Are we still evolving? Mapping sites of selection in the human genome Simon Myers

Targets of selection are important Humans Other species What makes us human? (FOXP2, gene loss) Resistance to pesticides Understand how we adapt to our environment Diet (Lactase, amylase) Mating success Physical environment (SLC24A5, EDAR…) Disease (LARGE, Duffy,…) ?? Pathogen evolution What parts of our genome are functional? (Genes, regulatory regions, siRNAs,….)

Adaptive evolution Time Advantagous mutations arise by chance Once arisen, carriers have more offspring “Positive selection” On average, higher rate of change towards advantageous mutations

Looking for positive selection Direct approach is very difficult –Need to observe trait for long time –Need very strong selection In many cases, need a more indirect approach –Compare genomes among closely related species –Look for “accelerated evolution” –Current day patterns of diversity –Look for “signature of selection”

FOXP2 Gene coding for a transcription factor Mutations in this gene cause speech impairment and other problems (Lai et al., Nature 2001) –Mutation in FOXP2 co-segregates with a disorder in a family in which half of the members have severe speech, linguistic and grammatical difficulties –Translocation in same gene in unrelated individual with similar disorder Are changes in this gene associated with human language development?

Yellow: human lineage mutations (since chimpanzee-human split) Blue: mutations on all other lineages Very conserved gene (top 5% of 1,880 genes) Only 3 non-repeat amino acid changes in 130 million years between human and mouse 2 occurred on human lineage in last 5-6 million years FOXP2 (Enard et al., Nature 2002)

156 synonymous changes, 0 on human lineage 4 non-synonymous changes 2 on human lineage (p= by Fishers exact test) FOXP2 (Enard et al., Nature 2002)

Gene loss CMAH: Loss of enzymes that transform sialic acid –Sugar on cell surface that mediates a variety of recognition events involving pathogenic microbes and toxins Myosin heavy chain –Reduces masticatory muscles? –Associated with gracilization KRTHAP1: –Hair keratin Wang et al (2006)

Is this the answer? Comparative genomics has disadvantages –Need repeated mutations to give power –Tells little about the timescale –Recent research suggests Neanderthals may share FOXP2 mutations with humans (Krause et al., Current Biology 2007) How do we find out if, and where, we’re currently evolving?

Looking for positive selection Direct approach is difficult –Need to observe trait for long time In many cases, need a more indirect approach –Compare genomes among closely related species –Look for “accelerated evolution” –Current day patterns of diversity –Look for “signature of selection”

Variation data and selection Revolution in population genetics Genome-wide datasets –HapMap project –Many unrelated individuals (60 CEU, 60 YRI, 45 JPT and 45 CHB) –Typed at ~4,000,000 loci that vary within population Allow systematic searches for selection –Comparison of interesting regions to genome –Identification of novel candidates for selection

Neutral alleles III III Neutral allele arises Neutral variation Recombination scrambles variation over time e.g. HapMap

The signature of positive selection III III Advantageous allele arises Neutral variation Spreads (sweeps) rapidly through population Recombination has much less time to scramble variation on selected background

The signature of positive selection Neutral mutation at 50% Selected mutation at 50% SelSim (Spencer and Coop, Bioinformatics 2004)

EHH Several authors have developed tests based on similar idea –Sabeti et al. (Nature 2002) –Focus on potentially selected mutation –Measure proportion of haplotypes identical, as a function of distance on either side –Compare selected/nonselected types –Look for signal of “extended haplotype homozygosity” (EHH)

Simulation results (Voight et al.,PloS Biology 2006)

Lactase gene –70% of all humans are lactose intolerant –In Europe, 95% lactose tolerance

Lactase gene DNA variant C/T kb upstream of Lactase gene Predicts lactose persistance (Enattah et al., Nature Genetics 2002) Mutation enhances promoter activity, so probably causal (Olds et al. Hum. Mol. Genet. 2003) Other mutations exist in some groups

EHH around Lactase From Bersaglieri et al. (AJHG, 2004)

EHH around Lactase 5’: p=.012 3’: p<0.0004

From the HapMap paper (Nature, 2005) Human evolution in action Infection by Lassa virus Malaria resistance

A complimentary approach SNPs that are at highly different frequencies across populations are excellent candidates for selection –EDAR (hair follicle development, HapMap paper, Sabeti et al. Nature 2007) –SLC24A5, SLC45A2 (HapMap paper, Lamason et al. Science 2005) –Explored in practical Non-synonymous SNP in FY gene

Conclusions Population genetics provides diverse information about molecular evolution Combining population genetics with knowledge of genomic sequence –New insights into adaptive evolution –Evolution is ongoing, and influenced by local environment –Limited power means we will probably never find all sites of selection Avalanche of variation data being gathered –Will bring many more insights –Presents major challenges in utilising vast and highly informative datasets, whilst keeping analyses computationally tractable

Purifying selection Much of the work of selection is removing disadvantageous alleles Regions performing some useful function (e.g. genes!) evolve more slowly Once again, comparative genomics can help! –Look for regions that are conserved between distantly related species Maladaptive mutation Fewer offspringMutation lost

Identifying conserved regions 5% of genome is “conserved” – but only 1.5% exonic sequence

SNP frequency “spectrum” in CNC’s SNPs are at lower frequencies in CNC’s (p=3x ) Signal is weak – not all CNCs selected? –Stronger near genes –Strongest at very highly conserved elements (Katzman et al., Science 2007) Drake et al. (Nature Genetics, 2005)

Conclusions Population genetics provides diverse information about molecular evolution Combining population genetics with knowledge of genomic sequence –New insights into adaptive evolution –Evolution is ongoing, and influenced by local environment –Limited power means we will probably never find all sites of selection Avalanche of variation data being gathered –Will bring many more insights –Presents major challenges in utilising vast and highly informative datasets, whilst keeping analyses computationally tractable