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Human Genetics > Gene Identification > Flashcards

Gene Identification Flashcards

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1
Q

General goal of linkage analysis

A

Identify marker alleles or haplotypes that are co-segregated with a disease phenotype

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2
Q

How linkage is detected

A

Determining the amount of recombination between two markers

Rarer recombination between two loci are, the closer together they are on a chromosome

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3
Q

Do linked loci segregate independently during meiosis?

A

No- they are inherited together

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4
Q

Genetic markers definition

A

DNA variants in a given population or pedigree that are linked to a given disease or trait

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5
Q

Do genetic markers associated with a trait generally cause that trait?

A

No- they generally are close to the causal genes, thus inherited together with them

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6
Q

Two major types of genetic markers

A

Variable length polymorphisms and SNPs

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7
Q

Variable length polymorphisms

A

Type of genetic marker
Characterized by long stretches of repeats
Different individuals have varying lengths of these repeats

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8
Q

Single nucleotide polymorphisms (SNPs)

A

Type of genetic marker
Characterized by 1 base difference between individuals (2 different allele possibilities at a locus: some individuals carry one, some carry another)

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9
Q

How SNP genotyping works

A

Used for already discovered SNPs
Different colored probes hybridize to different nucleotides (ex- homozygous A allele is one color, homozygous B allele is a second color, and heterozygous is a third color)
Hybridized DNA is shown on a plate: every SNP shows up as a dot on the plate
Can show up to several million SNPs on one plate
Each plate is one individual: can have multiple plates on a large plate

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10
Q

Genetic distance

A

How often two markers are separated by recombinations

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11
Q

Physical distance

A

Related to genetic distance

How many bases there are in between two markers

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12
Q

What “1 centiMorgan” refers to

A

1% recombination per generation

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13
Q

Is recombination uniformly distributed across the genome?

A

No- recombination resides primarily in “hot spots” (areas of higher recombination)

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14
Q

Recombination fraction

A

Designated as Greek letter theta
Measures degree of linkage: fraction of times two markers are separated by recombination in a pedigree
Ranges from 0 to 0.5 (in meiosis, 2 chromosomes stay together half the time)

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15
Q

What recombination fraction value (theta) is associated with linkage of two traits?

A

Two loci are said to be linked with theta is less than 0.5

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16
Q

What does a recombination fraction value (theta) of 0.5 mean?

A

Loci are segregating independently- no linkage

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17
Q

Log of the odds (LOD) score

A

Used to measure statistical significance of linkage

Higher score: linkage more likely

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18
Q

What LOD score is considered to be significant?

A

Greater than or equal to 3

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19
Q

Weaknesses of linkage analysis

A

Requires studying relatives (cannot use unrelated individuals)
Works best for rare, dominant traits (not useful for common traits)
Linkage regions are large and finding “the gene” is hard

20
Q

Do rare variants with large effects (as identified from pedigrees) underlie common genetic diseases?

A

No

21
Q

Common disease/common variant hypothesis

A

There are many variants with modest effects at higher frequency in the population that lead to common disease

22
Q

Significance- association analysis

A

Measures whether or not an association between a given SNP and disease is real

23
Q

Effect size- association analysis

A

Measures the strength of variant effect

24
Q

Power- association analysis

A

Measures the likelihood of finding a real association

25
Q

What are p values used to measure?

A

Statistical significance

26
Q

P value definition

A

Probability of observing a given association, if there is no real association (null hypothesis)

27
Q

What p value indicates that an association is statistically significant?

A

p < 0.05

28
Q

Genome-wide association studies (GWAS)

A

Testing millions of SNPs across the human genome to discover which genetic variations are associated with a given trait/disease

29
Q

Which populations GWAS tests

A

Population with given trait/disease

Population without given trait/disease

30
Q

Bonferroni correction: what it does and how it is calculated

A

Used to decrease number of false positives when testing a large number of samples
Calculated by dividing 0.05 by number of tests

31
Q

2 ways to quantify effect size

A

Odds ratio

Relative risk

32
Q

When is odds ratio used?

A

Case-control designs

33
Q

When is relative risk used?

A

Cohorts and general population samples

34
Q

Odds ratio formula

A 
a/b divided by c/d
a- cases with allele
b- controls with allele
c- cases without allele
d- controls without allele
35
Q

Relative risk formula

A 
a/(a+b) divided by c/(c+d)
a- cases with allele
b- controls with allele
c- cases without allele
d- controls without allele
36
Q

Interpretation of odds ratio

A

Used to determine how likely an individual with the risk allele is to have the specific phenotype
Bigger odds ratio: greater likelihood of having disease
Odds ratio of 2 means that person who inherits risk allele is twice as likely to develop disease

37
Q

Interpretation of relative risk

A

Relative risk = 1: no difference in risk between experimental and control group
Relative risk <1: event is less likely to occur in experimental group
Relative risk >1: event is more likely to occur in experimental group

38
Q

How to calculate absolute risk

A

Multiply population risk by relative risk

39
Q

What is GWAS useful for finding?

A

Genetic variations contributing to common complex diseases where many common SNPs are associated with small effect sizes as well as large effect size from more rare SNPs for less common conditions

40
Q

How it is possible to see the effects of all the SNPs that were not directly genotyped in a GWAS

A

Not all theoretical haplotypes for a given combination of alleles on a chromosome exist- haplotype of a given individual can be inferred

41
Q

Linkage disequilibrium

A

Non-random association of two or more alleles (in GWAS, marker allele and disease-causing allele)

42
Q

How linkage disequilibrium is measured

A

Correlation coefficient (r^2 value): value ranges between 0 and 1

0: complete equilibrium (random segregation) of two alleles
1: complete linkage disequilibrium

43
Q

Do larger or smaller sample sizes yield higher power?

A

Larger sample sizes

44
Q

Do larger or smaller effects yield higher power?

A

Larger effects

45
Q

Is power higher for SNPs with higher or lower allele frequency?

A

Higher allele frequency

46
Q

3 outcomes of low powered studies (i.e. small sample size)

A

True effects can be missed
Effect estimates can be less precise (even in the wrong direction)
Some “detected” effects can be false positives

Human Genetics (26 decks)

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