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Maria Carlota Vaz Patto
ADONIS Workshop Oeiras, 3rd March 2009
1
Some basic conceptsLinkage map developmentLinkage map developmentQTL linkage analysisQTL linkage analysisGenetic genomics
ADONIS Workshop Oeiras, 3rd March 2009
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ADONIS Workshop Oeiras, 3rd March 2009
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That area of genetics that deals with the inheritance of characteristics that are controlled by many genes and by the inheritance of characteristics that are controlled by many genes and by the environment.Concerned with natural variation and not Concerned with natural variation and not major mutants.Quantitative traits could be controlled by one gene plus large environmental variance Quantitative traits could be controlled by one gene plus large environmental variance or several genes plus environment.Genes called polygenes or QTLGenes called polygenes or QTL(Quantitative Trait Loci).
ADONIS Workshop Oeiras, 3rd March 2009
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L1L1L2L2
L5L5L3L3
L4L4
5 loci (genes or markers):loci 1, 2, 3, and 4 have the same form (allele)locus 5 has two different forms
In diploid plant cells, two copies of each chromosome are found. In plants, polyploids are frequently found: each chromosome is present in
locus 5 has two different forms (alleles)
plants, polyploids are frequently found: each chromosome is present in more than two copies.
In a diploid plant the two homologous chromosomes are very similar but not necessarily identical in DNA sequence.
ADONIS Workshop Oeiras, 3rd March 2009
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not necessarily identical in DNA sequence.
Four diploid plantsplants
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Four diploid plantsplants
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During gamete formation each member of the allelic pair (= locus) separates from the other member to form the genetic constitution of the gamete
AA aaxP AA aax
Aa
P
F1AaAAAaA
Union of gametes at random:
Aa
A aaaAaaAaAAA
F1gametes A a
F2: 1/4AA : 1/2Aa : 1/4aa
gametes
ADONIS Workshop Oeiras, 3rd March 2009
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During gamete formation the segregation of the alleles of one allelic pair (= locus / gene) is independent of the
This is the basic concept to understand segregation of the alleles of another allelic pair (= locus /
gene)understand linkage relationships among AABB aabbxP
Union of gametes at random:among genes, among markers, and among
AABB aabbx
AaBb
P
F1AaBbAaBBAABbAABBAB
abaBAbAB
and among genes and markers and to construct
AaBb
AbAB aB
F1
F1gametes ab aabbaaBbAabbAaBbab
aaBbaaBBAaBbAaBBaB
AabbAaBbAabbAABbAb
to construct linkage maps
AbAB aBgametes ab aabbaaBbAabbAaBbab
F2: 9A_B_ : 3A_bb : 3aaB_ : 1aabb
ADONIS Workshop Oeiras, 3rd March 2009
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o Involves the exchange of exchange of pieces between homologous chromosomes
o It occurs during the meiosis I, when the two when the two homologous chromosomes are aligned
ADONIS Workshop Oeiras, 3rd March 2009
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Genes located in the same chromosome tend to be inherited together, and will not assort to be inherited together, and will not assort independentlyThe closer the location of the genes the The closer the location of the genes the higher the chance that they will be transmitted together to the progenytogether to the progenyThe chance of recombination is not homogeneous along the chromosomes; in homogeneous along the chromosomes; in some regions it happens more frequently than in other regions
ADONIS Workshop Oeiras, 3rd March 2009
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Definition: One of two or more alternate forms (alleles) of a chromosomal locus that differ in (alleles) of a chromosomal locus that differ in nucleotide sequence or have variable numbers of repeated nucleotide units
To know whether a chromosomal locus is To know whether a chromosomal locus is polymorphic, we need to compare genomes (for example, the two haploid genomes of a diploid organism or the two diploid genomes of two diploid organism or the two diploid genomes of two diploid organisms)DNA-polymorphisms can be found in coding and in non-coding regionsnon-coding regionsDNA-marker techniques are tools which allow to detect DNA-polymorphisms in genomes
ADONIS Workshop Oeiras, 3rd March 2009
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The transmission of DNA-markers follows Mendel s laws
During gamete formation the segregation of the alleles of one During gamete formation the segregation of the alleles of one allelic pair (=locus) is usually independent of the segregation of the alleles of another allelic pair (=locus)
Different DNA-marker forms at a given locus are also called alleles
A diploid plant posses two DNA-marker alleles at a given locusA diploid plant posses two DNA-marker alleles at a given locusA plant can be homozygous for one locus and heterozygous for another locus in the neighborhood
For nuclear DNA-markers: one DNA-marker allele was inherited from the father and another allele was inherited from the motherfrom the father and another allele was inherited from the mother
If one trait is influenced by more than one gene, DNA-markers in different genomic loci will show association with the trait
ADONIS Workshop Oeiras, 3rd March 2009
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in different genomic loci will show association with the trait
Involves:The development of a linkage mapThe development of a linkage map
Look for associations between trait variation and the presence or absence variation and the presence or absence of a particular molecular marker allele.
ADONIS Workshop Oeiras, 3rd March 2009
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ADONIS Workshop Oeiras, 3rd March 2009
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Definition: Graphical representation of the genome of an organism
A linear map of the relative positions of genes, molecular markers and phenotypic markers along a chromosome. Distances are established by linkage chromosome. Distances are established by linkage analysis, which determines the frequency at which two loci become separated during chromosomal recombinationrecombination
A genetic linkage map can be compared to a road map. Just as mile posts guide the motorist along a linear highway, molecular tools enable the geneticist to linear highway, molecular tools enable the geneticist to establish specific genetic markers (DNA-markers) at defined places along each linear chromosome.
ADONIS Workshop Oeiras, 3rd March 2009
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A mapping populationBackcross population (BC)Backcross population (BC)F2 populationDouble haploid (DH) populationRecombinant Inbred (RI) populationRecombinant Inbred (RI) populationNear-Isogenic (NI) population
Hundreds to thousands of DNA-Hundreds to thousands of DNA-markers
Appropriate software
ADONIS Workshop Oeiras, 3rd March 2009
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X X
Out crossingInbreeding
DH: Regenerate plants from single (haploid) pollen grains produced by the F1, and
X X
F1 Cross-pollinator (CP)Constructed by selfing the
produced by the F1, and inducing chromosome doubling
X X
F2 Backcross (BC) Crossing the F1 hybrid to one of the parents (the recurrent parent). Only alleles derived
by selfing the F1 hybrid
(the recurrent parent). Only alleles derived from the donor (non-recurrent parent) segregate
NIL: The F1 hybrid is
Recombinant Inbred (RI) The progeny of an F2 cross are self-pollinated during several generations, by applying single-seed-descent
NIL: The F1 hybrid is backcrossed to one of the parents (the recurrent parent) for various generations
ADONIS Workshop Oeiras, 3rd March 2009
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seed-descent
1.Detection of polymorphic loci in segregating populationpopulation2.Segregation analysis3.Calculate all linkages among pairs of loci (pair wise recombination frequencies, LOD Scores)wise recombination frequencies, LOD Scores)4.Group all loci that have at least one significant linkage with another member of the group linkage with another member of the group (establishment of linkage groups)5.Obtain with a highly probable order with a few 5.Obtain with a highly probable order with a few markers6.Sequentially add markers to this group until all of them are mapped and calculate map
ADONIS Workshop Oeiras, 3rd March 2009
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all of them are mapped and calculate map distances
(aa) (ab) (bb)(aa) (ab) (bb)
(a-) (b-)
ADONIS Workshop Oeiras, 3rd March 2009
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Check for deviation from expected segregation (X2 test) EO 2
2
E
EO2
O: observed frequency
E: Expected frequency
ADONIS Workshop Oeiras, 3rd March 2009
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F2 population
ADONIS Workshop Oeiras, 3rd March 2009
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A
A
A
A
B
B
B
b¼
A AB b¼
¼B
b
b
b
a
a
a
a
¼
¼b
Recombination fraction = r = # recombinant gametes/Total # gametes
0» r » 0.5
ADONIS Workshop Oeiras, 3rd March 2009
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¼ ABA B
¼ Ab
¼ aBa b
¼ aB
¼ ab
ADONIS Workshop Oeiras, 3rd March 2009
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½ (1-r)ABr = 0.30
35
r = 0
50A B
½r Ab
½r aB
35
15
15
50
0
0a b½r aB
½ (1-r)abr
15
35
0
50r 35
N = 100
50
N = 100N = 100 N = 100
ADONIS Workshop Oeiras, 3rd March 2009
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Generic name of statistical approach in which one aims to find the parameter value (the value of r in our case) that maximizes the likelihood of of r in our case) that maximizes the likelihood of the dataThe likelihood ratio is the ratio between the The likelihood ratio is the ratio between the likelihood of r taking value r1 (MLE), and the likelihood of r under the null hypothesis r0 (r0 =0.5; no linkage)=0.5; no linkage)LOD Score (test of significance)
LOD values = 3.0 (1.000 times more probable that the data indicate linkage than probable that the data indicate linkage than independence)
noLinkageLikelihood
LinkageLikelihoodLOD )10(log
ADONIS Workshop Oeiras, 3rd March 2009
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noLinkageLikelihood
Define groups of markers with a high likelihood to segregate together, using the LOD scoreslikelihood to segregate together, using the LOD scoresThe most stringent the chosen LOD score is, the higher the number of linkage groups is, the higher the number of linkage groups which is formedIdeally the number of linkage groups equals the haploid chromosome number over a Ideally the number of linkage groups equals the haploid chromosome number over a wide range of LOD valuesBut if not enough markers are used a much But if not enough markers are used a much higher number of LG will be obtained
ADONIS Workshop Oeiras, 3rd March 2009
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Once we know which markers belong to the same linkage group and which is the pair-same linkage group and which is the pair-wise recombination between all of them, we can order the markers along the linkage groupgroupTo do this, we try to find the marker order that minimizes the number of crossoversthat minimizes the number of crossoversMost mapping software packages apply shortcuts to find the (almost) best order shortcuts to find the (almost) best order (MapMaker, JoinMap, Carte Blanche )
ADONIS Workshop Oeiras, 3rd March 2009
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The chance that recombination occurs between loci located in close (physical) proximity of each other is smallbetween loci located in close (physical) proximity of each other is smallThe number of crossovers between two loci can be used to estimate the map distancecan be used to estimate the map distance(centiMorgans) between themRecombination events can be recognized only the basis of haplotypes, and Recombination events can be recognized only the basis of haplotypes, and haplotypes can only be known or estimated when relatives are compared, estimated when relatives are compared, linkage analysis requires the analysis of families (= mapping populations)
ADONIS Workshop Oeiras, 3rd March 2009
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r is not the optimal parameter for map constructionconstruction
r tends to a maximum of 0.5recombination is not additive, double recombinations are not consideredrecombinations are not considered
INTERFERENCE: When a crossover occurs, it is less probable that another one will occur at the same region of the that another one will occur at the same region of the chromosome.
ADONIS Workshop Oeiras, 3rd March 2009
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Functions that convert recombination fractions into genetic distancesfractions into genetic distances
Haldane: assumes no interferenceKosambi: includes some degree of interferenceinterference
Distance unit: CENTIMORGAN (cM)1 cM
1 % recombination1 cM
1 % recombination
ADONIS Workshop Oeiras, 3rd March 2009
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The genetic distance is only loosely related to the physical quantity of DNA (in terms of bp) between genetic markersgenetic markersThis is because recombination frequency is influenced by genetic, epigenetic, and environmental factorsby genetic, epigenetic, and environmental factorsOn the other hand, corresponding genetic markers in different taxa often show similar recombination distances, despite large differences in physical DNA distances, despite large differences in physical DNA content of the chromosomesFor example, repetitive DNA elements are relatively inert in recombination, recombination is also reduced inert in recombination, recombination is also reduced around the centromers
ADONIS Workshop Oeiras, 3rd March 2009
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H7E35M49-266 [email protected]@41.5H7E32M62-174 H7E42M50-368H7E32M55-7342.7
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H1E38M55-1125@ H7E32M62-134H1E32M55-176 H7E32M55-8937.5
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50.2H7E32M55-7342.7
H7E35M49-221 H1E38M59-44543.4H1E32M61-168@ H7E32M61-302H7E38M54-361 H7E32M55-220H7E35M49-350 H7E35M55-182H7E33M55-125 H7E42M48-404H1E42M47-288 H1E33M55-143
44.0
H1E33M55-445 H1E32M61-99H1E35M48-248@ H1E35M54-404E32M55-410/411@ H1E38M61-83H1E38M61-141@ H1E32M62-340@H1E42M50-112 H1E33M55-117H1E35M55-194 H1E35M55-259@
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H1E35M54-40554.6
H1E38M55-13659.6H1E33M55-165@64.2H7E32M61-37173.1H1E42M48-150075.8H7E32M61-37685.2H1E38M59-236@93.3H7E35M48-152 H7E38M55-8696.6H1E38M54-76 H7E42M48-60098.9
H7E42M48-11322.0H1E32M55-17824.3H1E38M54-6928.4H7E42M47-12831.0 Hordeum chilense
ADONIS Workshop Oeiras, 3rd March 2009
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ADONIS Workshop Oeiras, 3rd March 2009
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Quantitative Trait Loci-mapping (QTL-mapping) Requires a detailed linkage map (hundreds of Requires a detailed linkage map (hundreds of molecular markers), using large progenies (typically 200 or more)Requires sophisticated statistical tools (MapQTL, Requires sophisticated statistical tools (MapQTL, QTLCartographer, PLABQTL, ..)
Linkage Disequilibrium mappingUses natural populations to map traits by means of Uses natural populations to map traits by means of association analysisHas the potential to identify a single polymorphism within a gene that is responsible for the difference in within a gene that is responsible for the difference in the phenotype
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Require the following 3 data files:Map positions of markersMap positions of markersGenotypes for all individuals in population for these markersTrait data for all genotypes (variation Trait data for all genotypes (variation for the trait in the segregating population)population)
(appropriate statistical tools)
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QTL-mapping tries to identify simultaneously the chromosomal location of all the genetic factors affecting the traitaffecting the traitIn a QTL analysis we infer the QTL genotypes in order to estimate the QTL effects and locations from order to estimate the QTL effects and locations from associations with known markersA QTL is described by
Its chromosomal locationIts chromosomal locationThe magnitude of its phenotypic effectThe effect of gene dosage at the locus (add, dom...)Its interactions with other QTLs (epistasis)
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Single Marker Analysis
Genetic map
* * * * ** * * * *
* * *
* *
*Initial data exploration
Non parametric test (robust to violations of normality in phenotypic data)
Tests for differences in the means of the genetic marker classes
Rough estimation of the location of a QTL and it is not possible to distinguish between size of a QTL effect and it position
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Simple Interval Mapping
Genetic map
Requires a linkage map
Based on the maximum likelihood estimates. Intervals between adjacent markers Based on the maximum likelihood estimates. Intervals between adjacent markers along a chromosome are scanned and the LOD of there being one versus no QTL at a particular point is estimated
A LOD-profile is constructed along the chromosome, and the maximum in this A LOD-profile is constructed along the chromosome, and the maximum in this profile which exceed a specified significance level, indicate likely sites of a QTL
Precision and power are increased by the use of extra information from a second marker, but the effect of other QTLs present in the genome is neglected
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marker, but the effect of other QTLs present in the genome is neglected
Multiple Composite Interval Mapping
Genetic map
Markers located nearby putative QTLs identified by e.g. IM, are used as co-factors in an approximate multiple-QTL model. At each testing point the factors in an approximate multiple-QTL model. At each testing point the effect of one or more co-factors is included
By entering QTLs identified by IM (with the biggest effects) as co-factors, the effects of these QTLs is absorbed, increasing the power to identify additional effects of these QTLs is absorbed, increasing the power to identify additional QTLs
The most used method at present
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The most used method at present
Example:The genetics and mechanism of avoidance of rust mechanism of avoidance of rust infection in Hordeum chilense
Spore depositionSpore depositionSpore depositionGerminationAppressorium formation
Spore depositionGerminationAppressorium formationStoma penetrationContact with plant cellsHaustorium formation
Stoma penetrationContact with plant cellsHaustorium formationHaustorium formationColonisationSporulation
Haustorium formationColonisationSporulation
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Poor stoma recognitionPoor stoma recognition
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% Germ tube/stoma encounters % Germ tube/stoma encounters without appressorium formation
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Germ tube / stoma encounters without appressorium formation (%) without appressorium formation (%) by P. hordei on Hordeum chilense
H47 90.7
H7 79.7
H1 24.6
H304 14.6
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Germ tube / stoma encounters without appressorium formation (%) without appressorium formation (%) by P. hordei on Hordeum chilense
H47 90.7
H7 79.7
H1 24.6
H304 14.6
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ExampleExampleF2 population (H1xH7)
Avoidance level20
25
N of
F2 pop. H1 % germ tube/stoma
encounters without appressorium 5
10
15
N ofplants
H7(94%)
F2 pop. (100 pl.)
H7
appressorium formation 0.00 25.00 50.00 75.00 100.00
Avoidance level
5
H1(23%)
QTL mapping - continuous segregation (polygenic inheritance) (polygenic inheritance) - h2
b avoidance=0.6
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QTL analysis resultsQTL analysis results
H1E32M62-3070
H1E42M48-17811
1
0
2
4
6
H1E32M62-4070H7E35M49-1236H7E32M55-322 H7E38M54-2219E32M61-328/329 H7E42M48-8011
qa
3'
0
2
4
6
8
H1E38M61-1790H1E38M54-1813
H1E42M47-3529qa
voi3
5
0
2
4
6
8
qavoid1 qavoid2 qavoid3
H1E42M48-17811
H1E42M48-13019
H7E38M54-25924
H7E38M59-50031
H7E32M62-22438E32M55-410/41143E35M49-113/11444H7E38M55-40247
0
2
4
6
E32M61-328/329 H7E42M48-8011H7E35M48-15812H7E32M62-30015H7E35M49-17817H7E42M48-33820
H7E42M50-15630H7E35M55-27833
H7E42M50-43540
E42M48-430/43247
qavoi2
0
2
4
6
8
H1E38M61-33013
H1E42M47-10328
H1E38M59-45041
H1E42M50-8248
qavo
i30
2
4
6
8
qavoi1
qavoi2H7E38M55-40247
H1E32M61-20557H1E35M48-32860
H1E32M55-23867H1E42M50-44068H1E32M61-24573
H7E38M59-25281E42M48-650/70083H1E32M62-25285
qavoi1
4
6
E42M48-430/43247
H7E42M48-34454
H7E35M54-24059H7E35M54-22262
H7E33M55-34077
qavoi2
0
2
4
6
8
H1E42M50-8248
H1E35M55-10055
H1E35M54-18260H1E38M59-25064
H1E42M48-13370H1E33M55-35271
qavo
i30
2
4
6
8
qavoi3
- polygenic inheritance
E42M48-650/70083H1E32M62-25285
H7E38M55-1150101
qavoi1
qavoi2
0
2
4
6
8
qavo
i30
2
4
6
8
% germ tube/stoma encounters without appressorium formation
- polygenic inheritance
- In total, 63% phenotypic variation explained- no interaction between QTLs, only additive effects
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- no interaction between QTLs, only additive effects
Large Confidence intervals on locationConfidence intervals on QTL position large; Confidence intervals on QTL position large; seldom less than 5cM, often >30cMDue to lack of recombinationDue to lack of recombination
Multiple tests: Type I and II errorsLack of statistical powerLack of statistical powerBiases (position, QTL number, effect)Multiple QTLMultiple QTL
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Coarse mapping using markers in segregating populationssegregating populationsFine mapping using Substitution Lines or NILsIdentifying possible candidate genesIdentifying possible candidate genesPositional cloning ..
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Parents A B
Generation Procedure
PHT[cm]Marker
# 1 2 3 4 5 .. M Laboratory
210190203159
1 B B H H A .. A 2 H A H A A .. H 3 B B H H H .. A 4 H H B B B .. H
Laboratory
F1
Field
159206. .
4 H H B B B .. H 5 H B H H A .. B . . . . . . . . . . . . . . . .
Laboratory
F2171
. . . . . . . . N A H H H A .. A
LOD score PHT
Office
F2:3
Alternatives: BC1, RIL, DHL
LOD score
Office
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Alternatives: BC1, RIL, DHL
Chromosome 1
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Jansen and Nap (2001, TIGs 17: 388)Combines QTL and transcriptome Combines QTL and transcriptome analysis
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Raise a QTL mapping population (RILs, DHLs etc)(RILs, DHLs etc)Genotype markersMeasure phenotypic traitsTake samples of mRNA for transcript Take samples of mRNA for transcript analysis
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For trait(s), locate phenotypic QTL ; pQTL, as beforepQTL, as beforeFor transcriptome data, identify sets of co-regulated genes or even individual genes whose expression varies genes whose expression varies across populationLocate these as expression QTLs ; Locate these as expression QTLs ; eQTL
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Correlate locations of both type of QTLQTLCis and trans acting eQTLLink to candidate genes
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The only important thing is to narrow down the QTL interval (no need to down the QTL interval (no need to know what they really are )
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Use linkage map to select DNA-marker loci linked to the trait of interest
Select identifiable marker variants (alleles) associated to non-identifiable favorable variants of the genes of interestfavorable variants of the genes of interest
First in the population used for linkage mapping (straightforward)Then in unrelated plant materials and in the whole population (less straightforward, sometimes impossible)
Depending on the relationship between the marker allele and the gene, Depending on the relationship between the marker allele and the gene, perform MAS:
the DNA-marker is located within the gene of interest. By following the inheritance of the marker alleles we follow the inheritance of the gene allelesthe marker is in linkage disequilibrium (LD) with the gene of interest throughout the whole population. By following the inheritance of the marker throughout the whole population. By following the inheritance of the marker alleles, we can make a very good prediction of the inheritance of the gene allelesThe marker is in linkage equilibrium (LE) with the gene of interest throughout the whole population. By following the inheritance of the marker alleles, we cannot make any prediction of the inheritance of the gene allelescannot make any prediction of the inheritance of the gene alleles
Identify sub-populations in which LD exist
Forget about MAS until markers which are more closely linked are identified
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