CFA- Molecular Breeding @

ICRISAT

Rajeev Varshney

Center of Excellence in Genomics

ICRISAT

Genomics-assisted breeding: Predicting the phenotype

Genotype

Gene(s)

Trait/QTL

Phenotype

Transcriptomics Proteomics Metabolomics TILLING EcoTILLING

EST Sequencing Genome Sequencing Map-based Cloning

Genetic Mapping Physical Mapping

Genetic Mapping Association Mapping QTL Mapping Trait Correlations

Genetic Resources

Improved germplasm

Trends Pl Science 2005; Trends Biotech 2006

MABC, MARS and GS approaches seem to most

promising for crop improvement

Need to have genomic resources and cost-effective

genotyping platforms

Precise phenotyping platforms required

Breeders-friendly pipelines and decision support tools required for prediction of phenotype

Modern breeding approaches for increasing genetic gains

A route developed and taken by breeders: From germplasm to

variety/hybrid

Germplasm

Superior variety

A variety of approaches (cars)

• MAS: MARKER-ASSISTED SELECTION - Plants are selected for one or more (up to 8-10) alleles

• MABC: MARKER-ASSISTED BACKCROSSING

– One or more (up to 6-8) donor alleles are transferred to an elite line

• MARS: MARKER-ASSISTED RECURRENT SELECTION – Selection for several (up to 20-30) mapped QTLs relies

on index (genetic) values computed for each individual based on its haplotype at target QTLs

• GWS: GENOME-WIDE SELECTION

– Selection of lines based on genome-wide marker data for tolerance/resistance/ superiority to traits of interest using GEBVs

Germplasm

Superior variety

Developing infrastructures and sign posts for providing directions

The sorghum genome

98% of genes were placed in their chromosomal context using whole-genome shotgun sequence validated by genetic, physical and syntenic information.

Genetic recombination is

largely confined to about one-third of the sorghum genome with gene order and density similar to those of rice.

Retrotransposon accumulation

in recombinationally recalcitrant heterochromatin explains the 75% larger genome size of sorghum compared with rice.

Illumina sequencing tech used to generate 237.2 Gb

72.7% (605.78 Mb) of the total pigeonpea genome assembled into scaffolds

Genome analysis predicted 48,680 genes

High levels of synteny observed between the pigeonpea and soybean

>50,000 SSR and SNP markers identified

Higher abundance of drought tolerance genes

The pigeonpea genome

The chickpea genome

• Illumina sequencing used to generate 153.01 Gb

• 73.8% of the genome is captured in scaffolds

• Genome analysis predicted 28,269 genes

• High levels of synteny observed between chickpea and Medicago

• > 81,845 SSRs and 4.4

million variants (SNPs and INDELs)

Center of Excellence in Genomics (CEG)

SSR genotyping

DArT genotyping

SNP genotyping

High-throughput Sequencing

CEG facilities

Genotyping services extended

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ICRISAT National partners Overseas

Create a new Project, Study

Start a new experiment

LIMS

Plate File Generated by LIMS System that servers as an input to the ABI Sequencer used (Sample file is for ABI Sequencer 3700)

LIMS

• Assemble & Align Raw Reads

• Mine SNPs • Generate Marker Matrix • Automated Visualize in

TABLET and FLAPJACK • Developing genotyping

assays • Export in FLAT Files

ISMU V1

Raw Reads

Reference

Assemble & Align Raw Reads Mine SNPs Generate Marker Matrix Visualize in TABLET and FLAPJACK Export in FLAT Files

ISMU

GDMS

GDMS

GDMS

1. Accession List

3. QTL Maps

4. Linkage Map

5. Heat Maps

6. Creation of Target Genotype

2. Subset

7. Similarity Matrix

MBDT- Molecular Breeding Design Tool

Information System for Marker-Assisted Backcrossing

(ISMAB)

Complete data management of breeding, including

management of segregating material, planting plans, analysis of data, data reporting and making field books

Using a single software package to manage variety and pedigree information, design trials, aid in field operations, and analyze and store data eliminates the time lost from transferring data between applications

Good software and user support provided

Breeding data management

First generation molecular breeding products for root traits in chickpea and leaf rust in groundnut

MABC products in fields

GWS

MARS

ISMU V2

Raw Reads

Reference

Assemble & Align Raw Reads Mine SNPs Generate Marker Matrix Visualize in TABLET and FLAPJACK Export in FLAT Files

GDMS

Genotypic Matrix & QTLs

Select lines for further crossing in MARS & GWS

External Genotyping Platforms

Called SNPs

ISMU version 2.0

Summary

State-of-art genotyping facilities are available Bioinformatics and molecular breeding pipeline

becoming available Regular monthly meeting being held (including

scientists from different disciplines) Efforts have initiated to implement GS in breeding

programme Working in close collaboration with Integrated

Breeding Platform of GCP

Linking with “Enhancing Genetic Gain” and “Digital Design for Agriculture” initiatives of Gates Foundation

Safe driving!

Genomics

Crop improvement

In context of Strategic Plan-2020

& CGIAR Research Programmes…

Crop improvement

Taking crop improvement to more heights

(higher genetic gains)