Kimberly McAllister: So I’m from the National Institute of Environmental
Health Sciences, and I’m going to give you just a really brief run through of the NIH
Roadmap Epigenomics Program, which in many ways is kind of the complimentary program
to ENCODE.
So as many of you know, there are a lot of different epigenomic changes that have been
implicated in many human diseases.
A lot of these changes occur during normal developmental processes, and there are also
lots of external influences and environmental exposures that can impact the epigenome as
well.
So the NIH Roadmap program is really a comprehensive program, a common-fund program that has a
lot of different complimentary components.
It’s really trying to accelerate the understanding of epigenomics in human health and disease,
through a lot of different new research tools, datasets, and infrastructure.
And this is listing a lot of the different components of the Roadmap Epigenomics Program.
So there is a large research component.
Those are mostly R01 grants that are focused on different disease outcomes.
There’s a discovery of novel epigenomic marks.
There’s a computational analysis component.
There’s also a technology development component that includes a lot of in vivo epigenomic
imaging.
And then the reference epigenome mapping consortium is kind of the public resource of the human
epigenomics data, and this has really leveraged a pipeline that includes a lot of next-generation
sequencing technologies to map DNA methylation, histone modifications, chromatin accessibility,
and RNA transcripts.
And I have down there -- I’ve listed the different mappings and their components, and
the coordination center.
So the mapping centers have made epigenomic profiles of many different primary cells and
tissues, and this includes the hearth, the G.I.
track, the lung, many brain components, many blood components.
And this is in both adult and fetal tissues, and they’ve also looked at a lot of different
derived embryonic stem cells, as well.
And these areas that were selected were carefully trying to represent as many of the normal
counterparts of many tissues and organ systems that are frequently involved in human disease.
So from these studies, many questions have now been answered about how different human
cell types and tissues do differ, epigenetically.
And there are lots of uses, of course, of this epigenomic information, and I know many
of you are using it in many different ways, and it’s been encouraging at ASHG to see
a lot of uses of the Roadmap data.
I just wanted to highlight a couple that I think do complement especially the ENCODE
use of the data.
And one is the marking of functional genomic elements, so along with ENCODE, the Roadmap
data has really assisted in annotating a lot of different areas of the genome and different
cell types.
And then the other one is interpreting GWAS hits.
And Mike already kind of alluded to this, but we’ve learned that a lot of the GWAS
hits are really in coding region -- not encoding regions, regulatory regions, rather, and that
a lot of them are in or near enhancer or promoter elements.
And that’s really impacted the types of functional follow-up studies that a lot of
investigators have used, and have focused on in recent years in order to interpret the
GWAS data.
And then I also just wanted to mention that it’s been used in recent years to try to
better identify different cell types that are involved in particular diseases, so for
this particular example in this paper, they were able to show that a number of different
immune cells were implicated in Crohn’s disease.
And so finally, I just wanted to mention that we had a big issue of “Nature” earlier
this year, that had a lot of different publications, including an integrative analysis reference
epigenome paper.
And I really encourage you to take a look at this issue if you haven’t already.
It kind of gives you a good idea of the breadth and the depth of this program, and there were
a number of other publications and Nature-associated journals, as well.
That -- thank you.
[end of transcript]