Complex Traits Flashcards

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1
Q

Simple Trait (Mendelian)

A

one gene has one distinct biological effect; equal risk for everyone with the mutation

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2
Q

Complex Trait

A

variations in multiple genes contribute to a single effect; individuals can have different levels of risk

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3
Q

Is red/green colorblindness simple or complex?

A

simple (X-linked)

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4
Q

Examples of complex traits?

A

hair color, litter size, breast cancer development

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5
Q

Polygenic Trait

A

trait influenced by the effects of more than one gene; many alleles each with a small effect that are subject to environmental factors
ex: susceptibility to disease (heart disease, obesity)

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6
Q

Multi-Locus Traits

A

alleles at a few loci interact to determine phenotype with no ennvironmental effect
ex: coat color

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7
Q

Oligogenic Trait

A

several alleles interact to determine phenotype, subject to overall g3enetics and environmental effects
ex: milk yield

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8
Q

Can you determine whether a complex trait is polygenic, multi-locus, or oligogenic?

A

Not unless you know the alleles that underlie its expression

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9
Q

Complex Traits and Variable Expression

A

Complex traits are ALWAYS variably expressed; can result in different phenotypes or discrete difference in expression
ex: height; osteoporosis in horse breeds (which joints are affected)

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10
Q

Overall Genetic Risk

A

coombination of multiple risk alleles, which can vary between and within groups resulting in different expression and different overall risk

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11
Q

Examples of traits with Multiple Risk Alleles

A

hip dysplasia in dogs, osteochondrosis in horses

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12
Q

Role of the Enivronment

A

diet/nutrition, exercise, exposure to toxins, trauma, biomechanics, hormones, infectious disease

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13
Q

Linkage Analysis

A

looking for haplotypes that are shared by affected individuals, not unaffected individuals, in order to narrowdown our region of interest

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14
Q

Are linkage studies more useful for simple or complex traits?

A

simple (Mendelian), or Mendelian-like, or family

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15
Q

Why do we use large unrelated populations in GWAS?

A

we need to limit false positives; difficult to distinguish what alleles you share because you are related and what alleles you share because you are affected

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16
Q

Genome-Wide Association Studies (GWAS)

A

look for a statistical association between allele frequency and trait/disease of interest in a large population of unrelated individuals

17
Q

3 Steps of Linkage Analysis

A
  1. Identify loci with alleles shared by affected individuals
  2. Eliminate loci that also appear in unaffected individuals
  3. Boom, you have your loci of interest
18
Q

Most important step for a good GWAS?

A

Accurate Phenotypes!!!

19
Q

Linkage Disequilibrium

A

the idea that markers that are close together are more likely to continue to be inherited together than those that are far apart

20
Q

Linkage Disequilibrium Diagram

A

use lots of known nearby SNPs in hopes of finding variants close by

21
Q

Manhattan Plots

A

how to visualize GWAS and see the difference in allele frequency between cases and controls (if anything is misphenotyped, your results are completely useless)

plots chromosomal position vs. statistical significance

22
Q

Is segregation analysis a perfect solution in complex traits?

A

No, each locus more than likely only accounts for a small amount of variability in the trait

23
Q

Coat Color as a Multi-Locus Trait

A

individual loci that affetc color can have Mendelian inheritance when considered alone, but it is truly the interaction of multiple loci that determines phenotype

24
Q

Horse Coat Color: Grey (STX17)

A

trumps ALL other color loci - a big G means the horse WILL be grey

25
Q

Horse Coat Color: Extension locus (MCR1)

A

responsible for the production of eumelanin (black) and pheomelanin (red)

26
Q

Horse Coat Color: Agouti locus (ASIP)

A

determines distribution of black hair, only in presence of a big E from the extension locus

27
Q

Do all variants found via GWAS explain all the variation in a trait?

A

NO, so many to find and there’s still environmental factors!
ex: human height - 10 genes found so far but only explain ~30% of human height variance