Recombination, and haplotype structure

1
Recombination, and haplotype structure

• Simon Myers, Gil McVean
• Department of Statistics, Oxford

2
The starting point

• We have a genomes worth of data on genetic
  variation
• We wish to understand why the haplotype structure
  looks how it does
• Differences between regions, populations

3
Where do haplotypes come from?

• In the absence of recombination, the most natural
  way to think about haplotypes is in terms of the
  genealogical tree representing the history of the
  chromosomes
• Tree affects mutation patterns
• Mutation patterns give information on tree

4
What determines the shape of the tree?
Present day
5
Ancestry of current population
Present day
6
Ancestry of sample
Present day
7
The coalescent a model of genealogies
Most recent common ancestor (MRCA)
coalescence
Ancestral lineages
Present day
time
8
Simulating histories with the coalescent
9
Simulating data with the coalescent
10
Haplotype structure in the absence of
recombination

• In the absence of recombination, the shape of the
  tree and where mutations fall on it determine
  patterns of haplotype structure
• Two mutations on the same branch will be in
  complete association, mutations on different
  branches will have lower and often low association

11
Haplotypes when there is recombination

• When there is no recombination, haplotype
  structure reflects the age distribution of
  mutations and the shape of the underlying tree
• When there is some recombination, every
  nucleotide position has a tree, but the tree
  changes along the chromosome at a rate determined
  by the local recombination landscape
• By using SNP information to inform us about the
  trees, we can learn about how quickly the trees
  changes
• This relates to the recombination rate

12
A bit of recombination shuffles genetic
variation
13
Lots of recombination does lots of shuffling
14
Recombination and haplotype diversity

• Without recombination, a new mutation can create
  at most one new haplotype
• Any two mutations delineate at most 3 haplotypes
  in total (ancestral, plus two new types)
• With recombination, this mutation can spread onto
  every existing haplotype background, creating the
  potential for more haplotypes
• For a given number of SNPs a region with
  recombination will tend to have (in comparison to
  a region with no recombination)
• More haplotypes
• Less variance in the pairwise differences between
  haplotypes
• Less skewed haplotype frequencies

15
The ancestral recombination graph

• The combined history of recombination, mutation
  and coalescence is described by the ancestral
  recombination graph

Event
Coalescence
Mutation
Coalescence
Coalescence
Mutation
Coalescence
Recombination
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In humans, recombination is not uniformly
distributed

• Most recombination occurs in recombination
  hotspots short (1-2kb) regions every 50-100kb
  that occupy at most 3 of the genome but probably
  account for 90 or more of the recombination
• This means that haplotype structure in humans is
  an interesting hybrid between the no
  recombination and lots of recombination situations

17
Learning about recombination

• Just like there is a true genealogy underlying a
  sample of sequences without recombination, there
  is a true ARG underlying samples of sequences
  with recombination
• We can consider nonparametric and parametric ways
  of learning about recombination
• There are useful nonparametric ways of learning
  about recombination which we will consider first
• These really only apply to species, such as
  humans, where we can be fairly sure that most
  SNPs are the result of a single ancestral
  mutation event

18
The signal of recombination?
Ancestral chromosome recombines
Recurrent mutation
Recombination
19
Detecting recombination from DNA sequence data

• Look for all pairs of incompatible sites
• Find minimum number of intervals in which
  recombination events must have occured (Hudson
  and Kaplan 1985) Rm

20
Improving the detection algorithm

• Rm greatly underestimates the amount of
  recombination in the history of a set of
  sequences
• Myers and Griffiths (2003) developed an improved
  way of detecting recombination events
• Without recombination, every new mutation can
  create only a single new haplotype
• With recombination, mutations can be shuffled
  between haplotype background, generating
  haplotype diversity
• Each recombination makes at most one new
  haplotype
• If I see H haplotypes with S segregating sites,
  at least H-S-1 recombination events must have
  occurred
• This offers potential to identify many more
  recombination events
• Carefully combine bounds from different
  collection of sites
• Dynamic programming algorithm makes computation
  extremely fast
• Better (sometimes slower) algorithms developed
  recently

21
Problems with counting recombination events
Tree-pairs where we cannot see recombination
events
A tree-pair where we could see recombination
events, but dont
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Modelling recombination

• Model-based approaches to learning about
  recombination allow us to ask more detailed
  questions than nonparametric approaches
• What is the rate of recombination (as opposed to
  just the number of events)
• Does gene A have a higher recombination rate than
  gene B?
• Is the rate of recombination across a region
  constant?
• Where are the recombination hotspots?
• We can use coalescent model approaches
  (approximations) to calculating the likelihood of
  arbitrary recombination maps given observed data

23
Fitting a variable recombination rate

• Use a reversible-jump MCMC approach (Green 1995)

SNP positions
Cold
Split blocks
Hot
Merge blocks
Change block size
Change block rate
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Acceptance rates
Ratio of priors
Composite likelihood ratio
Hastings ratio
Jacobian of partial derivatives relating changes
in dimension to sampled random numbers

• Include a prior on the number of change points
  that encourages smoothing

25
Strong concordance between fine-scale rate
estimates from sperm and genetic variation
Rates estimated from genetic variation McVean et
al (2004)
26
Inferring hotspots

• We perform a statistical test for hotspot
  presence
• Based on an approximation to the coalescent
  similar to that used for rate estimation
• All previously identified hotspots are 1-2kb in
  size
• At a position in genome, consider where 2kb
  hotspot might be present
• Fit a model with hotspot
• Fit one without
• Compare in terms of (approximate) likelihood
  ratio test
• Evaluate significance via simulation
• When p-value below threshold, declare a hotspot

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Rates and hotspots across the human genome
Hotspots throughout human genome (35,000
identified)
From Myers et al. (2005)
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Applications of recombination approaches to real
data

• Rates and hotspots across the human genome (Myers
  et al. 2005)
• Previously, no understanding of why hotspots
  localise where they do
• Can 35,000 hotspots, accounting for gt50 of human
  recombination, help?
• Comparison of recombination rates (Winckler et
  al. 2004, Ptak et al. 2005)
• Between humans and chimpanzees
• At individual recombination hotspots
• Understanding genomic rearrangements (Myers et
  al., submitted!)
• Cause a number of genomic disorders
• Relationship to recombination hotspots

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32,996 Phase II HapMap hotspots
Estimated 50-70 of all human recombination Hotspo
ts on all chromosomes, including X
THE1B (LTR of retrotransposon)
20,000 hotspots localised to within 5kb
THE1B Found in 1196 hotspots versus 606
coldspots (pltlt10-20) AluY Found in 3635
hotspots versus 3262 coldspots (p7x10-5)
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THE1 consensus
...CTTCCGCCATGATTGTGAGGCCTCCCCAGCCATGTGGAACTGTGAGT
CCATT...
CCTCCCTAGCCAC
(n165)
CCNCCNTNNCCNC
(n263)
CCTCCCCNNCCAT
(n10,690)
3-4 of hotspots
L2 consensus
...TGTCACCTCCTCAGAGAGGCCTTCCCTGACCACCCTATCTAAAATWG
CACACC...
CCTCCCTGACCAC
(n157)
CCNCCNTNNCCNC
(n6,901)
CTTCCCTNNCCAC
(n1,211)
3-4 of hotspots
AluY, AluSc, AluSg consensus
...CTCCTGACCTCGTGATCCGCCCGCCTCGGCCTCCCAAAGTGCTGGGA
TTACAG...
CCGCCTTGGCCTC
(n14,028)
CCNCCNTNNCCNC
(n15,706)
CCGCCTCNNCCTC
(n55,916)
3-4 of hotspots, including DNA3
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Human hotspot motifs

• In humans, specific words produce recombination
  hotspot activity
• Hotspot motif CCTCCCTNNCCAC (plt10-33)
• Raises probability of a hotspot across genetic
  backgrounds
• Degenerate versions CCNCCNTNNCCNC and truncated
  CCTCCCT also raise probability, to lesser extent
• Motif explains 40 of human hotspots
• Operates in both sexes
• We dont know, very clearly, which hotspots
• On THE1 background, hotspot 70-80 of time!
• Biology not clearly understood
• We identified a second, different hotspot motif
  (the best 9bp motif), CCCCACCCC, also by
  comparison of hot and cold regions of the genome

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Variation in individual hotspots
Sequence variation affects recombination at DNA2
(Jeffreys and Neumann, Nature Genetics 2002)
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SNPs disrupting hotspots disrupt motifs!

• DNA2
• NID1

Jeffreys and Neumann (Nature Genetics 2002, Hum
Mol. Evol. 2005)
AAAAGACAGCCTCCCTGTTGCTGC
Hot
AAAAGACAGCCCCCCTGTTGCTGC
Cold
Hot
CACCCCCCACCCCACCCCAACATA
CACCTCCCACCCCACCCCAACATA
Cold
34
SNPs disrupting hotspots disrupt motifs

• DNA2
• NID1

Jeffreys and Neumann (Nature Genetics 2002, Hum
Mol. Evol. 2005)
AAAAGACAGCCTCCCTGTTGCTGC
Hot
AAAAGACAGCCCCCCTGTTGCTGC
Cold
Disruption of CCTCCCT, best 7bp motif
Hot
CACCCCCCACCCCACCCCAACATA
CACCTCCCACCCCACCCCAACATA
Cold
Disruption of CCCCACCCC, best 9bp motif
35
Role of motif in X-linked ichthyosis
VCX2
1/5000 births

• The 1kb deletion hotspot contains 25 repeats of
  CCTCCCTNNCCAC
• Highest motif density in any LCR in entire
  genome
• Strongly implicates motif in producing hotspot
• Points to a link between deletion-causing and
  normal recombination

36
A more general link?

• Many other diseases are caused by
  recombination-mediated deletions and duplications
  (NAHR)
• Smith-Magenis syndrome (hotspot)
• CMT1A (hotspot)
• NF1 microdeletion syndrome (hotspot)
• DiGeorge syndrome.
• Two recent studies suggest normal hotspots and
  hotspots of disease-causing deletion may coincide
• de Raedt, Stephens et al. (Nature Genetics, 2006)
• Two NF1 deletion hotspots both likely to coincide
  with crossover hotspots

37
Other major NAHR hotspots
CCNCCNTNNCCNC overrepresented in hotspots
p0.0006
38
Evolution of recombination human vs. chimps
LDhot hotspots
Human
Chimp
LDhat rate estimates
No significant correlation in hotspots positions
between species (Winckler et al. Science 2005,
Ptak et al. Nature Genetics 2005)
39
Reading

• Haplotype structure and recombination
• The International HapMap Consortium A haplotype
  map of the human genome. Nature 2005,
  4371299-1320.
• McVean G, Spencer CCA, Chaix R Perspectives on
  human genetic variation from the International
  HapMap Project. PLoS Genetics 2005, 1e54.
• Myers S, Bottolo L, Freeman C, McVean G, Donnelly
  P A fine-scale map of recombination rates and
  recombination hotspots in the human genome.
  Science 2005, 310321-324.
• The coalescent
• Nordborg M Coalescent Theory. In The Handbook
  of Statistical Genetics (eds Balding, Bishop and
  Cannings), 2001. Wiley Sons.
• Hudson RR Gene genealogies and the coalescent
  process. In Oxford Surveys in Evolutionary
  Biology (eds Futuyama and Antonovics) 1990,
  7144. Oxford University Press.

40
Selected references

• - Jeffreys, A.J., L. Kauppi, and R. Neumann.
  2001. Intensely punctate meiotic recombination in
  the class II region of the major
  histocompatibility complex. Nat Genet 29
  217-222.
• - Jeffreys, A.J. and R. Neumann. 2002. Reciprocal
  crossover asymmetry and meiotic drive in a human
  recombination hot spot. Nat Genet 31 267-271.
• Jeffreys, A.J. and R. Neumann. 2005. Factors
  influencing recombination frequency and
  distribution in a human meiotic crossover
  hotspot. Hum Mol Genet 14 2277-2287.
• Myers, S., L. Bottolo, C. Freeman, G. McVean,
  and P. Donnelly. 2005. A fine-scale map of
  recombination rates and hotspots across the human
  genome. Science 310 321-324.
• Ptak, S.E., D.A. Hinds, K. Koehler, B. Nickel,
  N. Patil, D.G. Ballinger, M. Przeworski, K.A.
  Frazer, and S. Paabo. 2005. Fine-scale
  recombination patterns differ between chimpanzees
  and humans. Nat Genet 37 429-434.
• The International HapMap Consortium. 2005. A
  haplotype map of the human genome. Nature 437
  1299-1320.
• The International HapMap Consortium. 2007. The
  Phase II HapMap. Nature
• - Winckler, W., S.R. Myers, D.J. Richter, R.C.
  Onofrio, G.J. McDonald, R.E. Bontrop, G.A.
  McVean, S.B. Gabriel, D. Reich, P. Donnelly et
  al. 2005. Comparison of fine-scale recombination
  rates in humans and chimpanzees. Science 308
  107-111.