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Sarah Hearne, Sukhwinder Singh, Carolina Saint-Pierre, Gilberto Salinas, Jorge Franco, Terry Molnar, Martha Willcox, Carolina Sansaloni, Cesar Petroli, Juan Burgueño, Jose Crossa, Alberto Romero, Charles Chen, John Hickey, Gregor Gorjanc, Janez Jenko, Andrzej Kilian, David Marshall, Ed Buckler, Peter Wenzl, Kevin Pixley + many more!
From genebank to field- leveraging genomics to identify and bring novel native variation to breeding pools.
Coordinated by:
Funded by:
Potentially valuable genetic variation, the raw material for crop
improvement, remains untapped on genebank shelves, at a time when challenges to crop production are
unprecedented
Genebanks should NOT be museums. Genetic variation is the basic ingredient of all plant breeding Genebanks should be a source of high-value genetic diversity to meet tomorrow’s challenges
Systematically identify & mobilize novel, beneficial genetic variation into breeding programs to accelerate and strengthen
genetic gains
Genetic resources
Crop improvement
Agronomy & seed systems
Improved livelihoods
SeeD
• Identify underutilized accessions of interest • Find patterns in genome characteristic of
beneficial adaptation: Selection imprints • New Heterotic patterns (maize) • ID rare but beneficial genome recombination
• Novel, beneficial alleles and donor germplasm identified
• Markers linked to genes that control priority traits
Molecular atlas Genomic Associations
Novel alleles and allele donors
“Bridging” germplasm
1 2
3
4 5
Capacity-strengthening
Information management
• Bridging germplasm (breeder-friendly lines and populations) enriched for novel, high-value alleles for stress tolerance, pest resistance and higher nutritional value available to breeders worldwide
• Toolkit to enable rapid adoption and accelerated breeding using bridging germplasm linked genetic elements that control priority traits
• Capacity to enable research and adoption of outputs from SeeD within the breeding community
Maize modules
Molecular atlas
Genebanks - supermarket
Molecular atlas
Common label - genotypic data
# markers vs. # samples GbS ‘flavors’
• Cornell University (ApeKI): Lots of markers (~850K markers; SNP only), ~50% missing data, imputation desirable maize AM
GbS = configurable platform
• DArTseq (Diversity Arrays Technology; PstI): Fewer markers (both SNP & ‘PAV’), higher coverage, lower error rates, less missing data, dynamic “reference” not dependent on B73 (~40% SNP tags no alignment with B73: re- seq 28 accessions and DH Langebio and NRGENE)
• maize diversity surveys
• DNA pools?
Molecular atlas
• Identified most repeatable method of complexity reduction
• GbS 8 diverse accessions minimum 92individuals / acc’n
• Simulated sampling of 4-40 individuals
• Distance and diversity
• Created real bulks -pooled DNA extraction
Molecular atlas
GBS for landraces- sampling
• Divergence between bulks stabilizes from 20 for all accessions
Number of individuals per bulk
0 10 20 30 40 50 60
Test ra
tios for
Ham
min
g m
atr
ix
betw
een tw
o independent bulk
s
0
5
10
15
20
25
30
OAXA173
PUEB75
VERA133
GUAT329
GUAT286
OAXA248
URUG1121
URUG1124A
Molecular atlas
n a me = OAXA2 4 8
He He _ p r e d i c t
0 . 1 3
0 . 1 4
0 . 1 5
0 . 1 6
0 . 1 7
0 . 1 8
0 . 1 9
0 . 2 0
0 . 2 1
0 . 2 2
n p l a n t
0 1 0 2 0 3 0 4 0 5 0
GBS for landraces- sampling
12 20
25
33
12-40+
Mean He
Molecular atlas
Composite (bulk) method provides very robust measures of genetic distance and good estimates of diversity
GbS = configurable platform
Individual samples
Po
ols
• DNA pools of 30 plants per
accession allele frequencies within accessions from SNPs
• 10% underestimation of He when all data used
• Little bias when consider markers of higher coverage
• 30-fold reduction in costs!
• Genetic distances among accessions from PAVs
Molecular atlas
• GbS of entire CIMMYT maize genebank (>27,500) completed end 2014
• Initial analysis of 21,000 accessions: – 1.2m SNP loci in total
– Mean 980k loci per accession (~ 20% missing data)
– 317k loci with coverage ≥5X
• Also genotyping breeding materials (donors) and ex-PVP lines for comparison
MAIZE genetic diversity survey Molecular atlas
Missing ingredients
6% 94%
10k accessions and 540 CML
Molecular atlas
ID accessions of interest
ID New sources of high value characters and alleles
Combine data resources
• Drought: 9954 landraces come from environments with long-term propensity for drought during flowering (Low AI)
• Genetic analysis using GbS data indicates these landraces cluster into six main groups
Cluster
Cluster
Molecular atlas
• The six groups come from significantly different environments: All dry but some much drier than others- indicating some genotypic patterning- adaptation
LS Means of AI across clusters identified for three months of flowering and the entire 6 month
growing period. The effect of cluster on AI for all three flowering months and over the growing
period was significant (p<0.0001). Entries with the same letter code do not differ significantly
(Tukey multiple comparison test <0.01 following ANOVA).
Group Period # acc
FL Month 1 FL Month 2 FL Month 3 6 month growing
1 1.926 c 1.923 b 2.498 d 1.885 e 2767
2 1.433 b 1.379 a 1.603 a 1.134 a 2279
3 1.459 b 1.486 a 1.776 b 1.249 b 1335
4 1.260 a 1.458 a 1.485 a 1.099 a 781
5 2.005 c,d 2.241 c 1.945 c 1.713 d 1211
6 2.136 d 2.213 c 2.009 c 1.592 c 1581
ID accessions of interest
Molecular atlas
Breeder-oriented cores
$300k 2y $150k 2y $72k 1y
$30k 1 season $14k 1 season
Molecular atlas
• Look for of selection motifs
Selection footprints / selection sweep
Palomero
Cónico
Arrocillo
Molecular atlas
Novel alleles and allele donors
Upstream Breeding-oriented
Genetically simple traits
[some diseases]
Genetically complex traits
[heat/drought tolerance]
Main emphasis: Mobilize novel alleles for complex traits into
breeding programs
‘Low-hanging fruits’ for breeding
Seek collab
oratio
ns to
min
e data
for b
asic research
Prioritization of traits Novel alleles
and allele donors
Accession 1 Accession 4,000
Tester Tester
SeeD Maize GWAS
…
34 trials
Three adaptation zones: • Lowland Tropical
• Subtropical • Highland Tropical
36 Latin American countries
Highland Subtropical Tropical
Novel alleles and allele donors
GbS Cornell and DArTseq methods - Maximize marker density (Cornell) - Enable identification of heterozygote regions
(DArTseq)
Accurate, field-based phenotyping is the main bottleneck
Traits Maize
Abiotic stresses
heat
drought
low N
Biotic stresses tar spot, ear rot, stalk rot, Turcicum, Cercospora
Grain quality and nutritional quality
hardness, starch, oil, protein content, amino acids, phenolics, vitamin A, Zn
• Maize: 800,000 data points from 35 trials across 14 locations
Novel alleles and allele donors
GWAS in SeeD POC: Flowering time
Association at known loci can provide insight into statistical power
500k SNP, imputation with FILLIN
GWAS were performed per trial using BLUPs for days to silking using naïve GLM and GLM+Q. Non parametric meta-analysis
There are markers with significant association at and close to Vgt1 and ZCN8
POC: we can perform GWAS in the SeeD panel
Novel alleles and allele donors
• Structural rearrangement- Inv4m locus
• Previously reported inversion in teosinte and highland maize (Hufford et al, 2013; Pyhäjärvi et al, 2013)
• Introgression with potential selective advantage
Signal in a new locus on chromosome 4
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0.0e+00 5.0e+07 1.0e+08 1.5e+08 2.0e+08 2.5e+08
46
810
12
14
AFNN MLM Q+K Chr 4
Position
−lo
g P
0 50 100 150 200 250
Chromosome 4 position (Mb)
Agua Fria 2011, MLM Q+K
Novel alleles and allele donors
Inv4m locus 4 has an additive effect on days to anthesis
Inv4m haplotype clustering
MDS Coordinate 1
MD
S co
ord
inat
e 2
Days to anthesis by cluster
Cluster
Day
s to
an
the
sis
Homozygous inversion
Heterozygotes
Heterozygotes
Homozygous reference
Homozygous inversion
Homozygous reference
Novel alleles and allele donors
Largest effect on flowering documented to date
Tar spot disease complex Novel alleles
and allele donors
Novel alleles and allele donors Tar spot disease complex
Alleles not present in CML
Drought
Alleles not present in elite germplasm
Nu
me
ro d
e T
C
Numero de TC
Novel alleles and allele donors
Pyramiding alleles: ID best accession sources
MAIZE phenotypic diversity: per-se
• Per-se phenotyping difficult • Accessions = populations • Lodging • Three adaptation zones
• Drought, heat, anthocyanin
• Used AI as proxy for selection for drought
• Evaluation of 700 Lowland tropical and sub-tropical materials
• 100 BiP populations formed
• GIS analyses = good complement/substitute for expensive phenotyping
Novel alleles and allele donors
“Bridging” germplasm
“Bridging” germplasm
Maize ‘bridging germplasm’
…using multiple strategies defined by trait complexity
and breeder needs
(desired input germplasm,
demand for new sources)
Useful novel alleles &
haplotypes
Early
generation lines & pools enriched for
favorable alleles
Breeder
demand
Trait complexity
Monogenic (1-3)
Oligogenic (4-10)
Polygenic (>10)
Urgent DH from
landrace & landrace / line crosses, selfing
DH from
landrace & landrace / line crosses, selfing
GS with
MABC for BC1S1 develop-ment
Medium-term
MABC MARS & prediction
index
GS with MABC for
BC1S2 develop-ment
Long-term MABC & GS
MARS, prediction
index & GS
GS with MABC for
BC1S2 develop-ment
“Bridging” germplasm
Assessment of options; simulations G
en
etic me
rit “Bridging” germplasm
Founder germplasm – Accession, TC, DH Marker density- 10k, 100k Retraining Accession sampling
Pre-breeding
6 GS populations- broad accession based synthetics- drought, heat, low N 100 lowland and sub-tropical accessions ID for drought – BC1S1 (CML) –selection of 50 pops data for GS 2 accessions for Tar Spot BC to favorable CML – ID additional alleles and use in MABC Blue maize – 8 accessions BC pops ID accessions Cercospora, Turcicum, PVA, protein, oil, Fusarium stalk rot. • DH- works but put in inducible background
first
“Bridging” germplasm
Prospects Swim in data (not drown), collaborate and enhance capacity • Data release- Germinate,
Dataverse
• Protocols, software, scripts
• Analysis – QTL; GWAS, Bi-P
– “Global” diversity
– Core sets
– Selection footprints
• Germplasm – Pre-bred germplasm with novel
high value traits- disease, drought, heat, quality and associated marker information – from 2016
“Bridging” germplasm
Novel alleles and allele
donors
Molecular atlas
Thank you
