Belo R. Guttenvolk1

USDA, Agricultural Research Service

BARC-West, Bldg. 005, Rm. 331C

Beltsville, MD 20705

I. Introduction

A. History and Program Establishment

B. Program Goals, Structure and Operation

1. National Research Initiative and Agricultural Research Service Cooperative

II. Progress

A. Summary of Four Years--1991-1994

B. Graminae

1. The Genomes of Maize and Sorghum

2. Genome Analysis in Small Grains and Sugarcane

C. Leguminosae

D. Cruciferae

E. Malvaceae

F. Solanaceae

G. Woody Species

III. The Plant Genome Database

IV. Future Projections

1Guttenvolk (to whom reprints should be send) thanks the authors who summarized genomic research in various plant groups and database parts of the document and to whom reprint requests should be sent: Altenbach, S. (Small Grains) USDA, ARS, WRRC, 800 Buchanan St., Albany, CA 94710; Anderson, O. (Small Grains) USDA, ARS, WRRC, 800 Buchanan St., Albany, CA 94710; Bigwood, D. (Plant Genome Database) USDA, NAL, BARC-E, Beltsville, MD 20705; Cartinhour, S. (Plant Genome Database) USDA, NAL, BARC-E, Beltsville, MD 20705; Coe, E. (Maize and Sorghum) USDA, ARS, Plant Genetics Research, Curtis Hall, Rm. 210, Columbia, MO 65211; Datko, A. (Competitive Grants) USDA, CRSEES, NRICG, 901 D St. SW, Rm. 323, Washington, DC 20250; Heller, S. (Plant Genome Database) USDA, ARS, BARC-W, Bldg. 005, Rm 337, Beltsville, MD 20705; Kaleikau, E. (Competitive Grants) USDA, CSREES, NRICG, 901 D St. SW Rm. 323, Washington DC 20250; McCouch, S. (Rice), Plant Breeding Dept., Bradford Hall 418, Cornell Univ., Ithaca, NY 14853-1901; Kohel, R. (Cotton) USDA, ARS, Crop Germplasm Research, Route 5 Box 805, College Station, TX 77845; Miksche, J. (Plant Genome) USDA, ARS, BARC-W, Bldg. 005, Rm331C, Beltsville, MD 20705; Moore, P. (Sugarcane) USDA, ARS, HI Sugar Planters Association, P.O. Box 1057, Aiea, HI 97601; Neale, D. (Woody Species) USDA, FS, SWFES, 800 Buchanan St., Albany, CA 94710; Osborne, T. (Crucifers) Dept. of Agronomy, Univ of Wisconsin, Madison, WI 53706; Paterson, A. (Cotton & Crucifers) Dept. of Soil and Crop Science, Texas A & M University, College Station, TX 77843-2474; Shoemaker, R. (Legumes) USDA, ARS, 1575 Agronomy Bldg. Rm G401, Iowa State University, Ames, IA 50011; Smith, G. (Plant Genome Data) USDA, ARS, NCRL, 1307 N 18th St. P.O. Box 5677, Univ. Station, Fargo, ND 58105; Tanksley, S. (Solanaceae) Plant Breeding Dept., Emerson Hall 248, Cornell Univ., Ithaca, NY 14853-1901; Wendel, J. (Cotton) Dept. of Botany, Iowa State University, Ames, IA 50011



The U.S. Congress appropriated funds in 1991 for the USDA Plant Genome Research Program, four years after its initial conception in 1987. Early in 1988, a formal proposal for the program was presented to the then Assistant Secretary for Science and Education Orville Bentley and later in the same year the leadership role of the program was assigned to the Agricultural Research Service (ARS). A conference held in December 1988 in Washington D.C. with plant science researchers from public, private, and government institutions addressed the need for and the goals of the program. A need for a plant genome mapping effort was uniformly recognized as important to U.S. agriculture. The director of the program was appointed April 11, 1989, after which an Interagency Plant Genome Coordinating Committee was formed and the committee met twice that same year. The committee's consensus states that the program would not specify one agricultural species but the effort would address genes of agricultural importance. ARS was given $99,000 "seed money" in 1990 for planning activities and formulation of a proposal for presentation to USDA Administration and Legislative bodies. An Informatics Project Leader was hired during the same year to begin addressing database information handling of the Plant Genome Research Program and the database effort was housed at the National Agricultural Library.


Discussions of the Plant Genome Science and Technology Coordinating Committee concluded that the project is more than mapping alone. It includes additional molecular biology techniques to pull out the gene system, characterize, and develop methods for transfer and gene expression. Because of the broadness of the effort, the committee named the activity the "USDA Plant Genome Research Program." Overriding the committee's discourse is the paramount importance of placing the genes or map marker locations in the hands of breeders for full application of the program. The goal, therefore, of the USDA Plant Genome Research Program (PGRP) is to improve plants (agronomic, horticultural, and forest tree species) by locating marker DNA or genes on chromosomes, determining gene structure, and transferring genes to improve plant performance with accompanying reduced environmental impact to meet marketplace needs and niches (Miksche, 1991). New cultivars will offer pest and disease resistance which reduces chemical applications and tolerance to abiotic stresses such as heat, cold, and drought conditions.

The Plant Genome Research Program is one program with two parts: (1) National Research Initiative, and (2) Plant Genome Database.


The grant proposals address the goal of improving plants through genomic research. Although this is an applied goal, the research efforts proposed by scientists that lean toward basic research are also considered for funding by the National Research Initiative (NRI) evaluation panel. A line of demarcation between basic and applied efforts in genomic research is not sharp and one can not advance the science of one aspect without the other's information.

The Request For Proposals (RFP) directed the proposals to address three categories: (1) broad genome maps; (2) fine maps, including physical mapping; and (3) new technology development to increase the efficiency of mapping, gene localization and characterization, and sequencing of desirable genes.



Total appropriation from Congress from 1991 through 1994 was $58.79 million for the program. The National Research Initiative and the Agricultural Research Service received $46.55 and $12.24 million, respectively, for the grants and database efforts. NRI plant genome competitive component awarded 381 grants to scientists from eighty-four public, private and government research institutions. Awards covered research on fifty-one agronomic, horticultural, forest tree species and four nonagricultural taxa. Within the fifty- five taxa, eighty- four percent of the research award dollars went to five plant groups: (1) Tree species - $1.8M; (2) Crucifers - $4.3M; (3) Legumes - $5.9M; (4) Solanaceae - $9.8M; and (5) Grasses - $16.6M. Over eighty gene/trait/genetic phenomena are at various stages progress as listed in table 1.

Some important accomplishments made by the grant awardees are:

- For the first time ever, a disease resistant gene was located and removed from the genome by map-based cloning technology. Bacterial Speck resistance trait was transferred to a susceptible variety resulting in resistance.

- One researcher is part of a team that discovered a new class of genes that allows plants to recognize a diverse group of pathogens.

- Quantitative trait loci (QTL) methods have been used to develop a barley line resistant to barley stripe rust and another researcher demonstrated an increase of 15% in corn yield.

- Forest researchers have analyzed the loblolly pine genome and mapped over 200 genetic markers as part of a tree improvement program in the Southeastern United States. Tree breeders can now expedite the improvement of loblolly pines by time compression and use of genetic resources with meaningful parents and desirable offspring.

The Plant Genome Database is now a real and functioning information and data resource for agricultural and other plant science genome researchers and it is in the public domain. The above progress represents only a small summary of findings but illustrates the subject areas of the program. Additional progress is given below according to major plant groups.



Maize has been called "The Human of the Plant World", considering that the corn genome is of similar bulk (approximately 3 billion base pairs); similar complexity (estimated 20,000 to 60,000 genes interspersed with much repetitive DNA); and similar high polymorphism per locus. The haploid number of chromosomes in maize is 10, and there is compelling evidence for extensive duplications in the genome (Helentjaris et al., 1988), reflecting an ancient hybridization between two species so diverged and rearranged that the genomes in the hybrid formed an effective, allopolyploid product that became modern maize. The state of genome analysis in this crop is reflected in the following:Genes, defined or prospective 4,980

Genes, defined to unique location or function 1,021

Genes, located to chromosome 974

Genes, sequences in GenBank 1,196

Genes, mitochondrion 38

Genes, plastid 79

Transposable elements 67

Mutants 6,205

RFLP probes 2,227

Breakpoints 2,351

Maps 152

Quantitative Trait Loci 169

Maize and sorghum are closely related to the other cereals and grasses (Bennetzen and Freeling, 1993), an insight made evident by mapping with molecular markers across species. The amount of genetic knowledge, plant breeding techniques, and genetic technology for maize is exceptional. Combine this information with other crops, prompt and efficient applications of new knowledge and new concepts among maize and the other cereals are the promise of coordinated research.

Sorghum has the same number of chromosomes as maize, and a genome of less than approximately 1 billion base pairs. Genetic studies have identified over 200 morphological and other variants (Melake-Berhan et al., 1993), but until the recent advent of molecular markers linkage mapping has been limited by a shortage of suitable tools.

Markers for Analysis and Manipulation of the Genome

Dramatic advances have been produced in a short time with tools which associate traits with efficient markers for the genes controlling them. These DNA probe tools can detect polymorphisms (RFLPs) at specific places in the genome. In the public sector, random genomic probes from maize developed at Brookhaven National Laboratory (BNL) and the University of Missouri are designated with prefixes bnl and umc, respectively. In the private sector prefixes include Native Plants Incorporated (NPI) with npi, Pioneer HiBred International with pio (now php), and Agrigenetics (Mycogen) with agr, among others. By marking the genome, simple and complex traits now can be dissected, analyzed, and manipulated with predictability and efficiency, multiplying the power of the breeder and of the biotechnologist. Map development for maize is moving very rapidly in several laboratories, and there are several parallel, mostly equivalent maps (table, Coe and Gardiner, 1994). The limits of computational tools needed for harmonizing and merging the data have so far delayed combined representation of all the information. Core Markers (Gardiner et al., 1993), chosen for their clarity, reliability, spacing, and a high rate of polymorphism, will aid harmonizing among maps, when use is made of these markers as pegs in common among the different maps and among maps in different species. A high-precision, statistically qualified Core Map for maize, with over 700 markers, has just been generated as a standard to use in comparative mapping of genes and gene candidates probed by cDNAs, with visibly defined genes (Davis et al., in preparation). The first published RFLP maps (Helentjaris et al., 1986a; Helentjaris et al., 1986b; Burr et al., 1988) have been subsumed in or superseded by more current maps (Gardiner et al., 1993; Matz et al., 1994; personal communication, Maize Genet. Coop. Newsl. 68, 198-208; Grant et al., 1993; personal communication, Maize Genet. Coop. Newsl. 67, 55-61). Additional maps are being generated in numerous populations prepared for QTL studies. Map distances among populations differ as expected because of widely differing parentages, progeny types, progeny sizes, probe numbers and probed loci, numbers of trait loci, marker coverage, and estimated genome size. The proximate order of markers varies in relatively few instances, within chance variations among samples and open to re-interpretations or re-evaluations. Maps of hybrids between maize and Zea diploperennis, and between maize and Zea luxurians, show some differences (Doebley et al., 1990.

Maps in Sorghum bicolor, developed with probes from maize (Hulbert et al., 1990; Melake-Berhan et al., 1993; Whitkus et al., 1992; Pereira et al., 1994), and one in Sorghum bicolor x S. propinquum, developed largely with probes from sorghum (Chittenden et al., 1994), have been advanced. These serve as the first genetic maps for sorghum and now have several morphological and quantitative traits on them. Less duplication is found within the sorghum genome than in maize.

Map Locations of Genes Encoding Key Cell Functions

Several probes used in the public-sector mapping projects with molecular markers have been derived by techniques that define them genetically as clones for specific cell functions. Examples include genes isolated by transposon tagging or by messenger selection and reverse transcription to produce a defined cDNA. In contrast, the agr probes developed and mapped by Murray et al. (1989) are random cDNAs from tissue-specific libraries, which have been mapped with bnl and umc RFLP markers. Recently, substantial numbers of random cDNA clones have been sequenced (Keith et al., 1993) and loci for them are being mapped (Chao et al., 1994; Helentjaris et al., 1994; personal communication, Maize Genet. Coop. Newsl. 68, 101-104). Because the sequences of these can be compared against existing data banks, potential functions often can be attributed to the loci that are mapped: Among 130 clones studied by Keith et al., 18 were found to show strong similarity to genes known in maize or in other species. The implication is that expanding numbers of sequences in various species will synergistically expand knowledge of functions and candidate functions of the others, including knowledge not only to maize but from maize as well.

Genome Structure and Synteny

Understanding of the relationships among species is now greatly enhanced by finding extensive homology seen in probe hybridization across species boundaries. Secondly, common order for extended segments of the genome between species that have been generally regarded as only distantly related, at best, also increases understanding of connection. Probes applied to sugarcane, foxtail millet, or sorghum display high frequencies of strong hybridization (Hulbert et al., 1990). All but 4 out of 250 maize probes showed strong hybridization with sorghum DNA (Bennetzen and Melake-Berhan, 1994). Up to 30% of the two genomes have been estimated to have common order (Whitkus et al., 1992) and the percentage is likely much higher. Such a considerable degree of synteny suggests that the genomes are moderately diverged. They may even be subject to transfer of genetic properties from one into the other if technologies permit some method of hybrid formation, amongst either whole genomes or genome segments (extensive attempts to cross maize with sorghum have been made in the past, without success; note, however, the instructive experiences with very wide crosses, in the next section). A species more closely related to maize, and crossable with it, Tripsacum dactyloides, shows considerable divergence in genome order (Blakey, 1993). Rice probes on maize, and maize probes on rice, display extensive regions of synteny (Ahn and Tanksley, 1993), as also found for wheat (Ahn et al., 1993).

Very Wide Crosses

Wheat has been crossed with maize pollen, after which the resulting zygotes lose the maize chromosomes in early divisions (Laurie and Bennett, 1986). This result is an effective method by which to generate haploids in wheat (Laurie and Bennett, 1988; Laurie et al., 1990; Suenaga and Nakajima, 1989). In oats also, haploids are generated (Rines and Dahleen, 1990) from crosses with maize pollen, and occasionally plants are obtained that carry one or more maize chromosomes. This work promises to provide needed cytogenetic tools for the analysis and manipulation of the oat genomes, and for maize as well. Crosses between maize and sorghum, which are much more closely related, have been attempted many times but have been unsuccessful, perhaps in part because of inhibition of pollen tube growth (Laurie and Bennett, 1989).

Quantitative Trait Loci and Marker Assisted Selection

The inheritance of quantitative traits in maize has been studied extensively by measurements and statistical analyses, especially analysis of variance. Design of quantitative experiments, and their interpretation, is grounded in Mendelian behavior of large numbers of genes. The very substantial advances in analysis that have become possible because of molecular markers are due to their clarity in most applications and to the irrelevance of variations in molecular markers to the genetics of the traits themselves. By the use of RFLP markers, distributed at intervals of 20 centimorgans or so, definition of intervals carrying a gene or genes affecting a measured trait has begun to advance at a rapid pace. Experiments to map Quantitative Trait Loci (QTL) began as soon as the technology could be applied (Beavis et al., 1991; Edwards et al., 1992; Romero-Severson et al., 1989), and are expanding rapidly. Notable in particular is the fact that a substantial part of the variation for many traits is attributable to variations in only a few segments of the genome. These findings are a prediction of the proposal of Robertson (1989) that subliminal variations at loci known from drastic mutants (e.g., dwarfs) are a source of quantitative trait variation (e.g., plant height).

Marking genetic regions for inclusion or exclusion, to save repeated testing and to reduce population sizes that must be advanced during breeding and selection, has been one of the most-sought-after consequences of map development. Now that maps are available whose coverage is adequate for the purpose, selection of targeted segments is proving effective-- demonstrated increases in yield substantially exceed the parent hybrid and a quality commercial hybrid (Stuber and Sisco, 1991).


Wheat, barley, rice, and oats are the major small grain crops, with wheat accounting for more acreage in the world than any other cereal, and wheat and rice vying yearly for the most tonnage worldwide. In contrast to rice, the other small grain genomes are large and complex. Bread wheat contains one of the largest genomes of the major crop plants, about 1.6 x 1010 bp of DNA per haploid nucleus, or approximately 40 times that of rice. The genome sizes of oats and barley are also large, 1.1 x 1010 for oats and 5.0 x 109 bp per haploid nucleus for barley. The large genome size of these plants coupled with the polyploid natures of both wheat and oats makes genome analysis particularly challenging in these species.


Doubled haploid populations developed from principal North American germplasm groups have been used to generate an extensive molecular map for barley (Hordeum vulgare L.). A cross between Steptoe, a six-rowed high yielding feed barley, and Morex, a six-rowed barley that is used as the standard of the American malting industry has been used to map 450 loci with an average distance of 3 centiMorgans (cM) between markers (Kleinhofs et al., 1993,1994). Several additional RFLP maps have also been developed using other populations (Heun et al., 1991; Graner et al., 1991; Kleinhofs et al., 1994).

The development of linkage maps is important for studies aimed at locating quantitative trait loci (QTL) that may be targets for map-based cloning or molecular marker-assisted selection (MMAS). Based on agronomic and malting quality phenotypes, data generated in five environments in 1991, and a 123-point skeleton linkage map, Hayes et al. (1993) located QTLs for grain yield, lodging %, plant height, heading date, grain protein, alpha amylase, diastatic power, and malt extract in the Steptoe x Morex population. In 1992, agronomic phenotypes were assessed in eleven additional environments, and malting quality traits in five environments (Hayes et al., 1994).


Since oats (Avena sativa L.), similar to wheat, is an allohexaploid species (genome designation AACCDD), initial efforts at genome analysis have centered around the development of RFLP linkage maps for the A genome of Avena using F3 families from a cross between two diploid species, A. atlantica and A. hiratula (O'Donoughue et al., 1992). A total of 192 RFLP markers, most derived from either oat or barley cDNA libraries, were mapped or assigned to seven linkage groups.


Rice (Oryza sativa L ) is one of the most important food crops in the world and is a staple food for much of the world's population. Rice is a diploid species with 12 chromosomes and has the smallest genome of any monocot known, about 4 x 108 bp per haploid nucleus. Rice has also become a model plant among the cereals for molecular genetic studies since plants can be regenerated from protoplasts and transformed at relatively high efficiencies (for reviews, see Lynch et al., 1991; Hodges et al., 1991, Kothari et al., 1993).

McCouch et al. (1988) described the construction of the first RFLP map in rice. This map was constructed from an F2 population derived from a cross between varieties representing the two major sub-species (indica and japonica) of cultivated rice. Primary trisomic stocks (Khush et al., 1984) were used to assign the 12 linkage groups to their respective chromosomes. The RFLP map generated has provided the basis for tagging a number of agronomically important genes with RFLP markers, including both single genes and quantitative trait loci (QTL) linked to blast resistance (Yu et al., 1991; Wang et al., 1994), insect resistance (McCouch and Tanksley, 1991; Mohan et al., 1993), bacterial blight resistance (McCouch et al., 1991; Ronald et al., 1992), photoperiod sensitivity (Mackill et al., 1992), grain aroma (Ahn et al., 1992), wide compatibility (Liu et al., 1992; Zheng et al., 1992), and the semi-dwarf character, sd-l (Cho et al., 1994).

A second RFLP map of rice based on a different indica/japonica cross was reported by Saito et al. (1991). A third map based on an indica/japonica cross is currently under development in Japan (Nagamura et al., 1993). That map is comprised of a combination of genomic and cDNA markers and currently consists of over 1400 markers. Efforts to integrate the rice maps are underway (Xiao et al., 1992).


The use of complementary approaches has been critical to the advancement of genome mapping efforts in wheat (Triticum aestivum L.). Hexaploid bread wheat exhibits relatively low levels of polymorphism, making RFLP linkage analysis somewhat difficult. However, wheat has the distinct advantage of having excellent cytogenetics and the availability of extensive sets of aneuploid stocks has proven to be invaluable in genome research. Aneuploid stocks with either whole chromosomes or segments of chromosomes added or subtracted from the genome have been used successfully to develop chromosome arm maps. Anderson et al. (1992) determined the locations of 800 restriction fragments in Chinese Spring that were homologous to 210 barley cDNA, oat cDNA and wheat genomic clones using ditelosomic and nullitetrasomic stocks. The construction of cytogenetically based physical maps of wheat chromosomes has also been possible using deletion stocks and has facilitated analyses of recombination in defined regions of wheat chromosomes (Werner et al., 1992).

RFLP linkage mapping has been performed in polymorphic diploid species such as Triticum tauschii, the D genome progenitor of hexaploid wheat (Gill et al., 1991. Partial RFLP linkage maps of hexaploid wheat have also been generated for homoeologous group 2, 3, 5, and 7 chromosomes using populations derived from wide crosses (Devos et al., 1993; Devos et al., 1992; Xie et al., 1993, Chao et al., 1989).

Along with the development of RFLP maps for hexaploid wheat have come a number of important observations about the structure of the wheat genome. When Werner et al. (1992) attempted to integrate existing linkage maps with cytogenetically based physical maps constructed using a collection of forty-one aneuploids containing partial arm deletions, they found that loci that were close to the centromere from genetic analysis were physically located on more distal regions of the chromosomes. This analysis indicated that recombination was suppressed in the proximal 70% of the chromosome and high in the distal ends, resulting in a compression of the genetic map in the middle and an expansion at the ends of the chromosomes. Thus, it appears that genes tend to be clustered on the distal portions of the wheat chromosomes. Such results have important implications when map-based cloning approaches are pursued to isolate genes of agronomic importance.

Perhaps the most exciting observation comes from comparative genetic mapping studies between wheat and other members of the Gramineae. Ahn et al. (1993) mapped 66 cDNA markers that had previously been assigned to wheat chromosome arms onto the 12 linkage groups of rice and found that the synteny of many loci appears to be conserved between the two species. A number of linkage group rearrangements could also be inferred from comparisons between the rice and the wheat genomes. For example, nine contiguous loci on rice chromosome 3 were located on wheat chromosome 4 while an additional 2 loci from the end of the rice chromosome were localized on wheat chromosome 5, suggesting that a translocation had occurred since the divergence of rice and wheat. By comparing the results of this study with a previous study (Ahn and Tanksley, 1993) in which comparative maps were generated for rice and maize, relationships between the wheat and maize genomes have been established as well. An example of these comparative mapping results is shown in Figure 1.

The observed synteny between the various species in the Gramineae should help to accelerate genome mapping in wheat since molecular maps for both maize and rice are well developed and a greater number of isozyme and morphological loci have been identified and mapped in these species. Sets of "anchor probes" might also be developed to serve as a framework for molecular mapping studies in the various cereal species. Since the rice genome is 40-fold smaller than that of wheat, it may also be possible to exploit the rice genome when considering map based cloning approaches for the isolation of agronomically important genes.

Genome Analysis in Sugarcane

Sugarcane presents even greater challenges than the other cereals in terms of genome analysis. Cultivated sugarcane is a genetically complex multispecies hybrid, that is generally considered to be an aneuploid of a basic octaploid. Sugarcane has a chromosome number of approximately 120 and the genome size is estimated to be greater than 3 x 109 bp per haploid nucleus. Modern cultivars are derived from interspecific crosses between Saccharum officinarum and either S. spontaneum, S. barberi, S. sinense, or S. robustum with subsequent recurrent backcrossing to the female parent. Single-dose markers that are present in one parent, absent in the other and segregate 1:1 in the progeny are useful in the genetic mapping of polyploid species where there are no known diploid relatives. Using such an approach, an RFLP linkage map of the wild sugarcane species S. spontaneum L. has recently been constructed. Two hundred and sixteen loci defined by 116 DNA probes from sugarcane, oat, rice and barley cDNA libraries and sugarcane and maize genomic libraries were mapped on 44 linkage groups (da Silva et al., 1993). The 44 linkage groups were shown to comprise 8 sets of homologous chromosomes. An additional 208 loci were placed on this map using RAPD technology (Al-Janabi, 1993).


The Leguminosae is the third largest family of flowering plants and contains approximately 650 genera and over 18,000 species (Polhill et al., 1981). The subfamily Papilionoideae is the largest of the three subfamilies of the Leguminosae whose members include the most diverse and economically important legumes. Accurate phylogenetic relationships among these complex and diverse plants for the most part, probably have not yet been fully resolved.

The great diversity within the family and their potential for food and forage contributes to their increasing economic importance. Perhaps the most striking characteristic of the legumes is their ability to fix atmospheric nitrogen in a symbiotic relationship with Rhizobium. In a survey of approximately 3000 legume species, it was found that about 90% formed N-fixing nodules and thus making this family crucial in environmentally friendly sustainable agriculture.

Genome Mapping Among the Legumes

The vast amount of mapping progress has been accomplished only very recently using molecular genetic markers (Table 2). Not surprisingly, most studies to date have involved crops of major importance as sources of seed protein or oil, or for high quality forage. These mapping studies employed a wide range of intra- and interspecific crosses and F2 as well as recombinant inbred populations. In some instances maps were derived from the integration of two or more populations (Echt et al. 1994; Shoemaker and Specht, 1995; Ellis et al., 1992).

Molecular probes detecting two or more loci are commonly reported in mapping studies involving legumes. It has been estimated that approximately 47% - 52% of all flowering plants are polypoids. It is generally thought that plants with approximately n = 13 or greater should be considered polyploid. Consequently, the greatest number of duplicate loci within legume genomes have been reported within those genera possessing the greatest chromosome number, e.g. peanut and soybean.

Nontraditional Genome Map Applications

A molecular genetic map alone is of limited value unless it can be applied to crop improvement breeding programs, to enhance our basic understanding of gene expression or to our understanding and determination of genome organization and evolution. One of the first efforts to demonstrate the application of map-based genome analysis of soybean cultivar pedigrees was reported by Shoemaker et al. (1992). This study demonstrated that segments of linkage groups could be followed through two generations, from parental cultivars to cultivars derived from them, thus correlating changes in genome allelic structure with cultivar development. Lorenzen (1994) applied this concept to the pedigree analysis of 43 soybean cultivars spanning nearly 70 years and 6 generations of cultivar development. This approach facilitates identification of those regions of a genome which have been selected for or against in breeding programs. This retrospecitve analysis of genome manipulation during cultivar development has potential to allow breeders to identify genomic regions important in their breeding programs and to make predictions on the success or failure of particular allele combinations.

Extensions of this type of analysis have shown that by combining pedigrees with graphical map-based analyses it is possible to identify regions of the genome that are undergoing high or low rates of recombination during breeding programs. Alleles that are selected for or against within northern and southern germplasm (different maturity groups), can be used estimate losses of genetic diversity during consecutive generations of cultivar development, and where losses in the genome have occurred (Lorenzen, 1994).

In cultivated alfalfa, an outcrossing autotetraploid (2n=4x=32), most mapping studies involved diploids. In this crop, where maximum heterozygosity is desirable, a high degree of segregation distortion is evident (Brummer et al. 1993; Kiss et al. 1993; Echt et al. 1994). The amount of segregation distortion is higher than reported for most other plants. The majority of instances segregation was skewed in the direction of the heterozygote. The Maximum Heterozygosity Theory maintains that multiple alleles at orthologous loci is a prerequisite for the successful expression of many of the traits associated with quality forage characteristics. Brummer et al. (1993) proposed that the genomic regions associated with distorted segregation may be important targets for manipulation during forage breeding programs.

Integration of Genes into Legumes Maps

Many of the mapping population studies cited in Table 2 segregated for isoenzyme, morphological or developmental qualitative traits. Consequently, many of these projects were able to incorporate agronomically important genes directly into the species map. Additionally, several groups attempted to integrate specific genes into molecular maps using populations unique to that purpose. Meuhlbauer et al. (1991) used a combination of near-isogenic lines and segregating populations to map genes for morphological characters in soybean (P1, r, and lf1). Other groups mapped agronomically important traits such as Fap2, a gene for fatty acid content in soybean seed oil (Nickell et al., 1994), and nts, a gene controlling nodulation in soybean (Landau-Ellis, et al., 1991). Shoemaker and Specht (1995), using a specially constructed population segregating for nearly 20 genes, integrated nearly half of the classical soybean linkage groups into the molecular map in a single study.

Several mapping studies focussed on disease resistance genes in legumes. Diers et al. (1992) mapped the location of 5 of 7 known genes conferring resistance to Phytophthora root rot in soybean. Several groups have concentrated efforts on mapping the genes conferring oligogenic resistance to soybean cyst nematode (Webb et al., in press; Weisemann et al., 1992; Concibido et al., 1994). A gene for the insect pests, bruchids, was mapped in mungbean (Young et al., 1992) as well as oligogenic resistance loci for powdery mildew (Young et al., 1993). Resistance to necrosis-inducing strains of bean common mosaic potyvirus (Nodari et al., 1993a) and common bacterial blight (Nodari et al., 1993b) were mapped in common bean. A resistance gene for soybean mosaic virus was mapped in soybean by Yu et al. (1994). The incorporation of many more disease reistance genes into molecular maps will likely occur as integration of classical and molecular maps proceeds.

Other projects incorporated agronomically important genomic regions into maps through QTL mapping. QTL mapping results to date have been carried out predominantly in soybean. QTL for seed protein and oil have been reported (Diers et al., 1992a; Mansur et al., 1993; Lark et al., 1994). Other studies have been reported on fatty acid composition (Diers and Shoemaker, 1992), seed coat hardness (Keim et al., 1990), seed weight (Mansur et al., 1993), nutrient efficiency (Diers et al., 1992b), and reproductive and morphological traits (Keim et al., 1990; Mansur et al., 1993).

Microsatellites or Simple Sequence Repeats

Hypervariable "minisatellites", or tandemly repeated short nucleotide sequences of variable length, were first reported in the human genome. "Microsatellites" have since proven to be invaluable, when coupled with polymerase chain reaction, in uncovering high levels of polymorphism in the human genome as well as in plant genomes. One of the first, and most detailed study of microsatellites in higher plants was conducted by Akkaya et al. (1992) within the soybean (Glycine max (L.) Merr.). They identified a number of di- and trinucleotide minisatellites (simple sequence repeats or SSRs), demonstrated their Mendelian inheritance, and established their multiallelic properties. The same laboratory demonstrated in soybean, which has a paucity of polymorphism among elite breeding lines, that SSRs are extremely valuable in genotype identification. SSRs have since been used in a study to locate and map the location of Rsv, a gene conferring resistance to soybean mosaic virus (Yu et al., 1994). A concerted effort is in progress to fully integrate a high number of SSRs into a combined molecular and classsical genetic map of soybean (Cregan, Specht and Shoemaker, unpublished) and the development of microsatellites is progressing in peanuts (Arachis sp.) (S. Kresovich, pers comm; G. Kochert, pers comm).

Comparative Mapping among Legumes

A comparison of genetic maps established from an interspecific cross in lentil (Lens) and from garden pea (Pisum) suggested that extensive conservation of linkage relationships exists between these members of the legume tribe Viceae (Weeden et al., 1992). These authors showed that approximately 40% of the linkage map for Lens remained conserved in Pisum. They suggested that all members of this tribe may possess linkage groups similar in structure to those of Lens and Pisum. It was noted that linkages conserved between isoenzyme loci in lentil and pea, could also be observed in faba bean (Vicia) (Torres et al., 1993). However, due to the lack of high resolution maps and the presence of many markers "bridging" the three genera, very few conserved linkages were observed.

Comparative mapping between mungbean (V. radiata) and cowpea (V. unguiculata), both members of the tribe Phaseoleae, also demonstrated a relatively high degree of linkage conservation between contiguous probes (Menancio-Hautea et al., 1993). The authors showed that 49 out of 53 loci retained linkage association. Although most regions of conservation were relatively small, a few large linkage blocks were retained between species. However, the linear order of loci within conserved linkage blocks occassionally was substantially rearranged.

The soybean is thought to be a "diploidized" tetraploid and many examples of duplicated genetic factors and duplicate loci are known. Polzin et al. (unpublished) showed that given adequate map resolution by genetic marker saturation these duplicated paralogous regions could be identified. These regions possessed considerable linkage conservation. The conclusion of these authors was that within the genome of an ancient tetraploid such as soybean, it is possible to transfer information between paralogous regions, from genetic rich regions to genetic poor regions. These conclusions are supported by the work of Funke et al. (1993) who also noted a high degree of sequence conservation between duplicated regions in soybean. This type of information has potential to enrich our understanding of gene expression of duplicated genes as well as our understanding of the genetics of multigenic agronomic traits.


The most economically important group of plants in the Cruciferae are in the genus Brassica (tribe Brassiceae) and include six cultivated species that are grown worldwide for several different uses. Three of the species are diploid (B. rapa, A genome, n=10; B. nigra, B genome, n=8; and B. oleracea, C genome, n=9) and three are amphidiploid (B. juncea, AB, n=18; B. napus, AC, n=19; and B. carinata, BC, n=17) which are believed to have arisen by interspecific hybridization of the diploid species. One of the most distinctive features of this genus is its wide range of morphological variation and end uses, including vegetables, fodder, oil and condiments. Even within species there is tremendous variation in form and uses. For example, B. rapa includes turnip, oilseed rape, Chinese cabbage and many other vegetable types.

One might expect this wide range of morphological variation to reflect a high level of DNA polymorphism. Indeed, Brassica species are among the most polymorphic of crop species surveyed. Not only are the different morphological types within a species highly polymorphic for both RFLP and RAPD markers, but cultivars within morphotypes also show extensive polymorphism (Diers and Osborn 1994; Figdore et al., 1988; Hu and Quiros 1991; Thormann et al., 1994). DNA markers have proved to be very useful for phylogenetic studies of Brassica and related genera. Results from RFLP analyses provide evidence for the evolutionary pathways of cultivated diploid forms from wild relatives (Song et al., 1990) and for the hybridization of specific diploid accessions to create amphidiploids (Song and Osborn 1992).

Genetic maps

This high level of DNA polymorphism accelerated the development of genetic linkage maps, and several maps are available for four of the Brassica species (Table 3). These maps consist mostly of RFLP markers, although some also include RAPD and isozyme markers. The numbers of marker loci for each map ranges from 49 to 360. Some of these maps have been developed independently by different researchers using different sets of marker loci. Therefore, the total number of marker loci mapped in Brassica species probably exceeds one thousand. An important future task is the integration of different maps so that researchers can have linkage information for a larger set of markers, and efforts toward this goal are currently underway (C. Quiros, personal communication). Use of alien chromosome addition lines which have been developed for some of the Brassica genomes (reviewed by Quiros et al., 1994) may help in this endeavor.

Several important themes emerged from inspection and comparison of Brassica genetic maps. One is that even diploid genomes, are highly duplicated. This was anticipated based on previous cytogenetic studies, but RFLP maps have added a large degree of precision to the analysis of genome duplication. All three diploid species contain duplicated RFLP loci, and some loci are present in at least four copies. The most detailed analyses of the arrangements of duplicated loci were reported for mapping populations of B. oleracea (Slocum et al., 1990) and B. rapa (Song et al., 1991). For these populations, over one-third of the DNA clones used detected replicated, segregating loci. Many of these loci were scattered throughout the genomes with no apparent conservation in linkage arrangement; however, a large portion were duplicated, or even triplicated, as conserved linkage blocks ranging from two to ten loci. There was no evidence from these, or any other studies, for duplication of entire linkage groups. Thus, if the diploid Brassica species have evolved as an ascending aneuploid series from a protype species of x=6, as hypothesized from cytological evidence (Prakash and Hinata 1980), there appears to have been extensive rearrangement of the replicated chromosomes.

A second theme emerging from mapping studies is that the overall length of the genetic maps in different Brassica species does not necessarily correspond to their nuclear genome size. This is most clearly illustrated for B. rapa and B. oleracea, which have very similar DNA contents but very different map lengths. Several factors can influence the overall length of a genetic map; however, the reported maps, which were developed by different researchers using different probes and different populations, are consistently larger for B. rapa than for B. oleracea. The three B. rapa maps with more than 100 marker loci range in length from 1785 recombination units to 1876 cM and are about twice as long as the four B. oleracea maps which range in length from 747 cM to 1127 cM (Table 3). These differences may be due to overall species differences in the frequency of recombination. Based on only one map, the diploid B. nigra appears to have a similar recombination frequency to B. oleracea. The amphidiploid B. napus, which consists of the A and C genomes, appears to have much less recombination than the sum of the diploid genomes; however, this comparison is based on fewer marker loci than present in the combined diploid maps.

A third theme that also has emerged from comparison of genetic maps is that Brassica chromosomes appear to have been extensively repatterned during evolution of the species. Linkage arrangement of duplicated loci within species has provided some evidence for this, but comparison between species of maps containing RFLP loci detected by the same set of clones has provided additional evidence. B. oleracea and B. rapa are closely related, produce viable but sterile hybrid progeny and differ in chromosome number by only one. Comparisons of linkage maps with common marker loci reveal extensive regions of conserved linkage arrangements (Osborn et al., 1991; McGrath and Quiros 1991; Slocum et al., 1990; Song et al., 1991; Teutonico and Osborn 1994). However, these comparisons also provide evidence for chromosomal rearrangements, such as translocations or inversions, after divergence of the species. Conservation of chromosomal integrity of these Brassica species appears to be much less than for other closely related species, such as tomato and potato (Bonierbale et al., 1988).

Maps with common marker loci also have allowed comparison of the amphidiploid B. napus to its hypothesized progenitor species B. rapa and B. oleracea (Honecke and Chyi 1991; Teutonico and Osborn 1994; Camargo 1994). As one might expect, there is evidence for extensive regions of conserved linkages; however, there also is evidence for rearrangements. These comparisons have not allowed identification of the A and C genome chromosomes in B. napus, and in fact, they suggest that these chromosomes as they exist in B. rapa and B. oleracea may not be intact in B. napus. Using a different strategy for genome comparison, Lydiate et al. (1993) have developed an RFLP map for a population from a natural B. napus crossed to a synthetic B. napus. This analysis allowed assignment of A and C genome linkage groups in natural B. napus and the results suggest that these genomes have remained relatively intact in B. napus.

Mapping trait loci

There are many useful and interesting traits in Brassica which could be better understood genetically, and perhaps manipulated in breeding programs, by using molecular markers. Mapping information for trait loci is only just begining to accumulate, but significant progress has been made in some areas (Table 3). An obvious target for these studies is morphological variation, and several genes controlling qualitative variation for morphology have been mapped in B. oleracea (Kianian and Quiros 1992; Landry et al., 1992) and B. rapa (Teutonico and Osborn 1994). However, much of the variation for morphology in Brassica is under polygenic control. Some of these quantitative trait loci (QTL) were identified by analyzing populations from crosses of very different morphological forms in B. oleracea (Kennard et al., 1994) and in B. rapa (Song et al., 1994). Although analyzed as QTL, alleles at many of the loci identified in these studies had very large effects, suggesting that major genes have played an important role in the evolution of morphological variation in Brassica. However, loci with small effects also were identified, and it is alleles at these types of loci that breeders have probably manipulated to fine tune the current forms of our cultivars. Vernalization requirement is an important component of morphological variation, and loci controlling this have been mapped in several studies (Camargo 1994; Ferreira et al., 1994b; Kennard et al., 1994; Kianian and Quiros 1992).

Another obvious target for mapping studies is disease resistance. In B. oleracea, QTL have been identified for clubroot resistance (Figdore et al., 1993; Landry et al., 1992) and for blackrot resistance (Camargo 1994). These diseases are sometimes hard to screen in a breeding program, and linked markers could prove useful for manipulating alleles from the resistance sources used in these studies. In B. napus, single major genes for cotyledon resistance to white rust and blackleg were mapped, along with field resistance to blackleg (Ferreira et al., 1994c and d).

Comparative chromosome organization of Brassica and Arabidopsis

Arabidopsis thaliana , n=5 (tribe Sisymbrieae), an extensively utilized model system in plant biochemistry, physiology, classical and molecular genetics, is often referred to as a close relative of plants within the genus Brassica. This relationship is further suggested by extensive conservation of coding sequences between Brassica and Arabidopsis (Lydiate et al., 1993). Comparative mapping of these genera is important because it will permit cross-utilization of tools and resources which have been developed for each and it will help us to understand the processes of evolution in greater detail. Moreover, use of the many cloned genes from Arabidopsis as RFLP probes in Brassica may provide insight on the possible function of these genes in regulating traits of interest in Brassica (Teutonico and Osborn 1994).

A comparative linkage map of the chromosomes of A. thaliana and B. oleracea has been constructed by applying previously mapped Brassica genomic DNA clones (Slocum et al. 1990) to two segregating populations of A. thaliana (Kowalski et al., 1994). Although extensive chromosomal rearrangements have occurred since the divergence of B. oleracea and A. thaliana, islands of conserved organization are discernible. At least one conserved region was detected on each of the five chromosomes. In total, 11 regions spanning 24.6% of the A. thaliana genetic map were closely-conserved with 29.9% of the B. oleracea genetic map. Chromosomal segments with an average length of 21.3 cM in A. thaliana were estimated to be uninterrupted by rearrangements distinguishing them from their order in B. oleracea. This calculation predicts that approximately 25 chromosomal rearrangements have occurred since divergence of these two species, at a rate of 2.5 rearrangements per million years since appearance of this plant family about 10 million years ago (paleopalynological evidence indicates that the plant order Capparales, including the families Capparaceae, Resedaceae and Cruciferae, first appeared during the upper Miocene, approximately 10 million ago; Muller 1981 and 1984). Relative to other plant species for which equivalent comparisons can be made, the chromosomes of B. oleracea and A. thaliana appear to have diverged relatively rapidly (see Kowalski et al., 1994). Chromosomal inversions appear to account for synteny of unlinked markers. Several DNA markers which are closely-linked in Brassica were found to be syntenic in Arabidopsis, but separated by intervening markers from other B. oleracea chromosomes or linkage groups. Inversion is the most likely means by which such markers have become separated (or joined). Syntenic markers at disparate sites on A. thaliana chromosomes were usually closely-linked in B. oleracea (Kowalski et al., 1994). This further supports the inference that such markers reflect localized regions of conservation between A. thaliana and B. oleracea, and that these regions are distinguished by inversions.

Two independent experiments suggest that ancient duplications have contributed to the present organization of the Arabidopsis genome. Kowalski et al. (1994) identified one region of chromosome 1 which may be homoeologous with a region of chromosome 5. McGrath et al. (1993) reported that three DNA probes detect RFLP loci duplicated on Arabidopsis chromosomes 1 and 5. Each of the duplicated regions are close to the respective homoeologous regions reported by Kowalski et al. (1994) based on anchor loci common to chromosome 1, and tightly linked reference loci on chromosome 5. In the McGrath et al. (1993) map, putative homoeologous regions of the genome may also be present between regions on chromosomes 2 and 3, and between regions on chromosomes 3 and 4. It must be noted that duplicate loci which contradict evidence of Kowalski et al. (1994) and McGrath et al. (1993) have also been reported, with duplications between chromosomes 1 and 3 (Hauge et al. 1993).

Based on analysis of organization of duplicated loci, it is clear that Arabidopsis and Brassica diverged from a common ancestor with less chromosomal duplication than B. oleracea. The relative orders of DNA markers along homoeologous chromosomal regions permit inference of whether specific chromosomal rearrangements predate, or postdate, duplication of Brassica chromosomes. A segment of chromosome 3 of A. thaliana spanning seven marker loci displays nearly complete linkage conservation with homoeologous regions on C8 and C3 of B. oleracea, except for two markers. Although these markers co-segregate on both C8 and C3 of B. oleracea, they are separated by a distance of 5.7 cM, and two other markers, in A. thaliana. The simplest explanation for this would be that the prototypical B. oleracea and A. thaliana chromosomes differed by a rearrangement in this region, and that chromosomal duplications then propagated this region in B. oleracea, i.e., the rearrangement predates duplication of the Brassica chromosomes. Sadowski et al. (1994) reported a complex of three tightly linked genes in A. thaliana, mapping to a single locus. Each of these probes map to duplicated loci in B. oleracea, co-segregating on one homoeolog, but with duplicated sites dispersed over three chromosomes. The simplest explanation for this would be that the prototypical B. oleracea and A. thaliana chromosomes showed close linkage of these markers, and that one B. oleracea homoeolog has been rearranged subsequent to duplication.

E. MALVACEAE: Cotton (Gossypium spp.)

Cotton is cultivated for production of spinnable fiber. The US cotton crop of ca. 18 million bales (218 kg/bale) has a value of ca. $4-6 billion/yr. Cotton was among the first species to which the Mendelian principles were applied (Balls 1906), and has a long history of improvement through breeding, with sustained long-term yield gains of 7- 10 kg lint/ha/yr (Meredith and Bridge 1984).

Cultivated cottons derived from four species, Gossypium hirsutum L., G. barbadense L., G. arboreum L., and G. herbaceum L., provide the world's leading natural fiber. Other wild relatives of cotton produce little or no fiber. Gossypium hirsutum accounts for about 90% of the world production. G. barbadense (Pima, Egyptian, and Sea Island cottons) fills a niche with high quality fibers that exceed those found in G. hirsutum germplasm. G. arboreum and G. herbaceum were the first cottons of world commerce, but today commercial production of diploid cotton is confined to India and Asia, and is primarily for domestic use.

Cotton is also the world's second most important oilseed. The use of cottonseed, or limitations in its use, are determined by its composition (Kohel 1989).


The genus Gossypium L. comprises about 50 diploid and tetraploid species indigenous to Africa, Central and South America, Asia, Australia, the Galapagos, and Hawaii (Fryxell 1979, 1992). Diploid species of the genus Gossypium all have 13 gametic chromosomes (n = 13), and fall into 7 different "genome types" , designated A-G based on chromosome pairing relationships (Beasley 1942, Endrizzi et al., 1984). A total of 5 tetraploid (n = 2x = 26) species are recognized, all of which exhibit disomic chromosome pairing (Kimber 1961). Tetraploid cottons contain two distinct genomes, which resemble the extant A genome of G. herbaceum (n = 13) and D genome of G. raimondii Ulbrich (n = 13), respectively. The A- and D-genome species diverged from a common ancestor about 6-11 million years ago (Wendel 1989). The A x D polyploidization occurred in the New World, about 1. 1- 1.9 million years ago, and required transoceanic migration of the matemal A-genome ancestor (Wendel 1989, Wendel and Albert 1992).

An extensive body of germplasm is maintained in the USDA Cotton Germplasm Collection (Percival 1987). The 5,000 accessions of G. hirsutum include wild and/or feral types collected in their native habitat, obsolete cultivars, and improved cottons. G. barbadense includes accessions collected in their native habitat, and improved cottons, for a total of over 2,000 accessions. The collection of cultivated diploids includes obsolete landraces to contemporary improved types; recent germplasm exchanges should increase this collection to about 2,000 accessions. Many wild diploids are not productive enough for routine maintenance, and have limited seed reserves or are maintained as live specimens (Percival, pers. comm.). Information regarding accessions and their availability are included in the Germplasm Resources Infon-nation Network (GRIN).

Evaluation of the cotton germplasm has included only limited numbers of accessions or traits that were readily measured. The wild diploids are difficult to grow and do not have fiber, so many desirable traits have no direct means for measurement. The tetraploids represent less of a problem, but perennial growth habits, late maturity, and photoperiodism makes screening difficult. Conversion programs for G. hirsutum and G. barbadense have begun (McCarthy et al., 1979; Percy, pers. comm.).

The Molecular Map of the Cotton Chromosomes

A detailed molecular map of cotton has recently been established (Reinisch et al., 1994), including the identity and ancestry of most cotton chromosomes, relationships among the chromosomes, and most of the rearrangements which distinguish corresponding (homoeologous) chromosomes.

The cotton map presently spans 4675 centimorgans (cM), representing 92-97% of the cotton genome. Among more than 1200 DNA probes examined with 4-6 restriction enzymes, 563 DNA probes revealed RFLPs at 705 loci, distributed at average intervals of 7.1 cM along the chromosomes. Among these, 683 (96.8%) have been assembled into 41 linkage groups of two or more loci, with the remaining 22 not yet linked to the map.

Mapped DNA probes included cloned genes and genomic DNA fragments, from several diploid and tetraploid cotton species. Low-copy DNA sequences from the A, D, and AD genomes have not diverged extensively, as genomic probes from each source readily detect genomic fragments across all genomes. Recent work has added sequence-tagged microsatellites (Zhao et al., 1994) and tandemly-repeated DNA elements to the map ( Zhao, Dong, and Paterson, unpubl.).

The map is based on 57 F2 progeny of a cross between single individuals of G. hirsutum race 'palmeri' and G. barbadense acc. 'KlOl'. These accessions were selected because they are relatively free from the interspecific introgression that characterizes cultivated types (Percy and Wendel 1990, Wang, Dong, Paterson, submitted), as well as some wild populations of these two species from overlapping portions of their indigenous ranges (Brubaker et al., 1993, Percy and Wendel 1990).

Cytogenetic Stocks, and Assignment of Linkage Groups to Chromosomes

Tetraploid cotton has the ability to tolerate haplodeficiencies, but no nullisomics have been identified. Therefore, cytogenetic aneuploids are represented by primary monosomes, which have one chromosome in the pair missing, or telosomes (monotelodisomes), which have one arm of a chromosome pair missing. Monosomes have been identified for 15 of the 26 chromosomes and 29 telosomes have been identified that include one arm of 4 additional chromosomes (Endrizzi et al., 1984). Translocations are available that involve 25 of the 26 chromosomes of cotton. Through the use of cytogenetic markers all 26 chromosomes are marked in at least one arm (Endrizzi et al., 1984).

To integrate the molecular and cytogenetic maps, a subset of the mapped DNA probes were applied to monosomic and monotelodisoniic substitution stocks, each with a single G. barbadense chromosome substituted for one pair of G. hirsutum chromosomes. Based on multiple genetically linked loci, the linkage groups which correspond to chrs. 1, 2, 4, 6, 9, 10, 17, 22, and 25 have been determined (Reinisch et al., 1994). The identity of chrs. 5, 14, 15, 18, and 20 is suggested by single loci, which are neither corroborated nor contradicted by any other locus on the linkage group. Three pairs of (tentatively) identified chromosomes showed homoeology, chrs. 1 and 15, chrs. 5 and 20, and chrs. 6 and 25. In each case, these homoeologies are corroborated by classical genetic analysis of mutant phenotypes (Endrizzi and Ramsay 1979, Endrizzi et al., 1984). Additional aneuploid stocks are being characterized to verify results to date, and to determine the chromosomal identity of additional linkage groups.

Deducing the Ancestry of Linkage Groups in Allotetraploid Cotton

Many valuable traits might be transferred to cultivated cottons from wild relatives, especially wild diploids. Consequently, it was important to determine the diploid genomic origin of linkage groups (chromosomes) in the cotton map. Some DNA probes detected genomic fragments in tetraploid cottons which were shared with either A- or D-genome ancestors, but not both. Based on these "alloallelic" loci, the genomic origin of 33 of the present 41 linkage groups, including all of the identified chromosomes, was determined (Reinisch et al., 1994). In 100% of cases, the majority of alloallelic information for a chromosome coincided with prior classical assignment of chromosomes to genomes (based on pairing in diploid x tetraploid hybrids; A = chrs. 1-13; D = chrs. 14-26).

Unravelling the History of Cotton Evolution Based Upon Duplicated loci

To better focus future efforts in cotton improvement, it was important to gain a better understanding of the history of cotton evolution. The distribution of linked duplicated loci across the map reveals strong evidence for a recent (ca. 1-2 million yrs ago) chromosomal duplication event in cotton, and tenuous evidence of a second, earlier event (Reinisch et al., 1994). Evidence for duplication of at least 23 of our 41 linkage groups, covering 1668 cM (36% of the genome) and including 11 of the expected 13 pairs of homoeologs, has been described (Reinisch et al., 1994). Further mapping is likely to show that the entire genome was duplicated in this event. All except two homoeologous chromosome pairs in n = 26 cottons show one or more rearrangements of gene order as based on present data.

While most duplicated loci mapped in "tetraploid" (n = 26) cotton can be accounted for by this relatively recent event (1.1-1.9 million years ago), new results support a classical theory that "diploid" (n = 13) cottons may be "paleopolyploids", derived from an earlier event involving ancestors with fewer chromosomes (Reinisch et al., 1994). This putative n = 6-7 to n = 13 transition must have antedated the evolution of the genus Gossypium (estimated to be at least 25 million years old; Wendel and Albert 1992), and indeed, must have antedated the entire tribe Gossypieae and the closely-related tribe Hibisceae, where all genera have high gametic chromosome numbers (Fryxell 1979).

Prospects for map-based cloning of agriculturally important genes in cotton and other polyploids

Several complications associated with map-based cloning in disomic polyploids are partly compensated for by unique advantages of polyploid genomes such as cotton, soybean, wheat, oat, canola, tobacco, peanut, and others.

The physical amount of DNA in cotton is not prohibitive to map-based cloning -- however, the lengthy genetic map will require a large number of markers in order to be sufficiently close to most genes for "chromosome walking." The average physical size of a centimorgan in cotton is about 400 kb (Reinisch et al., 1994), only moderately larger than that of Arabidopsis (ca. 290 kb), and smaller than that of tomato (ca. 600 kb), both species in which map-based gene cloning has been accomplished. However, even with the advantage afforded by homoeologous information, the cotton map of 5000 cM (Reinisch et al., 1994) will require ca. 3000 DNA markers to map at average 1 cM density, and the physical genome of 2246 Mb will require ca. 75,000 YACs/BACs of average size 150 kb for 5x coverage.

Map-based cloning in polyploids such as cotton introduces a new technical challenge not encountered in diploids, e.g. virtually all "single-copy" DNA probes occur at two or more unlinked loci. This makes it difficult to assign YACs (or other large DNA vectors) to their site of origin. However, interspersed repetitive DNA elements, which differ between the two genomes of tetraploid cotton, may provide a means of determining the genomic identity of individual YACs from tetraploid cottons (Zhao, Wing, Paterson, submitted). Such an approach may prove generally applicable to map-based cloning in other major crops, many of which are disomic polyploids (e.g. soybean, wheat, oat, canola, tobacco, peanut, and many others).

Application of DNA Markers to Cotton Improvement

The cotton RFLP map is a starting point for use of DNA markers to identify and manipulate determinants of agricultural productivity and quality. Historically, introgression has been practiced to transfer desirable traits into cultivated cottons. Such introgression events may be detectable using existing DNA markers, including transfer of numerous genomic regions from G. hirsutum into cultivated G. barbadense ( Wang, Dong, and Paterson, submitted), as well as introgression of specific traits such as Verticillium wilt resistance (Staten 1971), bacterial blight resistance (Staten 1971), nectariless leaves (Meyer and Meyer 1961, Tyler 1908), restoration of cytoplasmic male-sterity (Meyer 1975, Weaver and Weaver 1977), and improved fiber quality (Culp and Harrell 1974, Culp et al., 1979). Rust resistance was transferred (Blank and Leathers 1963), but has limited importance, and is not widely used. Other traits such as nematode resistance (Yik and Birchfield 1984) and unique natural products have been identified (Balls 1906) in wild diploids. Efforts to introgress quantitative traits, such as fiber properties, have had limited success (Meredith 1984).

The availability of a detailed molecular map of cotton affords opportunities to pursue comprehensive mapping of both simple and complex traits, by well-developed strategies (cf. Paterson et al., 1988).

As in many predominantly self-pollinated crops, the gene pools of each of the cultivated cotton species show only modest levels of DNA polymorphism. While the large number of DNA markers now mapped in cotton partly compensates for this limitation, routine application of DNA markers to cotton breeding may benefit from new technologies such as microsatellite-based DNA markers, which are being superimposed on the existing RFLP map (Zhao et al., 1994) to create a unified body of information on cotton genetics and evolution.

A detailed map of DNA markers offers the opportunity to utilize the polymorphic genus Gossypium and its diverse relatives such as Hibiscus (kenaf, roselle) and Abelmoschus (okra), to investigate plant chromosome evolution in exquisite detail, and to have a major impact on improvement of one of the world's oldest and most important crops.


Comparative Mapping in the Family Solanaceae

The family solanaceae (nightshade family) contains a number of economically important plant species including tomato, pepper, potato, eggplant, petunia, and tobacco. The majority of nightshade species have a basic chromosome number of x = 12. Comparative linkage maps have now been constructed for three of these species - tomato, potato, and pepper (Bonierbale et al., 1988, Tanksley 1992, Prince et al., 1993). The results from these comparative maps reveal several interesting aspects of plant chromosome evolution.

Speciation and morphological differentiation are not always accompanied by major genome rearrangements

Tomato and potato are well differentiated species and are sexually incompatible. Nonetheless, the genetic content and chromosomal organization of tomato and potato are nearly identical. Comparative maps reveal no interchromosomal rearrangements (e.g. reciprocal translocations). The only apparent gross differences between the genomes are five paracentric inversions (chromosomes 5, 9, 10, 11, and 12). Four of these involve short arm inversions (chromosomes 5, 9, 11, 12) while one (chromosome 10) involved a long arm inversion. The high level of conservation in linkage of tomato and potato permits easy cross use of probes for genome mapping between these two species.

Breakpoints for chromosomal rearrangements often occur at or near centromeres

All of the inversions that differentiate the tomato and potato genomes appear to involve a break point at that chromosomal location of the affected chromosome, resulting in an inversion of the entire chromosome arm. In no instances could a second breakpoint for an inversion be seen in the distal part of the arm, indicating that the entire arm had been inverted (fig. 2). Genome studies in tomato show that telomeres and centromeres share some repetitive DNA sequences which may involve occasional recombination events which result in the inversions of entire chromosome arms as found in tomato and potato (Tanksley 1992).

Pepper is more distantly related to tomato and potato and has a higher nuclear DNA content. While there are many more chromosomal rearrangements differentiating the pepper genome from the tomato and potato genomes, conserved linkage blocks can still be observed and these often correspond to segments of chromosomes with putative break points at or near centromeres (Prince et al., 1993, fig. 2).

Gene repertoire is more conserved than gene order

The most conserved feature of the tomato, potato, and pepper genomes is the gene content. Cloned genes from any one of these species usually cross hybridize with orthologous gene copies in each of the other species. The level of gene conservation (based on cross hybridization with cDNA clones) is greater than 99% for tomato and potato and greater than 90% for most solanaceous species (e.g. tomato, pepper, potato, petunia, tobacco, etc) (Zamir and Tanksley 1988). The high degree of gene conservation makes cDNA clones ideal for comparative genome mapping in these species.

Application of comparative maps in the Solanaceae

Molecular mapping of nightshade species has advanced dramatically in the past 10 years. These maps and their associated technology have now been used successfully for a number of applications in plant breeding and genetics including: 1) characterization of genetic variation in germplasm collections, 2) gene tagging (i.e. identification of markers tightly linked to major genes), 3) map-based gene cloning, and 4) analysis of quantitative traits. The ability to cross use probes has accelerated genome applications in nightshade species - especially potato and pepper for which the tomato genetic map has offered a source of probes whose homoeologous chromosome positions can often be identified through use of comparative genetic maps. It is likely that a more synergistic relationship will develop between breeders and geneticists of these crop species since they are now tied together through common mapping information. We can also expect that in the near future comparative genetic maps will also be available for other nightshade species including petunia, tobacco, and eggplant.


Genetic Mapping in Forest Trees


There are many aspects of genome mapping research in forest trees which parallel genome mapping in agronomic crops, for example the types of markers used, methods of linkage analysis, and some of the applications of genetic marker technology. There are however many unique aspects to genome mapping in forest trees which will be the focus of this section. Several more comprehensive reviews of genome research in forest trees have been written (Neale and Williams 1991; Grattapaglia et al., 1993; Neale and Harry 1994).

Trees, unlike most crops, are long-lived perennial plants. Generation times are long and multigeneration pedigrees are rarely available. Most species are difficult to self-pollinate and inbreeding depression is common, thus typical mapping pedigrees such as F2s or backcrosses are generally not used. Trees are also highly genetically variable so mapping populations are constructed from matings among highly heterozygous parents.

Forest tree species are found in both the angiosperms and gymnosperms. Taxa of great interest in the angiosperms include Populus and Eucalyptus. Within the gymnosperms the pines (Pinus) predominate but spruces (Picea), firs (Abies), larches (Larix), and Douglas-fir (Pseudotsuga) are also important. An interesting but challenging aspect of conifer genome research is the size of their genomes. C-value estimates range from 20-30 pg among pines (Wakamiya et al., 1993). One theory for the large genomes of pines is that they appear to have exceptionally large gene family sizes based on Southern blot analysis (Kinlaw and Gerttula 1993; Devey et al., 1994).

Reasons similar to those for crop species exist for constructing genetic maps in forest trees; e.g. understanding genome organization and evolution, gene and quantitative trait mapping and marker-aided breeding. In contrast to most crops however, trees are relatively undomesticated and are grown in wildland environments. There is an important need to monitor changes in genetic diversity in these populations as they are effected by human intervention and global climate change. Tree genome research will play an important role in solving these practical forest management problems.

Genetic mapping.

Genetic maps have been constructed for a number of forest tree species and a variety of approaches have been employed. The first mapping projects in forest trees were based on RFLP markers and mutigeneration pedigrees. Devey et al. (1991, 1994) mapped 73 RFLP loci to 20 linkage groups (N= 12) using 65 cDNA and 3 genomic DNA probes in a three-generation outbred pedigree of loblolly pine (Pinus taeda L.). Groover et al. (1994) subsequently constructed a second RFLP map for loblolly pine using many of the same DNA probes used in the earlier study. Genetic maps were constructed for both the female and male parent of the mapping population and were used to demonstrate that the rate of meiotic recombination is slightly greater in the male versus the female in loblolly pine (Groover et al., 1995). The two loblolly pine RFLP maps are currently being integrated to form a consensus map.

Bradshaw et al. (1994) have constructed a detailed map for Populus using RFLP, STS, and RAPD markers in an F2 population derived from a hybrid cross between P. trichocarpa and P. deltoides. Populus is dioecious thus the F2 resulted from a full-sib mating of two Fl plants. A total of 343 markers were mapped to 25 linkage groups (N=19). The Populus mapping project has lead to some intertesting basic biology. Bradshaw and Stettler (1994) demonstrated that segregation distortion at one linkage group was due to the presence a linked recessive allele in one of the progeny homozygous classes. An RFLP map has also been constructed for a second species of Populus, trembling aspen (P. tremuloides Michx.). Liu and Fumier (1993) mapped 54 RFLP and 3 arozyme loci to 14 linkage groups (N=19) using genomic DNA probes from trembling aspen.

Although RFLP markers are highly informative for most applications in forest trees, very few forest genetics labs have used this technology because of the technical difficulty of RFLPs with large genomes and the slow rate of data aquisition. The development of the RAPD marker system (Williams et al., 1990) profoundly changed the view of many researchers towards the feasibility of genetic mapping in trees. The speed and ease of RAPDs was obvious, but more so for tree geneticists was the ability to perform RAPD assays and construct genetic maps using the haploid megagametophyte tissue of conifer seeds. Tree geneticists had long taken advantage of this unique genetic system in conifers to establish inheritance and linkage relationships among allozyme loci and to study the population genetics of conifers. Carlson et al. (1991) first reported on the inheritance of RAPD markers in a conifer, however this study was based on segregations in diploid Fls of a controlled mating of Douglas-fir (Pseudotsuga menziessii). In a subsequent paper, this group reported on the construction of a RAPD map in white spruce (Picea glauca) based on megagametophyte segregations from a single mother tree (Tulsieram et al., 1992). Since then single-tree RAPD maps have been reported for a number of conifers (Nelson et al., 1993; Binelh and Bucci 1994). These RAPD maps will generally be used for QTL mapping and for marker aided breeding.

RAPD maps have also been developed in angiosperm forest tree species. Grattapaglia and Sederoff (1994) used a "two-way pseudotestcross" mapping strategy to construct maps for both the female and male parent of a hybrid cross of E. grandis x E. urophylla. These maps had 240 markers in 14 linkage groups and 251 markers in 11 linkage groups, respectively.

Quantitative Trait Mapping in Forest Trees

Most traits of economic interest in forest trees are quantitatively inherited; for example height growth, volume, wood density, and bud phenology. Unlike many crop species, there are almost no traits of interest which are known to be caused be single genes (see the discussion of disease resistance mapping below for an exception) and mutant stocks have never been developed for forest trees. Thus, the demonstration that QTLs could be mapped in plants (Paterson et al., 1988) was met with great enthusiasm by forest geneticists. Groover et al. (1994) mapped five major QTLs for wood specific gravity in loblolly pine using a large F2 family from a three generation outbred pedigree. They used RFLP markers so in cases where the linked RFLP marker segregated for more than three alleles (fully informative marker) it was possible to estimate the number and relative effects of the QTL alleles segregating in each of the two parents.

Information of this type will be valuable if the markers are to be used in a marker breeding application in a full-sib but outbred mating design.

QT'Ls have also been mapped in interspecific crosses of two angiosperm species. Bradshaw and Stettler (1995) mapped QTLs for a number of growth and adaptative traits in an F2 population of a Populus trichocarpa x P. deltoides hybrid. In several cases, a small number (1-5) of QTLs explained a very large percentage of the total genetic variance for a quantitative trait. These results demonstrate that the purely polygenic and additive model for inheritance of growth and adaptative traits in trees may not be appropriate. The high proportion of genotypic variance attributed to a few QTLs should be not be generalized to intraspecific crosses because these data are from interspecific crosses where linkage disequilibrium is expected to be high.

In Eucalyptus, Grattapaglia (1994) mapped QTLs for traits related to vegetative propagation, growth and wood properties. QTLs for vegetative propagation traits were mapped using RAPD markers and the "pseudotestcross" strategy in a E. grandis x E. urophylla hybrid cross. It was shown that shooting responses are inherited from E. grandis whereas rooting responses are inherited from E. urophylla. The growth and wood property QTLs were mapped in half-sib families from E. grandis.

Mapping of Disease Resistance Genes

Protection from disease and insects is an objective of many forest tree breeding programs. A quantitative genetic approach to breeding for resistance has most always been applied and progress has been made (Carson and Carson 1989). It has only been recently however that gene-for-gene relationships have been identified and that this theory has been applied to breeding for resistance. One of the most destructive pathogens of forest trees are the pine stem rusts (Cronartium). Fusiform rust (C. quercuum) attacks pines of the subsection Australes in the southeastern United States. Research has been initiated to identify and map fusiform rust resistance genes in lobolly pine (Wilcox et al., 1993) and slash pine (P. elliottii Engelm.) (Nance et al., 1992; Nelson et al., 1993). Gene-for-gene relationships have been established in both species and significant progress towards mapping resistance genes has been made.

A second important pine rust is white pine blister rust (C. ribicola Fisch.) which attacks members of the Section Strobus (white pines). In a pioneering study, Kinloch et al. (1970) discovered a single dominant gene for resistance in sugar pine (P. lambertiana Dougl.). Later, a gene-for-gene relationship with the rust was demonstrated (Kinloch and Comstock 1981). Based on the well characterized genetics of resistance in sugar pine, Devey et al. (1994a) recently mapped the dominant resistance gene, R. Their strategy employed haploid genetics, RAPD markers, and bulked segregant analysis (Michelmore et al., 1991). Ten linked RAPD markers were identified; the closest being 0.9 cM from the R. These markers may ultimately assist in the cloning of this gene.

Gene Sequencing

Tree molecular geneticists have cloned, sequenced and studied the expression of a wide array of genes (see review by Davis et al., 1995). These efforts have largely been one gene at a time using standard "cloning by homology" or "reverse genetic" approaches. The Human Genome Project has led to an alternative approach to identifying genes based on automated sequencing of anonymous cDNAs (Adams et al., 1991, 1992). In plants, this approach has recently been applied to rice (Uchiiniya et al., 1992), Arabidopsis (Hofte et al., 1993; corn (Keith et al., 1993) and Brassica (Park et al., 1993). Tens of thousands of cDNAs have already been sequenced and several thousand have been identified based on homology searches to databases. A gene sequencing project has recently been initiated at the Institute of Forest Genetics. Approximately 200 cDNAs, which had previously been used as RFLP mapping probes (Devey et al., 1994b; Groover et al., 1994), have been sequenced. Identities were determined for approximately 30% of the cDNAs (Kinlaw et al., 1995). In the future, random cDNAs will be sequenced from tissue and developmentally specific libraries.

Marker-aided Breeding and Selection

The potential of marker-aided breeding (MAB) and/or marker-aided selection (MAS) in forestry has been hotly debated over the last few years. The potential for MAB/MAS with inbred agricultural crops and backcross breeding has been firmly established, however, it is not certain that MAS/MAB could be applied to highly heterozygous and outbred plants such as forest trees. In their review, Neale and Williams (1991) identified three potential limitations; (1) polygenic inheritance of economically important traits, (2) genotypic x environment interactions, (3) linkage equilibrium conditions between marker alleles and QTL alleles. In June of 1991 a symposium was organized to debate the pros and cons of MAB/MAS (Tuskan 1992 and papers therein). In a thorough review on this topic, Strauss et al. (1992) identified additional limitations to MAB/MAS such as; (1) high cost, (2) QTL x genetic background interactions, and (3) changes in QTL genes frequencies over generations.

Opinions among the symposium participants ranged from highly optimistic to completely pessimistic; the only consensus reached was that empirical data was needed before MAB/MAS could be fully evaluated for application in forestry.

In the last two two years several developments have occurred that provide optimism for MAB /MAS in forestry. First, it has been demonstrated that QTLs of major effect can be identified for economic traits (Groover et al., 1994; Grattapaglia 1994; Bradshaw and Stettler, 1995) and that inheritance of such traits is not strictly polygenic and/or additive. Second, the problem of linkage equilibrium can be overcome if marker and QTL allele phase relationships can be determined for all members of a breeding population. These relationships, however, are best determined in experimental populations where genetic segregation of the quantitative trait has been maximized. Once marker-QTL phase relationships are determined for members of a breeding program then this information can be used to guide breedings in an applied breeding program. This task is possible with highly-informative RFLP markers (Groover et al., 1994) but is not likely to be cost effective. RAPD markers are less informative but are much more cost-effective for genotyping large numbers of individuals (Grattapaglia et al., 1993). Clearly, more empirical testing is needed to identify the best strategies and opportunities for MAB/MAS in forestry.



The Plant Genome Database (PGD) is actually a suite of several information products

produced at the National Agricultural Library (NAL) in collaboration with the Agricultural

Research Service and Forest Service species coordinators. The species groups initially consisted of wheat (which soon expanded to the Triticeae), soybean, maize, and lobolly pine (which has expanded to include other conifers). Arabidopsis was added soon after. At present, the Solanaceae, rice, and Chlamydomonas are included, and cotton and sorghum will be added in the near future. Expansion to include other species will continue. The products include a gopher server (PGD/Gopher), a World Wide Web server (PGD/WWW), a CD-ROM (PGD/CD), an electronic mail query server (PGD/Email) and an anonymous ftp server (PGD/Ftp). These information products along with their evolution will be discussed. The species coordinators are responsible for collecting, organizing, and evaluating data for their respective species into separate databases. These databases are discussed elsewhere in this article; however, a description of the software used by the majority of the coordinators, ACEDB, is presented below.


During the initial phases of the database project a number of site visits were made to

locations which were already producing similar databases. Several were involved in the

Human Genome program including the GDB at Johns Hopkins, Lawrence Berkeley Labs,

Lawrence Livermore Labs, and the Los Alamos National Lab. Site visits were also made to the National Center for Biotechnology Information at the National Library of Medicine and to two private companies; Agrigenetics and DuPont. These visits were useful with respect to database design and to hardware and software selection.

The primary goal of the first two and one-half years of the project was to develop a working prototype of an integrated genome database for plants. The focus would then change to releasing the database to the users, to reevaluating the initial design and to redesigning portions of the database where necessary and to start forging tighter links to external data sources. The goals and timetable have been followed closely although the number of information products has increased significantly over what was anticipated.

Discussion of the PGD Information Resources

The initial phase of the design development consisted primarily of deciding the scope of the database. It was decided that the core of the database would consist of maps and loci along with alleles, probes, phenotypic traits, gene products, and metabolic pathways. It was also deemed essential that this information be linked with existing information such as germplasm (via the USDA Germplasm Resources Information Network), and sequence data (Genbank/EMBL/DDBJ and SwissProt/PIR) as well as NAL's AGRICOLA bibliographic database.

As database designing was taking place not only at NAL, but also at the species group level, it was decided to hold review meetings approximately every three months in order to exchange ideas about how to achieve an optimal design and to ensure that all collaborators were maintaining design compatibility. A decision was made early on not to enforce a single design for two reasons: 1. one design was not necessarily optimal for all groups, and 2. as the goal was to eventually include data from many additional sources it was necessary to develop a paradigm for integrating data which would likely be formatted in many different ways. Therefore, a major design goal was to develop a generic mechanism which would allow data formatted in multiple ways to be accessed in a consistent manner. Initially, it was assumed that this would require a centralized relational database, but with the advent of new data delivery mechanisms on the Internet, particularly the World Wide Web (WWW), gopher, and WAIS, this approach was replaced by one in which databases are "federated", that is, they remain separate entities, but are accessed as if they are a single entity. This paradigm allows such extreme flexibility that a new database with a unique data model can be integrated into this system in less than an hour. Also, species database curators can alter their data models at will without worrying about the impact to PGD.

Gopher and WAIS caused a virtual information explosion in 1992. A complete description of gopher, WAIS, Mosaic, and WWW is beyond the scope of this document. Further information, including how to obtain and install gopher and WWW clients, should be obtained from your local computer center or network "guru." Gopher uses a menu-oriented paradigm and a simple protocol to allow the user to access text documents, files, and images. When coupled with WAIS, it provides full-text searching of data files. PGD/Gopher provides access to all of the plant genome data as well as the retrieval of AGRICOLA records. Although gopher is simple to use, it is limited in the ways that data can be retrieved and presented. Figure 3 shows a menu available through PGD/Gopher.

A more recent and more important addition to data retrieval via the Internet has been WWW. It is similar to gopher in that it uses a simple protocol to allow users to navigate through the "web" of information available on the Internet. It is, however, more sophisticated and flexible than gopher, primarily due to its use of hypertext links and, with the appropriate WWW viewer, in-line graphics (e.g. genetic maps) and a point-and-click method of navigation. Most viewers including the most popular one, Mosaic, also "understands" the gopher, WAIS, and ftp protocols. Versions of Mosaic exist for Unix (several flavors), MS-Windows, and Macintosh. See Figure 4 for an example of a screen from PGD/WWW.

PGD/WWW, besides providing for simple database navigation, also gives the user several options for data retrieval including fuzzy and WAIS searching. When one of these options is selected, the user is presented with a form into which the search criteria are entered. Simple searches, as well as boolean and wildcard searches can be carried out. Fuzzy searching, in which mismatches (insertions, deletions, or substitutions) are allowed, is particularly useful in cases where the exact spelling of a search term is not known (e.g. a person's name) or to accommodate slight differences in nomenclature among species databases. An example of the latter is the symbol for alcohol dehydrogenase 1 which might be either adh1 or adh-1 depending on the database of origin. Either symbol could be used as a search term for fuzzy searching and all records containing either of these symbols would be retrieved. WAIS searching is provided as an alternative for those who are more familiar with its capabilities or for those who do not require fuzzy searching. In either case, the user can select which database, or combination of databases, to search. Also, the user can choose to search all plants or all grasses.

One major advantage of the WWW that is used extensively in PGD is the ability to link to external data sources on the WWW. A simple example: If a database curator provides an accession number for a SwissProt protein sequence anywhere in a database object, a link is made directly from that object to the ExPASy WWW server in Geneva where SwissProt is maintained. By clicking on that link, the user retrieves the full SwissProt sequence record. In addition to SwissProt, links are provided in PGD/WWW to Genbank/EMBL/DDBJ, GRIN, AGRICOLA, dbEST, Enzyme, Plant Variety Protection data, and Mendel (Commission on Plant Gene Nomenclature database). It is anticipated that many additional links, such as to metabolic pathways data, will be made in the future.

The PGD/CD (the initial prototype was pressed in April, 1994 - the first release will be in January, 1995) contains a version of the database which is similar to PGD/WWW, that is, browsable with a WWW client. Navigation through the data is also accomplished via hypertext links. Three versions of the Mosaic viewer are included on the CD. Although lacking in the prototype, subsequent CD's will contain full-text searching. It should be noted that PGD/CD is, of necessity, not updated nearly as frequently as other versions of PGD and should only be used if Internet connectivity is not available to the user.

PGD/Email is an electronic mail server that allows users to query the plant genome database by sending electronic mail to the server. This allows searching for people who may have an electronic mail gateway to the Internet, but who are not directly connected to it. Also, those who are directly connected may have slow or otherwise poor Internet connections may prefer to use this method. The results are returned to the user by electronic mail.

PGD/Ftp allows users to use anonymous ftp to retrieve certain data. All of the species databases are available in native ACEDB format. Many graphical images, mainly in gif and jpeg formats are also available. Additional data and tools will be deposited in the anonymous ftp directories in the future.

All of these resources are changing rapidly and more up-to-date information can be found by accessing the particular resource. This information is given in the next section.

Accessing the PGD Information Resources

Regardless of which of the various PGD resources is being accessed, the user should always consult the README, ABOUT or HELP files to learn about that particular resource. Also, WHAT'S NEW files are included when applicable. Technical help for any of the resources can be obtained by sending an email message to or by calling 301-504-6813. Database content questions or comments should be addressed to the curators for a particular species database.

PGD/Gopher: Host - Port - 70


PGD/Email: Send an electronic mail message with only the word help in the body to

PGD/Ftp: Ftp to Login: anonymous Password: [your

electronic mail address]

PGD/CD: Send electronic mail to or call 301-504-6613 for



A major challenge facing the research community is how to present and integrate complex and rapidly accumulating data. Unfortunately the solution--the development of specialized "genome" databases--has come about more slowly than anticipated. One problem is that resources are limited; a full-fledged database design and implementation team using a commercial database management system can easily consume over $1 million per year for software, personnel, and hardware. Second and more critical, a new group desiring to "clone" an existing database is faced with software licensing fees and the need to hire expensive experts for maintenance and to make modifications. These factors discourage the reuse and proliferation of database technology even though user demand for it is greater than ever.

Recently a product that largely overcomes these problems has become available to biologists. ACEDB, "A C. elegans Data Base", was created in 1991 by Jean Thierry-Mieg and Richard Durbin (1991) to represent information for the C. elegans genome project. In the short time since then it has been adopted by a dozen different genome projects and is in use at over a hundred research sites worldwide. The rapid acceptance of ACEDB-based genomic databases is due to several attractive features: the software is free and includes a sophisticated graphical interface immediately capable of displaying genetic maps (see Figure 5), physical maps, sequences, and any text-based biological information. The software can also present scanned images such as autoradiograms and photographs. Finally, reconfiguration for a new species is straightforward and requires no computer expertise. Thus biologists can initiate and control the entire database development effort from prototyping to public release. This has vastly accelerated the rate at which new databases appear.

Users favor the software because data is accessible for casual browsing as well as by formal query. Browsing is supported by a hypertext interface, similar in spirit to HyperCard applications on the Macintosh. Most objects that appear on the screen--locus symbols, lines representing cloned DNAs, names of stocks, people, sequences, publications, and so forth--are sensitive to the mouse. Users traverse links between information by clicking with the mouse. The related information appears in a new window which itself will have hypertext links.

ACEDB is available via Anonymous FTP from several sites. The major site for the software in the United States is ( in /repository/acedb. Fully-loaded databases are available from ( in /pub/ACEDB.databases. ACEDB runs on the Macintosh and many Unix systems, under X11: any machine running SunOS 4.x, e.g. Sun SPARCstation 1, 1+, 2, IPC, IPX; any machine running Solaris; DEC DECstation3100, 5100 etc.; DEC Alpha/OSF-1; Silicon Graphics Iris series; PC 386/486 with Linux (public domain Unix).

Information about ACEDB can be obtained via Anonymous ftp from several on-line sources (Cherry and Cartinhour, 1993; Dunham et al., 1993). An introductory manual (Cartinhour et al., 1992) is available free. In addition a Usenet/Biosci conference ( has been established. Extensive documentation on ACEDB can be found on PGD/WWW.


Plant genomic research is here to stay. The future looks excellent. The advancements made during the last decade in gene mapping and associated research activities permits optimism. This tendency toward a hopeful outlook is justifiable based on the results to date.

Finally, it is becoming evident from genomic research that geneticists can increase their understanding of genotypes and related gene expression processes. They have the tools to learn how genotype x environment interactions work and how to use that information to productively manipulate quantitative characters in breeding schemes. The capabilities of handling single gene traits by plant breeders are more effective than ever before with the new molecular techniques. Molecular Map Markers or Marker Assisted Selection gives the breeder increased research power and precision. This new strength hastens finding and manipulating genes that code for desirable traits over the use traditional phenotypic selection.

Besides precision, the new methods speed up the breeding process by reducing the time it takes to develop a new cultivar with desired traits. Concurrent with time, reductions in expenditures are evident. This occurs even when considering the initial high of cost start-up for equipment and chemicals for a molecular biology laboratory. As new tools develop, the breeders will enhance and expand their capacities to address breeding problems and develop solutions. The challenges facing the breeder are still the same, e. g. disease and pest resistance, yield enhancement, increased tolerance to abiotic stresses such as heat, drought, and salt. This battle has been conducted for hundreds of years. The difference now is speed of the counter attack against those ever present obstacles. Further, rapid instrument throughput of experimental data and the incorporation of digital information into a readily accessible open database hastens development of research results. It is also becoming evident that future laboratory and field experiments will require use of a computer, i.e., recording results lab trends is over.

Genomic research is bridging the gap by serving as catalyst between basic and applied genetics. That gap also contains plant physiologists/biochemist, as they also use molecular tools to address genes/gene systems/domains that regulate primary and secondary metabolism that form wanted products and increased understanding of processes and functions in plants. The future will yield a continuous spectrum of plant science research from the most fundamental molecular to applied efforts. There will be systems development that will encompass vertical integration of agricultural industry from before and after the farm gate to processing, new farm and non farm products, retailing and exports. This kind of approach is necessary to keep US agriculture competitive in the domestic and foreign markets. Plant genome research will play a critical role in advancing agriculture.


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