S1: W3 (Prof. Kelsey) Flashcards
1
Q
Types of heterozygosity? (2)
A
• Observed heterozygosity.
• Expected heterozygosity.
2
Q
Observed heterozygosity?
A
= alleles observed in the population (polymorphic).
3
Q
Expected heterozygosity?
A
= uses the HWE (2pq).
4
Q
Population?
A
= group of individuals that interbreed
5
Q
Population properties? (2)
A
• Density.
• Dispersion.
6
Q
Density?
A
= number of individuals in a given area.
7
Q
Dispersion?
A
= pattern of the distribution of individuals in a population.
8
Q
Types of dispersion? (3)
A
• Clumped.
• Spaced.
• Random.
9
Q
Metapopulation structure?
A
= population of subpopulations/patches.
10
Q
2 things to consider when talking about metapopulation structure?
A
• Patch.
• Patch size.
11
Q
Two pressures that play a large role in dispersion?
A
• Gene flow.
• Drift.
12
Q
What does the level of population differentiation depend on? (2)
A
• Gene flow.
• Drift.
13
Q
Consequences of metapopulations? (2)
A
• Bottlenecks.
• Odd patterns of genetic diversity & differentiation.
14
Q
What do you mean by odd patterns of genetic diversity?
A
We mean that genetic diversity is high or low.
15
Q
Eg of Odd patterns of genetic diversity & differentiation?
A
Guppies
- downstream guppies have low genetic differentiation but high genetic diversity due to downstream flow.
16
Q
Genetic diversity vs Gentic differentiation?
A
● Genetic diversity
= number of alleles.
● Genetic differentiation
= comparison between composition of alleles in populations.
17
Q
Causes of population differentiation? (3)
A
• Reduced gene flow.
• Local adaptation (slxn).
• Vicariance (geographic isolation).
18
Q
Why do we care about population differentiation? (3)
A
• Conservation.
• Population divergence.
• Evolution.
19
Q
How do we measure population differentiation?
A
By estimating genetic diversity & looking at how it’s distributed (variation = heterozygosity).
20
Q
Why do populations diverge? (4)
A
• Migration of individuals.
• Local adaptation (slxn).
• Habitat fragmentation.
• Limited dispersal abilities & philopatry.
21
Q
Philopatry?
A
= the tendency to go back to a specific area habitually.
22
Q
Eg of philopatry?
A
Salamanders going back to ponds that they were born in.
23
Q
Indications of subpopulations in data?
A
Via the Wahlund effect.
24
Q
Wahlund effect attributes? (3)
A
• Reduced heterozygosity due to structure of data.
• Both subpopulations in HWE.
• Two or more populations have different allele frequencies, but are in HWE.
25
Why care about subdivisions? (3)
• Gender diversity.
• Conservation.
• Range of trait/behaviour sampling.
26
Eg of Consersation in Importance of subdivisions?
Erica vertiallote.
- brought back at the brink of extinction.
27
Key part of subpopulation genetic differentiation?
Gene flow.
28
How do alleles/genes move?
Dispersal.
29
Dispersal?
= movement of individuals between discrete populations/locations.
30
Dispersal attributes? (3)
• Disperse to share alleles.
• Ofen good intentions, but not always a successful endeavor.
• Surrogate for gene flow.
31
Eg of Dispersion?
Calopteryx splendens
- discriminate against immigrant females & kill them.
32
Migration?
= the periodic movement to & from a geographic area.
33
Migration attributes? (2)
• Doesn't contribute to gene flow/movement of alleles.
• Eg is Monarch butterflies.
34
Dispersal & Migration attributes? (2)
• Both precede gene flow.
• Neither result in gene flow until reproduction takes place.
35
Eg that shows why it matters how/when alleles are shared?
Malaria mosquitoes.
36
Barriers to dispersal & gene flow? (2)
• Man-made.
• Natural.
37
Egs of Man-made barriers? (3)
• Roads.
• Farms.
• Turbines.
38
Egs of Natural barriers? (5)
• Mountains.
• Rivers.
• Salinity.
• Nutrient gradients.
• Ocean upwelling.
39
Interspecific interactions?
= where organisms rely on each other to disperse alleles (for gene flow) through dispersal mechanisms, host-parasite interactions & hybridization.
40
Host-parasite interactions attributes? (2)
• Host dispersal to avoid infection.
• Parasites also manipulate host dispersal.
41
Eg of Host dispersal to avoid infection?
Cliff swallows
- will abandon a colony to avoid parasites.
42
Eg of Parasites also manipulating host dispersal?
Fire ants.
- Fungi took over a fire ant (no a zombie) to move towards an ideal condition for fungal growth.
43
Implications of host-parasite interactions for evolution? (2)
• Affects gene flow/dispersal of alleles.
• Study protein changes in cells that alter behaviour.
44
Eg of Implications of host-parasite interactions?
Toxoplasma gondii (cats & rats).
45
Hybridization attributes? (4)
• On a continuum.
• Can lead to unique evolutionary lineages.
• Can lead to divergence.
• Can lead to homogenization of species.
46
Lay out Hybridization continuum for me? (3)
● Left side
= species divergence.
● Middle
= maintenance of hybrid swarm.
● Right side
= species homogenization.
47
How to measure Hybridization?
By measuring introgression.
48
Introgression?
= movement of genes from one species to another by recurrent/repeated backcrossing of a hybrid to parent species.
49
Backcrossing?
= crossing of a hybrid with one of its parents or an individual genetically similar to its parent, to achieve offspring with a genetic identity closer to that of the parent.
50
Eg of introgression?
Finches.
- Bill depth changes due to introgression of G. fortis & G. fuliginosa finches on Island Daphne Major.
51
Subsume adaptively radiated taxa?
= where a generation of genetic diversity enables rapid evolutionary change in new environments.
52
What causes radiations in subsume adaptively radiated taxa?
Gene duplications.
53
Eg of Subsume adaptively radiated taxa?
Cichlids.
- More on the homogenous side of the Hybridization continuum.
54
Why is experimental design important? (2)
• Develop an efficient way to test a hypothesis.
• Ensures a conclusion due to a real pattern & not researcher error.
55
Steps for testing ideas? (5)
• Resesrch question & hypothesis.
• Experimental approaches.
• Marker choice.
• Sampling.
• Data analysis.
56
List the experimental approaches? (2)
• Observational.
• Experimental.
57
Observational approach attributes? (2)
• Use natural variation to test for correlation between variables.
• Infer cause-effect relationship.
58
Eg of Observational approach?
Do sable horn curves differ between sexes?
- You would observe the difference in males & females, and see whether it gives males a sexually selective advantage.
59
Experimental approach attribute?
Manipulate one variable in a system to measure effects on other variables.
60
Eg of Experimental approach?
Alter predator context/content to test for selection pressure on guppies.
61
Marker choice attributes? (3)
• Links back to your question (What scale?).
• Inheritance patterns (eg nDNA; mtDNA; cpDNA).
• Variability of marker.
62
How to quantify genetic diversity? (2)
• Based on the number of variants.
• Based on the frequency of variants.
63
Based on the number of variants attributes? (4)
• Polymorphism or rate of polymorphism (Pj).
• Proportion of polymorphic loci.
• Richness of allelic variants (A).
• Average no. of alleles per locus.
64
Based on frequency of variants attributes? (2)
• Effective no. of alleles (Ae).
• Average expected heterozygosity (He; Nei's genetic diversity).
65
Importance of quantifying genetic diversity?
Helps in estimating composition of alleles in the population (= diversity) [using microsatellites].
66
Sampling attributes? (5)
• How many individuals do you need to sample?
• How many populations do you need to visit?
• Who?
• Where?
• What tissue?
67
Data analysis components? (2)
• Basic morphologies of microsatellites.
• Genalex files.
68
Basic morphologies of microsatellites attributes? (3)
• Translate gel to chromatographs.
• 1 peak (1 gel band) = homozygous.
• 2 peaks of similar same peak height = heterozygous.
69
Genalex files attributes? (2)
• Chromatograph to table.
• Eg: 322 to 324 = heterozygous.
70
Ways to test for population differentiation using molecular data? (4)
• Non a prior approach.
• Individual-based analyses.
• Multi-variate statistics.
• TESS & Geneland.
71
Individual-based analyses?
= used to test for structure in your dataset.
72
Multi-variate statistics kinds? (2)
• PCA.
• MDS.
73
Multi-variate statistics attributes? (2)
• Qualitative.
• Only shows whether data is clustered or not.
74
TESS & Geneland?
= helps you incorporate geographic data, therefore helping you to relate species based on geographic regions.
75
Thing to note about the methods for testing population differentiation?
They require careful sampling to reduce potential biases in data.
76
How to estimate population differentiation? (2)
• Direct measures.
• Indirect measures.
77
Direct measures of estimating population differentiation? (3)
• Mark recapture.
• Radio transmitters.
• Parentage analyses.
78
Pro of Direct measures to estimate population differentiation?
Provides direct evidence of dispersal.
79
Cons of direct measures of estimate population differentiation? (4)
• Expensive.
• Time consuming.
• Need at least 1 parent.
• No evidence of gene flow.
80
Indirect measures to estimate population differentiation? (4)
• Non a priori approach.
• Individual-based analyses.
• Multi-variate statistics.
• TESS & Geneland.
81
3 things that the indirect measures to estimate population differentiation fall under?
• Assignment tests.
• Nei's genetic distance.
• F (ST).
82
Assignment tests?
= where individuals are allocated in a group due to genotypic similarities.
83
Assignment tests attributes? (3)
• Based on allele frequencies.
• We try to achieve HWE with this by allocating individuals with similar genotypes into a group to achieve HWE within that group.
• Enables clusters to be in HWE.
84
Aim of Assignment tests?
To understand population structure.
85
Structure file things to look for? (4)
• Abo A205; A205 = individual.
• 2 rows/individual.
• Abo L74, L87 = loci.
• Loci with both homozygous & heterozygous information is informative + polymorphic locus.
86
Why 2 rows/individual?
It's because you're dealing with diploids.
87
Nei's genetic distance for population differentiation?
= genetic distance is based on allele frequencies.
88
Structure graph attributes? (3)
• Read from left to right.
• Has individual bars.
• HWE is violated & we're trying to figure out whether it's because of hybrids, backcrossing or gene flow.
89
Why are structure bars important? (3)
• Help us figure out where individuals are from.
•
•
90
Admixture/Admixed individuals?
= individuals that are either hybrids, backcrossed individuals or as a result of gene flow.
91
Eg of structure bar?
Zebra population structure.
92
Lorenzen et al. 2008 summary? (3)
• Speaks on zebra population structure.
• k = 2 means 2 populations.
• k = 3 means 3 populations.
• k = 4 means 4 populations.
93
Nei's genetic distance (D) steps? (2)
● Know I.
● Calculate D.
94
D equation?
D = -ln I
95
I? (2)
• Nei's estimate of similarity.
• Based on frequency of alleles in two or more populations.
96
D range?
0 –> infinity
97
D approaches zero? (2)
• I approaches 1.
• 2 populations are similar.
98
D approaches infinity? (2)
• I approaches zero.
• 2 populations don't share alleles.
99
Important thing to note regarding Nei's genetic distance (D)?
This is different from genetic distance calculated with MEGA! It is based on allele frequencies NOT sequence comparisons.
100
Factors affecting heterozygosity (F(ST))? (2)
• Drift or NS.
• Inbreeding.
101
F-statistics attributes? (2)
• Quantification of the genetic variation in metapopulations (population structure).
• Measure the heterozygosity (genetic variation) deviation from HWE using 3 different measures of H.
102
F(ST) attributes? (2)
• Identifies population differentiation.
• Range: 0 - 1.
103
How to partition variation?
Combine different sources of reduction in expected heterozygosity into one equation:
1 – F(IT) = (1–FST)(1–FIS)
104
1–FIT?
= overall deviation from HW expectations.
105
1–FST?
= deviation due to subpopulation differentiation.
106
1–FIS?
= deviation due to inbreeding within a population.
107
Equation that partitions variation?
= a means to characterize evolutionary processes acting on a population.
108
Evolutionary processes for FST? (2)
• Selection.
• Gene flow.
109
Evolutionary processes for FIS? (2)
• Random & Non-random mating.
• Inbreeding.
110
Estimating heterozygosity?
= partition variation to the total metapopulation (HT), subpopulation (HS), individuals (HI).
111
HT?
= expected heterozygosity of total population level.
112
HS?
= expected heterozygosity of subpopulation level.
113
HI?
= observed heterozygosity for each subpopulation.
114
How to estimate heterozygosity? (4)
• 2 allele model.
• 2pq = observed & expected heterozygosity.
• HT = average expected heterozygosity in total metapopulation from HWE.
• 2pq –> mean p & mean q across all subpopulations.
115
How does F-statistics relate to heterozygosity?
Via:
FIT = (HT–HI)/HT
116
HT attributes? (2)
• Average Ho.
• p1q1 + p2q2
117
FIS equation?
FIS = (HS–HI)/HS
118
FIS large values (closer to 1)? (3)
• Lots of inbreeding.
• Selfing plants.
• Small animal populations of related individuals.
119
FIS smaller values (& negative values)?
Outcrossing.
120
FST equation?
FST = (HT–HS)/HT
121
FST?
= reduction in heterozygosity due to population structure.
122
HT in FST equation?
= variation between populations.
123
HS in FST equation?
= variation within population.
124
FST = 1? (2)
• High variation between populations (100%).
• No variation within populations (0%).
125
FST = 0? (2)
• No variation between populations (0%).
• High variation within populations (100%).
126
FST = 0.11? (2)
• Variation between populations (11%).
• Variation within populations (89%).
127
Causes of low FST? (3)
• Sampling.
• Markers used.
• Taxonomic relatedness.
128
In Willow leaf beetle, you're given following data/table:
FST in different river drainage = 0.04.
FST in same river drainage = 0.02.
Interpretations? (3)
• Gene flow occurs at short distance.
• Nearby subpopulations are mating with each other.
• Mating is not happening often between beetles at different river drainages.
129
Types of F-statistics? (2)
• Pairwise F-statistics.
• Global F-statistics.
130
Global F-statistics?
= 1 F-statistic for all populations.
131
Pairwise F-statistics?
= 2 F-statistics for all populations.
132
F-statistics? (3)
• FIS.
• FST.
• FIT.
133
F-statistics in equations? (3)
● FIS = (HS–HI)/HS
● FST = (HT–HS)/HT
● FIT = (HT–HI)/HT
134
Scarlet Tiger Moth exercise
• Calculate Global F-statistics from data below: (6)
× Subpopulations: 1; 2; 3; 4; 5
× p : 0.86; 0.80; 0.96; 0.73; 0.91
× Ho : 0.06; 0.12; 0.03; 0.15; 0.06
● Use p to calculate q for each one (p+q=1)
q1= 0.14.
q2= 0.20
q3= 0.04
q4= 0.27
q5= 0.09
● Calculate HI
HI
= (Ho1 + Ho2 + Ho3 + Ho4 + Ho5)/total # population
HI
= (0.06+0.12+0.03+0.15+0.06)/5 = 0.084
HI = 0.084.
● Calculate HS
• 2pq for each subpopulation.
• HS = (2p1q1+2p2q2+2p3q3+2p4q4+2p5q5)/total # population
HS = 0.239.
● Calculate HT
• Calculate average p.
• Calculate average q.
• 2pq (with dash).
HT = 2(ave. p)(ave. q)
HT = 2(0.852)(0.148)
HT = 0.252.
● F-statistics in equations
• FIS = (HS–HI)/HS = (0.239–0.084)/0.239 FIS = 0.649.
• FST = (HT–HS)/HT = (0.252–0.239)/0.252 FST = 0.052.
• FIT = (HT–HI)/HT = (0.252–0.084)/0.252
FIT = 0.667.
● Therefore,
• FIS = 0.649.
• FST = 0.052.
• FIT = 0.667.
135
Steps to calculating Global F-statistics from data given? (5)
● Use p to calculate q for each one (p+q=1).
● Calculate HI.
● Calculate HS.
● Calculate HT.
● Calculate F-statistics in equations.
136
HI equation in Global F-statistics?
HI = (Ho1 + Ho2 + Ho..) /total # popn
137
HS equation in Global F-statistics?
HS = (2p1q1 + 2p2q2 +...)/total # popn
138
HT equation in Global F-statistics?
HT = 2 (ave. p) (ave. q)
139
"Levels" of heterozygosity? (3)
• Individual.
• Subpopulation.
• Metapopulation.
140
Types of metapopulation structure? (3)
• Classical.
• Mainland.
•
