Quantitative genetics Flashcards

(50 cards)

1
Q

discontinuous qualitative

A

traits can be categorised into few classesc

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2
Q

continuous quantitative

A

characteristics vary along scale of measurement

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3
Q

quantitative traits

A

complex- many genetic environmental influences

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4
Q

qualitative traits

A

can be complex traits if categories reflect continuously variable underlying traits

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5
Q

discontinuous characteristics

A

exhibits only a few easily distinguished phenotypes

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6
Q

continuous characteristics

A

continuous quantitative characteristics exhibits a continuous range of phenotypes

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7
Q

normal distribution

A

create bell shaped curve

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8
Q

positively skewed distribution

A

to the right

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9
Q

polyphenism (bimodal)

A

individuals in different conditions represent different traits

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10
Q

meristic countable traits

A

determined by multiple genetic and environmental factors

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11
Q

threshold traits

A

measured by presence or absence
how susceptible you are to a disease
takes into account a risk store

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12
Q

complex traits are polygenic

A

controlled by many genes
phenotypic reflects the cumulative effects of alleles at many loci
influenced by environmental factors

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13
Q

phenotypic variance

A

total amount of variation among individuals in some trait

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14
Q

components of phenotypic variance

A

genetic variance
environmental variance

Vp=Vg+Ve (simple partitioning)

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15
Q

heritable genetic variation

A

parent offspring variation
additive genetic variance

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16
Q

non heritable genetic variation

A

genetic variation that does not contribute to parent-offspring resemblance

dominance genetic variance
epistatic variance Vi

Vg=Va+Vd+Vi +Ve

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17
Q

heritable

A

phenotypic trait differences of individual reflect genetic differences

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18
Q

inherited

A

property passed down from parent to offspring

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19
Q

narrow sense heritability

A

the proportion of phenotypic variation that contributes to the resemblance between parents and offspring.

Va/Vp

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20
Q

broad sense heritability

A

The proportion of phenotypic variation attributed to all types of genetic differences between individuals

Vg/Vp

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21
Q

how can something be genetic but not heritable

A

for example, healthy parents and diseased child

diseased parents and healthy child

22
Q

how can narrow sense heritability be measured

A

by regression
linear relationship between phenotype of offspring and phenotype of their parents

23
Q

regression

A

predicting value of one variable if the other variable value is given

24
Q

regression coefficient

A

represents the slope of the regression line, indicating how much one value changes on.

25
environmental impact on genotypes
variation due to different environments (eg more or less moist) Vp=Vg+Ve+Vge
26
why are some traits correlated (eg taller and larger feet)
could be environmental (well fed) could be genetic due to pleiotropy or linkage disequilibrium
27
correlations can reflect trade offs
trade off between seed size and number of Italian ryegrass folium multiform
28
what is pleiotropy
single locus affects expression of multiple traits
29
linkage disequilibrium
occurs when there is association between alleles at different loci not necessarily physical, but physical linkage can facilitate LD
30
linkage disequilibrium
overrepresentation of alleles frequencies of coupling and repulsion gametes eg tall and big feet inherited together
31
equation for deviation
F(AB)*F(ab)-F(Ab)*-F(ab)
32
what does complete LD look like
pleiotropy
33
recombination erodes LD
breaks up associated alleles effective at reducing linkage disequilibrium
34
single heterozygote
only one chromosome is a heterozygote, no new haplotypes are created
35
double heterozygotes
both homozygotes (AB, ab) so when recombination occurs new haplotypes are created
36
genetic interactions
genetic effects we have discussed are assigned to a single locus ( so measured independent of other loci) effects on one loci will often depend on the alleles present at another locus
37
epistasis
one gene controlling or modifying the expression of another gene masks or modifies (epistatic) gene whose effect is altered (hypostatic)
38
genetic background dependence
another locus that has an affect on the locus we focus on or more generally multi locus genotype for example affects on mutations on mice depends on the strain of mice
39
independence and interactions
genes have no effect on their own. genes contribute to regulatory networks, biochemical pathways, metabolic pathways so many opportunities for genes to interact
40
how do loci interact
in complex networks constructed from pairwise interactions (between two loci)
41
how do we identify genes causing continuous variation
locate loci that affect quantitative characteristics map quantitative trait loci (QLS) genome-wide association studies (GWAS)
42
QTL analysis
location of genome that causes different values of the trait in question does not have to be caused by differences in the coding regions of the gene (instead maybe regulatory elements) not associated with differences I proteins but rather in gene expression
43
how are QTL analysis identified
using statistical approaches testing either different genotypes have significantly different trait values (phenotypes) done using genetic markers (where alleles can be distinguished) identify causal variation linked to markers
44
genome wide association studies
identifies locus associated with that variation testing whether groups of different phenotypes have different frequencies of alleles at a locus use genotyping array data, also be done using type of marker data
45
linear model approach
can we predict a phenotype by taking into account allele frequency in an individual
46
characteristics of gwas
can be done for any measurable trait large sample sizes can be controversial
47
results of GWAS depend on what
depends on trait heritability and size effects
48
missing heritability problem
GWAS often fail to explain most variation traits due to statistical power enormous number of loci with small effect too low effect to pick up on also overestimation of heritability- usually environment plays a key role in
49
what do GWAS and QTL analysis aim to identify
specific loci associated with trait variation and characterise their effects simply want to use genomic data to predict the phenotype of an individual
50
what info do we have from previous GWAS
500K id from UK biobanks whole genome sequences correlations of around 0.65 between what we are predicting and what we are observing in phenotypic variations