Genome-wide Identification of Craniofacial Transcriptional Enhancers

1. Genome-wide Identification ofCraniofacial Transcriptional Enhancers Axel Visel Scientist, Genomics Division Lawrence Berkeley National Laboratory

2. Outline 1 Distant-Acting Enhancers Why are they important? How can we find them in the genome (and determine their function)? 2 Finding Developmental Face/Palate Enhancers Data from preliminary ChIP-seq and transgenic mouse studies 3 FaceBase – Contributions and Expectations Data and reagents Interactions

3. distant-acting enhancers human Shh enhancer point mutations 1 megabase Sagai et al. 2005 Lettice et al. 2003 limb enhancer Shh gene wild-type limb enhancer deleted Lettice et al. 2003 mouse embryo Enhancers are Required for Development promoter protein- coding

4. 60% 40% Of 1,200 disease-associated SNPs, 40% are not linked to any coding gene Noncoding Sequences in Human Disease Meta-Analysis of Genome-Wide Association Studies (GWAS): Distant Enhancers? Noncoding LD blocks Linked to Exons Visel/Pennacchio/Rubin 2009 (Nature 461:199)

5. inject into fertilized mouse egg PCR amplify clone reimplant collect at e11.5 LacZ staining P LacZ pHsp68LacZ minimum reproducibility: 3 embryos How do we find enhancers? Approach A: Extreme Conservation of Non-coding sequences mouse fugu Major limitation: can’t find enhancers active in a particular process, e.g. face development >500 enhancers identified to date see http://enhancer.lbl.gov

6. microdissection midbrain tissue forebrain tissue limb tissue p300 ChIP-Seq limb 2,400,000 reads 2,100 peaks forebrain 3,600,000 reads 2,400 peaks midbrain 3,500,000 reads 600 peaks How do we find enhancers? Approach B: ChIP-seq with the enhancer-associated p300 protein mouse embryo (e11.5) Test in transgenic mouse assay (Nature 457:854, 2009)

7. p300 ChIP-Seq Predicts in vivo Enhancer Activity ChIP-seq forebrain midbrain limb transgenic mouse assay 80%-90% success rate (n>100) Enables accurate predictions of genomic locations AND activity of enhancers 11/12 11/11 5/5 8/8 (Nature 457:854, 2009)

8. Outline 1 Distant-Acting Enhancers Why are they important? How can we find them in the genome (and determine their function)? 2 Finding Developmental Face/Palate Enhancers Data from preliminary ChIP-seq and transgenic mouse studies 3 FaceBase – Contributions and Expectations Data and reagents Interactions

9. enhancer SNP disrupts a single AP-2a binding site x virtual section of mouth region enhancer activity in ectoderm of fusing facial prominences SNP associated with cleft lip/palate Enhancers Play a Role in Clefting Disorders human chr1 IRF6 gene human cleft lip and palate Rahimov et al. 2008 (Nature Genetics 40:1341) Jeff Murray Lab, OPT data: David FitzPatrick

10. ChIP-seq for Craniofacial Enhancer Discovery

11. Example: Enhancer near known clefting gene MSX1 Msx1 gene expression in maxillary component of 1st branchial arch (Mackenzie et al., Development 111:269) mx mx mx

12. Three-dimensional imaging of enhancer activity Optical Projection Tomography (Sharpe et al., Science 296:541) OPT of Enhancer Browser embryos: David FitzPatrick/Harris Morrison, MRC Edinburgh

13. Three-dimensional imaging of enhancer activity Optical Projection Tomography (Sharpe et al., Science 296:541) OPT of Enhancer Browser embryos: David FitzPatrick/Harris Morrison, MRC Edinburgh

14. In vivo validation of ChIP-seq predictions OPT scans: David FitzPatrick/Harris Morrison, MRC Edinburgh

15. Outline 1 Distant-Acting Enhancers Why are they important? How can we find them in the genome (and determine their function)? 2 Finding Developmental Face/Palate Enhancers Data from preliminary ChIP-seq and transgenic mouse studies 3 FaceBase – Contributions and Expectations Data and reagents Interactions

16. Visel Lab – FaceBase Aims Genome-wide identification of enhancer candidates p300 ChIP-seq: timepoints (e11.5 – e15.5), better spatial resolution RNA-seq data large-scale sequence-based data Transgenic validation and characterization test 30 candidate sequences/year in transgenic mice whole-mount photos and OPT data (collaboration with FitzPatrick lab) provide validated vectors as reagents to other FaceBase investigators image/video/3D data Follow-up of human genetic studies test risk alleles of clefting-associated craniofacial enhancers in mice integration of enhancer data with human genetic data

17. Visel Lab – FaceBase Expectations Developmental biology and expression imaging groups Intersect with gene expression data Please approach us with regions of interest! Human genetics groups Please approach us with non-coding cleft-associated regions! Use ChIP-seq and transgenics to search for enhancers Transgenic testing of cleft-associated risk variants

18. Acknowledgments Collaborators/Contributors: Terri Beaty, Robert Cornell, Michael Dixon, David FitzPatrick, Rulang Jiang, Michael Lovett, Mary Marazita, Jeff Murray, Stephen Murray, Leif Oxburgh, Bing Ren, John Rubenstein, Brian Schutte, Alan Scott, Douglas Spicer NIDCR (FaceBase) DOE, NHGRI Lawrence Berkeley National Lab and DOE Joint Genome Institute Len Pennacchio Eddy Rubin Matt Blow Shyam Prabhakar http://enhancer.lbl.gov Mouse Transgenics Malak Shoukry Jennifer Akiyama Veena Afzal Amy Holt Ingrid Plaijzer-Frick Roya Hosseini Next-Gen Sequencing Tao Zhang Feng Chen Crystal Wright Enhancer Browser Inna Dubchak Simon Minovitsky