VL 24 (Michael Lenhard) Flashcards
Is there a genetic
influence on variation in
a quantitative trait?
- grow different genotypes under the
same environment
–> is there phenotypic variation? - intercross individuals (e.g. large with
large and small with small)
–> do progeny phenotypes resemble
parental phenotypes?
The mean and the standard deviation can be used to describe a normal distribution
There is often no simple relationship between genotypes, phenotypes:
Francis Galton ́s quincunx:
- Nails/pins in border
- Containers in bottom
–> Funnel → balls;
Balls fall down in container - Result: normal distribution; chance of being displaced left/right = same
- Left/right extreme: always deflected left/right (less probabile)
→normal distribution if final outcome depends on number of independent decisions; each decision contributes to final outcome
* Expect: normal distribution of trait values; trait variation influenced by variation in a number of different genes (each having small/large trait allele) → random allele combinations determine
what trait expression will be
* small + large trait alleles (mostly), few: small, few: large
What is the essential difference between qualitative and quantitative traits?
gene numbers with different alleles, that contribute to phenotypic variation
Example
* P: 3 loci; homozygous
* F1: heterozygous at all 3 loci
* F2: 2^3→8 gametes for female, male; 20 intermediate; 64 → normal distribution
Result:
* 30 loci → individual loci contribution would be smaller; much closer normal distribution approximation
* = number of loci that contribute to trait variation and inversely the strength of the individual locus contribution (quantitative traits)
* Mendelian: qualitative traits; single locus with 2 alleles → huge effect on phenotypic variation
Reaction norm describes relationship between given genotype and its phenotypes in different environments
- Norm of reaction = describes phenotype range that a single genotype can give rise to under different environments
Example
* Homozygous, inbred drosophila strains→replicate same genotype
* Flies under different T
* for each T, genotype: count trait (number of abdominal bristles)
Result:
* different genotypes respond different to T; single high trait value genotype that would have highest trait value throughout all of different environments; complex interaction between genotype + environment
Determining norms of reaction:
- Difficult, laborious, as many individuals of same genotype need to be grown under different environmental conditions
- Reaction norm known for how many human traits?
→ no it is not; no way of replicating human genotypes - Plants: ability to vegetatively propagate plants by cuttings allow generation of genetically identical clones
→ clones in different environment - Plants, animals:
inbreeding → pure lines → different environments
Implications for breeding
- vary 2 different parameters (environmental quality = fertilizer amount)
- inbred maize genotypes
- measure yield
- plot reaction norms
- dense planting: under all conditions; blue outyields red → use blue
- loose planting: red crosses blue → better at higher fertilizer amount
- know for which environment type you breed (→different genotypes
performing best in one environment)
Phenotypic similarity between relatives
- Relatively easy for experimental organisms
- Studies in human
–> Very difficult to exclude environmental variation/influence
–> Preferred method:
comparing phenotypic similiarity between monozygotic – dizygotic twins
Picture
Parental generation
* Interbreed individuals with low trait values + high trait values →
trait distribution
–> Blue: same trait distribution (not heritable: parents phenotype doesn ́t predict offspring phenotype)
–> Red: lower/higher trait value distribution; heritable
–> not in humans possible
- monozygotic (identical twins) – dizygotic (fraternal twins) under same environmental conditions
- mono: two individuals are genetically identically
- di: two individuals in twin pair aren ́t not more similar than brother + sister
Phenotypic similarity between relatives:
Estimating the components of variance
- phenotype (p) = genetic influence (g) + environment (e); cant measure them; look at variation in these traits
- 2 * cov(ge) ignored (hard to measure)
Picture
* 1st mendelain law: cross 2 homozygous inbred parents
→ heterozygous, uniform F1
→ phenotypic variation in F1 without genetic basis
→ environmental influence
* larger because genetic + environmental variation contribute to trait variation
* result: genetic influence responsible for 54,5 % of phenotypic variation
The interpretation of H2
- H2 relates to given population in given environment
- H2 > 0, genetic variation plays role in generating phenotypic variation in this population, environment
- H2 = 0, doesn ́t mean that trait is inheritable, means: genetic variation doesn ́t contribute to phenotypic variation (e.g. no relevant genetic variation segregating in this population)
Narrow-sense heritability:
- Genetic variance sg2 = additive genetic variance (sa2) + dominance-dependent variance (sd2)
- Sa2 relevant for selection, breeding
- Proportion of overall phenotypic variance that is due to additive genetic variance
QTL mapping/Linkage analysis and association mapping:
- Linkage analysis + association studies rely on co-inheritance of functional polymorphisms + neighboring DNA variants
- Linkage analysis: few recombination opportunities to occur within families + pedigrees with known ancestry→low mapping resolution
- Association mapping (b, showing haplotype): historical recombination + natural genetic diversity were exploitedc→chigh-res mapping
- Linkage disequilibrium between functional locus + molecular markers = low, except for those within very short distance
QTL:
* cross parents (different phenotype) homozygous inbred lines
* F1: uniform, heterozygous
→ recombinant gametes via meiosis
* F2: gametes combined
→ F2 with phenotypic + genotypic segregation
* measure trait value (in example: height)
→ genotype them throughout whole genome; look: associations between parental alleles – trait expression
* middle: association: short homozygous for red allele; tall homozygous for blue allele
QTL (quantitative trait locus):
- Chromosomal interval carrying different alleles that influence phenotype in question
- Goal: trying to find these intervals
→ associating a parental allele in chromosomal interval with phenotypic values - Recombinant inbred lines
- repeated measurements
→ more accurate phenotype estimate for given genotype (random error should, average out from multiple measurements) - allows studying genotype x environment interactions
- only have to be genotyped once
→ for additional traits, only phenotyping required
Picture
* P=g+e
* Measurements on single individuals are problematic
* Recombinant inbred lines (RIL)
–> goal: measure multiple individuals with same genotype
→ trait estimate that is determined by this genotype
→ used for QTL
* parents → F1 → self F1 → F2
* 200 individuals from F2 selfed → progeny → pick 1 progeny and self again
* 200 inbred lines with homozygous genome; differs in genotype from other RILs
* Plant out 20 individuals → measure phenotype → phenotype estimate for genotype
* For every genotyped marker: difference between subpopulation by genotype at this position?
* 100 homozygous for red, 100 for blue allele
- Are 100 homozygous red alleles on average different in there phenotype than 100 homozygous blue lines? Yes
→ allele near marker, that influences phenotypic variation
Linkage disequilibrium
- 2^3→8 genotypes with frequencies in population
Alleles at SNP1 independet of SNP2 or are they associated with each other across the population?
- SNP1: (14,5 + 14,5 + 0,3 + 0,3)% = 29,6% mit A
- SNP2:(14,5+34,5+0,3+0,7)%=50%mitG
- 0,5*0,296 = 0,148
- AG: (14,5 + 0,3) = 14,8%→alle Werte passen in Tabelle 2 überein→SNP1 + SNP2 in linkage equilibrium; genotypes at these positions are independently distributed
Tabelle
* Observed not expected frequency →2 genotype combinations over /underrepresented
* Linkage disequilibirum between SNP2, 3 → not independent of each other in population
* Knowing SNP2 genotype → tell SNP3 genotype (98% accuracy)
e.g. physical proximity between loci
right:
* 20 possibilities for breaking chromosome + recombine it with other
→fragments = places where LD will appear = haplotypes
The length of haplotype blocks depends on the distribution of cross-over frequencyHaplotypes, linkage disequilibrium:
- Peaks → high number of crossing over events in different meiotic divisions
- Blocks between peaks→passed on generations; unrecombined
→modern genomes = mosaics of haplotype blocks derived from ancestral chromosomes +
recombined - Each population: individual genome = mosaics of haplotype blocks (each of which is present in only few different states, reshuffled + put together over generations)
- 4-6 haplotype blocks
- 1/4 or 1/6 haplotype blocks in certain genome region
Logic of association mapping:
- Chromosomes passed down many generations → meiotic events
- Each haplotype block between 3-4 different haplotypes
- Disease inducing mutation in todays generation: SNP close mutation
in haplotype block in LD with mutation → SNP far away not in LD with mutation
