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Natural Variation in Arabidopsis
ecotypes
Using natural variation to
understand diversity
Correlation of phenotype with environment (selective pressure?)
Correlation of phenotype with phenotype
WUE
T. Mitchell-Olds
Average yearly rainfall in collection site
Maloof et al, 2001: Correlation of latitude with light response and
Identification of responsible polymorphism in 2 ecotypes
El-Lithy et al, 2004: Correlation of seed size with early
but not late development rates
Using Natural Variation to Dissect Molecular Mechanisms
Underlying Diversity
What are the genes responsible for morphological differences
among closely related plants (ie. size, flower number, fruit size)?
What are the genes responsible for variation in environmental
responses (fitness, resistance to pathogens and disease,
resistance to stress, response to light)?
What kind of changes occur in evolution to allow plants to adapt
Under selective pressure (regulatory vs coding region changes)?
How do multiple genes interact to determine plant phenotype?
Can we develop better strategies for crop improvement?
Two kinds of traits can create intra-species diversity
Continuous Trait
# of
people
4
5
6
7
Height
Complex
Or
Quantitative
Trait
(under control
of multiple
Loci)
Discontinuous Trait
# of
people
Simple
Trait
(1-2 genetic
Loci control)
Symptoms of Muscular Dystrophy
Examples of Complex Traits
• Most human diseases
–
–
–
–
–
Heart disease
Susceptibility to cancer
Asthma
Diabetes
Lifespan
Traits of Agricultural Importance
–
–
–
–
–
Yield
Stress Resistance
Growth Rate
Nutrient efficiency
lifespan
Breeding for complex trait
improvement
Elite Line #1
Elite Line #2
Elite Line #1
Elite Line #2
10 QTL that contribute to trait
10 alleles that contribute positively to the trait
210 possible combinations of QTL alleles
Markers for each QTL assist breeders in creating desired lines
Useful/cool things that QTL are
good for
• Marker assisted breeding
• Defining interactions between loci
• Identifying unknown genes involved in traits
– Undetectable by forward genetics because of gene
interactions, weak effect, redundancy, or null allele in
starting accession
• Defining genes responsible for trait variation
among lines of interest
• Asking questions about evolution and adaptation
In recombinant inbred lines, chromosomes are
homozygous chimeras of parental chromosomes
100
50
25
12.5
6.25
3.125
1.6
COL
.8
.4
.2 = 99.8% homozygous
F2
x9
Inbred
Lines
(F9)
LER
F1
Population of RI lines
123456789…….
Chromosome 1
L L SS SS S S LL S S S S LLLS S L S S SS S S SS S S LS S S S L SLS S S S LSL S S
RED YELLOW
8
2
1
8
9
9
4
2
1
7
Chromosome 1
123456789…….
RED YELLOW
Population of RI lines
2
1
3
4
…
9 8 2 1 3 4 2 1 7 8 9 1 1 3 6 7 8 1 2 9 1 2 22 3 1 44 4 5 9 1 1 3 2 9 18 2 2 33 9 9 9 1 2
9
8
7
8
…
Sample QTL map for chromosome 1
10
LOD
Score
5
0
10
5 Seed
Weight
0 (ng)
-5
1
Position on Chromosome 1 (cM)
LOD
Additive
For red
allele
Limitations on mapping with RI lines
1. Must be genotyped with high density of markers
2. Must be variation within population, preferably with transgression
Parents
# of
RI
lines
Seed weight
Parents
# of
RI
lines
Seed weight
3. Limited by # of RI line
4. Limited by # and density of markers
5. Limited by # of breakpoints in chromosomes
More RI populations, high-throughput marker identification and
Lines with higher number of sib-crosses before inbreeding are
In progress.
Some examples of cool and
innovative QTL mapping
Sergeeva et al., 2004
Glc6-P (glycolysis) <----->Glc1-P (starch and cellulose)
PGM
1) Good distribution in RI lines from Cvi x Ler
2) Tissue specificity of PGM activity is variable
Ler
Cvi
• Most of the QTL for intensity of staining in
distinct regions overlapped with QTL for activity
in total extracts, with similar directions.
However
Additional QTL found for individual tissues, and
primary QTL for total extract activity doesn’t
overlap with cot or root activity
This study reveals the presence and location of
global regulators and organ specific regulators of
inportant enzymatic activity
Steve Briggs, July 2004
Arabidopsis Conference
• Used level of gene expression in seedling as
mapping trait
• Identified QTL that regulate gene expression or
are upstream of gene in regulatory pathway
• Compare QTL’s from many different mapping
experiments to find genes that are regulated by
similar QTL’s and therefore may be co-regulated
and/or function together.
• This kind of approach can lead to the development
of transcriptional networks, or, if done with
Cloning genes responsible for
QTLs
Mendelize
Fine Map
Candidate gene identification, if possible
Proof of gene identity by allele swapping
Mendelizing a QTL
Create near isogenic line (NIL) to isolate a locus from one parent in the
Background of another parent.
Col
Ler
NIL
F2 from a
NIL x Col cross
3: 1-10
1: 15-18
1-10
15-25
15-18
Fine Mapping
F2 from a
NIL x Col cross
3: 1-10
1: 15-18
Gene in QTL region can now be
Fine-mapped using molecular markers
by conventional methods
Candidate Gene identification (optional)
based on genome annotation and knowledge
of the genes affecting trait
Identification without a candidate
gene and Confirmation
Swap alleles of the genes between parents by:
1) Introducing allele from one parent into null allele in other parental
background
2) Introducing dominant allele into parent carrying two copies of
the recessive allele
IF NO CANDIDATE GENES KNOWN, THE ABOVE METHODS
USE LARGE REGIONS (BACs) TO CONFIRM PRESENCE
OF GENE, AND THEN IDENTIFY GENE BY USING
PROGRESSIVELY SMALLER PIECES.
Examples of cloning genes
associated with QTL
QTL for flowering time assigned by candidate gene approach
To CRY2 (blue light receptor), which was proved to be responsible
for variation in 2 ecotypes.
QTL for insect herbivory assigned by fine-mapping and candidate
Gene approach to glucosinolate processing enzyme.
3 Heading time genes identified by map-based cloning ONLY
in rice and found to correspond to known regulators of flowering in
Arabidopsis (FT and constans)
Natural Variation in Arabidopsis
ecotypes
Correlation of traits with environment and with eachother
Identification of loci controlling complex traits
marker assisted breeding
Identification of novel genes and pathways that could not be found
by forward genetic screens due to interaction, small affect or null allele
Defining the molecular nature of intra-species diversity