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(1)

Integrated Breeding Platform

Breeding Management System

(BMS)

IBP Management Team

March 2014

(2)

Rationale for the IBP

l 

Large private seed companies have successfully

implemented extensive suites of integrated informatics

tools to turbocharge their breeding programs

l 

Implementation of this integrated informatics in public

programs lags behind, especially in developing countries

l  Some tools have been developed at various CG centers, but

implementation has been uneven and they are not integrated into a comprehensive system

l  Most NARS programs still rely on rudimentary tools, from pen

and paper to Excel spreadsheets

l  Small SMEs in developing countries typically do not have the

(3)
(4)

Breeding Management System

(BMS) – Product Concept

t 

Simple and easy-to-use application containing all

informatics tools needed by a breeder

t 

Seamless flow of data between applications

t 

Accumulation, sharing and re-use of breeding data

t 

Targets routine breeding activities and will not replace

research tools

t 

Will allow integration of users own tools into the system

t 

Implementable as a standalone system

t  Access central and local DB, as well as the BMS on a local PC

t 

Will also be implementable as a cloud-based system via

iPlant cyber-infrastructure

t  For computationally intensive analyses or large data storage

(5)

Breeding Management System

(6)
(7)

BMS Project Planning

Crop Databases

l

Bean

l

Cassava

l

Chickpea

l

Rice

l

Sorghum

l

Wheat

Databases used by a program :

l

Cowpea

l

Groundnut

l

Maize

l

Program Database

(8)

BMS Project Planning

Crop Databases

l 

Genealogy Management System (GMS)

l  Germplasm nomenclature, chronology, IP and passport data

l  Pedigrees and breeding history

l 

Phenotyping Data Management System (DMS)

l  Germplasm characterization and evaluation data

l  Annotated with Crop Research and Crop Trait Ontologies

l 

Genotypic Data Management System (GDMS)

l  Medium density fingerprinting data

l  Genotyping data for MAS and MABC

l  Genotyping data for Marker-trait association analysis

(9)
(10)

Breeding Management System

(11)

Once the strategy and parental material have

been identified, the breeder wants to:

l 

make crosses,

l 

develop populations,

l 

track pedigrees,

l 

track inventory,

l 

characterize lines

(12)

Germplasm Management

List Manager Functionality

The List Manager is at the center of all activities in the Breeding

Management System:

l  First screen you arrive at after opening your Breeding Program

l  New left navigation menu provides direct access to all tools

l  Easily build and work with the lists that are used in each stage of

the breeding cycle

l 

Key List Manager Features:

l  Ability to browse and modify existing lists

l  Ability to search for lists and germplasm entries

l  Ability to create a new list dynamically by pulling from existing

lists or germplasm search results

l  Expanded ability to modify list contents

l  Ability to export lists for use outside of the Breeding Management

(13)
(14)
(15)
(16)

Breeding Management System

(17)

Field Testing

Once populations are developed, the breeder

wants to:

l 

select traits,

l 

make lists of germplasm,

l 

generate designs,

l 

produce fieldbooks,

l 

collect data,

(18)

Germplasm Evaluation

Nursery and Trial Management

l 

Breeding Manager configured for different crops

l  Crossing manager, nursery manager, pedigree recording

l  Focuses on population development and line selection

l  Nursery advance and seed inventory tracking

l 

IB Fieldbook

l  Focuses on field trial management for germplasm evaluation

l  Trait selection, field design, labels and sample tracking

l 

Android-based hand-held device

l  Optimized for use with Samsung Galaxy tablet for field data

collection

l  Other Android devices can be used if preferred

(19)

Germplasm Evaluation

Trait Dictionaries

Measurement Variate

Trait property

Reporting units or scale

(20)
(21)
(22)
(23)
(24)
(25)

Molecular Analysis

Genotyping Data Management

To use molecular technologies, the breeder

wants to:

l 

select population,

l 

select markers,

l 

genotype population,

(26)
(27)

Breeding Management System

(28)
(29)

Statistical Analysis

Breeding View

l 

Breeding View provides easy access to the high

throughput analyses routinely required by breeders

l 

The same interface can be used to access procedures in

Genstat or R-scripts and allows analyses to be configured

l 

Single site analysis is available for complete and

incomplete block designs as well as row-column designs

and spatial analysis. New designs are being added at

each update,

l 

Analyses can be run in batches over environments and

traits,

l 

Two-stage multi-site analysis is available for GxE and

stability analysis with or without grouping of

environments,

l 

Single pass meta analysis of unbalanced site by season

data is being incorporated.

(30)

Breeding View - QTL analysis

l 

Single trait linkage analysis (QTL)

l  Quality control phenotypes (summary statistics)

l  Quality control marker data

l  QTL detection – genome wide scan using single and composite IM

l  Output includes profile plots and tables

l  Results available for automatic viewing in Flapjack

l  HTML report of QTL results

l 

Multiple trait sequential analysis

l  QTL results for each trait combined

(31)
(32)

Decision support for

Marker implementation

l  OptiMAS

Developed at INRA, Le Moulon

Implementation of markers in a MARS breeding scheme Identify and track

favorable alleles through cycles of recombination and selection

l  Molecular Breeding

Decision Tool (MBDT)

Developed by team at ICRISAT

Implementation of

(33)

Future Directions

l 

Continuous improvement of UI based on user

feedback

l 

Additional analysis methods for expanded

experimental designs and genetic analysis

l 

Seed inventory management system

l 

LAN based deployment available in June 2014,

cloud based deployment available in 2015

l 

Data will be stored in a single shareable database

with user access roles

l 

Off-line capability will be supported by a data cache

References

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