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Ecogeographic core collections and FIGS


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Ecogeographic core collections and FIGS

  1. 1. Representativeness in genebanks  Measured in terms of diversity captured within ex situ genebanks  Is the best guarantee to face future threats  Is a concern for curators, not for breeders  The reference must be nature for CWR, agroecosystems for landraces  To assess it, comparative studies (genebank vs nature/farm) are required
  2. 2. Why is it so difficult to assess it? REPRESENTED GAPS!  We conserve genetic diversity – genetic markers – pheno/genotypic  Massive characterization involve high costs and efforts  How to evaluate unsampled populations?
  3. 3. Ecogeography and genetics Phenotype = Genotype + Environment + (GxE) Incomplete, totally absent Longitude / Latitude or unaffordable Genebank External sources Adaptation (indirectly)
  4. 4. Ecogeography:Study of adaptive scenarios of any individual, population or species throughthe analysis of those biotic and abiotic factors which affect their survival orare able to create new ecotypes or landraces
  5. 5. Abiotic factors  More predictable and stable  Easier to interpret  Increased availability
  6. 6. Ecogeographical representativeness If we are able to map the different adaptive scenarios for the target species, we could:  Carry out efficient germplasm collections  Create ecogeographical core collections  Support genotypic/phenotypic studies  Determine optimal places to multiply/regenerate germplasm
  7. 7. Ecogeographical Land Characterization maps GIS Geophysic Edaphic E L C maps Bioclimatic
  8. 8. Ecogeographical core collections P E Ecogeographical Core Collection Phenotypic Core collection REPRESENTATIVENESS
  9. 9. Utilization  Curators Representativeness  Breeders Traits
  10. 10. Utilization paradox  Few funds for germplasm characterization & evaluation  Plant breeders need information (characterization and evaluation data) about germplasm collections in order to use them  Curators/PGR centers focus their efforts on conservation and sometimes (when funds are available) on germplasm characterization  Plant breeders may expect up to 100-200 germplasm accessions to evaluate for a particular trait as a part of their routine activities  Frequently what they find are large gene bank collections  They have limited screening capacity  Scarce evaluation data (at least, available data)  Low level of utilization
  11. 11. Focused Identification Germplasm Strategy  FIGS idea: Michael Mackay (1986,1990, 1995) Phenotype = Genotype + Environment + (GxE) Resistance/Tolerance = Genotype + Environment + (GxE)  Identifying plant germplasm with a higher likelihood of having desired genetic diversity for a target trait  Using ecogeographic data for prediction of crop traits a priori, BEFORE the field trials  With fewer or no characterization efforts, providing a reduced number of germplasm accessions to breeders/curators to be evaluated Boosting  Generating FIGS subsets (≠ core collections)
  12. 12. Classic approach Germplasm FILTERING!! Illustration by Mackay (1995) based on latitude & longitude Data layers sieve accessions Temperature Ecogeographical variables Salinity score GIS layers / Elevation Rainfall Agro-climatic zone Expert’s knowledge Disease distribution  Species specialists  Breeders  Entomologists, pathologists FOCUSED IDENTIFICATION OF GERMPLASM STRATEGY
  13. 13. Model approach Resistance/ Ecogeographical Tolerance Y = b + X1 + X2 + X3 variables Characterized germplasm Pattern Prediction on uncharacterized germplasm Classifier method AUC Kappa Real (field) validation Principal Component 0.69 0.40 ? Regression (PCR) Partial Least Squares (PLS) 0.69 0.41 ? Random Forest (RF) 0.70 0.42 ? Support Vector Machines 0.71 0.44 ? (SVM) Artificial Neural Networks 0.71 0.44 ? (ANN) (Genebank: ICARDA wheat collection – Trait: Stem rust (Puccinia gramini)
  14. 14. Perspectives  ELC maps are being used in designing CWR in situ conservation strategies in Europe (Czech Republic and Spain cases). PGR secure project WP3.  Ecogeographical core collections for several legume species will be created and published by the Spanish National Program (CRF-INIA). SIERFE Project.  FIGS method is being used to prioritize areas for in situ conservation of CWR and landraces for Beta, Avena, Medicago and Brassica genus groups in Europe. PGR secure project WP2.  Field validation (field resistance evaluation) of FIGS subsets (both approaches) from Phaseolus vulgaris Spanish collection for bacterial diseases.  ELC maps and FIGS to collect germplasm  FIGS to detect areas of high interest for in situ conservation of Trifolium repens and T. pratense genepool on a global scale using evaluation data (over 20 traits).
  15. 15. More information ELC maps: 1. M. Parra-Quijano, J.M. Iriondo , M.E. Torres. 2012. Ecogeographical land characterization maps as a tool for assessing plant adaptation and their implications in agrobiodiversity studies. Genetic Resources and Crop Evolution 59(2):205-217 Ecogeographical Core Collections: 2. M. Parra-Quijano, J.M. Iriondo , M.E. Torres, L. De la Rosa. 2011. Evaluation and validation of ecogeographical core collections using phenotypic data. Crop Science 51:694-703 FIGS “classic” approach (study case): 3. El Bouhssini, M., et al.(2011). Sources of resistance in bread wheat to Russian wheat aphid (Diuvaphis noxia) in Syria identified using the Focused Identification of Germplasm Strategy (FIGS). Plant Breeding 130: 97-97 FIGS modelling approach: 4. Bari, A., K. Street, , M. Mackay, D.T.F. Endresen, E. De Pauw, and A. Amri (2011). Focused Identification of Germplasm Strategy (FIGS) detects wheat stem rust resistance linked to environment variables. Genetic Resources and Crop Evolution [online first]. doi:10.1007/s10722-011-9775-5.Websites (FIGS subsets on wheat)Review about ecogeographical and GIS tools