Test #2 Review Flashcards
Dominance in selection
Most of the time its not purley dominant or recessive –> can quantofy the degree of dominannce
h
Dominance coefficient for an allele –> describes the degree of intermediate state***Always a value between 0 and 1
Meaning of selection coefficants 0, 0.25, 0.5
0 –> no selection against that0.25 – 25% cost to have that genotype 0.5 –> 50% decrease in fitness relative to other fitness % Cost/decrease in fitness
Modifying for dominance
Quantify s for allle (rather than genotypes) and the modify with a dominance coeffciants
Meaning of h = 0 for AA
h = 0 –> there is no dominance in a –> A is complteley dominant to a - There is no affact of a in Aa Selection against Aa is 0 ***Add inmage slide 19 (postclass)
Modifying s to account for degree of dominance
Use 1 selection coefficient AA = h Aa = hs (selection coefcinat X SC) aa = s Example h = 0 s of AA = 0 s of Aa = hss of aa = s HERE – A is completely dominant to a
Meaning of h = 1 for AA
a is completely dominant to A - Affect of SC s – s of aa is domiant Selection against Aa is 1 X s
Example of Quantofying the degree of dominance WAA = 1WAa = 0.75Waa = 0.5s AA = 0s Aa = hss aa = s
SAA = 1-1 = 0 (1 - RF) SAa = 1 - 0.75 = 0.25 Saa = 1 - 0.5 = 0.5 –> means s = 0.5 1 - WAa = hs1 - WAa = h X 0.51 - 0.75 = h X 0.5h = 0.5
Example – Quantify the degree of dominance s AA = 0s Aa = hss aa = sWAA = 1WAa = 0.55Waa = 0.5
TO FIND S: s aa = 1 - RF aa –> 1 - 0.5 = 0.5S Aa = 1- RF Aa = 1 - 0.55 = 0.45 0.45 = hs0.45 = 0.5hh = 0.9 LOGIC: Saa = 1-RFS aa = 1 - 0.5S aa = 0.5hs = 1 - WAa1 - 0.55 = hs1 - 0.55 = 0.5 X h h = 0.9
Meaning of h = 0.9
Dominance coefficient is closer to 1 = phenotypic affect of a is bigger than A
- Bigger affect if a; less affect of A
Meaning of all h values
h tells us about the degree of similarity between heterozygote and homozygote fitnessIf h = 1 –> Aa is exactly like the deleterious homozygotes If h = 0 –> Aa is exactly like the selectively favored homozygote If h = 0.5 –> The fitness of Aa is exactly intermediate
Graphing the dominance
REMEMBER – we looking at h from the persecutive of a (is Aa like AA or aa) –> get straight line –> Aa falls on the line at h = 0 –> A is dominant and a is recessive(Because is at WAA) - At h = 0 Aa has the same fitness as AA –> therefore a is completely recessive h = 1 – Aa is like aa –> aa is dominant (Because is at Waa) - Aa has the same fitness as aa –> therefore aa is completely dominant ***Image on lide 31
Quantifying mutation rate
u (Mu)
Mutation rate for one BP at one locus
All of the rates are very low (often order of magnitudes less than 1) for rate at a single BP –> probability of a given BP chnaging from one generation to the next is low –> BUT when scale up over entire genome = get 30-40 mutations occuring - Chance at any one mutation is small mu BUT the chance of Mu across genome is large Looking at change of one allele at one locus from one generation to the next = use very small numbers***Those mutation rate values on the previous slide werevery small numbers: ~10-8 for humans
How does mutation affect H-WExample
Start: 90% A – P = 0.9 10% a – q = 0.1 Mutation occurs in germline producing gametes – Parental genotype –> gamete – gamete now has mutation) Mutation rate = 10^-4 (relatuvley high rate of mutation) Convert 1 A –> a out of every 10,000 gametes in gamete pool Change in allele frequncey – p = 0.8991; q = 0.10009 –. get very small chnage in popultion with a relativley high mutation rate = small chnage in one gneration 1 out if every 10,000 gamete
Overall: Get very small chnage in popultion with a relativley high mutation rate = small change in one generation
Mutation rate over time (scaling up)
Mutationrate can add up through time Rate of chnage in one generation: dP = -up - Because p –> q = use negitive mutation rate dP = chnage in one generation We can scale this up over any number of generations: Pn = P0e^-un P0 = starting allele frequcey n = number of generations HERE = use exponetial (in one generation we just multiplied) Pn = p after n generstions from a starting point of P0
Allele frequcney chnage from mutation after 100 generation
Allele frequncey change is still very small (even after 100 generations) - Still not much chnage but adds up over very long amounts of time
Mutation as a force of evolutionary change
Mutation is necessary for change BUT it is not sufficient
- Mutation by itself does almost nothing – mutation is not what causes evolutionary change
- Mutation is needed (need variation) – necessary for evolution but not a good force by itself – works with other forces
- Other forces act on mutation and drive change in allele frequency
Mutation is necessary for long-term evolutionary change, but it is no where near sufficient to explain genetic and phenotypic change in nature
What does selection need
Selection requires genetic variation – some prvious mutation events are a prerequisite for evolution by NS
What does mutation produce
In the case of favorable alleles –> mutation occasionally produces fodder for adaptations shaped by NS - Have mutation –> THEN selection can act
Mutation working with selection
Experiment = tells us that mutations does make beneficial mutations + might have beneficial effect
- IF impose stress = new variation matters – when you have selection = you can see much more rapid change - New variation = NS can act on it = evolve more rapidly with weak variation + Strong selection
Mutation Vs. Mutation + selection
Mutation + Selection – The selection lines show that selection acting on that new variation leads to much larger changes
Mutation – The control populations evolveddegree of improve salt tolerance through mutation alone
Selection vs. Deletrious alleles
Evolutionary force of selection and force of mutations work against each other Selection = wants to get rid of deletrious alleles Have two forces 1. Mutation adding in new mutants (u) 2. Selection taking out mutants from popultion (s)u = weak –> se;ection pushes together – push against each other S = strong QUESTION – if u is weak and s is strong why doesn’t selection just push out deletrious alleles
If u is weak and s is strong why doesn’t selection just push out deletrious alleles
ANSWER – dominance
Selection vs. Deletrious alleles equillirbium
You can have a stable equillirbirum point where forceses are balanced – we can define an equillirbium point where these forces are balanced - Can calculate teh expected allele frequncey of deletrious mutations at this point Where equillirbium point occurs = affected by dominance vs. recessive
Where is equillirboum beteween selection vs. deletrious alleles
Where that point occurs is affected by dominance vs. recessive
Calculating mutation selection balance for anything more than purley recessive (if have effect in Aa)
q> = u/hs Used if h is anything other than 0 Exampleh = 0.05 (have a small amount of dominance – get some deleterious affect in Aa –> 5% deleterious affect) u = 10^-4 2 = 0.98 (very deletrious) NOW q> = 0.002Used for anything other than pure recessive (if h is anytjing other than 0)h = 0.05 = have 5% deleterious affect
Why is CF maintained at 2%
The answer is likely an overdominant effect of heterozygote resistance to Typhoid (which interacts with the same proteins when it infects lung tissue)
Constaints on NS’s ability to optimize popultions
- The outcome of natural selection doesn’t just depend on the overall fitness of an allele, it depends on the population context that theallele exists in
- Mutation can interact with the weak effects of selection on deleterious mutations at low frequencies to maintain low fitness genotypes in populations
When does Genetic Drift occur
Occurs if you violate infinate popultion size MEANS it is possible it is going on in all popultions
How important is genetic Drift
Very important – tied with Natural selection (almost if not just as important as natural selection)
Where is drift important
Important in small popultions BUT it is not absent in large popultions - Can still have drift in large popultions Important for variations within/between species
What does H-W mean by infinate popultion size
Means that the ganete pool is sampled exuhstivley - Every single copy of allele in gamete pool gets represented exactley once in the next generation
What happens when we subset popultion
If we subset a popultion = we open ourselves uo to errorIf sample 50 alleles out of total popultion–> we might get the actual allelle frequncey but we might now = driftIf we are not sampling fully = open to drift
How do we get drift
Has to do with sampleing error –> if we do not sample the popultion fully then open to sampling error + open to drift that has to do with sample errior - Sampling error in gamete pool = open to chnage in allele frequncey = drift –> continous mechanism in popultion
Parts of genetic drift (thing that influences it)
- Random mortality2. Sampleing errors in zygote formation
Larger sample size + dirft
Larger smaple size = more sure we are to get the same intial underlying frequency
What happens if lose infinate popultion size
As soon as we ease off this assumption – chance events can start to influence allele frequenciesTrue evern in very large popultions
Genetic Drift
Random chnages in allele frequcneues in popultion
Selection vs. Drift
BIG difference = in predictability Selection = determanistic (if you know start then know how it ends) Drift = Stochastic (probablistic) – don’t know exatcley what will happen because it is based on random sampling - NOW using a different perspective (because proabbilistic) – don’t know exactley what will hapen because based on random sampling - Can look at allele frequncies that are more likley BOTH chnage allele frequencies but in different ways
Drift is…
Stichastic – we can’t predict the outcome - If we know the starting point of the system we can’t know where it will end up
At a given point we might be able to calculate the proability of ending up at a particular state but we won’t know what will actually happen in that instance - We can look at the most likley outcome from one generation to the next
Some aspects of dirft are…
Some general aspects of the outcome of drift are inevitable BUT we can’t know the end state (nor even the state of the next generation) for a particular popultion - Has some inevitable features
Example #2 – how drift leads to chnage in allele frequncey (sampleing gametes with red and blue)
IF start with 50% A and 50% a (50% red and 50% blue) – have 20 alelles in gamete pool (have 10 red and 10 blue) IF we sample a fixed amount of times (if we pick 20 gametes) –> we can get p = 0.5 and q = 0.5 - Each round the alleles have a 1 in 20 chnace of getting chosen BUT some might get chosen X2 abnd some might not get pciked at all Here = sampleing 20 times with replacment = some might get chosen twice and some might not get chosen at all - Means that you can start with 10 and 10 BUT end with 7 and 13 = have evolutiion BUT – what if we did this many many time (Sampled 20 in many rounds each woth replacemnt) Reuslt = stabilize around 50:L50
What happens when have repeated sampleing (if do samples of 20 many times)
If start with 50:50 –> End up stabilizing around 50:50 - If kept sampleing 20 again and again –> end up stabilizing around 50:50 - The highest proabbility outcome = 50:50 – end up stabilizing around 50:50 Avergae end outcome = 50:50 BUT you do not get 50:50 in each generation If end at 50:50 –> why do populations chnage?
If our highest probabilityoutcome is to get thesame allele frequency,why does this result inevolution?(If we end up stabilizing around 50:50 – why do we get evolution)
- In a single generation,the ”on average” partdoesn’t matter – there’sonly one round of zygoteselection* Any sampling errors(deviation of a subsetfrom the true populationvalues) stick* Even if started at p = 0.5 –> THEN The population isrestocked at the newvalue of p = 0.35 TEHN you sample another 20 gametes BUT you are sampleing from p = 0.35 and then might get p = 0.4
Experimnet – Most likley outcome from each sample
If start at p = 0.6 – when sampling gametes – most often get back to p = 0.6 - Getting back to p = 0.6 is the most likley outcome BUT in experiment it only occured 18% if the time MEANS that 82% of the time get something other that p = 0.6 –> 82% of the time get chnage – the liklihood of statying at 0.6 is low even though it is the most common outcome - 82% of the time = get chnage in allele frequencey - Standrad error = can avergae how far you are for subset sample size
How to we talk about genetic drift
You can look at the probability of chnage even though you can’t know if P will increase or decrease or the magnitude of chnage BUT you can get probability that P will chnage ***There is no dP equation for drift
Inevitable aspects of drift
When sampling pools a finite number of times = eventually get fixation for one allele - Means sampling errors are important – critical affect = when lose sometuing = lose it for good - Each time one is missed from sampling error, it’s gone for good Means that dirft will tend towards fixation in the long one but don’t know which allele that will be Affect of drift = genetcually decrease – every time misample something and soemthing is not representaed = that copy is lost = lose variation
Liklihood of picking certain alleles + liklihood of fixing for alleles
Every copy of each allele has equal probability of going to fixation (Probability of any one copy of A or any one copy of A is equally likley to reach fixation) - In a given population, each individual allele segregating in the population has an equal probability of being the one that goes to fixation eventually (Doesn’t mean that p and q alelles are equally likley to go to fixation – means individual copies of alleles in the gamete pool are equally likley to go to fixation) - If have 20 copies of an allele in a population then porbvility of any one copy if allele going to fixation is 1/20 IF P = 0.6 and q = 0.4 –> NOt equally likeley for p or q ro be fixed BUT each individuakl copy has the sameprobability Each copy in the gamate pool has the same probability Example – if have 20 copies of an allele – each copy has a 1/20 chance of going to fication IF p = 0.6 and q = 0.4 –> Probaboliyu pf P OR q going to fixation is Mutaually exclusive - One copy pf p or one copy of q Since ME (one copy of P will go to fixation or a different copy of P will go to fixation) - P(One copy of P going to fixation) OR P(Andifferent copy of P going tp fixation) = 1/20 + 1/20 – since have 12 copis of P (the probability of any one copy going to fixation is mutation exulsive) – add all 1/20 = get 12/20 = 0.6
Example of probability of P or Q going to fixation
P = 0.6 and q = 0.4 –> porbaility of P going to fixation = 60% and q going to fixation is 40% (because probability of any one copy gping to fixation is 1/20 and ME = can add individual orobabilities together)— The probability being 0.4 is ONLY for the starting generation –> As soon as the allele frequncey chnages due to drift that porbabiloity resets THEN if P = 0.45 and q = 0.55NOW probability of P going tp fixation is 45% and Probability of q going to fixation is 55%
Probability of P or Q going to fixation
Probability of P or Q going to fixation = equal to the frequncey of P or Q in the popultion BUT only in that starting point – IF chnage frequncey then that chnage sticks around and change probability
Probability of P or Q going to fixation
Probability of P or Q going to fixation = equal to the frequncey of P or Q in the popultion BUT only in that starting point – IF chnage frequncey then that chnage sticks around and change probability
What happens to probability of allele going to fixation once allele frequencey chnages
As soon as the allele frequency changes due to drift, that probability resets
Example – if start with p = 0.4 IF the sampling error going to the next generation causes the frequcncey to chnage to p = 0.55 - NOW the proabbility of blue going tp fixation has gone from 0.4 to 0.55NOTE: There was nothing intrinsic about blue that made it less likely to go to fixation in the last generation
Drift in small populations
Drift is a stronger evolutionary force in small populations (harder for NS to recon with) - True for small popultions that stay small for many generations (like rare or endagered species) AND it is also true for events in large popultions that cause temperary popultion reductions
Affect of drift after larger popultion that contracted increases back in size
Affect of drift stays around even after gets larger again
2 terms describing evens that lead to strong drift in otherwise large popultions
- Founder events
- Bottlenecks
Cause otherwise large popultion to go through contraction BOTH have short lived stage of small popultion
Founder events
A new popultion is derived from a small number of individuals drawn from a large ancestral population - Start popultion derived from small amount of individuals Ex. A small numver of people go to colonize islands - The allele frequncey of the new popultion has lots oif drift = very different allele frequncey (frequcney is very different than ancestral population)
Bottleneck effect
A population’s history is marked by one or more generation of very small population size before regrowth
Founding events in DR
Because the foundingpopulation was small, eachperson had a large chance ofcontributing disproportionatelyto future generations –> One of these people, AltagraciaCarrasco, did have adisproportionate effect and ithad consequences later on – Carrasco had children with atleast four women –and his genesrose in frequency in thepopulationCarrasco – He was also a carrier for amutation in the gene for 5-alpha-reductase-2
Potential affect of drift
Drift can lead to increased frequencies of deleterious allles – in small popultions this effect can be dramatic
Use of Founder events
Founder effects can be useful in studying human genetics –> The effects of rare allles are hard to study in larger popultions even if they have large effects BUT rare alles can be studies in smaller popultions with higher frequncey due to found effects
Time to build varaition
It takes a lot of time to build up varaition –> If that is wpied out (like from bottle neck or founder events) = wipe out million of years of varaitionand will take millions of years to get that varaition again***Strong drift in historical events can instantly undue the work of natural selection and thousands of generation’s worth of mutation accumulation
Effect of bottle neck or founder event
Low genetic diversity – that effect stays even after the popultion increases in size - effect of drift when small popultion stciks around *** Strong drift in historical events can instantly undue the work of natural selection and thousands of generation’s worth of mutation accumulation - when in low popultion size sticks around loss of varaition = low varaition because population crash –> low varaition + effect of drift when small popultion stciks around - Only the varaition from the small popultion gets passed down = ONLY get varaition from 28 inidviuals when small popultion size
Subpopultions
Many (most) species do not exist as a single continous gene pool – they are subdivided into seperate pools across space - There are cases of species NOT in subdivsion popultions BUT most are - They are vaiarble across space = doesn’t amke sense to treat as one gamete pool Ex. Balck baers in upstate NY do not form a cohesive reproductive popultion with the black bears in florida - Doesn’t it make sense to make one gamete pool across all North America because there are baers in florida that are not likley to mate with baers in adirondacls == have subdivisions populations of species
Differences in Subdived popultions
Subdivided = different = important to treat them seperatley 1. Subdivided population can differ due to differences in selection pressures and the mutations that occur in one but not the others - Difference in selection pressures - Difference in mutations –> have different amounts of genetic varaition – it would be hard to get mutations from one subpopultion to another 2. But they are also bound to differ from each other due to drift - In subdivided populations, random changes are inevitably going to accumulate between them - They are bound to have differences due to drift – error in one popultion = bound to be different than error in the other popultion = change the subdivided popultions to be difefrent even if they started at the same frequncey ***They are vaiarble across space = doesn’t amke sense to treat as one gamete poolEx. Balck baers in upstate NY do not form a cohesive reproductive popultion with the black bears in florida - Doesn’t it make sense to make one gamete pool across all North America because there are baers in florida that are not likley to mate with baers in adirondacls – have subdivisions populations of species
Subpopulations + Drift
But they are also bound to differ from each other due to drift - In subdivided populations, random changes are inevitably going to accumulate between them - They are bound to have differences due to drift – error in one popultion = bound to be different than error in the other popultion = change the subdivided popultions to be difefrent even if they started at the same frequncey
Varaition within subpopultion vs across all subpopultions
Variation within popultin is lost BUT varaition across popultions is maintained – By producvt of probability based drift starting out - Within popultion varaition decreases BUT maintain varaition across subdivide popultion - Because stochastic = mainatin across popultions Allele frequncey across all popultions = still around 0.5 – dirft decreased varaition within popultions but moantained varaition across popultionsBut the probabilities of which allele goes to fixation work out such that geneticvariation in maintained among populations at the starting allele frequency
Drift + Subpopultion example – blue and red
Start with p = 0.4 –> and subdivide into 10 smaller popultions - Porbability in each popultions = 60% blue and 40% red – same for all populations (smae proabbility for each one) MEANS 40% on average end red and 60% end blue fixation = IN THE END the avergae varaition will stay the same - Varaition across popultions is mainatained BUT the varaition within popultions is miantained - Axross subdivided popultions = have varaition - Within = lose varaition (Fix for one allele) - When divide into sub-popultions – each sub popultions strats as the same as sancestrla popultion – each sub popultion starts with 40% red and 60% blue –> Each subpopultion has 40% chance of fixing for red and 60% chance for fixing for blue –> Each will lose varaition because each will fix for an allele BUT each will fix for different alelle (Because stochastic) so across population mainatins varaition - Since each have the same 0.4 chnace and 0.6 chance –> the most likley outcome is that 0.4 fix for red and 0.6 will fix for blue = maintain varaition across popultions BUT within popultions fiox for one allele (p is either 1 or 0) = lose varaition within popultsions BUT among popultions you still have p = 0.4 and 1 = 0.6 (Still have 60% red and 40% blue– becaus eexpect 60% of subpopultions to fix for red and 40% of subpopultions to fix for blue) They will all fix for one allele = lose varaition BUT they will fix for different alles = across popultions they keep the varaition - Each popultions has the same probability of fixing for red or blue allele at the start (0.4 chnace of red and 0.6 chance of blue) – the most likley outcome is that 40% of then fix for red and 0.6 fox for blue –> within popultions p will be 0 or 1 BUT among the popultions p will stay 0.4
Quantofying loss of variation within popultions
Heterozygosity - Use the expected # of heterozygous NOT the observed number
Heterozygosity (H)
Metric for diversiity –> Genotypic frequency of heterozygotes in the population – It is the expected frequency of heterozygotesgiven the allele frequency and assuming HWE - Use the expected # of heterozygous NOT the observed number - Allows us to quantify the loss of variation within populations
Varaition in p = 0.4 vs. p = 0.15
There is more varaition in p = 0.4 than p = 0.15 – more even mix (cloer to 0.5 and 0.5) = more heterozygoues - If no go fixation = heterozygotsity decreases = less varaitionP = 0.4 –> H = 0.48 Q = 0.85; P = 0.15 –> H = 0.255
Where is drift inevitable
Drift = inevitable in population less than infantite in size – any popultions drift is always there ***Drift = based on Stnadrad error in gamete pool –> Smaller sample = more error - Change then sticks –> get new allele frequncey
What is drift based on
Drift = based on standrad error in gamate pool – error that you don’t have the same allele frequncey
Inevitable outcome of drift
Inevitable outcome = loss of varaition over time –> Now chnage in varaition in gene pool for good
Lose within subpopultion varaition –> decreases within subpopultion Maintain varaition acriss subdivided popultion – because stochastic = mainatin varaition acriss popultions
Chnage in H as P/Q changes
As allele frequcneies are more polarized (As p/q get closer to 0 and 1) = heteropzygosity decreases - Peak of varaition = when have 50:50 (P = 0.5; q = 0.5)When closer to even amount (Closer to 50:50) = increase varaition (Because increase in H and H is a measure of varaition)P = 0.4 (more 50:50 split) = higher H = more varaition p = 0.15 (more polarized) = Lower H = Less vraaition
How is Heterozygotsity Distrubuted
Peak = 0.5 –> Highest H value when we have 2 alleles in the population - IF we start with a popultion with all Heterozygotes –> expected frequncey stays the sameIN a two allele system expected Heterozygotsity is highets (Most amount of varaition is highest) at p = 0.5
How does Popultion size affect H
As N Increases = Avgerage chnage in H decreases - As N Increases = 1/2N gets small = less change in H over time because you are closer to being 1 (if 1/2N is smaller – 1-1/2N stays closer to 1 because you are substracting a smaller numebr from one) – If 1 - smaller number = 1 Times the current H = stays close to current H
As population size increases, the average change in heterozygosity decreases (1 minus a smaller fraction)
Example - Calculating H in the next generation Start with H = 0.5N = 1000
Hg+1 = Hg [1- 1/2N] Hg+1 = 0.5 [1 - 1/(2 X 1000) = 0.49975 - HERE = we get a number that is slightley less than 0.5 – expect small Sampel errow making 1000 zygotes = lose a little genetic varaition but not much We are likley to decrease in H from one generation to the next
Extending Chnage in H across generations
We can look at the effect of drift through time - Before = we were just looking at one generation - Heterozygostity is lost after many generations (Alleleic shake up but to drift over time) TO make it for across generations = Had T expeonent – add t to generations HERE = we assume that the popultion size is the same across multiple generations Hg+t = Hg [1 - 1/2N]^t t = numbver of generations
Affect of mutation vs. Affect of drift
Affect of mutations = needs more gernations to have allele freuqncey chnage BUT With drift = have substantaial frequcey change in shorter amount of timeWith drift – even with a population of a 100, over 10 generations, we’reexpecting an average allele frequency shift of over 0.1
Rate of drift
Often occurs much fater than epxcted (like in dropshilla experimnet) - Populations often druft faster than we would epxect based on their true popultion size – instead they dirft at the rate of a smaller population Drift = often occurs faster than censeus popultions – common –> often occurer faster thna expcted based on popultion size itself - Because often dirft is based on teh effective popultion size rather than the true/cecus size
Cesusus vs. effective popultions size
Census – actual popultion size – true popultion szie (Ex. in dropshilla experiment = 16)Effective popultion size – The popultion size expected to match the realized rate of driftDRift = based on Ne (Ne is smaller than N)
Effective popultions size
The popultion size expected to match the realized rate of drift - Ne = # of indiviuals actually reproducimng in popultion - Actual indovdiouals contributing to the gene pool that we are misampling from DRift = based on Ne (Ne is smaller than N)Example – Efefctive popultion size in dros[hila expeirment = 9 – only 9 breeding indidviaiuls on average –> 9 indidvuals on average reprdoucing (7 do not) - 16 = cencus size - 9 = Ne
Why don’t popultions actually drift at the census popultion size
Because of 3rd postulate of NS –> Varaition in popultion ins S/R even if unrelated to phenotypes/genes If dirfting at N –> All indiviaual probability of S/R = 1.0 – dorft at N = drifyoing at the actual counyd of Indiodvuals (Census popultion size) - Dirfting at N = everyone has probability of 1 - Phenotype is not affecting proibabiliyu Vs. Drifting at Ne (Effective popultion size) - HERE = 60% chnace of reproduction –> NOT per phenotype (Still uniform distrubution across all phenotypes) BUT all have probability of 60% = not all S/R - Actual breeding popultions = NOW subset of overall popultions –> NOT all repriduce = # of indiviualks reproducing = NeDRift = based on Ne (Ne is smaller than N = more dirft = drift occurs faster in most popultions than epxected) - Because variation in S/R = drift occurs more powerfully than if it was just based on census size alone
Calculating Ne
We will just look at sex ratio –> Sex ratio makes a big difference in effective popultion sizeEquation – Ne = 4NmNf/(Nm + Nf)
Things that affect sex ratio
- Polygamy – One male + many females - Very common in nature 2. Polyandry – One female + multiple males - Less common in natire but sometimes is still very important Throughs off the sex ratio = affects the rate of genetic drift
Exampe of calculating Ne
Example – rate of drift in popultion starts the same In mating popultions 1 Bull = mates with 25 females If have 500 in popultions –> 250 femnales – if have 1:25 mating ratio –> only 10 males mate 250 females (50:50 sex ratio) –> only 10 males mate - IN mating popultion only have 10 males and 250 females – sampling acros 250 females + smapling across 10 males = very little varaition Equation: Ne = 4NmNf/(Nm + Nf) Nm = # of mating males Nf = # of mationg females Ne = 4 X 10 X 250/ (10 + 250) = 38.5 - 38.5 = much smaller than 500 –> Sex ratio throughs off Ne a lot ***Sex ratio throughs off Ne a lot
N vs. Ne affect on H
If N = 500 (much bogger) = varaiotion stays for a while If N = 38.5 (Ne = 38.5) = much more drift occurs = lose varaition much faster
How do we quantofy the effect of drift across sub popultions
Compoare the within popultion varaition to the between sub popultion varaition - Look at varaition iwthin popultions vs. varaition between popultions to see how much drift has gone on - We can quantify the degree of genetic differentiation that drift hascaused between these populations by examining heterozygositywithin and between themCompare Observed vs. expected value to see how effective dirft i
Example – Affect of drift across subsivided popultions
Example – eaisest to look at 2 sub popultions of the same species - Look at the varaition loss within the popultion and compare that to the exoected between popultions - Look at varaition iwthin popultions vs. varaition between popultions to see how much drift has gone on We can quantify the degree of genetic differentiation that drift hascaused between these populations by examining heterozygositywithin and between themStart = find H within each popultions and take avergae of H of the two popultions - Start by calculating the expected Heterozygosity within bothpopulations and taking the average Population 1H = 2pqP = 0.35H = 0.455 Population 2P = 0.8H = 2pq = 0.32 THEN avergae varaition within the popultions – take Average of both H H pop 1 + H pop2/ 2 = 0.455 + 0.32/2 –> Hs = 0.38756 Hs = Average H across the two popultionsTHEN – We need tp turn to finidng the expected H if this was one big connected popultion –> Do so by combing the allele frequncies and Calculate H as before - Now we need H if one popultions –> Exopected H based on the avwerage allele frequcnies across the popultions - Find H if you take an avergae of the allele frequncies - If we assume equal popultion size = combined allele frequencey os just the average of the two Find Average P = 0.35 + 0.8/ 2 = 0.575 –> combine the alelle frequncies if in one popultions - Average alelle freqincey (assuming that they have teh same p[opultion szie) – get alelle frequncey if they were one popultion - Means that if all of the indiovdiuals belongs to the same big popultion – the allele frequcney would be o = 0.575 –> now we can use this to calculate the expected H across all popultions THEN find H with teh Average P –> Ht = 0.489 (2 X 0.575 X 0.425) - Gives you the expected H across all popultions THEN – we can use these numbers to quantify the degree of magnbitude of genetic difference between the popuotions using FST index - Now look at the difference between the two - Divide by the total amount of varaition in popultionHs = should always be equal to or smallter than HtFST = Ht-Hs/HtFST = 0.489 - 0.388 = 0.489FST = 0.207
What does FST show
FSt = indicates how close the popultions are from having drifted to fized differences from each otherFST = between 0-1
Meaning of FST
FST = 0 –> No difference in allele frequncey between popultions - - Most of the varaition is within popultions –> there is little vraaition between popultions - Can teat as one population – little variation between subpopulations
FST = 1 – Popiultion is fixed for allele = ALl of the varaition is between popultions - All of the varaition is between the popultions – none of the varaition is within the popultion – all of the varaition is exists between popultoons
Why find FST
FST = used very often –> Why calculate it Example 1 – baer survivorship population - If we are hunting baers in Florida = we might wnat to know how they connected they are to baer popultion in other places –> if have differences = might have to say they are different BUT if FST = 0 –> They you can treat them at one population - Little genetic varaition between them = treat as one popultion Example 2 – Used in epidemialogy –> Have a certain parasite that causes disease - Have a parasite that causes diseae + a vector (Parasite gets to misquitos and masiquiotes infect people) –> If want to control the disease = might need to think about popultion of parasite + vesctor popultion - Might have 2 popultions a a new variant of drug resistant nematodes –> need to know how worries are you that they will go to the other popultion – might look at genetic differences between popultions + look for the same thing for masquitos - Quation = are they sepearet or is the FST LOW – Look to see IF the two popultions are genetically differemt IF FST is low = the popultions are more in contact with each other
How do we know drift acts in large popultoiomns
We know because we can see chnage in nuetral loci ***Drift in large popultions dirves constant change at nuetal loci If only selection = should only have to do with things that affect fitness but since doesn’t affect fitness = can’t be selection = we know drift cuases chnage in large popultions
Why should we care about dirft in a large popultions
For a long time they didn’t thnk drift was important in a large popultion THEN when looking at the molecular level = they found controdictions to idea that drift isn’t acting in large popultions When looking at the molecular level they found that most varaition within/between species = selectivley nuetral –> no affect on phenotype = can’t affect surviva/reproduction = not chnaging due to natural selection = due to something else causinhg nuetral to change
What did they find about drift when looking at the molecular level
When looking at the molecular level they found that most varaition within/between species = selectivley nuetral –> no affect on phenotype = can’t affect surviva/reproduction = not chnaging due to natural selection = due to something else causinhg nuetral to change
What do we focus on with drift
With drift we focus on neutrality at the molecular level
What kind of mutations are nuetral
Synonymous mutations – nutral mutation –> means you get the same Amino Acid Mutation were if you change nucleotide sequence = can still specify the same amino acid = the secondary and tertiary structure is the same = function is the same = change to DNA that can’t affect genotype - Still herediatry change in coding region
Most varaition within and between species
Sequence genome – variation = mostly changes that don’t affect phenotype –> changes that don’t affect Amino acid = don’t affect phenotypeA lot of varaition in protein coding regions = synonomous mutations (Within and among species)
Issue with nuetral varaition
How would this varaition build if Natural selection can’t see it (no difference in S/R if can’t make a phenotype) ANSWER: due to druft
Rate that neutral varaition builds
Constant rate – Nuetral varaition appears to build at a constant rateVaraition builds in clocklike reptative rate