Trait data mining using FIGS (2006)
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Trait Mining, prediction of agricultural traits in plant genetic resources with ecological parameters. Focused Identification of Germplasm Strategy (FIGS). For the Vavilov seminars at the IPK Gatersleben 13th June 2007. Dag Endresen, Michael Mackay, Kenneth Street.
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Trait data mining using FIGS (2006)
- 1. Cover slide Utilization of Genetic Resources Prediction of agricultural traits in plant genetic resources with ecological parameters June 13, 2007, IPK Gatersleben Dag Terje Filip Endresen , Nordic Gene Bank (NGB), Sweden Michael Mackay , Australian Winter Cereals Collection (AWCC), Tamworth Agricultural Institute , NSW DPI, Australia Kenneth Street , Project Coordinator, Genetic Resource Unit, ICARDA
- 14. Long-term average precipitation for all collection sites
- 15. Logical process Select Parents Identify the Problem Understand Problem Information & Knowledge Identify Likely Accs. Evaluate Sub Set Breeding & Selection Cultivar
- 16. VIR ICARDA AWCC ? USDA ? Database GIS Traits specific selection Figs Set Figs Set Figs Set Figs Set Figs Set Evaluation VIR ICARDA AWCC ? USDA IPK? Database GIS Trait-specific selection Figs Set Figs Set Figs Set Figs Set Figs Set Evaluation
- 18. Core and FIGS drought sets Core accessions FIGS accessions
- 19. After M C Mackay 1995
- 20. Distribution of 17,000 bread wheat landraces ICARDA, Aleppo, Syria VIR, St Petersburg, Russia AWCC, Tamworth, Australia A virtual collection from these gene banks: www.figstraitmine.com
- 21. Origin of Concept : Boron toxicity of wheat and barley example of late 1980s FIGS What is F ocused I dentification of G ermplasm S trategy
- 24. openModeller The openModeller project aims to provide a flexible, user friendly, cross-platform environment where the entire process of conducting a fundamental niche modeling experiment can be carried out. The software includes facilities for reading species occurrence and environmental data, selection of environmental layers on which the model should be based, creating a fundamental niche model and projecting the model into an environmental scenario. [ http://openmodeller.sourceforge.net/ ] The project is currently being developed by the Centro de Referência em Informação Ambiental (CRIA) , Escola Politécnica da USP (Poli) , and Instituto Nacional de Pesquisas Espaciais (INPE) as an open-source initiative.
- 28. Phenotype
- 30. http://barley.ipk-gatersleben.de/genres … screen dump cropped Screen dump continued…
- 43. Thank you for listening!
Notas del editor
- 13-JUN-2007 10:00 AM . Seminarraum der Genbank . Vavilov-Seminar . Pr ediction of agricultural traits in plant genetic resources with ecological parameters ; Dag Terje Filip Endresen Nordic Gene Bank, Alnarp, Sweden . Host: Dr. H. Knüpffer [http://www.ipk-gatersleben.de/Internet/Veranstaltungen/KolloquienSeminare]
- Some keywords; the main topics of the talk
- Image:
- Image: Wine grapes, field trip during a PGR Forum workshop at the Azores (2004). Photographer Dag Terje Endresen (NGB Picture Archive, image 003869)
- Image: A field of sugar beet at Alnarp. Sugar B eet ( Beta vulgaris L.) . Photographer Dag Terje Endresen (NGB Picture Archive, image 003896)
- [ 1 ] Hutchinson, G.E. (1957). Concluding Remarks. In Cold Spring Harbor Symposia on Quantitative Biology. 22: 415-42. [2] Sutton, T., R. de Giovanni, M. F. de Siqureira (2007). Introducing openModeller . OSGeo Journal volume 1, May 2007. [ http://www.osgeo.org/journal/ ] Image: Söderåsen, Sweden, June 24 2006, Dag Endresen.
- * Alercia A., Diulgheroff S., metz T. (2001). Multicrop Passport Descriptors. FAO, IPGRI. * Frankel O.H. (1984). Genetic perspectives of germplasm conservation. In Arber W., Illmensee K., Peacock W.J., Starlinger P. (eds.): Genetic Manipulation: Impact on Man and Society. Cambridge University Press, for ICSU Press, Cambridge U.K., 161-170. Frankel O.H. (1970): Preface. In Frankel O.H., Bennett E. (eds.): Genetic Resources in Plants – Their Exploration and Conservation. Oxford & Edinburgh, Intrnational Biological Programme & Blackwell Scientific Publications, 1-4. * Mackay , M. C., Von Bothmer R., & Skovmand B. 2005 . Conservation and utilization of genetic resources - what will happen in the future? 5th Triticea Symposium, Prague, Check Republic. * Image Centers of origin, This image is a work of a United States Department of Agriculture employee, taken or made during the course of the person's official duties. As a work of the U.S. federal government , the image is in the public domain .
- Image: Wheat spikes, Dag Endresen, 2004-07-20 [ http://www.nordgen.org/sesto/index.php?scp=ngb&thm=pictures&mod=det&id=002855&img_size=768x512 ] Illustration: Distribution of the FIGS core set . Yellow dots represent collection sites - 700 sites, 750 accessions, 52 countries represented. [ http://www.bwldb.net/images/coreset.gif ]
- We can actually begin to introduce “layers” of information for a range of environmental and geographic parameters. Here we can see precipitation data for collection sites. P
- Just quickly explain the diagram.
- These layers of information can be in the form of continuous surfaces of, for example, temperature, humidity, precipitation, salinity problems, and soil types. In this example we are looking at the probability of salinity being a problem based on soil types. This is recent work undertaken by ICARDA scientists, and the collection sites are for bread wheat landraces held by the AWCC. The great thing about GIS technology is that, in this case, we can directly assign a ‘salinity probability index’ on germplasm collected at each individual site. P
- Here we can compare the two approaches geographically. As I said earlier, this is a work in progress - and we hope to have much more information about the results that the FIGS approach can produce within a few years. But it certainly represents a new way of combining biological and environmental information to benefit PGR utilization and plant improvement.
- We can then use these layers of information as sieves, through which we can filter our accessions to identify those most likely to contain the genetic variation we are seeking. We can “tune in” the environments from which we want to sample germplasm. For example, we can specify annual precipitation, temperature during heading, humidity at another growth stage - and so on. Then we tip our collection of accessions in the top of the FIGS machine and wait for those that filter out the bottom. These ones we evaluate thoroughly.
- OK , we have different types of PGR and a range of these are likely to provide the resources we need to breed cultivars in the future. The next question to ask is - Do we have sufficient PGR? Is our coverage of the available genetic variation good enough? Ex situ gene banks were a growth industry in the 1960s, 1970s and 1980s. Collecting missions were conducted in many parts of the globe, including Vavilov’s centres of diversity, and thousands of landraces and wild relatives were sampled and put into long term storage. But there does not seem to be a collated central register of what was sampled - at the accession level. So, it is still difficult to make definitive statements about how well we have achieved the goal of conserving genetic variation before it is displaced by modern cultivars. One way we can get an idea of how well we have sampled genetic variation is by using GIS, or geographic information system, technology. By mapping the sites where primitive varieties and wild relatives were collected we can quite easily provide an overview of the coverage achieved. It is also possible to include different layers of information, using this technology, to make decisions about collection coverage on an environmental basis as well as geographically. Dr Valkoun also demonstrated the value of GIS in his lecture on wild cereal relatives yesterday. This example shows how several gene banks can collaborate to build a ‘virtual’ primitive varieties (landraces) germplasm distribution map.
- Text
- Image: GBIF-MAPA banner (rotated 90°) [http://gbifmapa.austmus.gov.au/mapa/images/ui/home_banner2.png] Illustration: PYXIS grid system [ http://www.gbif.org/images/IMG_B_STORY1137509545 ]
- The images are from the openModeller web site [ http://openmodeller.sourceforge.net/ ]
- Image: Barley accession from NGB, EURISCO and SINGER as input to the MaxEnt Niche Modeling algorithm, prediction of occurences, displayed with ArcView (created by Dag Endresen during the GBIF workshop on Niche Modeling, December 2004 in Kansas, US).
- Image: Rheum x hybridum Murray , 2004, Photographer Gitte K. Björn . [ http://www.nordgen.org/sesto/index.php?scp=ngb&thm=pictures&mod=det&id=003672 ]
- Dynamic Evaluation Data Analyser [http://www.nordgen.org/sesto/index.php?scp=ngb&thm=observations] Image: Solanum tuberosum L. Potato. Light sprout. Photographer NGB (NGB Picture Archive, image 001289).
- Dynamic Evaluation Data Analyzer [ http://barley.ipk-gatersleben.de/genres/index.php?scp=barley&thm=matobs&prorecnum=1 ] The original version is developed in SESTO [ http://www.nordgen.org/sesto/index.php?scp=ngb&thm=matobs&ampr=305360601 ]
- Dynamic Evaluation Data Analyzer. When a trait character is selected the results are displayed split on Site, Year, Taxon, Biological status of sample, Country of origin … or any other useful categories as defined by the responsible administrator. [ http://barley.ipk-gatersleben.de/genres/index.php?scp=barley&thm=matobs&prorecnum=2&dscnum=254&top=&cur_group= ]
- Photo: Field been from Boreal, accession NGB11518, 2005-03-05, Dag Endresen [http://r142b.ngb.se/ngb/2005-03--the-making-of-seeds-pictures/index.php?offset=19&size=medium&stp=1]
- Image: Rheum x hybridum Murray Rhubarb (2004). Photographer Gitte K. Björn (NGB Picture Archive, image 003683) Image: Rheum x hybridum Murray Rhubarb (2004). Photographer Gitte K. Björn (NGB Picture Archive, image 003714) Image: Brassica nigra (L.) W. D. J. Koch Black Mustard . Photographer Dag Terje Endresen (NGB Picture Archive, image 003840) [ http://www.nordgen.org/sesto/index.php?scp=ngb&thm=pictures ]
- * IPGRI Descriptors lists [http://www.ipgri.cgiar.org/system/page.asp?frame=programmes/inibap/home.htm] (119 descriptor lists, 2005) * MCPD [http://www.ipgri.cgiar.org/publications/pdf/333.pdf] * UPOV - International Union for the Protection of New Varieties of Plants (UPOV) [ http://www.upov.int/] * UPOV - The International Union for the Protection of New Varieties of Plants or UPOV (French: Union internationale pour la protection des obtentions végétales) is an intergovernmental organization with headquarters in Geneva, Switzerland. [http://en.wikipedia.org/wiki/UPOV] * COMECON - The Council for Mutual Economic Assistance (COMECON / Comecon / CMEA / CEMA), 1949 – 1991, was an economic organisation of communist states and a kind of Eastern European equivalent to the European Economic Community. The military counterpart to the Comecon was the Warsaw Pact. [http://en.wikipedia.org/wiki/Comecon] * Multi-crop Passport Descriptors (MCPD) [http://www.ipgri.cgiar.org/publications/pdf/124.pdf] F AO (Food and Agricultural Organization of the United Nations) - IPGRI (International Plant Genetic Resources Institute). This is a revised version (December 2001) of the 1997 MCPD List. * FAO World Information and Early WarningSystem ( WIEWS) [http://apps3.fao.org/wiews/] * 19 Plant Uses Categories based on categories developed for the Working Group on Taxonomic Databases (TDWG) (Cook, Frances E.M., 1995. Economic Botany: Data Collection Standard. Royal Botanic Gardens Kew). [ http://www.ecpgr.cgiar.org/epgris/Training/MCPD-1998.doc] * The mapping of MCPD to ABCD was started in 2004 by Helmut Knüpffer and Walter Berendsohn, and continued by Javier de la Torre and Dag Terje Filip Endresen in 2005. [ http://ww3.bgbm.org/MCDPH] [ http://www.bgbm.org/TDWG/CODATA/Schema/Mappings/EURISCO-2-ABCD.pdf ]
- * Illustration: Corn earworm pupae that will be used to produce control parasites for release in the field. Photo by Scott Bauer. [http://www.ars.usda.gov/is/graphics/photos/k5554-2.htm] * UBIF is an attempt to define a common foundation for several TDWG/GBIF standards like SDD (see SDD WIKI), ABCD (see ABCD content schema homepage) or TaxonConceptNames (see Taxonomic Concept Transfer Schema WIKI). * Unified Biosciences Information Frameword (UBIF) XML schema for data exchange and integration across knowledge domains. The schema has been design for biological data, but is applicable to other knowledge areas as well. It is based on work of the TDWG SDD and ABCD subgroups and currently jointly authored by the SDD, ABCD, TaxonName subgroups and by GBIF (Global Biodiversity Information Facility). The framework may be used without changes for new schemata, no registration is necessary. * Complex Types are part of the UBIF infrastructure (TDWG common complex type for several schemas, ABCD, SDD, TCS, Lnnean Core, etc.)
- * The mapping of MCPD to ABCD was started in 2004 by Helmut Knüpffer and Walter Berendsohn, and continued by Javier de la Torre and Dag Terje Filip Endresen in 2005. [ http://ww3.bgbm.org/MCDPH] [ http://www. bgbm .org/TDWG/CODATA/Schema/Mappings/EURISCO-2-ABCD. pdf ]
- GCP_Passport v 1.03 [http://tor.ngb.se/dev/temp/gcp_passport_01_03.xsd] The GCP Passport 1.03 descriptor standard is based on the MCPD and ABCD standards and implemented for the PyWrapper/BioCASE data exchange software. A mapping for automatic “upgrade” between ABCD 2.06 and GCP_Passport_1.03 is also included in the PyWrapper/BioCASE software. The Generation Challenge Programme is a research and capacity building network that uses plant genetic diversity, advanced genomic science, and comparative biology to develop tools and technologies that enable plant breeders in the developing world to produce better crop varieties for resource-poor farmers. [http://www.generationcp.org]
- OMG-LSR, Object Management Group – Life Science Research [http://www.omg.org/lsr/]
- http://apps3.fao.org/wiews/wiews.jsp
- Solanum tuberosum L. Potato. Light sprout. Photographer NGB (NGB Picture Archive, image 001289).
- Image: Field of wheat at Alnarp. Photographer Dag Terje Endresen (NGB Picture Archive, image 002981) Image: Spider in a spiderweb Image: Dag Terje Filip Endresen in Benin Image: Michael Mackay Michael Mackay: < michael.mackay@agric.nsw.gov.au>