UNIVERSITY of FLORENCE
Department of Plant, Soil and Environmental Science
EVALUATION OF THE GENETIC VARIABILITY
USING MOLECULAR MARKERS IN POPULATIONS
OF CULTIVATED SPECIES AND ITS UTILIZATION
IN THE GENETIC IMPROVEMENT OF THE
ZOLFINO BEAN
Lisetta Ghiselli and Stefano Benedettelli
lisetta.ghiselli@unifi.it
Biodiversity in Agroecosystems
Milano, 24-25 February 2011
WHAT ARE THE PROBLEMS FOR THE
CULTIVATION OF “ZOLFINO” ?
The Zolfino cv.
is a typical
Tuscan
common bean
Pratomagno landscape
Traditional food
It is cultivated
in the hilly and
mountainous
region of
Pratomagno
PROBLEMS
LOW PRODUCTION
GENETIC EROSION
The actual breeding systems in practice could produce varieties
not suitable for this cultivation
“GREEN REVOLUTION”
Contributed to world
famine reduction
Caused a loss of
GENETIC DIVERSITY
The breeding systems
were changed.
This resulted in the
selection of cv with:
•High production,
•Uniform crops,
•Introduction of standards,
•Homogeneous plants
LOSS of
numerous
heterogeneous
traditional farmers’
varieties
NOW
150 species of food
crops are cultivated
Mankind lives off no
more than 12 plant species
DANGERS OF GENETIC EROSION
Green revolution
Modern Breeding
systems in practice
(intensive agricultural
systems, environmental
pollution, ground erosion)
High degree of
genetic similarity
of new varieties
GENETIC EROSION
Loss of local species and varieties usually results in an
irreversible loss of genetic diversity.
This has dangerously reduced the genetic pool that is
available for natural selection
 Problems of adaptability of species to
environmental change (climate change),
 Increase in the vulnerability of agricultural crops
to abiotic and biotic stress (pests and diseases)
DANGERS OF GENETIC EROSION
1845
potato
Phytoftora infestans (UK)
1860
vitis europea
Phylloxera vastatrix
1890
coffee
Hemileia vastatrix (rust) Sri Lanka
1917
wheat
Puccinia graminis (stem rust)
1943
rice
Cochliobolus myabeanus
1946
oat
Cochliobolus victoriae (America)
1960
tobacco
Peronospora tabacina (Italy)
1970
coffee
Hemileia Vastatrix (Brasile)
1971
maize
Helminthosporium maydis (America)
1950
banana
Fungal diseases
History has provided some important examples of these dangers
EXPERIMENT ON THE ZOLFINO BEAN
To address the problem of genetic uniformity, an experiment was
carried out on the Zolfino bean.
The experiment was conducted over five years.
The OBJECTIVE was to select genotypes with
different properties that could be used for a
multi-line variety constitution.
EXAMPLE: “ZOLFINO” BREEDING
COLLECTION
GERMPLASM
Field trials evaluation
DNA extraction
Seed production
Genetic evaluation of the
gene pool
Pure lines
Pure lines combination
Varietal trial evaluations
MULTI-LINE VARIETY
CONSTITUTION
VARIABLES CONSIDERED
GENOTYPE FIELD EVALUATION
• Morphological
• Production
•Tolerance to biotic and abiotic stress
• Quality characteristics
In collaboration with the farmers
LABORATORY ANALYSIS
• Genetic characterization with SSR primers
• Genetic variability with Storage Proteins
• Diseases monitoring and characterization
1,8 m
LINE EVALUATION AND SEED
PRODUCTION
2m
For the production of seed,
the material was isolated from
insects in tunnels. This was
done to promote selfimpollination
MORPHOLOGICAL CHARACTERISTICS
Plant data
in the field
Plot Data
• % Emergence
• % Flowering
• Production t/ha
• date of flowering
• estimation of fruit
development
• plant height
• n. of side-branches
• viral incidence
Post-harvest parameters
• n. of pods
• pod length
• pod width
• n. of seeds per pod
• weight of 1000 seeds
Evaluation of Genetic Variability
To evaluate the genetic variation in the selected lines
two methods were used
94 kD ►
m a rk e r
m a rk e r
12 different SSR Primer
Combinations
m a rk e r
4 different STORAGE PROTEINS
1000bp
500bp
67 kD ►
100bp
•1
•3
43 kD ►
•2
•4
prim er 4
prim er 6
•5
12•
•10
•11
m a rk e r
30 kD ►
m a rk e r
•9
m a rk e r
•6
7•
8•
1000bp
500bp
100bp
prim er 12
20.1 kD ►
F
1
F2
F3
F4
F1
F
1
F5
F
1
F1
F6
F7
prim er 13
altezza
attesa
163 bp
STATISTICAL DATA ANALYSIS
Quantitative characters
• Univariate analysis of variance (ANOVA):
years and locality were considered random effect factors
genotypes were considered fixed effect factors
• Multivariate analysis of variance (MANOVA) included
the Principle Component Analysis PCA and cluster
identification (k-means clustering)
Molecular data
• Jaccard index
• Sahn clustering method
The results were shown using Dendrograms
RESULTS: MORPHOLOGICAL AND YIELD
CHARACTERISTICS
 The PCA showed the
distribution of the lines
on the basis of the
morphological and yield
data.
 We obtained an initial
phenotypic classification,
where it was possible to
observe homogeneity in
each group.
 These genotypes,
respected the varietal
standards of the modern
varieties.
RESULTS: GENETIC CHARACTERISTICS
This dendrogram
shows the distribution
of the lines
representative of the
populations of Zolfino
on the basis of the
genetic variability
obtained from using
the SSR primers
By combining the genetic and morphological
characteristics, it was possible to obtain pure lines for
the multi-line variety constitution.
G 36 G 27
G 31
G 1 G 17
G 19
G 15
G 13
G 22
G 28
G 40
G 16
G 25
G 23
G 24
G 46
G 14
G 38
The aim was to have the maximum variability in each homogeneous class
MULTI-LINE VARIETY CONSTITUTION
Variety name
Genotype
Variety
Characteristics
Variety name
Genotype
Variety
Characteristics
Variety 1
G36
Less productive
genotypes.
Elevated genetic
variability
Variety 4
G13
Morphological
and productive
characteristics
variable. Less
genetic
variability.
G27
G17
G14
G24
G1
Variety 2
G19
G15
G22
G16
Variety 3
G25
G23
G46
G22
G31
Average
production
genotypes.
Elevated genetic
variability
Highly
productive
genotypes.
Elevated genetic
variability
Variety 5
G27
G28
G36
G40
Average
morphological
and productive
characteristics.
Less genetic
variability.
On the basis of the results, after
the fourth year, we constituted
five multi-line varieties.
Each variety was produced from the combination of four
different genotypes extracted from 18 genotypes.
EXPERIMENTAL FIELD EVALUATION
It is very important to evaluate
the behaviour of the plants
under field conditions for
many years
The photo shows the experimental field trials to evaluate the
morphological and productive characteristics in the final year. The
samples were cultivated in a randomized block design with three
replicates in four localities in Tuscany
GENERAL COMBINING ABILITY AND
SPECIFIC COMBINING ABILITY (SCA)
It is also important to evaluate the combining ability of each single
genotype with all the other genotypes
GENOTYPE
G1G17
G1
G1G19
G1G27
G1G36
G17G19
G17G27
G17G36
G19G27
G19G36
G17
G19
G27G36
G27
G36
SGCA
1 5 2
4

X

X 2

i
p  2 i 1
p  p  2
5
S SCA
5
1 5 2
2
  x 
X

X 2

i
p  2 i 1
( p  1)( p  2)
i  j j i 1
2
ij
For example combining
5 genotypes, 2 at a
time, it is possible to
have 10 different
combinations
These formula (Partial
Diallelic Cross) are used
to evaluate the Combining
Ability (general and
specific) of each single
genotype (by Griffing 1956)
The method allows the identification of those genotypes that combine
better with others
CONCLUSIONS
The combination of Multivariate analysis with Genetic
variability data are useful:
 To define new varieties that are suitable as food crops and
that are adapted to different environments
 To obtain multi-line varieties which contain elevated genetic
variability, and consequently an elevated stability in
production
 To monitor the genetic changes of frequencies of genotype
within both populations and varieties, useful for germplasm
conservation and for variety stability
Tank you very much
for your attention