Breeding Nutritionally
Enhanced Maize:
The Tropical Experience
K. Pixley, R. Babu, J. Yan, N. Palacios
& colleagues
GEM Cooperator Meeting, 8 December 2010, Chicago
QPM: Nutritionally enhanced maize
“The Pigs”
QPM also “works”
with chickens…
QPM

Pellagra: diarrhea, dermatitis; due to
niacin deficiency. Tryptophan is a
precursor of niacin

Kwashiorkor: edemas, anorexia,
increased susceptibility to infections;
due to low quality protein
Normal
Maize
What is QPM?
• Contains one gene – opaque2 (o2) –
that affects protein production in the
grain
– No change in protein quantity
– More of proteins rich in tryptophan and
lysine
• o2 was found in maize; QPM is not
transgenic
• Looks, cooks and tastes like normal
maize
• Must be, and many are,
agronomically competitive
Where is maize an important source
of protein?
FAO Stat
WHO, 2007. Protein and amino acid requirements in human nutrition.
http://whqlibdoc.who.int/trs/WHO_TRS_935_eng.pdf
Summary: QPM meta-analysis
Gunaratna et al.
• 9 studies: 5 countries (Ethiopia, Ghana, India, Mexico,
Nicaragua); 48-486 children; 3.5 mo – 5 yr old
• Consuming QPM instead of normal maize resulted in:
– 12% (95% CI: 7-18%) increase in weight gain
– 9% (95% CI: 6-15) increase in height gain
These results were robust; essentially unchanged by:



Various adjustments/transformations to
the data, or methods to calculate CI
Discard studies with most extreme
results
Discard any of the studies
Gunaratna et al., Food Policy 2010
Iron deficiency affects >2 billion people
• Iron deficiency anemia (IDA)
– Maternal and perinatal mortality
– Impaired cognitive skills and physical activity
• Women and children in South Asia and Africa
Zinc deficiency
• Zn deficiency
– 800,000 child deaths per year; increased risk
• Diarrhea, pneumonia, malaria
– Stunting during early childhood
– Equally affects males and females
– South Asia and Africa
Photo: N. Palacios
Vitamin A deficiency
• Vitamin A deficiency (VAD)
– Night blindness, corneal scarring &
blindness
– Weakened immune system: VAD
associated with
• 20% of measles• 24% of diarrhea• 20% of malaria-related mortality
in children;
• 20% of maternal mortality
– South Asia and Africa have highest
VAD prevalence
– 157 million pre-school children
– 30 million pregnant women
* Micronutrient malnutrition
affects more than half of the
world’s population –
United Nations SCN, 2004.
Dietary sources
• Vitamin A
– Meat (esp. liver)
– Vegetables (carrot, sweet potato, spinach)
• Iron
– Red meat, fish, poultry
– Lentils, beans, leafy vegetables
• Zinc
– Oysters, animal proteins,
– Beans, nuts, whole grains
Rural Bangladesh
Share of expenditures
before price rise
$$$
$
Staples
Animal
Nonstaple
plants
$$$$
$$
Share of expenditures
after price rise
Staples
Meat &
Fish
Non-Food
Non-staple
plants
Meat &
Fish
Non-Food
Biofortification of staple food crops
• Micronutrients available in staple foods
– Sustainable, affordable
– Accompanied by dietary/nutrition information
– Complemented by supplementation and fortification
• Acute malnutrition
• Equal or better agronomic performance of biofortified crops
– Yield, disease resistance, drought tolerance…
Cross high proA x good drought tolerance…
De3,
SC55,
CI7
BC1S1
X
X X
X
X
XX
BC1S2
BC1S4
2nd Dose F1’s
BC1 2nd Dose S1’s
X
X X
8 promising proA hybrids: 5 sites in
Zambia + 2 sites in Zimbabwe
Tons per hectare
Best hybrid check
ProA
(ug/g)
Hybrid 1: 8.9
Hybrid 2: 7.1
Hybrid 3: 6.3
Hybrid 4: 6.5
Hybrid 5: 7.4
Hybrid 6: 5.7
Hybrid 7: 6.9
Hybrid 8: 5.9
LCYE affects the ratio of carotenoids in
the biosynthetic pathway
GGPP
PSY
PDS
Z-ISO
ZDS/CRISTO
1. Alleles for LCYE identified by:


Association mapping
Linkage mapping
LCYE
lycopene
δ-carotene

Expression analysis
LCYB

Mutagenesis
α-carotene
HYDb
zeinoxanthin
Harjes et al., Science 2008
HYDE
lutein
2. HYDB1 has a large effect on BC
Yan et al., Nature Genetics 2010
LCYB
γ-carotene
LCYB
β-carotene
HYDb1
β-cryptoxanthin
HYDb
zeaxanthin
ABA
 De3
 (KU1409/DE3/KU1409)S2-18-2-B
Total proA (ug/g) in 9 genotypic classes
of 6 crosses
LycE
4
HydB
1
4
2
4
H
2
1
2
2
2
H
H
1
H
2
H
H
Pop 1
5.60
5.74
7.41
7.40
2.08
2.06
4.16
4.11
9.45
9.47
3.58
3.59
4.83
4.87
Pop 2
12.03
11.94
4.27
4.09
6.17
11.11
10.74
3.36
3.34
4.07
4.07
12.96
13.20
4.14
4.21
6.82
6.80
Pop 3
9.97
9.70
4.78
4.73
7.19
6.92
3.73
3.71
5.30
5.40
Pop 4 Pop 5
6.15
6.12
3.46
3.99
3.57
4.08
7.42
7.51
6.25
6.19
2.60
4.28
2.50
4.33
3.88
4.42
3.89
4.43
5.08
4.98
3.95
4.13
5.41
5.41
 B104
 CML325, CML327, CML460
Pop 6
5.74
5.75
3.90
3.74
5.10
5.09
3.31
3.29
3.88
3.93
3.64
3.60
 Bank accessions (hets)
 KUI carotenoid syn-FS17-3-2-B
Seed genotyping pre-planting


Dry chipping using dog nail clippers
≈10,000 seeds will be genotyped pre-planting this season
Steps to develop a hybrid cultivar (w/MAS)
year
1 UU x FF -> UF
Elim.50%
UF x UU -> UU:UF
200UF seeds -> 50UU:100UF:50FF
2 50FF S1 ears -> 40FF S2 ears
1-2 best S6 x 3 tester -> 15 Stage3 hyb
5 S7 -> HPLET
75%
40FF x tester -> 15 stage1 hybrids
3 15 best S3 -> 15 best S4
4-5 best x tester -> hyb
6 Multilocation on-farm trials
1-2 best -> release
7 Multilocation on-farm demo’s
8 Begin marketing seed
$10
15 S4 (HPLC) x 3 tester -> 15 Stage2 hyb
per
4 5 best S5 -> 5 best S6
row +
time
$5850
$25150+120+45 nursery
75/sa
+ (45x6) trial rows
mple
$2250
What happens to provitamin A during
cooking?
Photo: N. Palacios
Photo: H. De Groote
Effect of porridge preparation
Shanshan Li et al.,
2007
25% loss of β-carotene
Effect of snack preparation
• 36% loss of
provitamins A
following
nixtamalization and
snack preparation
by deep frying
(n=13)
Lozano Alejo et al., 2006
What happens to provitamin A after we
eat them? …bioaccessibility
In vitro assessment of
bioaccessibilty of carotenoids
from foods
Parker, FASEB J, 1996
Mark Failla
Department of
Human
Nutrition
KUI carotenoid syn-FS17-3-1-B-B/CML356-B
20.5
41.1
Combining proA and Zn …bioefficacy
21.1 37.7
KUI carotenoid syn-FS17-3-1-B-B/(CML-356 x GWIB) -1-23TL-1-2-1-B
dehydrogenase
Vision
KUI carotenoid
syn-FS17-3-2-B-B/CML353-B
retinal
retinol
19.7
32.0
 Zn in the action of retinol dehydrogenase
KUI carotenoid syn-FS17-3-2-B-B/(CML-239 x GWIC) -1-7TL-1-1-1-B
18.7 for
32.5
monooxygenase
(retinol to retinal); essential pigment
Digestion
-carotene
2 retinal
Zn KUI carotenoid syn-FS17-3-2-B-B/CML355-B
vision
15.8 29.8
KUI carotenoid syn-FS17-3-2-B-B/CML356-B
 Zn is a probable co-factor for b-carotene
22.4 35.2
KUI carotenoid syn-FS17-3-2-B-B/(CML-356
x GWIB) -1-23TL-1-2-1-B
mono-oxygenase
(cleaves proA to23.1
vitA)33.2
Protein synthesis
retinol binding protein
retinol:RBP in blood
KUI carotenoid syn-FS25-3-2-B-B/CML353-B
 Zn deficiency depresses synthesis22.9
of the
(RBP)
33.0
carrier protein
of vitA => lower plasma
KUI carotenoid syn-FS25-3-2-B-B/(CML-239
x GWIC) -1-7TL-1-1-1-B
22.0 31.9
retinol concentrations
0.5
0.5
0.3
Zn
Zn
KUI carotenoid syn-FS25-3-2-B-B/P903 C0 H364-1-8TL-3-2-1-1-B-B-B-B-B -B
0.5
0.2
2.0
2.0
2.0
2.1
19.8
29.3
0.3
KUI carotenoid syn-FS25-3-2-B-B/(CML-356 x GWIB) -1-23TL-1-2-1-B
ppm
22.6
ppm
29.8
ppm
0.5
KUI carotenoid syn-FS17-3-1-B-B/CML353-B
Carotenoid Syn3-FS5-1-5-B-B/CML353-B
18.1
20.5
33.3
28.6
0.6
KUI carotenoid syn-FS17-3-1-B-B/(CML-239 x GWIC) -1-7TL-1-1-1-B
17.9
34.8
0.3
20.5
41.1
0.5
KUI carotenoid syn-FS17-3-1-B-B/(CML-356 x GWIB) -1-23TL-1-2-1-B
17.2
23.1
0.4
CML-304-B-B/CML353-B
KUI carotenoid syn-FS17-3-2-B-B/CML353-B
14.5
19.7
26.0
32.0
0.3
0.3
KUI
carotenoid syn-FS17-3-2-B-B/(CML-239 x GWIC) -1-7TL-1-1-1-B
Average
20.4
18.7 31.6
32.5 0.8
0.5
2010: Stage 1 High Zn x ProA
KUI carotenoid syn-FS17-3-2-B-B/CML356-B
2011: S2’s High Zn x ProA (HYDB1) to TC
15.8
29.8
0.2
22.4
35.2
2.0
Pedigree
Carotenoid Syn3-FS5-1-5-B-B/CML355-B
KUI carotenoid syn-FS17-3-1-B-B/CML356-B
CML-305-B-B/CML356-B
KUI carotenoid syn-FS17-3-2-B-B/CML355-B
Fe
32.0
21.1
Zn
32.9
37.7
Al
0.6
0.6
0.5
Will farmers and consumers grow/
consume biofortified crops?
• ProA sweet potatoes are orange;
consumers prefer white
• Will farmers choose to plant the
biofortified varieties?
• Will farmers choose to grow orange
maize varieties?
• Will seed companies market the new
orange varieties?
No complaints from these consumers!
Agriculture for nutrition and health
+
0.00
13.698
0.02
10.578
11.517
0.04
9.183
0.06
6.717
7.024
7.217
7.957
+
3.332
3.961
4.485
4.750
+
+
AU
0.08
18.859
0.10
16.246
5.473
0.12
-0.02
2.00
Plant breeding
and agronomy
Education &
marketing
+
8.00
10.00
12.00 14.00
Minutes
16.00
18.00
20.00
22.00
24.00
+
+
+
Socio-economics
6.00
Plant biochemistry
Molecular
biology
+
4.00
Nutrition
Healthy families
Food technology
Seeds of Discovery
(SeeD)
A Mexican initiative to contribute
to global food security vis-à-vis
climate change and resource
scarcity by broadening the
genetic base of global maize and
wheat-breeding programs
P. Wenzl, K. Pixley, G. Atlin, G. Edmeades,
M. Banziger & many colleagues
Historical bottleneck
10 – 20 years
Genetic
resources
Breeding
programs
SeeD: new genetic
variation to raise future
crop production
Variety
adoption and
improvement
Increased
agricultural
production
Factors limiting the use of GR
 Factor 1: So many accessions, so little information!
– Challenges to characterize accessions at phenotypic and
molecular levels
– Missing or ‘superficial’ passport data
 Factor 2: Insufficient tools
to mine
information
Many
of the
same
– Outdated/user-unfriendly data management tools
challenges and
– Limited query capabilities
issues of GEM!
 Factor 3: How to effectively utilize exotic germplasm?
– How to identify beneficial alleles in exotic germplasm?
– How to capture novel, useful variation into elite backgrounds
Objectives of SeeD
 Objective 1: To mine maize/wheat genetic resources for
novel alleles and beneficial traits combining genotyping
and phenotyping methods
 Objective 2: To build on-line catalogues that facilitate
the identification of beneficial genetic variation, and
 Objective 3: To put in place practical delivery pathways
that empower maize and wheat programs to broaden
their genetic base by incorporating novel variation
Marker-assisted
introgression
pipeline service
facility
Doubled haploid
service facility?
Develop and
release “bridging
lines”
SeeD: A technology intensive project!

Because of the size and complexity of the initiative,
will require strategic alliances with key players.

Key partnerships:
1. Genotyping
2. Phenotyping
3. High-performance bioinformatics approaches for
genetic analyses
4. Cyberinfrastructure for a SeeD web portal
Concept-development guidelines:

Focus on user base targeted by SeeD: maize and
wheat breeding programs, especially public and
SME breeding programs in developing countries
Design practical delivery paths that enable the
adoption of novel and useful genetic diversity in
breeding programs.
Draft strategy for maize
General points (and working assumptions)
•
The CIMMYT maize collection has about 26,000
accessions with no genotypic data, incomplete passport
data, and some phenotypic data
•
Most accessions are heterogeneous with much more
genetic variability among than within accessions.
•
Alleles that are rare globally, and at low
frequencies in the accessions in which they occur,
are unlikely to be very important or detectable.
•
Most traits in maize are highly polygenic.
•
Haplotypes with small effects likely control most
variation
General points (cont’d)
•
Main diversity is to be found in the Mexican-Guatemalan
germplasm, which has been in long co-existence with
teosinte
•
Much genetic variability remains in teosinte, but there are
few introgression populations available that could allow
us access to this variability
•
Demand for direct access to landrace or teosinte
accessions by breeders will be limited
Two main products of SeeD for maize
•
Haplotype effect estimates for loci with small effects
•
Well-characterized accessions for specific traits to be used
as donors for large-effect alleles
Haplotypes as the unit of evaluation
•
•
Because haplotypes are likely to be replicated across many
accessions, it is the haplotype rather than the accession
itself whose effect we want to estimate, and that is the
unit of evaluation or selection
To sample haplotype frequencies and to begin estimating
haplotype effects, one plant per accession will be initially
genotyped at >1,000,000-plex, on the assumption that this
would detect all but the rarest alleles
Test crosses
•
To estimate haplotype allele effects, the single-plant
representatives of core accessions will be crossed to elite,
adapted testers (testers as females)
•
The testcrosses will be phenotyped in screens of interest.
GEBV prediction for all accessions
•
Because haplotypes will usually be replicated across
accessions, it not necessary to estimate the effect of each
testcross with high precision via high levels of replication
on individual accessions.
•
Based on allelic effects estimated by phenotyping the
subset of core accessions, the entire collection will be
examined for accessions that have high GEBVs for traits of
interest, and that are under-sampled in the existing elite
germplasm.
•
New pre-breeding populations will be established from
these accessions and improved by genomic selection.
“Details of this approach to delivery of new
genetic variation for quantitative traits needs
a lot more thought…”
Large-effect alleles
•
The objective is to identify accessions with high frequencies
of unusual alleles with large effects on simple or oligogenic
traits. There will likely be very few of these.
•
The accession is the unit of evaluation
•
The core and materials that have a high likelihood of
having been selected for the trait (based on passport
information) need to be phenotyped at high precision,
either per se or in testcrosses.
Large-effect alleles
•
Map, and develop gene-based markers
•
Introgress the allele of interest into elite inbreds (“bridge
inbreds”), which breeding programs will be want to use
• As donors for MAS-based conversion, or
• As parents of pedigree starts.
•
SeeD probably needs to develop such inbreds as
deliverables, to ensure that any genes discovered are truly
accessible to smaller public and private breeding programs
in the developing world
SeeD and GEM
 Many opportunities for complementarity and
partnership with GEM
 Important to communicate often and learn from each
other
 Many questions we can work together to answer and
enhance the use of genetic resources
P.Wenzl@cgiar.org
G.Atlin@cgiar.org
K.Pixley@cgiar.org