Transcript A MAGICal approach to explore and utilize functional diversity in plants Guri Johal Department of Botany and Plant Pathology October 13, 2010

A MAGICal approach to explore
and utilize functional diversity in
plants
Guri Johal
Department of Botany and
Plant Pathology
October 13, 2010
MAGIC: Mutant-assisted gene identification and characterization
Topics to be covered
• What is MAGIC and what is so novel about it
• How it was conceived
• How we are using it to explore and enrich genetic
networks underlying the hypersensitive response (HR)
• How it can be extended to other traits
MAGIC: Mutant-assisted gene identification and characterization
It allows us to sift through natural variation for functional
diversity quickly and effectively
Why bother about Natural Variation (NV)
• Represents a huge repository of trait variants
• An ideal source of adaptive variation
• Much of it could be useful directly because it has been
defined, refined and tested by millions of years of
evolution and natural selection
• Mostly represents not loss-of-function or gain-of-function but
change-of-function variation
• Understanding the genotype - phenotype relationship
Extent of Natural Variation in our crops
Exotics include only those lines that cross readily with their domesticated counterparts.
Maize-----
Tanksley and McCouch, 1997
Extent of Natural Variation in our crops
Such lost alleles can be recovered only by going back to the wild
ancestors of our crop species.
Tanksley and McCouch, 1997
Problems with Natural Variation
• Much of it stays cryptic
• Complex: exhibits multigenic inheritance
• Therefore, can not be explored by simple genetic
approaches
The next big challenge in biology is to make
sense of natural variation
Current strategies for the evaluation and
utilization of NV
• Phenotypic analysis
• QTL mapping and analysis
• Association mapping
Phenotype alone is not a good predictor of the
genetic worth of a line
Tanksley and McCouch, 1997
C
A
B
C
D
e
product or trait
The QTL approach
- Various types of mapping/segregating populations can be
used for this purpose:
- F2, F3 populations
- Back cross populations
- Doubled haploids (DH)
- Immortalized populations: DH, RILs, or NILs
-RILs – recombinant inbred lines
-NILs – Near isogenic lines
Recombinant inbred lines (RILs)
(Self pollination)
IBM RILs in maize – derived from a cross of
B73 x Mo17
Problems with the QTL approach
• Only two parents can be used at a time
- To alleviate this problem partially, multiple RIL/NIL
populations are being made
• In maize – in addition to the IBM RIL population, 25 RIL
RIL populations have been generated between B73
and 25 diverse lines (the NAM resource)
• In Arabidopsis – 20 RIL populations between different
accessions have been made
Nested association mapping (NAM) resource
Multiple parent populations
Multi-parent advanced generation inter-cross
World germplasm resources
Estimated number of seed bank entries worldwide for selected crops
Crop
Entries
Collections of 200+
Percent wild species
Wheat
410,000
37
60
Rice
215,000
29
10
Maize
100,000
34
15
Soybean
100,000
28
30
Potato
42,000
28
40
Tomato
32,000
28
70
Cotton
30,000
12
20
So we need a really creative and effective method(s) to
mine and harness natural variation
Mutant-assisted detection and capture of NV
by MAGIC
Its underlying principle is:
The phenotype of a mutant (in the trait of interest) can be
used to:
- unveil useful variation present in any line
- consolidate this variation in individual plants
To perform MAGIC
X
mutant
Diversity
line
recessive mutant
F1 hybrid
F2 progeny
Transgressive segregants
Second-site suppressor/enhancer screen
following intentional mutagenesis
EMS
pollen
X
Dwarf mutant
M1
M2 population
MAGIC (screen) is even more effective if we use a
dominant mutant
F1
P2
P1
X
F1
P3
P1
X
How was MAGIC conceived?
Disease lesion mimic mutants of maize
- characterized by having symptoms that resemble disease (or a
massive HR) but in the absence of pathogens
• Lesion mimic mutants have been identified
in every plant species.
• More than 50 lesion mimic loci have been
identified in maize.
Les8
Les9
Les4
Lesion mimic is one of the most common
phenotypes in plants
Can result from:
•
Genetic aberrations in R genes ( e.g., Rp1-D21, Ssi4, Snc1)
•
Defects in genes that modulate plant defense responses (e.g.,
Acd6, cpn1, lsd1, mlo1, spl11)
•
Errors or impairments in metabolism (e.g., acd2 and lls1
(acd1) in chlorophyll degradation; Les22 chlorophyll
biosynthesis)
•
Defects in genes involved in cell death control or execution
(e.g., acd5, acd11 (both in the sphingolipid pathway) and lls1)
•
Defects in nucleotide-gated channel genes (e.g., dnd1 and
hlm1)
•
Blockage of exocytotic secretion (les24)
Why Lesion mimics?
Two most common mechanisms for Les/les mutations
•
Inappropriate production of reactive oxygen species (ROS)
•
Constitutively induction of defense responses,
•
especially because of the ectopic activation of NBS-LRR
proteins, causing spontaneous induction of the HR
response
Most lesion mimics are conditional
mutants
• Developmental factors
• Genetic background
Effect of genetic background on lesion mimic mutants
Rp1-D21 in Mo20W
Rp1-D21 in B73
Effect of genetic background on maize
Les/les mutants
Initially recognized by Gerry Neuffer while
working with Les1 (1985)
Mo20W – suppressed Les1
W23 - enhanced Les1 severity
Genetic background effect …
les23 plants
Light-dependent expression of les23
Mo20W
Va35
Brent Bucker, a sabbatical scientist in 1997
To look into the Genetics of ‘genetic background’
MO20W x les23 (Va35)
F1 (+/les23)
X
F2
A large F2 population (3,400 plants) was developed
that was planted in Iowa and Missouri
Phenotypic range of les23 mutants in an F2 population
derived from the cross MO20W X les23;Va35
1
6
2
7
3
8
- Percent coverage of leaf 7 and leaf 10 with lesions
- Date of initiation of lesions
4
5
9
10
Bryan Penning
Marker
bnlg1520
-
bnlg1316
-
bnlg1045
-
-
bnlg1887
bnlg1036
umc1259
-
-
-
-
umc1261
-
-
bnlg1297
Likelihood Ratio
QTL scan of chromosome 2
600
500
400
Rating
300
Leaf7
Leaf10
Initiation Date
200
100
0
Chromosome 2 QTL
bnlg1297
23.4
umc1261
umc1261
25.2
• We have named this QTL –
Slm1
(suppressor of lesion mimics-1)
40.5
4.6
2.2
7.3
bnlg2248
umc1259
les23
bnlg1036
bnlg1887
19.4
bnlg1045
16.8
3.6
0.5
1.6
18.7
umc1259
les23
bnlg1036
bnlg1887
17.8
slm1
bnlg1316
bnlg1045
10.1
slm1
bnlg1316
15.5
bnlg1520
Bryan Penning
37.8
IA99
bnlg1520
Mo01
189.4
189.7
190.1
197.8
MZA10615
MZA18257
IDP8680
*
c0176e15_7 +_8
c0176e15_23
c0176e15_42
MZA3156
c0176e15_45 +_46
MZA10027
c0176e15_32
187.7
c0176e15_37
186.9
c0176e15_18
174.2
IDP3952
*
MZA5988
Map-based cloning of Slm1
Chr. 2
381
264
28
11
193
10
7
2
0
5
Co-S egregating Marker
Left Flanking Marker
RP P 13-like P rotein
Old Left Flanking Marker
Indole-3-acetic acid amido transferase
Co-S egregating Marker 2bp Insertion
Low Copy
Slm1 Region
28 431 bp
Right Flanking Marker
les23 F2 phenotypic range
1
6
2
3
4
5
7
8
9
10
Used the les23 phenotype as an assay (reporter) to see
how individual QTL assorted and interacted with each
other to impact the final phenotype of F2 plants.
All les23 homozygous leaves at maturity
But they differ for Slm1
Does Slm1 suppress HR cell death triggered by Rp1-D21
HR cell death
The HR response is plant world’s most important immune response
Compatible vs. incompatible plant-pathogen interaction
Rp1-D21
Caused by constitutive activation of an allele at the Rp1 disease
resistance locus, which confers resistance to common rust
HR cell death
The HR response is controlled genetically and it
is programmed to be unleashed as a result of
specific interaction of disease resistance (R)
genes in the host with corresponding Avr genes
following a gene-for-gene paradigm (Flor, 1941)
Molecularly HR often involves R gene proteins of
the NBS-LRR class
CC/
•
•
•
•
CC– coiled coil
TIR- toll interleukin receptor
NBS nucleotide binding site
LRR- leucine rich repeats
Molecular basis of the HR response
R gene activation
Biochemical mechanisms underlying the HR response
In Rp1-D21, the HR response is induced constitutively
Rp1 - a complex locus
The Rp1-D allele – is made up of 9 NBS-LRR genes
1
2
3
4
5
6
7
8
9
Undergoes unequal crossing over frequently
1
2
3
4
5
6
7
8
9
1
2
3
4
5
6
7
8
9
1
2
3
4
5
6
7
8
9
1
2
3
4
5
6
7
8
X
X
9
Generation of the Rp1-D21 recombinant
7
8
1
Rp1-D21
9
X
2
3
1
A dominant lesion mimic
mutant
4
2/9
5
6
7
8
9
The HR phenotype of Rp1-D21 in H95
Maintained as a heterozygote
Rp1-D21 plants exhibit all the hallmarks of the HR
response
Rp1-D21
WT
PR1
PR5
superoxide
PRms
WIP1
18S rRNA
H2O2
mut
Does Slm1 suppress HR cell death triggered by Rp1-D21
Rp1-D21 in H95 background
Rp1-D21; H95 X Mo20W
Rp1-D21; H95 X B73
Expression of Rp1-D21 in B73 vs. Mo17
Expression of Rp1-D21 in B73 vs. Mo17
IBM RIL population
• 302 lines
• Derived from a cross between B73 with Mo17
• F2 plants were allowed to intermate for 4 generations before
inbreds (RILs) were extracted
MAGIC screen of the IBM population for modifiers of Rp1D21 (HR response)
- Rp1-D21::H95/+ was crossed with all the IBM RILs
- The resulting F1 progenies were evaluated for the severity of the
Rp1-D21 phenotype
Other RILs significantly suppressed Rp1-D21
MAGIC screen of the IBM population for modifiers of Rp1D21 (HR response)
- Rp1-D21::H95/+ was crossed with all the IBM RILs
- The F1 progenies were evaluated for the severity of the Rp1-D21
population
- The phenotypic data thus collected was correlated with the
genotypic data (which was already available for all these
IBM RILs) using a QTL software (QTL cartographer)
QTL scan
Identification of Hrml1 (HR modulating locus-1)
Chromosome 10
Rp1
To clone Hrml1 and to identify additional modifiers of the
HR response
We have started a MAGIC screen of the NAM resource
Nested association mapping (NAM) resource
Rp1-D21 phenotype in hybrids of H95 with the
NAM founders
In some cases HR becomes dependent on
temperature
Symptom morphology was impacted too
We are crossing many of the NAM RILs with
Rp1-D21(H95)
- The testcrosses of Rp1-D21::H95 with the IBM and NAM RILs are
allowing us to identify dominant modifiers of Rp1-D21
- To identify recessive suppressors and enhancers, we need to
go to F2 or BC populations.
- For Rp1-D21, we make F2 populations by pollinating WT F1
plants with pollen from their mutant siblings
MAGIC with wilty mutants
Wi2, Wi3, Wi4
Genetic background dependence of the wilty
phenotype
MAGIC does not have to be based on mutants alone
• Transgenes
• Cytoplasmic traits
In fact, using Tcms maize we have been looking for genes
imparting resistance to Cochliobolus heterostrophus race T
Southern corn
leaf blight
Acknowledgements
• Satya Chintamananni
• Anshu Garg
• Vijay Chaikam
• Bala Venkata
• Jiabing Ji
• Emma Gachomo
• Sandeep Marla, Kevin Chu, Anna Hasan, Bob Easter
• Brent Bucker ,Truman State University
• Peter Balint-Kurti, NC State University
• Cliff Weil, Purdue University
• Scot Hulbert, Kansas State University
Funded by: NSF (PGRP)
Purdue University Start-up Funds for G. Johal
RPP13-like Protein
B
c0176e15 44
c0176e15 45 to 46
Site of 2bp Insertion
C0176e15_23
c0176e15 42
c0176e15 7 to 8
Slm1 Interval2
1 3645 bp
M3
M1
c0176e15 44
c0176e15 44
c0176e15 42
c0176e15 45 to 46
RPP13-like Protein
C0176e15_23
Site of 2bp Insertion
M2
c0176e15 44
c0176e15 7 to 8
Mo20W BAC Slm1 Interval
77583 bp