Quantitative Genetics. Continuous phenotypic variation within populations- not discrete characters...
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Transcript of Quantitative Genetics. Continuous phenotypic variation within populations- not discrete characters...
![Page 1: Quantitative Genetics. Continuous phenotypic variation within populations- not discrete characters Phenotypic variation due to both genetic and environmental.](https://reader036.fdocuments.us/reader036/viewer/2022062301/56649f165503460f94c2cea1/html5/thumbnails/1.jpg)
Quantitative Genetics
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Quantitative Genetics
• Continuous phenotypic variation within populations- not discrete characters
• Phenotypic variation due to both genetic and environmental factors
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Quantitative traits are described by a frequency distribution
Figure 18-3b
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The distribution of a trait is composed of the distributions of thedifferent genotypes
Figure 18-16
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A norm of reaction is the relation between environment and phenotype
Figure 18-6
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Crosses are performed to test for heritability
Figure 18-11
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Quantitative Trait Loci (QTL):the specific loci whose allelic differences are
responsible for the genetic variation in a quantitative trait (e.g. total sleep time)
Note: QTL does not refer to the sum total of all loci that influence a particular trait, only those
loci that are functionally polymorphic (with respect to the trait of interest in a given
environment) between the parental strains or within the population. In mice, Mutagenesis and engineered KOs can artificially alter any gene, however, “natural” polymorphisms can
represent more subtle variations.
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Selection altered bristle number
Figure 18-14
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Selection increased egg production
Figure 18-15
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An experimental protocol for localizing genes
Figure 18-17
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Only a small percentage of character difference is associated withany one DNA marker
Figure 18-18
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QTL Mapping• QTL mapping: identification of chromosomal regions containing
gene(s) that correlate with measured phenotypes
• Different methods– Single-marker analysis: compares phenotypic means of different
marker genotypes – Interval mapping: estimates position of QTL between two markers
using maximum likelihood (compares null hypothesis of no QTL vs. a QTL between the markers).
– Composite Interval mapping: IM and multiple regression– Multiple QTL models
• QTL present when LOD score exceeds critical threshold– LOD = Log of the Odds = log10 (H1/H0) – often for single locus analysis, 3.0 is significant and 2.0 is
suggestive depending on sample size, number of markers, and other variables.
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Crosses are performed to test for heritability
Figure 18-11
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Generating the Backcross
Cast/EiJ x C57BL/6J
F1 x Cast/EiJ
BC1s
Backcross progeny have on average:
75% CE, 25% B6 alleles50% C/C, 50% C/B genotypes for all loci
C57BL/6J (B6)
Cast/EiJ (CE)
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Some types of detectable variation
• RFLPs (Restriction fragment length polymorphisms)
• VNTRs (Variable nucleotide tandem repeats) = minisatellites
• Microsatellites
• SNPs (Single nucleotide polymorphisms)
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LOD Scores
• Null hypothesis: assume no linkage.
• Alternative hypothesis: assume the disease (or phenotype) and the marker locus are linked.
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Mice have 20 chromosomes
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Generating the Backcross
Cast/EiJ x C57BL/6J
F1 x Cast/EiJ
BC1s
C57BL/6J (B6)
Cast/EiJ (CE)
# Scored:
(21/20)
(16)
(224)
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CE
B6
CE/B6
F2 lines
CE
B6
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Genetic Map of Markers used in Analysis
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