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Follow on from Compositae Whitepaper Meeting
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|
Taxon |
Genome size 1C (Gb and pg) |
|
Arabidopsis thaliana1 |
0.16 / 0.16 |
|
Leontodon taraxacoides spp. taraxacoides2 |
0.29 / 0 .30 |
|
Leontodon taraxacoides spp. longirostris2 |
0.33 / 0.34 |
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Oryza sativa3 |
0.49 / .50 |
|
Lactuca sativa4 |
2.6 / 2.7 |
Helianthus annuus5 |
3.5 / 3.6 |
1Bennett et al. (2003), 2E. Baack & L. Rieseberg, unpublished; 3Uozu et al., (1997), 4Michaelson et al., (1991), 5Price et al., (2000).
No estimate of genome size is currently available for safflower (2N = 24).
Current Resources
Genetic stocks
The International Lactuca database reports over 12,028 accessions worldwide; however, there is considerable overlap among the collections (www.cgn.wur.nl/pgr/collections/ildb/). The Center for Genetic Resources, Wageningen, NL includes 2,429 lettuce accessions, including 1168 cultivars, 896 wild species, and 201 landraces. Smaller collections are housed in Prague, Czech Republic (1,328 accessions), Pullman, WA (1,315), Davis, CA (1,200), Salinas, CA (1,221), Gatersleben, Germany (870), Wellesbourne, UK (770), St. Petersberg, Russia (709), Brion, France (534), Zaragoza, Spain (472).
For sunflower, a fairly extensive collection of germplasm is available at the Northern Crop Science Laboratory in Ames, IA. The USDA Germplasm Resources Information Network (GRIN; http://www.ars-grin.gov/) lists 2,919 Helianthus accessions, with 2,384 of these coming from H. annuus. In Argentina, the INTA Germplasm Resource Program comprises of 829 cultivated accessions at the Active Bank in Manfredi Experimental Station and a lower number of wild species at Balcarce Experimental Station. A fairly large collection is also maintained in South Africa (xxxx ref?).
The USDA-GRIN lists 2,223 accessions of Carthamus, with 2,144 accessions of these coming from C. tinctorius (safflower).
There are 250 accessions for chicory and endive germplasm at the North Central Regional Plant Introduction Station, Ames, Iowa.
Germplasm for other species??
Collections for weedy species..??
Genetic Maps and Mapping Populations
Lettuce: The core mapping population comprises of 110 RILs from L. sativa cv. Salinas x L. serriola (Agryris et al., 2005; Truco et al., 2007). Over 1,600 markers have been mapped on this population (http://cgp.ucdavis.edu). This population has recently been expanded to 300 RILs to provide increased genetic resolution. Detailed genetic maps have been constructed using six inter- and intra-specific crosses of Lactuca spp. An integrated map of all the current segregation data comprises over 2,700 markers and spans 1,505 cM (Landry et al., 1987; Kesseli et al., 1994; Truco et al., 2007). In addition, a set of 29 Backcross Inbred Lines from the interspecific cross L. saligna x L. sativa introgression lines have been created and used for mapping (Jeuken & Lindhout 2004, Jeuken et al. 2001).
Sunflower: Mapping resources include high-resolution linkage maps for the cultivated sunflower and six wild species with over 2,000 simple sequence repeat (SSR) and sequence-tagged-site (STS) markers (Tang et al. 2002, 2003b; Burke et al. 2002, 2004, 2005; Tang & Knapp 2003; Rieseberg et al. 2003; Lai et al. 2005). The composite linkage map of sunflower based on these markers comprises 657 loci and spans1423 cM with a mean density of 2.2 cM per locus. The integrated map based on AFLP and SSR markers includes 495 markers, spans 1824.6 cM and mean density of 3.7 cM per locus (Al-Chaarani et al. 2004, Poormohammad Kiani et al. unpubl. data).
Artichoke Cynara cardunculus L. var. scolymus: A genetic linkage map is being developed using a pseudo testcross approach at the University of Bari (S. Pavan, G. Sonnante, M. Ippedico, A. De Paolis). More details
Summarize details (generation, size etc.) in table??
Molecular Resources
A ~3x BAC library exists for lettuce with an average insert size of 111 kb (Frijters et al, 1997); additional libraries may exist in the private sector. A ~8x BAC library with average insert size of ~100 kb has been constructed for sunflower (xxxx). Neither of these libraries have been fingerprinted. BAC libraries do not exist for other Compositae species.
Sequence Information, EST databases.
The Compositae Genome Project (CGP) was initiated with funding from the USDA IFAFS program and continued with support from the NSF Plant Genome Program. The CGP has developed extensive EST data that have allowed both lettuce and sunflower to partly catch up with other more intensively studied species.
The first phase of the CGP generated over 132,000 ESTs from lettuce and sunflower. EST libraries were made from ten pools of RNA from different tissues/developmental stages/environmental conditions of each of the two genotypes that had been used as parents for the core mapping populations for each species. Over 68,000 ESTs were generated from L. sativa and L. serriola. Likewise, more than 67,000 ESTs were generated for sunflower, including 44,000 from cultivated confectionary and oilseed sunflower lines and 23,000 from drought- and salt-tolerant wild sunflowers, H. argophyllus and H. paradoxus, respectively.
The second phase of the CGP has generated over 600,000 ESTs from several tissues of 17 species within the Compositae (Table 3). EST data as well as the trace files are displayed at the CGP web site (http://cgpdb.ucdavis.edu/), and have been released to GenBank. Clones generated by the CGP can be obtained on a recharge basis from the Arizona Genomics Institute (AGI) (http://www.genome.arizona.edu/).
There are several other EST projects in progress in addition to the CGP. These include 6,000 normalized ESTs for Centaurea maculosa (J. Vivanco, Colorado State University), 9,777 floral ESTs for Senecio spp. (S. Hiscock, University of Bristol, UK), 40,000 ESTs for Senecio spp. (A. Lowe, University of Queensland, Australia), xxxx for Taraxacum xxxx (D, Shinati, U Nevada, Reno), French and Argentinean sunflower efforts??.
Other EST projects??
There are a total of nearly 800,000 ESTs from over 30 species available from NCBI. These represent over 1.5% of all eukaryote ESTs and 6% of all plant ESTs. Because many of the clones available from the AGI are full-length, these represent a tremendous resource for functional and comparative studies.
Table 3. EST Resources, February 2007.
|
Species |
Common name |
Total # ESTs |
% CGP |
# Unigenes |
|
Helianthus annuus |
Common sunflower |
94110 |
76.58 |
31605 |
|
Lactuca sativa |
Cultivated lettuce |
80779 |
99.25 |
26720 |
|
Lactuca serriola |
Prickly lettuce |
55490 |
100.00 |
19877 |
|
Cichorium intybus |
Chicory |
41747 |
91.80 |
22038 |
|
Taraxacum officinale |
Dandelion |
41296 |
100.00 |
15761 |
|
Carthamus tinctorius |
Safflower |
40878 |
100.00 |
19395 |
|
Centaurea solstitialis |
Yellow starthistle |
40407 |
100.00 |
22917 |
|
Helianthus tuberosus |
Jerusalem artichoke |
40361 |
100.00 |
21994 |
|
Centaurea maculosa |
Spotted knapweed |
39958 |
99.99 |
20922 |
|
Helianthus argophyllus |
Silverleaf sunflower |
35720 |
100.00 |
17839 |
|
Helianthus exilis |
Serpentine sunflower |
33960 |
100.00 |
19784 |
|
Lactuca saligna |
Willowleaf lettuce |
30696 |
100.00 |
11491 |
|
Helianthus paradoxus |
Puzzle Sunflower |
30517 |
100.00 |
17874 |
|
Cichorium endivia |
Endive |
30171 |
100.00 |
18951 |
|
Lactuca virosa |
Bitter lettuce |
30068 |
100.00 |
11865 |
|
Lactuca perennis |
Blue lettuce |
29125 |
100.00 |
11472 |
|
Helianthus petiolaris |
Prairie sunflower |
27484 |
100.00 |
12982 |
|
Helianthus ciliaris |
Texas blueweed |
21590 |
100.00 |
14857 |
|
Zinnia elegans |
|
17975 |
0.00 |
|
|
Gerbera hybrid cv. Terra Regina |
Gerbera |
15851 |
0.00 |
8665 |
|
Stevia rebaudiana |
Stevia (sugarleaf) |
5548 |
0.00 |
3345 |
|
Taraxacum kok-saghyz |
|
4731 |
0.00 |
3363 |
|
Senecio cambrensis |
|
2019 |
0.00 |
|
|
Senecio chrysanthemifolius |
|
2019 |
0.00 |
|
|
Senecio vulgaris subsp. vulgaris |
|
1956 |
0.00 |
|
|
Senecio squalidus subsp. squalidus |
|
1925 |
0.00 |
|
|
Senecio aethnensis |
|
1884 |
0.00 |
|
|
Gerbera hybrid cv. Terra Nero |
Gerbera |
1146 |
0.00 |
|
|
Cirsium arvense |
|
173 |
0.00 |
|
|
Ageratum conyzoides |
|
20 |
0.00 |
|
|
Tagetes erecta |
|
2 |
0.00 |
|
|
Artemisia apiacea |
|
1 |
0.00 |
|
|
All Asteraceae |
|
799607 |
89.83 |
|
Other initiatives have generated differential cDNA libraries using suppressed subtractive hybridization (Diatchenko et al. 1996) to identify low-copy mRNA and differentially expressed sunflower transcripts from several developmental stages (Fernández et al. 2003). This included 319 unique sunflower unigenes related to responses to abiotic and biotic stresses as well as low abundant transcripts with high similarity to homeobox genes, transcription factors, and signaling components. Functional SNPs and IN/DELs markers are being characterized in a set of 20 inbred lines including parental genotypes of three mapping populations. A total of 52 SNPs and 15 indels were preliminarily obtained with an overall frequency of 1 SNP per 91 bp and 1 indel per 326 bp in sunflower genome.
Phenotypic Information
QTLs have been or are being identified for numerous traits including root architecture, bolting, branching, spines, leaf development, leaf succulence, shoot biomass, flowering, seed size, seed oil concentration and composition, seed germination, mineral ion uptake traits, photosynthetic rate, water use efficiency, nutrient uptake, disease resistance, senescence, tolerance to water deficit, etc. These are being mapped relative to candidate genes (Table 4) for nutrient ion transporters, enzymes associated with seed dormancy and germination, disease resistance and response, drought, salt and stress tolerance, glycerolipid, tocopherol, and flavonoid synthesis, and floral, leaf and root development.
Table 4. (Numbers need to be updated)
|
# candidates to date |
# so far mapped |
|||
|
Traits |
Lettuce |
Sunflower |
Lettuce |
Sunflower |
|
Disease resistance |
724 |
140 |
273 |
60 |
|
Developmental |
250 |
114 |
68 |
59 |
|
Abiotic stress |
49 |
102 |
6 |
68 |
|
Physiological |
199 |
211 |
17 |
105 |
|
Othera |
302 |
1103 |
302 |
433 |
|
Total |
1524 |
1655 |
666 |
725 |
a includes genes mapped due to obvious indel polymorphisms.
Databases
A series of public and private databases provide access to Compositae genomic data: Compositdb contains genetic map and marker information; Lettcv contains information on over 4,500 cultivars; Sundb contains information for 214 markers on 10 genotypes; the CGPdb contains extensive EST and genetic information (http://compgenomics.ucdavis.edu/).
Resources Under Development
Genetic stocks
Several new RIL populations are being generated for lettuce, in particular 300 RILs from an intra-specific L. sativa cv. Salinas x cv. Valmaine that will allow the dissection of the determinants of plant type. (M. Truco, R. Michelmore, unpublished).
For sunflower, Cms HA89 x Ann1238 (elite wild progenitor) population consisting of 192 RILs is being generated in the US. Also, the Hopi x Ann1238 (primitive domesticate wild progenitor) population currently consisting of 384 F2s, could be advanced to RILs depending on resources. Argentinean mapping strategies include the development of advanced population for resistance/tolerance to biotic and abiotic stress: a) two advanced (F5) mapping populations derived from RHA801 x HA89 and RK416 x HA89 (EEA INTA Balcarce, Argentina) for resistance to Sclerotinia sclerotiorum and additional mapping populations for resistance to Verticillium dalhiae, and b) drought and middle drought resistance populations derived from R 417 x R 419, A 59 x R423 and HA 64 x HA 89 (F3) were developed at EEA INTA Manfredi, Argentina.
Mapping populations and RILs involving annual x annual and annual x perennial forms of Leontodon are being developed (L. Rieseberg, unpublished).
Others?
Genomic Resources
An Affymetrix chip has been developed for massively parallel genetic mapping and sensitive expression analysis of lettuce. This chip has a total of 6.6 million features representing ~29,000 unigenes, each with ~170 oligonucleotides with a 2 bp stagger (A. van Deyzne, R. Michelmore et al. unpublished). This chip is available and protocols for using and analyzing it are under development. An Agilent array (60mer) will also be developed for lettuce (~1000 annotated genes from the EST database, M. Jeuken).
The development of an oligonucleotide array for sunflower is also under development. This will be likely be similar, although less dense Affymetrix chip with 2.6 million features and 80-100 probes per unigene.
The utility of these chips for the analysis of other Compositae species remains to be determined.
Genomic Sequence Information
There is only limited genomic sequence information for any species in the Compositae. There has yet to be a coordinated effort to sequence any genome completely.
Needs
These are displayed by subject area and in approximate priority within in each area.
Research
Genetics and Genetic Stocks
(1) Genetic analysis of agriculturally important traits and those involved in domestication and invasiveness. This genetic characterization provides the foundation for the functional and comparative genomics described below. Traits of importance include:
Disease resistance. There are numerous sources of disease resistance with varying degrees of genetic characterization.
Seed oil composition. There have been multiple domestications oil seed crops within the Compositae.
Flowering time and bolting. There is wide variation within and between species for these agriculturally important traits.
Seed dormancy, physiology, size, vigor and longevity. There are large amounts of phenotypic variation that are beginning to be characterized.
Vegetative development, leaf morphology and branching. There are many examples of convergent and divergent evolution within and between species of the Compositae
Floral development. The Compositae have a rich diversity in floral architectures that are unique to this family.
Abiotic tolerances (particularly drought and salt). The Compositae offer a rich source of genetic diversity as they are adapted to many extreme environments. This has yet to be exploited.
Domestication traits, self-incompatibility, shattering. The multiple parallel domestications in the Compositae provide the opportunity to identify the genes critical to domestication and the effects of domestication on their evolution.
Post-harvest quality. Little is known about the genetic basis of this complex phenotype.
Secondary metabolism. The Compositae provide an unparalleled diversity of secondary metabolites that await further characterization.
Secondary products (particularly rubber). There are several Compositae spp. that make high quality rubber.
Genetic basis of invasiveness traits. Very little is known of the genetic basis of weediness. Analyses of the spread of herbicide tolerance and inter-specific hybrid fitness are needed.
Genetic basis of phenotypic diversification in wild model spp.
(2) More RIL populations, particularly RIL populations with inter-mated progenitors for lettuce and sunflower. This is needed to provide enhanced genetic resolution of mapping.
(3) Development of NILs differing for individual QTLs, for functional analyses and sexual or transgenic introgression of traits of agricultural or evolutionary importance.
(4) Development of mapping and RIL populations for minor Compositae crops (safflower) and model weed species (Leontodon, dandelion, and spotted knapweed).
(5) Development of mapping populations and RILs for species important for evolutionary studies, silverswords, wild sunflowers, Senecio spp., and Stephanomeria. Hexaploid-diploid crosses for evolutionary studies of polyploidy in Helianthus species.
Genomic resources
(1) Massively parallel genetic analysis of transcribed genes.
The high density oligonucleotide chips should be exploited to analyze allelic variation in multiple populations. This will locate many unigenes (10,000s?) in bins. The size of the bins will be determined by the sizes of the segregating populations analyzed and therefore the numbers of cross-overs. There is a need to increase the sizes of the populations analyzed to reduce the bin size. In the long term, this will provide a genetically-defined framework to anchor genomic shotgun sequences.
(2) Tiled oligonucleotide arrays for sunflower and other Compositae spp.
It is currently unclear how useful Affymetrix arrays designed from Lactuca and sunflower sequences will be for other species. However, it is possible that chips will at least be useful for species within individual tribes. It will be particularly beneficial if the lettuce array can be used to analyze Leontodon. The novel Lactuca array will be a learning experience that will allow the design of arrays with enhanced utility for other Compositae species. The oligonucleotide arrays will also be useful for identifying sequences that may be useful as PCR primers for amplifying sequences from little-studied exotic Compositae species.
(3) Greater depth in BAC libraries.
Current BAC libraries are ~3x for lettuce and ~8x for sunflower. At least 10 to 15x coverage is desirable.
(4) BAC fingerprints, contigs, minimum tiling path, and BAC end sequences.
As a foundation for sequencing, it would be useful to develop BAC fingerprints, generate a minimum tiling path, and sequence their ends. This would provide a framework for assemblies of random shotgun sequences and complement the genetically-defined bins of unigenes.
(5) Development of tools for Leontodon as a model.
Considerable resources will be required to develop Leontodon as a useful model. These include EST sequencing, BAC library construction, and physical mapping.
(6) Integration of genetic and cytological maps.
FISH, GISH, BAC-FISH are being developed for sunflower at the University of Buenos Aires-Instituto de Biotecnolgia INTA, Argentina. The hexaploid H. resinosus is currently investigated using molecular cytogenetics and markers in order to elucidate species origin through polyploidy (Carrera et al. 2004).
Gene Discovery and Sequencing
(1) Sequencing of the gene space for lettuce and sunflower.
Sequencing the gene space of lettuce and sunflower is a high priority as it will enable proteomic approaches and provide alleles and regulatory sequences for transgenic manipulation. Gene discovery through conventional EST sequencing is probably approaching saturation. Based on data from other species, sequencing of the high Cot and methyl filtered fractions will provide over 90% of the genic sequences in these two crops. Alternative strategies for accessing the gene space of these species should be applied as they become available. Such sequencing would supply the fraction of coding regions that is currently missing and as well as sequences of introns, promoters, and 5 and 3 UTRs.
(2) Analysis of allelic and orthologous series of agriculturally important and evolutionarily significant genes.
Resequencing projects are needed to access allelic variation across numerous genotypes within and between species.
(3) Exploratory sequencing of Leontodon.
Sequencing of low numbers of random genomic sequences as well as the gene space of Leontodon will provide data on the desirability of whole genome sequencing of Leontodon.
Whole Genome Sequencing.
The new generation of sequencing technologies is revolutionizing the opportunities to sequence large genomes. Individually, however, they are still less than ideal. We should prepare for the whole genome sequencing of several Compositae species in the next ~five years using a combination of sequencing approaches.
We envision three phases:
Phase one, immediate priorities:
Sequencing the gene space of lettuce and sunflower using a combination of sequencing approaches.
Sequencing of a small number of BACs from high interest areas in lettuce and sunflower.
Developing resources and information for lettuce and sunflower: high density maps of transcribed sequences, minimal tiling path of BACs, and xxxx..
Developing of Leontodon as a small genome model.
Developing of bioinformatics capabilities for acquiring, curating, and querying large amounts of sequence data.
Organizing the community to share the work load and generate the funding.
Phase two, intermediate term:
Draft whole genome, random shotgun sequencing of lettuce and sunflower using several technologies: e.g. 1 2x skim sequencing with Sanger, 5 10+x with one or more high-throughput, paired-end technologies (454 or Solexa).
BAC end sequencing of the minimum tiling paths of lettuce and sunflower.
Draft 1 2x genome sequencing of Leontodon.
Selective sequencing of BACs from high interest areas from multiple Compositae species.
Phase three, longer term:
High-quality sequencing of lettuce, sunflower, and Leontodon.
Draft sequencing of key nodal species across the Compositae.
Re-sequencing of close relatives of lettuce and sunflower.
The exact timescale and the amount of overlap between of each of these three phases will be determined by the availability of funding and the advancement of sequencing technologies.
Functional Genomics
(1) Understanding the molecular basis of agriculturally important traits as well as those involved in domestication and invasiveness.
As detailed above, disease resistance, dormancy, flowering time, seed oil traits, salt and drought tolerance, and seed size, vigor and longevity are all traits that require detailed analysis at the molecular level.
Bulked segregant analysis using Affymetrix chips will rapidly and efficiently correlate phenoptypes with candidate genes to provide functional maps of sunflower, lettuce, and Leontodon. The rate-limiting step will be the generation of high quality, phenotypic data on large populations and accessions.
(2) Improved methods for gene silencing.
Current projects will generate many correlations between phenotypes and candidate genes. A major challenge will be to move from gene/trait correlations to functional assays. The development of VIGS and efficient RNAi are needed for silencing of individual genes and gene families.
(3) Comparative functional genomics.
The functional significance of allelic variation for traits of agricultural and/or evolutionary importance should be determined.
(4) Massively-parallel genetic and expression analyses across other crops, weeds, and adaptive radiation/speciation models in the Compositae.
Development and utilization of microarrays or tag sequencing for global transcriptomic analyses of specific developmental stages associated with genetic and phenotypic variation for traits of interest. Use of the tiling arrays to obtain differential expression data among genotypes will link genetic variation to expression and phenotypic variation.
Database Development, Data Visualization
(1) Acquisition, curation, visualization of increasingly complex datasets from multiple sources.
It will be particularly challenging to assimilate and exploit the large amount of sequence data that will be generated by the next generation of sequencing technologies.
(2) Tools for data visualization and enhanced queries across heterogeneous datasets.
(3) Universal ontology for phenotypic information. This is required for integration of datasets and queries across different species within the Compositae as well as with species in other families.
Translation (Breeding)
(1) High-throughput, inexpensive marker systems and robust molecular markers for agriculturally important traits.
Current and future studies have/will identify numerous trait-marker associations. However, many of the current marker technologies are too expensive and laborious for routine analysis of breeding materials. Methods for are required to identify and exploit molecular markers in a breeding context. This includes the development of inexpensive automated DNA extraction methods and efficient SNP discovery as well as subsequent analysis. Total costs should be below a few cents per datapoint. Assay systems should be flexible and allow variable numbers (in the few hundred range) and compositions of markers. Disease resistance should be an earlier application of marker-assisted selection.
(3) Methods for stable, regulated transgene expression.
Agrobacterium-mediated transformation is routine for lettuce but not sunflower. However, for both species introduced transgenes become silenced and transgenic lines with adequate levels are rare. Research is needed to increase transformation efficiencies in recalcitrant Composite species and to provide a variety of predictable transgene expression patterns.
(4) Analysis and access of broader germplasm.
The sequences generated, particularly the candidate genes, will be useful for introgression of favorable alleles from wild germplasm using marker-assisted selection.
(5) Development of stress tolerant plants.
There is great intra- and inter-specific for resistance to abiotic stresses that has yet to be exploited but could great reduce the impact of agriculture as well as improve the efficiency and predictably of several Compositae crops.
(6) Improvement of post-harvest quality and shelf life.
Several Compositae crops are subject to major post-harvest losses. Application of the developing knowledge of the physiological and pathological bases of these losses provides opportunities to mitigate these losses.
(7) Development of reliable strategies for transgene containment (e.g., transgenic mitigation; Gressel, 1999; Stewart. 2004).
Some Compositae crops, including lettuce and sunflower, are grown in the same geographic region as sexually compatible wild relatives. This raises the possibility of transgene escape into the wild population. Research and implementation of strategies to minimize transgene flow from crops to wild relatives will assist the acceptance of transgenics for these and other crops.
Education
(1) Training of students in plant breeding methods to take advantage of the large amounts of genomics data available for Compositae species.
(2) Training of students in functional, comparative, and evolutionary genomics using the opportunities afforded by the Compositae.
(3) Training of the next generation of weed scientists with a particular focus on the many noxious weeds in the Compositae.
(4) Training of students in physiological genetics to exploit the diversity of abiotic stress phenotypes exhibited by the Compositae.
(5) Exposure of high school students and high school science teachers to current issues and technology used to sustain and increase food production while minimizing environmental impact.
(6) Developing alternative approaches to train plant breeders to supplement the reduced numbers of academic plant breeding programs, particularly in specialty crops. Professional education programs can be targeted to personnel currently employed in the agricultural or seed industry to enhance their theoretical and practical knowledge of genetics and breeding, as for example in the UC Davis Plant Breeding Academy (http://sbc.ucdavis.edu/Events/Plant_Breeding_Academy.htm).
Extension
Workshops targeted at plant breeders and weed scientists.
Workshops are needed to publicize the molecular markers and genetic maps generated in the Compositae and to educate breeders in their application in these crops. A model for such workshops is the Breeding with Molecular Markers extension course presented by the UC Davis Seed Biotechnology Center (http://sbc.ucdavis.edu/Events/Courses.htm). Such workshops should emphasize hands-on sessions illustrating how to access genomic and marker information and apply it in practical breeding programs.
Development of new courses such as the one developed in 2004 at U. Mass, Boston that apply new understandings of invasive species biology to land management strategies (http://bio697.blogspot.com/).
Stakeholders involved in this draft
This draft reflects the input from the PIs of the Compositae Genome Project: Richard Michelmore (UC Davis), Loren Rieseberg (U. Indiana), K. Bradford (UC Davis), J. Burke (Vanderbilt U), D. Still (Cal Poly, Pomona), R. Kesseli (U. Mass, Boston), and S. Knapp (U. Georgia). There has also been significant input from M. Jeuken (U. Wageningen), and Ruth Heinz (INTA, Buenos Aires) as well as from participants in the Compositae White Paper meeting.
The Compositae White Paper meeting was held at UC Davis in August 2006 to get input from the broad community of researchers working on Compositae species (http://compgenomics.ucdavis.edu/cwp2006/). This was attended by ~50 researchers from diverse scientific backgrounds and several different countries. The program consisted of scientific presentations in the morning and break-out groups to discuss priorities followed by an integrating session in the afternoon. Input from this meeting has been incorporated into this draft.
We are now seeking additional input and refinement from the broad community of researchers working on Compositae species.
Stakeholder groups that have or will be consulted in the continued development of this white paper (partial list; please suggest others)
Large community of plant systematists, evolutionary biologists, and weed biologists study who Compositae species.
PIs of the Compositae Genome Project.
The NSF Floral Genome Project.
Breeders of Compositae crops.
USDA Leafy Vegetable Germplasm Committee.
California Lettuce Research Board http://www.calettuceresearchboard.org/
Seed companies breeding Compositae species.
USDA facilities involved in maintenance and study of Compositae species
Land managers and environmental protection agencies interested in managing invasive or endangered Composite species
Others???
References: Only partial listing. Not checked.
Aguirrezabal L, Bouchier-Combaud S, Radziejwoski A, Dauzat M, Cookson SJ, Granier C. 2006. Plasticity to soil water deficit in Arabidopsis thaliana: dissection of leaf development into underlying growth dynamic and cellular variables reveals invisible phenotypes. Plant, Cell and Environment, accepted for pub
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What other supplementary tables would be useful?
Supplementary Table 1. Economics of Major Compositae Crops.
|
Production Quantity | World |
|
|||||||
|
|
year |
|
||||||
|
commodity |
|
1990 |
2000 |
2005 |
|
|||
|
Artichokes |
1,323,471.00 |
tonnes |
1,330,299.00 |
tonnes |
1,262,982.00 |
tonnes |
|
|
|
Lettuce and chicory |
11,520,342.00 |
tonnes |
18,279,329.00 |
tonnes |
22,399,319.00 |
tonnes |
|
|
|
Safflower oil |
215,593.22 |
tonnes |
170,397.72 |
tonnes |
126,581.90 |
tonnes |
|
|
|
Safflower seed |
834,539.00 |
tonnes |
623,356.00 |
tonnes |
717,778.00 |
tonnes |
|
|
|
Sunflower oil |
8,097,652.95 |
tonnes |
9,975,013.13 |
tonnes |
10,244,873.62 |
tonnes |
|
|
|
Sunflower seed |
22,707,244.00 |
tonnes |
26,510,666.00 |
tonnes |
30,595,462.00 |
tonnes |
|
|
|
FAOSTAT | © FAO Statistics Division 2007 | 12 February 2007 |
|
|||||||
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
Area Harvested | World |
|
|||||||
|
|
year |
|
||||||
|
commodity |
|
1990 |
2000 |
2005 |
|
|||
|
Artichokes |
117,030.00 |
Ha |
123,056.00 |
Ha |
125,128.00 |
Ha |
|
|
|
Lettuce and chicory |
542,103.00 |
Ha |
839,485.00 |
Ha |
1,024,018.00 |
Ha |
|
|
|
Safflower seed |
1,207,019.00 |
Ha |
822,270.00 |
Ha |
916,443.00 |
Ha |
|
|
|
Sunflower seed |
17,046,747.00 |
Ha |
21,161,673.00 |
Ha |
22,823,330.00 |
Ha |
|
|
|
FAOSTAT | © FAO Statistics Division 2007 | 12 February 2007 |
|
|||||||
Supplementary Table 2. Sunflower seed production (in 1,000 metric tons)
|
Sunflower seed |
||||||
|
World supply & disappearance (in 1,000 metric tons) |
||||||
|
Item |
2000/01 |
2001/02 |
2002/03 |
2003/04 |
2004/05 |
2005/06 |
|
|
|
|
|
|
Revised |
Forecast |
|
Area harvested (1,000 HA) |
19,540 |
18,485 |
19,892 |
22,918 |
21,262 |
22,791 |
|
yield (MT/HEC) |
1.18 |
1.18 |
1.2 |
1.17 |
1.23 |
1.29 |
|
|
|
|
|
|
|
|
|
Seed Production |
|
|
|
|
|
|
|
Argentina |
2,950 |
3,720 |
3,340 |
2,990 |
3,650 |
3,800 |
|
Eastern Europe |
1,657 |
1,861 |
1,648 |
2,295 |
2,270 |
1,950 |
|
European Union |
3,333 |
3,030 |
3,718 |
4,078 |
4,133 |
3,765 |
|
China (Peoples Republic of) |
1,954 |
1,750 |
1,946 |
1,820 |
1,750 |
1,850 |
|
Russia/Ukraine |
7,368 |
4,936 |
7,194 |
9,348 |
8,001 |
10,450 |
|
United States |
1,608 |
1,551 |
1,112 |
1,209 |
930 |
1,824 |
|
India |
730 |
870 |
1,060 |
1,160 |
1,300 |
1,250 |
|
Turkey |
630 |
530 |
830 |
560 |
640 |
790 |
|
Other |
2,880 |
3,551 |
3,108 |
3,467 |
3,505 |
3,665 |
|
TOTAL |
23,110 |
21,799 |
23,956 |
26,927 |
26,179 |
29,344 |
|
Seed Import |
|
|
|
|
|
|
|
Mexico |
23 |
10 |
104 |
38 |
11 |
23 |
|
European Union |
1,999 |
1,155 |
1,007 |
1,473 |
763 |
1,000 |
|
Other |
704 |
467 |
812 |
1,249 |
813 |
801 |
|
TOTAL |
2,726 |
1,632 |
1,923 |
2,760 |
1,587 |
1,824 |
|
|
|
|
|
|
|
|
|
Oilseed crushed |
21,116 |
18,514 |
21,149 |
23,442 |
23,115 |
25,510 |
|
|
|
|
|
|
|
|
|
Seed export |
|
|
|
|
|
|
|
Argentina |
94 |
342 |
232 |
44 |
97 |
121 |
|
United States |
153 |
176 |
122 |
136 |
116 |
225 |
|
Russia/Ukraine |
1,768 |
100 |
524 |
1,271 |
73 |
560 |
|
Other |
711 |
1,084 |
1,112 |
1,277 |
1,257 |
957 |
|
TOTAL |
2,726 |
1,702 |
1,990 |
2,728 |
1,543 |
1,863 |
Supplementary Table 3. Oil composition of sunflower and comparison to other oilseeds
|
Source |
Contents (%) |
||
|
Oleic |
Linoleic |
Saturated |
|
|
Conventional sunflower oil |
20 |
69 |
11 |
|
Mid oleic sunflower oil |
65 |
26 |
9 |
|
High oleic sunflower oil |
82 |
9 |
9 |
|
Olive oil |
77 |
8 |
14 |
|
Canola oil |
62 |
21 |
16 |
|
Cottonseed oil |
18 |
54 |
27 |
Source: US Sunflower Crop Quality Report 2003 http://www.sunflowernsa.com/uploads/cqr/cqr2003.pdf
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