QTL as a measure

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QTL as a measure of
Molecular Phenotype
Kamal Swarup
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Gene Discovery and Functional Analysis
Laboratory - induced mutants
Forward genetic screens
Reverse genetic screens Assign a function to
all the genes using these methods ?
Redundant and lethal genes
Labour intensive mutant
screens Mutant phenotype undetected if WT allele
is weak or null
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There is yet another Resource..... Strains,
ecotypes, subspecies accumulate many more
mutations (Natural Allelic Variation) Phenotypic
variation central to evolutionary
adaptations Variation as a result of genetically
complex traits Genes that contribute to these
complex traits are called Quantitative Trait Loci
(QTLs) QTL is any locus that contributes to a
phenotype that is measured quantitatively
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Height - An example of a Quantitative Trait
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Definition..... QTLs are genes whose phenotypic
effects show a continuous range of variation in a
population and is more or less normally
distributed
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QTLs - Characteristic Features
Continuous distribution
Involvement of multiple loci (polygenic)
Effect of each can be small Environmental
effects can be large
Analysis and Mapping has been challenging
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Advances in .... Genomic Resources, Scientific
technologies Statistical software Have
made it possible to map, analyse and clone QTLs
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Quantitative Trait Locus(QTL) Mapping An
alternative approach to gene identification
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Requirements For QTL Mapping
Segregating Population F2 , F3 - easy,
quick Use is limited
Recombinant Inbred Lines (RILs) Doubled
Haploid Lines
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Recombinant Inbred Lines Parent A X Parent B
F1
True breeding or homozygous Immortal
collection Replicate experiments in different
environments Molecular Marker database can be
updated Laborious
AB
F2
F3
F8
RILs
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Doubled haploid Lines(DHL) Spontaneous
chromosome doubling of Haploid microspores in in
vitro culture Homozygosity achieved in a single
step Plants are produced in quantity in a single
step Less recombination between linked
markers Not all systems are amenable to in vitro
culture
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Prerequisites for QTL Mapping -Molecular mapping
markers to cover the genome Restriction
Fragment Length Polymorphism(RFLP)
Amplified Fragment Length Polymorphism(AFLP)
Cleaved Amplified Polymorphic Sequences(CAPS)
Simple Sequence Length Polymorphism(SSLP)
Single Nucleotide Polymorphisms(SNPs) -The
genotype at each marker locus in the segregating
population -Quantitative measure of the trait of
each line -Statistical Software Packages
(http//www.public.iastate.edu/mmalek/Qtllinks.ht
ml)
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Flow Chart explaining QTL analysis
Create a Linkage map with molecularmarkers
Parent 1
Parent 2
Recombinant Inbred Lines (RILs,F2,F3,Doubled
Haploid Lines)
Genotype with molecular markers
Analyse trait data for each line
Link trait data with marker data - Mapping
software
Trait QTL mapped at bottom of small chromosome
QTL
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Principles of QTL Mapping
Parent allele A
Parent allele B
Plant height8cm
Plant height8cm
QTL ! Allele B increases by 2.0 cm
M
Plant height10cm
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QTLs for root elongation 2,4-D sensitivity
120 Ler x Cvi RILs analysed in Arabidopsis
thaliana Seeds germinated on MS media and
transferred to MS and MS 4 x 10-8M 2,4-D
plates. Roots measured on the 4th day after
transfer.
Cvi
Ler
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QTLs for root elongation 2,4-D sensitivity
120 Ler x Cvi RILs analysed 3
QTLs identified
Ler
Ler
Cvi
Cvi
Linkage group 5
Linkage group 3
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Map Positions for Putative
2,4-D QTLs
cM
1
2
3
4
5
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2,4D2
42
60
2,4D1
78
104
2,4D3
117
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Steps towards cloning the QTL
Hurrah!
Cloning gene characterisation
Locus Identification
Fine Mapping
Broad mapping
NILs
Trait analysis QTL mapping
RILs
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The Way Forward .
Characterisation of an Individual QTL Use of
Near Isogenic Lines (NILs)
Parent A
Parent B
RILs
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Confirmation of QTL 2,4-D1
3 NILs used(Chr1,2,4,5 are like Ler)
QTL
3-13
3-14
3-15
Ler
Cvi allele decreases root elongation in 2,4-D
media at this locus
No
Yes
Yes
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Steps towards cloning the QTL
Hurrah!
Cloning gene characterisation
Locus Identification
NIL X parent, phenotype, genotype(lt1cM)
Fine Mapping
Broad mapping
NILs
Trait analysis QTL mapping
RILs
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Locus identification Candidate
genes DNA sequencing Gene expression profiling in
combination with genetic mapping data(trait
variation is due to expression differences) Repace
ment of one phenotypic variant for another Use of
Knockouts and quantitative complementation with
parental alleles (QTL-knockout interaction)
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Steps towards cloning the QTL
Hurrah!
Cloning gene characterisation
Candidate gene Knockouts Complementation
Locus Identification
NIL X parent, phenotype, genotype
Fine Mapping
Broad mapping
NILs
Trait analysis QTL mapping
RILs
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QTL analysis finds application in both plant and
animal systems
Plants
Animals
Dicots
Monocots Rice Maize Wheat
Vertebrates
Invertebrates
Mice Humans
Drosophila
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Recombinant Inbred Lines in mice
Requires 20 generations of sib-mating to reach
homozygosity Viability of the inbred strains is
reduced Maintenance can be difficult Hence, RI
families are generally small Data from other
families is combined RI lines were first
developed for mapping in mice (Taylor 1975) Over
25 mouse RI families exist Putative QTLs
confirmed by use of Congenic lines
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Trait
Gene
Molecular Basis
Complementation
Human
Cattle
Mouse
Rat
Adopted from Glazier et al 2002, Science, 298,
2345-2349
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Trait
Gene
Molecular Basis
Complementation
Tomato
Rice
Maize
Yeast
Adopted from Glazier et al 2002, Science, 298,
2345-2349
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Merits of QTL Mapping
Identification of novel genes
Where mutant approaches fail to detect
genes with phenotypic functions , QTL
mapping can help
Good alternative when mutant screening is
laborious and expensive e.g circadium rhythm
screens
Can identify New functional alleles of known
function genes e.g.Flowering time QTL,EDI was
the CRY2 gene
Natural variation studies provide insight into
the origins of plant evolution
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Limitations....
Mainly identifies loci with large effects
Less strong ones can be hard to pursue
No. of QTLs detected, their position and effects
are subjected to statistical error
Small additive effects / epistatic loci are not
detected and may require further analyses
Cloning can be challenging but not impossible
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Future Prospects

• Constant improvements of Molecular
  platforms
• New Types of genetic materials( e.g.
  Introgression
• linessmall effect QTLs can be detected)
• Advances in Bioinformatics