Role of Biotechnology in Improving Productivity for Rice Producers in Asia from IRRI's Perspective by David Johnson, IRRI, Philippines

1. Role of Biotechnology in Improving
Productivity for Rice Producers in Asia
Abdel Ismail, Ajay Kohli,
David E Johnson

2. Outline
• Rice production and Constraints
• Genetic Resources and tools for improvement
• Targets for improvement – nutrition, stress
tolerance, yield pest resistance
• Results with stress tolerance
• Looking ahead

3. Drought prone
Submergence prone
Saline affected
Reducing risks and raising productivity in the
unfavorable rice environments
Upland systems

4. GLOBAL RICE DEMAND
SOURCE: IRRI
GLOBAL RICE MODEL
300
350
400
450
500
550
600
Asia Africa Americas Rest of World
MILLION TONS
MILLED RICE
2010 global rice
production
Rice Science for a Better World
Additional rice
needed:
116m tons by
2035

5. T.T. Chang Genetic Resources Centre
• International Rice Genebank Collection – the largest
collection of rice diversity in the world
Number of available
accessions
Distributio
n 2016
Regular
genebank
material
Oryza sativa 112,704 13,196
Oryza glaberrima 1,653 3,636
Wild Oryza spp. 4,643 1,139
Genetic stocks Breeding or Inbred Lines 9
Chromosome Substitution
Segment Lines
140
Mutant Lines 31 161
Magic Population 1,357
Near Isogenic Lines 35 54
Purified lines 7,345 15,277

6. Allele mining for
high-value traits
Bioinformatics Activities at IRRI
Computing
• Genomic
Prediction/Selection
• GWAS
(BIG) Data-driven
Sequence/genotypes
• 3k Rice Genomes
• High Density Rice Array
International Rice Informatics
Consortium (IRIC)
Software & Databases
• SNP-Seek
• IRRI Galaxy
• Genotyping4Rice
• Genomic OpenSource
Breeding Informatics Initiative
Yield and quality
• Yield Potential
(panicle/spikelets
• Grain quality
Stress Tolerance
• Biotic (diseases)
• Abiotic / Climate-change
related (drought,
temperature, floods,
etc)
Bioinformatics
Team
• Provide access to well organized information about rice,
• facilitate communication and collaboration for rice community

7. SNP-Seek database, Alexandrov et al. NAR database, 2015, Mansueto et al., update 2016
> 29 mio SNPs, 2.3 mio
indels x ~4.5k rice entries
• Discovered in 5 reference
genomes
• Soon to include other
published SNPs and ~500
new rice entries from
IRRI
~4,500 Rice Entries
• 3k RG, ~1.5k HDRA entries
• Population grouping
• Passport info
• Phenotypic data
Tutorial
• How to use SNP-Seek
View the genome
• SNPs and genes together
• Graphical genotype of
entries
snp-seek.irri.org
Contents and functionalities
Query for SNPs
Query for variety passport and phenotype

8. Multi-parent Advanced
Generation Inter-Cross
Bandillo N et al 2013. Rice 6: 11–15.
Using MAGIC lines as
reference population
in Rice Array and for
trait discovery
Create Novel Genetic Resources: MAGI, NAM, etc..

9. Resistance
Source
Resistance
Gene
Pre-BreedingLine &
Variety
BacterialBlight
Blast
RYMV
RTSV
RTBV
SheathBlight
BrownSpot
FalseSmut
Utilization of Host Plant Resistance

10. 5
2
HotspotSites
Philippines
X
BB Blast Virus
X = None
= Low
= Medium
= High
Surveillance strategies and tools ready for
pathogen monitoring
Southeast Asia South Asia
Sub-Saharan
Africa
Hotspots
Phenotyping
Molecular
Diagnosis

11. Anemia
- India: anemia in 6 month to 5 year old
children ranged from 35.7% in Assam to
63.5% in Bihar (NFH Survey 2015-2016 ),
prevalence in women up to ~60%
- ~50% of anemia is due to iron (Fe)
deficiency (Stoltzfus et al., 2004)
Data : FAO and Stevens et al., Lancet 2013; Map: IRRI, A. Nelson
Over 165 million children globally
are stunted
Zinc deficiency
Nutritious rice (Fe and Zn)

12. High Fe an Zn biofortified rice
Iron distribution in the starchy
endosperm (6 fold of control)
Co-expressing bean ferritin and rice nicotianamine synthase in rice:
Achieved iron and zinc nutritional targets (+30% EAR) in IR64
under field conditions
No yield penalty or change in grain quality
BR29 BC3F2
(Trijatmiko et al., 2016, Nature’s Scientific report)

13. Gene Discovery: abiotic stress tolerance
-Yield under drought QTL cloning.
-qDTY12.1; qDTY2.3 (epistatic QTLs).
-Upland NERICA drought tolerance markers/genes.
-Differentially tolerant isolines U3 vs U4.
-Functional characterization of genes for AG (IRRI).
-Role of jasmonic acid in drought tolerance (Germany).
-Candidate gene validation for salinity tolerance (UK).
-Gene identification - yield under multiple stress (NUS)
-Role of a tetra-functional protein in stress tolerance
and grain development
Ajay Kohli

14. Phenotype of quintuple cross plants
PEPC / PPDK / MDH / ME / CA
Quintuple cross plants
Wild-type 1 2
Overproduction of maize PEPC, PPDK, MDH, ME and CA
rice plants didn’t affect the plant’s growth.
Calculations suggest ~ 5% of the carbon fixed is moving
through Malate—a potential sign of a “C4”-like rice

15. Genome editing projects at IRRI
Targeted Insertions Biofortification
Gene Validation Diagnostic Markers and new editing targets
Gene Stacking Golden Rice, C4
Allele replacement Biotic stress resistance
What are we editing for?
System improvements Proof of concept
What are we planning to do editing for?
Product development
Abiotic stress
Biotic stress
Grain quality
C4 and water use efficiency
Virus resistance
Standardization of CRISPR Technologies for rice:
CRISPR-Cas9, CRISPR-Cpf1, CRISPR-C2c2, Multiplexing , Single base editing, knock-ins
Anindya Bandyopadhyay et al.

16. High-resolution phenotyping
RGB
Thermal Hyperspec
LiDAR PC
RGB
LiDAR
IRRI Phenotyping Facility
Rob Coe et al.

17. LiDAR - Light detection and ranging
Perspective view of canopy
2D intensity image
R2 = 0.75
Non-destructive determination of
LAI, biomass, plant height etc..
R2 = 0.75
HRPPC, CSIRO, Australia

18. Phenotyping 3k panels
Wet season 2016 with manual, tractor, drone traits
S. Klassen
aus/indica
indica
Panels have 625 entries:
P-rep design (30% plot replication
4 levels of replication
Drone image, 6 Sept 2016
6 Sept 2016

19. A Global
Network of
Action Sites
Conducting
Integrated
Research
Possible trial sites
Capacity to build a global rice field research
network.
Global Rice Arrays: A new concept to
stay ahead of climate change

20. Submergence during vegetative stage
devastates over 20 m ha of rice in Asia
Lowland rice +SUB1A
Air Air
Short-term (1-2 wk)
complete flooding
(attempted escape)
Short-term(1-2 wk)
complete flooding
(quiescence)

21. SUB1 confers tolerance of transient
submergence in rice
0 10 20 30 40
LOD score
50cM
100cM
150cM
OPN4
OPAB16
C1232
RZ698
OPS14
RG553
R1016
RZ206
RZ422
C985
RG570
RG451
RZ404
Sub-1(t)
1200
850
900
OPH7
950
OPQ1
600
SUB1
Chr 9
Delivery
Major QTL on Chr 9,
protect rice for 3 -18
days against flooding
Landraces discovered in 1950s
1970s: tolerant types identified
+Sub1-Sub1
1990: Breeding lines, mapping
2006: SUB1 cloned, MABC
FR13A
2009 – varieties released

22. Pooja
SUB1 in farmers’ fields:
Swarna-Sub1
Swarna-Sub1
Field flooded with turbid
water for 10 d
Field submerged for 12
d, UP, India
Swarna

23. Farmer Grain yield (t/ha)
Swarna-Sub1 Swarna (t/ha)
12-17 days complete submergence
F. C. Dasarathpur 3.03 0.0*
Ranjit Sahoo, Dasarathpur 3.10 0.0
Pitabar Naik, Barachana 3.25 0.0
T. K. Barachana 2.98 0.0
G. B. Dharmasala 3.06 0.0
S. B. Dharmasala 3.28 0.0
B. N. Dharmasala 2.90 0.0
No submergence
M. S. Jajpur 6.25 5.97
N. S. Koral 6.34 5.64
*Farmers did not harvest their fields
Performance of Swarna-Sub1 in farmers’ fields
Gov. of Odisha minikit program

24. Looking forward

25. New horizons in plant biotech for agriculture
• High throughput sequencing, marker detection &
Omics
– Advanced QTL, eQTL and GWAS analysis
– Genomic selection
– Rapid generation advance
– Accelerated Yield TechnologyTM
– Epigenetics-based improvements
– Unique and novel populations for genetic diversity
– Integrated Omics-based selection
• CRISPR/Cas9-mediated genome editing
– Modified non-transgenic plants
• Gene knock-out or activation
• Allele replacement
• Gene excision

26. New horizons in plant biotech for agriculture
• Microbiome
– Disease tolerance
– Abiotic stress tolerance
– Yield increase
– Plant nutrition
• Environmental biotechnology
– Pest/pathogen life, life-cycle and population
analysis
• Big data bioinformatics
– Trait, gene, genome, genotype and phenotype
association analysis
Omics based models for candidate genes

27. Thank You
• More information
• http://irri.org/our-impact