preview what does recombination do to sequence histories. probabilities of such histories....
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Preview
What does Recombination do to Sequence Histories.
Probabilities of such histories.
Quantities of interest.
Detecting & Reconstructing Recombinations.
Haploid Reproduction Model (i.e. no recombination)
1 2 2N3
1 2 2N3
i. Individuals are made by sampling with replacement in the previous generation.
ii. The probability that 2 alleles have same ancestor in previous generation is 1/2N.
iii. The probability that k alleles have less than k-1 ancestors in previous generation is vanishing.
0 recombinations implies traditional phylogeny
4321
Diploid Model with Recombination
An individual is made by:
1. The paternal chromosome is taken by picking random father.
2. Making that father’s chromosomes recombine to create the individuals paternal chromosome.
Similarly for maternal chromosome.
A recombinant sequence will have have two different ancestor sequences in the grandparent.
The Diploid Model Back in Time.
The ancestral recombination graph
N1
Tim
e
1- recombination histories I: Branch length change
431 2
431 2 431 2
1- recombination histories II: Topology change
431 2
431 2 431 2
1- recombination histories III: Same tree
431 2
431 2 431 2
1- recombination histories IV: Coalescent time must be further back in time than recombination time.
3 41 2
c
r
Recombination Histories V: Multiple Ancestries.
Recombination Histories VI: Non-ancestral bridges
Summarising new phenomena in recombination-genealogiesConsequence of 1 recombination
Branch length change
Topology change
No change
Time ranking of internal nodes
Multiple Ancestries
Non-ancestral bridges
Recombination genealogies are called ”ancestral recombination graphs - ARGs”
What is the probability of different histories?
r recombination pr. Nucleotide pair pr.generation. L: seq. length
R = r*(L-1) Recombination pr. allele pr.generation. 2Ne - allele number
:= 4N*R -- Recombination intensity in scaled process.
Adding Recombination
sequence
time
Discrete timeDiscrete sequence
Continuous timeContinuous sequence
1/(L-1)
1/(2Ne)time
sequence
Recombination Event:
/2
Waiting time exp(/2)
Position Uniform
Recombination versus Mutation:
•As events, they are identically position and time wise.
•Mutations creates a difference in the sequence
•Recombination can create a shift in genealogy locally
Recombination-Coalescence Illustration Copied from Hudson 1991
Intensities
Coales. Recomb.
1 2
3 2
6 2
3 (2+b)
1 (1+b)
0
b
Age to oldest most recent common ancestor
From
Wi uf an
d H
ei n, 1999 G
eneti cs
Scaled recombination rate -
Age
to
old
est
mos
t re
c en
t co
mm
on a
nce
stor
0 kb 250 kb
Properties of Neighboring Trees.(partially from Hudson & Kaplan 1985)
Leaves Topo-Diff Tree-Diff2 0.0 .6663 0.0 .6944 0.073 .7145 0.134 .7286 0.183 .74010 0.300 .76915 0.374 .790
500 0.670
1 2 3 4 1 2 3 4
Grand Most Recent Common Ancestor: GMRCA(griffiths & marjoram, 96)
i. Track all sequences including those that has lost all ancestral material.
ii. The G-ARG contains the ARG. The graph is too large, but the process is simpler.
Sequence number - k.
Birth rate: *k/2
Death rate:
€
k
2
⎛
⎝ ⎜ ⎞
⎠ ⎟
1 2 3 k
E(events until {1}) = (asymp.) exp() + log(k)
Old +Alternative Coalescent Algorithm
Adding alleles one-by-one to a growing genealogy
1 1 2 31 231 2
Old
Spatial Coalescent-Recombination Algorithm(Wiuf & Hein 1999 TPB)
1. Make coalescent for position 0.0.
2. Wait Exp(Total Branch length) until recombination point, p.
3. Pick recombination point (*) uniformly on tree branches.
4. Let new sequence coalesce into genealogical structure. Continue 1-4 until p > L.
Properties of the spatial process
i. The process is non-Markovian
ii. The trees cannot be reduced to Topologies
* =
*
Compatibility 1 2 3 4 5 6 7
1 A T G T G T C
2 A T G T G A T
3 C T T C G A C
4 A T T C G T A
i i i
i. 3 & 4 can be placed on same tree without extra cost.
ii. 3 & 6 cannot.
1
4
3
2
Definition: Two columns are incompatible, if they are more expensive jointly, than separately on the cheapest tree.
Compatibility can be determined without reference to a specific tree!!
Hudson& Kaplan’s RM(k positions can at most have (k+1) types without recombination)ex. Data set:
A underestimate for the number of recombination events: ------------------- --------------- ------- --------- ------- -----
If you equate RM with expected number of recombinations, this would be an analogue to Watterson’s estimators. Unfortunately, RM is a gross underestimate of the real number of recombinations.
Myers-Griffiths’ RM
Basic Idea: 1 S
11 , jiB
55 , jiB44 , jiB
33 , jiB22 , jiB
positive 'r and s B'allfor so Minimize l,
11
1
sBrr ji
j
ill
S
ll ≥∑∑
−
=
−
=
Define R: Rj,k is optimal solution to restricted interval., then:
€
R j,k = max{R j,i + Bi,k : i = j, j +1,..k −1}
Bj,i
Rj,k
Rj,ij ki
Recombination Parsimony
1
2
3
T
i-1 i L21
Data
Trees
Recursion:W(T,i)= minT’{W(T’,i-1) + subst(T,i) + drec(T,T’)}
Initialisation:W(T,1)= subst(T,1)
W(T,i) - cost of history of first i columns if local tree at i is T
subst(T,i) - substitution cost of column i using tree T.
drec(T,T’) - recombination distance between T & T’
Metrics on Trees based on subtree transfers.
Trees including branch lengths
Unrooted tree topologies
Rooted tree topologies
Tree topologies with age ordered internal nodes
Pretending the easy problem is the real problem, causes violation of the triangle inequality:
Observe that the size of the unit-neighbourhood of a tree does not grow nearly as fast as the number of trees.
Allen & Steel (2001)
Song (2003) Explicit computation
No known formula
The 1983 Kreitman Data(M. Kreitman 1983 Nature from Hartl & Clark 1999)
Methods # of rec events obtained
Hudson & Kaplan (1985) 5
Myers & Griffiths (2002) 6
Song & Hein (2002). Set theory based approach. 7
Song & Hein (2003). Current program using rooted trees. 7
• 11 sequences of alcohol dehydrogenase gene in Drosophila melangaster. Can be reduced to 9 sequences (3 of 11 are identical).• 3200 bp long, 43 segregating sites.
We have checked that it is possible to construct an ancestral recombination graph using only 7 recombination events.
1
2
3
4
56
7
Quality of the estimated local tree
True ARG
Reconstructed ARG
1 2 3 4 5
1 23 4 5
(1,2) - (3,4,5)
(1,2,3) - (4,5)
(1,3) - (2,4,5)(1,2,3) - (4,5)
n=7
Rho=10
Theta=75
Due t o Y
un Song
Actual, potentially detectable and detected recombinations
1 2 3 4 1 2 3 4
True ARG
Minimal ARG
0400 kb
n=8
=15
=40
Leaves Topo-Diff Tree-Diff2 0.0 .6663 0.0 .6944 0.073 .7145 0.134 .7286 0.183 .74010 0.300 .76915 0.374 .790
500 0.670
Due t o Y
un Song
s1 =
s2 =
s3 =
s4 =
s5 =
0 0 0 0
0 0 1 1
0 1 0 1
1 1 0 0
1 1 1 1 1
2
3
00000011010111001111
1
000000xxxx11010111001111
2
000000xx010111001111
3
Ancestral states
Yun Song
1st
2nd
Ancestral configurations to 2 sequences with 2 segregating sites:
k1
k2
(k2+1)*k1 +1 possible ancestral columns.
• Asymptotic growth?• Enumerating ancestral states in minimal histories?• Branch and bound method for computing the likelihood?
Enumeration of Ancestral States(via counting restricted non-negative integer matrices with given row and column sums)
Due to Yun Song
Ignoring recombination in phylogenetic analysis
Mimics decelerations/accelerations of evolutionary rates.
No & Infinite recombination implies molecular clock.
General Practice in Analysis of Viral Evolution!!!Recombination Assuming No Recombination
1 432 1 4 32
Simulated Example
Gene Conversion
Recombination: Gene Conversion:
Compatibilities among triples:
+
- -
Gene Conversions & Treeness
Pairwise Distances as sequences gets longer and longer
Recombination Gene Conversion
Coalescent:Star tree:
Summary
What does Recombination do to Sequence Histories.
Probabilities of such histories.
Quantities of interest.
Detecting & Reconstructing Recombinations.