5. It is difficult to get an overview of the collection
and thus to decide what should be a added or could
be removed
It is difficult to chose material since there is so
much material to chose
It is difficult to focus; knowing very much about
a relatively few accessions can be better than
knowing relatively little about very many
accessions.
Problems in Maintaining GermplasmCollection
6. Frankel and Brown (1984) suggested that greater use
of germplasm in crop improvement is possible if a small
collection representing diversity of well characterized
accessions is made available to researchers.
Frankel (1984) coined the term “core collection” to sample
representative variability from the entire collection.
A core collection contains a subset of accessions from the
entire collection that captures most of available diversity in the
species (Brown 1989a).
The core collection thus formed can be evaluated extensively
and the information derived could be used to guide more
efficient utilization of the entire collection (Brown 1989b).
Core Collection – An Introduction
7. • The entire collection is a large collection with a taxonomic entity
• The core collection has a reduced size
• The core is a representative sample of the entire collection
• Like the entire collection, core too is a diverse set of germplasm.
The guiding principles to constitute a core
collection
8. Global core collection: A core collection developed from these
global germplasm collections could be termed as global core collection.
Regional core collection: Ecological environments influence adaptation of
germplasm accessions
For example, groundnut is cultivated in over 113 countries, but it is an
important crop in 25 countries in the Asian continent. The core developed
from the accessions involving accessions from these countries might be more
beneficial to users in Asia than a global core collection.
Trait-specific core collection: Some research programs might have
special focus on developing a trait-specific core collection, for example,
early maturity.
high heritability and are least affected by G x E interaction.
Types of Core Collection
10. Definition of the domain: The first step in creating a core
collection is defining the material that should be represented,
i.e. the domain of the core collection.
Division in groups: The second step is dividing the domain in
groups, which should be genetically as distinct as possible.
Allocation of entries: The size of the core collection has to be
determined, and the choice of number of entries per group
has to be made.
Choice of accessions: The last step is the choice of
accessions from each group that are to be included in the
core.
General methodology for creating a core
collection
15. Entire collection(EC) in genebank.
Characterize and evaluate EC for complete data set.STEP1
Form groups( using Taxonomic, Morphological & Geographic data; Accessions from
smaller and adjacent countries with similar agro-climatic conditions could be
grouped together)
STEP2
STEP3 Group1 Group2 - - - - - - - - - - - -- - Group n-1 Group n
Clusters Clusters Clusters clusters
Clusters15
16. Analyse the standardized data sets within each group separately.Use standard
clustering produce to group accessions in clusters in each groups.
Select 10% of accessions from each cluters, minimum 1 acccessions if < 10
accessions in a cluster to contribute core (CC)
Compare CC with EC to determine the representiveness in terms of mean
variance, diversity, frequency distributions.etc.CC is representative of EC if these
parameters did not differ significantly between the two sets(CC)
STEP4
step5
21. 5. Choose the entries
from each group that
will be included in
the core.
22.
23. Seminal two-stage strategy for selecting mini core collections with minimum
loss of variability.
the core collection as a basis for developing a mini core collection, which
consists of ~10% accessions of the core collection (~1% of the entire
collection).
The first stage in constituting a mini core collection involves developing a
representative core collection (about 10%) from the entire collection using
the available information on origin, characterization and evaluation
data.
The second stage involves evaluation of the core collection for various
morphological, agronomic and grain quality traits, and selecting a further set
of about 10% accessions from the core collection.
At both the stages, standard clustering procedures were used to create
groups of similar accessions
Mini core Upadhyaya and Ortiz (2001)
24. Entire collection(EC) in genebank.
Characterize and evaluate EC for complete data set.STEP1
Form groups( using Taxonomic, Morphological & Geographic data; Accessions from
smaller and adjacent countries with similar agro-climatic conditions could be
grouped together)
STEP2
STEP3 Group1 Group2 - - - - - - - - - - - -- - Group n-1 Group n
Clusters Clusters Clusters clusters
Clusters24
25. Analyse the standardized data sets within each group separately.Use standard
clustering produce to group accessions in clusters in each groups.
Select 10% of accessions from each cluters, minimum 1 acccessions if < 10
accessions in a cluster to contribute core (CC)
Compare CC with EC to determine the representiveness in terms of mean
variance, diversity, frequency distributions.etc.CC is representative of EC if these
parameters did not differ significantly between the two sets(CC)
Evaluate the representative CC in replicated multilocation trial for morphological,
agronomical and quality traits to identify parents for use. Use unreplicated data
for making subgroups and developing mini core collection(MCC) if the size of CC is
too large
Repeat step 3 and 4 to select MCC there represent CC. Follow step5 to confirm
representativeness of MCC with CC. Mini-core ready for use.
STEP4
step5
STEP6
STEP7
26. The principles and methodologies for appropriate
sampling proportions and the choice of individual
accessions from basic collections are yet
controversial.
Stratified sampling and M (maximization) strategies
are preferred by most researchers (Peeters and
Martinelli 1989; Charmet and Balfourier 1995;
Spagnoletti and Qualset 1993; Schoen and Brown
1993, Zhang, 2010)
Principles and Methodologies for Sampling
Strategies
28. (1) C—constant number
(2) G—proportional to Nei’s gene diversity
index of the group in basic collection****
(3) L—proportional to the logarithmic group
size in the basic collection,
(4) P—proportional to the group size in the
basic collection,
(5) S—proportional to the square-root of the
group size in the basic collection
(Li et al. 2002)
Group Based Sampling Strategies
**** use of markers in core collections
29. (1) by EZ
(2) by sub-species (SS)
(3) by population structure (PS)
30.
31.
32. An increasing number of germplasm
collections are being genotyped for marker
loci such as allozymes, RFLPs,RAPD and SSR
markers.
Schoen and Brown (1993) proposed two
strategies that can use marker diversity to
allocate sampling effort for the
construction of the core collection.
The H strategy seeks to maximize the total
number of alleles in the core collection by
sampling accessions from groups in pro
portion to their within-group genetic
diversity.
Use of Markers in Core Collection
AA AA
bbbb
CCCCdddd
EEEE
ffff
GGGG
hhh
h
A C
fb
G
h
33. The M strategy examines all possible core collections and singles
out those that maximize the number of observed alleles at the
marker loci.
These can then be chosen as final candidates for the core. The
expected superiority of this marker-based method is based on the
correlation between observed allelic richness at the marker loci
and allelic richness on other loci.
Such a correlation (or linkage disequilibrium between marker and
target alleles) is expected on theoretical grounds either because
of (1) shared coancestry of populations, (2) the mating system of
the species considered, or (3) episodes of selection whereby
selected (target) and neutral (marker) alleles become associated
through hitchhiking.
35. Spurious associations due to population structure
Case (50%)
Population 1
20%
Population
2
80%
Control
(65%)
Higher proportion of a causal SNP allele in the subgroup;
Higher penetrance of the causal genotype in the subgroup due to environment;
Ascertainment bias.
36. Sample Marker 1 Marker 2 Marker 3
A1 A2 A3 A4 A5 A6
S1 1 0 0 1 0 0
S2 1 0 1 0 1 0
S3 1 0 0 1 0 1
S4 1 0 1 0 1 0
S5 1 0 0 1 1 0
S6 1 0 0 1 0 1
Example of selection of core sub set based on marker data
39. Retention of SSR alleles (RT) in each core set developed by 225 group-
based sampling
40. Nei’s gene diversity index (He) in each core set developed by 225 group-based
sampling schemes
41. The M strategy aims at selecting the highest diversity among
subsets and is expected to perform well in marker based
grouping.
The MSTRAT program was able to implement the M strategy,
providing the opportunity not only to determine an optimal
CC size, but also to choose the representative individuals for a
given sized CC (Gouesnard et al. 2001)
MSTRAT- M(Maximizing) Strategies
42. Once a core collection has been established, an important
question for genebank managers is the extent to which it meets
its original objectives in terms of the representation of diversity
and lack of repetition.
The principal component score strategy(Noirot et al. (1996))
tends to select entries with extreme expressions of character
states used. With this method, entries with median expressions
may be under-represented.
Test for Redundency (Ortiz.,et al.,1999)
Biochemical and molecular markers have been suggested
core collections of about 10% should possess about 70% of the
alleles found in the whole collection.
Validating the core collection
43. Analysis with statistical indicators
The search using the Power Core was heuristic Approach.
Mean Difference % Variance Difference %
Me: Mean of entire collection
Mc: Mean of core collection
Statistical Parameters Involved
Ve: Variance of entire collection,
Vc: Variance of core collection
44. Re: Range of entire collection
Rc: Range of core collection
CVe: coefficient of variation of entire collection
CVc: coefficient of variation of core collection
m: number of traits
Confidence Ratio % Variable Rate %
Coverage %
De: Classes in entire collection
Dc: Classes in core collection
m: number of traits
45. FUNCTIONS OF A CORE COLLECTION
Addition of
new accessions
Conservation
Characterisation
Evaluation
Germplasm
enhancement
Germplasm
distribution
The core collection
provides a reference
set.
A gene bank are worth
adding to the
collection.
The core collection
provides a reference
set.
A gene bank are worth
adding to the
collection.
46. THE FUNCTIONS OF A CORE
COLLECTION
Addition of
new accessions
Conservation
Characterisation
Evaluation
Germplasm
enhancement
Germplasm
distribution
The core contains material
of highest priority for
conservation.
The core contains material
of highest priority for
conservation.
47. FUNCTIONS OF A CORE COLLECTION
Addition of
new accessions
Conservation
Characterisation
Evaluation
Germplasm
enhancement
Germplasm
distribution
The core is the suitable material
for developing an adequate list
of descriptors
The core is the suitable material
for developing an adequate list
of descriptors
48. FUNCTIONS OF A CORE COLLECTION
Addition of
new accessions
Conservation
Characterisation
Evaluation
Germplasm
enhancement
Germplasm
distribution
Two-step procedure to be carried out in sampling
1.Expensive or complex traits.
2.Focusing evaluation on a restricted set of accessions,
the core assists the development of a multivariate
database.
Two-step procedure to be carried out in sampling
1.Expensive or complex traits.
2.Focusing evaluation on a restricted set of accessions,
the core assists the development of a multivariate
database.
49. THE FUNCTIONS OF A CORE
COLLECTION
Addition of
new accessions
Conservation
Characterisation
Evaluation
Germplasm
enhancement
Germplasm
distribution
The core forms a reduced set of
representative accessions.
The core forms a reduced set of
representative accessions.
50. THE FUNCTIONS OF A CORE
COLLECTION
Addition of
new accessions
Conservation
Characterisation
Evaluation
Germplasm
enhancement
Germplasm
distribution
Representative germplasm on a reduced
scale.
Representative germplasm on a reduced
scale.
54. Core collection Authors Year Reported
Ballforieru Fodder 2005 GRACE
Hu J Rice 2000 TAG
Diwan Medicago 1995 TAG
Thome, J Cassava 1999 IPGRI
Bhattachariayajee,R Pearl
millet
2007 Euphytica
Upadhyaya,HD Groundnu
t
2002 GRACE
Upadhyaya,HD Chickpea 2001 TAG
Li, Y2005 Maize 2005 GRACE
Hot Papers on Core Collection of Different Crops
55. Cereals 4 amaranth, barley, maize (4)†
, wheat
Pulses 8 bean (2), chickpea, cowpea, greengram (3), peanut
Oilseeds 3 safflower, sesame (2), soyabean
Industrial crops 3 beet, hops, rubber
Fruits 12 blueberries, citrus, currants, dates, grape (2), hazelnut,
persimmon, pear, pecan, plum, raspberries, strawberry
Vegetables 6 brassica (2), capsicum, eggplant, lettuce (2), okra (2), potato
Beverages, herbs and spices 4 coffee, garlic, mint, mountain mint
Forages 11 alfalfa, annual medics, berseem clover, Kentucky bluegrass,
red clover, ryegrass (3), shaftal clover, subclover, sweet
clover, trefoil, white clover
Numbers of core collections of various crop types,(IPGRI Survey
†
The number in parentheses is the number of different core collection for that crop.
57. 1.vulnerability of the reserve
collection
2.bias towards diversity rather than
usefulness;
3.inflexibility of core entries; and
4.lack of validity in sampling
variation.
Threaten the size of the total
collection.
Core Collection at Cross Roads (Today)
58. These objections can be grouped
under four headings:
1.vulnerability of the reserve
collection;
2.bias towards diversity rather
than usefulness
3.inflexibility of core entries; and
4.lack of validity in sampling
variation.
A suboptimal sample.
Ignores the relative ease of making the
crosses needed to use a character in
breeding.
Core Collection At Cross Roads
59. These objections can be grouped
under four headings:
1.vulnerability of the reserve
collection;
2.bias towards diversity rather than
usefulness;
3.inflexibility of core entries; and
4.lack of validity in sampling
variation.
The diversity of a collection that is
itself changing.
Reduced scope for studying
interactions among attributes of
all kinds that accrue.
.
Core Collection At Cross Roads
60. These objections can be grouped
under four headings:
1.vulnerability of the reserve
collection;
2.bias towards diversity rather than
usefulness;
3.inflexibility of core entries; and
4.lack of validity in sampling
variation.
Available knowledge of genetic
diversity in any crop may be
insufficient.
No explicit account of
polymorphism within accessions
Core Collection At Cross Roads
61.
62. Uses of Core collections
Several new sources of variation for use in crop improvement
programs.
Allele mining
Duplicate conservation (Black Box arrangement)
Limited size of the core is the key reason for its overall manageability
Reference set of accessions for the whole collection
Pre Breeding Programs
Greater information value of the collection, reduced costs and
increased efficiency in evaluation
(1) Comprehensive synthetic core collections for a whole species,
(2) Clonal core collections
(3) Core collections in glacie or DNA banks
(4) Core collections for in situ conservation.
64. Common set of reference materials to help R.E.A.D.
R-Represent existing diversity
E- Enter the whole collection
A-Assess phenotypic variation
D-Dissect trait–gene associations
Germplasm through concerted efforts within the research
community.
R.E.A.D.
65. SINGER
Documentation is essential in good genebank management to allow efficient and
effective use of germplasm.
CGIAR’s System-wide Information Network for Genetic Resources (SINGER).
This searchable database has information on the identity, origin, and characteristics
of the accessions in CGIAR genebank http://singer.grinfo.net.