A presentation in the IMBIM-IGP Friday seminar on Nov 27th 2015.
I wanted to highlight recent discoveries in chromatin topographic domains (or TADs). The importance of CTCFs in the organization and discuss general implications in the discovery of causative mutations.
I also highlighted some of the available protocols to assay chromatin organization, both genome-wide and locus-centered.
Cell Signaling is an important facet of biological life. It allows cells to perceive and respond to the extracellular environment allowing development, growth, immunity, etc. Additionally, errors in cell signaling may result in cancer growth, diabetes. ... The inducer does not diffuse from the cell producing it.
Cell Signaling is an important facet of biological life. It allows cells to perceive and respond to the extracellular environment allowing development, growth, immunity, etc. Additionally, errors in cell signaling may result in cancer growth, diabetes. ... The inducer does not diffuse from the cell producing it.
Transcription factors and their role in plant disease resistanceSachin Bhor
The transcription of DNA to make messenger RNA is highly controlled by the cell. For higher organisms (plant or animal) to function, genes must be turned on and off in coordinated groups in response to a variety of situations. For a plant this may be “abiotic” (non-living) stress such as the rising or setting sun, drought, or heat, “biotic” (living) stress such as insects, viral or bacterial infection, or any of a limitless number of other events.
The job of coordinating the function of groups of genes falls to proteins called transcription factors (TF’s). TFs are proteins that binds to specific sequence of DNA in promoter region and regulate transcription.
Eukaryotic transcription is the elaborate process that eukaryotic cells use to copy genetic information stored in DNA into units of transportable complementary RNA replica.
COMPUTATIONAL ANALYSIS OF CIS-REGULATORY ELEMENTS AND ASSOCIATED TRANSCRIPTIO...VartikaRai17
The plant-specific DOF transcription factors have important biological role in plant morphogenesis growth and development. In this study sequences of ten Ocimum bacilicum Dof gene promoters were analyzed. Identification of biologically significant CREs (Cis-acting regulatory elements) was performed and CREs corresponding to light response, abiotic and biotic stress response, phytohormone response, and tissue-specific elements were found. Genes promoter analysis also revealed the presence of AP2, C2H2, bZIP, bHLH, GATA, Dof, GATA, HSF, NF-Y, and Homedomain. Transcription factor binding site in the promoter region of ObDof genes. These findings not only contribute to the understanding of the gene function of candidate ObDof genes for further analysis, but the information also contributes to the understanding of the gene regulatory network.
Basics of Undergraduate/university fellows
Transcription is more complicated in eukaryotes than in prokaryotes because
eukaryotes possess three different classes of RNA polymerases and because of the
way in which transcripts are processed to their functional forms.
More proteins and transcription factors are involved in eukaryotic transcription.
Introduction
Types of Transcription
factors involves in different Polymerase initiation complex
Structure of transcription factor
Role of transcription factor
Significance
All eukaryotes have at least three different RNA polymerase (Pol I, II,and III; and plants have a Pol IV & a Pol V). In addition, whereas bacteria require only one additional initiation factor (σ), several initiation factors are required for efficient and promoter-specific initiation in eukaryotes. These are called the general transcription factors (GTFs)
THE IMPORTANCE OF MARTIAN ATMOSPHERE SAMPLE RETURN.Sérgio Sacani
The return of a sample of near-surface atmosphere from Mars would facilitate answers to several first-order science questions surrounding the formation and evolution of the planet. One of the important aspects of terrestrial planet formation in general is the role that primary atmospheres played in influencing the chemistry and structure of the planets and their antecedents. Studies of the martian atmosphere can be used to investigate the role of a primary atmosphere in its history. Atmosphere samples would also inform our understanding of the near-surface chemistry of the planet, and ultimately the prospects for life. High-precision isotopic analyses of constituent gases are needed to address these questions, requiring that the analyses are made on returned samples rather than in situ.
Cancer cell metabolism: special Reference to Lactate PathwayAADYARAJPANDEY1
Normal Cell Metabolism:
Cellular respiration describes the series of steps that cells use to break down sugar and other chemicals to get the energy we need to function.
Energy is stored in the bonds of glucose and when glucose is broken down, much of that energy is released.
Cell utilize energy in the form of ATP.
The first step of respiration is called glycolysis. In a series of steps, glycolysis breaks glucose into two smaller molecules - a chemical called pyruvate. A small amount of ATP is formed during this process.
Most healthy cells continue the breakdown in a second process, called the Kreb's cycle. The Kreb's cycle allows cells to “burn” the pyruvates made in glycolysis to get more ATP.
The last step in the breakdown of glucose is called oxidative phosphorylation (Ox-Phos).
It takes place in specialized cell structures called mitochondria. This process produces a large amount of ATP. Importantly, cells need oxygen to complete oxidative phosphorylation.
If a cell completes only glycolysis, only 2 molecules of ATP are made per glucose. However, if the cell completes the entire respiration process (glycolysis - Kreb's - oxidative phosphorylation), about 36 molecules of ATP are created, giving it much more energy to use.
IN CANCER CELL:
Unlike healthy cells that "burn" the entire molecule of sugar to capture a large amount of energy as ATP, cancer cells are wasteful.
Cancer cells only partially break down sugar molecules. They overuse the first step of respiration, glycolysis. They frequently do not complete the second step, oxidative phosphorylation.
This results in only 2 molecules of ATP per each glucose molecule instead of the 36 or so ATPs healthy cells gain. As a result, cancer cells need to use a lot more sugar molecules to get enough energy to survive.
Unlike healthy cells that "burn" the entire molecule of sugar to capture a large amount of energy as ATP, cancer cells are wasteful.
Cancer cells only partially break down sugar molecules. They overuse the first step of respiration, glycolysis. They frequently do not complete the second step, oxidative phosphorylation.
This results in only 2 molecules of ATP per each glucose molecule instead of the 36 or so ATPs healthy cells gain. As a result, cancer cells need to use a lot more sugar molecules to get enough energy to survive.
introduction to WARBERG PHENOMENA:
WARBURG EFFECT Usually, cancer cells are highly glycolytic (glucose addiction) and take up more glucose than do normal cells from outside.
Otto Heinrich Warburg (; 8 October 1883 – 1 August 1970) In 1931 was awarded the Nobel Prize in Physiology for his "discovery of the nature and mode of action of the respiratory enzyme.
WARNBURG EFFECT : cancer cells under aerobic (well-oxygenated) conditions to metabolize glucose to lactate (aerobic glycolysis) is known as the Warburg effect. Warburg made the observation that tumor slices consume glucose and secrete lactate at a higher rate than normal tissues.
Transcription factors and their role in plant disease resistanceSachin Bhor
The transcription of DNA to make messenger RNA is highly controlled by the cell. For higher organisms (plant or animal) to function, genes must be turned on and off in coordinated groups in response to a variety of situations. For a plant this may be “abiotic” (non-living) stress such as the rising or setting sun, drought, or heat, “biotic” (living) stress such as insects, viral or bacterial infection, or any of a limitless number of other events.
The job of coordinating the function of groups of genes falls to proteins called transcription factors (TF’s). TFs are proteins that binds to specific sequence of DNA in promoter region and regulate transcription.
Eukaryotic transcription is the elaborate process that eukaryotic cells use to copy genetic information stored in DNA into units of transportable complementary RNA replica.
COMPUTATIONAL ANALYSIS OF CIS-REGULATORY ELEMENTS AND ASSOCIATED TRANSCRIPTIO...VartikaRai17
The plant-specific DOF transcription factors have important biological role in plant morphogenesis growth and development. In this study sequences of ten Ocimum bacilicum Dof gene promoters were analyzed. Identification of biologically significant CREs (Cis-acting regulatory elements) was performed and CREs corresponding to light response, abiotic and biotic stress response, phytohormone response, and tissue-specific elements were found. Genes promoter analysis also revealed the presence of AP2, C2H2, bZIP, bHLH, GATA, Dof, GATA, HSF, NF-Y, and Homedomain. Transcription factor binding site in the promoter region of ObDof genes. These findings not only contribute to the understanding of the gene function of candidate ObDof genes for further analysis, but the information also contributes to the understanding of the gene regulatory network.
Basics of Undergraduate/university fellows
Transcription is more complicated in eukaryotes than in prokaryotes because
eukaryotes possess three different classes of RNA polymerases and because of the
way in which transcripts are processed to their functional forms.
More proteins and transcription factors are involved in eukaryotic transcription.
Introduction
Types of Transcription
factors involves in different Polymerase initiation complex
Structure of transcription factor
Role of transcription factor
Significance
All eukaryotes have at least three different RNA polymerase (Pol I, II,and III; and plants have a Pol IV & a Pol V). In addition, whereas bacteria require only one additional initiation factor (σ), several initiation factors are required for efficient and promoter-specific initiation in eukaryotes. These are called the general transcription factors (GTFs)
THE IMPORTANCE OF MARTIAN ATMOSPHERE SAMPLE RETURN.Sérgio Sacani
The return of a sample of near-surface atmosphere from Mars would facilitate answers to several first-order science questions surrounding the formation and evolution of the planet. One of the important aspects of terrestrial planet formation in general is the role that primary atmospheres played in influencing the chemistry and structure of the planets and their antecedents. Studies of the martian atmosphere can be used to investigate the role of a primary atmosphere in its history. Atmosphere samples would also inform our understanding of the near-surface chemistry of the planet, and ultimately the prospects for life. High-precision isotopic analyses of constituent gases are needed to address these questions, requiring that the analyses are made on returned samples rather than in situ.
Cancer cell metabolism: special Reference to Lactate PathwayAADYARAJPANDEY1
Normal Cell Metabolism:
Cellular respiration describes the series of steps that cells use to break down sugar and other chemicals to get the energy we need to function.
Energy is stored in the bonds of glucose and when glucose is broken down, much of that energy is released.
Cell utilize energy in the form of ATP.
The first step of respiration is called glycolysis. In a series of steps, glycolysis breaks glucose into two smaller molecules - a chemical called pyruvate. A small amount of ATP is formed during this process.
Most healthy cells continue the breakdown in a second process, called the Kreb's cycle. The Kreb's cycle allows cells to “burn” the pyruvates made in glycolysis to get more ATP.
The last step in the breakdown of glucose is called oxidative phosphorylation (Ox-Phos).
It takes place in specialized cell structures called mitochondria. This process produces a large amount of ATP. Importantly, cells need oxygen to complete oxidative phosphorylation.
If a cell completes only glycolysis, only 2 molecules of ATP are made per glucose. However, if the cell completes the entire respiration process (glycolysis - Kreb's - oxidative phosphorylation), about 36 molecules of ATP are created, giving it much more energy to use.
IN CANCER CELL:
Unlike healthy cells that "burn" the entire molecule of sugar to capture a large amount of energy as ATP, cancer cells are wasteful.
Cancer cells only partially break down sugar molecules. They overuse the first step of respiration, glycolysis. They frequently do not complete the second step, oxidative phosphorylation.
This results in only 2 molecules of ATP per each glucose molecule instead of the 36 or so ATPs healthy cells gain. As a result, cancer cells need to use a lot more sugar molecules to get enough energy to survive.
Unlike healthy cells that "burn" the entire molecule of sugar to capture a large amount of energy as ATP, cancer cells are wasteful.
Cancer cells only partially break down sugar molecules. They overuse the first step of respiration, glycolysis. They frequently do not complete the second step, oxidative phosphorylation.
This results in only 2 molecules of ATP per each glucose molecule instead of the 36 or so ATPs healthy cells gain. As a result, cancer cells need to use a lot more sugar molecules to get enough energy to survive.
introduction to WARBERG PHENOMENA:
WARBURG EFFECT Usually, cancer cells are highly glycolytic (glucose addiction) and take up more glucose than do normal cells from outside.
Otto Heinrich Warburg (; 8 October 1883 – 1 August 1970) In 1931 was awarded the Nobel Prize in Physiology for his "discovery of the nature and mode of action of the respiratory enzyme.
WARNBURG EFFECT : cancer cells under aerobic (well-oxygenated) conditions to metabolize glucose to lactate (aerobic glycolysis) is known as the Warburg effect. Warburg made the observation that tumor slices consume glucose and secrete lactate at a higher rate than normal tissues.
Multi-source connectivity as the driver of solar wind variability in the heli...Sérgio Sacani
The ambient solar wind that flls the heliosphere originates from multiple
sources in the solar corona and is highly structured. It is often described
as high-speed, relatively homogeneous, plasma streams from coronal
holes and slow-speed, highly variable, streams whose source regions are
under debate. A key goal of ESA/NASA’s Solar Orbiter mission is to identify
solar wind sources and understand what drives the complexity seen in the
heliosphere. By combining magnetic feld modelling and spectroscopic
techniques with high-resolution observations and measurements, we show
that the solar wind variability detected in situ by Solar Orbiter in March
2022 is driven by spatio-temporal changes in the magnetic connectivity to
multiple sources in the solar atmosphere. The magnetic feld footpoints
connected to the spacecraft moved from the boundaries of a coronal hole
to one active region (12961) and then across to another region (12957). This
is refected in the in situ measurements, which show the transition from fast
to highly Alfvénic then to slow solar wind that is disrupted by the arrival of
a coronal mass ejection. Our results describe solar wind variability at 0.5 au
but are applicable to near-Earth observatories.
A brief information about the SCOP protein database used in bioinformatics.
The Structural Classification of Proteins (SCOP) database is a comprehensive and authoritative resource for the structural and evolutionary relationships of proteins. It provides a detailed and curated classification of protein structures, grouping them into families, superfamilies, and folds based on their structural and sequence similarities.
Deep Behavioral Phenotyping in Systems Neuroscience for Functional Atlasing a...Ana Luísa Pinho
Functional Magnetic Resonance Imaging (fMRI) provides means to characterize brain activations in response to behavior. However, cognitive neuroscience has been limited to group-level effects referring to the performance of specific tasks. To obtain the functional profile of elementary cognitive mechanisms, the combination of brain responses to many tasks is required. Yet, to date, both structural atlases and parcellation-based activations do not fully account for cognitive function and still present several limitations. Further, they do not adapt overall to individual characteristics. In this talk, I will give an account of deep-behavioral phenotyping strategies, namely data-driven methods in large task-fMRI datasets, to optimize functional brain-data collection and improve inference of effects-of-interest related to mental processes. Key to this approach is the employment of fast multi-functional paradigms rich on features that can be well parametrized and, consequently, facilitate the creation of psycho-physiological constructs to be modelled with imaging data. Particular emphasis will be given to music stimuli when studying high-order cognitive mechanisms, due to their ecological nature and quality to enable complex behavior compounded by discrete entities. I will also discuss how deep-behavioral phenotyping and individualized models applied to neuroimaging data can better account for the subject-specific organization of domain-general cognitive systems in the human brain. Finally, the accumulation of functional brain signatures brings the possibility to clarify relationships among tasks and create a univocal link between brain systems and mental functions through: (1) the development of ontologies proposing an organization of cognitive processes; and (2) brain-network taxonomies describing functional specialization. To this end, tools to improve commensurability in cognitive science are necessary, such as public repositories, ontology-based platforms and automated meta-analysis tools. I will thus discuss some brain-atlasing resources currently under development, and their applicability in cognitive as well as clinical neuroscience.
Richard's entangled aventures in wonderlandRichard Gill
Since the loophole-free Bell experiments of 2020 and the Nobel prizes in physics of 2022, critics of Bell's work have retreated to the fortress of super-determinism. Now, super-determinism is a derogatory word - it just means "determinism". Palmer, Hance and Hossenfelder argue that quantum mechanics and determinism are not incompatible, using a sophisticated mathematical construction based on a subtle thinning of allowed states and measurements in quantum mechanics, such that what is left appears to make Bell's argument fail, without altering the empirical predictions of quantum mechanics. I think however that it is a smoke screen, and the slogan "lost in math" comes to my mind. I will discuss some other recent disproofs of Bell's theorem using the language of causality based on causal graphs. Causal thinking is also central to law and justice. I will mention surprising connections to my work on serial killer nurse cases, in particular the Dutch case of Lucia de Berk and the current UK case of Lucy Letby.
(May 29th, 2024) Advancements in Intravital Microscopy- Insights for Preclini...Scintica Instrumentation
Intravital microscopy (IVM) is a powerful tool utilized to study cellular behavior over time and space in vivo. Much of our understanding of cell biology has been accomplished using various in vitro and ex vivo methods; however, these studies do not necessarily reflect the natural dynamics of biological processes. Unlike traditional cell culture or fixed tissue imaging, IVM allows for the ultra-fast high-resolution imaging of cellular processes over time and space and were studied in its natural environment. Real-time visualization of biological processes in the context of an intact organism helps maintain physiological relevance and provide insights into the progression of disease, response to treatments or developmental processes.
In this webinar we give an overview of advanced applications of the IVM system in preclinical research. IVIM technology is a provider of all-in-one intravital microscopy systems and solutions optimized for in vivo imaging of live animal models at sub-micron resolution. The system’s unique features and user-friendly software enables researchers to probe fast dynamic biological processes such as immune cell tracking, cell-cell interaction as well as vascularization and tumor metastasis with exceptional detail. This webinar will also give an overview of IVM being utilized in drug development, offering a view into the intricate interaction between drugs/nanoparticles and tissues in vivo and allows for the evaluation of therapeutic intervention in a variety of tissues and organs. This interdisciplinary collaboration continues to drive the advancements of novel therapeutic strategies.
12. 12
TFs
Regulatory acƟve
gene promoters and/or enhancers
Core promoter Core promoter
NDR
GTFs
RNAPII RNAPII
)
)
(B)
(i) Silent state
Enhancer
(ii) SƟmulus-in
Enhancer
(iii) Lagged ge
(i) (ii)
Enhancer
w
RNAPII
transcripƟon
Low abundance
of factors
InacƟve
regulatory
element
AcƟve regulatory element
Promoter strength and/or transcripƟonal level
High
High abundance
of factors
1. Active regulatory elements are divergently transcribed. (A) Both regulatory active gene promoters and gene-distal enhance
II) recruitment and transcription initiation are mediated by general transcription factors (GTFs) binding core promoter re
somes. This is facilitated by transcription factors (TFs), which often bind proximal to core promoters. Transcription often initiat
ucleosome-depleted region (NDR). (B) Gene expression is often preceded by, or changes concurrently with, changes in
xpressed) state (i), enhancers and promoters may, or may not, bind RNAPII. Upon stimulus (ii), transcriptional activity at enhance
ocal transcription and increases in RNAPII recruitment at the target gene promoter. (iii) Gene expression may lag behind trans
13. 13
TFs
Regulatory acƟve
gene promoters and/or enhancers
Core promoter Core promoter
NDR
GTFs
RNAPII RNAPII
)
)
(B)
(i) Silent state
Enhancer
(ii) SƟmulus-in
Enhancer
(iii) Lagged ge
(i) (ii)
Enhancer
w
RNAPII
transcripƟon
Low abundance
of factors
InacƟve
regulatory
element
AcƟve regulatory element
Promoter strength and/or transcripƟonal level
High
High abundance
of factors
1. Active regulatory elements are divergently transcribed. (A) Both regulatory active gene promoters and gene-distal enhance
II) recruitment and transcription initiation are mediated by general transcription factors (GTFs) binding core promoter re
somes. This is facilitated by transcription factors (TFs), which often bind proximal to core promoters. Transcription often initiat
ucleosome-depleted region (NDR). (B) Gene expression is often preceded by, or changes concurrently with, changes in
xpressed) state (i), enhancers and promoters may, or may not, bind RNAPII. Upon stimulus (ii), transcriptional activity at enhance
ocal transcription and increases in RNAPII recruitment at the target gene promoter. (iii) Gene expression may lag behind trans
14. 14
TFs
Regulatory acƟve
gene promoters and/or enhancers
Core promoter Core promoter
NDR
GTFs
RNAPII RNAPII
)
)
(B)
(i) Silent state
Enhancer
(ii) SƟmulus-in
Enhancer
(iii) Lagged ge
(i) (ii)
Enhancer
w
RNAPII
transcripƟon
Low abundance
of factors
InacƟve
regulatory
element
AcƟve regulatory element
Promoter strength and/or transcripƟonal level
High
High abundance
of factors
1. Active regulatory elements are divergently transcribed. (A) Both regulatory active gene promoters and gene-distal enhance
II) recruitment and transcription initiation are mediated by general transcription factors (GTFs) binding core promoter re
somes. This is facilitated by transcription factors (TFs), which often bind proximal to core promoters. Transcription often initiat
ucleosome-depleted region (NDR). (B) Gene expression is often preceded by, or changes concurrently with, changes in
xpressed) state (i), enhancers and promoters may, or may not, bind RNAPII. Upon stimulus (ii), transcriptional activity at enhance
ocal transcription and increases in RNAPII recruitment at the target gene promoter. (iii) Gene expression may lag behind trans
15. 15
TFs
Regulatory acƟve
gene promoters and/or enhancers
Core promoter Core promoter
NDR
GTFs
RNAPII RNAPII
)
)
(B)
(i) Silent state
Enhancer
(ii) SƟmulus-in
Enhancer
(iii) Lagged ge
(i) (ii)
Enhancer
w
RNAPII
transcripƟon
Low abundance
of factors
InacƟve
regulatory
element
AcƟve regulatory element
Promoter strength and/or transcripƟonal level
High
High abundance
of factors
1. Active regulatory elements are divergently transcribed. (A) Both regulatory active gene promoters and gene-distal enhance
II) recruitment and transcription initiation are mediated by general transcription factors (GTFs) binding core promoter re
somes. This is facilitated by transcription factors (TFs), which often bind proximal to core promoters. Transcription often initiat
ucleosome-depleted region (NDR). (B) Gene expression is often preceded by, or changes concurrently with, changes in
xpressed) state (i), enhancers and promoters may, or may not, bind RNAPII. Upon stimulus (ii), transcriptional activity at enhance
ocal transcription and increases in RNAPII recruitment at the target gene promoter. (iii) Gene expression may lag behind trans
16. 16
TFs
Regulatory acƟve
gene promoters and/or enhancers
Core promoter Core promoter
NDR
GTFs
RNAPII RNAPII
)
)
(B)
(i) Silent state
Enhancer
(ii) SƟmulus-in
Enhancer
(iii) Lagged ge
(i) (ii)
Enhancer
w
RNAPII
transcripƟon
Low abundance
of factors
InacƟve
regulatory
element
AcƟve regulatory element
Promoter strength and/or transcripƟonal level
High
High abundance
of factors
1. Active regulatory elements are divergently transcribed. (A) Both regulatory active gene promoters and gene-distal enhance
II) recruitment and transcription initiation are mediated by general transcription factors (GTFs) binding core promoter re
somes. This is facilitated by transcription factors (TFs), which often bind proximal to core promoters. Transcription often initiat
ucleosome-depleted region (NDR). (B) Gene expression is often preceded by, or changes concurrently with, changes in
xpressed) state (i), enhancers and promoters may, or may not, bind RNAPII. Upon stimulus (ii), transcriptional activity at enhance
ocal transcription and increases in RNAPII recruitment at the target gene promoter. (iii) Gene expression may lag behind trans
Stormo, G. D. et al. Nucleic Acids Research (1982)
17. 17
TFs
Regulatory acƟve
gene promoters and/or enhancers
Core promoter Core promoter
NDR
GTFs
RNAPII RNAPII
)
)
(B)
(i) Silent state
Enhancer
(ii) SƟmulus-in
Enhancer
(iii) Lagged ge
(i) (ii)
Enhancer
w
RNAPII
transcripƟon
Low abundance
of factors
InacƟve
regulatory
element
AcƟve regulatory element
Promoter strength and/or transcripƟonal level
High
High abundance
of factors
1. Active regulatory elements are divergently transcribed. (A) Both regulatory active gene promoters and gene-distal enhance
II) recruitment and transcription initiation are mediated by general transcription factors (GTFs) binding core promoter re
somes. This is facilitated by transcription factors (TFs), which often bind proximal to core promoters. Transcription often initiat
ucleosome-depleted region (NDR). (B) Gene expression is often preceded by, or changes concurrently with, changes in
xpressed) state (i), enhancers and promoters may, or may not, bind RNAPII. Upon stimulus (ii), transcriptional activity at enhance
ocal transcription and increases in RNAPII recruitment at the target gene promoter. (iii) Gene expression may lag behind trans
Stormo, G. D. et al. Nucleic Acids Research (1982)
TFIIIC
B box
Cohesin
Pol III
Enhancer
Condensin
tRNA gene
and SINE
CTCFCTCF
Module 2Module 1 Module 3 Module 4
CTCF
ETC locus
REVIEWS
Ong C-t and Corces V. G.
Nature Review Genetics 2014
18. 18
TFs
Regulatory acƟve
gene promoters and/or enhancers
Core promoter Core promoter
NDR
GTFs
RNAPII RNAPII
)
)
(B)
(i) Silent state
Enhancer
(ii) SƟmulus-in
Enhancer
(iii) Lagged ge
(i) (ii)
Enhancer
w
RNAPII
transcripƟon
Low abundance
of factors
InacƟve
regulatory
element
AcƟve regulatory element
Promoter strength and/or transcripƟonal level
High
High abundance
of factors
1. Active regulatory elements are divergently transcribed. (A) Both regulatory active gene promoters and gene-distal enhance
II) recruitment and transcription initiation are mediated by general transcription factors (GTFs) binding core promoter re
somes. This is facilitated by transcription factors (TFs), which often bind proximal to core promoters. Transcription often initiat
ucleosome-depleted region (NDR). (B) Gene expression is often preceded by, or changes concurrently with, changes in
xpressed) state (i), enhancers and promoters may, or may not, bind RNAPII. Upon stimulus (ii), transcriptional activity at enhance
ocal transcription and increases in RNAPII recruitment at the target gene promoter. (iii) Gene expression may lag behind trans
19. 19
TFs
Regulatory acƟve
gene promoters and/or enhancers
Core promoter Core promoter
NDR
GTFs
RNAPII RNAPII
)
)
(B)
(i) Silent state
Enhancer
(ii) SƟmulus-in
Enhancer
(iii) Lagged ge
(i) (ii)
Enhancer
w
RNAPII
transcripƟon
Low abundance
of factors
InacƟve
regulatory
element
AcƟve regulatory element
Promoter strength and/or transcripƟonal level
High
High abundance
of factors
1. Active regulatory elements are divergently transcribed. (A) Both regulatory active gene promoters and gene-distal enhance
II) recruitment and transcription initiation are mediated by general transcription factors (GTFs) binding core promoter re
somes. This is facilitated by transcription factors (TFs), which often bind proximal to core promoters. Transcription often initiat
ucleosome-depleted region (NDR). (B) Gene expression is often preceded by, or changes concurrently with, changes in
xpressed) state (i), enhancers and promoters may, or may not, bind RNAPII. Upon stimulus (ii), transcriptional activity at enhance
ocal transcription and increases in RNAPII recruitment at the target gene promoter. (iii) Gene expression may lag behind trans
Lindblad-Toh, K. et al. Nature (2011)
20. 20
TFs
Regulatory acƟve
gene promoters and/or enhancers
Core promoter Core promoter
NDR
GTFs
RNAPII RNAPII
)
)
(B)
(i) Silent state
Enhancer
(ii) SƟmulus-in
Enhancer
(iii) Lagged ge
(i) (ii)
Enhancer
w
RNAPII
transcripƟon
Low abundance
of factors
InacƟve
regulatory
element
AcƟve regulatory element
Promoter strength and/or transcripƟonal level
High
High abundance
of factors
1. Active regulatory elements are divergently transcribed. (A) Both regulatory active gene promoters and gene-distal enhance
II) recruitment and transcription initiation are mediated by general transcription factors (GTFs) binding core promoter re
somes. This is facilitated by transcription factors (TFs), which often bind proximal to core promoters. Transcription often initiat
ucleosome-depleted region (NDR). (B) Gene expression is often preceded by, or changes concurrently with, changes in
xpressed) state (i), enhancers and promoters may, or may not, bind RNAPII. Upon stimulus (ii), transcriptional activity at enhance
ocal transcription and increases in RNAPII recruitment at the target gene promoter. (iii) Gene expression may lag behind trans
Kim, T.H. and B. Ren, Annu Rev Genomics
Hum Genet, 2006
21. 21
TFs
Regulatory acƟve
gene promoters and/or enhancers
Core promoter Core promoter
NDR
GTFs
RNAPII RNAPII
)
)
(B)
(i) Silent state
Enhancer
(ii) SƟmulus-in
Enhancer
(iii) Lagged ge
(i) (ii)
Enhancer
w
RNAPII
transcripƟon
Low abundance
of factors
InacƟve
regulatory
element
AcƟve regulatory element
Promoter strength and/or transcripƟonal level
High
High abundance
of factors
1. Active regulatory elements are divergently transcribed. (A) Both regulatory active gene promoters and gene-distal enhance
II) recruitment and transcription initiation are mediated by general transcription factors (GTFs) binding core promoter re
somes. This is facilitated by transcription factors (TFs), which often bind proximal to core promoters. Transcription often initiat
ucleosome-depleted region (NDR). (B) Gene expression is often preceded by, or changes concurrently with, changes in
xpressed) state (i), enhancers and promoters may, or may not, bind RNAPII. Upon stimulus (ii), transcriptional activity at enhance
ocal transcription and increases in RNAPII recruitment at the target gene promoter. (iii) Gene expression may lag behind trans
Kim, T.H. and B. Ren, Annu Rev Genomics
Hum Genet, 2006
Segal E, Nature 2006
22. 22
TFs
Regulatory acƟve
gene promoters and/or enhancers
Core promoter Core promoter
NDR
GTFs
RNAPII RNAPII
)
)
(B)
(i) Silent state
Enhancer
(ii) SƟmulus-in
Enhancer
(iii) Lagged ge
(i) (ii)
Enhancer
w
RNAPII
transcripƟon
Low abundance
of factors
InacƟve
regulatory
element
AcƟve regulatory element
Promoter strength and/or transcripƟonal level
High
High abundance
of factors
1. Active regulatory elements are divergently transcribed. (A) Both regulatory active gene promoters and gene-distal enhance
II) recruitment and transcription initiation are mediated by general transcription factors (GTFs) binding core promoter re
somes. This is facilitated by transcription factors (TFs), which often bind proximal to core promoters. Transcription often initiat
ucleosome-depleted region (NDR). (B) Gene expression is often preceded by, or changes concurrently with, changes in
xpressed) state (i), enhancers and promoters may, or may not, bind RNAPII. Upon stimulus (ii), transcriptional activity at enhance
ocal transcription and increases in RNAPII recruitment at the target gene promoter. (iii) Gene expression may lag behind trans
Kim, T.H. and B. Ren, Annu Rev Genomics
Hum Genet, 2006
Segal E, Nature 2006
23. 23
TFs
Regulatory acƟve
gene promoters and/or enhancers
Core promoter Core promoter
NDR
GTFs
RNAPII RNAPII
)
)
(B)
(i) Silent state
Enhancer
(ii) SƟmulus-in
Enhancer
(iii) Lagged ge
(i) (ii)
Enhancer
w
RNAPII
transcripƟon
Low abundance
of factors
InacƟve
regulatory
element
AcƟve regulatory element
Promoter strength and/or transcripƟonal level
High
High abundance
of factors
1. Active regulatory elements are divergently transcribed. (A) Both regulatory active gene promoters and gene-distal enhance
II) recruitment and transcription initiation are mediated by general transcription factors (GTFs) binding core promoter re
somes. This is facilitated by transcription factors (TFs), which often bind proximal to core promoters. Transcription often initiat
ucleosome-depleted region (NDR). (B) Gene expression is often preceded by, or changes concurrently with, changes in
xpressed) state (i), enhancers and promoters may, or may not, bind RNAPII. Upon stimulus (ii), transcriptional activity at enhance
ocal transcription and increases in RNAPII recruitment at the target gene promoter. (iii) Gene expression may lag behind trans
Kim, T.H. and B. Ren, Annu Rev Genomics
Hum Genet, 2006
Andersson R et al., Genome Research 2009
24. 24
TFs
Regulatory acƟve
gene promoters and/or enhancers
Core promoter Core promoter
NDR
GTFs
RNAPII RNAPII
)
)
(B)
(i) Silent state
Enhancer
(ii) SƟmulus-in
Enhancer
(iii) Lagged ge
(i) (ii)
Enhancer
w
RNAPII
transcripƟon
Low abundance
of factors
InacƟve
regulatory
element
AcƟve regulatory element
Promoter strength and/or transcripƟonal level
High
High abundance
of factors
1. Active regulatory elements are divergently transcribed. (A) Both regulatory active gene promoters and gene-distal enhance
II) recruitment and transcription initiation are mediated by general transcription factors (GTFs) binding core promoter re
somes. This is facilitated by transcription factors (TFs), which often bind proximal to core promoters. Transcription often initiat
ucleosome-depleted region (NDR). (B) Gene expression is often preceded by, or changes concurrently with, changes in
xpressed) state (i), enhancers and promoters may, or may not, bind RNAPII. Upon stimulus (ii), transcriptional activity at enhance
ocal transcription and increases in RNAPII recruitment at the target gene promoter. (iii) Gene expression may lag behind trans
Kim, T.H. and B. Ren, Annu Rev Genomics
Hum Genet, 2006
Andersson R et al., Genome Research 2009
25. 25
TFs
Regulatory acƟve
gene promoters and/or enhancers
Core promoter Core promoter
NDR
GTFs
RNAPII RNAPII
)
)
(B)
(i) Silent state
Enhancer
(ii) SƟmulus-in
Enhancer
(iii) Lagged ge
(i) (ii)
Enhancer
w
RNAPII
transcripƟon
Low abundance
of factors
InacƟve
regulatory
element
AcƟve regulatory element
Promoter strength and/or transcripƟonal level
High
High abundance
of factors
1. Active regulatory elements are divergently transcribed. (A) Both regulatory active gene promoters and gene-distal enhance
II) recruitment and transcription initiation are mediated by general transcription factors (GTFs) binding core promoter re
somes. This is facilitated by transcription factors (TFs), which often bind proximal to core promoters. Transcription often initiat
ucleosome-depleted region (NDR). (B) Gene expression is often preceded by, or changes concurrently with, changes in
xpressed) state (i), enhancers and promoters may, or may not, bind RNAPII. Upon stimulus (ii), transcriptional activity at enhance
ocal transcription and increases in RNAPII recruitment at the target gene promoter. (iii) Gene expression may lag behind trans
Barski A et al., Cell 2007
Garber M et al., Mol Cell 2012
Mikkelsen T et al., Nature 2007
26. 26
Figure 2. Histone Methylation near Transcription Start Sites
(A)–(L) Profiles of the histone methylation indicated above each panel across the TSS for highly active, two stages of intermediately active and silent
genes are shown. Twelve thousand human genes were separated into twelve groups of one thousand genes according to their expression levels (see
Barski A et al., Cell 2007
27. 27
TFs
Regulatory acƟve
gene promoters and/or enhancers
Core promoter Core promoter
NDR
GTFs
RNAPII RNAPII
)
)
(B)
(i) Silent state
Enhancer
(ii) SƟmulus-in
Enhancer
(iii) Lagged ge
(i) (ii)
Enhancer
w
RNAPII
transcripƟon
Low abundance
of factors
InacƟve
regulatory
element
AcƟve regulatory element
Promoter strength and/or transcripƟonal level
High
High abundance
of factors
1. Active regulatory elements are divergently transcribed. (A) Both regulatory active gene promoters and gene-distal enhance
II) recruitment and transcription initiation are mediated by general transcription factors (GTFs) binding core promoter re
somes. This is facilitated by transcription factors (TFs), which often bind proximal to core promoters. Transcription often initiat
ucleosome-depleted region (NDR). (B) Gene expression is often preceded by, or changes concurrently with, changes in
xpressed) state (i), enhancers and promoters may, or may not, bind RNAPII. Upon stimulus (ii), transcriptional activity at enhance
ocal transcription and increases in RNAPII recruitment at the target gene promoter. (iii) Gene expression may lag behind trans
Bell J.T T et al., Genome Biology 2011
28. 28
TFs
Regulatory acƟve
gene promoters and/or enhancers
Core promoter Core promoter
NDR
GTFs
RNAPII RNAPII
)
)
(B)
(i) Silent state
Enhancer
(ii) SƟmulus-in
Enhancer
(iii) Lagged ge
(i) (ii)
Enhancer
w
RNAPII
transcripƟon
Low abundance
of factors
InacƟve
regulatory
element
AcƟve regulatory element
Promoter strength and/or transcripƟonal level
High
High abundance
of factors
1. Active regulatory elements are divergently transcribed. (A) Both regulatory active gene promoters and gene-distal enhance
II) recruitment and transcription initiation are mediated by general transcription factors (GTFs) binding core promoter re
somes. This is facilitated by transcription factors (TFs), which often bind proximal to core promoters. Transcription often initiat
ucleosome-depleted region (NDR). (B) Gene expression is often preceded by, or changes concurrently with, changes in
xpressed) state (i), enhancers and promoters may, or may not, bind RNAPII. Upon stimulus (ii), transcriptional activity at enhance
ocal transcription and increases in RNAPII recruitment at the target gene promoter. (iii) Gene expression may lag behind trans
Murrell A et al., Human Mol Genet 2004
van Laere AS et al., Nature 2003
29. 29
TFs
Regulatory acƟve
gene promoters and/or enhancers
Core promoter Core promoter
NDR
GTFs
RNAPII RNAPII
)
)
(B)
(i) Silent state
Enhancer
(ii) SƟmulus-in
Enhancer
(iii) Lagged ge
(i) (ii)
Enhancer
w
RNAPII
transcripƟon
Low abundance
of factors
InacƟve
regulatory
element
AcƟve regulatory element
Promoter strength and/or transcripƟonal level
High
High abundance
of factors
1. Active regulatory elements are divergently transcribed. (A) Both regulatory active gene promoters and gene-distal enhance
II) recruitment and transcription initiation are mediated by general transcription factors (GTFs) binding core promoter re
somes. This is facilitated by transcription factors (TFs), which often bind proximal to core promoters. Transcription often initiat
ucleosome-depleted region (NDR). (B) Gene expression is often preceded by, or changes concurrently with, changes in
xpressed) state (i), enhancers and promoters may, or may not, bind RNAPII. Upon stimulus (ii), transcriptional activity at enhance
ocal transcription and increases in RNAPII recruitment at the target gene promoter. (iii) Gene expression may lag behind trans
location, composition and turnover of nucle
and the patterns of post-translational histone m
tions. Technological advances in microarrays a
generation sequencing have enabled many of the
to be scaled genome-wide. Notable examples
the DNase I–seq9,10
, FAIRE–seq11
and Sono–seq12
a
chromatin accessibility; whole-genome and r
representation bisulphite sequencing (BS-seq
MeDIP-seq15
assays for DNA methylation;
MNase–seq16,17
and CATCH–IT18
assays for elu
nucleosome position and turnover, respective
technologies and their integration have been ex
reviewed elsewhere19,20
. In this section, we focu
tone modifications and, in particular, on how
wide ChIP–seq-mapping studies have enhan
understanding of the chromatin landscape.
Mapping histone modifications genome-wide. A
ChIP has been used since 1988 (REF. 21) to pro
matin structure at individual loci, its combinat
microarraysand,morerecently,next-generation
ing has provided far more precise and compr
views of histone modification landscapes, wh
highlighted roles for chromatin structures acros
genomic features and elements that were not
REVIEWS
Zhou V W et al. Nat Rev Genetics 2011
30. 30
Andersson R et al. TiG 2015
ed to neither enhancer nor promoters. Although generally
used to distinguish active from inactive enhancers [15],
H3K27ac is often also observed at active gene promoters
[14,53], to which it has a strong preference [55].
What, then, is the biological property reflected in
these marks? Recent work proposes that histone mod-
supported by the high relative importance of H3K4me
well as H3K27ac in predicting gene-expression levels f
histone modifications [57].
Although the idea that H3K4me3 is linked to transc
tional levels is difficult to test directly, there is s
supporting evidence already in the literature. For exam
Pekowska et al. replaced the endogenous Tcrb enha
with a mutated copy that confers a lower activity
observed a local increase in H3K4me1 and decreas
H3K4me3 compared with wild type [54], supportin
causal relation between transcriptional activity and
tone methylation. This notion is also consistent w
reports that H3K4 methyltransferases are recruited
the carboxy-terminal domain of RNAPII [58–60]. T
we argue that there is a relation between H3K4 met
ation and transcription levels that applies at both enh
cers and gene promoters.
However, the level of H3K4me3 is not related solel
transcription level, which is reflected by their relati
weak correlation (Figure 3B). Although H3K4 Set1 met
transferases are directly acquired by RNAPII, there i
observed bias of H3K4me3 to CpG-rich sequences med
ed by the CpG binding Cfp1 subunit of Set1 comple
[61]. The localization and level of H3K4me3 is fur
affected by the presence and position of the first exo
splice site, and inhibition of splicing reduces H3K4
levels, suggesting a link between splicing and H3K4
[62]. However, interfering with splicing is also likel
decrease the nuclear stability of a transcript [46,47]
discussed above, and, thus, is likely to decrease RNAPI
each regulatory element.
Understanding the relation between enhancer and
promoter function
The relation between the potential of each regula
element to act as a local promoter and its ability to enha
transcription at distal promoters remains poorly un
stood. Although based upon only a few cases, Li et
H3K4me3
TranscripƟon level
Stable RNA
H3K4me1
TranscripƟon level
Unstable RNA
(A)
(C)(B)
Highly transcribed
gene promoter / enhancer
Lowly transcribed
gene promoter / enhancer
High H3K4me3, low H3K4me1
H3K27ac
Key:
High H3K4me1, low H3K4me3
RNAPII RNAPII RNAPII RNAPII
TRENDS in Genetics
Figure 3. Transcriptional level is related to histone modifications at regulatory
elements. (A) Highly transcribed enhancers are often marked by histone H3 lysine
4 trimethylation (H3K4me3) and histone H3 lysine 27 acetylation (H3K27ac), making
them hard to distinguish from transcribed gene promoters using histone
modifications alone. Lowly transcribed gene promoters and gene-distal enhancers
are rarely marked by, or only by low levels of, H3K4me3 or H3K27ac, but often by
H3K4me1. (B) The level of H3K4me3 at the nucleosome-depleted regions (NDRs) at
the 50
end of transcripts encoding stable RNAs (e.g., mRNA) and unstable RNAs [e.g.,
enhancer-templated noncoding RNAs (eRNAs)] is correlated with their
transcriptional activity (see Figure 2 for the connection between RNA stability and
regulatory element). (C) The level of H3K4me1 at the NDRs of stable RNAs and
unstable RNAs is inversely correlated with their transcriptional activity. Nucleosome
illustrations in (A) reproduced, with permission, from [38]; (B,C) modified, with
permission, from [19].
Zhou V W et al. Nat Rev
Genetics 2011
Figure 3 | Chromatin patterns and regulation by promoter class. Promoters can be classified according to their CpG
content. High CpG-content promoters (HCPs) and low CpG-content promoters (LCPs) are subject to distinct chromatin
REVIEWS
32. Wenfei J et al.
Nature 25 Nov 2015
arepredictiveofgeneexpression.Finally,weapplyscDNase-seqtopools even single cells (Fig. 1a). A
g h i1,000 cells
62,704
Cell 1
40,855
Cell 1
40,855
Cell 2
40,918
a
FACS-sorted single cell
Lyse and digest with DNase I
Stop reaction, add circular carrier DNA
end-repair and adaptor ligation
PCR amplification of
small DNA fragments
Isolate desired fragments and sequencing
Schema of scDNase-seq
1,000 cells
62,704
Pooled five cells
49,988
0 0.01 0.02 0.03
0
0.01
0.02
0.03
Tagdensityof1,000cells
Tag density of 10,000 cells
r = 0.97
0 0.01 0.02 0.03
0
0.01
0.02
0.03
Tagdensityof100cells
Tag density of 1,000 cells
r = 0.79
c d e f
Tagdensityof1,000cells
0 0.01 0.02 0.03
0
0.01
0.02
0.03
Tag density of pooled single cells
r = 0.73
0 0.01 0.02 0.03
0
0.01
0.02
0.03
Tag density of cell 1
Tagdensityofcell2
r = 0.90
b
Chr7:
10,000 cells
1,000 cells
100 cells
Five single
3T3 cells
ENCODE
Fourteen single
ESCs
0
2
4
52150000 5225000050 kb
Fig
in
of
so
wi
lig
am
DN
dis
an
tra
de
14
the
lib
g–
ov
37. ChromImpute: Ernst J and Kellis M.
Nature Biotech 2014
As in b
Same-sample diff-marks features Same-mark diff-sample features
Combine in ensemble predictor trained in other samples
E1 E1
H3K27ac
H3K9ac
DNaseI
H3K4me3
H3K4me1
E8E7E6E5E4E3E2
E8E7E6E5E4E3E2
E1 E8E7E6E5E4E3E2
Target
mark
Target
mark
b
c
d
DDIT4 DNAJB12
H3K4me1
H3K4ac
H2AK5ac
H4K5ac
H2BK12ac
H3K18ac
H4K91ac
H2BK120ac
H4K8ac
H2BK15ac
H3K14ac
H2BK20ac
H2BK5ac
H3K23ac
H3K27ac
H3K9me1
H2AK9ac
H3K79me1
H3K4me2
H3K79me2
H3K56ac
H4K20me1
H2A.Z
H3K9ac
H3K36me3
DNase
H3K4me3
H3K27me3
H3K9me3
DNA methyl
H3K27me3
H3K36me3
H3K9me3
H3K27ac
H3K9ac
DNase
H3K4me2
H2A.Z
H3K79me2
H4K20me1
H2AK5ac
H2BK120ac
H2BK5ac
H3K18ac
H3K23ac
H3K4ac
H3K79me1
H4K8ac
H2BK12ac
H3K14ac
H4K91ac
H2BK15ac
H3K9me1
H2BK20ac
H3K56ac
H4K5ac
H3K23me2
H2AK9ac
H3T11ph
H4K12ac
DNAmethyl
RNAseq
Tier 1 Tier 2 Tier 3
d Imputed only Observed only
RefSeq genes
E017
E092
E080
E055
E090
E005
E089
E006
E111
E056
E063
E049
E084
E085
E096
E077
E094
E062
E113
E106
E107
Imputed
Imputed
MostE017-correlatedH3K36me3
signaltracksacrosssamples
MostH3K4me1-correlatedmarkswithinE017
As in
c
c
b
rview. (a) Matrix of observed and imputed datasets across 127 reference epigenomes (‘samples’), including 111
ect (rows 1–111) grouped and colored by cell/tissue type, and an additional 16 from ENCODE (rows 112–127),
38. R
T
PF
WE
CTCF
E
TSS
Segment class
TAF1
BRCA1
POLR2A
FOS
CHD2
NRF1
POLR3A
STAT3
EP300
Depleted
(log2 = −10.0)
1 2 3 4 5 6 1 2 3 4 5 6
Cell type in each
CTCF segment
Mean cell type in segment
Segmentcount
010,00025,000
Cell type in each
E segment
020,00040,000
1 2 3 4 5 6 1 2 3 4 5 6
Cell type in each
T segment
0100,000250,000
Cell type in each
TSS segment
04,0008,000
1 2 3 4 5 6
Cell type in each
R segment
0100,000250,000
2
6
10
Percentmethylated
R
CTCF
WE
Seg
c d
Figure 5 | Integration of ENCODE data by genome-wide segmentation.
a, Illustrative region with the two segmentation methods (ChromHMM and
Segway) in a dense view and the combined segmentation expanded to show
each state in GM12878 cells, beneath a compressed view of the GENCODE
gene annotations. Note that at this level of zoom and genome browser
resolution, some segments appear to overlap although they do not.
Segmentation classes are named and coloured according to the scheme in
Table 3. Beneath the segmentations are shown each of the normalized signals
that were used as the input data for the segmentations. Open chromatin signals
from DNase-seq from the University of Washington group (UW DNase) or the
ChIP-seq control sign
input to the segmenta
and RNA (right) elem
expressed as an obser
transcription factor o
map scale shown in t
between cell lines, sho
cell lines at specific ge
in all six cell lines for
methylation level at i
CTCF-binding-associated state is relatively invariant across cell types, with individual
regions frequently occupying the CTCF state across all six cell types
The ENCODE Consortium
Nature 2012
40. CTCF
Nature Reviews | Genetics
5mC
Nucleosome-
depleted region
Cell type A
HypermethylatedHypomethylated
CTCF
Cell type B
Immortalized cell
CTCF
CTCFCTCF CTCF
CTCF
Figure 2 | Regulation of CTCF binding to DNA. Constitutive binding sites of CCCTC-binding factor (CTCF), which
are bound by CTCF in cells from different tissues, are present in non-methylated and nucleosome-free regions.
Cell-type-specific CTCF binding is partly regulated by differential DNA methylation and nucleosome occupancy across
different cell types. This suggests that cells can use ATP-dependent chromatin remodelling complexes to regulate
nucleosome occupancy at specific CTCF-binding sites and control the interaction of this protein with DNA. In addition,
the methylation status of cell-type-specific CTCF-binding sites may be determined by a combination of activities of
methyltransferases and ten-eleven translocation (TET) enzymes that regulate the presence and levels of
5-methylcytosine (5mC) at specific sites. Immortalized cancer cell lines contain high levels of 5mC at CTCF-binding
sites, which correlates with the low CTCF occupancy in these cells. Filled red circles represent methylated DNA, and
open circles denote unmethylated DNA.
REVIEWS
Ong C-t and Corces V. G.
Nature Review Genetics 2014
41. Odd-numbere
nucleosome
Even-number
nucleosome
Plane of
nucleosome la
DNA
Protein scaffo
Chromatin loo
Metaphase
chromosome
1
2
3
4
5
1
3
5
2
41
2
3 5
f Organization of whole
chromosomes inside the
nucleus (quaternary level)
d Loops of 30-nm
fiber (tertiary level)
e Interdigitating layers of
irregularly organized
nucleosomes (tertiary level)
a 11-nm fiber
(primary level)
b Nucleosome stacking
(folded 11-nm fiber with
zigzag linker DNA)
c 30-nm fiber
(secondary level)
Nucleus
Figure 1
Different levels of chromatin compaction. (a) Multiple nucleosomes in a row form the 11-nm fiber that is the primary level of
chromatin compaction. Alternating nucleosomes are depicted with blue and green surfaces. (b) The 11-nm fiber folds on itself to f
umanGenet.2012.13:59-82.Downloadedfromwww.annualreviews.org
dedbyUniversityofUppsalaon11/26/15.Forpersonaluseonly.
Odd-numbered
nucleosome
Even-numbered
nucleosome
Plane of
nucleosome layers
DNA
Protein scaffold
Chromatin loop
Metaphase
chromosome
1
2
3
4
5
1
3
5
2
41
2
3 5
f Organization of whole
chromosomes inside the
nucleus (quaternary level)
d Loops of 30-nm
fiber (tertiary level)
e Interdigitating layers of
irregularly organized
nucleosomes (tertiary level)
a 11-nm fiber
(primary level)
b Nucleosome stacking
(folded 11-nm fiber with
zigzag linker DNA)
c 30-nm fiber
(secondary level)
Nucleus
Figure 1
Different levels of chromatin compaction. (a) Multiple nucleosomes in a row form the 11-nm fiber that is the primary level of
chromatin compaction. Alternating nucleosomes are depicted with blue and green surfaces. (b) The 11-nm fiber folds on itself to form
two stacks/columns of nucleosomes such that odd-numbered nucleosomes interact with other odd-numbered nucleosomes and even-
numbered nucleosomes interact with other even-numbered nucleosomes. The linker DNA zigzags between the two nucleosome stacks.
om.HumanGenet.2012.13:59-82.Downloadedfromwww.annualreviews.org
providedbyUniversityofUppsalaon11/26/15.Forpersonaluseonly.
Sajan S.A and Hawkins R.D.
Annu. Rev. Genomics Hum. Genet. 2012
GG13CH03-Hawkins
ARI
25 July 2012
11:40
Odd-numbered
nucleosome
Even-numbered
nucleosome
Plane of
nucleosome layers
DNA
Protein scaffold
Chromatin loop
Metaphase
chromosome
1
2 3
4
5
1
3
5
2
4
1
2 3
5
f Organization of whole
chromosomes inside the
nucleus (quaternary level)
d Loops of 30-nm
fiber (tertiary level)
e Interdigitating layers of
irregularly organized
nucleosomes (tertiary level)
a 11-nm fiber
(primary level)
b Nucleosome stacking
(folded 11-nm fiber with
zigzag linker DNA)
c 30-nm fiber
(secondary level)
Nucleus
Figure 1
ent levels of chromatin compaction. (a) Multiple nucleosomes in a row form the 11-nm fiber that is the primary level of
ompaction. Alternating nucleosomes are depicted with blue and green surfaces. (b) The 11-nm fiber folds on itself to form
s of nucleosomes such that odd-numbered nucleosomes interact with other odd-numbered nucleosomes and even-
interact with other even-numbered nucleosomes. The linker DNA zigzags between the two nucleosome stacks.
ms a two-start helix to produce the 30-nm chromatin fiber that is the secondary level of compaction.
nd forms a more compact fiber that is arranged in loops (blue), with some portions attached to a
rtiary levels of compaction. (e) The 30-nm fiber may also result in the formation of
leosomes, particularly in metaphase chromosomes. Note that these plates do cont
0-nm fibers or another type. Regardless, this is another tertiary level of
mensional organization of entire chromosomes inside the nucleus a
embrane. The black lines on the pink chromosome represe
Quatern
of chro
the 3D
chro
rel
(Figure
1f). It is
e is affected
within
t.2012.13:59-82.Downloadedfromwww.annualreviews.org
versityofUppsalaon11/26/15.Forpersonaluseonly.
lear
s of
nct
ins
96,97
.
een
asts
ete
ains
were
d to
and
ugh
ted
ned
ted
eri-
ina
ing
ains
fer-
rge
up
the
ma-
also
and
t on
ose
ted
CKs
ons
e in
ave
ned
s. It
Figure 5 | Histone modification signatures associated
with features in the mammalian cell nucleus.
Signature histone modifications correlate with various
nuclear features, although the relationships might be
indirect. Chromatin with modifications generally
associated with active transcription (green dots) often
replicates early, whereas chromatin with generally
repressive modifications (purple dots) replicates late.
Regions enriched for some sets of active modifications
(blue dots) may converge into transcription factories
(TRFs). Blocks of histone H3 lysine 27 trimethylation
(H3K27me3; red dots) may form Polycomb bodies (Pc)
and diffuse domains marked by H3K9me2 or H3K9me3
REVIEWS
ARI
25
July 2012
11:40
Odd-num
bered
nucleosom
e
Even-num
bered
nucleosom
e
Plane of
nucleosom
e layers
DNA
Protein
scaffold
Chrom
atin
loop
M
etaphase
chrom
osom
e
1 2
3
4
5
1
3
5
2
4
1 2
3
5
f Organization
of whole
chrom
osom
es inside the
nucleus (quaternary level)
d
Loops of 30-nm
fiber (tertiary level)
e
Interdigitating
layers of
irregularly organized
nucleosom
es (tertiary level)
a
11-nm
fiber
(prim
ary level)
b
Nucleosom
e stacking
(folded
11-nm
fiber with
zigzag
linker DNA)
c
30-nm
fiber
(secondary level)
Nucleus
ure
1
nt levels of chrom
atin
com
paction. (a) M
ultiple nucleosom
es in
a row
form
the 11-nm
fiber that is the pr
n
com
paction. Alternating
nucleosom
es are depicted
with
blue and
green
surfaces. (b) T
he 11-nm
fi
olum
ns of nucleosom
es such
that odd-num
bered
nucleosom
es interact with
other odd-num
b
eosom
es interact with
other even-num
bered
nucleosom
es. T
he linker D
N
A
zigzags be
-nm
fiber form
s a two-start helix to
produce the 30-nm
chrom
atin
fiber that is th
twists further and
form
s a m
ore com
pact fiber that is arranged
in
loops (bl
T
his is one of the tertiary levels of com
paction. (e) T
he 30-nm
fiber m
regularly oriented
nucleosom
es, particularly in
m
etaphase chro
unclear whether they are 30-nm
fibers or another type. R
ry level refers to
the three-dim
ensional organizatio
well as with
the inner nuclear m
em
brane. T
h
above.
9,
26)
o
rep-ng.
inner
nuc
known
by
9-82.Downloaded
from
www.annualreviews.org
Uppsalaon
11/26/15.Forpersonaluseonly.
location, composition and turnover of nucleosomes;
and the patterns of post-translational histone modifica-
tions. Technological advances in microarrays and next-
generation sequencing have enabled many of these assays
to be scaled genome-wide. Notable examples include:
the DNase I–seq9,10
, FAIRE–seq11
and Sono–seq12
assays for
chromatin accessibility; whole-genome and reduced-
representation bisulphite sequencing (BS-seq)13,14
and
MeDIP-seq15
assays for DNA methylation; and the
MNase–seq16,17
and CATCH–IT18
assays for elucidating
nucleosome position and turnover, respectively. These
technologies and their integration have been extensively
reviewed elsewhere19,20
. In this section, we focus on his-
tone modifications and, in particular, on how genome-
wide ChIP–seq-mapping studies have enhanced our
understanding of the chromatin landscape.
Mapping histone modifications genome-wide. Although
ChIP has been used since 1988 (REF. 21) to probe chro-
matin structure at individual loci, its combination with
microarraysand,morerecently,next-generationsequenc-
ing has provided far more precise and comprehensive
views of histone modification landscapes, which have
highlighted roles for chromatin structures across diverse
genomic features and elements that were not appreci-
ated in targeted studies. The basis of ChIP is the immu-
noprecipitation step, in which an antibody is used to
enrich chromatin that carries a histone modification (or
other epitope) of interest. In ChIP–seq, next-generation
technology is used to deep sequence the immunoprecip-
itated DNA molecules and thereby produce digital maps
of ChIP enrichment (BOX 1). An example is the compre-
hensive work by Keji Zhao’s group to profile 39 different
histone methylation and acetylation marks genome-wide
in human CD4+
T cells22,23
. These maps and similar data
sets24–26
have associated particular modifications with
gene activation or repression and with various genomic
features, including promoters, transcribed regions,
enhancers and insulators (FIG. 2). These and subsequent
Figure 1 | Layers of chromatin organization in the mammalian cell nucleus.
Broadly, features at different levels of chromatin organization are generally associated
with inactive (off) or active (on) transcription. From the top, genomic DNA is methylated
(Me) on cytosine bases in specific contexts and is packaged into nucleosomes, which
vary in histone composition and histone modifications (for example, histone H3 lysine 9
trimethylation (H3K9me3)); these features constitute the primary layer of chromatin
REVIEWS
Ong C-t and Corces V. G.
Nature Review Genetics 2014
42. CTCF molecule
Biotin
Adapter A with
an Mme1 site
Adapter B with
an Mme1 site
Chromatin that
intervenes between
segments that interact
Distal genomic
segments that interact
with each other via
looping of chromatin
Transcription
factor molecule
1
2
3
4
5
6
7
8
9
Reverse cross-links, digest with Mme1,
and capture biotinylated fragments on
streptavidin beads
Reverse cross-links,
shear, and capture
biotinylated fragments on
streptavidin beads
High-throughput
paired-end sequencing
High-throughput
paired-end sequencing
Dilute sample and ligate
to favor intramolecular
ligation events
a Hi-C
Digest chromatin with a
restriction enzyme that
leaves 5' overhangs
Fill in overhangs
with nucleotides, one of
which is biotinylated
Mix the two aliquots, dilute, and allow
intramolecular ligation to occur (some
intermolecular ligation may also occur)
1
2
3
4
5
6
7
8
9
b ChIA-PET
Sonicate chromatin
Aliquot A Aliquot B
Divide into two aliquots and ligate each
aliquot with a different biotinylated
adapter containing an Mme1 restriction site
Cross-linked chromatin
Annu.Rev.Genom.HumanGenet.2012.13:59-82.Downloadedfromwww.annualreviews.org
AccessprovidedbyUniversityofUppsalaon11/26/15.Forpersonaluseonly.
Additionally, in metaphase chromosomes
the chromatin exists in platelike structures
containing interdigitating layers of irregularly
all regions of the genome contain nucleosomes
at any given time. Nuclease digestion and
other biochemical and genetic methods have
CTCF molecule
Biotin
Adapter A with
an Mme1 site
Adapter B with
an Mme1 site
Chromatin that
intervenes between
segments that interact
Distal genomic
segments that interact
with each other via
looping of chromatin
Transcription
factor molecule
Dilute sample and ligate
to favor intramolecular
ligation events
a Hi-C
Digest chromatin with a
restriction enzyme that
leaves 5' overhangs
Fill in overhangs
with nucleotides, one of
which is biotinylated
Mix the two aliquots, dilute, and allow
intramolecular ligation to occur (some
intermolecular ligation may also occur)
1 3 7
9
b ChIA-PET
Sonicate chromatin
Aliquot A Aliquot B
Divide into two aliquots and ligate each
aliquot with a different biotinylated
adapter containing an Mme1 restriction site
Cross-linked chromatin
Sajan S.A and Hawkins R.D.
Annu. Rev. Genomics Hum. Genet. 2012
43. Reverse cross-links
Intramolecular
ligation (circle
formation required)
Intramolecular ligation
(circle formation
not required)
c d4C(i) 4C(ii)
Reverse cross-links,
clone fragments,
and pick colonies
b 6C
ChIPChIP
Cross-linked chromatin
Digest chromatin with a
4-bp cutter restriction enzyme
[6-bp cutter for 4C(ii)]
Reverse
cross-links and
amplify one or
a few regions
by quantitative
PCR with specific
primers
3C
Obtain a measure
of interaction
frequency
High-throughput
sequencing of PCR
products
High-throughput
sequencing of PCR
products
Self-ligation of short
molecules to form circles,
and amplification using
bait-specific primers
(red arrows)
Trim linear fragments
with a 4-bp cutter
restriction enzyme
Reverse cross-links
and amplify using
bait-specific primers
(red arrows)
Digest clones with
original restriction
enzyme, run on gel,
and sequence clones
with multiple inserts
Intramolecular
ligation
(circle formation
not required)
3C, 5C
Intramolecular ligation
(circle formation not required)
a
5C
Reverse
cross-links
and amplify a
large number
of regions
by MLPA
High-throughput
sequencing of
PCR products
Bait-specific primers
used in 4C to amplify
all fragments that
interact with the bait
Vector in which
interacting fragments
are cloned in 6C
Digested fragments
from two 6C clones
resolved by gel
electrophoresis
Primers
complementary to
the universal linkers
for amplification of
multiple interacting
segments in 5C
Sequence-specific
primers (colored
portions) with
universal linkers
(black and gray) for
detecting long-range
chromatin interactions
via MLPA-PCR in 5C
Sequence-specific
primers for detecting
a given long-range
chromatin interaction
in 3C
Antibody specific for
a particular
transcription factor
Chromatin that
intervenes between
segments that interact
Distal genomic
segments that
interact with each
other via looping of
chromatin (red is a
bait used in 4C)
Transcription factor
molecules
CTCF molecule
Annu.Rev.Genom.HumanGenet.2012.13:59-82.Downloadedfromwww.annualreviews.org
AccessprovidedbyUniversityofUppsalaon11/26/15.Forpersonaluseonly.
Sajan S.A and Hawkins R.D.
Annu. Rev. Genomics Hum. Genet. 2012
46. Rao S.S.P. et al
Cell 2014
C
D
Figure 1. We Used In Situ Hi-C to Map over 15 Billion Chromatin Contacts across Nine Cell Types in Human and Mous
Resolution in Human Lymphoblastoid Cells
(A) During in situ Hi-C, DNA-DNA proximity ligation is performed in intact nuclei.
47. Rao S.S.P. et al
Cell 2014
C
D
Figure 1. We Used In Situ Hi-C to Map over 15 Billion Chromatin Contacts across Nine Cell Types in Human and Mouse, Achieving 1 kb
Resolution in Human Lymphoblastoid Cells
(A) During in situ Hi-C, DNA-DNA proximity ligation is performed in intact nuclei.
(B) Contact matrices from chromosome 14: the whole chromosome, at 500 kb resolution (top); 86–96 Mb/50 kb resolution (middle); 94–95 Mb/5 kb resolution
(bottom). Left: GM12878, primary experiment; Right: biological replicate. The 1D regions corresponding to a contact matrix are indicated in the diagrams above
and at left. The intensity of each pixel represents the normalized number of contacts between a pair of loci. Maximum intensity is indicated in the lower left of each
panel.
(C) We compare our map of chromosome 7 in GM12878 (last column) to earlier Hi-C maps: Lieberman-Aiden et al. (2009), Kalhor et al. (2012), and Jin et al. (2013).
(D) Overview of features revealed by our Hi-C maps. Top: the long-range contact pattern of a locus (left) indicates its nuclear neighborhood (right). We detect at
least six subcompartments, each bearing a distinctive pattern of epigenetic features. Middle: squares of enhanced contact frequency along the diagonal (left)
indicate the presence of small domains of condensed chromatin, whose median length is 185 kb (right). Bottom: peaks in the contact map (left) indicate the
presence of loops (right). These loops tend to lie at domain boundaries and bind CTCF in a convergent orientation.
See also Figure S1, Data S1, I–II, and Tables S1 and S2.
Cell 159, 1665–1680, December 18, 2014 ª2014 Elsevier Inc. 1667
D
er 15 Billion Chromatin Contacts across Nine Cell Types in Human and Mouse, Achieving 1 kb
on is performed in intact nuclei.
48. = 13
AGGTGGCGCCAGATCCC-3’
17.6
1 kb resolution
Chr 1
Chr1
17.6 Mb17.4
0 0.5 1 1.5 2 2.5 3 3.5 4
Number of PeaksD
ardmotif
Percentage of peak loci bound
(2%)(3%)(3%)(92%)
AGGTGGCAG
x 1000
CTCF anchor
(arrowhead indicates
motif orientation)
Loop domain
Ordinary domain
290 Kb
110
Kb
190 Kb
350 Kb
270 Kb
130 Kb
450 Kb
170
Kb
F
6. Many Loops Demarcate Contact Domains; The Vast Majority of Loops Are Anchored at a Pair of Convergent CTCF/RAD21/SMC3
Sites
grams of corner scores for peak pixels versus random pixels with an identical distance distribution.
act matrix for chr4:20.55 Mb–22.55 Mb in GM12878, showing examples of transitive and intransitive looping behavior.
ent of peak loci bound versus fold enrichment for 76 DNA-binding proteins.
pairs of CTCF motifs that anchor a loop are nearly all found in the convergent orientation.
(legend continued on next page)
Cell 159, 1665–1680, December 18, 2014 ª2014 Elsevier Inc.Rao S.S.P. et al
Cell 2014
Vast Majority of Loops Are Anchored at a Pair of Convergent CTCF/RAD21/SMC3 Binding Sites
C E
= 13
= 30
Intransitive
Chr
22.55
5’-GAGCAATTCCGCCCCCTGGTGGCAGATCTG-3’
5’-GGCGGAGACCACAAGGTGGCGCCAGATCCC-3’
17.417.6
1 kb resolution
CTCF
RAD21
SMC3
Chr 1
Chr1
17.6 Mb17.4
0 0.5 1 1.5 2 2.5 3 3.5 4
Number of PeaksD
Reverse motif
Forwardmotif
FoldChange
0
0.5
1.0
1.5
2.0
2.5
0% 20% 40% 60% 80% 100%
Percentage of peak loci bound
YY1
ZNF143
CTCF
RAD21
SMC3
0 1 2-1-2
Corner score
0
1
2
Numb
(2%)(3%)(3%)(92%)
CTGCCACCTNGTGGconsensus
CCACNAGGTGGCAGconsensus
x 1000
Loop domain
Ordinary domain 350 Kb
270 Kb
450 Kb
170
F
49. TFIIIC Cohesin
SINE
tRNA
gene
Gene
Enhancer
c
b
a Interaction heat map
Enhancer facilitatorEnhancer blocker
Gene
CTCF
TAD interiorTAD border
CTCF-binding
sites
TADs
Ong C-T and Corces V. G.
Nature Review Genetics 2014
TAD Borders: CTCF, cohesin,
condensin, TFIIIC, SINEs,
hosekeeping genes, SMC3,
RAD21
Intra-TAD: Cohesin, Mediator
complex
50. Ong C-T and Corces V. G.
Nature Review Genetics 2014
Cohesin
Nature Reviews | Genetics
Housekeeping gene tRNA gene
Cp190
D. melanogaster
ChromatorETC locus
SINE
tRNA
gene
Gene
CTCF
CTCFCTCF CTCF Pol III
SINE
TFIIICMammals
c
Condensin
Gene
TFIIIC
CondensinSu(Hw)
BEAF-32
Mod(mdg4)
Cohesin
Figure 7 |CTCF regulates three-dimensional genome architecture. a | Schematic data generated by Hi-C in
mammalian cells are shown in an interaction heat map of a ~2.5-Mb chromosome segment. The topologically associating
domains (TADs) and their borders are indicated. b | The presence of multiple binding sites for CCCTC-binding factor
(CTCF) and TFIIIC at TAD borders may contribute to the establishment of the border. This arrangement may provide an
explanation for the observed function of CTCF as an enhancer blocker. Conversely, CTCF-binding sites within TADs may
facilitate enhancer–promoter looping through the recruitment of cohesin. The blue box denotes the promoter of the
gene. c | Chromatin features of TAD borders in mammals and are shown. The TAD borders in
mammals are enriched for housekeeping and tRNA genes, short interspersed nuclear elements (SINEs) and
CTCF-binding sites. In , they are enriched for highly transcribed genes and clusters of binding sites for
various architectural proteins, such as Suppressor of Hairy wing (Su(Hw)), Modifier of mdg4 (Mod(mdg4)) and Boundary
element-associated factor of 32 kDa (BEAF-32). The roles of TFIIIC, cohesin and condensin proteins in mediating TAD
51. Rao S.S.P. et al
Cell 2014
t the appearance of a loop in a cell type was frequently
companied by the activation of a gene whose promoter over-
ped one of the peak loci. For example, a cell-type-specific
markedly upregulated in GM12878. When we compa
GM12878 to the five other human cell types for which ENCO
RNA-seq data were available, the results were very sim
C
E
ure 4. Loops Are Often Preserved across Cell Types and from Human to Mouse
Examples of peak and domain preservation across cell types. Annotated peaks are circled in blue. All annotations are completely independent.
Of the 3,331 loops we annotate in mouse CH12-LX, 1,649 (50%) are orthologous to loops in human GM12878.
E) Conservation of 3D structure in synteny blocks. The contact matrices in (C) are shown at 25 kb resolution. (D) and (E) are shown at 10 kb resolution
52. A C
B
D E
Figure 7. Diploid
domains and
CTCF-Binding Ta
tive X Chromoso
(A) The frequency o
in SNP allele assign
two paired read
read pairs are over
(B) Preferential int
Left/top is materna
aberrant contact
and 11/paternal (ci
(C) Top: in our unp
we observe two loo
the maternally-exp
the paternally-exp
HIDAD. Using diplo
loops: the HIDAD-H
maternal homolog
present only on the
(D) The inactive (pa
(bottom) is partitio
domains’’ not seen
(top). DXZ4 lies at t
are shown at 500 k
(E) The ‘‘superloop
present in the unp
the paternal GM12
the map of the fe
right); it is absent fr
Rao S.S.P. et al
Cell 2014
53. A C
B
D E
Figure 7. Diploid
domains and
CTCF-Binding Ta
tive X Chromoso
(A) The frequency o
in SNP allele assign
two paired read
read pairs are over
(B) Preferential int
Left/top is materna
aberrant contact
and 11/paternal (ci
(C) Top: in our unp
we observe two loo
the maternally-exp
the paternally-exp
HIDAD. Using diplo
loops: the HIDAD-H
maternal homolog
present only on the
(D) The inactive (pa
(bottom) is partitio
domains’’ not seen
(top). DXZ4 lies at t
are shown at 500 k
(E) The ‘‘superloop
present in the unp
the paternal GM12
the map of the fe
right); it is absent fr
HIDAD-H19 loop
present only on the
maternal homolog
!
!
HIDAD-Igf2 loop is
present only on the
paternal homolog
Rao S.S.P. et al
Cell 2014
54. • Contact domains median lengh=185kb
• W/i domain: interact frequently, have similar patterns of chromatin
modifications, and exhibit similar long-range contact patterns.
• Domains tend to be conserved across cell types and between human and
mouse.
• Chromatin modifications pattern w/i domain changes, domain’s long-range
contact pattern also changes.
• Domains exhibit 6 patterns of long-range contacts (subcompartments)
• Subcompartments associated with distinct chromatin patterns
• In densest map (GM12878), observed ~10k loops
• CTCF and the cohesin subunits RAD21 and SMC3 associate with loops (86%)
• CTCF motifs at loop anchors occurs in convergent orientation >90%
• Motif orientation between loci are separated, on average, 360 kb
• Boundaries observed associated with either subcompartment transitions
(approx every 300 kb), or loops (approx every 200 kb). Many are associated
with both.
55. Highlights
Matteo Vietri R
Christopher B
Suzana Hadju
Correspond
s.hadjur@ucl.a
In Brief
To explore the
the evolution o
structures, Vie
four mammali
direct link bet
divergence an
chromatin dom
point to a dire
driving structu
Accession N
Vietri Rudan M. et al
Cell Reports 2015
57. Sanborn A.L. et al
PNAS 2015
tribution of 3D
explains a much
r, it provides a
form between
n the same cell
del also explains
ental data.
l Results, Given
whether the ex-
ental results in
data alone.
arget region on
ated an in silico
adding forward
observed in ex-
rength of each
unit would halt)
hor orientation
motif associated
ta.
mer in a solvent
sulting contact
ned using Hi-C
ks and contact
d appropriate ɣ
in. The results
S12D).
ing the tension
n CTCF ChIP-
n based on the
k. However, to
mental results,
es that do not
on: Loops were
and the likeli-
h of the peaks,
e number and
simulations did
l (SI Appendix,
20.3022.6020.3022.60
20.30 22.60Mb
A
Chr4
CTCF
ChIP-seq
Binding
Strength
B
(i)
(ii)
(iii)
(iv)
Extrusion complex
Stop!
= 90
CTCF motif
-0.70
10-1
10-2
10-3
10-4
104
105
106
C
Forward
Reverse
Distance, bp
Contactprobability
40
0
1
0
Extrusion globule
D
Fig. 5. Model based on loop extrusion makes it possible to recapitulate Hi-C
maps accurately using only CTCF ChIP-Seq results. (A, i and ii) Extrusion
complex loads onto the fiber at a random locus, forming an extremely short-
range loop. (A, iii) As the two subunits move in opposite directions along the
fiber, the loop grows and the extruded fiber forms a domain. (A, iv) When
a subunit detects a motif on the appropriate strand, it can stop sliding.
ND
BIOLOGY
PNASSEECOMMENTARY
l Results, Given
whether the ex-
ental results in
data alone.
arget region on
ated an in silico
adding forward
observed in ex-
rength of each
unit would halt)
hor orientation
motif associated
ta.
mer in a solvent
sulting contact
ned using Hi-C
ks and contact
d appropriate ɣ
in. The results
S12D).
ing the tension
n CTCF ChIP-
n based on the
k. However, to
mental results,
es that do not
on: Loops were
and the likeli-
h of the peaks,
he number and
simulations did
l (SI Appendix,
and Is Consistent
multaneously by
hips among the
” for GM12878
20.3022.6020.3022.60
20.30 22.60Mb
Chr4
CTCF
ChIP-seq
Binding
Strength
B
(iii)
(iv)
Stop!
= 90
10-4
104
105
106
Forward
Reverse
Distance, bp
40
0
1
0
Extrusion globule
D
Fig. 5. Model based on loop extrusion makes it possible to recapitulate Hi-C
maps accurately using only CTCF ChIP-Seq results. (A, i and ii) Extrusion
complex loads onto the fiber at a random locus, forming an extremely short-
range loop. (A, iii) As the two subunits move in opposite directions along the
fiber, the loop grows and the extruded fiber forms a domain. (A, iv) When
a subunit detects a motif on the appropriate strand, it can stop sliding.
Unlike diffusion, extrusion cannot mediate co-location of motifs on different
chromosomes. (B) Three-dimensional rendering of a 3-Mb extrusion globule
from the ensemble described below. Convergent CTCF anchors (orange
spheres) lead to an unknotted loop spanning a compact, spatially segre-
gated contact domain (highlighted in blue). (C) Contact probability vs. dis-
BIOPHYSICSAND
COMPUTATIONALBIOLOGY
SEECO
58. Sanborn A.L. et al
PNAS 2015
D
E
A B
A
B
C
133.8 134.55
Chr 1
A
180.3 181.3
CTCF
ChIP-seq
Binding
Strength
Prediction Experiment Prediction Experiment
B
Chr 1
0
1
0
40
0
1
0
1
0
1
0
1
0
400
0
1
0
1
0
1
133.8 134.55 Mb 180.3 181.3 Mb
CTCF
ChIP-seq
Binding
Strength
788
325
10014
X X
X X
X X
XXX
90269
88672
1953141
X X
X X X
X
XX XX
XX
Chr 8 Chr 8
A B C A B C D E F D E F
D
E
A B
C
A
B
C
Chr 1
180.3 181.3
Prediction Experiment
Chr 1
0
1
0
1
0
1
0
1
180.3 181.3 Mb
Binding
Strength
90269
88672
1953141
X X
X
X X
X
XX XX
XX
D E F D E F
SEECOMMENTARY
31.3 32.3
Prediction Experiment
C
Chr 5
0
1
0
1
0
300
31.3 32.3 Mb
CTCF
ChIP-seq
Binding
Strength
X X
X
1509
655
Chr 5
E
Exclusion
0
1
325
23934
6712
18638
12325
X X
X X
1953141
1363122
XX XX
XX
G H I G H I
of CTCF motifs allows reengineering of loops in accordance with the convergent rule; the resulting contact maps can be predicte
lations. (A) Results of CRISPR/Cas9-based genome editing experiments at chr8:133.8–134.55 Mb in HAP1 cells. Extrusion simulat
ata (Right) are shown. (A, first row) Contact map for the WT locus, calculated using in silico simulations (Left), closely matches
experiments (Right). (A, second row) Deletion of A/Forward eliminates the A-B and A-C loops and the contact domain boundar
59. Sanborn A.L. et al
PNAS 2015
probability exhibits
different exponent
our low-resolution
This value is in
librium. To determ
consistent with a f
mains, we proved a
the Minkowski (fra
is mapped using a f
known theorem of
we find that values
1 and 2, implying t
globule. We illustr
iant of the famou
snakes through a 2D
achieving ɣ close to
nomic questions to
unrelated to biolog
Another way of
simulations to iden
original Hi-C study
external forces natu
ɣ = 1. In the prese
ternal forces, attrac
a role. We found
forces results in a
when external forc
process is symmetri
At the other extrem
along the polymer
Loop Domain
Smc3 Smc1
Rad21
SA1/2
CTCF
A
C
B
CTCF motif
CTCF
Cohesin
Fig. 8. We hypothesize that loops are formed during interphase by an
extrusion mechanism comprising CTCF and cohesin. Here, we illustrate pos-
60. Odd-numbere
nucleosome
Even-number
nucleosome
Plane of
nucleosome la
DNA
Protein scaffo
Chromatin loo
Metaphase
chromosome
1
2
3
4
5
1
3
5
2
41
2
3 5
f Organization of whole
chromosomes inside the
nucleus (quaternary level)
d Loops of 30-nm
fiber (tertiary level)
e Interdigitating layers of
irregularly organized
nucleosomes (tertiary level)
a 11-nm fiber
(primary level)
b Nucleosome stacking
(folded 11-nm fiber with
zigzag linker DNA)
c 30-nm fiber
(secondary level)
Nucleus
Figure 1
Different levels of chromatin compaction. (a) Multiple nucleosomes in a row form the 11-nm fiber that is the primary level of
chromatin compaction. Alternating nucleosomes are depicted with blue and green surfaces. (b) The 11-nm fiber folds on itself to f
umanGenet.2012.13:59-82.Downloadedfromwww.annualreviews.org
dedbyUniversityofUppsalaon11/26/15.Forpersonaluseonly.
Odd-numbered
nucleosome
Even-numbered
nucleosome
Plane of
nucleosome layers
DNA
Protein scaffold
Chromatin loop
Metaphase
chromosome
1
2
3
4
5
1
3
5
2
41
2
3 5
f Organization of whole
chromosomes inside the
nucleus (quaternary level)
d Loops of 30-nm
fiber (tertiary level)
e Interdigitating layers of
irregularly organized
nucleosomes (tertiary level)
a 11-nm fiber
(primary level)
b Nucleosome stacking
(folded 11-nm fiber with
zigzag linker DNA)
c 30-nm fiber
(secondary level)
Nucleus
Figure 1
Different levels of chromatin compaction. (a) Multiple nucleosomes in a row form the 11-nm fiber that is the primary level of
chromatin compaction. Alternating nucleosomes are depicted with blue and green surfaces. (b) The 11-nm fiber folds on itself to form
two stacks/columns of nucleosomes such that odd-numbered nucleosomes interact with other odd-numbered nucleosomes and even-
numbered nucleosomes interact with other even-numbered nucleosomes. The linker DNA zigzags between the two nucleosome stacks.
om.HumanGenet.2012.13:59-82.Downloadedfromwww.annualreviews.org
providedbyUniversityofUppsalaon11/26/15.Forpersonaluseonly.
Sajan S.A and Hawkins R.D.
Annu. Rev. Genomics Hum. Genet. 2012
GG13CH03-Hawkins
ARI
25 July 2012
11:40
Odd-numbered
nucleosome
Even-numbered
nucleosome
Plane of
nucleosome layers
DNA
Protein scaffold
Chromatin loop
Metaphase
chromosome
1
2 3
4
5
1
3
5
2
4
1
2 3
5
f Organization of whole
chromosomes inside the
nucleus (quaternary level)
d Loops of 30-nm
fiber (tertiary level)
e Interdigitating layers of
irregularly organized
nucleosomes (tertiary level)
a 11-nm fiber
(primary level)
b Nucleosome stacking
(folded 11-nm fiber with
zigzag linker DNA)
c 30-nm fiber
(secondary level)
Nucleus
Figure 1
ent levels of chromatin compaction. (a) Multiple nucleosomes in a row form the 11-nm fiber that is the primary level of
ompaction. Alternating nucleosomes are depicted with blue and green surfaces. (b) The 11-nm fiber folds on itself to form
s of nucleosomes such that odd-numbered nucleosomes interact with other odd-numbered nucleosomes and even-
interact with other even-numbered nucleosomes. The linker DNA zigzags between the two nucleosome stacks.
ms a two-start helix to produce the 30-nm chromatin fiber that is the secondary level of compaction.
nd forms a more compact fiber that is arranged in loops (blue), with some portions attached to a
rtiary levels of compaction. (e) The 30-nm fiber may also result in the formation of
leosomes, particularly in metaphase chromosomes. Note that these plates do cont
0-nm fibers or another type. Regardless, this is another tertiary level of
mensional organization of entire chromosomes inside the nucleus a
embrane. The black lines on the pink chromosome represe
Quatern
of chro
the 3D
chro
rel
(Figure
1f). It is
e is affected
within
t.2012.13:59-82.Downloadedfromwww.annualreviews.org
versityofUppsalaon11/26/15.Forpersonaluseonly.
lear
s of
nct
ins
96,97
.
een
asts
ete
ains
were
d to
and
ugh
ted
ned
ted
eri-
ina
ing
ains
fer-
rge
up
the
ma-
also
and
t on
ose
ted
CKs
ons
e in
ave
ned
s. It
Figure 5 | Histone modification signatures associated
with features in the mammalian cell nucleus.
Signature histone modifications correlate with various
nuclear features, although the relationships might be
indirect. Chromatin with modifications generally
associated with active transcription (green dots) often
replicates early, whereas chromatin with generally
repressive modifications (purple dots) replicates late.
Regions enriched for some sets of active modifications
(blue dots) may converge into transcription factories
(TRFs). Blocks of histone H3 lysine 27 trimethylation
(H3K27me3; red dots) may form Polycomb bodies (Pc)
and diffuse domains marked by H3K9me2 or H3K9me3
REVIEWS
ARI
25
July 2012
11:40
Odd-num
bered
nucleosom
e
Even-num
bered
nucleosom
e
Plane of
nucleosom
e layers
DNA
Protein
scaffold
Chrom
atin
loop
M
etaphase
chrom
osom
e
1 2
3
4
5
1
3
5
2
4
1 2
3
5
f Organization
of whole
chrom
osom
es inside the
nucleus (quaternary level)
d
Loops of 30-nm
fiber (tertiary level)
e
Interdigitating
layers of
irregularly organized
nucleosom
es (tertiary level)
a
11-nm
fiber
(prim
ary level)
b
Nucleosom
e stacking
(folded
11-nm
fiber with
zigzag
linker DNA)
c
30-nm
fiber
(secondary level)
Nucleus
ure
1
nt levels of chrom
atin
com
paction. (a) M
ultiple nucleosom
es in
a row
form
the 11-nm
fiber that is the pr
n
com
paction. Alternating
nucleosom
es are depicted
with
blue and
green
surfaces. (b) T
he 11-nm
fi
olum
ns of nucleosom
es such
that odd-num
bered
nucleosom
es interact with
other odd-num
b
eosom
es interact with
other even-num
bered
nucleosom
es. T
he linker D
N
A
zigzags be
-nm
fiber form
s a two-start helix to
produce the 30-nm
chrom
atin
fiber that is th
twists further and
form
s a m
ore com
pact fiber that is arranged
in
loops (bl
T
his is one of the tertiary levels of com
paction. (e) T
he 30-nm
fiber m
regularly oriented
nucleosom
es, particularly in
m
etaphase chro
unclear whether they are 30-nm
fibers or another type. R
ry level refers to
the three-dim
ensional organizatio
well as with
the inner nuclear m
em
brane. T
h
above.
9,
26)
o
rep-ng.
inner
nuc
known
by
9-82.Downloaded
from
www.annualreviews.org
Uppsalaon
11/26/15.Forpersonaluseonly.
location, composition and turnover of nucleosomes;
and the patterns of post-translational histone modifica-
tions. Technological advances in microarrays and next-
generation sequencing have enabled many of these assays
to be scaled genome-wide. Notable examples include:
the DNase I–seq9,10
, FAIRE–seq11
and Sono–seq12
assays for
chromatin accessibility; whole-genome and reduced-
representation bisulphite sequencing (BS-seq)13,14
and
MeDIP-seq15
assays for DNA methylation; and the
MNase–seq16,17
and CATCH–IT18
assays for elucidating
nucleosome position and turnover, respectively. These
technologies and their integration have been extensively
reviewed elsewhere19,20
. In this section, we focus on his-
tone modifications and, in particular, on how genome-
wide ChIP–seq-mapping studies have enhanced our
understanding of the chromatin landscape.
Mapping histone modifications genome-wide. Although
ChIP has been used since 1988 (REF. 21) to probe chro-
matin structure at individual loci, its combination with
microarraysand,morerecently,next-generationsequenc-
ing has provided far more precise and comprehensive
views of histone modification landscapes, which have
highlighted roles for chromatin structures across diverse
genomic features and elements that were not appreci-
ated in targeted studies. The basis of ChIP is the immu-
noprecipitation step, in which an antibody is used to
enrich chromatin that carries a histone modification (or
other epitope) of interest. In ChIP–seq, next-generation
technology is used to deep sequence the immunoprecip-
itated DNA molecules and thereby produce digital maps
of ChIP enrichment (BOX 1). An example is the compre-
hensive work by Keji Zhao’s group to profile 39 different
histone methylation and acetylation marks genome-wide
in human CD4+
T cells22,23
. These maps and similar data
sets24–26
have associated particular modifications with
gene activation or repression and with various genomic
features, including promoters, transcribed regions,
enhancers and insulators (FIG. 2). These and subsequent
Figure 1 | Layers of chromatin organization in the mammalian cell nucleus.
Broadly, features at different levels of chromatin organization are generally associated
with inactive (off) or active (on) transcription. From the top, genomic DNA is methylated
(Me) on cytosine bases in specific contexts and is packaged into nucleosomes, which
vary in histone composition and histone modifications (for example, histone H3 lysine 9
trimethylation (H3K9me3)); these features constitute the primary layer of chromatin
REVIEWS
Ong C-t and Corces V. G.
Nature Review Genetics 2014
61. Odd-numbere
nucleosome
Even-number
nucleosome
Plane of
nucleosome la
DNA
Protein scaffo
Chromatin loo
Metaphase
chromosome
1
2
3
4
5
1
3
5
2
41
2
3 5
f Organization of whole
chromosomes inside the
nucleus (quaternary level)
d Loops of 30-nm
fiber (tertiary level)
e Interdigitating layers of
irregularly organized
nucleosomes (tertiary level)
a 11-nm fiber
(primary level)
b Nucleosome stacking
(folded 11-nm fiber with
zigzag linker DNA)
c 30-nm fiber
(secondary level)
Nucleus
Figure 1
Different levels of chromatin compaction. (a) Multiple nucleosomes in a row form the 11-nm fiber that is the primary level of
chromatin compaction. Alternating nucleosomes are depicted with blue and green surfaces. (b) The 11-nm fiber folds on itself to f
umanGenet.2012.13:59-82.Downloadedfromwww.annualreviews.org
dedbyUniversityofUppsalaon11/26/15.Forpersonaluseonly.
Odd-numbered
nucleosome
Even-numbered
nucleosome
Plane of
nucleosome layers
DNA
Protein scaffold
Chromatin loop
Metaphase
chromosome
1
2
3
4
5
1
3
5
2
41
2
3 5
f Organization of whole
chromosomes inside the
nucleus (quaternary level)
d Loops of 30-nm
fiber (tertiary level)
e Interdigitating layers of
irregularly organized
nucleosomes (tertiary level)
a 11-nm fiber
(primary level)
b Nucleosome stacking
(folded 11-nm fiber with
zigzag linker DNA)
c 30-nm fiber
(secondary level)
Nucleus
Figure 1
Different levels of chromatin compaction. (a) Multiple nucleosomes in a row form the 11-nm fiber that is the primary level of
chromatin compaction. Alternating nucleosomes are depicted with blue and green surfaces. (b) The 11-nm fiber folds on itself to form
two stacks/columns of nucleosomes such that odd-numbered nucleosomes interact with other odd-numbered nucleosomes and even-
numbered nucleosomes interact with other even-numbered nucleosomes. The linker DNA zigzags between the two nucleosome stacks.
om.HumanGenet.2012.13:59-82.Downloadedfromwww.annualreviews.org
providedbyUniversityofUppsalaon11/26/15.Forpersonaluseonly.
Sajan S.A and Hawkins R.D.
Annu. Rev. Genomics Hum. Genet. 2012
GG13CH03-Hawkins
ARI
25 July 2012
11:40
Odd-numbered
nucleosome
Even-numbered
nucleosome
Plane of
nucleosome layers
DNA
Protein scaffold
Chromatin loop
Metaphase
chromosome
1
2 3
4
5
1
3
5
2
4
1
2 3
5
f Organization of whole
chromosomes inside the
nucleus (quaternary level)
d Loops of 30-nm
fiber (tertiary level)
e Interdigitating layers of
irregularly organized
nucleosomes (tertiary level)
a 11-nm fiber
(primary level)
b Nucleosome stacking
(folded 11-nm fiber with
zigzag linker DNA)
c 30-nm fiber
(secondary level)
Nucleus
Figure 1
ent levels of chromatin compaction. (a) Multiple nucleosomes in a row form the 11-nm fiber that is the primary level of
ompaction. Alternating nucleosomes are depicted with blue and green surfaces. (b) The 11-nm fiber folds on itself to form
s of nucleosomes such that odd-numbered nucleosomes interact with other odd-numbered nucleosomes and even-
interact with other even-numbered nucleosomes. The linker DNA zigzags between the two nucleosome stacks.
ms a two-start helix to produce the 30-nm chromatin fiber that is the secondary level of compaction.
nd forms a more compact fiber that is arranged in loops (blue), with some portions attached to a
rtiary levels of compaction. (e) The 30-nm fiber may also result in the formation of
leosomes, particularly in metaphase chromosomes. Note that these plates do cont
0-nm fibers or another type. Regardless, this is another tertiary level of
mensional organization of entire chromosomes inside the nucleus a
embrane. The black lines on the pink chromosome represe
Quatern
of chro
the 3D
chro
rel
(Figure
1f). It is
e is affected
within
t.2012.13:59-82.Downloadedfromwww.annualreviews.org
versityofUppsalaon11/26/15.Forpersonaluseonly.
lear
s of
nct
ins
96,97
.
een
asts
ete
ains
were
d to
and
ugh
ted
ned
ted
eri-
ina
ing
ains
fer-
rge
up
the
ma-
also
and
t on
ose
ted
CKs
ons
e in
ave
ned
s. It
Figure 5 | Histone modification signatures associated
with features in the mammalian cell nucleus.
Signature histone modifications correlate with various
nuclear features, although the relationships might be
indirect. Chromatin with modifications generally
associated with active transcription (green dots) often
replicates early, whereas chromatin with generally
repressive modifications (purple dots) replicates late.
Regions enriched for some sets of active modifications
(blue dots) may converge into transcription factories
(TRFs). Blocks of histone H3 lysine 27 trimethylation
(H3K27me3; red dots) may form Polycomb bodies (Pc)
and diffuse domains marked by H3K9me2 or H3K9me3
REVIEWS
ARI
25
July 2012
11:40
Odd-num
bered
nucleosom
e
Even-num
bered
nucleosom
e
Plane of
nucleosom
e layers
DNA
Protein
scaffold
Chrom
atin
loop
M
etaphase
chrom
osom
e
1 2
3
4
5
1
3
5
2
4
1 2
3
5
f Organization
of whole
chrom
osom
es inside the
nucleus (quaternary level)
d
Loops of 30-nm
fiber (tertiary level)
e
Interdigitating
layers of
irregularly organized
nucleosom
es (tertiary level)
a
11-nm
fiber
(prim
ary level)
b
Nucleosom
e stacking
(folded
11-nm
fiber with
zigzag
linker DNA)
c
30-nm
fiber
(secondary level)
Nucleus
ure
1
nt levels of chrom
atin
com
paction. (a) M
ultiple nucleosom
es in
a row
form
the 11-nm
fiber that is the pr
n
com
paction. Alternating
nucleosom
es are depicted
with
blue and
green
surfaces. (b) T
he 11-nm
fi
olum
ns of nucleosom
es such
that odd-num
bered
nucleosom
es interact with
other odd-num
b
eosom
es interact with
other even-num
bered
nucleosom
es. T
he linker D
N
A
zigzags be
-nm
fiber form
s a two-start helix to
produce the 30-nm
chrom
atin
fiber that is th
twists further and
form
s a m
ore com
pact fiber that is arranged
in
loops (bl
T
his is one of the tertiary levels of com
paction. (e) T
he 30-nm
fiber m
regularly oriented
nucleosom
es, particularly in
m
etaphase chro
unclear whether they are 30-nm
fibers or another type. R
ry level refers to
the three-dim
ensional organizatio
well as with
the inner nuclear m
em
brane. T
h
above.
9,
26)
o
rep-ng.
inner
nuc
known
by
9-82.Downloaded
from
www.annualreviews.org
Uppsalaon
11/26/15.Forpersonaluseonly.
location, composition and turnover of nucleosomes;
and the patterns of post-translational histone modifica-
tions. Technological advances in microarrays and next-
generation sequencing have enabled many of these assays
to be scaled genome-wide. Notable examples include:
the DNase I–seq9,10
, FAIRE–seq11
and Sono–seq12
assays for
chromatin accessibility; whole-genome and reduced-
representation bisulphite sequencing (BS-seq)13,14
and
MeDIP-seq15
assays for DNA methylation; and the
MNase–seq16,17
and CATCH–IT18
assays for elucidating
nucleosome position and turnover, respectively. These
technologies and their integration have been extensively
reviewed elsewhere19,20
. In this section, we focus on his-
tone modifications and, in particular, on how genome-
wide ChIP–seq-mapping studies have enhanced our
understanding of the chromatin landscape.
Mapping histone modifications genome-wide. Although
ChIP has been used since 1988 (REF. 21) to probe chro-
matin structure at individual loci, its combination with
microarraysand,morerecently,next-generationsequenc-
ing has provided far more precise and comprehensive
views of histone modification landscapes, which have
highlighted roles for chromatin structures across diverse
genomic features and elements that were not appreci-
ated in targeted studies. The basis of ChIP is the immu-
noprecipitation step, in which an antibody is used to
enrich chromatin that carries a histone modification (or
other epitope) of interest. In ChIP–seq, next-generation
technology is used to deep sequence the immunoprecip-
itated DNA molecules and thereby produce digital maps
of ChIP enrichment (BOX 1). An example is the compre-
hensive work by Keji Zhao’s group to profile 39 different
histone methylation and acetylation marks genome-wide
in human CD4+
T cells22,23
. These maps and similar data
sets24–26
have associated particular modifications with
gene activation or repression and with various genomic
features, including promoters, transcribed regions,
enhancers and insulators (FIG. 2). These and subsequent
Figure 1 | Layers of chromatin organization in the mammalian cell nucleus.
Broadly, features at different levels of chromatin organization are generally associated
with inactive (off) or active (on) transcription. From the top, genomic DNA is methylated
(Me) on cytosine bases in specific contexts and is packaged into nucleosomes, which
vary in histone composition and histone modifications (for example, histone H3 lysine 9
trimethylation (H3K9me3)); these features constitute the primary layer of chromatin
REVIEWS
Ong C-t and Corces V. G.
Nature Review Genetics 2014
B
Sanborn A.L. et al
PNAS 2015
62. (C)
Enha
(iii) Lagge
(i) (ii)
Enha
Low
RNAPII
transcripƟon
Low abundance
of factors
InacƟve
regulatory
element
AcƟve regulatory element
Promoter strength and/or transcripƟonal level
High
High abundance
of factors
Figure 1. Active regulatory elements are divergently transcribed. (A) Both regulatory active gene promoters and gene-distal enh
(RNAPII) recruitment and transcription initiation are mediated by general transcription factors (GTFs) binding core promot
nucleosomes. This is facilitated by transcription factors (TFs), which often bind proximal to core promoters. Transcription often i
the nucleosome-depleted region (NDR). (B) Gene expression is often preceded by, or changes concurrently with, chang
(nonexpressed) state (i), enhancers and promoters may, or may not, bind RNAPII. Upon stimulus (ii), transcriptional activity at enh
with local transcription and increases in RNAPII recruitment at the target gene promoter. (iii) Gene expression may lag behind
Chromatin interactions place regulatory elements in close physical proximity. The individual properties of regulatory elements (c
RNAPII recruitment strengths) as well as context-dependent properties (such as promoter competition, insulation, and core p
formation of multiple regulatory interactions (Box 1). Via regulatory cooperation, multiple regulatory elements may increase the
co-activators, and RNAPII) needed for transcription in RNAPII-enriched foci (i) and thereby achieve in aggregate different levels
RNAPII foci, including fewer regulatory elements (ii). Nucleosome illustrations in (A) reproduced, with permission, from [38]; (
428
Weak enhancer
Enhancement
Target
gene promoter
(B)
Enhancer strength
Hypothesis:
strong enhancers are strong promoters
Promoterstrength
?
Stong enhancer
Enhancement
Target
gene promoter
Enhancement
(A)
Enhancer strength
Promoterstrength
Hypothesis:
weak promoters are strong enhancers
Strong promoter
No or minor
enhancement
Target
gene promoter
Weak promoter Target
gene promoter
?
RNAPII
TranscripƟon
TRENDS in Genetics
Figure 4. Chromatin interactions and strength of regulatory elements determine transcriptional activities. (A) Competition between individual regulatory elements may
Opinion Trends in Genetics August 2015, Vol. 31, No. 8
Andersson R et al. TiG 2015
63. Ni X. et al
PLoS Biol. 2012
Adaptive evolution and the birth of CTCF binding sites in the Drosophila genome.
Figure 1. Conserved binding preference of CTCF. (A) Topological illustration of the phylogenetic relationships between the four Drosophila
species in our study. (B) The number of CTCF binding peaks identified in ChIP-seq experiments in the four Drosophila species. (C) Genomic
distribution of CTCF binding sites in the four Drosophila species. The percentages of CTCF binding sites distributed in different genomic locations are
shown in the four pie charts: intergenic (.1 kb to nearest TSS, purple), promoter (,1 kb to nearest TSS, light blue), intronic (light green), and exonic
(white). In all four species, .90% of the binding sites reside in the noncoding regions with highest percentages in promoter regions. (D) Species-
specific binding motifs. The 9 bp core motif for each species is de novo generated by MEME using the top 2000 ChIP-seq-enriched CTCF binding site
DNA sequences.
doi:10.1371/journal.pbio.1001420.g001
Adaptive Evolution of CTCF Binding Sites
68. Ni X. et al
PLoS Biol. 2012
Adaptive evolution and the birth of CTCF binding sites in the Drosophila genome.
Figure 4. Functional consequences of CTCF binding evolution. (A–B) CTCF binding evolution is associated with gene expression evolution.
The bar plots show the proportion of genes with diverged expression between (A) D. melanogaster/D. simulans and (B) D. melanogaster/D. yakuba
comparisons associated with different groups of CTCF binding sites: Genome-wide (black), Conserved TWOB (pink), Diverged TWOB (green), Old
FWOB (orange), and Young FWOB (light purple). The table below each bar plot shows the number of genes with diverged and conserved gene
expression in the corresponding comparisons and associated with the corresponding CTCF binding sites. For each groups of CTCF binding sites, the
associated genes are the union of the nearest gene to each binding site. The evolutionary status of gene expression (conserved or diverged) is
determined using triplicate WPP mRNA-seq data through a generalized linear regression framework. Label abbreviations are the same as described in
Figure 3. Significance levels: * p,0.05; **p,0.01; one-sided Fisher’s exact test. (C–E) CTCF binding evolution is correlated with new gene origination.
The four colored wiggle tracks in each of the plots show the ChIP CDP enrichment scores of the four species (D. melanogaster, blue; D. simulans,
green; D. yakuba, orange; D. pseudoobscura, purple) across different genomic regions. CTCF binding peaks are observed in D. melanogaster, D.
simulans, and D. yakuba at flanking genomic regions of newly evolved genes TFII-A-S2 (C) and CheB93a (D). The two genes both originated after the
split of the melanogaster group with the pseudoobscura group. CTCF binding peak is only observed in the D. melanogaster genome in the flanking
genomic regions of D. melanogaster lineage-specific gene sphinx (E).
doi:10.1371/journal.pbio.1001420.g004
PLOS Biology | www.plosbiology.org 8 November 2012 | Volume 10 | Issue 11 | e1001420
Figure 4A,B). Such correlation is also observed when using
microarray data for inferring gene expression divergence (Figure
S14) as well as when using high-sequence coverage sites (Figure
S15). These observations indicate that CTCF binding evolution
impacts gene expression evolution, which previously has been
shown to evolve rapidly and to be shaped by selection in these
species at the WPP stage [51,52].
Selection on gene expression can lead to adaptive evolutionary
signatures in cis-regulatory elements. Indeed, in Drosophila,
adaptive gene expression has been linked to adaptive cis-DNA
evolution [53]. We thus hypothesized that the stronger positive
selection signature observed in the diverged TWOBs might stem
from the sites being associated with diverged expression that has
more directly been subject to natural selection. We calculated and
compared a values for two additional subgroups of TWOB sites:
diverged TWOBs near genes with divergent expression and
conserved TWOBs near genes with conserved expression.
Consistent with our hypothesis, we observed a larger difference
in a values between these two subgroups than between all
conserved and diverged TWOBs (Figures S16 and S17).
CTCF Binding Evolution Is Correlated with the Origin of
New Genes
CTCF binding sites in Drosophila have been associated with
syntenic break points, consistent with their role in delineating the
regulatory architecture of genes [13]. We wished to determine
whether CTCF binding evolution correlates with any other
genome structural evolution. New genes are defined as genes
Adaptive Evolution of CTCF Binding Sites
69. Ni X. et al
PLoS Biol. 2012
Adaptive evolution and the birth of CTCF binding sites in the Drosophila genome.
Figure 4. Functional consequences of CTCF binding evolution. (A–B) CTCF binding evolution is associated with gene expression evolution.
The bar plots show the proportion of genes with diverged expression between (A) D. melanogaster/D. simulans and (B) D. melanogaster/D. yakuba
comparisons associated with different groups of CTCF binding sites: Genome-wide (black), Conserved TWOB (pink), Diverged TWOB (green), Old
FWOB (orange), and Young FWOB (light purple). The table below each bar plot shows the number of genes with diverged and conserved gene
expression in the corresponding comparisons and associated with the corresponding CTCF binding sites. For each groups of CTCF binding sites, the
associated genes are the union of the nearest gene to each binding site. The evolutionary status of gene expression (conserved or diverged) is
determined using triplicate WPP mRNA-seq data through a generalized linear regression framework. Label abbreviations are the same as described in
Figure 3. Significance levels: * p,0.05; **p,0.01; one-sided Fisher’s exact test. (C–E) CTCF binding evolution is correlated with new gene origination.
The four colored wiggle tracks in each of the plots show the ChIP CDP enrichment scores of the four species (D. melanogaster, blue; D. simulans,
green; D. yakuba, orange; D. pseudoobscura, purple) across different genomic regions. CTCF binding peaks are observed in D. melanogaster, D.
simulans, and D. yakuba at flanking genomic regions of newly evolved genes TFII-A-S2 (C) and CheB93a (D). The two genes both originated after the
split of the melanogaster group with the pseudoobscura group. CTCF binding peak is only observed in the D. melanogaster genome in the flanking
genomic regions of D. melanogaster lineage-specific gene sphinx (E).
doi:10.1371/journal.pbio.1001420.g004
PLOS Biology | www.plosbiology.org 8 November 2012 | Volume 10 | Issue 11 | e1001420
Figure 4A,B). Such correlation is also observed when using
microarray data for inferring gene expression divergence (Figure
S14) as well as when using high-sequence coverage sites (Figure
S15). These observations indicate that CTCF binding evolution
impacts gene expression evolution, which previously has been
shown to evolve rapidly and to be shaped by selection in these
species at the WPP stage [51,52].
Selection on gene expression can lead to adaptive evolutionary
signatures in cis-regulatory elements. Indeed, in Drosophila,
adaptive gene expression has been linked to adaptive cis-DNA
evolution [53]. We thus hypothesized that the stronger positive
selection signature observed in the diverged TWOBs might stem
from the sites being associated with diverged expression that has
more directly been subject to natural selection. We calculated and
compared a values for two additional subgroups of TWOB sites:
diverged TWOBs near genes with divergent expression and
conserved TWOBs near genes with conserved expression.
Consistent with our hypothesis, we observed a larger difference
in a values between these two subgroups than between all
conserved and diverged TWOBs (Figures S16 and S17).
CTCF Binding Evolution Is Correlated with the Origin of
New Genes
CTCF binding sites in Drosophila have been associated with
syntenic break points, consistent with their role in delineating the
regulatory architecture of genes [13]. We wished to determine
whether CTCF binding evolution correlates with any other
genome structural evolution. New genes are defined as genes
Adaptive Evolution of CTCF Binding Sites
CTCF-binding
sites are shaped
by natural
selection and
influence gene
expression
patterns