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Data Management for Integrated Breeding
Graham McLaren
Principles of DM for Integrated Breeding (IB)
IB requires high standards of sample and pedigree identification,
it requires integration of field and lab data, and quality is of paramount importance. Data collected during breeding processes
has immediate value for breeders and it also has cumulative value over years and
populations.
Three Types of Data for IB
1) Genealogy or pedigree data
parents
unique identification of germplasm through Germplasm IDs (GID)
names
2) Phenotypic data
3 Types of Data
observable characteristics or traits
environmental
data across studies are linked via controlled trait vocabularies / standard terms
3) Genotypic data
3 Types of Data
usually with reference to a specific trait under consideration
genetic composition
Importance of Data Management
Data that are properly managed are:
Importance of Data Management
Data that are properly managed are:
= Shareable more accessible to
research partners
national and global sharing & linking of data
Importance of Data Management
Data that are properly managed are:
= Available enables reliable
analysis & conclusions
leads to better science & more sophisticated research
Importance of Data Management
Data that are properly managed are:
= Re-usable more likely to be used again
for different purposes
Importance of Data Management
Data that are properly managed are:
important for historically significant data
scientific method changed to: hypothesize , then look up answer in database
= Preservable
Importance of Data Management
Data that are properly managed are:
areable
vailable
e-usable
reservable
Information Cycle for Crop Improvement
Public Crop Informationaccessible via internet
Genetic Resources Information
Systems
Genomics and
Genetics Databases
Crop Lead CentersCuration, integration and publication
of Public Crop Information
Breeding Inform
atics C
omm
unity of Practice
InstitutionalCIS
NationalCIS
ProjectCIS
PrivateCIS
ARILocal CIS
NARSLocal CIS
NetworksLocal CIS
SMEsLocal CIS
Shared Information management Practices
The IBP Configurable Workflow System
Breeding Activities
Parental selectionCrossingPopulation development
GermplasmManagement
Open ProjectSpecify objectivesIdentify teamData resourcesDefine strategy
Project Planning
Experimental DesignFieldbook productionData collectionData loading
GermplasmEvaluation
Marker selectionFingerprintingGenotypingData loading
MolecularAnalysis
Quality AssuranceTrait analysisGenetic AnalysisQTL AnalysisIndex Analysis
DataAnalysis
Selected linesRecombinesRecombination plans
BreedingDecisions
MB design tool,Cross predictionand Strategic simulation
Breeding ProjectPlanning
Breeding nurseryand pedigreerecordmanagement
Breeding Management
System
Trial field bookand environment characterizationsystem
Field Trial Management
System
Genotypic DataManagement
System
Statistical analysisapplications andselection indices
AnalyticalPipeline
MABCMASMARSGWS
Decision Support System
Breeding Applications
Lab book,quality assuranceand diversityanalysis
1. Search for Germplasm Search a particular germplasm by name from the database
Understand the information about germplasm entries contained in the ICASS database.
2. Import Parental ListsMALE2009FEMALE2009
Set of 12 female parents and 12 male parents (some repeated) with high protein content and CMD Resistance
There were will be two lists created. One for female parents and another one for male parents
3. F1 NurseryNR2009F1(2008-11-15)
F1s planted 12 crosses made from the female and male parents
4. Clonal PropagationNR2010C1
283 plants developed through clonal propagation
Derive 284 plants from the F1 through clonal propagation
5. Selected ClonesNR2011V1
25 selected from the initial list of clones
Select 25 individuals from the initial clones for traditional clonal increase
6. Field TrialNR2011V1
The selected clones will be tested in the field for evaluation
There will be 3 locations and 3 reps in RCBD
A Simple Workflow for the Cassava Tutorial
Running the Cassava Tutorial
