Epigenomics
Exploring transcription factor binding and the epigenomic
landscape
Saurabh Sinha
(several slides here are courtesy of
Lisa Stubbs)
Eukaryotic genomes are complex structures comprised of
modified and unmodified DNA, RNA and many types of
interacting proteins
• Most DNA is wrapped around a “histone core”, to form nucleosomes
• The classical histone protein complexes bind very tightly to DNA and prevent
association with other proteins
• Modifications of the classical histones, or their replacement with unusual histone
types under certain conditions, can “loosen” the interaction with DNA, allowing
access to transcription factors, RNA polymerase, and other proteins
Eight histone proteins (2 copies of each of H2A, H2B, H3,
H4) at the core of a nucleosome
All eight histones have “tails” that can be modified in various ways, but the
most consequential modifications, with respect to transcriptional activity,
appear to involve methylation or acetylation of Lysines (K) in histone H3
Histone H3 modifications, especially methylation and
Acetylation, mark “open” or “closed” DNA
• CLOSED: Histones bound more tightly to DNA
– H3K27Me3, H3K9Me3
• OPEN: Histones can be displaced by TFs, RNA Polymerase, and
other proteins
– H2K27Ac, HeK4me1, H3K4me3
• Histone marks, together with other assays of open chromatin,
are presently the only reliable indicators of the locations and
activities of regulatory elements
Many types of regulatory elements
• “Docking sites” for site-specific regulatory proteins
– Transcription factors, TATA binding factors, and other site-specific binders
– Recruit additional proteins: co-factors, RNA polymerase and others
• Enhancers
– Tissue-specific activators of transcription
– Binding sites for proteins that interact with the promoter to enhance transcription
• Silencers
– Also prevalent, but more difficult to detect and assay
– Many transcription factors repress, rather than enhance, gene expression
– “Enhancers” and “Silencers” are not mutually exclusive! Most regulatory elements can
serve either function, depending on the proteins bound at a particular time
• Insulators
– “boundary elements” that shield genes from the enhancers or heterochromatin proteins
in neighboring gene “territories”
– Involved in establishing loop structures that isolate genes
ChIP Seq
How to find them? Chromatin ImmunoPrecipitation (ChIP)
•
Antibody to a DNA binding protein is
used to “fish out” DNA bound to the
protein in a living cell
– DNA and protein are crosslinked in the cell
using brief treatment with low
concentration of high quality formaldehyde
– Crosslinked chromatin is sheared, usually by
sonication, to yield short fragments of
DNA+protein complexes
– Antibody to a TF or other binding protein
used to fish out fragments containing that
DNA binding protein
– DNA is then “released” and can be analyzed
by various methods:
• Original method is PCR: query for
enrichment of specific (known or
suspected) DNA binding regions in
ChIP-enriched DNA
• Creates a pool of sequences highly
enriched in binding sites for a
particular protein or sites with a
specific histone mark
– Requires availability of excellent
antibodies that can detect the protein in
its in vivo context
ChIP can be used to map DNA:protein interactions of
virtually any type
• Histone modifications.
• DNA binding proteins (transcription factors)
• Secondary interactions (no direct linkage to DNA)
– Histone modifying proteins, such as SWI/SNF, histone deacetylases,
histone methylases
– Cofactors that bind to TFs at particular sites, and that stablize
chromatin loops
– Proteins that link chromatin to nuclear matrix
• RNA polymerase and elongation factors, to find promoters
and active sites of transcription
• Proteins involved in DNA recombination, repair, and
replication
• All of these methods require highly specific and efficient
antibodies (which are rare!)
ChIP Analytical challenges
• Genomic neighborhoods
– Shear efficiency is not really “random”
• Some genomic regions are fragile and sensitive
• Some regions are protected from shear or degradation
– “Sticky” chromatin
• Some DNA regions bind to any antibody you use
• Chromatin-matched, co-sheared controls are essential, but mock ChIP
(with IgG treatment) is helpful too
– Other artifacts
• Centromeres: repeat sequences that are not all represented in the genome assembly
• Polymorphic regions
• Repeats: most programs cannot manage sequence reads that are not mapped uniquely
• Peak width
– Transcription factors are typically sharp peaks; chromatin marks are more diffuse
• The best tools permit the user to modify these parameters
– MACS ( Xiaole Liu Lab; Zhang et al, 2008; Feng et al. Nature Methods 2102) is
a user-friendly and widely used tool
ChIP computational issues
• First step is to map reads:
BOWTIE, Novalign, BWA or other
• ChIP seq reads surround but may
not contain the DNA binding site
•
Sequence is generated from the ends
of randomly sheared fragments,
which overlap at the protein binding
site
• Gives rise to two adjacent sets of
read peaks
• Defines a “shift” distance between
read peaks at which you will find
the true ChIP peak summit
• Programs like MACS
automatically subtracts your
control (genomic input) from
sample reads to define a final set
of peaks
Binding site
Seq reads
ChIP fragments
Traditional methods fail with broad, flat peaks
• Most tools designed for TF proteins: discreet, sharp peaks
• Certain chromatin proteins, and modified histones in certain regions, bind
continuously to large regions of chromatin and do not yield “peaks”
• MACS in default mode will carve the “mesa” into many peaks, or not
detect it at all
• New settings in MACS 2 can be set to overcome this problem
• Other tools, e.g. Zinba (R-based) are designed specifically for this problem
Scale
chr7:
HOXA3
HOXA3
Enhanced H3K27Ac
Layered H3K4Me1
Layered H3K4Me3
hg18
20 kb
27,140,000 27,150,000 27,160,000 27,170,000 27,180,000 27,190,000 27,200,000 27,210,000
RefSeq Genes
HOXA-AS3
HOXA-AS4
HOXA11-AS
HOTTIP
HOXA4
HOXA5
HOXA7
MIR196B
HOXA11
HOXA13
HOXA6
HOXA9
HOXA-AS3
HOXA10
HOXA10-HOXA9
HOXA10
ENCODE Enhancer- and Promoter-Associated Histone Mark (H3K27Ac) on 8 Cell Lines
ENCODE Enhancer- and Promoter-Associated Histone Mark (H3K4Me1) on 8 Cell Lines
ENCODE Promoter-Associated Histone Mark (H3K4Me3) on 9 Cell Lines
NHGRI Catalog of Published Genome-Wide Association Studies
Lessons from ENCODE chromatin assays: human data
•
Massive deep-sequencing of multiple chromatin features in cell lines
(ENCODE), primary cell types and tissues (Epigenetics Roadmap)
– Histone H3 modifications: highlight on H3K4me1, H3K4me3, H3K27Ac, H3K27me3.
– Other chromatin proteins: e.g. P300 (acetyltransferase)
•
•
H3K4me3 marks are enriched at active promoters
– H3K4me3 marks are largely the same in all cell lines, with a small fraction
of marks being cell-specific
P300, and H3K4me1 without H3K4me3 is enriched at enhancers
– Most P300 peaks also contain H3K4me1
– P300, H3K4me1 marks are highly cell-type specific
– Most P300 marks are enhancers, but not all enhancers have P300
– Most enhancers have an H3K4me1 mark but, not all H3K4me1 marks are
in enhancers
• Other marks: H3K27Ac or H3K27me3
– Mutually exclusive marks for open (Ac) versus closed (Me3) chromatin
regions
– H3K27Ac is perhaps the most general mark of open chromatin: promoters
and enhancers
– Can be found in combination with H3K4 me1/me3
Combinatorial marks define subclasses of enhancers
• H3K4me1+ , H3K27Ac + mark enhancers with highest levels of
activity
– Represent cell-type specific active enhancers in differentiated cells
– Mouse enhancers: gain K27Ac upon differentiation in mouse ES cells, leading to
higher expression
• H3K4me1+, H3K27Ac- marks
– Called “intermediate” enhancers, linked to a variety of non-specific cellular functions
• In humans especially, H3K4me1+, H3K27me3+ are called “poised”
enhancers,
– H3K27me3 is a mark of polycomb repression; polycomb proteins are also associated
with these sites
– H3K9me3+ marks also found at poised enhancers
– These enhancers are associated specifically with development-related functions;
H3K27me3 may be replaced by H3K27Ac as differentiation progresses
– Poised enhancers are more likely to be conserved between species, and therefore
most of the enhancers that have been tested so far are probably of this subclass
Other properties of human enhancers
• A subset of human enhancers have been shown to give rise to non-coding
RNA
– ChIP with the RNA pol2 antibody identifies binding to enhancers that are far
from any known gene promoters
– Do not have marks that are shared by other types of promoters (e.g.
H3K4me3)
– Some are verified enhancer loci, e.g. the beta-globin control region gives rise
to a regulatory RNA
• Histone marks other than H3K4 and H3K27 are also found
– For example, H2 variant H2AZ and H3 variant, H3.3
– Double variant (H2AZ/H3.3) marks are common at enhancers
• More sites of open chromatin (e.g. DNAse sensitive) exist that have
not been associated with any specific protein, implying that the
story is still more complicated
Overview: ENCODE and modENCODE
• Data paint an extremely similar picture for human, mouse and
Drosophila cis-regulatory landscapes
• Promoters marked by H3K4Me3
• Active enhancers marked by H3K4me1 + H3K27Ac and p300/CBP
– Major difference is that fewer fly enhancers are found far from a TSS
• “Poised” enhancers marked by H3K4me1+ H3K27me3 : a mix of activating
and repressing marks, waiting to be transferred to one or the other states
– Enriched in developmentally-active transcription factor and signaling
genes
• Repressed regions marked by H3K9me3 (stable), H3K27me3 (dynamic)
• Insulators marked by CTCF and centrosomal/cytoskeletal proteins
(CP190, cohesins)
• TFBS, chromatin marks and expression data can be used to predict
regulatory relationships, but the precise linkage between regulatory
elements and “target genes” is very hard to decipher, especially in
mammalian genomes
modENCODE Chromatin profiles are displayed in the
UCSC browser
Scale
chr3R:
Spliced ESTs
10 kb
26,675,000
26,680,000
D. melanogaster ESTs That Have Been Spliced
dm3
26,685,000
FlyBase Protein-Coding Genes
tll
BDTNP Chromatin Accessibility (DNase) Stage 5, Replicate 1
BDTNP Chromatin Accessibility (DNase) Stage 9, Replicate 1
BDTNP Chromatin Accessibility (DNase) Stage 10, Replicate 1
BDTNP Chromatin Accessibility (DNase) Stage 11, Replicate 1
BDTNP Chromatin Accessibility (DNase) Stage 14, Replicate 1
BDTNP ChIP/chip: bicoid (bcd) antibody 2, stage 4-5 embryos, False Discovery Rate (FDR) 1%
BDTNP ChIP/chip: caudal (cad) antibody 1, stage 4-5 embryos, False Discovery Rate (FDR) 1%
BDTNP ChIP/chip: giant (gt) antibody 2, stage 4-5 embryos, False Discovery Rate (FDR) 1%
BDTNP ChIP/chip: hunchback (hb) antibody 1, stage 4-5 embryos, False Discovery Rate (FDR) 1%
BDTNP ChIP/chip: hunchback (hb) antibody 1, stage 9 embryos, False Discovery Rate (FDR) 1%
BDTNP ChIP/chip: knirps (kni) antibody 2, stage 4-5 embryos, False Discovery Rate (FDR) 1%
BDTNP ChIP/chip: Kruppel (Kr) antibody 2, stage 4-5 embryos, False Discovery Rate (FDR) 1%
BDTNP ChIP/chip: huckebein (hkb) antibody 1, stage 4-5 embryos, False Discovery Rate (FDR) 1%
BDTNP ChIP/chip: tailless (tll) antibody 1, stage 4-5 embryos, False Discovery Rate (FDR) 1%
BDTNP ChIP/chip: Dichaete (D) antibody 1, stage 4-5 embryos, False Discovery Rate (FDR) 1%
BDTNP ChIP/chip: fushi tarazu (ftz) antibody 3, stage 4-5 embryos, False Discovery Rate (FDR) 1%
BDTNP ChIP/chip: hairy (h) antibody 2, stage 4-5 embryos, False Discovery Rate (FDR) 1%
BDTNP ChIP/chip: paired (prd) antibody 1, stage 4-5 embryos, False Discovery Rate (FDR) 1%
BDTNP ChIP/chip: runt (run) antibody 1, stage 4-5 embryos, False Discovery Rate (FDR) 1%
BDTNP ChIP/chip: sloppy paired 1 (slp1) antibody 1, stage 4-5 embryos, False Discovery Rate (FDR) 1%
BDTNP ChIP/chip: daughterless (da) antibody 2, stage 4-5 embryos, False Discovery Rate (FDR) 1%
BDTNP ChIP/chip: dorsal (dl) antibody 3, stage 4-5 embryos, False Discovery Rate (FDR) 1%
BDTNP ChIP/chip: Mothers against dpp (mad) antibody 2, stage 4-5 embryos, False Disc. Rate (FDR) 1%
BDTNP ChIP/chip: Medea (med) antibody 2, stage 4-5 embryos, False Discovery Rate (FDR) 1%
BDTNP ChIP/chip: Medea (med) antibody 2, stage 10 embryos, False Discovery Rate (FDR) 1%
BDTNP ChIP/chip: Medea (med) antibody 2, stage 14 embryos, False Discovery Rate (FDR) 1%
BDTNP ChIP/chip: schnurri (shn) antibody 2, stage 4-5 embryos, False Discovery Rate (FDR) 1%
BDTNP ChIP/chip: snail (sna) antibody 2, stage 4-5 embryos, False Discovery Rate (FDR) 1%
BDTNP ChIP/chip: twist (twi) antibody 2, stage 4-5 embryos, False Discovery Rate (FDR) 1%
BDTNP ChIP/chip: zeste (z) antibody 2, stage 11 embryos, False Discovery Rate (FDR) 1%
BDTNP ChIP/chip: RNA Polymerase II (PolII) antibody, stage 4-5 embryos, False Discovery Rate (FDR) 1%
Chromatin “states”: an unbiased,
systematic characterization
• ChromHMM tool
combines
information from
38 different
histone marks,
Pol2 and CTCF
profiles to
identify different
‘states’
• Other tools exist,
e.g., ChromaSig,
Segway
From TF-ChIP profiles to
gene expression
•
•
•
Furlong lab (Nature 2009)
used ChIP profiles of five TFs
in five different
developmental stages.
They predicted enhancers as
places where two or more
TF ChIP-peaks occur close to
each other
They used the
presence/absence/strength
of TF-binding (over all TFs
and stages) to predict the
expression ‘pattern’ driven
by each enhancer
Zinzen et al. PMID: 19890324
From TF-ChIP profiles to TF functions
Summarize TF’s ChIP profile around a gene into one score
Use TF’s ‘binding score’ at a gene to predict
probability of the gene being regulated by the TF
Combine TF’s score and gene’s differential
expression, repeat for every gene, and derive a
‘signature’ for the TF in the condition of study
Chen et al. doi:10.1371/journal.pcbi.1003198.
DNA accessibility assays
DNAse sensitivity assays are antibody free
The first approach:
Crawford et al., Genome Research 16:123,
2006 (Francis Collins’ laboratory)
Genome-wide identification of Dnase
Hypersensititive (HS) sites
Does not allow footprinting, because TF
binding sites inside the HS regions have
been digested away
Latest (and better) approach: sequences DNAse sensitive regions
per se and permits transcription factor “Footprinting”
• The easiest method uses
low concentrations of
Dnase I to generate short
fragments at sensitive
(“open) sites
• Released fragments can be
blunt-ended, ligated to
linkers and sequenced
directly
• Permits DNase
Footprinting: Very deep
sequencing can “see” short
protected regions that are
absent from the released
DNA, and appear as
protected “valleys” inside
the DNAse sensitive peaks
– protected from DNAse I
because they are occupied by
TF proteins
Related methods and twists on the theme
(see Furey et al., 2012 for review)
• Exo-ChIP
– Follows sonication with an exonuclease step, to “pare back” all but the
protein-protected region in ChIP
• Nano-ChIP
– ChIP normally required ~107 cells as input; hard to achieve for many cell types
– Nano ChIP works with as few as 104 cells
• FAIRE: formaldehyde assisted isolation of regulatory elements
– Takes advantage of the fact that open chromatin regions are hypersensitive
also to shearing and chromatin prep (cross-linking) steps
– Formaldehyde cross-linking works less well in open regions; non cross-linked
regions are separated out and sequenced.
From DNA accessibility to
regulatory programs
•
•
•
•
Obtain accessibility profile in cellular conditions of interest.
Then look for motif matches in ‘open regions’
‘Poor man’s ChIP’
Use this computationally predicted TF-binding profile to
reconstruct regulatory networks
Blatti et al. doi: 10.1093/nar/gkv195
Accessibility profiles alone can lead to
valuable insights
Evidence of lineage patterning in
primary DHS data. DNase I
cleavage-density profiles for 24
exemplary primary human cell
types and ESCs across an ∼350
kb region along chromosome 9.
Cell types are colored according
to their embryological derivation
Source: Stergachis et
al http://dx.doi.org/10.1016/j.cell.
2013.07.020
Accessibility profiles alone can lead to
valuable insights
Clustering DHS profiles recovers precise
embryological relationships. Unbiased
clustering of the linear patterning of
DHSs from 48 diverse, definitive cell
types plus ESCs. Branches and cell types
are colored according to their
embryological origin, with embryological
ancestors common to multiple cell types
indicated on the right. Note the rooting
of the tree by ESCs and the partitioning
of major branches corresponding to the
trilaminar embryo. Note also the
demarcation of early fate decisions such
as partitioning of hemangioblast
derivatives into endothelia and blood.
Source: Stergachis et
al http://dx.doi.org/10.1016/j.cell.2013
.07.020
DNA Methylation
DNA Methylation
• Methyl (-CH3) group added to Cytosine (‘C’)
• CpG (CG dinucleotide) is often methylated
• CpG island: > 200 bp long stretches of DNA
enriched in CpG
• CpG islands are often not methylated
(“unmethylated CpG”).
• CpG islands often fall in or near promoter
regions
DNA Methylation and gene expression
• Methylated CpG may hinder transcription factor
binding to DNA at that site
• Methylated CpG may recruit proteins that render local
chromatin less accessible
• Roughly speaking, DNA methylation is repressive for
gene expression
• DNA Methylation levels can be condition-dependent
– Aberrant methylation patterns in cancer (e.g.,
hypermethylation of tumor suppressors and
hypomethylation of oncogenes)
– Progressive increase in global methylation levels with age.
Also aging-correlated hypomethlation at some genes.
DNA Methylation and gene expression
• DNA methylation in gene body positively
correlates with expression
• Alternative splicing: included exons tend to be
more methylated than excluded exons
• Retrotransposons are usually methylated,
protecting the genome against these parasitic
mobile elements
CpG Methylation profiling
• Bisulfite sequencing
Other methods:
• DNA cleavage by methylationsensitive restriction enzymes
• Immunoprecipitation with methylbinding protein
Summary
• Transcription factor binding sites genomewide
• Histone modification profiles (different marks
or combinations of marks can point to
different classes of regulatory elements)
• DNA accessibility profiles
• CpG methylation profiles
• Epigenomic profiles are predictive of gene
expression and phenotypes