 840 12 Draft assembly Potato Genome SeqVitis vinifera 500 19 Draft assembly International Grap

monly, Sanger's method of DNA sequencing provides large enoughread length with quality sequence but it is time consuming and labourintensive. With the availability of next generation sequencing (NGS)technologies for DNA sequencing like FLX454 (Roche), Solexa(Illumina) and SOLiD (Applied Biosystems), there has been tremen-dous increase in the sequence database of several organisms. Forinstance, a single run of the 454 FLX machine on an average yieldsaround 400,000 reads of 400 bp each, at a reasonable price in a fewdays time. Due to the large number of reads generated by the 454 DNAsequencing technology, it is possible to reveal the expression of manyrare transcripts that would not be covered with Sanger's technology(Cheung et al., 2006). The generated sequence data are being analyzedfor characterization of genes and validation of their functions throughcomparative and functional genomics approaches. For the applicationof genomics in crop improvement several high-throughput methods,genomic platforms and strategies are currently available to the plantcommunity. Genomic research has great potential to revolutionize themolecular biology research in horticultural crops in many ways.

The whole genome sequencing of model plant Arabidopsis thalianalaid the foundation of plant genomics research (AGI, 2000). Since thenrapid progress has been made in decoding complete genome sequenceof plants with significant developments like generation of high-qualityrice genome sequence (IRGSP, 2005), draft genome sequence of poplar(www.eurekalert.org), sorghum (www.phytozome.net/sorghum),grapevine (Jaillon et al., 2007), transgenic papaya (Ming et al., 2008),and Cucumber (Huang et al., 2009). The draft sequence of several otherplant species like cassava, potato, tomato, shepherd's purse and peachare currently available in database. Multinational genome projects onBrassica (www.brassicagenome.org) and Solanaceous genomes (www.solgenomics.net) are in progress. Such huge sequence data of severalspecies facilitate comparative genomics studies in plants. However,trained human resources in computational biology and efficientbioinformatics tools are required to make use of this information.

Among the solanaceous crops, tomato and potato have been usedas scientific model for genomic studies. International SolanaceaeGenome Project (ISGP) was formulated in 2003 to sequence tomato as

iversity of Wisconsintute(JGI)Institutety, Japan, Max Planck Institute, Michigan State University,sica Genome Project

t, The Multinational Brassica rapa Sequencing Projecttitute of Bioscience and Biotechnology, Seoul National University, Cornell Universitye Sequencing Consortiumia, USAcs Initiative, University of Californiaal Floridaticultureome Initiativeal Florida, Vegetable Crops Research Unitzen Genome Sequencing Centerof Innovative Technology for the Earth, Japan, University of California, Davis (UCD)nter, The Horticulture and Food Research Institute of New Zealandics Consortium (GMGC)

ao de Investigaciones Agrarias, INRA Avignonhnology Research Center at CUGI, CUGI

onal Genomics Initiative (RosIGI)al Florida, Molecular Biology and Microbiology, USA, Orlando, TIGR

to Genome Sequencing Project; solgenomics.net

uencing Consortium, TIGR, The Canadian Potato Genome Projecte Genome Program, IASMA Research Center

201H. Sonah et al. / Biotechnology Advances 29 (2011) 199–209

the first diploid crop among the asteroids (Mueller et al., 2009). TheISGP has distributed twelve tomato chromosomes among teninternational teams for sequencing. The tomato genome is composedof approximately 950 Mb of DNA, more than 75% of which isheterochromatin and largely devoid of genes. Hence, the internationalconsortium has targeted euchromatic region of tomato genome fordecoding. The draft sequence of tomato genome has been declared inAugust 2010 and is available in public domain (www.sgn.cornell.edu).Moreover the draft sequence of entire potato genome has also beendeclared by Potato Genome Sequencing Consortium (PGSC; www.potatogenome.net). These will provide invaluable resources forcomparative genomic studies among other Solanaceae crops andwill pave the way for functional analysis of the large numbers ofSolanaceae genes. Since tomato and potato are easily transformable,and highly amenable to the investigations of gene function bybiotechnological approaches (An et al., 1986). In addition sequenceresources like cDNA, genomic DNA, conserved orthologous genes,and molecular markers have been mapped to allow comparativegenome analysis between eggplant, tomato, potato, pepper and otherSolanaceae crops (Pratt et al., 2008).

The Multinational Brassica Genome Project (MBGP) has beensuccessful in providing genomic resources like genetic maps andmapping populations, simple sequence repeat (SSR) markers, ESTs,BAC libraries and physical maps (www.brassica.info/info/about-mbgp.php) toplant community. First phaseofBrassica rapa sequencingprojecthas been completed and second phase is in progress. This consortiumwould complete the sequencing of Chinese cabbage (B. rapa ssp.pekinenesis) even though the genome is 7 to 10 times larger thanArabidopsis. Physical maps of the Brassica A and C genomes are beingconstructed in UK (www.brassica.bbsrc.ac.UK/IGF/) and, Korea (www.brassicagenome.org). Analysis of Brassica oleracea shotgun sequenceswill be completed very soon. These international efforts will makeefficient use of genomic resources in comparative and functionalgenome analysis across Brassica species and related genera.

Among fruit crops, first draft with 8× high quality grapevine sequencewas releasedby the InternationalGrapeGenomeProject (IGGP)which is aFrench–Italian consortium (Jaillon et al., 2007). The goal of IGGP was tounderstand the genetic and molecular basis of all biological processesinvolved in grapevine growth anddevelopment. The draft sequence of thegrapevine genome is the fourth one among the flowering plants, secondamong woody species and first for a fruit crop being sequenced. Thesecond fruit crop transgenic ‘SunUp’papayawas sequencedby theHawaiiPapaya Genome Project (HPGP; Ming et al., 2008). The papaya marks thefirst transgenic fruit crop and fifth plant genome to be sequencedcompletely. Thepapayagenome(372 Mbp), is three timesbigger than thesize of Arabidopsis genome, but contains 20% less genes. It containsapproximately 13,311geneswhichare far less thanotherfloweringplantssequenced so far (www.asgpb.mhpcc.hawaii.edu/papaya/).

Cucumis sativus (Cucumber) a member of the Cucurbitaceaewhichincludes important crops such as melon, watermelon, squash andpumpkin is used as a model system for sex determination studies andplant vascular biology. The Gy14 gynoecious inbred line of cucumberwas sequenced de novo using both random shotgun and paired-endshotgun reads. The 454-FLX technology has been used to sequenceCucumis genome and the draft sequence has been released in thepublic domain (www.jgi.doe.gov). The accuracy of the assembly wascompared with the genetic map of cucumber and comparativeanalysis and also with other related plant genomes. These resultsshowed the use of next generation long-read pyrosequencingmethods for the decoding of complex eukaryotic genomes. Thecucumber genome provides a valuable resource for developing elitecultivars and for studying the evolution and function of the plantvascular system.

The Floral Genome Project (FGP), another important genomesequencing consortium has been in operation which will analyzethe source, conservation, and diversification of the genetic architec-

ture of the flowers (www.fgp.bio.psu.edu/). It has also developedseveral computational tools for evolutionary and functional genomicstudies. The FGP has been exploring the evolution of floraldevelopment and to characterize the ancestral floral transcriptomeby using different genomic approaches. Presently, this consortium isfocusing on basal angiosperms like Amborella, Nuphar (spadderdock;Nymphaeaceae), Liriodendron (tulip poplar; Magnoliaceae), and basaleudicot (Eschscholzia). Dozens of genes with specific roles in flowerdevelopment have been identified in Arabidopsis and other modelorganisms by using various developmental genetics and genomicstudies (Benlloch et al., 2007). The flowering plant species Mimulusguttatus (monkey flowers) has become a leading model system forstudying ecological and evolutionary genetics and has been sequencedby Joint Genome Institute (www.jgi.doe.gov). Like all plant geneticmodel systems,Mimulus species have a small genome (about 430 Mb),short generation time (6 to 12 weeks), high productiveness (100 to2000 seeds per pollination), self-compatibility, and easy propagation.Many plant species which have been sequenced till date were selectedon the basis of model features of the genomes. Now this trend is shiftedtoward the sequencing of plant species having economical importanceand mostly from developed countries. With the availability of costeffective NGS technologies, now the target should be beyond thescientific curiosity and the species should be selected on the basis oftheir utility and economical importance. The best example of such shiftis sequencing of cassava genome, which is one of the three major tubercrops, theworld's sixth largest food crop used bymore than 600 millionpeople in the world. The genome sequencing of cassava has beencompleted by using multi sequencing platforms like Solexa, 454, andBAC Blending Strategy (www.jgi.doe.gov). Completion of the cassavawhole-genome sequencing project has great significance in global foodsecurity and bio-energy development. Application of genomic scienceresources to such orphan crops may prove to have a large impact onglobal human welfare.

3. Large-insert genomic libraries used in genome sequencing

High throughput genome sequencing of eukaryotic organismstraditionally used large inserts genomic libraries prepared in bacterialartificial chromosome (BAC), yeast artificial chromosome (YAC) or PIartificial chromosome (PAC) vectors. Of these, BAC vectors are usuallypreferred because of limitations of other vector systems. BAC-by-BACsequencing provides systemic and efficient strategy for completegenome sequencing than the shotgun sequencing approach. The BAClibraries have become the main vehicle of genomic resource fordeveloping physical maps and map-based gene cloning (Gaafar et al.,2005). The study of comparative genome organization and evolutionacross plant species can also be performed by using BAC libraries.Another important significance of these BAC libraries is to use BACclones for chromosome identification using fluorescence in situhybridization (FISH) and using them as chromosome-specific cyto-genetic DNA markers (Dong et al., 2000). However, development ofphysical maps using BAC libraries representing entire genome is avery specialized job for which availability of good genetic linkage mapis essential.

Once the genome is cloned in BAC or YAC libraries next step is toarrange them in overlapping order. This is accomplished by finger-printing ends of each of the BAC clones in the library. Development ofphysicalmapwithminimumnumber of overlappingBAC reduces cost ofsequencing although this is very slow and tedious job. Ideally, theminimum tilling path consists of a non-redundant set of clones whichare used for developing physical maps and sequencing. In addition,physical map is also useful for map based cloning and fine mapping ofspecific genes prior to the release of the complete genome sequence(Meyers et al., 2007). It is necessary to analyze random representativesequences to know the content, complexity and unique features of thegenome. BAC-end sequencing provide random sampling of the genome

202 H. Sonah et al. / Biotechnology Advances 29 (2011) 199–209

and it is also useful for SSR mining and development of STS markers.BAC-end sequences are also being used to establish syntenic relation-ship among related species (Cheung and Town, 2007). A large scale BACend sequencing strategy has the potential to anchor a genome to thewell annotated genomes like Rice and Arabidopsis.

Integration of molecular genetic linkage map and physical mapshave been facilitated with the availability of whole genome sequenc-ing data for several model as well as crop species in public domain .Such integration accelerated the process of fine mapping, positionalcloning, comparative genomeanalysis, and clone-by-clone sequencingof different species (Beyer et al., 2007; Kim et al., 2010; Cova et al.,2010). Screening of BAC or YAC library required availability ofchromosome specific molecular markers which can be used as DNAprobes. In general, fingerprinting of BAC clones is performed by usingrestriction enzymes for the development of physicalmap. Besides, PCRbased markers mostly developed from BAC-end sequencing or fromestablished linkagemap are also used to align BAC clones in a physicalmap (Han et al., 2007; Han and Korban, 2008). In some casesidentification of a particular BAC from the library is also done for finemapping and cloning of the gene. It has been achievedmostly by usinglabelled cloned DNA, PCR products, or oligonucleotides for colonyhybridization (Kim et al., 2010; Cova et al., 2010; Vu et al., 2010). Inseveral horticultural crops, BACor YAC libraries have beenused forfinemapping and cloning of genes. Kaufmann et al. (2003) constructed aBAC library from Rosa rugosa covering 5.2 genome equivalents. Thechoice ofR. rugosa as a source of DNA to construct the librarywas basedon information regarding the small genome size of this species.Recently, by using information ofR. rugosa, a BAC library constructed inRosa multiflora hybrids has been assembled to fine map Rdr1 locus forblack spot resistance in roses (Biber et al., 2009). To facilitate genomecomparisons and gene discovery in the Rosaceae, BAC library has beendeveloped for peach as the model genome basically for makerdevelopment (Georgi et al., 2002). Recently, a TERMINALFLOWER1(TFL1) gene locus has been characterized in peach and apricot by usingBAC library which provided basis for the understanding of flowerdevelopment in angiosperm (Liang et al., 2010). Similarly, severalstudies have proved the utility of BAC library and being used for thecloning andmapping of genes inmany horticultural crops (Deng et al.,2001; Cova et al., 2010; Vu et al., 2010; Liu et al., 2010).

4. EST resources in horticultural crops

Expressed Sequence Tag (EST) sequencing represents an efficientalternative to whole genome sequencing, yielding information of themost expressed parts of the genes at a lower cost. It is also called genesignature which helps in cloning and characterization of full lengthgenes. With the development of ESTs in several plant species, a lot ofDNA sequence information has been produced across species anddeposited in online databases. In several horticultural crops sequencedata for many fully characterized genes and full-length cDNA cloneshave been generated. In the NCBI EST database (dbEST; www.ncbi.nlm.nih.gov/dbEST/), there are 296,963, 277,147 and 149,480 ESTsavailable for Tomato, Potato and B. rapa, respectively (Fig. 1A;Table S1). Tomato and Potato (Solanaceous crops) are highlycultivated and consumed throughout the world. In addition theseare relatively easy to grow, transform and regenerate through tissueculture hence used as model system for molecular studies. More than8000 cucumber ESTs are available in the database andwere generatedfrom gynoecious and hermaphrodite flowers using the FLX 454pyrosequencing technology (Table S1). In vegetable crops, specieshave been used to generate the EST resources are mostly fromSolanaceae, and Brassicaceae families (Fig. 2). In case of fruits, grapes(362,193) have the largest number of ESTs in database followed byapple (324,429) and citrus (208,909) (Fig. 1B; Table S2).The obviousreason is the worldwide importance of the grapes. According to the“Food and Agriculture Organization” (FAO) estimates 75,866 km2 of

the world cultivated areas are dedicated to grapes cultivation.Approximately 71% of world grape production is used for wine, 27%as fresh fruit, and 2% as dried fruit. This might be one of the reasonsthat this fruit has attracted lot of attention of the biologists forgenomic studies. Similarly, apple and citrus are also economicallyimportant fruits and thus being studied extensively at genomic level.In case of flowers, M. guttatus has maximum number of ESTs(231,095) (Fig. 1C; Table S3).Mimulus is phylogenetically well placedfor comparative genome analysis because of its relationships to cropplants with well developed genomic resources (e.g., tomato, sun-flower, lettuce; all Asterids and Arabidopsis) and its flower structureused as a model for developmental studies. Furthermore, a relativelysmall genome size (~500 Mb) and large map length (~2000 cM in M.guttatus complex) enable genetic dissection of this species relativelyeasy (Fishman et al., 2001; www.mimulusevolution.org). Mostly,species of few genera have been extensively studied to generate DNAsequence information (Fig. 3). Many crops other than the fruits andvegetables which have importance in medicine, spices, or plantationhave been studied and EST resources for some of these are available inthe public domain (Table S4). However, development of ESTs frommany horticultural crops is still far from these figures.With the adventof new sequencing technologies, the number of sequences willsignificantly increase in the near future. These ESTs will form animportant source not only for the discovery of candidate genes andgenetic markers, but also for the development of microarrays, untilthe whole genome get sequenced.

5. Molecular markers in horticultural crops

Advances in technologies for identifying accurate genetic poly-morphisms have accelerated the discovery of molecular markers. Themost popular markers developed from the genomic resources includeSSR, SNP and conserved ortholog set (COS) markers. ESTs have beenused for the generation of SSR and SNP markers in severalhorticultural crops (Frary et al., 2005; Sargent et al., 2006; Ekué etal., 2009; www.bioinformatics.nl/tools/). SSR markers are relativelyeasy and cheap to develop, and will remain a choice of markers forcrop research community. However, ESTs derived markers are mostlymonomorphic, thus limit their use in developing linkage maps andDNA fingerprints. Another marker system developed from genomicresources is SNPs and insertion/deletion (InDel). The SNPs markersare simple to develop since they are composed of a nucleotidedifference at single position. Nowadays there has been muchdiscussion on the use of computational methods for the developmentof SNP markers from large collection of DNA sequences (Marth, 2003;Weil et al., 2004; Huntley et al., 2006; Matukumalli et al., 2006). It hasalso been suggested that SNP markers developed in one system maybe applicable across different systems (Grapes et al., 2006). SNPs havebeen developed in many species (Gilchrist et al., 2006; Hyten et al.,2008) including grape where they were derived from BAC end andEST sequences, and used successfully for the construction of geneticlinkage maps (Salmaso et al., 2008; Vezzulli et al., 2008a). These havealso been anchored to the physical maps (Troggio et al., 2007). Inaddition, SNPs identified in grape gene sequences have been usedin genetic diversity studies and linkage disequilibrium analyses(Le Cunff et al., 2008). The recent decoding of the grape genomesequence of the Pinot Noir cultivar provided 1,700,000 SNPs to thegrape research community (Velasco et al., 2007). Likewise SNPs havebeen generated and utilized in other horticultural crops (Simko et al.,2006; Chagne et al., 2008). Development of allele-specific markers forthe genes controlling important horticultural traits will be necessaryfor their effective utilization in breeding superior varieties. The choiceof the most appropriate marker system is based on a case by casebasis. It will also depend on many issues, including the easyavailability of marker technology platforms, costs for marker

Fig. 1. ESTs resources available in public database for (A) vegetables, (B) fruits, (C) flowers, and (D) other miscellaneous horticultural crops up to August 2010.

203H. Sonah et al. / Biotechnology Advances 29 (2011) 199–209

development, cross-species transferability, information content andapplicability.

A total of 71,482 putative SNPs have been identified in apple usingEST database of approximately 350,000 sequences which were usedfor designing SNP markers (Chagne et al., 2008). SNP markers for theapple offer new opportunities for understanding the genetic controlof important horticultural traits using QTL or linkage disequilibriumanalysis. These also serve as important markers for aligning physicaland genetic maps and as potential transferable markers across theRosaceae family (Chagne et al., 2008; Folta and Gardiner, 2009).Ortholog specific EST-SSR markers have been developed for geneticmapping and other genotyping applications in Iris and described theabundance and utility of SSRs identified in the transcript assembly.The cross-species utility and polymorphisms of I. brevicaulis–I. fulvaEST derived SSR markers among wild ecotypes and horticulturallyimportant cultivars have also been discussed (Tang et al., 2009).Development of SSR markers has been very costly as it involved highcost of library screening and clone sequencing. But now-a-dayslarge public SSR datasets exist for several crop species and many ofthese have been used and exploited for cross species transferabilityanalysis (Table 2). SSR markers can also be used for studying syntenybetween distantly related species (Dirlewanger et al., 2004a; Howadet al., 2005; Celton et al., 2009) and breeders can take advantageof these findings to identify markers for traits of interest in theirspecialist crops.

Markers tightly linked to major genes responsible for theexpression of important traits (disease/pest resistance, fruit/nutquality, self incompatibility etc.) have been developed in manyhorticultural crops and are being used for marker assisted selection

(Dirlewanger et al., 2004b; Zhu and Barritt, 2008; Iezzoni et al., 2010;Bliss, 2010). Marker-assisted breeding is widely used amonghorticultural crops to improve breeding efficiency as well as to reducecost involved in breeding programmes. Marker assisted breeding willsurely benefit horticultural crop breeding using information frommodel plant species. Ogundiwin et al. (2008) have used a number ofadvanced molecular genetics techniques and information fromArabidopsis studies to identify a gene encoding the leucoanthocyani-din dioxygenase (PpLDOX) enzyme. This enzyme is potentiallyinvolved with a QTL controlling enzymatic browning of the peachfruit mesocarp leading to chilling injury. The molecular informationcan be used in breeding programme for the development of varietiestolerant to chilling injury in peach and other stone fruits (Peace et al.,2005; Bliss, 2010). Iezzoni et al. (2010) have proposed an eight-stageprocess to improve routine utilization of markers for breeding. Thesesteps are prioritization of available marker-locus-trait associations,demonstration of screening efficiency of markers, improving markersfor specific loci and traits, validating the markers across crops,demonstrating marker utility within target populations of specificbreeding programmes, making strategic decisions on MAPS,performing cost and logistics analyses based on marker assistedselection (MAS), and actually demonstrating utility of MAS for cropimprovement (reviewed by Bliss, 2010).

During the last decade, linkagemaps have been prepared for severalhorticultural crops by using various types of mapping populations andmolecular markers (Table S5). However due to the perennial nature ofmost of the fruit crops, linkage maps have not been successfullyemployed for gene mapping and tagging experiments. In addition,availability of high density genetic maps is restricted to a few crops.

Fig. 2. Contribution of species representing different genera of (A) vegetable crops,(B) fruit crops and (C) flower crops used to generate EST resources.

204 H. Sonah et al. / Biotechnology Advances 29 (2011) 199–209

Fortunately, ultra dense genetic linkage (UDGL)map has been reportedin potato which contains 10,000 markers which is the densest mapamong all crop species (van Os et al., 2006). Development of such UDGLmap will be expected in many more horticultural crops in near futurewhichwould serve as the basis for map based gene cloning and markerassisted breeding in horticultural crops. For fruit crops, most of themapping resources are available for grape, apple, citrus and prunus spp(Liebhard et al., 2003; Celton et al., 2009; Chen et al., 2008; Olmstead

Fig. 3. Species from vegetables, fruits and flowers having EST resources N1000,GSSN1000 and UniSTSN100 entries available in the public databases up to August 2010.

et al., 2008). Unfortunately, considerable efforts made to developmolecular linkage maps were very rare for floriculture crops. Moreprobably this is due to the lack of funding available to researchers infloriculture. However, well saturated linkage maps were available insome floriculture crops like Roses, Helianthus, Monkey-flower, Petuniaand Catharanthus (Yan et al., 2005; Tang et al., 2002; Lowry et al., 2009;Stuurman et al., 2004;Gupta et al., 2007). Currently, improved statisticaltools and increasing number of linkage maps with anchored markershave been utilized to establish a consensusmap for several crop species.This facilitates the research on mapping and cloning of genes forbreeding commercial varieties and allows the basic understanding ofevolution and domestication of these species.

6. Candidate gene identification and positional cloning

Availability of genomic resources in public domain help molecularbiologists to identify candidate genes in the genome sequences usingbioinformatics approach and then clone them from the related speciesby PCR amplification and sequencing. A candidate gene approach hasbeen used for isolating plant genes that underlie specific traits(Pflieger et al., 2001; Sharma et al., 2005b). In potato, cloning of theGro1-4 gene, which confers resistance to pathotype Ro1 of the cystnematode Globodera rostochiensis, has been achieved using a jointcandidate gene and positional cloning approaches (Paal et al., 2004). Acandidate gene approach in which genes identified in Arabidopsis hasbeen used to identify related genes in cauliflower and broccoli (King,2003). The ap1-1/cal-1 mutant of Arabidopsis thaliana results in aproliferating and arrested inflorescence phenotype similar to cauli-flower and broccoli leading to speculations that similar genes mightbe responsible for this characteristic trait in B. oleracea.

Most of the important traits in plants are governed by QTL.Recentlymany QTL have been identified for several important traits infruit as well as vegetable crops (Kenis et al., 2008; Olmstead et al.,2008; Zhang et al., 2010; Kubo et al., 2010; Hatakeyama et al., 2010).Many of these loci are very large and difficult to transfer genetically.However, advances inmolecular tools and genomic resources allow usto dissect QTL and clone the candidate genes responsible for thequantitative traits. Presently, several QTL have been fine mappedand some of these were successfully cloned by positional cloningapproach (Table 3). In some cases, an association between allelicvariation present within a candidate gene and a phenotype has beenestablished by using existing genetic accessions. These strategiescan be made more effective by using appropriate genetic materialslike introgression libraries and panels of unrelated accessions, andemploying latest forward- and reverse-genetic approaches. Highquality genome sequences and efficient bioinformatics tools willfacilitate in silico identification of candidate sequences showing highhomology with QTL in positional cloning or association mappingprogrammes. Based on map information and observations, severalQTL have been associated to candidate genes without resorting tocloning. For instance, QTL for fruit shape, fruit weight (Frary et al.,2000; Liu et al., 2002) and fruit sugar contents have been cloned fromtomato and functionally validated by using transgenic approach(Table 3). Hence, this approach can also be extended for otherimportant horticultural traits in future. The cloned QTL can betransferred to cultivated varieties using marker assisted selection.

Along with the economically important traits many studies wereconducted for the improvement of nutritional quality of fruits andvegetables. The major area of nutritional genomics in horticulture isfocusing on cloning of genes related to antinutitional, nutraceutical,and pharmaceutical applications. Carotene production (precursor ofvitamin A) is one of the extensively studied topics, mainly focused onthe identification of genes and understanding of related pathways.Several genes of carotenoids were cloned from horticulture crops liketomato, citrus and papaya (Davuluri et al., 2005; Zhang et al., 2009;Blas et al., 2010). A gene (Or) isolated from a high-β-carotene orange

Table 2Examples of interspecific or intergenic transferability of genic molecular markers in horticultural crops.

Crops Species used for validation Markers used References

Tomato (Solanum lycopersicum) Solanaceous members EST-SSR, SNP,Gene specific

Frary et al. (2005)

Grape (Vitis vinifera) Vitaceae and Rosaceae species EST-SSR, SNP Scott et al., 2000; Arnold et al., 2002; Decroocq et al.,2003; Vezzulli et al., 2008b; Rossetto et al., 2002

Apricot (Prunus armeniaca) Vitaceae and Rosaceae species EST-SSR Decroocq et al. (2003)Strawberry (Fragaria vesca) F. gracilis. F. nilgerrensis, F. npponica, F. iinumae EST-SSR Bassil et al. (2006)Citrus (Citrus sinensis) Poncirus trifoliate EST-SSR Chen et al. (2006)Coffee (Coffea ssp.) 16 species of coffee and Psilanthus EST- SSR Bhat et al., 2005; Poncet et al., 2006; Aggarwal et al.,

2007Sweet cherry (Prunus avium L.) Prunus sps SSR, CAPs Olmstead et al. (2008)White Campion (Silene latifolia) Silene species EST-SSR Moccia et al. (2009)Litchi (Litchi chinensis) 16 Ackee trees, Pulasan (Nephelium ramboutan-ake L.) SSR Sim et al., 2005; Ekué et al., 2009Iris 26Lousiana Iris species (I. brevicaulis, I. fulva, I. hexagona, and I. nelsonii) and13

(I. germanica), yellow-flag (I. pseudacorus), and Siberian (I. sibirica) IrisEST-SSR Tang et al. (2009)

Brassica Brassica sps SSR Yadava et al., 2009; Bhati et al., in pressLactuca sativa L. 96 accessions representing all major horticultural types and 3 wild

species (L. serriola, Lactuca saligna, and Lactuca virosa)EST-SSR Simko (2009)

Potato (Solanum tuberosum) 65 Solanum tuberosum lines and 14 other species SSR Grover et al. (2009)Sunflower Safflower, Compositae sps SSR, InDel, gene

based markersHeesacker et al., 2008; García-Moreno et al.,2010

Cucumis melo L. C. melo, Citrullus lanatus, Cucurbita maxima, C. moschata, C. pepo andCucumis sativus,, Sps

SSR Ritschel et al. (2004)

Vicia faba (Fabaceae) Faba beans, Pisum sativum EST-SSR Gong et al. (2010)

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cauliflower mutant provides a good resource to make transgenic incarotenoid deficient crops (Zhou et al., 2008). Like vitamins,antioxidant has prime interest in several horticultural crops. Dietaryconsumption of anthocyanins (antioxidant) has been associated withprotection against a broad range of human diseases. However,anthocyanin levels in most commonly eaten fruits and vegetablesmay be inadequate to confer optimal benefits. In tomato, expressionof the two transgenes enhanced the hydrophilic antioxidant capacitythreefold (Butelli et al., 2008). This approach can be used towardgeneration of new medicines. Fruits are also thought to be used todeliver vaccines and so many attempts have been performed to makeedible vaccines (Sharma and Sood, 2010; Rybicki, 2010). Such studieshave demonstrated the application of molecular techniques inmanipulation of nutritional contents in many horticultural crops.

7. The DNA microarray studies

DNA microarray analysis is a powerful technology for the globalexpression analysis of genes in an organism. However development ofmicroarray chips need well characterized cDNA or EST sequences. Thegeneration of large EST collections is a primary route for large-scalegene discovery. The application of cDNA arrays has become extremelywidespread in many horticultural crops like potato (Rensink et al.,2005), citrus (Forment et al., 2005), gerbera (Laitinen et al., 2005),B. oleracea (Soeda et al., 2005) and strawberry (Aharoni et al., 2004).

Table 3QTL cloned in important horticultural crops.

Crops QTL/gene function Molecular identification

Tomato Fruit shape (Ovate) UnknownFruit sugar content (Brix9-2-5/Lin5) InvertaseFruit weight (fw2.2) UnknownSw4.1 QTL ABC transporter gene

Potato Resistance to Ro1Globodera ostochiensis (Gro1-4) UnknownQuality trait cold-sweetening (invGE/GF) InvertaseFlavonoid 3_,5_-hydroxylase (f3_5_h) –

Apple Scab resistance gene VF Leucine rich repeat domTransmembrane domain

Sugarbeet Nematode resistance HS1pro-1 Leucine rich repeat domPepper Virus resistance e1F4E gene Leucine rich repeatCauliflower Orange gene (Or) Dna J Cysteine Rich domPapaya CpCYC-b Lycopene β cyclase

Oligonucleotide arrays are commercially available for many cropspecies including Solanum lycopersicon and Vitis vinifera (www.affymatrix.com). Array-based SNP technologies have been demon-strated in potato genome analysis (Rickert et al., 2005) and willundoubtedly be used in many more species. Sequencing efforts intomato have yielded results of translational value as data depositedinto publicly accessible databases have been used to discovermolecular markers and candidate genes for use in genetics andbreeding research (Yang et al., 2004; Frary et al., 2005).

A non redundant set of 10,000 ESTs were used by The Institute forGenomic Research (TIGR) to develop a cDNA potato microarray thatwas made available to the research community at minimal cost.Moreover, the same organization offered a transcription profilingservice to allow the evaluation of these arrays by a wide range of usersworking on different Solanaceous plant species. This allowed gener-ation of massive microarray data that is available publicly (www.tigr.org/tdb/potato/). The potato oligochip initiative (POCI) has selectedthe Agilent “44K feature platform” system, which was made availablefor use in gene discovery in 2006. This system is quit flexible andallows for redesign of the arrays as and when more gene sequenceinformation becomes available in future. Among the methods used forrapid identification and genotyping, the detection of genetic differ-ences with specifically designed DNA chip arrays is perhaps the mostpromising technique for horticultural crops (Huber et al., 2002; Stearset al., 2003; Wong et al., 2004). The melon cDNA array (v 1.0) have

Candidate gene Method used References

Positional cloning Transformation Liu et al. (2002)Positional cloning Complementation Fridman et al. (2002, 2004)Positional cloning Transformation Frary et al., 2000; Cong et al., 2002Positional Cloning RNAi Transformation Orsi and Tanksley (2009)Positional cloning – Paal et al. (2004)Positional cloning – Li et al. (2005)Positional cloning Transformation Jung et al. (2005)

ain Positional cloning – Xu and Korban (2003)

ain Positional cloning – Cai et al. (1997)Candidate gene Complementation Ruffel et al. (2002)

ian Positional Cloning Complementation Lu et al. (2006)Candidate gene Complementation Blas et al. (2010)

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9216 spots representing 3068 genes and is available from the Centerfor Gene Expression Profiling (CGEP) (www.icugi.org).

A powerful approach for identifying different haplotypes at targetloci andmaking them available for associationmapping is provided byEcotilling (Comai et al., 2004). This technique is used for identificationof all SNPs and small InDel within 1 kb window in a set of genotypes.Ecotilling has been successfully used to examine genetic variation inMelon ecotypes (Nieto et al., 2007) and Tomato (Stergiopoulos et al.,2007). Ecotilling is being used for the identification of allelic variantswithin natural populations for rapid gene discovery method acrossspecies. Application of microarray for detecting polymorphism amonglarge number of individuals is very costly. However, with rapidadvancement in cost effective tools, the use of microarray for largescale applications like genetic mapping, diversity analysis andEcotilling in various horticultural crops is expected in future.

8. Comparative genomics in horticultural crops

Comparative genomics is the study of relationship betweenstructural and functional attributes of genomes across differentspecies. The sequence information of several horticultural cropsdeposited in public databases can be utilized for both basic andapplied research in related genera. This will help in elucidatingevolutionary relationships among different species and developingbetter phylogenetic classification. Comparative genomic approacheshas been utilized in horticultural crops, mostly across families likeFabaceae (Zhu et al., 2005; Cronk et al., 2006), Rosaceae (Dirlewangeret al., 2004a,b), Solanaceae (Mueller et al., 2009), Asteraceae (TheCompositae Genome Project: www.compgenomics.ucdavis.edu) andBrassicaceae (Hall et al., 2002; Lysak and Lexer, 2006). These studieshave shown that genome evolution mostly consisted of chromosomalrearrangements, leading to syntenic co-linearity among large chro-mosomal regionswithin a family. For instance, inMaloideae, high levelof co-linearity has been observed between Malus and Pyrus genomes(Yamamoto et al., 2004). This has also been proved by construction offirst genetic linkage map of loquat (Eriobotrya japonica) by using SSRmarkers derived fromMalus (Gisbert et al., 2009). Accordingly this co-linearity can be further utilized for comparative mapping studiesamong other members of the Maloideae, such as loquat and quince.The comparative plant genomics was actually started in 1988 in theSolanaceae, by developing a genetic linkage map of potato chromo-somes based on genomic and cDNA clones from tomato (Bonierbale etal., 1988) and at the same time, genomic information of tomato hasalso been used in pepper (Tanksley et al., 1988). Later on, genomicinformation of tomato has been utilized for the comparative analysisof several other Solanaceae crops. In case of Brassica, the Arabidopsisgenome sequence provides a valuable resource for structural andfunctional genomics. Brassica and Arabidopsis genes share, on average,87% sequence identity (Cavell et al., 1998), and this facilitate theutilization of Arabidopsismicroarray for expression analysis in Brassica(Liu et al., 2005; Fu et al., 2009). Several studies have demonstratedthe use Arabidopsis genome for fine mapping of QTLs and cloning ofgenes in Brassica (Formanová et al., 2010; Zhao et al., 2010). Physicalanchoring of Brassica unigene derived markers on the A. thalianagenome has been reported (Parida et al., 2010). This studydemonstrated the use of unigene derived markers for the establish-ment of synteny between related genera and will be used tounderstand complex chromosomal rearrangements such as inver-sions, tandem and segmental duplications, and insertions/deletionsoccurred in different Brassica species.

Several online tools and databases are also available to compileinformation of different horticultural crops. For instance, a GenomeDatabase for Rosaceae (GDR) is integrated web-based relationaldatabase providing centralized access to Rosaceae genetics andgenomics data and analysis tools to facilitate cross-species comparisons(Jung et al., 2008; www.rosaceae.org). The GDR contains annotated

databases of all publicly available Rosaceae ESTs, the geneticallyanchored peach physical map, Rosaceae genetic maps and comprehen-sively annotated markers and traits. Similarly, Solanaceae GenomicsResource (SGR) developed at Michigan State University provides arobust, rich, and integrated resource allowing broad and deep data-mining of Solanaceae sequences (www.Solanaceae.plantbiology.msu.edu/). This resource provide access to the Solanaceae community forperforming comparative and de novo analysis on the partial genomicsequences provided by the Tomato, Potato and Tobacco genomesequencing consortia. It also provides information on Solanaceaetranscript assemblies, and link Solanaceae sequences to the functionalgenomics resources of other related model dicot species. Presently,plenty of tools and databases are available for genomics studies mostlybecause of advances in sequence generation, informatics, computer andinformation technology.Howevereffective utilizationof these resourcesis a great challenge for horticultural breeders.

9. Harnessing genomic information of model species

The availability of well annotated genome sequences in modelplant species like Arabidopsis and rice helps to annotate sequence ofother related crop species. Rice is the first crop whose genome hasbeen sequenced and proved their utility in the comparative genomicsof cereal crops (IRGSP, 2005; Singh et al., 2004; Singh et al., 2007). Akey challenge arising from comparative genome analysis is theidentification of genes that are candidates for controlling importantagronomic features of crop plants based on the analysis of model plantspecies. The first major success of the model to crop genomicsapproach in the monocots came with the isolation of the wheat semi-dwarfing genes Rht-B1 and Rht-D1 known for green revolution (Penget al., 1999). These genes were isolated prior to the availability ofArabidopsis and Rice genome sequences by using rice EST database.Now positional cloning of genes is relatively easy in those cropswherecomplete genome sequence is available in the public domain. Forinstances in rice several disease resistance genes and resistance genesanalogues have been cloned and mapped on the rice chromosomes(Sharma et al., 2005a; b; Kumar et al., 2007a; Ghazi et al., 2009). OnceQTL are mapped on specific chromosomes, their fine mapping andeventual cloningwould be facilitated by taking the help of high qualityplant genome sequence (Deshmukh et al., 2010; Channamallikarjunaet al., 2010). Comparative analysis of specific locus on genomesequence of Indica and Japonica types of rice has revealed thatmicrosatellite are associated with disease resistance genes whichmight be playing an important role in reshuffling of genes within thegenome (Kumar et al., 2007b). Comparison of ESTs derived fromdisease resistance rice line with those of different plant species hasshown conservation of specific genes across genomes (Dixit et al.,2009). Detailed information of rice genomes helps to use universalsequences of rice as DNA markers for molecular analysis of othermicrobial (Jana et al., 2005) and plant species (Dikshit et al., 2007) andeven in vegetable crops like carrot (Jhang et al., 2010). Thedevelopment of various genomic tools in model crops, such as thegenetic map, physical map, transcript map and map based genomesequence is important for comparative genomics. Such implementa-tion of knowledge from model species is also applicable for thehorticultural crop improvement. Several attempts have been made touse genomic information of Arabidopsis in Brassicaceae (like broccoli,spinach, cabbage, cauliflower) research (Ayele et al., 2005; Lee et al.,2007). Information on synteny between the short arm of barleychromosome 1 and short arm of rice chromosome 6 was used for thesuccessful cloning of barley stem rust resistance gene Rpg1 (Han et al.,1999). Identifying the syntenic region that is likely to be orthologsbetween species can be aided by optimizing the sequence alignmentvariables. We have optimized expected e-values, gap penalties,mismatch penalties, etc. by utilizing well characterized genes with ahigh, medium and low level of similarity between rice and wheat

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(Singh et al., 2004). Identification of homologous and orthologoussequences in crop plant is therefore important in studying synteny andmicro-synteny across genomes of horticultural crops.

10. Challenges

The ultimate goal of functional genomics and bioinformatics is tointegrate large-scale data for understanding the molecular mechanisminvolved in various developmental processes. Recent knowledge allowseloquent and qualitative understanding of most of the problems inbiology. Rapid development in molecular biology leaves behind all theallied crop sciences which are more applicable in crop improvement.The gap between these crop sciences and genomics will widenwith thechanging scenario of technology. These limitations present a number ofchallenges for technology development, data interpretation, andultimately, for integrating information from multiple disciplines. Manyeconomically important horticultural crops have very less or nogenomic resources available which need to be taken on priority basis.

The most important challenge in many of the fruit species isunavailability of well defined molecular genetic linkage maps. Manytimes these species are difficult to study at genetic andmolecular levelsbecause of their perennial nature. Because of this, development ofmapping population and map based studies are not easy. However, theadvances in genomics, along with powerful statistical tools can be usedfor developingmarkers linked to a specific trait. One of the challenges inunderstanding genome structure of woody plants is unavailability ofESTs or other genomic resources. Being complex genomes, it would alsobe difficult to sequence these species de novo using NGS technologies.Though one can generate enough sequences from any species, de novogenome assembly becomes a stumbling block. Therefore, it would bedesirable to first determine the genome size of species and also developsufficient DNA markers from the ESTs or other GSS.

Even after identification of trait specific genes from the genomicresources, their functional validation would be difficult because theseare recalcitrant and not amenable to tissue culture techniques. Hence,alternative strategies should be developed for the functional analysisof identified and cloned genes in most of these crops. In future, moreemphasis should be given to perform genetic transcriptomics andgenomic analysis of so called orphan horticultural crops so that latesttechnologies can be used for their improvement.

Acknowledgements

TRS is thankful to the Indian Council of Agricultural Research, NewDelhi for financial assistance for the Bioinformatics project underNetwork Project on Transgenic Crops.

Appendix A. Supplementary data

Supplementary data to this article can be found online at doi:10.1016/j.biotechadv.2010.11.002.

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