Download Announcements Lab next week Multiple loci: quantitative genetics

Announcements
Lect 13: Quantitative genetics II
• Exam 1
• Evolution at multiple loci
– Key posted
• Quantitative genetics
– At least 1 week for grading
– Selection gradients
– 3 generalization
• Seminars:
• Constraints on evolutionary
responses
Mon, 9 Oct, 4:10 pm, 201 Abelson
– Dr. Sean Rice, “Developing an exact, and
universal, evolutionary theory”
– Genetic variation
– Genetic correlations
Lab next week
Discussion, Discussion Reading Reports
1.Download paper of choice from
website (use link to WSULIBS)
2.Read paper
3.Write a Discussion Reading Report
• Instructions in lab manual, website
• Example on website
Multiple loci:
quantitative
genetics
Measuring Directional
Selection
Fig. 8.1
Selection Gradient, !
Selection differential
S = Xa - Xb
Xb Xa
Selection Gradient, !
1. Different measures of
fitness
A measure of the
strength of
phenotypic selection
Selection Gradient, !
Selection Gradient, !
2. Measure phenotypic value of a
trait
•
Seed number
•
Flower size
•
Mating success
Growth rate
•
Beak depth
•
•
Wing length
•
Convert absolute
fitness to relative
fitness
wrel = Wabs / Wbar
4. Calculate
regression: trait
value vs. relative
fitness
! = 0.13
Stabilizing selection – human birth weight
Disruptive selection – bimodal resources
Fitness
• Directional
Frequency
3 Modes of selection
Fitness
• Stabilizing
Frequency
Plant height
Black-bellied Seedcracker
(Pyrenestes ostrinus)
Cameroon
Fitness
• Disruptive
Frequency
Plant height
Plant height
Infants born in London from 1935 to 1946.
Generalizations
Survivors
Sedge
• Bimodal trait distribution for juveniles: lower bill width
• Feed on hard seeded and soft seeded sedge species
Generalizations
W
Phenotypic trait value
P(Survive)
2. Evolution lead to an increase population
mean fitness
Non-Surviving
• removes less fit phenotypes
1. Directional, Stabilizing selection:
decreases genetic variation
Generalizations
Genetic constraints
When the genetic system prevents or slows
adaptation
W
Phenotypic trait value
3. The rate of evolution is proportional
to the additive genetic variance
–
Lack of genetic variation
When heritability is low, response is
slow
• Fisher’s Fundamental Theorem
of Natural Selection (FFT)
Two flavors:
R = h2S
1. Lack of genetic variation
2. Genetic correlations
- Linkage disequilibrium
- Pleiotropy
Response stops!
Single locus example of pleiotropy
Genetic Correlations
• Imagine : a single locus controls inflorescence
height and flower date
Early flowering
-Loci effect more than a single phenotype
-Single locus example
Tall inflorescence
a
30
20
Short inflorescence
15
10
6
Inflorescence height
40
• Selection favors: (Fig 8.16)
25
NS
20
15
16
21
Flowering date
a
Late flowering
• Beak depth, width positively correlated
a
NS
11
Medium ground finch
Positive genetic
correlation
30
Early flowering
a
A
25
Late flowering
35
A
40
35
• Fig 8.16
A
10
6
11
16
21
Flowering date
• Natural selection cannot lead to late flowering plants
with short inflorescences
•Nor to early flowering with tall inflorescences
•
Fig 8.16
•Selection gradients relate phenotypic trait values
to relative fitness
•Selection removes less fit phenotypes
•Rate of evolution depends on S, h2 (FFT)
•Directional, Stabilizing selection
–reduces genetic variation
•Genetic constraints result from lack of genetic
variation, genetic correlations
•Genetic correlations are caused by pleiotropy
and/or linkage disequilibria
•Genetic correlations can slow response to selection
Negative genetic
correlation
Tall inflorescence
Positive genetic
correlation
Inflorescence height
A
Inflorescence height
Short inflorescence
1. Linkage disequilibria
2. Pleiotropy
40
40
35
35
AA
30
30
25
25
a
a
20
20
15
15
10
10
6
6
11
11
16
16
Flowering date
21
21