1. Genomics of Gene Regulation Genomic and Proteomic Approaches to Heart, Lung, Blood and Sleep Disorders Jackson Laboratories Ross Hardison September 9, 2008

2. Heritable variation in gene regulation “Simple” Mendelian traits, e.g. thalassemias Variation in expression is common in normal individuals Variation in expression may be a major contributor to complex traits (including heart, lung, blood and sleep disorders)

3. Deletions of noncoding DNA can affect gene expression Forget and Hardison, Chapter in Disorders of Hemoglobin, 2nd edition

4. Substitutions in promoters can affect expression Forget and Hardison, Chapter in Disorders of Hemoglobin, 2nd edition

5. Variation of gene expression among individuals Levels of expression of many genes varies in humans (and other species) Variation in expression is heritable Determinants of variability map to discrete genomic intervals Often multiple determinants Points to an abundance of cis-regulatory variation in the human genome "We predict that variants in regulatory regions make a greater contribution to complex disease than do variants that affect protein sequence" Manolis Dermitzakis, ScienceDaily –Microarray expression analyses of 3554 genes in 14 families Morley M … Cheung VG (2004) Nature 430:743-747 –Expression analysis of EBV-transformed lymphoblastoid cells from all 270 individuals genotypes in HapMap Stranger BE … Dermitzakis E (2007) Nature Genetics 39:1217-1224

6. Risk loci in noncoding regions (2007) Science 316: 1336-1341

7. DNA sequences involved in regulation of gene transcription Protein-DNA interactions Chromatin effects

8. Specific DNA sequences bind proteins that recruit transcriptional machinery Maston G, Evans S and Green MR (2006) Annu Rev Genomics Hum Genetics 7:29-59

9. Distinct classes of regulatory regions Maston G, Evans S and Green M (2006) Annu Rev Genomics Hum Genetics 7:29-59 Act in cis, affecting expression of a gene on the same chromosome. Cis-regulatory modules (CRMs)

10. CRMs are clusters of specific binding sites for transcription factors Hardison (2002) on-line textbook Working with Molecular Genetics http://www.bx.psu.edu/~ross/

11. Silent and repressed chromatin Hardison (2002) on-line textbook Working with Molecular Genetics http://www.bx.psu.edu/~ross/

12. Transcription initiation and pausing General transcription initiation factors, GTIFs Assemble on promoter Repressors bind to negative control elements

13. Basal and activated transcription Activators bind to enhancers

14. Histone modifications modulate chromatin structure http://www.imt.uni-marburg.de/bauer/images/fig2.jpg Uta-Maria Bauer H3K27me3H3K4me2, 3

15. Biochemical features of DNA in CRMs Pol IIa Pol II Coactivators Accessible to cleavage: DNase hypersensitive site Bound by specific transcription factors Associated with RNA polymerase and general transcription factors Nucleosomes with histone modifications: Acetylation of H3 and H4 Methylation of H3K4 Clusters of binding site motifs

16. Examples of genome-wide data on CRM features RNA polymerase II, preinitiation complex –IMR90 cells: Kim TH …Ren B (2005) Nature 436: 876-880 Start sites for transcription –Carninci et al. (2006) Nature Genetics 38:626-635 Histone modifications –T cells: Roh... Zhao K (2006) PNAS 103:15782-15878 Insulator protein CTCF –Primary fibroblasts: Kim TH … Ren B (2007) Cell 128:1231-1245 DNase hypersensitive sites –CD4+ T cells: Boyle… Crawford G (2008) Cell 132:311-322 Many datastreams: ENCODE project –Birney et al. (2007) Nature 477:799-816

17. Chromatin immunoprecipitation: Greatly enrich for DNA occupied by a protein Elaine Mardis (2007) Nature Methods 4: 613-614

18. ChIP-chip: High throughput mapping of DNA sequences occupied by protein http://www.chiponchip.org Bing Ren’s lab

19. Enrichment of sequence tags reveals function Barbara Wold & Richard M Myers (2008) “Sequence Census Methods” Nature Methods 5:19-21

20. Genomic features at T2D risk variants Overlap of SNP rh564398 with DHS suggests a role in transcriptional regulation, but overlap with an exon of a noncoding RNA suggests a role in post-transcriptional regulation. Different hypotheses to test in future work.

21. GATA-1 occupancy in erythroid cells

22. GATA-1 is required for erythroid maturation Aria Rad, 2007 http://commons.wikimedia.org/wiki/Image:Hematopoiesis_(human)_diagram.png MEP Hematopoietic stem cell Common myeloid progenitor Myeloblast Basophil Common lymphoid progenitor Neutrophil Eosinophil Monocyte, macrophage GATA-1 G1E cells G1E-ER4 cells

23. GATA-1 occupancy over a large chromosomal region ----( )---- Ahsp enhancer ChIP: antibody to GATA-1 chip: NimbleGen high density tiling array Yong Cheng, Lou Dore,…Xinmin Zhang, Roland Green, Mitch Weiss, R.H.

24. ChIP-chip for GATA-1 at Hbb locus

25. GATA-1 ChIP-chip hits localize to targets of this transcription factor GATA-1

26. Almost all sites occupied by GATA-1 have the consensus binding site motif WGATAR Of the 63 validated ChIP-chip hits, 60 (95%) have at least one WGATAR motif –Other 3 have AGATAT, GGATAT, CGATAG, … –Of 6000 randomly chosen DNA intervals of 500bp from the 66Mb, 3886 (65%) have a WGATAR motif –Occupied sites are about 1.4-fold enriched for the motif GATA-1 discriminates exquisitely among available sites –Only 94 out of 78,013 potential sites (500bp interval with at least one WGATAR) are occupied –About 1 in 1000 intervals are occupied –Indicates exquisite specificity of the ChIP-chip data (<99%)

27. DNA segments occupied by GATA-1 were tested for enhancer activity on transfected plasmids Occupied segments

28. Some of the DNA segments occupied by GATA-1 are active as enhancers

29. Comparative genomics for predicting CRMs Sometimes high quality data on biochemical signatures of CRMs is not available Use sequence properties of CRMs for prediction Clusters of binding site motifs for transcription factors –Low specificity - MANY false positives Deep conservation of noncoding DNA sequences, from humans to fish or chicken –Low sensitivity - less than 5% of CRMs show signs of constraint across vertebrates Conservation of clusters of transcription factor binding sites in mammals Conservation patterns that distinguish CRMs from neutral DNA

30. Finding clusters of binding sites for transcription factors Resources and servers for finding transcription factor binding sites (TFBSs) –TRANSFAC http://www.gene-regulation.com/ –JASPAR http://jaspar.cgb.ki.se/cgi-bin/jaspar_db.pl –TESS http://www.cbil.upenn.edu/cgi-bin/tess/tess –MOTIF (GenomeNet) http://motif.genome.jp/ –MatInspector http://www.genomatix.de/

31. Finding known motifs in a query sequence MatInspector at http://www.genomatix.de/ K. Cartharius et al. (2006) MatInspector and beyond: promoter analysis based on transcription factor binding sites. Bioinformatics 21:2933-2942. Genomatix Software GmbH, Munchen, Germany Query: an enhancer in SOX6 1356 bp About 1 in 4 bp is the start of a TFBS match!

32. Three modes of evolution

33. Negative and positive selection observed at different phylogenetic distances :

34. phastCons score identifies conserved DNA segments Siepel et al. 2005, Genome Research

35. Ultraconserved elements = UCEs At least 200 bp with no interspecies differences –Bejerano et al. (2004) Science 304:1321-1325 –481 UCEs with no changes among human, mouse and rat –Also conserved between out to dog and chicken –More highly conserved than vast majority of coding regions Most do not code for protein –Only 111 out of 481overlap with protein-coding exons –Some are developmental enhancers. –Nonexonic UCEs tend to cluster in introns or in vicinity of genes encoding transcription factors regulating development –88 are more than 100 kb away from an annotated gene; may be distal enhancers

36. Intronic UCE in SOX6 enhances expression in melanocytes in transgenic mice Pennacchio et al., http://enhancer.lbl.gov/ UCEs Tested UCEs

37. Distinctive divergence rates for different types of functional DNA sequences pTRRs: putative transcriptional regulatory region; likely CRMs Sites identified as occupied by sequence-specific transcription factors based on high-throughput chromatin immunoprecipitation assayed by hybridization to high density tiling arrays of genomic DNA= ChIP-chip

38. Genes likely regulated by clade-specific pTRRs are enriched for distinctive functions 310 450 91 173 Millions of years Percentage of pTRRs that align no further than: Primates: 3% Eutherians: 71% Marsupials: 21% Tetrapods: 4% Vertebrates: 1% David King Enriched GO categories q-value for FDR Immune response Protease inhibition Mitosis and cell cycle Transcriptional regulation 0.0006 0.0005 0.004 0.012 Ion transport King, Taylor, et al. (2007) Genome Research

39. Conservation of TFBSs between species Servers to find conserved matches to factor binding sites –Comparative genomics at Lawrence Livermore http://www.dcode.org/ zPicture and rVista Mulan and multiTF ECR browser –Consite http://mordor.cgb.ki.se/cgi-bin/CONSITE/consite Conserved TFBSs are available for some assemblies of human genome at UCSC Genome Browser Binding site for GATA-1

40. Clusters of conserved TFBSs: PReMods Blanchette et al. (2006) Genome Research http://genomequebec. mcgill.ca/PReMod/

41. ESPERR Evolutionary and Sequence Pattern Extraction through Reduced Representation Taylor et al. (2006) Genome Research 16:1596-1604

42. ESPERR: a different approach Don’t assume a database of known binding motifs Don’t assume strict conservation of the important sequence signals Instead, use alignments of validated examples to learn sequence and evolutionary patterns that characterize a class of elements Machine learning approach to discriminate functional classes of DNA based on patterns in alignments

43. Regulatory potential (RP) to distinguish functional classes

44. Good performance of ESPERR for gene regulatory regions (RP)

45. Predicted cis-Regulatory Modules (preCRMs) Around Erythroid Genes - Gene is known to respond to the restoration of GATA-1 in an erythroid cell line - DNA segment with positive regulatory potential (RP) score - DNA segment contains at least one match to the GATA-1 binding site (WGATAR) that is preserved in multiple mammalian lineages Wang et al. (2006) Genome Research 16: 1480-1492

46. Examples of validated preCRMs

47. Validation status for 99 tested fragments cc = consensus binding site motif is conserved and matches the consensus in multiple mammalian lineages cnc = binding site motif has a mismatch from the consensus but is conserved Wang et al. (2006) Genome Research 16: 1480-1492

48. preCRMs with High RP and Conserved Consensus GATA-1 Tend To Be Validated

49. Accurate prediction of a GATA-1 responsive enhancer for miR-144, 451 A Dore L, Amigo JD et al. (2008) PNAS 105:3333-3338.

50. Constraint on a binding site motif in an occupied DNA segment strongly correlates with enhancement Cheng et al. (2008) revised manuscript submitted

51. Comparative genomics signals suggestive of CRMs around T2D risk variants

52. Summary: Genomics of Gene Regulation Genetic determinants of variation in expression levels may contribute to complex traits - phenotype is not just determined by coding regions Biochemical features associated with cis-regulatory modules are being determined genome-wide for a range of cell types. These can be used to predict CRMs, but occupancy does not necessarily mean that the DNA is actively involved in regulation. Comparative genomics is a complementary approach to predicting CRMs. Evolutionary preservation of binding site motifs within regions containing other indicators of CRMs (e.g. regulatory potential or protein occupancy) is a good predictor of function.

53. Many thanks … Alignments, chains, nets, browsers, ideas, … Webb Miller, Jim Kent, David Haussler RP scores and other bioinformatic input: Francesca Chiaromonte, James Taylor Funding from NIDDK, NHGRI, Huck Institutes of Life Sciences at PSU Erythroid cell biology and biochemistry: Mitch Weiss, Gerd Blobel, Barry Paw Yong Cheng, Demesew Abebe, Christine Dorman, …, Ying Zhang, David King, Swathi Ashok Kumar