What has variation data taught us about the biology of recombination? Simon Myers Rory Bowden, Afidalina Tumian, Ronald Bontrop, Colin Freeman, Tammie MacFie, Gil McVean, Peter Donnelly Recap: Composite likelihood results Individuals Loci 1 0 1 1 1 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 1 1 1 1 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0 1 1 0 0 0 0 0 1 1 0 0 0 1 0 1 0 0 0 1 0 1 0 0 0 0 0 0 1 0 1 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 1 0 0 0 0 1 0 1 0 0 0 1 0 1 0 0 0 1 1 1 1 0 0 0 0 0 1 1 1 0 0 1 1 0 0 0 1 0 0 0 1 0 1 0 0 0 1 1 1 0 0 1 1 0 1 0 0 0 1 0 1 0 0 0 1 0 1 0 0 0 0 0 0 1 0 1 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 1 0 0 0 0 1 0 1 0 0 0 0 1 0 0 0 0 0 0 1 0 1 0 0 0 0 0 1 1 0 0 1 0 0 1 1 0 0 1 0 0 1 1 1 1 0 1 0 0 0 1 0 1 1 0 0 0 1 0 1 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 1 0 0 1 0 0 1 0 0 0 1 0 0 1 1 1 1 0 1 0 0 0 1 0 0 1 0 0 0 1 0 1 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 1 0 0 1 0 0 1 1 0 0 1 0 0 1 1 1 1 0 1 0 0 0 1 0 0 1 0 0 0 1 0 1 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 1 0 0 1 0 0 1 1 0 0 1 0 0 1 1 1 1 0 1 0 0 0 1 0 0 1 0 0 0 1 0 0 1 0 1 0 0 1 0 0 0 1 0 0 1 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 1 0 0 0 1 0 1 0 1 1 0 0 1 0 0 1 1 0 0 1 0 1 1 1 1 1 1 1 1 0 0 1 0 0 1 0 0 0 1 0 1 1 0 0 0 0 0 1 0 0 0 1 0 1 0 1 1 0 0 1 0 0 1 1 0 0 1 0 1 1 1 1 1 1 1 1 0 0 1 0 0 1 0 0 0 1 0 0 0 ? ? 0 1 0 0 ? ? 0 0 1 0 1 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 1 1 1 0 0 0 0 0 1 1 0 1 1 0 0 0 1 0 0 0 0 1 0 1 1 0 1 1 0 0 0 0 0 1 1 0 1 0 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 1 1 1 0 0 1 0 1 1 0 0 0 0 0 1 1 0 1 ? ? ? ? ? ? ? ? 0 0 0 0 1 1 1 1 0 0 1 1 1 0 0 0 1 1 1 0 1 0 0 0 0 0 0 1 0 0 1 1 1 1 0 0 0 0 ? 0 0 1 0 0 1 1 0 0 1 0 1 0 0 0 0 1 1 0 0 0 0 0 1 0 0 0 1 0 1 1 1 0 0 1 0 1 1 0 0 0 0 0 1 1 0 1 ? ? ? ? ? ? ? ? 0 0 0 0 ? 1 1 1 0 0 1 0 0 0 0 1 0 0 0 1 0 1 1 1 1 0 1 0 0 1 0 0 0 0 0 1 1 0 1 ? ? ? ? ? ? ? ? 0 0 0 0 1 1 0 1 0 0 1 1 0 1 1 0 0 0 1 0 1 0 0 0 0 1 0 0 0 0 1 1 1 0 1 0 0 1 0 0 1 1 0 0 1 0 1 1 1 1 1 0 0 1 0 1 1 0 1 0 1 1 0 0 0 1 0 1 0 0 0 0 1 0 0 0 0 1 1 1 0 1 0 0 1 0 0 1 1 0 0 1 0 1 1 1 1 1 0 0 1 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 1 1 0 1 0 0 0 1 0 1 0 0 1 0 1 1 0 0 1 0 0 0 1 1 1 1 0 0 1 1 1 0 0 1 1 0 0 0 1 1 0 1 0 0 1 0 0 0 0 1 0 1 0 0 0 0 0 1 0 0 0 0 0 1 • Statistical algorithms to estimate historical rates, and identify hotspots – Applied genome-wide – Kilobase scale resolution 0 0 0 0 0 0 1 1 1 0 0 1 0 0 0 0 0 0 0 0 0 1 1 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 1 0 0 1 0 0 0 0 0 0 1 1 1 0 0 1 1 1 0 0 0 0 0 0 0 1 1 0 1 0 0 1 0 0 0 0 1 0 1 0 0 0 1 0 1 0 0 1 0 0 1 0 0 0 0 0 0 1 1 1 1 0 1 0 0 0 0 0 1 0 0 0 1 1 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 1 0 0 0 0 0 0 1 1 1 1 0 1 0 0 0 0 0 1 0 0 0 1 1 0 1 0 0 1 1 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 1 0 1 0 0 0 1 1 1 1 1 1 1 0 0 0 0 1 1 1 0 0 1 1 0 1 1 0 1 1 0 0 0 0 0 0 0 0 0 1 0 1 1 0 0 0 0 1 1 0 1 1 1 0 0 0 0 0 0 0 0 0 1 1 0 0 0 1 1 0 0 1 0 0 1 0 0 1 1 1 0 1 0 1 1 1 0 1 0 0 1 0 1 1 0 (Myers et al. 2005) 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 1 0 0 0 0 1 0 0 0 0 0 1 0 1 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 1 0 0 0 1 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 1 0 0 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 1 0 0 1 0 0 0 0 1 0 0 0 1 0 1 1 1 0 0 0 0 0 0 0 0 0 1 1 0 0 0 1 1 0 0 1 0 0 1 0 0 1 1 1 0 1 0 0 1 1 0 1 0 0 1 0 1 1 0 1 0 1 1 1 0 0 0 0 0 0 0 0 0 1 1 0 0 0 1 1 0 0 1 0 0 1 0 0 0 1 1 0 1 0 0 1 1 0 1 0 0 1 0 1 1 0 1 0 1 1 1 0 0 0 0 0 0 0 0 0 1 1 0 1 0 1 1 0 0 1 0 0 1 0 0 1 1 1 0 1 0 0 1 ? 0 1 0 0 1 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 ? 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 1 0 1 0 1 1 0 0 1 1 1 0 0 0 0 0 1 1 0 1 1 0 0 0 1 0 1 1 0 0 1 0 0 1 0 1 0 0 1 0 1 ? 0 0 1 0 0 1 0 1 0 1 1 0 0 1 1 1 0 0 0 0 0 1 1 0 1 1 0 0 0 1 0 1 1 0 0 1 0 0 1 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 1 1 1 0 0 0 0 1 1 0 0 0 1 1 1 0 0 0 0 0 0 0 0 0 1 0 1 1 0 0 0 0 1 1 0 1 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 0 1 1 1 1 0 0 1 0 1 0 1 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 1 0 0 0 0 0 1 0 0 0 1 0 0 0 1 1 0 0 0 0 0 0 ? 0 0 0 1 0 0 0 1 0 1 1 0 0 0 0 0 1 1 0 0 0 0 0 1 0 1 0 1 0 1 0 1 1 0 0 1 1 1 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 1 0 0 0 0 1 1 0 0 0 1 0 1 0 1 1 1 0 0 0 1 0 0 0 1 1 1 0 0 0 0 0 0 0 0 0 1 0 1 0 1 0 1 1 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 1 0 1 0 0 1 0 0 1 0 1 0 0 0 1 0 0 0 1 1 0 1 0 1 0 1 1 0 1 1 1 0 0 1 1 0 0 1 0 0 0 0 1 0 0 1 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 ? 0 0 ? ? ? ? 1 0 1 0 0 0 1 0 0 1 0 0 0 0 0 1 0 1 0 0 0 0 1 ? ? 0 0 1 0 1 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0 0 1 1 0 1 1 1 0 0 0 1 1 0 1 0 0 0 0 1 0 0 1 0 0 0 0 1 1 0 0 0 0 0 0 0 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 1 1 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 1 0 1 0 1 1 0 0 0 0 0 1 1 0 1 1 1 0 0 0 1 1 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 1 1 1 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 1 1 1 0 0 1 0 0 1 0 0 1 1 0 0 1 1 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 1 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 1 0 0 0 0 0 0 0 0 0 0 0 1 0 1 1 1 0 0 1 1 0 0 0 0 0 0 0 • Model-based inference from linkage disequilibrium data (LD) – coalescent model 1 1 0 1 0 0 0 0 0 1 0 0 0 0 0 0 1 0 1 1 1 0 ? ? ? ? ? ? 0 0 0 1 0 1 1 1 0 0 1 1 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 1 1 0 0 0 ? 0 0 1 1 1 0 1 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 1 1 1 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 1 1 1 0 1 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 1 1 0 1 1 1 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 1 1 1 0 1 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 1 0 0 0 1 1 0 1 1 0 1 1 1 1 0 1 0 0 1 0 0 0 0 0 1 1 0 1 0 0 1 ? 1 0 1 1 1 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Recombination questions • Human recombination is poorly understood despite intense work • Recombination clusters into 1-2kb “hotspots” – why? • Why are hotspots where they are in the genome? – Primary DNA sequence? – Epigenetics? • What biological machinery produces hotspots? • How are hotspots evolving? 32,996 “HapMap” hotspots • These hotspots account for 50-70% of all human recombination • Why are they where they are? • We can look at the fraction of a genome that is “G” or “C” in a region Also see weak correlation with e.g. positions of genes Are there any stronger predictive features? Broad scale sequence features and recombination THE1B (LTR of retrotransposon) Use >20,000 hotspots localized to within 5kb For each, create a matched “coldspot” Compare sequence features THE1B: Found in 1196 hotspots versus 606 coldspots (p<<10-20) AluY: Found in 3635 hotspots versus 3262 coldspots (p=7x10-5) A motif for human hotspots • • • Compared primary DNA sequence at 30,000 human hotspots and matched coldspots THE1 repeats in hotspots THE1 repeats in coldspots ...CTTCCGCTATGATTGTGAGGCCTCCCTAGCCATGTGGAACTGTGAGCCCATT... ...CTTCCGCCATGATTGTGAGGCCTCCCCAGCCATGTGGAACTGTGAGTCCATT... ...CTTCCGCCATGATTGTGAGGCCTCCCTAGCCATGTGGAACTGTGAGTCCATT... ...CTTCCGTTATGATTGTGAGGCCTCCCCAGCCATGTGGAACTGTGAATCCATT... ...CTTCCGCCATGATTGTGAGGCCTCCCTAGCCACGTGGAAC-GTGAGTCCATT... ...CTTCCGCCATGATTGTGAGGCCTCCCCAGCCATGTGGGACTGTGAGTCCATT... ...CATCCGCCATGATTGTGAGGCCTCCCTAGCCACGTGGAACTGAGAGTCCATT... ...CTTCCGCC-TGATTCTGAGGCCTCCCCAGCCATGTGGAACTGTGAGTCCATT... ...CTTCCGCCATGATTGTGAGGCCTCCCCAGCCATGGGGAACTGTGAGTCCATT... ...CTTTCGCCATGATTGTGAGGCCTCCCCAGCCATGTGGAACTGC-TGTCCATT... Looked at all “words” of length 5-9 (e.g. 131072 possible 9-mers), refined results Identified a 13-bp motif, CCNCCNTNNCCNC (Myers et al. 2008) Average rates around the motif Penetrance >60% 3-5% of hotspots • • • Penetrance 7.5% 5% of hotspots Confirmed via sperm studies, revealing disruption of first 7-bp part of motif disrupts hotspot activity (Neumann and Jeffreys 2002) Active on multiple backgrounds (e.g. THE1, L2, Alu repeats and unique DNA…) Plays a role at c. 43% of hotspots identified through LD, or directly through sperm typing The motif is actually longer • • • Based on examining only non-repeat DNA in hotspots Independent of results on previous slide Region that matters >30bp Recombination and human disease: X-linked ichthyosis (Myers et al. 2008) Deletion breakpoint hotspot (Van Esch et al. 2005) The breakpoint hotspot contains the greatest concentration of the 13-bp motif, within a segmental duplication, anywhere in the entire genome The motif is associated with NAHR syndromes Multiple genomic disorders are caused by the same phenomenon: “nonallelic homologous recombination” (NAHR) Rearrangement endpoints are consistently clustered into narrow hotspots: • X-linked ichthyosis • Charcot-Marie-Tooth disease (CMT1A) • NF1 • Sotos syndrome • Smith-Magenis syndrome • Williams-Beuren syndrome The motif is present, close to breakpoint hotspots, in each case (p=0.00055) A ‘common deletion’ in mitochondria occurs at the motif Myers et al (2008) What binds the motif? • • • • 3-bp periodicity suggests by a “zinc finger” (ZF) protein with at least 12 zinc fingers (Myers et al. 2008) For genes coding for ZF proteins, we can predict their binding target bioinformatically (Persikov et al. 2009) Searched systematically – Zinc finger protein database of 691 C2H2 ZF proteins – Perform in silico binding predictions Look for matches to 13-bp motif, degeneracy (Myers et al. 2009) PRDM9 is unique candidate for the motif binding protein PRDM9 binding of the motif Motif identified by hotspotcoldspot comparison Bioinformatic prediction of PRDM9 binding “target” ZF part of PRDM9. 13 zinc fingers, one separated (showing four codons in each zinc finger that determine binding target) (Myers et al. 2009) Details of PRDM9 • Independent work by two additional groups confirms that PRDM9 is a gene that directly determines hotspot locations in both humans and mice – – – • PRDM9 puts an epigenetic mark on the histone DNA packaging – – – • Mapped a gene in mice, meaning different inbred strains possess different hotspot positions, to PRDM9 Baudat et al. (2009), Parvanov et al. (2009), Myers et al. (2009) Gel shift assays demonstrate PRDM9 really does bind the predicted motif: Baudat et al. (2009) H3K4 trimethylation The identical mark is used by yeast to mark hotspots (Borde et al. 2009) Conservation over >1 billion years of evolution In mice – – – Different PRDM9 types mean different hotspot positions (Buard et al. 2009; Baudat et al. 2009) Prdm9 expressed only in meiotic prophase (Hayashi et al. 2005) Prdm9 -/- mutants infertile,fail to repair DSBs (Hayashi et al. 2005) Baudat et al. (2009) Percent usage of LD hotspots • Considerable variation in PRDM9 in humans, which influences the usage of hotspots as defined from LD data • Different humans have different hotspot How are hotspots evolving? Hotspots are radically different between humans and chimps LDhot hotspots Human Chimp LDhat rate estimates Winckler et al. (2005) PRDM9 is radically different in chimpanzees • Sharing between human and chimps: 1 of 13 zinc fingers • Least shared of all 544 orthologous ZF protein pairs with at least two distinct zinc fingers in each species • Patterns in multiple species indicate positive selection (Oliver et al. 2009) • One of the fastest evolving genes in the human genome Crossover activity at motif is human-specific Human motif sites Chimp motif sites THE1 repeats L2 repeats Position relative to motif Position relative to motif 694 SNPs, 36 western chimpanzees 16 THE1 regions, 6 L2 regions HapMap data, 210 humans p=0.0007 Conclusions and current directions • Why are hotspots where they are in the genome? – – – – – PRDM9 has sequence specific binding Specifies narrow hotspot sites Targets primary DNA sequence but makes an epigenetic “mark” Only 40% of hotspots?? Looking at PRDM9 binding in vivo using Chip-seq • PRDM9 is evolving like crazy! – – – – Between species Within humans Within mice, chimps,…. Resequencing data for 10 chimpanzees to define their hotspots • PRDM9 is the only mapped speciation gene in any mammal – Hybrid sterility in mouse (Mihola et al. 2009) – What is the link between recombination and speciation? – Does PRDM9 evolution, in general, lead to breeding barriers between species? • Recombination and the motif implicated in multiple diseases – PRDM9 variation suggests different people susceptible to different genomic disorders