Population genetics - Migration Flashcards
What does migration usual conjur up
Organism moving across space
examples:
1. Wildbeasts across area – variation in raine = drives popultion shifting range
- Artic turns
What do we mean by migration
Emigration + imigration drynamics between sub popultions
- When indiviual in one popultions contrubutes to genes in other popultion
Movement of alleles from one breeding popultion to another breeding popultion
- Indiviouals departing from or arriving in a new breeding popultion
What does migration violate in H-W
H-W = no one can go in or out –> when you are born into a popultion you contrubute to that popultion and no one comes in
- Violating the 3rd assumption
This is the assumption we are violateing to model migration
NOW the gentic makeup of the new generation is NOT just a function of within popultion reproductive dynamics – NOW it also includes some input from other popultions
Migration example
Can get movemnt between the forest and evergaldes black bears or night not get any migration
Individuals going between popultions birng alleles to the other popultion –> move from one gene pool to another gene pool
Two models of migration
- Continent island model – larger popultion going to smaller
- Two island model – recpiprcal gene flow (this is the one we use)
Migration model
Start = have 2 subdivided popultions with difefrent alelles frequnceies
AT H-W –
Poplation 1 – P = 0.8 –> p1 = 0.8
Popultion 2 – P = 0.2 –> p2 = 0.2
At H-W the allele frequencies would stay the same (no migration) –> BUT THEN we can swap individulas at a rate of m
m = proportion of one population that will contrubute to reproduction pool of other popultion in the next generation
m in migration models
Proportion of popultion that contributes to the next generation of the other popultion
HERE = we assume that m is the same for both popultions
- We could do m1 and m2 for each popultion BUT we willl treat m symetrically
Things we need to account for in migration model
- m – proportion of popultion that contributes to the next generation of the other popultion
- Input
- m - 1 – need to account for individuals leaving popultion (need to take account loss)
- Loss from original population
- Loss of migrants from our focal popultions
Change in allele frequencey in migration model
Get chnage in allele frequency because move individuals in and out = undergo evolutionary change
Looking m and 1-m = allele frequencies change
Mathamatical model of migration
𝑝′1 = (1 − 𝑚) (𝑝1) + (𝑚)(𝑝2)
- 1-m X p1 – only have individulas with p1 allele frequncey
- m = migration rate
- m X p2 – get indiviuals at a raye of m at P2 allele frequncey
𝑝′2 = (1 − 𝑚) (𝑝2) + (𝑚)(𝑝1)
p’ = allele frequncey in the next generation
(1- 0.05) X (0.8) – only 95% f 0.8 allele frequncey contribute to next generation
(0.05) X o.2 - 5% of popultion have frequncey of 0.2
Because the system is symetrical migration chnage alelle in both popultion by same amount in different direction (because same m)
- Since we set up the system to be symetrcal (same m for both) = they change by the same amount
Change in alelle frequncey in both popultions
Because the system is symetrical migration chnage alelle in both popultion by same amount in different direction (because same m)
- Since we set up the system to be symetrcal (same m for both) = they change by the same amount
Popultion A – allele frequnceies are close together
- P goes up in ine popultin and down in the other by the same amount
- Allele frequncey chnage in A is smaller than B because allele frequncey in A is already similar to begin with
Popultion B the allele frequcneies are far apart
- Even though the allele frequncey is NOT the same = the allele frequcney chnage is still is –> means that suymetery in chnage is not because of p being mirrories it is becuase m is the same
Pop A vs. Pop B.
- Allele frequncey chnage in A is smaller than B because allele frequncey in A is already similar to begin with
Affect of same m
If m is the same = p chnages by the same amount in different directions in both popultions
- Even though the allele frequncey is NOT the same = the allele frequcney chnage is still is –> means that suymetery in chnage is not because of p being mirrories it is becuase m is the same
dP = same –> sign is different but the absolute value is the same
- Even if allele frequncey is not symetric dP still is if m is the same for both popultions
What is happening with migration over time
Use general dP –
dP = m(p2 - p1)
- Assume m is the same
- p2 - p1 – Frequcney of same allele in popultions 2 vs population 1 –> drives magnitude of change
End point of migration
if dP = 0 –> get equillirbium point - get an end point of popultion
IF migration is ongoing dP = 0 when P2 = p1 (when the allele frequnceies are identical)
- Have end point in middle + know what endpoint is
END – P2 = P1 –> end is when dP = 0
Migration is…
Determanistic – have an endpoint and know what the endpoint os –> if you know the start you can know what effect will be
- Migration will go until p2 = p1
Effect of migration
Migration acts to decrease genetic diffeerntaion between popultions – homogenizes genetic varaition across subdivided popultions
- If migration keeps occuring popultions will evenually have the same alelle frequncey
- Makes allele requncies of popultion more similar through time until there is no difference between thwm
Homogenize until get equal Pt (will end equal to the frequncey across popultions Pt)
Pt
If two popultions were in one popultions what would overall p be
- Allelic varaition in total popultion if subdivided were in one popultion
- Pt = used to find Ht = Heterpzygosity across popultions
THIS is what migration pushes P to in each popultion – pushes to average of 2 alleles
- Migration acts to drive P1 and P2 towards PT
FST of drift vs. migration
Drift = increases FST towards 1
- Drift = makes Pt less similar
- Increases differences between popultions
Migration decreases FST towards 0
- decrwases difefrences between popultions
- Make popultions converge of Pt
Migration and drift = in direct opposition
- If migration acts to dirve P1 and P2 towards PT = acting in direct opposition of drift
Can find an equillirbium between the two
Meaning of FST
Increase difefrence between popultions
FST = 1 = no shared alleles (have P = 1 and P =0)
FST = 0 – ni allele frequency differences (they are the same)
FST
The measure of genetic differentiation between subdivided popultions
Drift vs. Migration
If migration acts to drive P1 and P2 towards Pt = acting in direct opposition to drift
- Effects can be viewed in terms of FST
Have an equillibrum point where forces balance out
Drift vs. migration equillbirum point
FST>
Size of m and FST>
If m is smalle (less than 10-15%)– can calculate FST at equillirbium between drift and migrayion –>
𝐹𝑆𝑇= 1/4𝑁𝑒𝑚+1
Nem = efefctive popultion size times the migraytion rate = the numver of effective migrants per generation
- Nem = improtant term
- Assume that level of FST = due to equillibrum between drift and migration = can use FST to see number of migrants moving in generation
***Ne and m = hard ot gte iun popultionn but they are meaningful
Use of FST
Assume that level of FST = due to equillibrum between drift and migration = can use FST to see number of migrants moving in generation
Given a value of FST = can find Nem = can find expected number of effective migrants
- Here we assuime that the popultions are at equillbirum
FST = 0.0476 –> FSt is much closer to 0 than 1 = these popultions are much more alike than they are different
Changing Ne
If increase Ne – loosing FST vakue = FST decreases
Increase Ne = FST decreases because ability for drift to maintain allele frequncey difefrences decreases and migration is strong
Increase Nem = favor of migration over drift = become similar
Decrease Nem = favor drift = miantain differences
FST> with larger popultion size
FST> = 0.0243
Increase Nem = favor of migration over drift = become similar
Decrease Nem = favor drift = miantain differences
FST at equillibrium
if m is small we can calculate FST at equillirium between drift and migration
FST> = 1/4Nem+1
Nem term
Effective population size times the migration rate – it is the number of effective migrants per generation
Meaning of FST
FST = equilibrium point between the effects of drift and effect of migration
- It is a function of migration rate and strength of drift
THIS IS A PUSHING EAQUILLIBRIUM = stable equillirbium between the two forces
Affect of drift vs. Affect of mutation
Drift = causes allele frequncey to be more different
Migration = Homogenoizes to Pt (Causes allele frequncey to be the same)
We can define an equillrbium point
FST
Metric of genetic difference between populations – how different are two populations genetically
- Look at FST by looking at varaition within and across popultions – take observed vs. expected form
How do we find FST (overall)
Take observed vs. expected form
- Compare heterozygosity in sub popultion to total variation
FST = Ht - Hs/Ht
- Ht = like epxected – expected H if they were one popultions
- Hs = observed H (Avg of sub H)
Observed parameter vs. expecteation given null
Pt (all varaition – if were one popultion) vs. how varaition is distrubuted in subdivided popultions (Hs)
Observed in FST Vs. Expected in FST
Observed = looking at varaition within popultions (Hs – avergae varaition within sub popultions)
Expected = null –> Null that 2 population stae part of one popultions
- All alleles in both popultions that mized as if they were one popultions THEN what would H be (THIS IS Ht)
- Null = treating as one popultion – Avg H if one popultion
FST (1 or 0)
FST = 1 – P = 1 and P = 0 –> H = 0
- Hs = 0.5 –> between the two of them
- All of varaition is between the popultions NOT within
FST = 0 – all varaition is within subdivided
- P = 0.5 and P =0.5 – allele frequencey is the same in both popultions
Low FST – allele frequncey in popultions are close together
Ht
Heterozygosity across both popultions
- Equal to or greater than variation within subdivided popultions
Uses Pt – Average between P of both populations
What can we use FST for
Given a value of FST – we can find the expected number of effective migrants (Can find Nem)
- Can get the number of individulas moving between 2 popultions
- Can use FST as equillirbium point –> calculte equillirbium level (FST) given strength of drift and migration rate BUT if we assume that something is already in equillirbium amd we measure FST (we know about strength of drift and migration) –> use FST to find Nem
***Can assume that the popultion we are exmaining is in equillirbium
Looking at how connected the 2 popultions are
IF FST = 0.5 – assume equillirbium
Nem = 1/FST/4FST
Nem = 1-0.5/4X0.5 = 0.25
- Nem = effective number of migrants
0.25 –> means have 0.25 individuaks (can be decimal because its an average)
- Means – 1 indiviuals every 4 generations (the popultions ate quite isolated)
- 0.25 is NOT the migration rate – it is the avergae number of migrations per generation
Looking at how indepent the popultions are –> you can find genotype frequncey –> use that to find FST –> get Nem
FST = 0.203 –> pretty intermediate
Nem = 0.981 –> If allelic varaition is driven by long term drift + migration = get 0.981 deer each generation
- 0.981 deer going from one to other (Since symetric = goes both ways)
Pairwise effects of forces
- Mutation selection balance
- Mutation adding alleles and NS getting rid of them
- s and u
- The dual effect of drift and mutation driving neutral molecular evolution
- Drift regarless of popultion size drives genotypic variation between two species
- u and N
- Drift regarless of popultion size drives genotypic variation between two species
- The tension between drift and migration in subdivided populations
- m and N
Mutation selection balance/Mutation and drift
Had fairly straight foward outcomes
- Mutation creates varaition and drift
Stable equillibrium
Example: Mutation creates varaition and drift turns some of it into substitutions at a constant rate
- Straight foward outcome in nucleotide substitution –: drift taking mutation and carrying it to fixation
- u drives nucleotide substitution rate because Ne is in both equations = cancels out = only u affects the rate of process
What drives nucleotide substitution rate
u drives nucleotide substitution rate because Ne is in both equations = cancels out = only u affects the rate of process
Nature of drift and selection
Selection = determanistic –> predictable
Drift = Stochastic –> don’t know direction
Differences in nature of them = makes intercation complicated
***They are two of the strongest forces – how do they interact
- Complicated
Since drift = always happening –> means that selection is always at play with drift
Drift and selection interaction
IMAGE:
- Left of 0 = selection predominates (negitive selection)
- Line at 0 = drift predominates
- Right of 0 = positive selection – selection predominantes
- INtersection of lines – point where drift = acting soley on alleles – there is no difefrence between drift affect on alleles and NS affect
Deviation from balance between Drift and mutation (deviation from intersection) = based on 2Nes
Probability of mutation being lost due to drift = more likley (1-1/2N)
Image = shows drift + selection simultaneously in a system (violating infinate popultion size)
Overall – there are osme parameters where selection will predominate and spme where drift will
- Popultion size decreases = stringer strength of ____ for selection to be predominante dirver of allele frequncey chnage
- Selection needs to act alongside drift – relative strength pf 2 ffoces = affects if selection can occur
Take home message – the relative magnitude of selection and drift matter – they often behave as if one force is predominant over the other
Probability of allele going to fication
Probability of new allele going to fixation = 1/2N –> relative increase or decrease of probabiliy of going to fixation = based on 2N
What effects if selection can occur?
Selection needs to act alongside drift – relative strength pf 2 forces = affects if selection can occur
Importane of drift vs. selection
There are ranges of parameter space where one is much more important than the other
Drift + selection on adaptive topographies
NS = acts to push popultions uphill – increase average popultion fitness (will go to make w/)
- Will keep going until get to a local maxiumum value of w/
How will drift affect AT?
***Drifts tendencey is not to go downhill it is just to move in either direction BUT at fitness peaks there is no where to go but down so drift pushes popultions off of fitness optima
Drift = changes alelle frequnceies randomly back and forth
- When at w/ (When at stable equillibrium) you can only go down in w/ BUT drift is not trying to decrease w/ it is just causing p to move randomly on X axis
- Drift causes back and forth movement from one generation to the next BUT if at w/ then drift can only move w/ down = drift decreases w/ because only way to go BUT if popultion is not at w/ (not at equillirbioum) then drift is equally likley to go in both dorections (Can make it decrease w/ OR can make it go uphill to w/ fatser)
- If no where to go but down drift can push popultion off of w/
Strength of NS + drift on AT
Steepness of slope = proportional to the strength of selection
- If steep – a small chnage in P = bigger change in fitness = stronger repsonse of NS = NS can counteract affect of druft more readily (when steep drift is constrained on how much it can chnage things because NS can put it back to w/)
- Steep – NS is going to give strong pushback as drift is moving the popultion around
- If shallow (less steep) = can move p a lot without a big change in W/ –> when p chnages and effects w/ THEN drift can drive the system more stringly (because NS isn’t ask strong if less chnage in w/) –> drift has stronger effect here
- If shallow – the NS pushback is much weaker = drift has a much freer hand
Smaller popultion size = affect but drift is large = harder for NS to keep popultion at an optimium
NS + Drift acting on beneficial recessive alleles
Recall – NS acting on beneficial recessive alleles has a hard time getting started (Slow at the start)
NS + drift = particularly impirtant for beneficial recessive alleles
Begging of recessive alelle increasing (starts slow) –> drift can move things very readily + selection is weak – drift is strong
- At low frequnceies when it is very shallow – drift can be strong –> the most likley outcome is that the benefical mutation will drift to zero before NS can get any traction
- Beneficial recssive allele = more likley to be lost due to drift than they ate to go to fixation
- Porbability of going to fixation is 1/2N BUT probability of not fixing = 1-1/2N –> drift is main threat to benefical recessive
- Recessive benefical is likley to be lost due to drift before selection can bring it to fixation (more likley lost than selection taking hold and incerasing it)
Phenomon = Holding seive
Halanes seive
Overall: At low frequnceies when it is very shallow – drift can be strong –> the most likley outcome is that the benefical mutation will drift to zero before NS can get any traction
- If beneficial mutations act in rescive fashion = most liklet will come and go to drift long before selection has a chance to act on them
- Sometimes these mutations can reach high enough frequncies to start being visable to selection through drift
Effect of drift on recssive benefical alleles at low frequencey –> most is lost due to drift before selection can take hold and do things (bring to fixation)
- Affects rate of selection
Affect of drift on rate of selection
Already have low mutation rates –> mutations rates give us mutations but drift can make is lost – can lose it befgore selections can do things = even lower rates of increase benefical recssive mutations
Drift increase or decreasing beneficial mutation
Drift can inrease are decrease BUT it is more likley to lose it (to decrease) because once it hits zero its gone
- If you have limit that affects increase/decrease for good + if have one copy –> if you lose one copy = its gone –> loss is more likley than increasing to go to fixation
Creates limitations of NS acting on new alleles
Outcome for new reccessive benefical allele
Evolutionary outcome for new recessive benefical alleles is heavily influnces by drift
Migration + Natural Selection
The influx of alleles from other populations can also push populations off and adaptive peaks, or prevent them from getting to
them in the first place
- Migration coming in adapted to different environments = can push population off of peak
Migration load
A lower average population fitness than predicted given selection regime due to migrants from populations with different selection regimes
- Knowck off optimum because influc of alleles adapoted elsewhere
- Espcially bad at edge of range
Where does migration load have big effect
Often effects at the edge of species ranges
- When populations are well-adapted (high mean fitness) in the center of their ranges, they may send out a lot of migrants –> These migrants can interfere with
local adaptation at the range edge- perhaps even determining the range limit itself
Example of migration load
Butterfly – sub optimally adapted to conditions –:> reason is because butterfly coming to island
- Get warm adpated end in small popultion = can’t adaopt to local climate
Can migration be good?
Migration is not always bad –> add variation
IF the strength of selection = proportional to varaition
- Selection = lose varaition
- Waiting to get varaition through mutation (mutation is a slow source of new varaition) –> get little variation – low rate of mutation = doesn’t give varaition + lose a lot of mutation = ability to adapt if run out of varaition – wait a while to get varaition through mutation BUT migration can add varaition
- Migration = can get new alleles into focal popultion that NS can act on –> might not need to worry about losing alleles because can have others with those alles come in
- Migration can be very effective force for infusing popultions with new varaition on which selection can act
Migration affect on NS
Migration - can help or hinder adaptation due to NS
Is pushing of adopative peaks always a bad thing?
If have scenerio in image –> You can go to w/ = 0.35 OR can go to w/= 1
IF p goes to p> = it will stay there – this is bad because low w/ – NS can’t move it from the valley BUT other evolutionary forces can
- If went to the right of valley = would go to p = 1 – would end at w/ = 0.35
- If have other forces with selection = won’t get stuck there –> drift can chnage { and can drift acros equillirbium to the left and NS can then bring it to P = 1
- Selection can’t do this by itself but it can with other forces – drift opens up posibility
- Selection + drift = two step process involoving chnage in predominance of first (first drift predominates then selection)
OR migration can come in – other population with benefical allele can come in – they can send migrants –> migrants can go to the focal popultion and can bring P across equillibrium and allow NS to bring P = 0 and w/ = 1
NS by itself can’t bring the popultion to the global optimum but selection in conjuction with other forces can
Wrights theory (overall)
Back during the modern synthesis, Sewall Wright proposed a model for how the interplay of evolutionary forces might be a more powerful mode of evolutionary change than selection by itself
- Thinkning about limits of NS and need other dorces to get complex traits
It’s called ”shifting balance” between it involves shifts in the predominance of the evolutionary forces acting on a species
- Think about how relative importance of forces might shift in system
When is wrights model useful
Particuly useful for thinkning about ways that evolution can act when adaptation is complex
- Model on how to adapt across rigged AT –> how to cross adaptive valley if NS can’t do that by itself
Rugged adaptive topographies
Have more than one local maximum
How to think about Rugged topographies
It is more realistic to think in multiple dimensions
Example – image
- Can see two traits
- Rugged topography because 2 points of high fitness states –> Can’t go between points without decrease w/ –> NS can’t go between them itself
- Have local optimum at combination of low values or trait 2 and moderate values of trait 1
- Have global optimum at combination of moderatley high values of trait 2 and highest values of trait q
- Highest fitness = high trait 2 and high trait 1
- There are two possibilities on high w/ based on right combination of trait values –> need right combo to have right value
Going from local optimum to global optimum with on NS
What makes adaptive topographies rigged
Epistsis – due to epistasis –> intercation between loci and affect on fitness
- Cam’t know affect of 1 locus on fitness without knowing the state of other trait
- Affect of Trait one depends on state of trait 2
Epistasis + NS
Epistasis = majore hindernace on effects of NS
Need other forces of have epistasis
Epistatic rigged topography – multiple genes affect trait –> get both to move in right direction together – hard for NS to do
Example – 2 locus fitness epistasis
Has two fitness peaks + 2 low vallues
A1 has high fitness in presence of B1
- A1 = only high fitness with B1
A2 only has high fitness in the presence of B2
- High A2 and B2 = high fitness
Wrong combo of alleles = decrease fitness
If to the left of valley = fix for A1B1 BUT if to the firght of balue fix for A2B2
Have Adaptive topography for A with w/ and Adaptive topography with B for W/ –> put them together to see interaction
What does wrights model work best for
Wright’s model occurs takes place on rugged adaptive topographies, but also works best in subdivided population – works best in subdivided popultions
Works best in subdivided because small popultion = increase drift + subdivided can have migration + mutation popultion drift independtley
Wrights model (overall)
Idea of how evolution could work NOT saying that it is universal + logical expliantion of evolving forces = allow popultions to evolove
- It is a hypothsis on how it can happen
Model = 4 Stage model – 4 ”shifts of balance” among evolutionary forces and one shift from within population dynamics to among population dynamics Wright’s Shifting Balance Theory
Wrights model (Slides)
Step 1 – in individual
subpopulations – drift can
predominate if population sizes
are small (relative to “height” of
fitness peak)
- If this is happening in multiple
subpopulations, some of these
populations are likely to end up the
bases of better optima
Step 2 – When drift brings the
population in contact with a steep
fitness slope, the strength of
selection starts to outweigh the
effect of drift – selection pushes
the population up the peak
- As mean population fitness increases,
population size is likely also increasing
Step 3 involves a shift toward
dynamics among populations –
large high fitness populations are
likely to produce a lot of migrants
- These migrants can influence the
evolution of other subpopulations
- This influx of new variation pushes the 2nd population of its local peak –
specifically in the direction of the peak in population 1
Step 4 occurs when this push from migration allows selection to take over
in the 2nd population – driving it towards the global optimum
Overall: The interaction of evolutionary forces acting
across large subdivided populations might allow for complex adaptation
that natural selection can’t drive by itself
Wrights model (Mine)
Step1 – all subdivided popultions = stuck on bad fitness peak –> NS can’t act to get to a better position (because at a peak)
-Height of peak is proprotional to W/ – depends on reproductive sucess
- Low w/ = popultions staying small + low fitness = popultion decreases = cam drift heavily –> drift has string hand and NS will be weak –> can have random change in alelle frequncey
- Random chnage in allele frequncey due to drift = csan be going on in 10 subdivided popultions independentley – all random change due to drift –> eventually popultions will leave peak
- Drift will predominate unless the frequncey goes to a slope and NS can accelerate
THEN – as popultion increases = drift acts less –> Selection will increase w/ to go up peak and get to a new peak = optimum fitness
When increase w/ = now hvae high probability of S/R = increase popultion size = can be highest w in subdivided popultion = NOW need to send migrants to other popultions
- Healthy popultion = only sending migrants out (not symetric)
Migrants now influence P in other popultion – other popultions in other peak can have low drift out– if send migrants from original popultions chnage P in other popultion determansticallty towards higher peak (not random) –> NS can bvring to peak after migration – NS can take over and end at overall species wide adaptation in complex trait
END = species wide adpatation in complex trait
SHOWS – NS can drive complex adptation in com face of epistasis –> other droces play important role NOT just NS – need other mechansims to get adapative being
Height of peak on Adaptive topographies
Height of peak is proprotional to W/ – depends on reproductive sucess
- Low w/ = popultions staying small + low fitness = popultion decreases = cam drift heavily
What does Wrights model explain
Explains how complex adaptation can occur
Using other forces = we can epxlain how complex adaptation can occur –> NS can’t do it by itself – relies on importance of forces shifting across process
What creates rugged adaptive topographies
Epistatic interactions in multiple loci under selection created rugged adaptive topographies –> requires changes in multiple sets of genes at ince
Limitation of NS
NS can’t explor broader adaptive space itself (in rugged adaptive topographies) because only goes uphill – it can get stuck at a sub optimal peak
Using other forces = we can epxlain how complex adaptation can occur –> NS can’t do it by itself – relies on importance of forces shifting across process
One shift within wright model
Shift from within sub populations to between sub population
***Works when in sub popultions
Step 3 = Shift within sub popultion to between sub popultion
Wright (2)
Start = popultion stuck in sub optimal peak – NS is stuck (w/ can’t go up anymore) –> at a low w/ at start
Beceasue at low w/ = low reroduction output = small popultion = drift – HERE drift can predominate and selection is weak
Stage 1 = drift = random chnage in allele frequncey – each sub popultion is independent of each other –> in some of the sub popultions = the popultion will move to go towards a better fitness peak due to drift –> when it reaches a steep slope = NS increases in strength (Strength of selection = proportional to slope = NS is stronger) –> NOW selection takes over
- Selection is strong –> Selection will take popultions up to optimual fitness peak = w/ increases
- Selection increases – drift decreases
AS w/ inreases = Popultion size increases
- At new peak w/ increases = get more offspring = popultion grows
NOW – go from within popultion to ACROSS sub popultions
If 2 sub popultions increases popultion size = it will disproportionaly send migrants to other popultions –> NOW other popultions is driven by migrants
BY sending out migrants = affect allele frequncey of other popultion = affect evolution of other popultion
- MIgration = determanistic = more efficient
- Sending migrants from one popultion to other = change allele frequcney in other = pull other popultion towards higher w/ on Adaptive topography – NOT random like drift – going to specific to higher peak
Other popultion goes to optimal peal
- Selection = takes over in other popultion (takes over within popultion – NOW back to within popultion) to drive up to optimal peak
- Now within popultion again
- Selection takes over again
Applying wrights shifting balance – What does Wrights hypothesis mean?
Example – Malaria
We know Anemia C alelle = almost completley resistant to malaria but it is in low frequncey
Because it is in low frequncey NS = can’t act on it
- Constaint on NS –> doesn’t mean contraint on evolution entirley – can change using other forces
To have C allele increase in the past they could have had = not in large popultion in Afirca but in small sub popultions where drift infleunces BUT they are also connected enough that mogration can carry alleles
- In the past they could have had small communities with drift but have migration
- As the popultions grow = drift decreases + limit subdivision = less likey for drift/wright and NS will happen
THIS in crease in C didn’t happen because of our interaction with malaria is recent –> we didn’t interact with malaria until agriculture
- Human malaria = because of trade and traffic with madacagscar – change in standing water = malaria infects humans now
- Here there is no longer condition for drift/migration to drive adapatation
