Complementary DNA libraries from wheat or closely related species will be produced and normalized to maximize the access to all genes in the wheat genomes. Approximately 80,000 of these cDNA clones will be single-pass 5' sequenced thereby producing a large database of expressed sequence tags (ESTs). Identification of singleton gene motifs from these ESTs, and those generated by international collaborators, will be carried out by 20,000 3' single-pass sequencing. Nucleotide sequence comparison of these ESTs will be used to arrive at a minimum of 10,000 EST singletons, representing approximately half of all the gene motifs in the wheat genomes. All chromosomal loci complementary to these singletons in the wheat genomes will be identified by their Southern hybridization with a unique mapping population of chromosome deletion stocks. Rice, maize and other grass genome ESTs homologous to the wheat singletons will be identified by nucleotide sequence match searches. Additional rice and maize ESTs of known chromosomal position in those genomes and not matching wheat ESTs will be mapped in wheat. These two approaches will produce detailed comparative maps between wheat and other grass genomes. The pool of wheat EST singletons will be used in gene-function studies focusing on the reproductive phase of the wheat plant. The database generated by these objectives will provide means to study specific questions about the structure, putative function, chromosomal location, and evolution of the expressed component of the wheat genomes.
Wheat genomes, like all genomes in the tribe Triticeae, are large in comparison to the current plant models, Arabidopsis and rice. A. thaliana was estimated to have 21,000 genes (Bevan et al. 1998). While wheat genomes have probably similar numbers of gene motifs as the small-genome plants, the large genome size makes it unrealistic to anticipate complete sequencing any of the Triticeae genomes in the near future. Therefore, large-scale discovery, isolation and deciphering gene function in wheat and its relatives must rely on other, less direct methods. The current approach of map-based cloning, transposon mutagenesis, differential display techniques, and other strategies of deciphering gene function, are either not suitable for large genomes or are tedious and expensive because they deal with a single gene at a time. Therefore, it is necessary to devise alternative strategies to access genomes of wheat and its relatives on a large scale and thus ensure continued advances in the biology of this immensely important plant. Such a strategy is described in this proposal. It focuses solely on the expressed component of the wheat genomes and takes a maximum advantage of unique strengths of the wheat genetic system. Moreover, it constructs a bridge between the wheat genome and other important grass genomes for fluid movement of information on gene location and function from other grass genomes to Triticeae and vice versa and facilitates exploitation of the high conservation of gene order among grass genomes (Moore et al. 1995; Devos and Gale 1997) for comparative functional genomics.
Identification of the chromosomal location of a large number of EST singletons will simultaneously construct a comparative map with other grass genomes. This is particularly important for linking wheat with rice genomes, since rice will likely be the first grass genome sequenced. Sequence matching of mapped wheat ESTs with a rice sequence database will automatically identify putative orthologous loci between the two genomes and facilitate transfer of information on gene function between wheat and rice. Needless to say, the project described here will lead to the development of technology and research tools which will benefit the entire Triticeae community in this country. Because of large-scale colinearity among Triticeae genomes, wheat and barley in particular, results of work on wheat can be extended to other Triticeae genomes with a minimum or no extra work.
The population of EST singletons will be the foundation for studies of gene-function, structure, and evolution of the expressed component of the wheat genomes, as illustrated in Figure 1. To study gene function, ESTs will be microarrayed and used in gene expression studies. Although a general, long-term utility of the ESTs is the primary motivation of the EST development in this project, we will focus the gene-function studies in this project on the reproductive phase of the wheat plant. The reproductive phase, commencing with the flowering signals and terminating by imposition of seed dormancy involves processes of great biological interests and is exceedingly important economically. Since seeds are the economically important part of the wheat plant and their characteristics are critical for the end-uses of wheat grain, the understanding of their development and environmental factors affecting their development are of a paramount practical significance. We will accordingly examine the seed development time-course and its modifications by environmental stresses and seed dormancy.
Transmission of genetic information in polyploid wheat and gametogenesis with complex nucleo-cytoplasmic interactions is another exceedingly important process of the reproductive phase. Meiotic chromosome pairing in polyploid wheats is tightly regulated by a complex gene system resulting in recognition of differentiation between homoeologous chromosomes and elimination of heterogenetic chromosome pairing that could potentially occur between wheat homoeologous chromosomes. The principal, and the best known, component of this genetic mechanism is the suppressor of homoeologous chromosome pairing, Ph1 (Riley and Chapman 1958; Sears and Okamoto 1958). We will exploit wheat deletion stocks and other cytogenetic tools in studies of gene expression with EST microarrays to identify genes participating in this fascinating modification of meiosis. Since wheat meiosis is likely to resemble the processes of diploid organisms, the EST microarray approach will facilitate relating the finding to diploid models, such as yeast, Drosophila, and Arabidopsis.
A general tendency in plant genomics has been to emphasize small-genome models. Nevertheless, the existence of large genomes is an undeniable reality. It is, therefore, essential to keep advancing the knowledge of the organization and evolution of large plant genomes in balance with efforts in the small-genome models. For many reasons, wheat and its close relatives offer unique advantages as models of large-genome plants. The mapping of a large number of ESTs in wheat deletions will provide extensive data on gene densities across chromosome arms. This knowledge is important for the basic understanding of the organization of large genomes and is exceedingly important in the practical design of gene isolation strategies by chromosome landing (Tanksley et al. 1995). Additionally, mapping of a large number of ESTs of known pattern of expression will provide data on the distribution of genes with similar developmental expression within the genome and may, in turn, contribute to understanding of factors responsible for conservation of gene order during the evolution of grass genomes.
Figure 1. Schematic of Proposal Organization. Budgeted activities are EST production, deletion mapping, and functional genomics.
Within the grass family, comparative genetics has revealed a remarkable level of macro-colinearity. Large segments of the maize, sorghum, rice, wheat, and barley genomes conserve gene content and order (Hulbert et al. 1990; Ahn and Tanksley 1993; Ahn et al. 1993; Kurata et al. 1994a; Van Dayze et al. 1995; Moore et al. 1995; Saghai Maroof et al. 1996; Devos and Gale 1997; Devos et al. 1998), although the correspondence among some of the genomes has been further modified by segmental chromosome duplications, inversions, translocations and paleopolyploidy. To date, most comparative mapping among the grasses has relied on RFLP probes to establish gross gene orders in specific chromosome segments.
Because rice is anticipated to become a model species for the entire grass family, rice-Triticeae comparative mapping is of great importance. Comparisons of the rice and hexaploid wheat and barley have led to the identification of a number of homoeologous regions and established the genetic correspondence of the seven homoeologous groups of the Triticeae genomes with the 12 rice chromosomes (Ahn et al. 1993; Kurata et al. 1994a; Sherman et al. 1995; Van Dayze et al. 1995; Saghai Maroof et al. 1996; Devos et al. 1995b; Devos and Gale 1997). Nevertheless, homoeologous relationships are obscured for many chromosome segments. The utility of rice as a model for the Triticeae genomes will not reach its full potential unless the colinearity between the rice genome and a consensus genome for wheat and other Triticeae genomes is established in greater detail.
It has been speculated that loci expressed in specific developmental stages or responding to specific environmental stimuli are nonrandomly distributed in the wheat genomes. For instance, loci expressed in seed development tend to be on wheat chromosome 1, those responding to osmotic stresses tend to be on chromosome 5 (Dubcovsky et al. 1995a) and meiotic loci tend to be on chromosomes 3 and 5. However, since only small numbers of loci of known function have been mapped, these trends may just be a coincidence. Nevertheless, studies of expression of yeast ORFs during cell cycle with microarrays revealed that loci expressed during same stages of cell cycle tend to be co-located (Cho et al. 1998). In tomato, a gene complex controlling genetic and morphological mechanisms of reproduction is co-located on the long arm of chromosome 1 (Bernacchi and Tanksley 1997). Similar associations in other flowering plants suggest that such complexities may have been conserved since early periods of plant evolution or may reflect a convergent evolutionary process (Bernacchi and Tanksley 1997). The determination of function and location of thousands of ESTs that will be conducted in this project will provide the necessary framework to shed light on the global organization of the expressed portion of the wheat genomes and, in turn, may suggest factors constraining the global gene order on the evolutionary time-scale.
Messenger RNAs (mRNAs) provide the opportunity to obtain significant information in a more rapid and usable form than studying the entire genome by converting the labile mRNAs into stable double-stranded (ds) DNA for cloning as complementary DNAs (cDNAs). Recombinant libraries of cDNAs then represent an approximate snapshot of the population of mRNAs in the tissue or organism under study and indirectly a picture of the total pattern of gene expression.
ESTs are the products of genes which serve as the templates for the synthesis of proteins and ultimately determine the shape, size, and characteristics of an organism. The basic strategy for EST production and use was formulated by Craig Ventner’s group (TIGR) in 1991 and is a rapid, efficient method for sampling a genome for active gene sequences. Typically, anonymous cDNAs are used to determine short DNA sequences (300-400 bp) in a single sequencing reaction. These sequences are then used to search existing databases (Adams et al. 1991a) to determine if a specific gene (or gene motif) has been found in the same or other organisms and if its function has been determined.
There is, as yet, no formula or protocols to insure identifying all wheat genes. An extensive EST program would likely require 300,000-500,000 sequences to hit most of the genes. As an example in another crop EST program, a goal of 300,000 reactions has been set by the recently organized and funded public soybean EST project (Vodkin et al. 1998; Shoemaker 1998) with a target of 30,000 singletons. However, even fewer wheat ESTs would provide a tremendous resource for U.S. wheat research and development, and comparative genomics.
The availability of EST databases is also essential to move onto the use of a number of new techniques, including cDNA and oligonucleotide micro-arrays, and SAGE (Serial Analysis of Gene Expression). The developing technology of DNA-chips is poised to revolutionize many areas of plant biology. In this technology, DNA is fixed to a solid surface (glass or a membrane) and hybridized with a fluorochrome-labeled nucleic acid probe. The degree of hybridization to each DNA gives a measure of the amount of probe complementary to the immobilized DNA. In one report, microarrays of 1046 of human anonymous cDNAs were produced and used to monitor differential expression in a two-color hybridization assay (Schena et al. 1996). Fluorescence intensities spanned more than three orders of magnitude. The differences in expression were compared between heat shock versus control tissue and found that 17 individual array elements displayed altered fluorescence of 2-fold or greater. These 17 were sequenced and 14 matched known genes, mainly related to heat-shock. Three did not match any known gene. Control experiments indicated a sensitivity of this assay as 1 mRNA in 500,000. Another version of DNA microarray usage is to immobilize gene sequences rather than cDNAs (DeRisi et al. 1997). Less than 2-fold changes in expression were easily detectable. As glucose was depleted in yeast culture, 710 genes were induced by at least 2-fold, and mRNA levels for 1030 genes decreased by at least 2-fold. About half of the differentially expressed genes had no apparent homology to genes of known function, thus providing the first clue to their metabolic roles. The data were used to compare entire pathways, assign genes into groups by common responses, and reveal previously unknown metabolic links. Chu et al. (1998) used microarrays representing all yeast genes to study the developmental system of sporulation in budding yeast. Seven distinct patterns of gene induction were observed, including coordination of gene sets and clues to potential functions for hundreds of previously uncharacterized genes. Ruan et al. (1998) and Desprez et al. (1998) monitored expression profiles of Arabidopsis genes with such microarrays. Novel expression patterns were identified for genes with putative identification and suggested possible functions for novel sequences of previously unknown function.
Oligonucleotide arrays are the versions of DNA microarrays where short oligonucleotides complementary to known genes or cDNA sequences can be directly synthesized and gridded on glass slides (Ramsay 1998; Marshall and Hodgson 1998). One nice example of use of oligonucleotide arrays is that of (Chee et al. 1996) who arrayed 135,000 oligonucleotides complementary to the entire 16.6 kb human mitochondrial genome and were able to detect single base polymorphisms throughout the entire mitochondrial genome in single hybridizations.
The SAGE technique allows for both qualitative and quantitative profiles of gene expression by relying on short DNA tags to identify individual transcripts (Velculescu et al. 1995). It is a rapid method of analyzing and cataloging tens of thousands of transcripts through the concatamerization and sequencing of gene tags. It offers the advantage of quantifying gene expression of thousands of genes without hybridization probes and is an alternative to DNA microarrays although the exact advantages and limitations of the two techniques for complex genomes is still to be determined. (Velculescu et al. 1997) analyzed 60,633 tags representing 4,665 yeast genes with expression levels varying from an average of 0.3 to more than 200 copies per yeast cell. One impressive feature of their SAGE results is the finding of genes that had not been predicted from previous analyses of the complete yeast genome sequence.
Although SAGE can quantitate the abundance of individual transcripts without prior information on the genome under study, its full utilization depends on knowledge of mRNA sequences (the 3' end in this case) and the association of each tag with a known gene (the eventual goal). Similarly, DNA microarrays depend on knowledge of at least partial gene sequences such can be obtained through EST programs.
The National Center for Biotechnology Information’s (GenBank) dbEST database contains (11-26-98) almost 2 million ESTs (http://www.ncbi.nlm.nih.gov/dbEST/dbEST_summary.html). Over half are human, with about 470,000 mouse + rat, 72,000 Caenorhabditis, 55,000 Drosophila, and lesser numbers for other organisms. Among plants, Arabidopsis has the most ESTs deposited with NCBI, at 37,000, and rice second at 35,000. After these two the numbers decline significantly: 2,700 for maize, 2,000 for loblolly pine, 1,400 for oilseed rape, 1,300 for upland cotton, and 1,034 for the common ice plant. Wheat and its relatives in the Triticeae tribe are pathetically low on the list for such an important crop group, with only 76 ESTs listed for barley and wheat combined.
Examples of private sector plant EST programs include the corn EST program at Pioneer Hi-Bred (Wang and Bowen 1998) which has reported 125,000 sequences clustered into approximately 54,000 unique sequences, although an unknown percentage of these are likely to be multiple unconnected contigs (an update given Susan Martino-Catt at the ITMI Workshop at the 1999 Plant and Animal Genome VII Conference puts the current figures at approximatley 350,000 ESTs and 59,000 unique sequences). DuPont (Rafalski et al. 1998) similarly has EST programs and has described using soybean ESTs to profile soybean seed development. The private programs have generally not been accessible to public researchers, or accessible only with proprietary restrictions. However, no matter what plans are pursued by private or other international entities, it remains critical that there are public EST databases available as a fundamental resource to U.S. public researchers.
Recently several larger public plant EST projects have been initiated in the U.S. The crops of these projects include tomato, cotton, maize, alfalfa, sorghum, soybeans, but not wheat or other Triticeae (http://www.nsf.gov/search97cgi/vtopic; search on plant genome awards.)
These sequences are being used by Albany staff (Dr. Gerard Lazo) to test methods of automating sequence analysis and data formatting for entry into the GrainGenes database or other relevant database (detailed more below) - see Table 1 for a test batch of 684 sequences, and http://wheat.pw.usda.gov/wEST for updates. Testing of automated sequence processing on the additional endosperm cDNAs will commence shortly.
The generation of wheat endosperm ESTs will continue at Albany and serve as both a test case for general wheat EST production and as a significant EST resource for this practically important tissue. The immediate plan is to complete 3000 random cDNAs, then proceed on a series of screenings (normalization/subtractions) to reduce redundant sequences. This screening will give the Albany personnel direct experience in several normalization procedures (described in detail below). The future plan is to sequence at least 5000 more endosperm cDNAs after normalization procedures. Thus, this current proposal assumes a basic wheat endosperm EST resource will be available through the ongoing Albany projects, and this proposal will concentrate on the other wheat tissues and conditions, although wheat endosperm subjected to specific conditions, such as heat stress, will still be included in new EST production.
The group of investigators on this project has a long and fruitful history of close collaboration. Virtually all participants on this project are members of the International Triticeae Mapping Initiative (ITMI). ITMI was founded in 1989 by the core-group of investigators on this project with the specific goal to develop genetic maps of wheat and its relatives. Founding of this international organization, which has been managed from the University of California since its conception, was a response to the realization that the development of detailed comparative genetic maps for wheat and its relatives required close coordination, collaboration, and sharing of resources and results. The success of ITMI is evident from the fact that after eight years of ITMI activity, wheat and related species now rank among the best-mapped plant species. The steady progress made by ITMI is clearly evident from the voluminous progress reports prepared annually by the coordinators of individual homoeologous groups in the tribe (McGuire and Qualset 1997). This exemplary track record in collaborative work provides the best guarantee for successful accomplishment of tasks placed in front of this group in this project. The existence of this formal, well established collaborative organization will greatly facilitate rapid dissemination of the results of this project in the ITMI workshops that are held annually in different countries.
The wheat EST project proposed here has galvanized complementary efforts in other countries participating in ITMI as well as preliminary efforts in the US. In the summer of 1998, ITMI fostered foundation of the International Triticeae EST Cooperative (ITEC) to initiate collaborative studies on gene function in wheat and the other members of the tribe Triticeae (see Wheat EST sub-section in the section below). The ITEC effort illustrates the role ITMI plays in fostering development of international links. There is little doubt that this grant will stimulate similar investments in other countries as indicated by attached letters from our collaborators in Australia and U.K. which will greatly amplify this country’s investment.
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Prolamine Storage Proteins: 94 Alpha/Beta-gliadins Gamma-gliadins LMW glutenins HMW glutenins Other (avenin, hordein, secalin) Non-Prolamine Storage Proteins: 30 Globulin, CMx, CM1, CM3, CM16 Starch associated: 15 UDP-glucose pyrophosphorylase, starch branching enzyme I, II alpha-amylase Puroindolines, Grain softness: 20 GSP-1a, GSP-1b Ribosomal Sequences: 30 Ribosomal Proteins: 34 Histones: 18 H2A, H2B, H3, H4 Tubulins: 10 alpha-, beta- Elongation Factors: 16 EF-1 alpha, EF-1 beta |
viral, repeats: 27 Vector: 6 Initiation Factors: 5 G-Proteins, Kinases: 14 Environmentally-induced: 29 Heat shock protein 70,82,90; low temperature salt-stress, defense Thionins: 6 alpha-1 alpha-2 purothionin type V Retrotransposons, Unknown Genomic: 79 Membrane Transport: 13 Miscellaneous Remaining: 211 Ubiquitin extensin-like protein invertase actin |
victorin binding protein S-adenosylmethionine synthetase S-adentlmet. decarboxylase glyceraldehyde-3-phosphate dehydrogenase, ribulose-1,5-bisphosphate carboxylase chlorophyll a/b binding acyl-CoA synthetase disulfide isomerase betaine aldehyde dehydrogenase alanine aminotransferase, glycine decarboxylase cysteine proteinase tryptophan synthase peptidylprolyl cis-trans isomerase glyoxysomal malate dehydrogenase phenylalanine ammonia-lyase 3-hydroxy-3-methylglutaryl coenzyme A reductase glutathione reductase glutathione S-transferase lipoxygenase others... |
Objective 2. Sequence a sufficient number of Triticeae clones to obtain 10,000 or more nonduplicated ESTs (singletons).
Premise: Normalization of cDNA clones will increase the efficiency of identification of unique clones by sequencing so that the targeted number of singletons can be achieved.
Objective 3. Hybridize singleton ESTs with a panel of DNAs of T. aestivum deletions to produce a high density EST map of T. aestivum.
Premises: The use of true-breeding deletion stocks and a collaborative approach will facilitate mapping of virtually all wheat loci homologous to each EST, thus beginning the process of physical mapping of Triticeae chromosomes. Comparison of nucleotide sequences of wheat ESTs with the mapped rice and maize ESTs, augmented by mapping of those heterologous ESTs that will not be detected in wheat, will allow construction of comparative EST maps of the wheat genomes and thus provide a framework for comparative functional genomics among grasses.
No single strategy for library selection and sequencing has been adopted. Höfte et al. (1993) utilized a set of libraries each constructed from different tissues, while Newman et al. (1994) constructed a single library from pooled mRNA samples from a number of different tissues. The latter strategy was intended to help reduce redundant sequencing of abundant cDNAs - by diluting the abundance of any cDNA specific to one or a few tissues. After discussion among Triticeae researchers and other ongoing plant EST projects we have decided on the multiple library approach. Libraries will be mainly from wheat, plus from closely related Triticeae with known potentials for trait transfer to wheat. Discussion among a number of U.S. wheat laboratories concluded library construction would best be accomplished at one site to better monitor library quality. Timothy Close (UC Riverside) was asked to take the lead in library construction because of his experience.
Based on ongoing and planned public and private plant EST projects, it is estimated that a comprehensive wheat EST program would require at least 30-50 different libraries from different tissues, developmental stages, and growth conditions. It is our intention to establish a set of at least 30 libraries from different tissues and conditions, with special emphasis on five areas: grain, floral/reproductive tissues, apex, roots, leaves and stems. These libraries will be made available to other sites for sequencing as part of an international Triticeae EST collaboration (ITEC; described above).
Acquisition of Existing cDNA Libraries: Existing libraries will be used if they match the project’s needs for appropriate source and quality. Examples of available cDNA libraries thus far identified and committed are listed below. Additional verbal, email, and letter offers of libraries and RNA preparations are being coordinated by the office of Calvin Qualset (University of California, Davis).
Acquisition of RNA for New cDNA libraries: New cDNA libraries will be produced from RNA from selected plants and regimes. Examples of commitments to provide RNA include:
Construction of cDNA Libraries: As with several aspects of this proposal we have attempted to provide backup capability in case unforeseen problems occur or a specific aspect requires more capacitiy/capability than initially planned. For example, libraries will be constructed in the laboratory of Timothy Close at the University of California, Riverside, with backup construction to be provided, if necessary, at Texas Tech (Henry Nguyen). Total RNA will mainly be prepared in collaborating laboratories although in specific cases (to be determined) RNA may be prepared in the laboratories of the PIs Olin Anderson, Tim Close, and Henry Nguyen. The integrity of each RNA sample will be assessed by formaldehyde-agarose gel electrophoresis upon receipt. Investigators who provide sub-standard RNA samples will be advised on RNA extraction procedures and asked to send new samples.
PolyA RNA will be purified from total RNA using the Promega PolyATract System IV, which utilizes a biotinylated oligo dT probe and streptavidin-conjugated paramagnetic particles for separation of polyA RNA from other RNA. Synthesis of cDNA and production of directional primary cDNA libraries will be achieved using a Stratagene Uni-ZAP XR library construction kit containing XhoI and EcoRI digested lambda Uni-ZAP II. The directionality provides an advantage later in the choice of sequencing primers, when the N-terminal end of the protein-coding region of each cDNA will be desired. Another advantage of the Uni-ZAP vector is that it contains the pBluescript phagemid, which can be excised in vivo using a helper phage.
Both the amplified lambda lysates and amplified phagemid libraries will be stored in 7% DMSO at -80oC in aliquots for distribution and future use. Another portion of each unamplified lambda ZAP library will be used to produce an amplified population of phagemids by excision of phagemid DNA from the lambda ZAP vector.
Testing library quality: Quality will be determined by the average insert size of the library, an estimation of the percent full-length clones, the representation of rRNA clones, and monitoring of the percent of singletons during sequencing. Newman et al. (1994) checked the quality of a library by using the sequences of multiple isolates of two example cDNAs - 7 of 12 catalase and 12 of 15 Chl a binding protein isolates included the initiation codon. We will select similar sequence examples as one of our quality controls, and plan on test sequencing 100 clones from each selected library before continuing more extensive sequencing.
A fundamental problem during EST projects is the occurrence of redundant sequences. This occurs because mRNA titers, and their derived cDNA clones, vary in cellular abundance over several orders of magnitude. The range of expression may be as high as 200,000 mRNA molecules per cell or as low as <1 per cell (on the average), and with perhaps 30% of the genes expressing at levels of less than 10 mRNA molecules per cell at any given time (Bishop et al. 1974; Galau et al. 1977). This can mean that several million clones are needed to have a reasonable chance of finding any specific low-abundance transcript. In large-scale cDNA sequencing for these low-abundance classes, strategies are needed to normalize the cDNA populations. Since our goal is to generate as many unique wheat ESTs as possible, some form of normalization is required although even normalization cannot completely remove members of gene families (Hillier et al. 1996).
Colonies will be picked and arrayed into microtiter plates. The ARS Albany site is planning to purchase a Genetix Q-Bot arraying robot which has the capability of picking colonies and plaques, arraying them into either 96- or 384-well microtiter plates, rearraying selected wells, and DNA micro-arraying (newly released accessory head). Backup arraying is expected to be available at Texas Tech University (H. Nguyen), and several other sites have offered assistance.
There is, as yet, no single optimal strategy to maximize the relative abundance of different sequences for EST production. Different strategies each have advantages and disadvantages which also depend on the scope and purpose of the EST project. A search of the literature and communications with researchers in large-scale EST projects leads us to three approaches that appeal to our predilections and anticipated needs of the wheat research community.
Screening with abundant sequences: These can either be total cDNA probes from mRNA of the same tissue as the library or with pools of common-sequence clones. Screening out the 50-100 most common sequences is the protocol settled on by Pioneer Hi-Bred’s maize EST program after testing various hybridization based normalization procedures (Dr. Tim Helentjaris, NAS Plant Genome Colloquium, Irvine, 1997; personnel communication).
Reassociation: The methods of Soares (Soares et al. 1994; Bonaldo et al. 1996) use several variations of reassociation of single-stranded plasmid/phagemid preparations and synthesized insert DNAs primed off the same clones. This is the favored procedure of DuPont’s (Delaware) plant EST program (Dr. Guo-Hua Miao, personnel communication), and the main procedure proposed for the new U.S. soybean EST project (Vodkin et al. 1998; Shoemaker 1998).
Hybridization to total genomic DNA: Kopezynski et al. (1998) used single-stranded biotin-dUTP labeled (ENZO Biochem) genomic DNA bound to streptavidin-coated magnetic beads (Dynal) to select first-strand cDNA according to relative genome representation. Upon elution, conversion to double-stranded cDNA, and cloning, libraries enriched for rarer mRNA sequences are generated. An added feature of the procedure is the use of a competitor RNA during hybridization to the bead-bound genomic DNA. In their experiment, cytosolic mRNA competitor resulted in a 5-fold enrichment of membrane and secreted proteins (whose mRNAs occur mainly on ER-bound ribosomes). The procedure does over represent transcripts from related large families, but it requires no optimization of hybridization times or hydroxylapatite conditions as does the Soares et al. (1994) procedure.
Our intention is to immediately begin testing these normalization procedures at Albany, CA, as part of an ongoing wheat endosperm EST sequencing project (O. Anderson) described in Preliminary Results. The initial evaluation of this testing is anticipated to be completed by Summer 1999.
The sequencing reaction mixture is prepared from a standard Fluorescent Dye Terminator kit provided by Beckman that is specific to the CEQ2000 8-channel capillary electrophoresis autosequencer, or from a master mix provided by Perkin Elmer/Applied Biosystems for use with the ABI 310 and ABI 3700 capillary autosequencers. The processes and results are equivalent with only the total time to complete the process varying. With either chemistry, the reactions can be prepared with 50% of the recommended reagents. Backup/supplementary sequencing has been arranged with staff at Texas Tech University with several additional CEQ2000 sequencers (H. Nguyen).
There is no fixed criterion for how many sequencing reactions should be preformed on any single cDNA library before moving on to other libraries - the specifics depend on goals, resources, quality of libraries, and ongoing sequencing results. DuPont’s criterion for continuing sequencing a specific library is generally 40% new genes per sequencing session, or 20% if a deep hunt is executed (Dr. Guo-Hua Miao, personnel communication). Pioneer Hi-Bred (Dr. Tim Helentjaris; NAS Colloquium, 1997 Irvine; personnel communication ) sequences 600 clones from a library, then assesses if the library is of sufficient quality. If yes, then they proceed to sequence 3000-6000 clones from the library. Our initial strategy in this proposal will be to sequence approximately 3000 clones in each of 25-30 normalized libraries, although this plan may change as sequencing progresses. Each clone will be 5' sequenced. Each putative singleton will also be 3' sequenced to ascertain that a unique gene motif was discovered. We initially will consider >80% homology in the 3' coding region as an arbitrary criterion for declaring two different 5' ESTs as representing the same singleton.
Contamination of the cDNAs could occur either by experimenter error or through inadvertent inclusion of cells of other eukaryotes associated with non-sterile wheat tissues (as has been reported in other projects). These potential library contaminations will become apparent during analyses of BLAST scores.
Single-pass sequencing inevitably includes errors. While this could potentially lead to problems in homology analyses, States (1992) has indicated that these errors do not significantly effect the reliability of BLAST searches.
The following protocol will be employed to ensure high quality standards in the EST mapping. Each singleton targeted for mapping will be amplified and unincorporated nucleotides will be removed by Wizard Purification Kits (Promega) and gel-sized in the Albany (O. Anderson) site. The 5' end of each insert will be resequenced to determine that the correct insert was PCR generated. An aliquot of the insert will be send to the one of the nine mapping laboratories (J. Anderson, J. Dubcovsky, J. Dvorak, B.S. Gill, K.S. Gill, P. Gustafson, S. Kianian, N. Lapitan, M. Sorrells). Probes will be prepared by the random priming method and hybridized with the four membranes. The phosphorimager files or electronic files of autoradiograms will be forwarded to UC Davis/ARS (Albany, CA) and the sizes of the fragments and their relative intensities will be computed using the FPC computer program (Soderlund et al. 1997) and the position of an EST singleton on the deletion map will be determined on the basis of lost bands. Since a large number of mapping labs are involved, initially 20% of EST singletons will be mapped in two different labs to ensure detection of potential problems. This duplication will be reduced once confidence in results are demonstrated. The sizes of restriction DNA fragments characterizing each clone and those associated with a specific deletion will be deposited in a database such as Xcel for cross-referencing and in GrainGenes. If a singleton shares fragment sizes and map positions with another mapped singleton in the database, the history of the clone will be reexamined for potential errors.
Space limitations prevents a detailed description of how each laboratory intends using the arrays, but a few examples are instructive. To investigate ESTs involved in the regulation of meiosis in the presence of the Ph1 locus, genes differentially expressed during a time-course involving premeiotic stages and onset of meiosis in anthers of Ph1 and Ph1-deficient nearly isogenic wheat deletion stocks will be investigated (B.S. Gill and J. Dvorak). ESTs involved in anther development and high pollen load will be investigated and compared to variations occurring in wheat (P. Gustafson and S. Kianian). Developmental time courses and responses to known relevant stimuli will be investigated for seed development (O. Anderson, H. Nguyen, M.-K. Walker-Simmons).
Hybridized microarrays will be analyzed either at the experimental site or sent to another project laboratory for analysis. Currently at least four sites (Albany, Cornell, Davis, and TexasTech) either already have, or are planning to purchase readers. The scanner data will be analyzed with GeneSpring or similar software. Data will be returned to the authors who will query them for two-fold or greater differences in the relative representation of a specific cDNA in the pair of probes. The patterns of the expression of EST during a developmental or induction time-course will be compiled annotated and stored in a database (see Bioinformatics section). Initially a selection of array experiments will be read at at least two sites to judge any variability between laboratories and to further ensure quality control.
Individual laboratories will carry out other functional assays (such as SAGE) as pertinent to their individual research objectives. As with microarrays, contact with other laboratories will be emphasized and contact with the bioinformatics staff will be required. Array construction and functional studies will not wait for the complete of ESTs to be generated. Smaller arrays, likely representing single tissues such as the endosperm, will be used as soon as possible both to analyze those tissues and to test the overall array construction, use, and analysis of results.
The five aspects of wheat reproduction which will be focused on are listed along with the coPIs to work on the functional genomics of that aspect. By different laboratories focusing on specific problems, the total result is expected to be bigger picture of total reproductive phase gene expression. A specific investigator may have a narrow interest in a specific tissue, but the total result from this collaborative project will be a picture of large numbers of ESTs in multiple tissues and conditions.
The submission of sequences for database searches have utilized the BLAST series of programs (Altschul et al. 1990). Pilot studies (G. Lazo) previously submitted sequences via e-mail using perl scripts (BLASTmailnr, BLASTmailest; in-house, G. Lazo) to the National Center for Biotechnology Information (NCBI) server which houses current sequence databases. Sequences will be searched using primarily BLASTN for nucleic acid homology, and BLASTX for peptide homology searches. PAM120 scores of >80 were considered to have potentially significant homology (Newman et al., 1994). The nr database contains all non-redundant GenBank, EMBL, DDBJ, and PDB sequences (but no EST, STS, GSS, or HTGS sequences) and contains 2,837,897 sequences comprising 2,008,761,784 bases (release 109.0, Oct. 1998). The dbEST database contains a collection of non-redundant GenBank, EMBL, and DDBJ EST classified sequences with 1,868,590 sequences and 707,570,380 bases. We will continue to utilize the service at NCBI, but are doing additional searches locally for comparisons of the Triticeae EST sequences. Likewise, as EST sequence data is generated by the project, the sequences will be submitted to GenBank using the NCBI Sequin v.2.70 (NCBI, 1998) program. Local Triticeae EST searches will help classify the cDNA populations generated by the project. A perl script, cleansearch (in-house, G. Lazo), will submit "cleaned" cDNA data to a locally housed Triticeae database and perform BLASTN and BLASTX homology searches (the utility of including other searches using other algorithms will be evaluated). This will show clustering within the sequenced populations (by plant, tissue, and condition). There are other programs that work with the phred program as a package (i.e. phrap, cross_match, consed). These programs are mainly used for sequence assembly. Another similar assembly program, TIGR_Assembler (Sutton et al., 1995), is also being evaluated for use. Each sequence will be searched against nucleic acid databases to identify gene classes using basic local alignment search tool programs. The tracking of local sequences will allow for the identification of gene families, over-abundant, and unique sequences. Identifying clusters of sequences will help in establishing library normalization.
The GrainGenes project currently uses the ACEDB (Thierry-Mieg and Durbin 1992; Dunham et al. 1994) program to display BLAST results. A perl script, blast2ace (in-house, G. Lazo), takes the raw BLASTN or BLASTX output and writes files for the ACEDB environment. Output files are then loaded into the GrainGenes database and linked to relevant data classes. In addition, the BLAST hits are annotated to reflect genome origin (color-coded), and by the raw scores and probability values and presented in a graphic display (http://wheat.pw.usda.gov/wEST/). The original trace file data may be viewed with the consed package (Gordon et al. 1998) or linked with ACEDB using the Acembly program (Thierry-Mieg and Thierry-Mieg 1998). We will also evaluate whether further processing should be conducted with other gene identification programs (HMM, PSI-BLAST, FASTA-ortholog clustering).
EST homologies analyses are, by nature, temporary. As more sequences are deposited in public databases, and as the function of genes become more defined, the result of a homology search for a specific EST will change. For this reason periodic database screens must be carried out and information updated. The current plan is to re-analyze all EST data for updates to GrainGenes quarterly, although more frequent updates may be instituted as needed.
Mapping data will be linked into the GrainGenes database by present procedures. It is anticipated that new map displays will be needed, and this will be a priority for ARS bioinformatics staff associated with GrainGenes and comparative genomics projects.
The recording, analysis, and linking of microarray data presents a new challenge, and we do not believe there is any consensus on the best approaches. Our intention is to initially use existing software and database resources, but be alert to what are expected to be rapid changes and improvements. For example, a number of software packages are now becoming availalable to measure such data (Eisen et al. 1998) (ImageQuant v.5.0/FluorSep v.2.0, Molecular Dynamics; ImaGene, BioDiscovery Inc.; SpotfirePro, Spotfire Inc.). Software such as ScanAlyze 1.5, Cluster, and TreeView (Eisen et al. 1998) can be used to sort, analyze, and visualize microarray data. Such data is usually comprised of a sequence identification (ID), sequence identity (if resolved from BLAST etc.), and fluorometric/radiometric intensity readings from a variety of experimental hybridizations. The trends exemplified over the tested conditions may be clustered, possibly grouping sequences associated with like function.
The ACEDB program currently used for displaying Triticeae-associated information be adapted for the display of microarray data. The C. elegans ACEDB contains arrayed hybridization data, and might be adapted to display new data types such as color tables associated with assigned fluoresence intensities of array hybridizations. Each data point in the array is hyperlinked linked to other associated information for a given clone, or probe. The display is primitive at this time, but may be able to incorporate newer displays. If not adaptable, then other programs and display tools will be used. As new tools become available, different ways of analyzing the data will be assessed. Eventually there will be extensive use of processed data displays to aid the researcher in mining the enormous amounts of data to be generated. Examples from recent reports include rearranging microarray results according to chromosome position (Winzeler and Davis 1997), grouping into categories based on knowledge of likely roles (Iyer et al. 1999), or grouping by time course of developmental or physiological induction (Chu et al. 1998). Exact determination of variation in expression of each two-color dot (array point) is another challenging task, but tools are in development; i.e., the Fourier transform method to assess periodicity and correlation measurements to determine if a gene is periodically regulated (Sherlock et al., 1999).
The ACEDB database system has both significant strengths and weaknesses. As a vertical application designed specifically for genome research, ACEDB has had the richest set of graphical interfaces available for visualizing and interacting with the genomic data, especially sequence data, although the display capabilities are becoming dated. However, it has still proven robust enough to support much larger projects than the one proposed here; i.e., entire physical map and sequence of the C. elegans genome. However, the web accessible version of the database is too limited and the querying language, while extremely powerful, has proven too obtuse for many users. Addressing these weakness is a major focus of ARS staff at Cornell and Albany. GrainGenes will also be joining its sister databases at Cornell in developing a parallel version of the database in a relational database management system (RDBMS) such as Oracle. The possibility of a hybrid (ACEDB/RDBMS) system is not excluded. For the RDBMS approach, all graphical interfaces will be written in Java with WWW as the target delivery mode, and designed to be independent of the underlying database management system. Communication with the database will be via middleware such as CORBA (Dicks et al. 1999), or Java DX which combines database access flexibility with powerful built-in visualization tools.
Adams, M. D., M. Dubnick, A. R. Kerlavage, R. Moreno, J. M. Kelley, T. R. Utterback, J. W. Nagle, C. Fields and J. C. Venter, 1992 Sequence identification of 2375 human brain genes. Nature 355:632-634.
Adams, M. D., J. M. Kelley, J. D. Gocayne, M. Dubnick, M. H. Polymeropoulos, H. Xiao, C. R. Merril, A. Wu, B. Olde, R. F. Moreno et al., 1991b Complementary DNA sequencing: Expressed sequence tags and human genome project. Science 252:1651-1656.
Adams, M. D., J. M. Kelley, J. D. Gocayne, M. Dubnick, M. H. Polymeropoulos, H. Xiao, C. R. Merril, A. Wu, B. Olde, R. F. Moreno et al., 1991a Complementary DNA sequencing: Expressed sequence tags and human genome project. Science 252:1651-1656.
Ahn, S. N., J. A. Anderson, M. E. Sorrels and S. D. Tanksley, 1993 Homoeologous relationships of rice, wheat and maize chromosomes. Mol. Gen. Genet. 241:483-490.
Ahn, S. N., and S. D. Tanksley, 1993 Comparative linkage maps of the rice and maize genomes. Proc. Natl. Acad. Sci. USA 90:7980-7984.
Ajioka, J. W., J. C. Boothroyd, B. P. Brunk, A. Hehl, L. Hillier, I. D. Manger, M. Marra, G. C. Overton, D. S. Roos, W. K.L. et al., 1998 Gene discovery by EST sequencing in Toxoplasma gondii reveals sequences restricted to the Apicomplexa. Genome Res. 8:18-28.
Altschul, S. F., W. Gish, W. Miller, E. W. Myers and D. J. Lipman, 1990 Basic logical aligment search tool. J. Mol. Biol. 215:403-410.
Anderson, J. A., M. E. Sorrells and S. D. Tanksley, 1993 RFLP analysis of genomic regions associated with resistance to preharvest sprouting in wheat. Crop Sci. 33:453-459.
Anderson, O. D., F. C. Greene, R. E. Yip, N. G. Halford, P. R. Shewry and J.-M. Malpica-Romero, 1989 Nucleotide sequences of the two high-molecular-weight glutenin genes from the D genome of hexaploid wheat, Triticum aestivum L. cv. Cheyenne. Nucleic Acid Research 17:461-462.
Aragón-Alcaide, L., S. Reader, T. Miller and G. Moore, 1997 Centromeric behaviour in wheat with high and low homoeologous chromosomal pairing. Chromosoma 106:327-33.
Benson, D. A., M. S. Boguski, D. J. Lipman, J. Ostell and B. F. Ouellette, 1998 GenBank. Nucleic Acids Res. 26:1-7.
Bernacchi, D., and S. D. Tanksley, 1997 An interspecific backcross of Lycopersicon esculentum x L. hirsutum: linkage analysis and a QTL study of sexual compatibility factors and floral traits. Genetics 147:861-77.
Bevan, M., I. Bancroft, E. Bent, K. Love, H. Goodman, C. Dean, R. Bergkamp, W. Dirkse, M. Van Staveren, W. Stiekema et al., 1998 Analysis of 1.9 Mb of contiguous sequence from chromosome 4 of Arabidopsis thaliana. Nature 391:485-8.
Bishop, J. O., J. G. Morton, M. Rosebach and M. Richardson, 1974 Three abundance classes in HeLa-cell messenger-RNA. Nature 250:199-204.
Bonaldo, M. F., G. Lennon and M. B. Soares, 1996 Normalization and subtraction: two approaches to facilitate gene discovery. Genome Res. 6:791-806.
Busch, R. H., and S. S. Maan, 1978 Effects of alien cytoplasms on agronomic and bread making traits of two spring wheat cultivars. Crop Sci. 18:864-866.
Cassidy, B. G., and J. Dvorak, 1991 Molecular characterization of a low-molecular-weight glutenin cDNA clone from Triticum durum. Theor. Appl. Genet. 81:653-660.
Cassidy, B. G., J. Dvorak and O. D. Anderson, 1998 The wheat low-molecular-weight glutenin genes: characterization of six new genes and progress in understanding gene family structure. Theor. Appl. Genet. 96:743-750.
Chao, S., P. J. Sharp, A. J. Worland, E. J. Warham, R. M. D. Koebner and M. D. Gale, 1989 RFLP-based genetic maps of wheat homoeologous group 7 chromosomes. Theor. Appl. Genet. 78:495-504.
Chee, M., R. Yang, E. Hubbell, A. Berno, X. C. Huang, D. Stern, J. Winkler, D. J. Bockhart, M. S.Morris and S. P. A. Fodor, 1996 Accessing genetic information with high-density DNA arrays. Science 274:610-614.
Chen, K. C., and J. Dvorak, 1984 The inheritance of genetic variation in Triticum speltoides affecting heterogenetic chromosome pairing in hybrids with Triticum aestivum. Can. J. Genet. Cytol 26:279-287.
Cho, R. J., M. J. Campbell, E. A. Winzeler, L. Steinmetz, A. Conway, L. Wodicka, T. G. Wolfsberg, A. E. Gabrielian, D. Landsman, D. J. Lockhart et al., 1998 A genome-wide transcriptional analysis of the mitotic cell cycle. Mol. Cell 2:65-73.
Chou, H.-H., 1998 Lucy, pp. . Proceedings of the Tenth Annual Genome Sequencing and Annotation Conference (GSAC X), Miami, FL, September 1998.
Chouard, P., 1960 Vernalization and its relation to dormancy. Ann. Rev. Plant Physiol. 11:191-238.
Chu, S., J. DeRisi, M. Eisen, J. Mulholland, D. Botstein, P. O. Brown and I. Herskowitz, 1998 The transcriptional program of sporulation in budding yeast. Science 282:699-705.
Clegg, M. T., B. S. Gaut, G. H. Learn, Jr. and B. R. Morton, 1994 Rates and patterns of chloroplast DNA evolution. Proc. Natl. Acad. Sci. USA 91:6795-801.
Coe, E. H., M. G. Neuffer and D. A. Hoisington, 1988 The genetics of corn, pp. in Corn and Corn Improvement, edited by G. F. Sprague, and J. W. Dudley. American Society of Agronomy, Madison, WI.
Cooke, R., M. Raynal, M. Laudie, F. Grellet, M. Delseny, P. C. Morris, D. Guerrier, J. Giraudet, F. Quigley, G. Clabault et al., 1996 Further progress towards a catalogue of all Arabidopsis genes:analysis of a set of 5000 non-redundant ESTs. Plant J. 9:101-124.
Curtis, C. A., and A. J. Lukaszewski, 1991 Metaphase I pairing of deficient chromosomes and genetic mapping of deficient breakpoints in common wheat. Genome 34:553-560.
Dear, S., and R. Staden, 1992 A standard file format for data from DNA sequencing instruments. DNA Sequence 3:107-110.
Delaney, D. E., S. Nasuda, T. R. Endo, B. S. Gill and S. H. Hulbert, 1995a Cytologically based physical maps of the group-2 chromosomes of wheat. Theor. Appl. Genet. 91:568-573.
Delaney, D. E., S. Nasuda, T. R. Endo, B. S. Gill and S. H. Hulbert, 1995b Cytologically based physical maps of the group 3 chromosomes of wheat. Theor. Appl. Genet. 91:780-782.
DePauw, R. M., and T. N. McCraig, 1983 Recombining dormancy and white seed color in a spring wheat cross. Can. J. Plant Sci. 63:581-589.
DeRisi, J. L., V. R. Iyer and P. O. Brown, 1997 Exploring the metabolic and genetic control of gene expression on a genomic scale. Science 278:680-686.
Desprez, T., J. Amselem, M. Caboche and H. Höfte, 1998 Differential gene expression in Arabidopsis monitored using cDNA arrays. The Plant J. 14:643-652.
Devos, K. M., M. D. Atkinson, C. N. Chinoy, H. A. Francis, R. L. Harcourt, R. M. D. Koebner, C. J. Liu, P. Masoje, D. X. Xie and M. D. Gale, 1993a Chromosomal rearrangements in the rye genome relative to that of wheat. Theor. Appl. Genet. 85:673-680.
Devos, K. M., M. D. Atkinson, C. N. Chinoy, C. Liu and M. D. Gale, 1992 RFLP based genetic maps of the homoeologous group 3 chromosomes of wheat and rye. Theor. Appl. Genet. 83:931-939.
Devos, K. M., S. Chao, Q. Y. Li, M. C. Simonetti and M. D. Gale, 1994 Relationship between chromosome 9 of maize and wheat homeologous group 7 chromosomes. Genetics 138:1287-1292.
Devos, K. M., J. Dubcovsky, J. Dvorak, C. N. Chinoy and M. D. Gale, 1995a Structural evolution of wheat chromosomes 4A, 5A, and 7B and its impact on recombination. Theor. Appl. Genet. 91:282-288.
Devos, K. M., and M. D. Gale, 1993 Extended genetic maps of the homoeologous group 3 chromosomes of wheat, rye, and barley. Theor. Appl. Genet. 85:649-652.
Devos, K. M., and M. D. Gale, 1997 Comparative genetics in the grasses. Plant Mol. Biol. 35:3-15.
Devos, K. M., T. Milan and M. D. Gale, 1993b Comparative RFLP maps of the homoeologous group-2 chromosomes of wheat, rye, and barley. Theor. Appl. Genet. 85:784-792.
Devos, K. M., G. Moore and M. D. Gale, 1995b Conservation of marker synteny during evolution. Euphytica 85:367-372.
Devos, K. M., Z. M. Wang, J. Beales, Y. Sasaki and M. D. Gale, 1998 Comparative genetic maps of foxtail millet Setaria italica and rice Oryza sativa. Theor. Appl. Genet. 96:63-68.
Dicks, J., M. Anderson, L. Cardle, S. Cartinhour, M. Couchman, J. Dickson, M. Gale, D. Marshall, H. McWilliam, A. O'Malia et al., 1999 UK CropNet and CORBA, pp. p.62. http://www.intl-pag.org/pag/7/abstracts/pg7180.html/. in Plant and Animal Genome VII, San Diego.
Dover, G. A., and R. Riley, 1972 Prevention of pairing of homoeologous meiotic chromosomes of wheat by supernumerary chromosomes of Aegilops. Nature 240:159-161.
Dubcovsky, J., M. Echeide, F. Giancola, M. Rousset, M. C. Luo, L. R. Joppa and J. Dvorak, 1997 Seed storage protein loci and RFLP maps od diploid, tetraploid, and hexaploid wheat. Theor. Appl. Genet. 95:1169-1180.
Dubcovsky, J., D. Lijavetzky, L. Appendino and G. Tranquilli, 1998 Comparative RFLP mapping of Triticum monococcum genes controlling vernalization requirement. Theor. Appl. Genet. 97:968-975.
Dubcovsky, J., M. C. Luo and J. Dvorak, 1995a Linkage relationships among stress-induced genes in wheat. Theor. Appl. Genet. 91:795-801.
Dubcovsky, J., M. C. Luo, G. Y. Zhong, R. Bransteitter, A. Desai, A. Kilian, A. Kleinhofs and J. Dvorak, 1996 Genetic map of diploid wheat, Triticum monococcum L., and its comparison with maps of Hordeum vulgare L. Genetics 143:983-999.
Dubcovsky, J., M.-C. Luo and J. Dvorak, 1995b Differentiation between homoeologous chromosomes 1A of wheat and 1A m of Triticum monococcum and its recognition by the wheat Ph1 locus. Proceedings of National Academy of Sciences 92:6645-6649.
Dunham, I., R. Durbin, J. T. Mieg and D. R. Bentley, 1994 Physical mapping projects and ACEDB., pp. 111-158 in Guide to Human Genome Computing, edited by M. J. Bishop. Academic Press.
Dvorak, J., 1972 Genetic variability in Aegilops speltoides affecting homoeologous piaring in wheat. Can. J. Genet. Cytol. 14:371-380.
Dvorak, J., 1987 Chromosomal distribution of genes in Elytrigia elongata which promote or suppress pairing of wheat homoeologous chromosomes. Genome 29:34-40.
Dvorak, J., and R. Appels, 1986 Investigation of homologous crossing over and sister chromatid exchange in the wheat Nor-2 locus coding for rRNA and Gli-B2 locus coding for gliadins. Genetics 113:1037-1056.
Dvorak, J., and K.-C. Chen, 1984 Distribution of nonstructural variation between wheat cultivars along chromosome arm 6Bp: Evidence from the linkage map and physical map of the arm. Genetics 106:325-333.
Dvorak, J., P. di Terlizzi, H. B. Zhang and P. Resta, 1993 The evolution of polyploid wheats: Identification of the A genome donor species. Genome 36:21-31.
Dvorak, J., M.-C. Luo and Z.-L. Yang, 1998 Restriction fragment length polymorphism and divergence in the genomic regions of high and low recombination in self-fertilizing and cross-fertilizing Aegilops species. Genetics 148:423-434.
Dvorak, J., and H. B. Zhang, 1990 Variation in repeated nucleotide sequences sheds light on the phylogeny of the wheat B and G genomes. Proc. Natl. Acad. Sci. USA 87:9640-9644.
Eisen, M. B., P. T. Spellman, P. O. Brown and D. Botstein, 1998 Cluster analysis and display of genome-wide expression patterns. Proc. Natl. Acad. Sci. USA 95:14863-14868.
Endo, T. R., and B. S. Gill, 1996 The deletion stocks of common wheat. Journal of Heredity 87:295-307.
Ewing, B., and P. Green, 1998 Basecalling of automated sequencer traces using phred. II. Error probabilities. Genome Research 8:186-194.
Ewing, B., L. Hillier, M. Wendl and P. Green, 1998 Basecalling of automated sequencer traces using phred. I. Accuracy assessment. Genome Research 8:175-185.
Feldman, M., 1993 Cytogenetic activity and mode of action of the pairing homoeologous (Ph1) gene of wheat. Crop Sci. 33:894-897.
Feldman, M., and L. Avivi, 1988 Genetic control of bivalent pairing in common wheat: the mode of Ph1 action, pp. 269-279 in Kew Chromosome Conference, edited by P. E. Brandham.
Galau, G. A., W. H. Klein, R. J. Britten and E. H. Davidson, 1977 Significance of rare mRNA sequences in liver. Arch. Biochem. Biophys. 179:584-599.
Galili, G., and M. Feldman, 1984 Mapping of glutenin and gliadin genes located on chromosome 1B of common wheat. Mol. Gen. Genet. 198:293-298.
Gao, L., and W. Bushuk, 1993 Polymeric glutenin of wheat lines with varying number of high molecular weight glutenin subunits. Cereal Chemistry 70:475-480.
Gill, B. S., B. Friebe and T. R. Endo, 1991a Standard karyotype and nomenclature system for description of chromosome bands and structural aberrations in wheat (Triticum aestivum). Genome 34:830-839.
Gill, K. S., B. S. Gill and T. R. Endo, 1993 A chromosome region-specific mapping strategy reveals gene-rich telomeric ends in wheat. Chromosoma 102:374-381.
Gill, K. S., B. S. Gill, T. R. Endo and E. V. Boyko, 1996a Identification and high-density mapping of gene-rich regions in chromosome group 5 of wheat. Genetics 143:1001-1012.
Gill, K. S., B. S. Gill, T. R. Endo and T. Taylor, 1996b Identification and high-density mapping of gene rich regions in chromosome group 1 of wheat. Genetics 144:1883-1891.
Gill, K. S., D. Hassawi, W. J. Raupp, A. K. Fritz, B. S. Gill, T. S. Cox and R. G. Sears, 1992 An updated genetic linkage map of Triticum tauschii, the D-genome progenitor of wheat, pp. 27-29 in Progress in genome mapping of wheat and related species. Proceedings of the 2nd International Triticeae Mapping Initiative, edited by B. S. Gill, W. j. Raupp and H. Corke. Genetic Conservation Program of University of California, Manhattan, Kansas.
Gill, K. S., E. L. Lubbers, B. S. Gill, W. J. Raupp and T. S. Cox, 1991b A genetic linkage map of Triticum tauschii (DD) and its relationship to the D genome of bread wheat. Genome 34:362-374.
Gordon, D., C. Abajian and P. Green, 1998 Consed: A graphical tool for sequence finishing. Genome Research 8:195-202.
Green, P., 1998 swat/cross_match/phrap package, http://bozeman.mbt.washington.edu/phrap.docs/phrap.html.
Gupta, R. B., J. G. Paul, G. B. Cornish, G. A. Palmer, F. Bekes and A. J. Rathjen, 1994 Allelic variation at glutenin subunit and gliadin loci, Glu-1, Glu-3 and Gli-1, of common wheats. 1. Its additive and interaction effects on dough properties. J. Cereal Sci. 19:9-17.
Gupta, R. B., N. K. Singh and K. W. Shepherd, 1989 The cumulative affects of allelic variation in LMW and HMW glutenin subunits on dough properties in the progeny of two bread wheats. Theor. Appl. Genet. 77:57-64.
Halford, N. G., J. M. Field, H. Blair, P. Urwin, K. Moore, L. Robert, R. Thompson, R. B. Flavell, A. S. Tatham and P. R. Shewry, 1992 Analysis of HMW glutenin subunits encoded by chromosome-1A of bread wheat (Triticum aestivum L.) indicates quantitative effects on grain quality. Theor. Appl. Genet. 83:373-378.
Harushima, Y., M. Yano, P. Shomura, M. Sato, T. Shimano, Y. Kuboki, T. Yamamoto, S. Y. Lin, B. A. Antonio, A. Parco et al., 1998 A high-density rice genetic linkage map with 2275 markers using a single F-2 population. Genetics 148:479-494.
Hillier, L. D., G. Lennon, M. Becker, M. F. Banaldo and B. Chiapelli, et. al., 1996 Generation and analysis of 280,000 human expressed sequence tags. Genome Res. 6:807-828.
Höfte, H., T. Desprez and J. Amselem, et al., 1993 An inventory of 1152 expressed sequence tags obtained by partial sequencing of cDNAs from Arabidopsis thaliana. Plant J. 4:1051-1061.
Hohmann, U., T. R. Endo, K. S. Gill and B. S. Gill, 1994 Comparison of genetic and physical maps of group 7 chromosomes from Triticum aestivum L. Mol. Gen. Genet. 245:644-653.
Holt, L. M., R. Astin and P. I. Payne, 1981 Structural and genetic studies on the high-molecular-weight subunits of wheat glutenin. 2. Relative isoelectric points determined by two dimensional fractionation in polyacrylamide gels. Theor. Appl. Genet. 60:237-243.
Höög, C., 1991 Isolation of a large number of novel mammalian genes by a differential screening strategy. Nucl. Acids Res. 19:6123-6127.
Hulbert, S. H., T. E. Richter, J. D. Axtell and J. L. Bennetzen, 1990 Genetic mapping and characterization of sorghum and related crops by means of maize DNA probes. Proc. Natl. Acad. Sci. USA. 87:4251-4255.
Iyer, V. R., M. B. Eisen, D. T. Ross, G. Schuler, T. Moore, J. C. F. Lee, J. M. Trent, L. M. Staudt, J. J. Hudson, M. S. Boguski et al., 1999 The transcriptional program in the response of human fibroblasts to serum. Science 283:83-87.
Jackson, E. A., L. M. Holt and P. I. Payne, 1983 Characterization of high molecular weight gliadin and low-molecular-weight glutenin subunits of wheat endosperm by two-dimensional electrophoresis and the chromosomal localisation of their expressed genes. Theor. Appl. Genet. 66:29-37.
Jampates, R., and J. Dvorak, 1986 Location of the Ph1 locus in the metaphase chromosome map and the linkage map of the 5Bq arm of wheat. Canad. J. Genet. Cytol. 28:511-519.
Jende-Strid, B., 1991 Gene-enzyme relations in the pathway of flavonoid biosynthesis in barley. Theor. Appl. Genet. 81:668-674.
Jia, J., K. M. Devos, S. Chao, T. E. Miller, S. M. Reader and M. D. Gale, 1996 RFLP-based maps of the homoeologous group-6 chromosomes of wheat and their application in the tagging of Pm12, a powdery mildew resistance gene transferred from Aegilops speltoides to wheat. Theor. Appl. Genet. 92:559-565.
Kidwell, M. G., and D. Lisch, 1997 Transposable elements as sources of variation in animals and plants. Proc. Natl. Acad. Sci. USA 94:7704-11.
Kihara, H., 1944 Discovery of the DD-analyser, one of the ancestors of Triticum vulgare (Japanese). Agric. and Hort. (Tokyo) 19:13-14.
Kopezynski, C. C., J. N. Noordermeer, T. L. Serano, W.-Y. Chen, J. D. Pendleton, S. Lewis, C. S. Goodman and G. M. Rubin, 1998 A high throughput screen to identify novel secreted and transmembrane proteins involved in Drosophila embryogenesis. Proc. Natl. Acad. Sci. USA. 95:9973-9978.
Kota, R. S., K. S. Gill, B. S. Gill and T. R. Endo, 1993 A cytogenetically based physical map of chromosome-1B in common wheat. Genome 36:548-554.
Kurata, N., G. Moore, T. Nagamura, T. Foote, Y. Yano, Y. Minobe and M. Gale, 1994a Conservation of genome structure between rice and wheat. Bio/Technology 12:276-278.
Kurata, N., Y. Nagamura, K. Yamamoto, Y. Harushima, N. Sue, J. Wu, B. A. Antonio, A. Shomura, T. Shimizu, S. Y. Lin et al., 1994b A 300 Kilobase Interval Genetic Map of Rice Including 883 Expressed Sequences. Nature Genetics 8:365-372.
Lagudah, E. S., R. Appels and A. D. H. Brown, 1991 The molecular-genetic analysis of Triticum tauschii, the D genome donor to hexaploid wheat. Genome 36:913-918.
Lazo, G. R., L. A. Larka, C. C. Hsia, K. F. McCue, M. E. Sorrells, D. E. Matthews, M. Au, N. A. Federspiel and O. D. Anderson, 1998 Assigning putative gene functions to mapped probe loci in the GrainGenes genome database and sequencing of wheat endosperm cDNAs. Plant and Animal Genome VI Conference. Abstract: http://www.intl-pag.org/pag/6/abstracts/404.html.
Liu, Y.-G., and K. Tsunewaki, 1991 Restriction fragment length polymorphism (RFLP) analysis in wheat. II. Linkage analysis of the RFLP sites in common wheat. Jap. J. Genet. 66:617-633.
Love, A., 1984 Conspectus of the Triticeae. Feddes Repertorium 95:425-521.
Lukaszewski, A. J., and C. A. Curtis, 1993 Physical distribution of recombination in B-genome chromosomes of tetraploid wheat. Theor. Appl. Genet. 84:121-127.
Luo, M. C., J. Dubcovsky and J. Dvorak, 1996 Recognition of homeology by the wheat Ph1 locus. Genetics 143:1195-1203.
Maan, S. S., 1992a A gene for embryo-endosperm compatibility and seed viability in allloplasmic Triticum turgidum. Genome 35:772-779.
Maan, s. s., 1992b The scs and Vi genes correct a syndrome of cytoplasmic effects in alloplasmic durum wheat. Genome 35:780-787.
Marino, C. L., Y. H. Nelson, Y. H. Lu, M. E. Sorrells, P. Leroy, N. A. Tuleen, C. R. Lopes and G. E. Hart, 1996 Molecular genetic maps of the group 6 chromosomes of hexaploid wheat (Triticum aestivum L. emend. Thell.). Genome 39:359-366.
Marshall, A., and J. Hodgson, 1998 DNA chips: An array of possibilities. Nature Biotechnol. 16:27-31.
McCombie, W. R., M. D. Adams, J. M. Kelley, M. G. FitzGerald, T. R. Utterback, M. Khan, M. Dubnick, A. R. Kerlavage, J. C. Venter and C. Fields, 1992 Caenorhabditis elegans expressed sequence tags identify gene families and potential disease gene homologues. Nature Genet. 1:124-131.
McFadden, E. S., and E. R. Sears, 1946 The origin of Triticum spelta and its free-theshing hexaploid relatives. Journal of Heredity 37:81-89, 107-116.
McGuire, P. E.and C. O. Qualset. (1997) Progress in Genome Mapping of wheat and Related Species Genetic Resources Conservation Program, Division of Agriculture and Natural Resources, University of California, Norwich, England and Sydney, Australia.
Mello-Sampayo, T., 1973 Somatic association of telocentric chromosomes carrying homologous centromeres in common wheat. Theor. Appl. Genet. 43:178-181.
Metzger, J. D., 1988 Localization of the site of perception of thermoinductive temperatures in Thalaspi arvense L. Plant Physiol. 88:424-428.
Mickelson-Young, L., T. R. Endo and B. S. Gill, 1995 A cytogenetic ladder-map of the wheat homoeologous group-4 chromosomes. Theor. Appl. Genet. 90:1007-1011.
Moore, G., 1998 To pair or not to pair: chromosome pairing and evolution. Curr. Opin. Plant Biol. 1:116-122.
Moore, G., K. M. Devos, Z. Wang and M. D. Gale, 1995 Cereal genome evolution - grasses, line up and form a circle. Curr. Biol. 5:737-739.
Nahm, B. H., S. H. Jeong, W. S. Kim, J.-K. Kim, S. J. Suk, M. C. Lee, Y. M. Park, K. Y. Kang, S. I. Kim and M. Y. Eun, 1998 Random sequencing analysis of rice immature seed ESTs from normal and subtracted libraries. Plant and Animal Genome VI Conference. Abstract: http://www.intl-pag.org/pag/6/abstrcts/168.html.
Nelson, J. C., M. E. Sorrells, A. E. Van Deynze, Y. H. Lu, M. Atkinson, M. Bernard, P. Leroy, J. D. Faris and J. A. Anderson, 1995a Molecular mapping of wheat. Major genes and rearrangements in homoeologous groups 4, 5, and 7. Genetics 141:721-731.
Nelson, J. C., A. E. VanDeynze, E. Autrique, M. E. Sorrells, Y. H. Lu, M. Merlino, M. Atkinson and P. Leroy, 1995b Molecular mapping of wheat. Homoeologus group 2. Genome 38:525-533.
Newman, T., F. J. de Bruijn, P. Green, K. Keegstra, H. Kende, L. McIntosh, J. Ohlrogge, N. Raikhel, S. Somerville, M. Thomashow et al., 1994 Genes galore: a summary of the methods for accessing the results of large scale partial sequencing of anonymous Arabidopsis thaliana cDNA clones. Plant Physiol. 106:1241-1255.
Nishikawa, K., 1983 Species relationship of wheat and its putative ancestors as viewed from isozyme variation, pp. 59-63 in Proc. 6th Int. Wheat Genet. Symp., Kyoto.
Noda, K., and D. J. Mares, 1995 Preharvest sprouting in cereal 1995, pp. in Center for Academic Societies Japan, Osaka.
Palmer, J. D., 1990 Contrasting modes and tempos of genome evolution in land plant organelles. Trends in Genet. 6:115-120.
Payne, P. I., 1987 Genetics of wheat storage proteins and the effect of allelic variation on bread-making quality. Ann. Rev. Pl. Physiol. 38:141-153.
Payne, P. I., K. G. Corfield, L. M. Holt and J. A. Blackman, 1981 Correlation between the inheritance of certain high-molecular weight subunits of glutenin and bread-making quality in progenies of six crosses of bread wheat. J. Sci. Food. Agric. 32:51-60.
Payne, P. I., J. A. Seeking, A. J. Worland, M. G. Jarvis and L. M. Holt, 1987 Allelic variation of glutenin subunits and gliadins and its effect on breadmaking quality in wheat: Analysis of F5 progeny from Chinese Spring x Chinese Spring (Hope 1A). J. Cereal Sci. 6:103-118.
Rafalski, J. A., M. Hanafey, G.-H. Miao, M. Dolan and S. V. Tingey, 1998 Electronic northerns: soybean gene expression information from EST data. Plant and Animal Genome VI Conference. Abstract: http://www.intl-pag.org/pag/6/abstracts/424.html.
Ramsay, G., 1998 DNA chips: State-of-the-art. Nature Biotechnol. 16:40-44.
Riley, R., and V. Chapman, 1958 Genetic control of the cytologically diploid behaviour of hexaploid wheat. Nature 182:713-715.
Riley, R., and C. N. Law, 1965 Genetic variation in chromosome pairing. Adv. Genet. 13:57-114.
Rounsley, S. D., A. Glodek, G. Sutton, M. D. Adams, C. R. Somerville, J. C. Venter and A. R. Kerlavage, 1996 The construction of Arabidopsis expressed sequence tag assemblies. Plant Physiol 112:1177-1183.
Ruan, Y., J. Gilmore and T. Conner, 1998 Towards Arabidopsis genome analysis: monitoring expression profiles of 1400 genes using cDNA microarrays. The Plant J. 15:821-833.
Saghai Maroof, M. A., G. P. Yang, R. M. Biyashev, P. J. Maughan and Q. Zhang, 1996 Analysis of the barley and rice genomes by comparative RFLP linkage mapping. Theor. Appl. Genet. 92:541-551.
Sasaki, T., J. Song, Y. Koga-Ban and E. Matsui, et al., 1994 Toward cataloguing all rice genes: large-scale sequencing of randomly chosen rice cDNAs from a callus cDNA library. Plant J. 6:615-624.
Schena, M., D. Shalon, R. Heller, A. Chai, P. O. Brown and R. W. Davis, 1996 Parallel human genome analysis: Microarray-based expression monitoring of 1000 genes. Proc. Natl. Acad. Sci. USA 93:10614-10619.
Sears, E. R., 1954 The aneuploids of common wheat. Research Bull. Univ. Missouri Agric. Exper. Station 572:1-59.
Sears, E. R., 1966 Nullisomic-tetrasomic combinations in hexaploid wheat, pp. 29-44 in Chromosome Manipulations and Plant Genetics, edited by R. Riley, and K. R. Lewis. Oliver & Boyd, Edinburgh.
Sears, E. R., 1976 Genetic control of chromosome pairing in wheat. Ann. Rev. Genet. 10:31-51.
Sears, E. R., and M. Okamoto, 1958 Intergenomic chromosome relationships in hexaploid wheat, pp. 258-259 in Proc. X Int. Congress Genet.
Sherman, J. D., A. L. Fenwick, D. M. Namuth and N. L. V. Lapitan, 1995 A barley RFLP map: alignment of three barley maps and comparisons to Gramineae species. Theor. Appl. Genet. 91:681-690.
Shoemaker, R. C., 1998 Welcome to the soybean EST project home page. http://129.186.26.94/soybeanest.html.
Soares, M. B., M. F. Bonaldo, P. Jelene, L. Su, L. Lawton and A. Efstratiadis, 1994 Construction and characterization of a normalized cDNA library. Proc. Natl. Acad. Sci. USA 91.
Soderlund, C., I. Longden and R. Mott, 1997 FPC: a system for building contigs from restriction fingerprinted clones. CABIOS 13:523-535.
Soper, J. F., R. G. Cantrell and J. W. Dick, 1989 Sprouting damage and kernel color relationships in durum wheat. Crop Sci 29:895-898.
Sorrells, M. E., and J. A. J.A. Anderson, 1996 Quantitative trait loci associated with preharvest sprouting in white wheat, pp. July 2-7, 1995, in Seventh International Symposium on Preharvest Sprouting in Cereals, Abashiri, Japan.
Staden, R., 1998 makeSCF, pp. . ftp://ftp.mrc-lmb.cam.ac.uk/pub/staden/src/makeSCF.c.
Takahashi, N., and M. S. Ko, 1994 Toward a whole cDNA catalog: construction of an equalized cDNA library from mouse embryos. Genomics 23:202-210.
Tanksley, S. D., M. W. Ganal and G. B. Martin, 1995 Chromosome landing: a paradigm for map-based gene cloning in plants with large genomes. Trends in Genet. 11:63-8.
Tao, H. P., A. E. Adelsteins and D. D. Kasarda, 1992 Intermolecular disulphide bonds link specific high-molecular- weight glutenin subunits in wheat endosperm. Biochimica et Biophysica Acta 1159:13-21.
Thierry-Mieg, D., and J. Thierry-Mieg, 1998 Acembly, pp. . http://alpha.crbm.cnrs-mop.fr/acembly/.
Thierry-Mieg, J., and R. Durbin, 1992 ACEDB: A C. elegans Database., pp. http://probe.nalusda.gov:8000/acedocs/users_guide.html.
Thomas, B., 1994 Internal and external controls on flowering. Oxon, UK, CAB International.
Tranquilli, G. E. a. D., J., 1999 Interactions between vernalization genes of Triticum monococcum, pp. http://www.intl-pag.org/pag/7/abstracts/pag7351.html/ in Plant and Animal Genome VII Conference.
Tsuji, S., and S. S. Maan, 1981 Differential fertility and transmission of male and female gametes in alloplamic wheat hybrids. Can. J. Genet. Cytol. 23:337-348.
Uchimiya, H., S. Kidou, T. Shimazaki, S. Takamatsu, H. Hashimoto, R. Nishi, S. Aotsuka, Y. Matsubayashi, N. Kidou, Umeda et al., 1992 Random sequencing of cDNA libraries reveals a variety of expressed genes in cultured cells of rice (Oryza sativa L.). Plant J. 2:1005-1009.
Upadhya, M. D., and M. S. Swaminathan, 1967 Mechanisms regulating chromosome pairing in Triticum. Biol. Zentrbl. 86:239-255.
Van Dayze, A., J. C. Nelson, E. G. Yglesias, S. E. Harrington, D. P. Braga, S. R. McCouch and M. E. Sorrells, 1995 Comparative mapping in grasses. Wheat relationships. Mol. Gen. Genet. 248:744-754.
Van Deynze, A. E., J. Dubcovsky, K. S. Gill, J. C. Nelson, M. E. Sorrells, J. Dvorak, B. S. Gill, E. S. Lagudah, S. R. McCouch and R. Appels, 1995 Molecular-genetic maps for group 1 chromosomes of Triticeae species and their relation to chromosomes in rice and oat. Genome 38:45-59.
Vassarotti, A., and A. Goffeau, 1992 Sequencing the yeast genome: the European effort. Trends Biotechnol. 10:15-18.
Velculescu, V. E., Z. L., W. Zhou, J. Vogelstein, M. A. Basrai, D. E. Bassett, P. Hieter, D. Vogelstein and K. W. Kinzler, 1997 Characterization of the yeast transcriptome. Cell 88:243-251.
Velculescu, V. E., L. Zhang, B. Vogelstein and K. W. Kinzler, 1995 Serial analysis of gene expression. Science 270:484-487.
Vodkin, L. O., R. C. Shoemaker, E. F. Retzel, P. Keim and N. D. Young, 1998 A functional genomics program for soybean. NSF Award Abstract : (http://www.nsf.gov/cgi-bin/showaward?award=9872565).
Walker-Simmons, M. K., and J. L. Ried, 1993 Pre-harvest sprouting in Cereals, pp. in 1992 American Association of Cereal Chemists, St. Paul MN.
Wallace, D., 1982 Structure and evolution of organelle genomes. Microbiological Reviews 46:208-240.
Wang, X., and B. Bowen, 1998 Plant and Animal Genome VI Conferences. Abstracts: http://www.intl-pag.org/pag/6/abstracts/wang.html.
Waterston, R., C. Martin and M. e. a. Craxton, 1992 A survey of expressed genes in Caenorhabditis elegans. Nature Genet. 1:114-123.
Werner, J. E., T. R. Endo and B. S. Gill, 1992 Towards a cytogenetically based physical map of the wheat genome. Proceedings of National Academy of Sciences 89:11307-11311.
Winzeler, E. A., and R. W. Davis, 1997 Functional analysis of the yeast genome. Current Opinion in Genetics and Development 7:771-6.
Wrigley, C. W., and K. W. Shepherd, 1973 Electrofocusing of grain proteins from wheat genotypes. Ann. N.Y. Acad. Sci. 209:154-162.
Xie, D. X., K. M. Devos, G. Moore and M. D. Gale, 1993 RFLP-based genetic maps of the homoeologous group 5-chromosomes of bread wheat (Triticum aestivum L.) Theor. Appl. Genet. 87:70-74.
Yamamoto, K., and T. Sasaki, 1997 Large-scale EST sequencing in rice. Plant Mol. Biol. 35:135-144.
As Director of GRCP, I serve as CoProject Director with R. Bye in Mexico on a McKnight Foundation funded six-year Collaborative Crop Research Program ($1.7 million), “Genetic Resource Conservation and Crop Improvement in Mexico: A Farmer-Based Approach”. This project involves collaboration among four U.S Universities (North Carolina State, Maine, Cornell, and UCDavis) and five institutions in Mexico. On the US side we coordinate graduate student training, visiting scientists, annual meetings and reports, and provide funding for research through GRCP. This project includes 18 investigators and 30 undergraduate and graduate students.
Previous NSF-funded Research: In the 1980s I served as CoPI with Professor E. Epstein on a field-based study of the potential for enhancing salinity tolerance in wheat and barley for crop production. We established genotype-specific response curves to detect salinity tolerance and the first field experiments to demonstrate salinity tolerance in wheat-Lophopyrum amphiploids and chromosome substitution lines, later used by Professor Dvorak in discovering Kna1, a major gene conferring salinity resistance in wheat.
I was PI on a small NSF International Programs grant in 1984 for exploration and collection of Dasypyrum villosum, an allogamous diploid (V) Triticeae species found in the Mediterranean area. With P. McGuire and colleagues in Italy, the resulting collections were used in studies on genetic diversity, mating system, and searches for useful traits. More than 20 papers have been published and useful traits were discovered, now being used in breeding programs throughout the world. Interesting diversity in seed storage proteins was found at Glu 1V, with 14 electrophoretically detectable alleles identified at that locus.
More recently (1990-94)I was CoPI with Professor S. Brush on a project to study the role of in situ conservation of landrace wheats in western Turkey in relation to genetic diversity for adaptive traits and socio-economic factors. This project is nearing completion with two Ph.D. students and collaborators in Turkey.
Current Research: Formal retirement from UCDavis in 1994 has permitted a return to Triticeae research, including a current BARD-funded project with M. Feldman in Israel to study the genetic architecture of quantitative traits in single chromosome arm recombinant substitution lines. Single chromosome arms were introgressed into hexaploid Bethlehem wheat from tetraploid T. dicoccoides and subsequently used to create recombinant inbred lines. Other QTL mapping work includes stomatal and yield-related traits in the ITMI mapping populations with Prof. E. Zeiger (UCLA). Long-term development of congenic lines for traits of putative adaptive significance in wheat is in various states of completion for several traits (liguleless, branched spike, reduced tillering, erect leaf, vernalization, HMW glutenin subunits). These stocks provide excellent materials for candidate gene detection and will be available to the various labs in this project and to others. The study of in situ landrace genetic diversity of wheat in Turkey, Iran, and Ethiopia is progress, as are studies of the genetics of wheat enduse quality with colleagues in Spain and Hong Kong.
The relationship to the proposed project is two-fold. As coordinator of the GrainGenes database Olin Anderson is ideally placed to ensure maximum interaction with project research and bioinformatics staff and GrainGenes staff. In addition, the GrainGenes project has a history of interest in comparative mapping and genomics and future efforts include close interactions with other ARS database projects. Secondly, the specific EST portion of the proposed project is a logical extension of the ongoing wheat endosperm EST project at Albany which is also being used at a test of handling EST data and inclusion in databases.
The second most important activity in my laboratory is the identification and mapping of genes controlling K+/Na+ in Lophopyrum elongatum. The objectives of this project are: (1) the construction of the populations of the first- and second- cycle disomic recombinant substitution lines (RSLs) for chromosomes 1, 3 an 7 of L. elongatum and to map crossover points with molecular markers and (2) mapping of genes controlling salinity tolerance and K+/Na+ selectivity in these RSL populations. In parallel to this project my laboratory is working on the enhancement of osmotic (salinity) tolerance in rice. The objective is to identify sources of salinity tolerance in exotic rice germplasm by screening for superior K+/Na+ selectivity. Salinity tolerance will be introgressed to California cultivars using molecular markers.
I collaborate with Jan Valkoun at ICARDA, Aleppo, Syria and Harold Bockelman (the curator of the National Small Grains Colection at Aberdeen, Idaho) on the acquisition and characterization of germplasm of T. urartu and Ae. tauschii, ancestors of bread wheat. The objectives of the proposal are (1) to acquire accessions of T. urartu from ICARDA and (2) collect germplasm of Ae. tauschii in the Transcaucasia and characterize both germplasms with molecular markers prior to their deposition in the US Small Grains Germplasm Collection in Aberdeen.
My laboratory is in initial stages of studies of the evolution of genepools and interploidy gene flow in wheat. Objectives of these studies are: (1) to determine the genetic basis of the hulled habit of primitive wheats, (2) to assess genetic distances and the presence of diagnostic alleles in the A and B genomes of all forms of tetraploid and hexaploid wheat and use this information in the interpretation of genetic relationships among the genepools of tetraploid and hexaploid wheats.
In recent years, molecular genetics has provided new methods to generate, identify, characterize, and manipulate genetic variation. We have used comparative genomics to facilitate the identification and localization of gene sequences controlling specific traits in the domesticated grasses. The emerging databases of gene sequences will allow directed discovery of genes in higher plants and classification of alleles present within breeding germplasm. Our goal is to identify the genes controlling critical traits and their DNA sequences and then classify variation in the germplasm pool by gene fingerprinting or by characterization of variation in key DNA sequences. Classification of the allelic variants for a particular locus would substantially reduce the amount of work required to determine the relative breeding value and lead to the identification of superior alleles based on DNA sequence. Incorporation of direct allele selection into our breeding program, allows more rapid and precise improvement of populations and breeding lines.
As shown in my current and pending support, our funding includes modest support for the small grains breeding program and 2 research projects as follows:
Application of molecular genetics for development of durum wheat varieties: This is a collaborative project with ICARDA and FCRI, Egypt. The overall objective of this project is to develop higher yielding, disease resistant durum varieties with improved pasta qualities for the primary wheat growing areas in middle and upper Egypt. Durum variety improvement will be enhanced using new breeding methods, biotechnology, and training. 1. Implement research to test new phenotypic selection criteria that are associated with higher yield and quality. 2. Construct a molecular marker map for a recombinant inbred population from the cross Jennah Ketifa x Cham1. 3. Identify, characterize, and map loci controlling yield potential, stress tolerance, disease resistance and grain quality in this durum recombinant inbred population grown under both high yield and stress environments. 4. Initiate marker assisted selection for superior alleles in backcross populations to develop improved durum varieties. 5. Provide training in breeding and genetics.
Integration of QTL, Candidate Gene, and Comparative Sequence Analyses for Crop Improvement: The overall objective of this project is to develop methodologies that integrate molecular information from different approaches and from distant taxonomic clades that facilitate genomic research on polyploids. To develop these techniques we propose to isolate and characterize candidate loci underlying QTL for PHS resistance in wheat by integrating information from our QTL, candidate gene, and comparative mapping research. Specific objectives are: 1. Utilize comparative genetics to identify, clone, and characterize candidate loci underlying genes affecting grain dormancy in wheat and barley. 2. Develop a catalog of sequence variation at each locus and associate variation with phenotypic effects in a selected germplasm core.
The proposed research will lead us to the characterization of candidate genes for use in our small grains breeding program.
This proposal not only adds needed genetic tools (mostly ESTs) for future use in locating genes affecting agronomically important traits, but also will reveal the degree of homology in important biochemical pathways that affect a large number of traits in grasses of agricultural importance. My contribution to the proposal will be as one of the eight laboratories assigned to map ESTs. The posdoctoral associate involved in mapping of ESTs using the deletion stocks also will use these ESTs in our continued mapping of Fusarium head blight resistance genes in wheat. Although not part of this proposal, we plan to collaborate with other scientists at the University of Minnesota (see letter from Dr. Muehlbauer) to use the EST arrays to investigate the wheat genes whose expression is modified in response to challenge by Fusarium graminearum. Below are objectives of my wheat breeding project at the University of Minnesota and the NRI-funded Fusarium head blight mapping grant. Other funded projects listed in my Current and Pending Support statement share objectives with the projects listed below.
University of Minnesota Wheat Breeding and Genetics
Current Research. DHNs have been purified from plants and genetically engineered Escherichia coli strains, as well as from the cyanobacterium Anabaena, for in vitro biochemical studies in work sponsored by the National Science Foundation and University of California Biotechnology Research and Education Program. Dr. Close’s laboratory demonstrated by immunocytochemical methods that plant dehydrins are present in the nucleus and cytoplasm of various cell types in the maize embryo, and by in vitro methods that DHNs are structured in association with lipids. The discovery that a cluster of barley dehydrin (Dhn) genes co-segregates with winter hardiness QTL is under further investigation in studies supported by the United States Department of Agriculture (USDA) to test the possibility that a Dhn gene is a growth-habit or freezing-tolerance determinant in barley and related cereal crop plants. Similarly a 35 kDa DHN of cowpea that is genetically associated with low temperature seed emergence is the subject of studies supported by the USDA through the Southwest Consortium on Plant Genetics and Water Resources. Dr. Close is active in several Triticeae genomics initiatives, from the production of cDNA libraries through allele-trait association studies and microsynteny analyses.
Relationship Between Proposed Activity and Current Research. During the studies described above, various cDNA and genomic libraries have been produced in Dr. Close’s laboratory. For example, Dr. Close’s laboratory recently produced lambda ZAP cDNA libraries from unstressed, cold-stressed and drought-stressed Morex barley seedling shoots and provided them to Rod Wing at Clemson University for arraying and sequencing. In addition, for several years Dr. Close has run a graduate laboratory course called “Plant Genomic Library Construction” and has provided a genomic library construction and distribution service for the North American Barley Genome Mapping Project. The assignment of cDNA construction duties to Dr. Close’s laboratory in the current proposal will ensure that all of the cDNA library construction needs of the group will be readily met. Dr. Close’s experience with the dispersed Dhn multigene family will also provide an important perspective in the design of EST arrays for gene expression and functional genomics studies in the Triticeae.
The tools that will be developed in this proposal will greatly accelerate the positional cloning efforts from our laboratory. The construction of microarrays including cDNAs from vernalized, unvernalized, and devernalized shoot apexes and young leaves will facilitate the identification of candidate genes based on their expression patterns. The sequence information that will be provided by this effort will be integrated to the expression patterns and the chromosome location to identify candidate genes.
This proposal is essential to incorporate new functional genomic technologies into our research program. The tools developed in this proposal in conjunction with the available BAC libraries will provide the appropriate tools for future cloning efforts of important agronomic genes. My laboratory is working in the preliminary QTL mapping of some of these traits and will greatly benefit for the availability of these genomic tools in wheat.
The major relationship between the current research effort and the proposed project is that currently I am trying to do the same for only a part of the genome and very inefficiently. The proposed project will target the whole wheat genome and we are approaching it in such a way that we clone and characterize wheat specific genes and in the process, generate many of the resources and infrastructure required for efficient and targeted functional genomics of world˙s most important food crop.
Even though wild species in the Triticeae family represent a vast reservoir of genes for improvement of pest resistance, grain quality, and agronomic fitness of wheat. Chromosome asynapsis and hybrid sterility are major obstacles to alien gene transfer, and genes producing nuclear-cytoplasmic (NC) interactions are directly or indirectly involved. A better understanding of NC compatibility and genic interactions in interspecific and intergeneric hybrids would broaden usage of alien species and improve gene transfer in wheat breeding. Thus, in a collaborative effort with Dr. S.S. Maan, my laboratory is investigating the molecular basis of NC interactions. The proposed project will provide the necessary tools to identify and clone the genes involved in these interactions and facilitate the ongoing effort of gene transfer from wild Triticeace into adapted wheat germplasm
As demonstrated, “The structure, function and evolution of the expressed portion of the wheat” will be an extension of wheat germplasm enhancement ongoing projects. Cloning, sequencing, tagging and mapping important regions of the wheat genome will greatly enhance our ability to transfer important genes from wild and related species and develop improved varieties. Wheat is the world’s most important food crop. The recent Fusarium head blight epidemic of the Northern Great Plains causing extensive damage to the US wheat production is a demonstration of how fragile our supply is. The proposed project will help us understand and devise rapid methods of obtaining better varieties to improve wheat production paralleling the increasing demand by ever-growing population.
The large genome size of wheat (15,000 Mbp) makes the application of positional cloning extremely difficult and impractical. We are currently investigating the gene organization in barley to determine whether barley genes are located in specific domains of the genome. The knowledge gained from the study can be used to develop cloning strategies that are appropriate for barley and its related species, wheat.
The development and genetic mapping of wheat ESTs proposed in this project will provide a valuable resource to our current research in mapping and cloning of RWA resistance genes. The availability of wheat ESTs will open the possibility of using a candidate gene approach in cloning RWA resistance genes. Our laboratory will contribute to this project our expertise in wheat molecular mapping.
Molecular analysis of heritable acquired heat tolerance in wheat: This project is funded by the USDA-NRI program. The long-term goal of the project is to determine if heat shock protein (HSP) genes or other genetic components can be used as genetic markers and whether any specific gene can be identified for direct genetic manipulation to improve heat tolerance of this important cereal crop. In this project, we will use a population of RILs to investigate the molecular basis of acquired thermotolerance. A combination of protein gel electrophoresis, RNA analysis, and differential display methods will be employed to investigate the extent of genetic association between the production of unique HSPs, level of gene expression, and acquired thermotolerance.
High-resolution mapping of QTLs controlling the stay green trait in sorghum: This project is supported by the USDA-NRI Plant Genome program. Previous work has identified two major QTLs controlling the stay green trait, an adaptive post-flowering drought resistance trait in sorghum, from a RIL population of B35 and Tx7000. The current work is aimed at the development of high resolution genetic and physical maps in these two regions in the sorghum genome. The research includes development of near-isogenic lines for these QTLs through marker-assisted backcrossing and physical mapping using BAC libraries in collaboration with the BAC Center at Texas A&M University. Comparative mapping with maize genome is being carried out.
Mapping of QTLs controlling drought resistance in rice (osmotic adjustment, root development, and yield-related traits): This project is supported by the Rockefeller Foundation and in collaboration with the International Rice Research Institute (IRRI). Doubled-haploid and recombinant inbred populations have been developed for genetic mapping and phenotypic evaluation. Several advanced backcrossed populations are being developed for QTL detection and introgression of desirable traits into elite breeding lines. Mapping work is done using DNA probes from the Japan Rice Genome Program and Cornell rice linkage maps.
Molecular mapping of osmotic adjustment and drought resistance in wheat: This project is supported by the BARD program in collaboration with Dr. A. Blum in Israel. Two RIL populations were developed for this purpose and comparative genetic mapping between wheat and rice will be pursued with particular interest on loci influencing the expression of osmotic adjustment capacity under drought. The PI is a member of the International Triticeace Mapping Initiative with a focus on abiotic stress. Recently, the PI assumed a leadership role to coordinate the Plant Genomics Program at Texas Tech University. The proposed NSF project is a logical extension of these activities which will provide an opportunity for a large scale EST sequencing of the wheat genome, including stress.
A major aspect of this proposal is the development of molecular genetic resources for Triticeae researchers and for the broader plant science community. This will involve the development of EST clones and sequences and cDNA EST arrays which will be available to the entire research community. All data generated by the project will be stored in public databases such as the NCBI dbEST and the USDA/ARS small grains computer database project (GrainGenes). Initially, these materials will be maintained and distributed from the USDA Triticeae molecular genetics resources facility at Albany, CA. After the completion of this project, the genetic resources will be transferred to other facilities; the US distributors for the I.M.A.G.E. consortium (American Type Culture Collection, P.O. Box 1549, Manassas, VA 20108; Genome Systems, Inc., 4633 World Parkway Circle, St. Louis, MO 63134; and Research Genetics, Inc., 2130 Memorial Pkwy., SW, Huntsville, AL 35801), or USDA facilities as structured at that time.
The conduct of this research will utilize information and materials from various public and private sources. In some instances the investigators will be requested to sign agreements with owners of intellectual property to gain access to protected materials. Such agreements must be approved by all investigators in this proposal to prevent misunderstandings about the use of materials and third party distributions.
The ownership of intellectual property rights will be respected according to NSF Grant Proposal Guide, October 1998, Section VII-K. Investigators will be requested to acknowledge the status of their developments which occurred prior to the support of this grant and to clearly identify those discoveries which benefited from financial support of the this grant. Since a key element of this proposal is multi-investigator collaboration, hence multi-institutional, the investigators directly involved in collaboration will be co-inventors of patentable discoveries and ownership will be respected in the filing of patents and ultimate licensing of products derived from those discoveries. This principle must be respected by the all institutions employing investigators contributing to this proposal to ensure equitable recognition to the inventors.
C.O. Qualset (PI) will serve as the project director and Chair of the Steering Committee, as noted above. P.E. McGuire will provide management services[25% time], including preparation of subcontracts, detailed planning of workshops and annual meetings, and writing and editing reports. He will service as webmaster for the project. Dr. McGuire is a key person for the project because of his personal interest in this Triticeae research and because, as Associate Director of GRCP, he has great knowledge of UC administrative procedures and authority for management of financial accounts. The project will provide 25% financing of his salary and benefits. No funds are requested for the project director. He has partial recall to service as Director of GRCP and will volunteer his time for work on this project. Based on experience with a similar extramural funded project (by McKnight Foundation) managed by GRCP, the workload for supporting a project of 14 CoPIs and numerous students and postdoctorals requires the part-time service of a program assistant (0.5 FTE requested). The program assistant will be required to handle project-generated purchase orders for the collaborative research of CoPI O. Anderson at nearby Albany, CA, to make arrangements for providing stipends to trainees and subsistence funds to visiting scientists, and distribution of information.
There is great interest in the proposed work on ESTs from the international members of the ITMI community, with letters of expressed collaboration from Australia, Canada, England, and Mexico. Further, ITMI has originated another collaborative group, ITEC, expressly to develop and share ESTs. The present proposal represents the capability of the US laboratories to participate. Briefly, ITEC is described below:
This activity was seen as the first stage in developing an international effort to produce a public set of information and materials for Triticeae genome research.
The present project will be supportive of the national effort to solve a crisis-level problem in wheat and barley production (Fusarium head blight). The disease can only be practically controlled by host plant resistance and locating genes has been particularly elusive for this disease. The EST libraries will have immediate value to the researchers on Fusarium.