ch 4: population subdivisionpeople.bu.edu/msoren/bi515_2014/lecture10.pdf · 2014-10-08 · 10/8/14...
TRANSCRIPT
![Page 1: Ch 4: Population Subdivisionpeople.bu.edu/msoren/BI515_2014/Lecture10.pdf · 2014-10-08 · 10/8/14 15 Nm = 1 corresponds to F ST = 0.2! Wright (1978) " F ST = 0.05 to 0.15 - “moderate](https://reader033.vdocument.in/reader033/viewer/2022042918/5f5d349ca6af1a51b2297075/html5/thumbnails/1.jpg)
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Ch 4: Population Subdivision
Population Structure
v most natural populations exist across a landscape (or seascape) that is more or less divided into areas of suitable habitat
v to the extent that populations are isolated, they will become genetically differentiated due to genetic drift, selection, and eventually mutation
v genetic differentiation among populations is relevant to conservation biology as well as fundamental questions about how adaptive evolution proceeds
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Definitions
v panmixia v population structure v subpopulation v gene flow v isolation by distance v vicariance (vicariant event)
Structure Results in “Inbreeding”
v given finite population size, autozygosity gradually increases because the members of a population share common ancestors ² even when there is no close
inbreeding
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“Identical by Descent”
v what is the probability that two randomly sampled alleles are identical by descent (i.e., “replicas of a gene present in a previous generation”)? ² Wright’s “fixation index” F
v at the start of the process (time 0), “declare” all alleles in the population to be unique or unrelated, Ft = 0 at t = 0
v in the next generation, the probability of two randomly sampled alleles being copies of the same allele from a single parent = 1/(2N), so…
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€
or
Ft =1- 1−12N
#
$ %
&
' ( t
“Identical by Descent”
€
Ft =12N
+ 1− 12N
#
$ %
&
' ( Ft−1
= probability that alleles are copies of the same gene from the immediately preceding generation plus the probability that the alleles are copies of the same gene from an earlier generation
assuming F0 = 0
compare to: mean time to fixation for new mutant = ~4N
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v Suppose multiple subpopulations:
Overall average allele frequency stays the same but heterozygosity declines
Predicted distributions of allele frequencies in replicate populations of N = 16
same process as in this figure…
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Population Structure
v Ft for a single population is essentially the same thing as FST ² a measure of genetic differentiation among
populations based on the reduction in heterozygosity
v due to increasing autozygosity, structured populations have lower heterozygosity than expected if all were combined into a single random breeding population
Aa = 0
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FST
v measures the deficiency of heterozygotes in the total population relative to the expected level (assuming HWE)
v in the simplest case, one can calculate FST for a comparison of two populations…
FST =HT −HS
HT
Two population, two allele FST
Frequency of "A"
Popula2on 1 Popula2on 2 HT HS FST 0.5 0.5 0.5 0.5 0
0.4 0.6 0.5 0.48 0.04
0.3 0.7 0.5 0.42 0.16
0.2 0.8 0.5 0.32 0.36
0.1 0.9 0.5 0.18 0.64
0.0 1.0 0.5 0 1
0.3 0.35 0.43875 0.4375 0.002849
0.65 0.95 0.32 0.275 0.140625
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FST - Whalund Effect
v Whalund principle - reduction in homozygosity that results from combining differentiated populations
0
0.1
0.2
0.3
0.4
0.5
0.6
0 0.2 0.4 0.6 0.8 1 0
0.1
0.2
0.3
0.4
0.5
0.6
0 0.2 0.4 0.6 0.8 1 0
0.1
0.2
0.3
0.4
0.5
0.6
0 0.2 0.4 0.6 0.8 1
Frequency of heterozygotes in the combined population is higher than the average of the separate populations (0.42 > 0.40)
FST =HT −HS
HT
=0.42− 0.400.42
= 0.0476
FST =var(p)pq
=0.010.21
= 0.0476
Allele Frequency
He
tero
zyg
osit
y
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FST - Whalund Effect
v Whalund principle - reduction in homozygosity due to combining differentiated populations ² R = frequency of homozygous recessive
genotype
€
Rseparate − Rfused =q12 + q2
2
2− q 2
=12q1 − q( )2 + 1
2q2 − q( )2
€
=σ q2
FST - Whalund Effect (Nielsen & Slatkin)
fA =2N1 fA1 + 2N2 fA2
2N1 + 2N2
≡ fA =fA1 + fA2
2
HS =2 fA1 1− fA1( )+ 2 fA2 1− fA2( )
2= fA1 1− fA1( )+ fA2 1− fA2( )
HT = 2 fA1 + fA2
2#
$%
&
'( 1− fA1 + fA2
2#
$%
&
'(= fA1 1− fA1( )+ fA2 1− fA2( )+ δ
2
2where δ = fA1 − fA2
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FST over time w/ no migration
Ft=12N
+ 1− 12N
"
#$
%
&'Ft−1
Ft =1− 1−12N
"
#$
%
&'t
≈1− e−12N
t
FST ≈1− e−12N
t
FST increases with time due to genetic drift in exactly the same way as
Ft
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Migration
v migration between populations results in gene flow, which counters the effects of genetic drift (and selection) and tends to homogenize allele frequencies
v what level of migration is sufficient to counter the effects of genetic drift? ² Nm ~ 1
v what level of migration is sufficient to counter the effects of selection? ² m > s
The Island Model
assumptions: v equal population
sizes v equal migration
rates in all directions
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Equilibrium value of FST
v change in Ft with migration
€
Ft =12N"
# $
%
& ' 1−m( )2 + 1− 1
2N"
# $
%
& ' 1−m( )2Ft−1
€
setting ˆ F = Ft = Ft−1
€
some algebra + ignoring terms in m2 and m/N ...
F̂ ≈ 11+ 4Nm
Equilibrium value of FST
F̂ ≈ 11+ 4Nm
€
Nm =1
Fig. 4.5, pg. 69
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Migration rate vs. Number of migrants
v migration rates yielding Nm = 1 ² Ne = 100, m = 0.01
² Ne = 1000, m = 0.001
² Ne = 10000, m = 0.0001
² Ne = 100000, m = 0.00001
Equilibrium value of FST
mtDNA or y-chromosome
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FST over time w/ no migration
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
0 5000 10000 15000
mtDNA or y-chromosome
autosomal loci
Nm = 1 corresponds to FST = 0.2
v Wright (1978) ² FST = 0.05 to 0.15 - “moderate differentiation” ² FST = 0.15 to 0.25 - “great genetic differentiation” ² FST > 0.25 - “very great genetic differentiation”
€
Nm =1
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Nm = 1 corresponds to FST = 0.2
v Wright (1978) ² FST = 0.05 to 0.15 - “moderate differentiation” ² FST = 0.15 to 0.25 - “great genetic differentiation” ² FST > 0.25 - “very great genetic differentiation”
v populations of most mammalian species range from FST = 0.1 to 0.8
v humans: ² among European groups: 0 to 0.025 ² Among Asians, Africans & Europeans: 0.05 to 0.2
FST
v theoretical maximum is 1 if two populations are fixed for different alleles
v but, there are some issues… v fixation index developed by Wright in
1921 when we knew essentially nothing about molecular genetics ² two alleles at a locus (with or w/o
mutation between them) was the model
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FST versus GST
v FST – derived by Wright as a function of the variance in allele frequencies
v GST – derived by Nei as a function of within and among population heterozygosities
GST =HT −HS
HT
=1− HS
HT
"
#$
%
&'
FST =var(p)pq
GST with multiple alleles v microsatellite loci, for example, may have
many alleles in all subpopulations
v FST can not exceed the average level of homozygosity (1 minus heterozygosity)
GST =1−HS
HT
<1−HS
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Balloux et al. 2000 Evolution
GST ~ 0.12
GST =HT −HS
HT
Hedrick (2005) Evolution
v a standardized genetic distance measure for k
populations: G’ST
v where:
€
GST (Max) =HT (Max) −HS
HT (Max)€
GST' =
GST
GST (Max)
=GST k −1+ HS( )k −1( ) 1−HS( )
€
HT (Max) =1− 1k 2
pij2
j∑
i∑and
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Allele 1 2 1 21 0.1 — 0.1 —2 0.2 — 0.2 —3 0.2 — 0.2 0.14 0.2 — 0.2 0.25 0.2 — 0.2 0.26 0.1 — 0.1 0.27 — 0.1 — 0.28 — 0.2 — 0.19 — 0.2 — —
10 — 0.2 — —11 — 0.2 — —12 — 0.1 — —
HS HS
HT HT
FST (GST) FST (GST)HT(max) HT(max)
GST(max) GST(max)
G'ST G'ST
0.0991 0.357
0.099
Subpopulation Subpopulation
0.9100.0350.8500.8200.820
0.9100.0990.910
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Coalescent-based Measures
v Slatkin (1995) Genetics
v where T and TW are the mean coalescence times for all alleles and alleles within subpopulations
FST =T −TWT
TW = 2Ned
TB = 2Ned +d −12m
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RST for microsatellites
v under a stepwise mutation model for microsatellites, the difference in repeat number is correlated with time to coalescence
v where S and SW are the average squared difference in repeat number for all alleles and alleles within subpopulations
v violations of the stepwise mutation model are a potential problem
€
RST =S - SW
S
ΦST for DNA sequences
v the number of pairwise differences between two sequences provides an estimate of time to coalescence
v method of Excoffier et al. (1992) takes into account the number of differences between haplotypes
v Arelquin (software for AMOVA analyses) calculates both FST and ΦST for DNA sequence data ² important to specify which one is calculated