genomics of gene regulation genomic and proteomic approaches to heart, lung, blood and sleep...
TRANSCRIPT
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Genomics of Gene Regulation
Genomic and Proteomic Approaches to Heart, Lung, Blood and Sleep Disorders
Jackson Laboratories
Ross Hardison
September 9, 2008
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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)
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Deletions of noncoding DNA can affect gene expression
Forget and Hardison, Chapter in Disorders of Hemoglobin, 2nd edition
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Substitutions in promoters can affect expression
Forget and Hardison, Chapter in Disorders of Hemoglobin, 2nd edition
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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
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Risk loci in noncoding regions
(2007) Science 316: 1336-1341
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DNA sequences involved in regulation of gene transcription
Protein-DNA interactions
Chromatin effects
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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
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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)
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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/
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Silent and repressed chromatin
Hardison (2002) on-line textbook Working with Molecular Genetics http://www.bx.psu.edu/~ross/
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Transcription initiation and pausing
General transcription initiation factors, GTIFs
Assemble on promoter
Repressors bindto negative controlelements
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Basal and activated transcription
Activators bind to enhancers
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Histone modifications modulate chromatin structure
http://www.imt.uni-marburg.de/bauer/images/fig2.jpg Uta-Maria Bauer
H3K27me3H3K4me2, 3
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Biochemical features of DNA in CRMs
Pol IIaPol 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 H4Methylation of H3K4
Clusters of binding site motifs
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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
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Chromatin immunoprecipitation: Greatly enrich for DNA occupied by a protein
Elaine Mardis (2007) Nature Methods 4: 613-614
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ChIP-chip: High throughput mapping of DNA sequences occupied by protein
http://www.chiponchip.org Bing Ren’s lab
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Enrichment of sequence tags reveals function
Barbara Wold & Richard M Myers (2008) “Sequence Census Methods” Nature Methods 5:19-21
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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-transcriptionalregulation. Different hypotheses to test in future work.
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GATA-1 occupancy in erythroid cells
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GATA-1 is required for erythroid maturation
Aria Rad, 2007 http://commons.wikimedia.org/wiki/Image:Hematopoiesis_(human)_diagram.png
MEP Hematopoietic stem cell
Commonmyeloidprogenitor
Myeloblast
Basophil
Commonlymphoidprogenitor
Neutrophil
Eosinophil
Monocyte, macrophage
GATA-1G1E cells
G1E-ER4 cells
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GATA-1 occupancy over a large chromosomal region
----( )---- Ahsp
enhancer
ChIP: antibody to GATA-1chip: NimbleGen high density tiling arrayYong Cheng, Lou Dore,…Xinmin Zhang, Roland Green, Mitch Weiss, R.H.
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ChIP-chip for GATA-1 at Hbb locus
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GATA-1 ChIP-chip hits localize to targets of this transcription factor
GATA-1
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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%)
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DNA segments occupied by GATA-1 were tested for enhancer activity on transfected plasmids
Occupiedsegments
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Some of the DNA segments occupied by GATA-1 are active as enhancers
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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
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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/
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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 SOX61356 bp
About 1 in 4 bp is the start of a TFBS match!
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Three modes of evolution
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Negative and positive selection observed at different phylogenetic distances
:
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phastCons score identifies conserved DNA segments
Siepel et al. 2005, Genome Research
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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
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Intronic UCE in SOX6 enhances expression in melanocytes in transgenic mice
Pennacchio et al., http://enhancer.lbl.gov/
UCEsTested UCEs
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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
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Genes likely regulated by clade-specific pTRRs are enriched for distinctive functions
310
450
91
173
Millions ofyears
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
0.0005
0.004
0.012Ion transport
King, Taylor, et al. (2007) Genome Research
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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
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Clusters of conserved TFBSs: PReMods
Blanchette et al. (2006) Genome Research
http://genomequebec.mcgill.ca/PReMod/
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ESPERREvolutionary and Sequence Pattern
Extraction through Reduced Representation
Taylor et al. (2006) Genome Research 16:1596-1604
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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
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Regulatory potential (RP) to distinguish functional classes
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Good performance of ESPERR for gene regulatory regions (RP)
-1
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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
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Examples of validated preCRMs
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Validation status for 99 tested fragments
cc = consensus binding site motif is conserved and matches the consensus in multiple mammalian lineagescnc = binding site motif has a mismatch from the consensus but is conserved
Wang et al. (2006) Genome Research 16: 1480-1492
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preCRMs with High RP and Conserved Consensus GATA-1 Tend To Be Validated
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Accurate prediction of a GATA-1 responsive enhancer for miR-144, 451
A
Dore L, Amigo JD et al. (2008) PNAS 105:3333-3338.
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Constraint on a binding site motif in an occupied DNA segment strongly correlates with enhancement
Cheng et al. (2008) revised manuscript submitted
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Comparative genomics signals suggestive of CRMs around T2D risk variants
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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.
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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