The Global Planning Meeting 2019 focused on implementation plans for modernisation of ICRISAT crop improvement and to review and enhance the existing crop breeding programs, discuss modernization of crop improvement, and strategize how to harness new tools to maximize genetic gains. Innovation systems research was also discussed in detail to ascertain how all the different disciplines in crop improvement, innovation systems and other global and regional programs can work together to contribute to ICRISAT’s mission.

1. ICRISAT Science
RP- Genetic Gains
By:
Rajeev Varshney & Team

2. Integration of RP-Genetic Gains with other RPs
Farmers fields
Research Program
Genetic Gains
Research Program
ISD
Research Programs
Asia, ESA, WCA
Crop Improvement
Int. Crop Management
Breeding Population
Selfing and selection
Advanced
breeding
lines
Parental
lines
Varieties Hybrids
NARS/ Pvt. Sector
Pre-breeding
Genomics &
Trait discovery
Forward
Breeding
Marker
Cell, Molecular
Biology & Genetic
Engineering
Seed Systems
Agribusiness and
Innovation
Platform
Systems analysis
for Climate Smart
Agriculture
Phenotyping
Diversity
Trait specific
lines
Strategies
Lessons
Mapping
homologous
environments to
target varieties/
quantity of seed
MIND analysis to
maximize
outcomes
Sequencing and Informatics Services
Consumers
Systems Biology
Research Initiative
Genebank
Rt =
irsA
y

3. • Focus- Climate resilience, nutrition and market traits
• Large-scale germplasm sequencing & value addition
• Novel trait pre-breeding lines and compressing pre-breeding time
• Candidate genes, QTLs and diagnostic markers for must-have traits
• Novel breeding approaches tested, validated and deployed
• Biotechnology and genomics approaches for aflatoxin in groundnut,
Striga resistance in sorghum, rancidity in pearl millet
• Doubled haploidy and speed breeding methods optimized
• Strengthening & modernization of seed systems
• Linking agriculture (our crops) with human health thru systems biology
• New sequencing and genotyping platforms
• Resource mobilization, enhanced capacity building & communication
Forward-looking synopsis

4. Germplasm Research
Promotion of the use – Molecular Characterization
• Collection management
• Collection rationalization (duplicates)
• Use of molecular markers linked to important traits.
Big objective:
• Genotype entire collection;
• Estimate diversity within and among accessions;
• Development of thematic subsets
DArT-seq Pilot Projects 1 and 2
• Genotyping: 12,000 samples, three crops,
8-25 plants/crop
• Phenotyping: ~ 5,000 samples in field and
12,000 samples – nutritional traits

5. Blast Drought Heat
 Four advanced backcross populations
(BC2F6)developed from Pennisetum violaceum
 Evaluated in multilocation trials over years
PearlMilletGroundnut
Stem rot LLS Rust
 Three advanced backcross populations
developed from A. duranensis , A. ipaensis, A.
kempff-mercadoi and A. hoehnei
 Evaluated in multilocation trials over years
PigeonpeaChickpea
• Blast
• Terminal drought
• Flowering-stage heat
• Phytophthora blight
• SMD and wilt
• Pod Borer
• Stem rot
• LLS
• Rust
• Botrytis gray mould (BGM)
• Dry root rot (DRR)
• Ascochyta blight (AB)
Global Crop Diversity Trust funded project
 Multiloation trials of high-yielding ILs in India
and Myanmar
 Four advanced backcross populations ( BC2F3,
& 4-way BC1F3) consisting of ~2321ILs
developed for improving pod borer tolerance
using C. scarabaeoides and c. acutifolius
 Four advanced backcross populations
developed using C. reticulatum and C.
echinospermum for BGM and DRR tolerance
Global Crop Diversity Trust funded project
Blight Wilt Pod Borer
BGM ABDRR
Bringing wild species alleles thru Pre-breeding

6. Sharing new pre-breeding materials and knowledge
to 8 countries in Asia and Africa
Crop Shared Lines Country
Groundnut 87 Malawi, Niger, Mali, India
Pearl millet 105 Niger, India
Pigeonpea 86 Myanmar, Kenya, India
Chickpea 1091 Ethiopia, Turkey, India

7. Compressing pre-breeding
time frame
Chickpea
Studied the effect of vernalization and photoperiod
treatments on flowering and identified wild Cicer species
and cultivated chickpea genotypes responsive to
vernalization and extended-photoperiod treatments
(Sharma & Upadhyaya 2015; Crop Science 55: 1-8)
Identified critical day length required by wild Cicer species
and cultivated chickpea (Sharma & Upadhyaya 2018; Crop
Science)
Studied the effect of light quality & response of ovule
culture versus immature seed germination (Manuscript
under preparation)
Extended-photoperiod treatment in chickpea
White light Yellow light
Response of ovule culture versus immature seeds
germination in chickpea & groundnut
8 days immature
seeds of chickpea
White
light
Yellow
light
Photoperiod treatments in pigeonpea
Immature seed
germination in
groundnut
11 days immature seeds
of chickpea in soil

8. Understanding genes, genomes, and germplasm
• Development of key genetic and genomic
resources
• Improved and high quality genome assemblies
for cultivated and wild species
• Deciphering the core and dispensable genome
through PAN Genome
• Capturing the genetic variation present in
diverse germplasm through whole genome
re-sequencing
• Connecting phenome with genome using
transcriptome, proteome and metabolome

9. Next-generation trait discovery
• Family-based and natural populations
• High-medium-low density genotyping assays
• Linkage and LD-based high resolution mapping
• Identification of QTLs and MTAs for target traits
as per PCNs and other global challenges
• Candidate gene discovery and functional
validation
• Development and validation of diagnostic
markers
Diagnostic markers
QTL and gene discovery
Multi-parent populations

10. Genomics-assisted breeding
• MAS, MARS and MABC for target
traits
• Development of super donors for
multiple traits
• Development, optimization and
deployment of GS breeding
• Understanding and development
of heterotic pools for crop
improvement
Genomic selection

11. Genome to field: downstream applications
• Strengthening seed-chain system through
• Marker-based purity testing
• DNA fingerprints database for elite
cultivars and founder parents
• Diagnostic markers for target traits
• Genomics-assisted improved lines
• Enabling NARS partners in genomics-based
crop improvement
• DNA-fingerprinting support for varietal release
• Socio-genomics for impact assessment
• Influencing national/international agriculture,
science and research policies

12. Rice
$306,058
Wheat
$153,378
Maize
$137,549
Potato
$89,232
Cassava
$183,766
Groundnut
$79,640
Common Bean
$37,824
Sorghum
$37,438
Cowpea
$25,528
Finger Millet
$16,123
PigeonPea
$11,400
Pearl Millet
$9,984
Soybean
$7,104 Yam
$4,800
Chickpea
$4,680
Overall Investment by Crop
(Routine + Verification)
Genotyping:
$1,104,505
High throughput genotyping (HTPG) project

13. $83,160 $144,462 $104,638
$592,234
Year 1
AUG 2016 to JUL 2017
Year 2
AUG 2017 to AUG 2018
2016 to 2018 volume to date
New genotyping
platform
•Expected offering in 2019
•Mid - High density genotyping
(100 to 5K SNPs)
•Global access though service provider
•All crops included
•Cost: < $10 per sample
•Includes: DNA, Genotyping,
Bioinformatics
•Data interoperability & scalability

14. P1 × P2 P1 × P2 P1 × P2 P1 × P2 P1 × P2 P1 × P2
F2
F5
Practical Haplotype Graph Genotyping
6000 F5 plants
Allele calling
Training
population
(320 lines)
Selection of lines based on GEBV
lines in field for evaluation
Oct 18-Mar 19
Compare field evaluation vs GEBV lines Apr-May 19
Genomic
selection in
chickpea

15. Line/ variety* No. of lines
selected
Varieties 69
Landrace 15
Hybrids 29
Donor/ recipient parent (bmr, shoot fly,
Anthracnose & Leaf bligh, biomass, QTL
donor lines)
17
B lines 59
R lines 36
A2 Hybrids 2
A3 Hybrids 1
A4 Hybrids 1
BC2F4 (ILs) 3
TOTAL 232
*Panel of 232 lines planted in 2018
Rainy season at three locations in India:
Parbhani, Akola and Patancheru
• Training population encompassing parent material for all important traits
• Participation of two AICSIP centres - Parbhani, Akola
• Varieties/ lines/ hybrids from NARS (both from India and Africa)
• Phenotyping for morphological and agronomical traits along with key traits for tolerance/resistance
• Multi-location data
Genomic selection in sorghum
Implementing GS in sorghum breeding

16. 2017
• Upload files from local computer
• BGLR models and allow model specification
• K fold cross validation
2018 (green= in active testing)
• Enhanced encoding and sample matching tools
• PCA and similarity matrix, clustering tools
• BLUP and BLUE calculator
• GEBV calculators, including GBLUP
• Consistent input and output formats to connect between tools
• User defined cross validation within and across groups
• Crop-specific GS workflow
2019+
• Galaxy to pull dataset from GOBii through livelink
• Direct query data and access to data sources GOBii or BDMS/BMS
• User friendly UI
• Include G x E
• Push BLUP/BLUE, GEBV, and selection results to store in databases
GS-Galaxy analysis pipeline functionalities
Start
Stop

17. Experimental
design
Capture Collate/
organize
Curate AnalyzeArchive
Planting and
labeling in field
DNA Assay 38474037 38668738 38748270 38867490 MSU7_12_17391484_G/TMSU7_12_17391872_A/GMSU7_2_10003379_C/A
Plate 01-A01 G:G G:G T:T T:T T:T A:A A:A
Plate 01-A02 G:G G:G T:T T:T T:T A:A C:A
Plate 01-A03 G:G G:G T:T T:T T:T A:A C:A
Plate 01-A04 A:G A:G C:T G:T T:T A:A C:A
Plate 01-A05 A:G A:G C:T G:T T:T A:A C:C
Plate 01-A06 A:A A:A C:C G:G T:T A:A A:A
Plate 01-A07 A:G A:G C:T G:T T:T A:A C:C
Plate 01-A08 A:G A:G C:T G:T T:T A:A C:A
Plate 01-A09 A:A A:A C:C G:G T:G A:A A:A
Plate 01-A10 G:G G:G T:T T:T T:T A:A C:A
Plate 01-A11 A:A A:A C:C G:T T:T A:A A:A
Plate 01-A12 A:G A:G C:T G:T T:G A:A C:A
Plate 01-B01 A:G A:G C:T G:T T:T A:A C:A
Plate 01-B02 G:G G:G T:T T:T T:T A:A C:A
Plate 01-B03 A:A A:A C:C G:G T:T A:A C:A
Plate 01-B04 G:G G:G T:T T:T T:T A:A C:A
Plate 01-B05 A:A A:A C:C G:G T:T A:A C:C
Plate 01-B06 A:G A:G C:T G:T T:T A:A C:A
Plate 01-B07 A:A A:A C:C G:G T:T A:A C:C
Plate 01-B08 A:A A:A C:C G:G T:T A:A C:A
Plate 01-B09 A:A A:A C:C G:G T:T A:A A:A
Order form
Genotyping
data
GOBii – HTPG integration
• Notify Intertek of upcoming orders
• Assign plate and sample IDs
• Provide barcodes
• Load raw data into GOBII
• Store genotypic data
• Facilitate data extraction
• Genotypic data in ready-to-
analyze formats
Connect data to
visualization and
analysis tools
HTPG

18. Biotechnological approaches for groundnut for
resistance to aflatoxin contamination
ICGV 15083 x 4EC
26-2
ICGV 86015 x 4EC 26-2ICGV 86015 Inoculated Control
ICGV 15083 Inoculated Control
Construct Event# AFB1 (ppb)
Def4Ec ICGV 15083 x Def4Ec 26-2-3 3.72
Def4Ec ICGV 15083 x Def4Ec 26-2-20 2.90
Def4Ec ICGV 15083 x Def4Ec 26-2-25 5.66
Def4Ec ICGV 15083 x Def4Ec 26-2-28 1.71
Def4Ec ICGV 15083 x Def4Ec 26-2-31 2.60
Def4Ec ICGV 15083 x Def4Ec 26-2-32 8.34
Def4Ec ICGV 15083 x Def4Ec 26-2-33 1.09
Def4Ec ICGV 86015 x Def4Ec 26-2-2 9.50
Def4Ec ICGV 86015 x Def4Ec 26-2-5 1.95
Def4Ec ICGV 86015 x Def4Ec 26-2-11 3.37
Def4Ec ICGV 86015 x Def4Ec 26-2-14 5.45
Def4Ec ICGV 86015 x Def4Ec 26-2-15 6.82
Def4Ec ICGV 86015 x Def4Ec 26-2-19 7.67
Def4Ec ICGV 86015 x Def4Ec 26-2-20 6.10
WT Parent AFB1 (ppb)
ICGV 15083 IC1 771.14
ICGV 15083 IC2 512.03
ICGV 15083 IC3 654.54
ICGV 15083 IC4 566.73
ICGV 15083 IC5 680.00
ICGV 86015 IC1 636.15
ICGV 86015 IC2 378.88
ICGV 86015 IC3 450.00
ICGV 86015 IC4 388.26
ICGV 86015 IC5 350.00
Selected F2 progeny
ICGV 15083 x Def4Ec 26 & ICGV 86015 x Def4Ec 26
CMBGE, Groundnut breeding, Groundnut Pathology
ICGV 15083
ICGV 03043
ICGV 86015

19. carlactone
MAX3,
MAX4,:
MAX1
STRIGOLACTONES
CCD7
CCD8
(P450)
D27 (β-carotene-9-isomerase)
CCD7 edited lines
HIGS- Striga PMEI
Pectin-Methyl-Estrase Inhibitor
HIGS- Cell Wall
Degradation Enzymes
Types of resistances
1. Germination & haustoria induction
2. Attachment
3. Post-attachment haustoria formation
strigolactones
Orobanche - Striga
Germination
stimulants
PARASITIC INTERACTION
Root exudates
(secondary metabolites)
Striga resistance in sorghum
CMBGE, Corteva Agriscience, Kenyatta University, U of Sheffield

20. New Breeding Techniques (NBTs) for addressing
rancidity in pearl millet
Knocking down FA
biosynthesis genes through
gene editing
Low rancid line
Functional flour market projected to
reach USD 954 billion by 2022*
Pearl millet has inherent
challenges due to rancidity
CMBGE, Pearl millet Breeding, GTD, CEGSB, NutriPlus &
Corteva Agriscience

21. Doubled Haploidy for accelerated plant breeding
Inducing Double Haploids in
commercial germplasm
CMBGE, GTD - Sorghum
INRA, Corteva Agriscience
Founder line 1 x Founder line 2
F1Selfing
Inbred line
DH
Inbred line
W
MTarget 1 Target 2
Sobic.001G348600
Sorghum phenotype
Candidate genes identified for generation of pre breeding material that has potential to be
used to induce Double Haploids in commercial germplasm

22. Biotechnology in Africa- i
• Validation of QTL regions for Striga detected by
GWAS through transcriptome analysis
• Characterizing sorghum for pre-germination Striga
resistance
• GWAS for resistance to blast disease in cultivated
finger millet accessions at seedling stage
• Development of essential genetic and genomic
resources for finger millet

23. • Genome wide Association studies (GWAS) to map to
genomic regions responsible for Striga resistance in pearl
millet, sorghum
• Characterizing a NAM population for Striga, anthracnose,
midge and drought tolerance
• Molecular characterization of groundnut accessions in
Africa
• Screening diverse sorghum genotypes for response to
anthracnose with or without Lr34
Biotechnology in Africa- ii

24. Delivery of nutritious grain legumes and
dryland cereals
Creating demand
for quality seed:
Product
advancement
criteria and
process to
prioritize
varieties
Seeds to business (S2B) operational model of the
Syngenta foundation for sustainable agriculture

25. Seed value chain: what drives seed purchase?
64% of legume farmers
are buying ‘seed’ from
grain traders (McGuire
and Sperling, 2016)
Affecting farm decisions:
• Allocation of resources
• Choice of crop
• Choice of variety
 Varietal turnover
• Choice of seed source
 Seed replacement rate

26. Engaging the private sector: breeding and
seed systems Operations Type 1 Type 2 Type 3 Type 4 Type 5
Variety
development
Breeding
Testing
Seed
Production
Breeder
Foundation
Certified
Seed
Marketing
Packaging
Selling
Resources
Private Staff +
Land +
Equipment
+ Varieties
Staff +
Land +
Equipment
Staff +
Equipment
Staff None
Public
(CGIAR;
NARS)
Breeding
lines
(co-
developme
nt and
release)
Varieties
(co-
developme
nt and
release;
Licensing)
Varieties +
Land
(Licensing;
contractual
seed
production
with seed
producer
groups)
Varieties +
Land +
Equipment
(contractu
al seed
productio
n with
seed
producer
groups)
Varieties +
Land +
Equipment
+ Staff

27. Genotypingandsequencingplatforms
WGRS GBS
RNA-Seq
Genome Assembly
Epigenomics
Microarrays
High Performance Computational Genome Analysis facility
 600 cores
 ~ 830 TB storage
 7.5 TB RAM
SISU- partnering in accelerating genomics research

28. SSR
6M data points
1.5M samples
DArT
75K data points
2K samples
KASPar
1.5M data points
4K samples
VeraCode
75K data points
1K Samples
GBS
3TB data
14K samples
RNA-seq
1.6TB data
243 Samples
Small RNA
130 GB data
132 Samples
WGRS
40TB data
4K samples
2008 2009 2010 2011 2012 2013 2014 2015 2016 2017
 Sequencing Costs may vary according to the genome size & coverage
 DNA extraction costs are not included
Cost-effective sequencing technologies

29. Bringing DNA extraction cost down…
NaOH DNA extraction
• Where no refrigerator, no centrifuge
• 5 min/plate, < $0.10/sample
+ =
Zou et al. (2017) PLoS Biology
• 30 seconds/sample, < $0.10/sample
• Modifying to scale to full-plate extractions
Conventional Phenol-Chloroform
Macherey Nagel DNA Extraction

30. HiSeq 2500
NovaSeq 6000
Output: 6TB data
Duration: 3 days
• Cost reduced by
million folds
• Read length increased
• Throughput increased
Upgrade
Output: 1TB data
Duration: 1 Week
New sequencing platforms
96-plex assay
$60-80/Gb data
Nextera Truseq

31. • Friendly interface
• Detailed results
• Advance visualization
• Prevent data duplication
• For scientific community’s
inspection
• Cross verification
• Comprehensive Workflow
Tools and Online resources

32. Impact of ICRISAT crop diet on gut
microbiome for curbing malnutrition
Anemia &
malnutrition in
pregnant woman
Malnutrition in
babies
Transmission of
gut microbiome
Poor nutrition
Vicious cycle
of
malnutrition
Does ICRISAT mandate crops play an important role in altering gut microbiota
for enhanced nutrient absorption and alleviate malnutrition?
Pearl Millet
Breeding
Asia Program,
ICRISAT
Anemia in
adolescent
girls

33.  Linking soil microbiome structure to function
 Association of microbiome structure/function with crop performance
 Defining the ‘functional’ microbiome
Employing soil microbiome for enhanced crop
productivity & environmental sustainability

34. Capacity Building
 Total activities conducted: 23
 Participants trained: 598 (M:492 and F: 106)
 No. of training conducted country wise
o India: 12
o Tanzania: 1
o Mali: 3
o Ethiopia: 3
o Uganda: 3
o Morocco: 1
*Capacity building activities (conducted/facilitated by RP- GG during 2018) including TL III & HOPE- II Annual Meeting

35. High impact oriented & high impact factor journal articles
Thanks to our collaborating partners

36. Sustainable fund raising
• Enhancing the awareness and visibility on impacts of
upstream & strategic science in crop improvement
 High quality scientific publications
 Communicating success stories with potential
donors
 Establishing a roadmap for impactful
communication with grant donors (e. g.,
brainstorming workshops with donors)
• Multi-disciplinary and multi-institutional mega-
proposals
• Strengthening national and international partnerships
through workshops/conferences

37. Communications…
• 12 Stories
• 4 Bulletins
RP- GG & CEGSB Tropical Legumes III
• 15 Stories
Key resources for genomics
and crop improvement
practitioners – series of
books released
India-Myanmar pigeon pea project gets a research boost
ICRISAT working on developing climate-resilient pigeon pea
Pre-breeding scientists at International Crops Research Institute for the Semi-Arid
Tropics (ICRISAT) are exploring possible solutions to increase nutritional value in
agriculture produce, sourced from wild species of cajanus.
A project funded by Global Crop Diversity Trust (GCDT), would evaluate promising
pre-breeding lines in India and Myanmar, bringing them one step closer to cultivation,
according to a release here on Thursday.
https://www.thehindu.com/sci-tech/india-myanmar-pigeon-pea-projectgets-a-
research-boost/article25344041.ece

38. Social Media…
RP Genetic Gains : 94 members,
CEGSB: 95 members, and
Systems Biology: 88 members
ICRISAT RP- GG
580 Followers
133,353 impressions
1,314 Followers
586,546 reach
437 Followers
137,117 impressions
1,875 Followers
2,174,590 reach
389 photos from
conferences/workshops
740 Followers
119,862 impressions
970 Followers
583,798 reach
CEGSB
933 photos from
conferences/workshops
received 302,887 hits from
more than 123 countries.
http://cegsb.icrisat.org/
@coeingenomics@rpgeneticgains
@rpgeneticgains
@tropicallegumesIII
@tropicallegumes@coeingenomics
2,389 Followers
1,032,000 impressions
4,296 Followers
5,333,205 reach
@rajvarshney @rajeevkvarshney

39. Thank You