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Ecogeographic core collections and FIGS
 

Ecogeographic core collections and FIGS

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    Ecogeographic core collections and FIGS Ecogeographic core collections and FIGS Presentation Transcript

    • 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
    • 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?
    • Ecogeography and genetics Phenotype = Genotype + Environment + (GxE) Incomplete, totally absent Longitude / Latitude or unaffordable Genebank External sources Adaptation (indirectly)
    • 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
    • Abiotic factors  More predictable and stable  Easier to interpret  Increased availability
    • 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
    • Ecogeographical Land Characterization maps GIS Geophysic Edaphic E L C maps Bioclimatic
    • Ecogeographical core collections P E Ecogeographical Core Collection Phenotypic Core collection REPRESENTATIVENESS
    • Utilization  Curators Representativeness  Breeders Traits
    • 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
    • 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)
    • 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
    • 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)
    • 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).
    • 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.Websiteshttp://www.figstraitmine.org/ (FIGS subsets on wheat)Review about ecogeographical and GIS toolshttp://revistas.inia.es/index.php/sjar/article/view/1859/1673