CAPFITOGEN english presentations for workshops

1. Mauricio Parra Quijano
FAO consultant
International Treaty on Plant Genetic Resources
for Nutrition and Agriculture
CAPFITOGEN Program Coordinator
Tools

2. Representa
Evaluates the ecogeographical representativeness
of germplasm collections

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. Ecogeographic representation
A BBBBBBB CCC
A B C Unique
A BB CC Even
A BBBB CC Proportional

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. Validation through
germplasm evaluation/characterization
-Apparents
-Non-apparents
Adaptive traits:

7. DIVmapas
Provides maps of phenotypic, genotypic and/or eco-
geographical diversity

8. Measuring the diversity of the collections
Characterization
Morphological
Biochemical /
Molecular /ADN
Agronomical /
Physiological /
Phytopathological
Entomological
Eco-geographical

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051015
Cluster analysis
hclust (*, "average")
Height
How we have visualized the genetic diversity

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. DIVmapas
A different way to visualize the diversity
 Collecting sites with a minimum level of geo-referencing quality

12. DIVmapas
 Overlapping a grid (N x N km cells)

13. DIVmapas
 Selection of cells that include collecting sites (centroids are points in
yellow )

14. DIVmapas
 Detection of neighbouring cells which centroids (green points) falls at X km
(radius ) around of the presence cell centroid (yellow points)

15. DIVmapas
 Generation of areas of influence from each centroid
 Detection of accessions collected within each area of influence

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. DIVmapas
 Same process for all cells that include collecting sites

18. DIVmapas
 Same process for neighbouring cells

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. DIVmapas
0 13 8
0 0 0 0 2 0
0 0 0 0
Result 2:
Averaged distances assigned to each cell

21. DIVmapas
 Bias in sampling? Correction via "bootstrapping"
1
2
.
.
.
.
.
.
n
Median = 2

22. Applied DIVmapas
Ecuadorian collection of
Arachis hipogaea L.

23. Applied DIVmapas
Number of collecting
sites per cell

24. Applied DIVmapas
Averaged
euclidean
distance