DNA Insertions and Deletions in the Human Genome. Philipp W. Messer



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Transcription:

DNA Insertions and Deletions in the Human Genome Philipp W. Messer

Genetic Variation CGACAATAGCGCTCTTACTACGTGTATCG : : CGACAATGGCGCT---ACTACGTGCATCG 1. Nucleotide mutations 2. Genomic rearrangements 3. DNA insertions / deletions (indels)

Outline 1. Origin and characteristics of indels 2. Indels in protein-coding regions 3. Duplications and genomic correlations 4. Duplications and alignment scores

Part 1 Origin and Characteristics of Indels in the Human Genome [Messer and Arndt, Mol Biol Evol 2007]

Identifying Insertions/Deletions Time ~5 Myr Human Chimp Rhesus High-quality flanks H:..ATACCTCGTACAATAGCGCTGGTACAGATA.. C:..ATACCTCGTACAAT--CGCTGGTACAGGTA.. R:..ATACCTCGTACAAT--CGCTGCTACAGATA.. Insertions can be distinguished from deletions (parsimony)

Insertion/Deletion Statistics Insertions: ~250 000 events 15% SSR Deletions: ~450 000 events 5% SSR

Molecular Mechanisms 1. Unequal Crossing Over (UCO) nonhomologous recombination 2. Replication Slippage (RS) slipped-strand mispairing

Indel Signatures for UCO and RS Insertions: Tandem duplications of preexisting duplicates Deletions: Remove one copy of preexisting duplicates

trace extension d insertion length l

Indel Trace Extensions UCO, RS (insertion) UCO, RS (deletion) Tandem duplication Random indel

Measured Trace Extensions (l=8 bp)

Chromosomal Rate Differences 800 Rates (bp / Mbp) 600 400 200 Autosomes Chr X Chr Y 0 Insertions Deletions 1. Indels occur preferentially in the male germline 2. Indels are not recombination-mediated

Indel Characteristics 1. The majority of insertions are tandem duplications 2. Long preexisting duplicates are often missing 3. Indels occur preferentially in the male germline 4. Indels are not recombination-mediated

Nonhomologous End Joining DNA break End joining Small or no homology required Filling in of single strands

Part 2 Indels in Protein-coding Regions of the Human Genome [Chaux, Messer, Arndt, BMC Evol Biol (submitted)]

Indel Rates in Coding Regions

Genetic Code

Inserted/Deleted Amino Acids

Physico-chemical Properties

Physico-chemical Properties suppressed intensified

Protein Secondary Structure suppressed

Part 3 Tandem Duplications and Genomic Correlations [Messer, Arndt, Lässig, Phys Rev Lett 2005] [Messer, Lässig, Arndt, J Stat Mech 2005] [Messer, Arndt, Nucleic Acid Res 2006]

Sequence Evolution Model Mutation Segmental Duplication length l A C A A G T C C A rate µ rate δ l A T A A G T C C AGA T C C A Random Insertion Segmental Deletion length l A T T G T C C A rate γ l + rate γ l - A GA G A C T T A length l

The Correlation Function Measures likelihood of finding two G/C base pairs separated by a distance r along the genome ( ) = (, + ) 2 ( ) C r P x x r P x G/C G/C G T A T G A T C G A G A A Position: x x+r

Types of Correlation Behavior Random sequence Local correlations Long-range correlations Cr () 0 ( r r) Cr () exp / 0 Cr () r α Noise fluctuations Characteristic scale Generated e.g by Markov-processes Scale free, fractal Generated by a nontrivial dynamical model

Calculation of C(r) for Our Model Approach: continuous time Master Equation formalism Exact equation for the dynamics of C(r) Stationary solution in a continuum limit: C( r) r α with α = 4µ eff λ

Correlations in Genomic DNA Cr () r α distance r distance r correlation C(r) correlation C(r)

Part 4 Tandem Duplications and Alignment Score Statistics [Messer, Bundschuh, Vingron, Arndt, RECOMB 2006] [Messer, Bundschuh, Vingron, Arndt, JCB 2007]

Alignment Score Statistics Sequence alignment Seq1: ACCTAGTGCTA Significance Seq2: ATCTAGTGATA P-values of scores Requires DNA null model Standard iid model Problem Score distribution in the null model iid model correlated model Correlations in DNA Incorporate into null model P-values change e λs

Gaussian Approximation Analytic approach to calculate alignment score statistics for null models with LRC sequences, i.e. C(r) r -α 2 s λ = σ 2 + c ζ (2 α ) vanishes for iid sequences LRC s increases probability of finding high alignment scores by chance

Numerical Verification Score distribution Decay parameter λ lrc (α=0.5) lrc (α=1.0) iid Gaussian approximation captures qualitative behavior

Biological Significance Alignment of random sequences with same correlation parameters as human chr. 22 λ iid 1.37 λ lrc 1.21 P lrc 3x10-5 P iid 2x10-6 Difference in λ is approx.16 %, p-value increase > 10 x

Summary 1. The majority of short DNA insertions are tandem duplications 2. Amino acid insertions/deletions are less deleterious than substitutions 3. Tandem duplications cause long-range correlations in genomic base composition 4. These correlations have profound impact on the statistics of sequence alignment scores

Acknowledgments Peter Arndt Nicole de la Chaux Paz Polak Federico Squartini Ralf Bundschuh Michael Lässig Martin Vingron