Presentation3 - Representa & DIVmapas tools

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Presentation3 - Representa & DIVmapas tools

  1. 1. Mauricio Parra Quijano FAO consultant International Treaty on Plant Genetic Resources for Nutrition and Agriculture CAPFITOGEN Program Coordinator Tools
  2. 2. Representa Evaluates the ecogeographical representativeness of germplasm collections
  3. 3. Genetic representation A B C accggtccc accggtcgc accggtctc A B C A A A A B C A A A A B BB B C BA
  4. 4. Ecogeographic representation A BBBBBBB CCC A B C Unique A BB CC Even A BBBB CC Proportional
  5. 5. Representativeness based on ELC maps y x Coordinates of passport dataELC map of Cuba (from ELC mapas tool) Sites with species´ occurrences 1 2 3 4 5 6 7 8 9 10 ELC categoriesNentries 100 200 300 Genebank set 1 2 3 4 5 6 7 8 9 10 ELC categories Nentries 100 200 300 External sources set1 2 3 4 5 6 7 8 9 10 ELC categories %cells 25 50 75 Overall distribution Categories of the map Χ2 test upper upper mid lower mid lower Quartiles
  6. 6. Validation through germplasm evaluation/characterization -Apparents -Non-apparents Adaptive traits:
  7. 7. DIVmapas Provides maps of phenotypic, genotypic and/or eco- geographical diversity
  8. 8. Measuring the diversity of the collections Characterization Morphological Biochemical / Molecular /ADN Agronomical / Physiological / Phytopathological Entomological Eco-geographical
  9. 9. 1246711883124701247112472124731248312484114611247812479114811186823021186911401114051140611407114081183511832118331148411827118281154211539115401246811891124651149311494115081150611507114961149211490114911148911501115631150411502115031154311546115471247411838115341153211533115291152711528115351156411764115241152311522115211152011519115171151811854118411184212477124751247612469114731147211471114691147011477114741147511467114681151611514115151246111848124801154912466124621246311879118751187211874124551245611480124481146011458114591245312454124581245912452114551145311452114511144811450114541145611457124641146611465114621146412457118571185311852118501185112449124501245112440114121141011411114131141412436124371141612441124381243911417114191143111430114281142711426114251142411423114211142212435114321143311551114381143911550114371143611434114351244212443115561156011557115581244712444124451144711445114461144011441114441144211443114881148212283122841148511487 051015 Cluster analysis hclust (*, "average") Height How we have visualized the genetic diversity
  10. 10. -0.2 0.0 0.2 0.4 -0.3-0.2-0.10.00.10.20.3 PCO for genotypic characterization PCO 1 PCO2 d = 2 1 2 3456 7891011 12 13 14 2526 3334353637 383940 414243444546 47 4849 505152 54555657 58596061626364 656667 69 74 75 767778 7980 81 82 838485 868788 899091 9293949596979899 100101102103104105 106 107108 109 113 120 121 122 123124 125126127 128 129130 131 132133134135 136 137 138 139 140141142143 144 145 148149 150 151 152 153 154 157158 159 160 161 162163 164 165166 167168 169 170171 172 173174 175 176 177 178 179 180 181 182 183184 185 186187188 189190 192193 X alt slope bio_15 bio_12 bio_18 bio_17 bio_1 bio_9 t_sand t_caco3 t_cec_clay t_silt t_ph_h2o t_ece Eigenvalues How we have visualized the genetic diversity
  11. 11. DIVmapas A different way to visualize the diversity  Collecting sites with a minimum level of geo-referencing quality
  12. 12. DIVmapas  Overlapping a grid (N x N km cells)
  13. 13. DIVmapas  Selection of cells that include collecting sites (centroids are points in yellow )
  14. 14. DIVmapas  Detection of neighbouring cells which centroids (green points) falls at X km (radius ) around of the presence cell centroid (yellow points)
  15. 15. DIVmapas  Generation of areas of influence from each centroid  Detection of accessions collected within each area of influence
  16. 16. DIVmapas OTU 89 233 152 89 0 233 10 0 152 15 14 0 OTU VAR1 VAR2 VAR3 VAR4 VAR5 89 233 0.56 13 600 0 233 198 1.43 13 700 0 152 201 0.88 10 600 1 Distance algorithm Averaged distance = (10+15+14)/3 = 13  Local multivariate analysis
  17. 17. DIVmapas  Same process for all cells that include collecting sites
  18. 18. DIVmapas  Same process for neighbouring cells
  19. 19. DIVmapas 0 0 0 0 1 3 2 1 1 0 1 1 2 1 1 1 0 1 1 0 0 0 0 0 0 0 0 0 Result 1: Number of analyzed accessions by cell
  20. 20. DIVmapas 0 13 8 0 0 0 0 2 0 0 0 0 0 Result 2: Averaged distances assigned to each cell
  21. 21. DIVmapas  Bias in sampling? Correction via "bootstrapping" 1 2 . . . . . . n Median = 2
  22. 22. Applied DIVmapas Ecuadorian collection of Arachis hipogaea L.
  23. 23. Applied DIVmapas Number of collecting sites per cell
  24. 24. Applied DIVmapas Averaged euclidean distance

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