Yoseph Beyene (Ph.D)Senor Maize Breeder, CIMMYT-Kenya

Email: y.beyene@cgiar.org

Harnessing Agriculture Biotechnology for Resilience to Climate Change: A Lesson from Water Efficient Maize for Africa (WEMA)

Project

Outline• WEMA Project

– Partners – Objectives– Approaches

• Progress by Breeding Approach – Conventional Breeding– Molecular Breeding– Transgenic 4RD

• Highlights of Achievements

Maize is vital for food security in Sub-Saharan Africa

• Over 300 million people depend on maize in SSA

• Example: consumption in Kenya 103 kg/ yr/ person

• Maize yield is low (1.8 t/ha compared to world average of 4.5 t/ha)

• Major constraints:• Drought • Low soil nitrogen • Diseases• Lack of access to quality

seed Recorded droughts between 1971 and 2000, and the number of people affected

Water Efficient Maize for Africa (WEMA)

• A public-private partnership to develop and deploy drought-tolerant and insect-pest protection white maize varieties to smallholder African farmers royalty-free.

Expected Outputs • Under moderate drought, WEMA maize expected to

increase yields by 25% over 2008 hybrids• 15% conventional • 10% transgenic

• Translates into additional 2 million MT maize during drought years to feed about 14 to 21 million people in the long-term.

AATF

African institution mandated to access, develop, & deliver appropriate agricultural technologies to smallholder African farmers royalty-free

Monsanto

World leader in gene discovery and commercialization of Transgenic crops

CIMMYT

World leader for breeding maize for African agro-ecological zones

WEMA Partnership Structure

NARS• Expertise in field trials • Breeding/Test DT maize•Capacity building opportunities

WEMA

KALRO; NARO; ARC; COSTECH; & IIAM

● Rapid development of completely homozygous inbred lines and faster product identification

● Four steps:o F1 is crossed with a haploid inducero Identification of kernels with haploid embryo

using visible anthocyanin markero Artificial genome duplication generation D0

o Selfing generating D1 seed

Accelerating Breeding Gains - Doubled haploids

DH technology is well-integrated in CIMMYT’s product development strategy

• 26, 221 DH lines developed from NARS, Monsanto and CIMMYT bi-parental crosses through WEMA Project

• The DH lines were evaluated for per se, reaction to major leaf diseases in Africa

• Testcross were developed and evaluated in stages 1, 2&3 and regional trials across locations in five countries

• Hybrids were released in Kenya, Uganda, Tanzania, South Africa and nominated in Mozambique

WEMA has strong breeding pipelinesStage Hybrids

Stage I 20, 900Stage II 9, 349Stage III 1, 761WWT 246Total 32, 256

Types of lines TotalDH lines 26, 221Elite lines 1,949Segregating lines 29,308Total 57,478

DH lines compared to pedigree lines under optimum

Pedigree Yield (t/ha)% increase over the best check

Anthesis date

Ear height

Plant height

CKDHL0556 4.7 38.0 66.7 85.0 174.4CKDHL0625 4.6 34.4 65.1 86.5 169.1CKDHL0399 4.0 18.1 63.1 77.0 157.9CKDHL0505 4.0 17.6 68.2 82.1 142.3CKDHL0500 3.7 9.9 73.7 78.7 130.9CML312 3.4 69.5 60.2 159.5CML395 2.4 67.8 93.1 164.3CML442 2.8 70.8 58.9 131.1CML444 3.0 72.7 74.3 126.3CML539 2.2 67.2 66.7 132.9LSD 1.2 2.4 14.7 20.3CV 20.6 1.7 8.9 6.7Heritability 0.9 1.0 0.9 0.9

Date of planting: 6 June 2012Date of last irrigation: 26 July 2012Date of harvesting: 10 Oct 2012

Evaluation of hybrids under managed drought stress

Date of planting: 25 May 2014Date of last irrigation:19 July 2014Date of harvesting: 28 Oct 2014

Accelerating Breeding Gains: Forward breeding

Entry EntryYield (t/ha)

increase over best check (%) AD EA ET

1 (CKDHL0089/CKDHL0333)//CKL14001 8.84 56.0 64.85 1.58 2.002 (CML395/CML444)//CKL14002 8.82 55.6 65.26 1.92 1.753 (CML395/CML444)//CKL14001 8.68 53.2 65.31 1.81 2.004 (CKDHL0159/CKDHL0295)//CKL14003 8.66 52.7 66.06 1.90 2.005 (CKDHL0089/CKDHL0333)//CKL14002 8.62 52.2 66.32 2.25 2.006 (CML395/CML444)//CKL14005 8.55 50.9 65.30 2.16 2.007 (CKDHL0089/CKDHL0295)//CKL14001 8.52 50.3 65.43 1.75 2.008 (CKDHL0089/CML395)//CKL14001 8.39 48.0 65.20 1.74 2.009 (CKDHL0089/CKDHL0295)//CKL14006 8.34 47.2 68.68 1.92 2.00

10 (CKDHL0159/CKDHL0295)//CKL14002 8.28 46.2 65.44 2.34 2.00Pioneer 3253 (Pioneer) 5.67 66.48 3.07 2.25DK8053 (Monsanto) 5.27 65.03 2.75 3.00DH04 (Kenya seed) 5.01 65.77 3.00 2.50

DK8031 (Monsanto) 3.45 65.88 3.84 2.50nlocs 6 6 6 2

Gmean 7.42 65.70 2.35 2.25LSD 1.10 1.32 0.49 0.69CV 7.53 1.02 10.71 15.40

Heritability 0.85 0.89 0.79 0.55

Hybrids Release and Commercialization

Nominating country Hybrid Kenya Uganda TanzaniaWE5101 Yes Yes YesWE5107 Yes Yes YesWE5109 Yes Yes YesWE5103 Yes YesWE5108 Yes YesWE5111 Yes Yes WE5117 Yes Yes

2012 2013 2014 20150

5

10

15

20

25

1

1618

24

Year of release

Num

ber

of h

ybrid

Timeline for delivery pathway of products

13

2013 2014 2015 2016 / 2017

Introduction of first WEMA Hybrid

MON810 application in Kenya

MON810 ApprovalsFor commercialization

MON87460 Approvals (allows

for Stacks with MON810)

Ramp up of WEMA Hybrids

Molecular Breeding

Use of Breeder-friendly Markers for Maize Streak Virus (MSV) Resistance

msv1

GWAS in a panel of 300 lines, genotyped with GBS (~700K SNPs) Validation of SNP markers in 660 DH lines (biparental

populations)

• Three SNP markers identified and validated within the Msv1 region

• MAS for this region increases resistance to MSV by 25% (1.2 units on a 1-5 scale)

Highly r

esista

nt

Resista

nt

Moderatel

y Susce

ptible

Susce

ptible

Highly s

usceptible

0

50

100

150

200

250

Forward breeding: Using markers for MSV resistance at early stage of testcross formation

Sampling leaf tissue in the DH nursery, Sept 2015

SNP Trait Chr SNP RR SS

PZE0186065237 MSV 1 C/T C:C T:T

PZE0186365075 MSV 1 C/A C:C A:A

PZE-10109395MSV

1 A/G A:A G:GPopulation PZE-

101093951PZE0186065237

PZE0186365075

Comment on msv1 data Decision

CML312/INTA-F2-192-2-1-1-1-B*7-2-B-10-B-B-B:@ A:A C:C C:C Homozygous for favorable alleles at 3 loci SelectCML312/INTA-F2-192-2-1-1-1-B*7-2-B-10-B-B-B:@ A:A C:C C:C Homozygous for favorable alleles at 3 loci SelectCML312/LaPostaSeqC7-F18-3-2-1-1-B-B-B:@ A:A C:C C:C Homozygous for favorable alleles at 3 loci SelectCML312/LaPostaSeqC7-F18-3-2-1-1-B-B-B:@ A:A C:C C:C Homozygous for favorable alleles at 3 loci SelectCML312/LaPostaSeqC7-F18-3-2-1-1-B-B-B:@ G:G T:T A:A Homozygous for unfavorable alleles at 3 loci RejectCML312/LaPostaSeqC7-F18-3-2-1-1-B-B-B:@ G:G T:T A:A Homozygous for unfavorable alleles at 3 loci RejectCML312/LaPostaSeqC7-F18-3-2-1-1-B-B-B:@ G:G T:T A:A Homozygous for unfavorable alleles at 3 loci RejectCML312/LaPostaSeqC7-F18-3-2-1-1-B-B-B:@ G:G T:T A:A Homozygous for unfavorable alleles at 3 loci Reject

Large-scale implementation of GS/MARS in Africa

• In 2008, CIMMYT started the largest public GS/MARS projects in SSA

• Over 35 bi-parental maize populations advanced through MARS/GS

• Genetic gain studies completed for 18 populations using two protocols:– using a subset of markers significantly associated

with QTLs for grain yield and ASI– Using all markers distributed across maize genome

without test for association with QTLs

Self selected Plants

Self selected Plants

Self selected Plants

Cycle 1

GenotypeSelf or recombine selected Plants

Cycle 2Genotype Self or

recombine selected PlantsCycle 3

Crossed with Tester

F4

Inbred A x Inbred B

F1

F2

F3 = Cycle 0 F3 x Tester

F5

F6

Evaluate TC under target environments

Phenotypic Selection Cycle 0 Cycle 1 Cycle 2 Cycle 3

Genotype, Select Best

Families Based on Phenotypic and Genotypic

Data and Recombine

Genotyping: All markers or

a subset of significant markers

QC/QA genotyping

Develop DH pop

MARS work flow

Genetic gain studies

Polymorphism screening

Genetic Gain Studies on C0-C3 from MARSCycle Design C0 Made balanced bulk from each F2:3

family within a population

C1 Made balanced bulk from the selected individuals/families

C2 Made balanced bulk from the selected individuals /families

C3 Made balanced bulk from selected individuals /families

Lines from Pedigree

6 random F6 lines from each population selected through pedigree breeding

Reference entries (3)

2 parents and F1

Single cross testerx

+ Best currently available commercial hybrids (checks)

Gain in grain yield using genome-wide SNPs under drought environments in SSA

CML440xCML504

CML441xCML444

CML444xMalawi

6x1008

6x1016

6x1017

6x1020

6x1028

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5 Cycle0 Cycle1 Cycle2 Cycle3

Populations

Gra

in y

ield

(Mg/

ha)

Genetic gain from conventional breeding in Africa 18 kg ha-1 yr-1 (Edmeades, 2013)32 kg ha-1 yr-1 (B. Masuka, submitted)

Genetic gain GS is 2- 4 times higher than from conventional breeding reported in sub-Saharan Africa.

Overall gain in GY : 70.5 kg ha-1 year-1

Beyene et al. (2015) Crop Sci. 55:154–163

Performance of hybrids developed from GS-C3-DH lines, founder parents and commercial checks

under optimumYi

eld;

t/ha

Populations

Pop1-GWS Pop2-GWS Pop3-GWS Pop4-GWS Pop5-GWS0

1

2

3

4

5

6

7

8

9 Top 5 hybrids Parents Commercial checks

Phenotyped at 3 optimum locationsGain over the commercial checks= 8.7 to 20.8%Gain over the parents = 9.0 to 91.1%

Gain in grain yield under drought and optimum across 10 MARS pops

Beyene et al. (2016) Crop Sci. 56:1–10

Genetic gain from conventional breeding in Africa 18 kg ha-1 yr-1 (Edmeades, 2013)32 kg ha-1 yr-1 (B. Masuka, submitted)

Genetic gain GS is 1.6- 2.8 times higher than from conventional breeding reported in sub-Saharan Africa.

Overall gain in GY : 51 kg ha-1 year-1

Performance of hybrids developed from individual C1S2 of MARS and pedigree breeding under drought

1008 1015 1016 1017 1018 1019 1020 1021 1023 10280.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

Best C1S2PedigreeCheckParents

Populations

Grai

n yi

eld

(t/h

a)

Beyene et al. (2015) Euphytica : online first

Heritability = 0.32 to 0.75

Improved inbred lines and hybrids developed through rapid-cycle GS

Fixed lines

Drought tolerant hybrids

Transgenic R&D

The effect of CspB gene on grain yield of maize under field condition in the USA

Grain yield of 3 hybrids with CspB gene evaluated in yield trials across the western dryland USA - averaged across locations that experienced water-deficit stress during the late vegetative or grain fill periods of theseason.Castiglioni et al., 2008

MON87460 yield differences between positive & negative across locations in South Africa (2008-2014)

• Hybrids showed significant benefit of trait (MON87460) under drought stress in general and under severe, high and moderate drought stress.

• The more severe the stress the higher the differences between positive and negative (up to 360 kg/ha).

**%

Delta

Optimum Stressed Severe High Moderate Low0

1

2

3

4

5

6

7

8

9

*

*Stress N Positive N Negative

Optimum 2472 2593Stressed 7076 7019

Severe 277 279High 3022 2951

Moderate 2383 2348Low 1394 1441

Positive Mean Negative Mean0

2

4

6

8

10

12

Yiel

d [t

/ha]

*24%

• The gene has a positive and significant effect on yield.

• The gene significantly reduced numbers of exit holes and tunnel length after artificial C. partellus infestation.

• The gene significantly reduced B. fusca larvae survival and leaf area consumed.

Prop

ortio

n B.

fusc

a la

rvae

aliv

e

Positive Mean Negative Mean0.00

0.10

0.20

0.30

*-81%

Leaf

Are

a Co

nsum

ed [m

m2 ]

Positive Mean Negative Mean0

10

20

30

40

50

*-73%

Tunn

el le

ngth

[mm

]

Positive Mean Negative Mean0

1

2

3

4

5

*-96%

Positive Mean Negative Mean0

1

2

3

4

Num

ber o

f Exi

t Hol

es *-96%

MON810 Kenya CFT1-3 Executive Summary

Highlights of Achievements• A total of 59 hybrids released in in Kenya, Tanzania, Uganda and

South Africa

• Successfully integrated molecular markers and DH technology into product development

• We have conducted the largest public MARS/GS projects and demonstrated 2-3 fold higher grain yield using MARS and GS than pedigree methods in tropical maize

• • Meta analysis of MON87460 indicated significant benefits of DT

trait under drought stress

• Combined analysis of MON810 in Kenya indicated positive and significant effects on grain yield under artificial infestation

Other contributors to the studies(in alphabetical order)

• Amsal Tarekegne• Barbara Meisel• Bindiganavile S. Vivek• Boddupalli M. Prasanna• Gregorio Alvarado• Jose Crossa• Kassa Semagn• Lewis Machida• Pierre Sehabiague• Raman Babu• Stephen Mugo• Sudha Nair• CIMMYT research assistants at different locations

Acknowledgements

• WEMA Partners• Bill and Melinda Gates Foundation (BMGF)• United States Agency for International

Development (USAID) • Howard G. Buffet Foundation (HGBF)