Lectures 14 and 15: Mapping QTLs and Disease genes

Most traits have a complex genetic basis

No single gene shows perfect segregation with the trait

Generally, Multiple loci contribute

Environmental effects are also important

Even with a single underlying gene, can have:

incomplete penetrance, variable expressivity.

Phenocopies -- individuals showing the trait for strictly environmental reasons.

These are any trait we can measure:

Height, weight, Blood pressure, Facial features, IQ or other quantifiable behaviors

Quantitative Genetics (Chapter 27 in the book) is the branch of genetics that deals with the analysis of such complex traits. There is a very heavy use of statistics, not for the faint-of-heart! ( More info )

Can score individuals as affected / unaffected

Alternatively, if known, the appropriate underlying physiological variable can be used as a quantitative character

e.g., Blood pressure vs. hypertension (affected / normal)

In most cases, don't know underlying biochemical variables.

QTLs (Quantitative Trait loci) -- those underlying quantitative traits

DS (Disease susceptibility) genes -- those influencing an individual's susceptibility to a particular disease (e.g., heart disease, Alzheimer's). Note that DS genes are simply QTLs that influence a disease.

Each copy of allele e₄ found to increases cholesterol level by 5-10

Each copy of allele e₂ decreases cholesterol level by 15-20

e₄ e₄ -- mean age of onset 68.4 years

e₄ e- (heterozygote) mean age of onset 75.5 years

No e₄ alleles -- mean age of onset 84.3 years

Individuals with long alleles higher in Novelty seeking

More exploratory, thrill-seeking, excitable

Individuals with no long alleles lower in Novelty seeking

More deliberate, rigid, and orderly

D4DR accounts for about 10% of all genetic variance in the trait novelty seeking

High amounts of polymorphism at the DNA level

Two random humans differ by on average 20 million base pairs

These differences provide genetic (molecular) markers for mapping genes

KEY : QTLs, DS genes can be detected by looking for marker-trait associations using these markers.

Can either examine an entire family ( Family analysis ) or pairs of affected individuals ( affected sib pairs )

Here, a number of highly polymorphic marker loci are examined

Suppose a marker locus M is linked to a QTL influences the trait of interest, where

• each copy of QTL allele Q adds an amount a to the trait of interest

• each copy of QTL allele q adds zero

If the father has (say) genotype M₁Q / M₂q , then he generates the following gametes

A significant difference between offspring carrying alternative parental marker alleles implies a linked QTL.

Suppose we observe the following data in a family. The father has marker genotype M₁ M₂ while the mother has marker genotype M₂ M₃

The following trait values are seen in the offspring:

Paternal allele means

M₁ = (20 + 30)/2 = 25

M₂ = (10 + 20)/2 = 15

Maternal allele means

M₂ = (20 + 20)/2 = 20

M₃ = (30 + 10)/2 = 20

Hence, the marker appears linked to a QTL that is heterozygous in the father (e.g., Qq), but homozygous in the mother (QQ or qq).

Here the idea is to compare the number of shared maternal and paternal marker alleles in pairs of affected sibs.

Affected sibs 1 & 3 share (1/2) their marker alleles

Both share paternal marker, but have different maternal marker

If the marker is unlinked to disease, we expect, on average, 50% of marker alleles shared

If significantly more than 50% of the marker alleles are shared, this indicates linkage to a QTL.

Using sib pairs nicely controls for shared environmental effects.

22 families with a total of 159 pairs of affected sibs were examined

57% of doubly-affected sib pairs shared the same allele from their parents at a microsatellite marker D18S56.

This is significantly different from 50%, suggesting this marker is linked to a DS gene influencing depression.

Hamer (1993) examined 32 pairs of gay bothers. 22 of these shared the same marker allele from their mother (an X-lined marker in region Xq28).

freq = 22/32 = 67%, which (for this sample size) is significantly different from 50%, indicating a QTL influencing male sexual preference linked to this maker.

No such association was found in 36 pairs of lesbian sisters