LECTURE 4 Alternatives For and With Microarrays David ... 4.pdf · Alternatives For and With...

LECTURE 4 LECTURE 4 Alternatives For and With Alternatives For and With

Microarrays Microarrays

David Galbraith David Galbraith

Alternatives For and With Alternatives For and With Microarrays Microarrays

1. Affymetrix/Nimblegen.

2. The ArrayPlate Technology.

3. SAGE/454 Solexa Sequencing.

4. Microarrays in genotyping.

Affymetrix arrays

• Probe “spots” are 10μm• Photolithographic synth. of

25mer oligo probes• 11-20 “match” probes and 11-

20 “mismatch” probes per gene

• Only one target per array• Arrays are not reused

Production of Affymetrix arrayshttp://www.affym

etrix.com/technology/m

anufacturing/index.affx

Note: Single channel measurements only.

Each chip costs about $400.

Hybridization costs are also extra ($100-150 per chip).

What is being measured?This depends on the chip design.

Chip Designs1. PM/MM method.

2. PM only.

Some advantages of Affymetrix arrays

• High precision because of:– careful probe design– up to 20 probes per gene– up to 20 mismatch probes

• Very precise measurements• Very high density (500,000 elements /

array)

Some disadvantages of Affymetrix arrays

• Inflexible: each set of new arrays requires a new production process.

• More expensive than spotted arrays.• Proprietary technology

– only one manufacturer of readers, etc.• Dependencies of results on method of

analysis.

NimbleGen arrays

• 786,000 individually addressable mirrors on a microchip

• Mirrors direct light to specific parts of microarray for oligonucleotide synthesis.

Disadvantages of NimbleGenke

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Multiplexed Molecular Profiling

• This is a microarray-based multiplexed Nuclease Protection Assay (mNPA®), using the wells of a 96-well microtiter plate.

• Advantage: Multiple genes and multiple treatments can be measured in parallel.

• Additional advantage: Provides an absolute measure of mRNA abundance within cells that is independent of gene sequence.

High Throughput Genomics, Tucson Arizona

Nuclease Protection Assay

AAAAA

AAAAA

AAAA

AAAA

targetprotectionprobe

nucleases

alkali

Nuclease Protection Assay

• Multiplexed processing.• Converts RNA target to stable DNA.• Solution-phase hybridization.• Stoichiometric, quantitative conversion.• Internal control overhang sequence.

mNPA®: Multiplexed Nuclease Protection Assay

adapter 1

gene-specificprobe

anchor

5 oligos are designed per gene

label

HRP-luminescence

adapter 2

QC involves Multiple Replicates

100% QC: All 1536 elements are competent for binding; no “drop outs”

ArrayPlate Assay Validation:

1GAPDH

M17851

2 IL-1

M15840

3TNF M10988

4TubulinAF141347

5cat-GM16117

6cox-2M90100

8GM-CSF

E02975

9GST

X06547

10HMG-17

M12623

11CycloX52851

12βTG

M17017

13LDHX02152

14TIMP-1

X03124

15MMP-9

J05070

16ActinM10277

7G-CSFE01219

KEY

GAPDH: Glyceraldehyde 3-phosphate dehydrogenase

IL-1: Interleukin-1βTNF: Tumor necrosis factor-αcat-G: Cathepsin G cox-2: Cyclooxygenase-2G-CSF: Granulocyte colony

stimulating factor GM-CSF: Granulocyte macrophage

colony stimulating factorGST: Glutathione S-transferase Pi-1HMG-17: High mobility group 17Cyclo: CyclophilinβTG: β-ThromboglobulinLDH: Lactate dehydrogenase TIMP-1: Tissue inhibitor

metalloprotease 1MMP-9: Matrix metalloprotease 9

Expression Profiling of Human Blood Cell Differentiation and Activation

PMA (48 hr)

Differentiated, Adherent,Monocyte

LPS (4 hr) + steroid(simulated bacterial challenge)

H2O2

NO

Il-1, TNF, enzyme secretion

Stimulated, ActivatedAdherent Monocytes

UndifferentiatedTHP-1 Cell Suspension

SIGNAL REPRODUCIBILITYGENE

Average CV Average CV GAPDH 1000 6% 1000 9%IL-1beta ---- ---- 1778 5%

TNF-alpha ---- ---- 1416 4%Tubulin 224 7% 80 10%

Cathepsin G 510 3% ---- ----Cox 2 ---- ---- 791 6%

G-CSF ---- ---- 103 8%GM-CSF ---- ---- 77 10%GST Pi-1 79 10% 35 13%HMG-17 541 6% ---- ----

Cyclophilin 333 10% 251 13%B-Thrombo ---- ---- 895 6%

LDH 228 5% 268 7%TIMP-1 ---- ---- 833 6%MMP-9 ---- ---- 1117 4%

Actin 1231 4% 1000 5%

Signal intensities were normalized to GAPDH = 1000

Untreated Cells Treated CellsH G F E D C B A

1

2

3

4

5

6

7

8

9

12

11

10

Alternating rows of untreated & treated cells

ArrayPlate Reproducibility

30,000 cells / Sample

ArrayPlate Dynamic Range

0.0 1.32 4.16 13.2 41.6 132 fM0.0 1.32 415 1320 4150 13200 41500 fM

ArrayPlate Sensitivity

10% CV

7% CV17%

CV

20% CV

23% CV

25% CV

22% CV

38% CV

25% CV

50% CV

10 75 100 1,000 10,000 75,000

GAPDH Signal as a function of Cell Number(for eight replicate wells per measurement)

1

10

100

1000

10000

100000

Number of Cells Analyzed

Sign

al I

nten

sity

The ArrayPlate Assay ProcessThe ArrayPlate Assay Process

Prepare tissue samples orGrow and treat cells in microplatesPerform nuclease protection assay

Transfer to the ArrayPlate

plate for analysis

Expr

essi

on

100

1 1000 Drug Conc. 0

96 Arabidopsis Plants in a microplate

mNPAmNPA Method as Applied to PlantsMethod as Applied to Plants

mNPA Method as Applied to Plants

• Arabidopsis seedlings are grown in liquid media for 10d in 96 well plates, then treated for 24h.

• Lysis buffer is added to wells and seedlings are homogenized.

• Homogenate is added directly to the nuclease protection assay.

• Nuclease protection assay is quantified in ArrayPlates via a CCD imaging system.

mNPA Assay with Osmotic Stress GenesmNPA Assay with Osmotic Stress Genes

ACT2 GST PAL1 S-19

COR47 β-TUB CHS ERD

14

RAB18

HMG-17 KIN1 KIN2

HIS1.1

HIS1.3

RD29A

RD29B

house keepingnegative controlstress regulated

Treatment with 150 mM NaCl

Assay SensitivityAssay Sensitivity

2000

4000

6000

8000

10,000

12,000

14,000

16,000

18,000

800

700

600

500

400

300

200

94 47 23 12 6 3 0

3000 1500 750 375 188 94 47 23 12 6 3 0

{inset

RNA (ng)

Signal Intensity

Error bars = S.D.

ng !

DoseDose--Response to NaCl TreatmentResponse to NaCl Treatment

0

2000

4000

6000

8000

10000

12000

14000

16000

18000

20000

0 18.75 37.5 75 150 300

[NaCl] mM

Nor

malized

Int

ensity

ActinGSTPAL1 S-19COR47 Beta Tubulin 8 CHSERD14 RAB18 b-thromboglobulinKIN1 KIN2RD29Histone 1.3 Histone 1.1 RD29A

Expanded ViewExpanded View

0

200

400

600

800

1000

1200

1400

1600

1800

2000

0 18.75 37.5 75 150 300

Nor

malized

Int

ensity

ActinGSTPAL1 S-19COR47 Beta Tubulin 8 CHSERD14 RAB18 b-thromboglobulinKIN1 KIN2RD29Histone 1.3 Histone 1.1 RD29A

[NaCl] mM

mNPA/ArrayPlate SummarymNPA/ArrayPlate Summary

• Very Many Treatments x Many Genes.• Requires as little as 12ng total RNA (microarray

requires ~ 50μg without amplification).• Assay can be used directly on single seedlings

grown in 96 well plates.• Excellent precision facilitates data collection. • Data reports mRNA abundances that are gene

independent.

Advantages of mNPA

• Extremely sensitive.• Very large dynamic range.• Very precise measurements.• Multiple genes AND multiple treatments

can be assayed in parallel.• Easily automated, scaled-up.• Appropriate for high throughput

screening.

Some disadvantages of mNPA

• Only 16 (now up to 64?) genes can be assayed at a time

• Expensive to set up– three 25-mers must be synthesized for

each gene• Proprietary technology.

SAGE (Serial Analysis of Gene Expression)

detectidentify

sequence short region of every transcript

clever trick: concatenate 20bp fragments of a reaching-restriction enzyme to facilitate sequencing

why not just sequence everything ?

count the frequency of each transcript

Extract mRNA

Make cDNA and attach to magnetic

beads

Cut the cDNA with a “4-cutter” so that just a fragment near the 3’

end remains

http://sciencepark.mdanderson.org/ggeg/sage_fig1_zoom.htm

SAGE cont’d

Ligate BsmFI linkers

Cut with BsmFI, which is a restriction enzyme

with a 15 bp “reach”

Ligate fragments together


SAGE cont’d


PCR amplify fragments

Cut, ligate(concatenate) and

clone

SAGE cont’d


Sequence inserts,identify. and count tags

SAGE cont’d

Some advantages of SAGE

• Very direct method of measuring transcript abundance

• Open-ended technology• Large dynamic range• Built-in quality control:

– e.g. spacing of tags & 4-cutter restriction sites

Some disadvantages of SAGE

• Must sequence >50,000 tags per sample– therefore >$5,000 per sample

• Most useful with fully sequenced genomes– otherwise difficult to associate 15bp tags

with their genes• 3’ ends of some genes can be very

polymorphic

Alternatives to SAGE

• SAGE reduces sequencing costs by concatenating small tags to efficiently accommodate the long read capability of automated Sanger sequencing.

• Alternative is to reduce the cost of short DNA sequencing to a level that allows comprehensive tag identification without loss of specificity.

• Requires “Next Generation” DNA sequencers.

Next Generation DNA SequencingNext Generation DNA Sequencing

• The aim is to reduce the cost as much as possible.

• Two companies are close to commercialization:

454 Life Sciences (now part of Roche; www.roche-applied-science.com).

Solexa (www.solexa.com; now becoming part of Illumina).

454 Genome Sequencer 20 System

• Generates ~20 Mbases of sequence per run.

• 200,000 reads per run.

• Each run takes 5.5 hours.

• Each run (including the prep steps) costs about $6,000.

• Preparative steps (which take longer than 5.5 hours) can be done in parallel to give an efficient pipeline.

• Run lengths are around 100 bases, but they are pushing this to longer reads.


sstDNA library production

• Sample preparation is dependent on the type of starting material used.

• It involves a series of enzymatic steps to produce single-stranded template DNA (sstDNA) incorporating primer and bead-binding adaptors.

• For example, genomic DNA (gDNA) is fractionated into smaller fragments (300-800 base pairs) that are subsequently polished to make blunt ends.



• Short Adaptors (A and B) are then ligated onto the ends of the fragments. These adaptors provide priming sequences for both amplification (emPCR) and sequencing of the sample-library fragments, and contain a streptavidin binding site for sample purification.

• Low molecular weight DNA can be used without fragmentation, and sample preparation begins with adaptor ligation. The A and B adaptors can also be added during PCR by using the appropriate primers



• The sstDNA library produced at the end of this preparation step is assessed for its quality.

• The optimal amount (DNA copies per bead) needed for emPCR is determined by a titration run.


emPCR Amplification

• The sstDNA library is immobilized onto specially designed DNA Capture Beads. Each bead carries a single sstDNA library fragment.

• The bead-bound library is emulsified with amplification reagents in a water-in-oil mixture. Each bead is separately captured within its own microreactor for PCR amplification.

• Amplification is performed in bulk, resulting in bead-immobilized, clonally amplified DNA fragments that are specific to each bead.


Sequencing-by-Synthesis

• Sequencing starts with the preparation of a PicoTiter Plate. During this step, a combination of beads, sequencing enzymes, and an sstDNA library is deposited into the wells of the plate.

• The bead-deposition process maximizes the number of wells that contain an individual sstDNAlibrary bead.

• The loaded PicoTiterPlate is placed into the Genome Sequencer 20 Instrument.



• The fluidics subsystem flows sequencing reagents (containing buffers and nucleotides) across the wells of the plate.

• Each sequencing cycle consists of flowing individual nucleotides in a fixed order (TACG) across the PicoTiterPlate. During the nucleotide flow, each of the hundreds of thousands of beads with millions of copies of DNA is sequenced in parallel.



• If a nucleotide complementary to the template strand is flowed into a well, the polymerase extends the existing DNA strand by adding nucleotide(s).

• Addition of one (or more) nucleotide(s) results in a reaction that generates a chemiluminescent signal that is recorded by the CCD camera in the Genome Sequencer 20 Instrument.

• This signal strength is proportional to the number of nucleotides incorporated during a single nucleotide flow.


• Solexa's platform is based on massively parallel sequencing of millions of fragments using a proprietary Clonal Single Molecule Array™technology and novel reversible terminator-based sequencing chemistry.

• The approach relies on attachment of randomly fragmented genomic DNA to a planar, optically transparent surface.

• Solid phase amplification is then used to create an ultra-high density sequencing flow cell with >10 million clusters, each containing ~1,000 copies of template per sq. cm.

Solexa Technology

• These templates are sequenced using a four-color DNA sequencing-by-synthesis technology, which employs reversible terminators with removable fluorescence.

• This approach achieves high accuracy and avoids artifacts due to homopolymeric repeats.

• High sensitivity fluorescence detection is achieved using laser excitation and total internal reflection optics.

Solexa Technology

• Short sequence reads are obtained. These are aligned against a reference genome and genetic differences are called using a specially developed data pipeline.

• Alternative sample preparation methods allow the same system to be used for a range of other genetic analysis applications, including gene expression and small RNA discovery.

Solexa Technology

See:

• http://www.solexa.com/technology/demo.html

Solexa Technology

Large-scale genotyping in rice using spotted oligonucleotide

microarrays

David Galbraith, Jeremy D. Edwards, Jaroslav Janda, Ambika Gaikwad, Bin

Liu, Hei Leung

Objectives

• Development of a microarray-based genotyping platform for rice.

Low cost per data point.Low cost per individual.Targeted to known polymorphic features.

Microarray-based genotyping

• Single Feature Polymorphisms (SFPs)

Differential hybridization to single probes. SFPs are a consequence either of insertions/deletion (InDel) polymorphisms or represent multiple SNPs across the complementary sequences.

Microarray-based genotyping

• SFPs identified through hybridization of genomic DNA to whole-genome tiling arrays (i.e., Affymetrix Genechips).

Yeast: Wodicka, L., H. Dong, M. Mittmann, M.H. Ho, and D.J. Lockhart. 1997. Nat Biotechnol 15: 1359-1367.Arabidopsis: Borevitz, J.O., D. Liang, D. Plouffe, H.S. Chang, T. Zhu, D. Weigel, C.C. Berry, E. Winzeler, and J. Chory. 2003. Genome Res 13: 513-523.

Targeted approach to microarray-based genotyping

• Computational identification of SFPs through whole-genome sequence alignments.

• Assay of SFPs using relatively low-cost spotted long oligonucleotide microarrays.

TACTATATACTACTGTAGTAGACACTC------------------------------------------------------------------------------------------------------TAGTACAAGTGAGGCAACAAGTGCTCATGG

TACTATATACTACTGTAGTAGACACTCTAGTACTGTATTGGTTAGCAGCAGCTTGGATCAGTGAAAATGGAGGTGGATTCGCAGGAGATGCTCCCGATCCACTTGGTCTATAGGAGTAGTCTATACTATTAGTACAAGTGAGGCAACAAGTGCTCATGG

Sample 1

Sample 2

Total genomic DNA

Shear DNA(sonication)

Cy5 direct labelby random priming

Cy3 direct labelby random priming

Hybridize labeled samples

InDel in sequence alignment

Synthesized70mer oligonucleotide probe Robotic spotting of probes on slides

Printed slide

Positive Controls(High copy)

Negative Controls

9311+Markers

Nipponbare+Markers

Positive Control(single copy)

Negative Controls

Positive Controls(High copy)

cv. Nipponbare cv. 9311

Positive Controls (High Copy) are 70mers representing transposable elements of known copy numbers (ranging from several hundred to several thousand per genome).

Negative Controls are 70mers representing random sequences and genes from other species not present in rice.

Positive Controls (single copy) are 70mers representing genes conserved between the two cultivars.

The targets were enzymatically labeled with Cy5 (direct labeling, random priming).

Allele discernment using two color microarrays

+ Cy5 labeled sample- Cy3 labeled sample

- Cy5 labeled sample+ Cy3 labeled sample

Monomorphic

SFP discovery

• Alignment of Japonica cv. Nipponbare assembled pseudomolecules with Indica cv. 9311 contigs using MUMmer/NUCmer.

• Blast InDel sequences against assembled genome sequences to assess uniqueness.

• Oligo design based on unique InDel sequences.

• Same pipeline can be used with sequences from additional cultivars.

Specifications for oligo design

• Length: 70 bases (or less)• Tm: 78.5 °C ± 5 °C (balanced GC content)

Tm = 81.5 + 16.6 × log[Na+] + 41 × (#G + #C)/length –500/length [Na+] = 0.1 M

• UniqueNo single nucleotide base repeat or poly (N) tract longer than 8bases.Less than 70% identity with any other sequence in the rice genome.No more than 20 contiguous bases common to any other sequence.

Distribution of SFPs

0

5

10

15

20

25

30

35

40

45

1 2 3 4 5 6 7 8 9 10 11 12

Japonica-derived probesIndica-derived probesCentromere

Chromosome

MegabasesMeg

abas

es

880 total SFPssuitable for oligonucleotide probe design

5 positive controls5 negative controls5 high copy controls

Experimental verification of SFPs

• Label and hybridize genomic DNA from Nipponbare and 9311 cultivars with Cy3 and Cy5 (dye swap, 4 slides)

• For each probe:Is ratio significantly different?Is difference in the predicted direction?

MA plot: SFP verification

12.5 13.0 13.5 14.0 14.5 15.0

-1.0

-0.5

0.0

0.5

1.0

A

M

9311NipponbarePositiveNegative

SFP verification: p-values vs fold change

1.E-08

1.E-07

1.E-06

1.E-05

1.E-04

1.E-03

1.E-02

1.E-01

1.E+00-1 -0.8 -0.6 -0.4 -0.2 0 0.2 0.4 0.6 0.8 1

Nipponbare9311

Log-fold change

P-v

alue

Experimental verification of SFPs

8807714105Total

4573954589311423376047Nipponbare

TotalCorrect and p-val < 0.1

Wrong and p-val < 0.1

p-val> 0.1

1.E-08

1.E-07

1.E-06

1.E-05

1.E-04

1.E-03

1.E-02

1.E-01

1.E+00-1 -0.8 -0.6 -0.4 -0.2 0 0.2 0.4 0.6 0.8 1

Nipponbare9311

Log-fold change

P-v

alue

Polymorphisms were detectedFor 87.6% of the probes

Polymorphism Survey

• How many of the Nipponbare/9311 InDelsare polymorphic between other rice cultivars?

• Genotype 24 diverse accessionsFour individuals from each of the five rice sub-populations.Nipponbare as a common reference.

Percent of polymorphic markers between O. sativa sub-populations.

35.3%Indica X Indica

38.5%Aus X Indica

37.8%Aus X Aus

53.0%Aromatic X Indica

46.7%Aromatic X Aus

22.2%Aromatic X Aromatic

58.1%Tropical Japonica X Indica

47.9%Tropical Japonica X Tropical Aus

30.4%Tropical Japonica X Aromatic

20.4%Tropical Japonica X Tropical Japonica

66.2%Temperate Japonica X Indica

54.3%Temperate Japonica X Aus

31.1%Temperate Japonica X Aromatic

25.0%Temperate Japonica X Tropical Japonica

13.8%Temperate Japonica X Temperate Japonica

Mean PolymorphismCross

The lowest is within temperate japonica. This is the group with the most narrow diversity.

There are sufficient polymorphic markers between and even withinmost subpopulations for QTL mapping applications.

Neighbor joining tree using genotyping microarray data(4 accessions/subpopulation, bootstrap values out of 10,000).

0.1

Tropical Japonica

Temperate Japonica

Aromatic

Indica

Aus

O. meridionalis

10,000

10,000

10,000

10,000

Quantitative genotyping:Bulked segregant analysis

• RIL mapping population segregating for a single-isolate major gene for blast resistance.

• DNA samples pooled according to phenotype (73 individuals per pool).

• Pooled samples labeled with Cy3 or Cy5 and hybridized (dye-swap design using four slides).

• Probes linked to the gene should have significant differences in color ratios.– The direction of the ratio differences indicates which

parental allele is causing the effect.

-5-2

02

46

810

-5-2

02

46

810

-5-2

02

46

810

-5-2

02

46

810

-5-2

02

46

810

-5-2

02

46

810

0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30

-5-2

02

46

810

-5-2

02

46

810

-5-2

02

46

810

-5-2

02

46

810

-5-2

02

46

810

-5-2

02

46

810

0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30

Chromosome 10

Chromosome 11

Chromosome 12

Chromosome 7

Chromosome 8

Chromosome 9

Chromosome 4

Chromosome 5

Chromosome 6

Chromosome 1

Chromosome 2

Chromosome 3

-Log

10 P

-val

ue

Pseudomolecule position (MB)

-20

24

68

10

0 2 4 6 8 10 12 14 16 18 20 22 24 26

-Log

10 P

-val

ue

Chr. 12 pseudomolecule position (MB)

4.2

12.1

26.4

0.07.9

15.1

11.90.00.54.40.32.58.34.8

20.7

2.72.68.0

7.1

6.3

27.7

9.5

RG869

Chr 12

Pi-GD-3(t)RM179

CG32CDO459

RM19A

RG235RG574ARM19C

RZ397RG81CG38C

RM101XLRfr-9

RM247

RM277RM260PK1K2-13RZ76

RM313RG413

RM235

RG181

1.22E-085745762E

1.09E-086713237D

5.90E-0914601035C

5.44E-0921797559B

4.15E-0913266396A

P-valuePositionProbe

A BCDE

The resistance gene was previously mapped to SSR markerRM179 at position 14451955

RM179

Bioinformatics Tools

• SFP discovery – Perl scripts– Find InDels in MUMmer/NUCmer whole-genome

alignments.– Probe design

• Analysis– R statistical programming language– Scripts for importing data, normalization and fitting

linear models using Bioconductor/Limma packages.– Tools for data visualization and graphical genotyping

under development.

Distribution of microarray technology

• Microarray production is done using either a GeneMachines OG300 (300 slides per print run, or a Genetix Arraymax (450 slides per run).

Distribution of microarray technology

• Two models for technology distribution are then possible:

– DNA and RNA (if expression analysis involved) shipped to Arizona. Hybridization results distributed.

Problem with Homeland security(?)

– Microarrays distributed. Genotyping and expression analyses done at distal sites.

Is technology portable?

Bulked DNA Individual Plants

SSR Genotyping

RM107 at Chromosome 9

1 2 3 4 5

1 = Azn2 = D6-2563 = IR644 = LM5 = Non-LM

1 = Azn2 = D6-2563 = IR644 to 13 = LM 14- to 23 = Non-LM

1 2 3 4 5 6 7 8 9 10 1112 13 1415 16 1718 19 20 21 22 23

Composite Cy3_Non-LM Cy5_LM

SFP Genotyping

09_20087276_20087276_I

Spot mean: Cy3=32,129; Cy5=55,793Ratio: 1.8 (cy5/cy3)

Chromosome 9 contig

attcgaagaaggcgagggcaGGGCGGTGTCCTTGAGTTCCATCTGGGGATCaacctcgatggtgcggaag

Agreement between SFP and SSR genotyping with all work done at IRRI argues technology can be transferred to end users. Microarrays took 3 days; SSR’stook one month.

Lesion mimic mutation crossed with Azucena – F2 generated and scored lesion mimic and wt. Pool 10 plants of each type for genotyping by bulk segregant analysis. SFP and SSR genotyping done separately.

Conclusions

• 880 SFPs suitable for probe design were identified in Nipponbare/9311 sequence alignments.

• The SFPs were experimentally verified with 87% success.

• The evolutionary relationships between rice sub-populations can be resolved .

• There are sufficient numbers of polymorphic markers for QTL mapping across (and in some cases within) sub-populations of rice.

• Bulk segregant analysis was used to map a single-isolate major gene for Blast resistance.

• Technology is portable.

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