Manolis Kellis - Researchers generate a reference map of the human epigenome
Better understanding of epigenetic modifications could elucidate their role in human traits, diseases.
Helen Knight | MIT News correspondent
February 18, 2015
sequencing of the human genome laid the foundation for the study of
genetic variation and its links to a wide range of diseases. But the
genome itself is only part of the story, as genes can be switched on and
off by a range of chemical modifications, known as “epigenetic marks.”
Now, a decade after the human genome was sequenced, the National
Institutes of Health’s Roadmap Epigenomics Consortium has created a
similar map of the human epigenome.
Manolis Kellis, a professor of computer science and a member of MIT’s
Computer Science and Artificial Intelligence Laboratory and of the
Broad Institute, led the effort to integrate and analyze the datasets
produced by the project, which constitute the most comprehensive view of
the human epigenome to date.
In a paper published today in the journal Nature, Kellis and
his colleagues report 111 reference human epigenomes and study their
regulatory circuitry, in a bid to understand their role in human traits
“The consortium set out to systematically characterize the human
epigenomic landscape, across diverse tissues and cell types,” Kellis
says. “Given the enormity of the task, that meant bringing together
multiple mapping centers and profiling a wide range of cell and tissue
samples, to capture the diversity of the human epigenome.”
150 billion genomic sequences
The researchers generated 2,805 genome-wide datasets, encompassing a
total of 150 billion sequencing reads, corresponding to 3,174-fold
coverage of the human genome. These captured modifications of both the
DNA itself, and of the histone proteins around which DNA is wrapped to
form a structure known as chromatin.
Kellis and his team then developed and applied machine-learning
algorithms that could translate these datasets into a reference map in
each of the 111 cell types and tissues. The algorithms distinguished
different classes of epigenomic modifications and used them to annotate
the genomic regions active in each sample, and in particular regulatory
elements that control where and when different genes are expressed.
“Different combinations of epigenetic marks characterize different
regions of the genome, reflecting the specific functions that they play
in each cell,” Kellis says. “By studying these combinations
systematically, we can learn the language of the epigenome, and what it
is telling us about both the activity and the function of each genomic
region in each of the cell types.”
The researchers distinguished 15 different epigenomic signatures, or
chromatin states, reflecting active, repressed, poised, transcribed, and
inactive regions of the genome in each cell type. About 5 percent of
each reference epigenome showed signatures associated with a regulatory
“Chromatin states allowed us to summarize the complexity of diverse
epigenomic marks into a small number of common patterns,” Kellis says.
“We could then interpret the biological functions of these patterns.”
The researchers then studied how these chromatin states varied across
different types of cells and tissues. This allowed them to group cell
types with similar regulatory circuitry. They also grouped together
regulatory regions that are active in the same types of cells. In this
way they could begin to reveal the building blocks of regulatory
“Unlike the genome, which is mostly unchanged across cell types, the
epigenome is extremely dynamic, reflecting the specialization of each
cell type, such as neurons, heart, muscle, liver, skin, blood, or immune
cells,” Kellis says. “By studying which regions turn on and off in the
same cell types, we can gain insights into gene regulation.”
The researchers grouped 2 million predicted regulatory regions into
200 sets, or modules, which appeared to be acting in a coordinated
manner across different types of cells. They found that 100 of these
modules contained common sequence patterns, known as regulatory motifs,
which may be responsible for their ability to work together in this way.
“Exploiting the predicted regulators and their motifs can help
dissect the circuitry of different tissues and cells,” Kellis says.
The researchers also compared these epigenomic signatures with groups
of genetic variants that are associated with different human traits and
diseases. This allowed them to produce a map of the tissue and cell
types that are most relevant to each trait or disease.
“We found that genetic variants are found in regulatory regions known
as enhancers, which are activated only in certain types of cell and
tissue,” Kellis says. “This suggests that many genetic variants affect
the regulatory circuitry of the cell, possibly disrupting gene functions
by altering tissue-specific gene expression levels.”
Tissue-specific enhancers affect 58 traits
The researchers found significant tissue-specific enhancer signatures
for genetic variants associated with 58 different traits. These
included height, in embryonic stem cells; multiple sclerosis, in immune
cells; attention deficit disorder, in brain tissues; blood pressure, in
heart tissues; fasting glucose, in pancreatic islets; cholesterol, in
liver tissue; and Alzheimer’s disease, in CD14 monocytes.
“This unbiased view allows researchers to focus on relevant cells and
tissues that may have been otherwise overlooked when studying a
particular disease,” Kellis says. “The regulatory circuitry of a diverse
range of cells can contribute to diseases that manifest in seemingly
Using these circuits to understand the molecular basis of human
disorders will take many years and the effort of many labs, Kellis says.
“Our results provide an invaluable map, and a rich set of hypotheses,
which can help guide these studies.”
Wolf Reik, head of the epigenetics research program at the Babraham
Institute in the U.K., who was not involved in the research, says the
project is an exciting resource for the biomedical community worldwide.
“Important epigenetic marks were mapped systematically in many human
cell types and tissues,” Reik says. “Integrative analysis of these
epigenomes provides a global map toward understanding fundamental
developmental and disease processes in humans.”