Core Collection

Core CollectionCore Collection

A. Manivannan Scientist(Genetics)

DMRNew Delhi

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BASE COLLECTION

CORE COLLECTION

RESERVE COLLECTION

MINI CC

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

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

• 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

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

200 accessions

20 accessions

Increase the balance between types of material in a relatively small selection of accessions.

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

Definition of the Domain

Division in Groups

Allocation of Entries

Choice of Accessions

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 clustersClusters15

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

1.Identify the material (collection) that will be represented.

2. Decide on the size of the core collection.

3. Divide the set of material used into distinct groups.

4. Decide on the number of entries per group.

5. Choose the entries from each group that will be included inthe core.

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)

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 clustersClusters24

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

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

Stratified sampling strategies

(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 groupsize 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

(1) by EZ (2) by sub-species (SS) (3) by population structure (PS)

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

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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.

Association analysis

Case (30%) Control (50%)

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.

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

Power Core

Zhang et al.,2011

Retention of SSR alleles (RT) in each core set developed by 225 group-based sampling

Nei’s gene diversity index (He) in each core set developed by 225 group-based sampling schemes

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

Once a core collection has been established, an importantquestion for genebank managers is the extent to which it meetsits original objectives in terms of the representation of diversityand 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 suggestedcore collections of about 10% should possess about 70% of thealleles found in the whole collection.

Validating the core collection

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

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

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.

THE FUNCTIONS OF A CORE COLLECTION


Conservation

Characterisation

Evaluation



The core contains material of highest priority for conservation.

The core contains material of highest priority for conservation.



Conservation

Characterisation

Evaluation



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



Conservation

Characterisation

Evaluation



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.



Conservation

Characterisation

Evaluation



The core forms a reduced set of representative accessions.

The core forms a reduced set of representative accessions.



Conservation

Characterisation

Evaluation



Representative germplasm on a reduced scale.Representative germplasm on a reduced scale.

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Applied 1

Applied 2 . . . . . .

Applied 6

Primary core-collection

Core-collection (100) ~ 10% of Base Collection

Mini core-collection(10) ~ 1% of Base Collection~ 10% of Core Collection

Applied core-collection

Basic Collection (1000)

Structure of a Core Collection

Algorithms for Core Collection

Core HunterPower CoreMSTARTPower MarkerSTRUCTURE

Core Selector "core from the core”

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 Groundnut

2002 GRACE

Upadhyaya,HD Chickpea 2001

TAG

Li, Y2005 Maize 2005 GRACE

Hot Papers on Core Collection of Different Crops

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.

Core Collection at Cross Roads (Today)

1.vulnerability of the reserve collection2.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)

These objections can be grouped under four headings:

1.vulnerability of the reserve collection; 2.bias towards diversity rather than usefulness3.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


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..



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


Uses of Core collectionsSeveral 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.

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Basecollection

Corecollection

Existing diversity

Reference Set

A set of genetic stocks that are representative of the genetic resources of the crop and are used by the scientific community as a reference for an integrated characterization of its biological diversity.(50-500)

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.

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.

Science

Core Collection