Polymorphism Structure of the Human Genome Gabor T. Marth Department of Biology Boston College Chestnut Hill, MA 02467

Human variation structure is heterogeneous chromosomal averages polymorphism density along chromosomes

Heterogeneity at the level of distributions “sparse” “dense” marker density “rare” “common” allele frequency

What explains nucleotide diversity? G+C nucleotide content CpG di-nucleotide content recombination rate functional constraints 3’ UTR5.00 x ’ UTR4.95 x Exon, overall4.20 x Exon, coding3.77 x synonymous 366 / 653 non-synonymous287 / 653 Variance is so high that these quantities are poor predictors of nucleotide diversity in local regions hence random processes are likely to govern the basic shape of the genome variation landscape  (random) genetic drift

Components of drift: Genealogy present generation randomly mating population, genealogy evolves in a non- deterministic fashion

Components of drift: Mutation mutation randomly “drift”: die out, go to higher frequency or get fixed

Modulators: Changing population size mutation randomly “drift”: die out, go to higher frequency or get fixed genetic bottleneck

Modulators: Population subdivision subdivision subdivision promotes private polymorphisms, and skews allele frequency

Modulators: Recombination accgttatgcaga acagttatgtaga acagttatgcaga accgttatgtaga accgttatgcagaacagttatgtaga recombination different nucleotide sites within the same DNA segment no longer share the same genealogy

Modulators: Natural selection negative (purifying) selection positive selection the genealogy is no longer independent of (and hence cannot be decoupled from) the mutation process

Modeling ancestral processes “forward simulations” the “Coalescent” process By focusing on a small sample, complexity of the relevant part of the ancestral process is greatly reduced. There are, however, limitations.

Inferences from variation data larger population size (N) -> more mutations -> higher diversity (θ) larger mutation rate (μ) -> more mutations -> higher diversity (θ) higher diversity -> larger population size OR higher mutation rate (θ = 4Nμ)

Ancestral inference: modeling past present stationaryexpansioncollapse MD (simulation) AFS (direct form) history bottleneck

Ancestral inference: model fitting bottleneck modest but uninterrupted expansion

Allelic association accgttatgcaga acagttatgtaga acagttatgcaga accgttatgtaga possible allele combinations (2-marker haplotypes) higher recombination rate (r)

Allelic association: LD measure of allelic association: “linkage disequilibrium (LD)”

Haplotype structure “haplotype block”