Elise Feingold: Okay.
Thanks, Mike, for that introduction to the series of concepts we’re going to be now
discussing.
I’d like to say that I’m presenting this on behalf of not only myself, but Mike and
Dan.
And I wanted to acknowledge the significant advice and input that we received from Adam
Felsenfeld and Josh -- Jeff Schloss.
Okay.
So, I’d like to give now just a real brief outline for my presentation.
I’m going to review the timeline for these initiatives, discuss the overall goals, really
pull out what we think are -- is new from what’s being currently done under ENCODE,
then briefly describe each of the concepts, identify some opportunities we think there
are for co-funding, and then describe the overall budget.
And then, after that, I’m going to go back, and council can discuss and vote on each individual
concept.
Okay.
So, this is the timeline for the initiatives.
As Mike mentioned, the current phase of ENCODE was funded in 2016 -- I’m sorry, 2012.
And funding will be ending in July of 2016.
We had the planning workshop in -- that Mike just described in March of this year.
We’re presenting the concept clearances to this council in May of this year.
If these concepts are approved, we will be releasing the funding opportunities at the
end of the summer, in August of this year, with a receipt date in November.
Scientific review will be next winter, probably February or early March.
And then, next May, we’ll be bringing these applications back to council for review, along
with a funding plan, and then issuing awards in July of 2016.
Okay.
So, based on the workshop recommendations that Mike just reviewed, we developed a series
of goals for future initiatives.
These include expanding the catalog of functional elements in human and mouse genomes, but moving
also beyond cataloging to understanding the functional roles of genomic elements in specific
biological contexts.
We want to develop strategies to apply these studies to disease.
Want to increase the number of scientists from the research community that’s participating
to and contributing to this resource.
We want to develop analytical tools to enhance data utility, and continue to make the data,
tools, analyses, and assembled encyclopedia freely available to the research community.
And so, in order to accomplish these goals, we’ve -- we are proposing four initiatives.
The first is functional element mapping centers.
The second is functional element characterization centers.
Third, computational analysis research projects.
And the fourth is the ENCODE Data Coordination and Analysis Center, or fondly known as the
EDCAC.
I’d like to highlight a few features of these initiatives, what really is -- we think
is different than what is currently being done under ENCODE.
The first is functional characterization at scale.
This would be, of course, under the characterization initiative.
The second is direct application of functional genomics assays to disease studies.
This would be both in the mapping and the characterization centers.
And significantly increase community participation through the mapping centers, the characterization
centers, and through data submission to the EDCAC.
Okay.
This is the proposed organization of these initiatives, at -- with the green components
being the new activities.
The data production activities will take place in the mapping centers and the characterization
centers, in part with using samples that are contributed by the community.
The data will be submitted to the ENCODE Data Coordination and Analysis Center, where it
will be processed, housed, and displayed and made available to the research community and
also analyzed to create the encyclopedia of functional -- or candidate functional elements.
We’ll also be receiving community data to the EDCAC, and it can contribute to the encyclopedia.
And as before, we want to support computational analysis to contribute to both the analyses
and directly to the encyclopedia.
Okay.
So, I’m now going to describe in more detail the first of the four initiatives.
The first is functional element mapping centers.
The purpose is to expand the catalog of functional elements in the human and mouse genome.
And this will be done by applying high-throughput assays to map biochemical activities that
are highly associated with specific functional elements in an expanded cell space that will
also -- will include disease studies.
And the idea is to support both technologies that are currently being used in ENCODE, as
well as new technologies.
For funding, we want to use the cooperative agreement U54 mechanism that we are currently
using in ENCODE to fund between six and eight centers, for a total level of $20 million
per year and total cost for four years.
And the idea is to fund these centers.
Groups will be working closely together to form a research consortium, as is the current
model, currently being done in ENCODE.
Okay.
So, there are a couple of new features for these functional element mapping centers that
I want to highlight.
As we’ve said, we want to broaden the community participation by obtaining unique biological
samples from experts.
And these may be, as Mike has referred to, these unbiased data collection for samples
that are just not currently in the -- in the catalog.
These may be of biological focus, such as on a differentiation pathway, or they may
be of disease interests.
We are proposing to devote approximately 25 percent of the mapping efforts to disease
samples -- or these -- to disease studies.
These can actually be samples from unaffected as well as affected individuals.
Both will be contributing to the catalog.
And we hope that we can learn something by examining the differences between the unaffected
and affected tissues and learn something about disease and, more broadly, by studying a number
of diseases, learn to -- how to develop a strategy that we can study disease using these
molecular genomic assays, you know, more broadly in the future.
We want to develop a scientific basis for bounding the experimental space.
If you think about what we say -- we want to make a comprehensive, complete catalog
-- well, thinking about every different possible cell type under every different environmental
condition is really just unbound-able.
And so, we want to -- through these centers and experiments, to try to bound it, to try
to identify, really, what are the most useful samples that we can use to do -- for very
deep interrogation?
We want to use -- only use samples that are consented for open-access data release.
As Mike mentioned a little earlier, we are currently doing that.
And we’ve piloted that in the current phase of ENCODE successfully.
We believe that this will really make the resource much more useful to the research
community.
We plan to have a limited focus on mouse, due to the limitation in budget that we have.
And we are proposing approximately 10 percent of that effort being devoted to mouse and
focused on adult tissues.
We are currently, in this phase of ENCODE, focusing largely on developmental time course.
And so, this, we believe, will nicely complement that.
And we believe this data will be helpful in annotating and understanding human genome.
And then, finally, we feel we need to have flexibility in the pipeline.
We may have some technologies that are not well tested, and we may want to focus those
initially on a subset of samples that are already well studied in ENCODE.
And then, if their feasibility of use at a high throughput has been demonstrated, then
we might scale that up to many more tissues.
We may want to bring in new technologies over time.
And we want to also be able to take advantage of new opportunities that are brought in by
collaborators.
Okay.
So, the second initiative is functional characterization centers.
This is a completely new activity, and the purpose is to enhance the catalog of function
elements by characterizing and validating a set of elements, both in mouse and human.
We’re hoping to obtain an understanding of the utility and the generalizability of
these functional characterization approaches.
And we would like to, by comparing the different methods, figure out if there’s a general
strategy that we can recommend to the community for further study and also -- I think really
important is to begin to develop ways in which we can better predict function.
Under the scope and objectives, we plan to support multiple approaches to test candidate
elements in specific biological contexts to validate and characterize functional elements.
We -- you can think about functional characterization -- it’s very broad; there are very different
scales.
You can think about function on a molecular level or an organismal level.
Of course, biological function is very context-dependent.
So, you may need to study them under different conditions.
And then, of course, there are a number of different function elements.
So, we do expect that we will need to be supporting multiple approaches.
For funding, we want to support these as U01s, again, using the cooperative agreement mechanism.
And we feel we need to support a critical mass of these centers, so we’re proposing
between seven and 10 centers.
Again, these will -- groups will work closely together.
They will also interact with groups from the mapping centers as part of the consortium.
And we are proposing $5.9 million in total costs per year for four years.
So, some of the key features of these functional characterization centers -- applicants can
select the cell system or biological context for in-depth studies.
Not what’s on the slide is, of course, they will -- can choose which functional elements
they can be studying.
We’re going to specifically encourage studies of specific diseases using relevant cell sources.
And similar to what I said about mapping centers, these can be done in samples that are highly
relevant to a particular disease, but they can be unaffected as well as affected.
And by comparing them, we may be able to see how different function elements operate under
normal and diseased conditions, and also hope to develop a strategy for applying these assays
to disease in the long run.
Any group can propose to do multiple assays.
And you can imagine that groups may propose to study many functional elements using high-throughput
methods such as massively parallel reporter assays.
They may want to study a smaller number of elements using lower-throughput methods that
may provide more physiological context, such as in transgenic animals.
The assays can be conducted in well-justified model organisms, not just in mouse.
They could do other model organisms, such as zebrafish or whatever is well-justified.
They need to focus on either human or mouse function elements.
We’re asking that each groups devote 25 percent of their own effort to elements that
are being studied by all, so that we have some opportunity to be able to compare the
different strategies and approaches that people are using on the same set of function elements,
to the extent that that’s practical.
And then, again, we’re looking only for use of samples consented for open-access data
release, again, to enhance the utility of those resource.
Okay.
The third initiative’s for computational analysis.
And the purpose of this is to maximize the utility of ENCODE and related functional genomics
resources by bringing in additional computational expertise to analyze ENCODE data.
So, this is another way we’re trying to expand the participation for the research
community.
And so, we’re seeking here investigator-initiated projects to develop and apply analytical and
statistical tools to use and improve the resources.
For funding, we’re looking for the cooperative agreement mechanism to fund approximately
six projects at $3 million in total costs per year for four years.
And we feel that, again, we need a critical mass of these.
And we have benefited by the cooperative agreement mechanism currently to have groups working
together and interacting and really understanding the ENCODE data in depth.
Could mention a number of different activities.
Some are suggested here, which would include developing new methods to improve on the analysis,
the visualization, and interpretation of ENCODE data; by -- also, by combining ENCODE data
with related functional genomics data from other projects, to derive new biological insights;
and using ENCODE data to improve on the analysis of disease-mapping studies to identify causal
variants.
Okay.
And then, the final initiative is the ENCODE Data Coordination and Analysis Center, EDCAC.
The idea is to support a center that can provide community access to ENCODE data and resources,
not only what will be conducted under this phase, but also what has previously been produced
for ENCODE.
We also want to support the analysis of ENCODE data necessary to create and make available
a high-quality encyclopedia for the community.
And we want to, also, support the center to organize and facilitate consortium activities.
And so, what we plan to do here is to support a data coordination center and a data analysis
center separately because we believe that there’s specific expertise that’s needed
-- that’s different for each group.
So, we fund them separately under this initiative.
But we expect them to work very closely together and to really come together and function as
a single entity.
And this is modeled off of what the current funding situation is for ENCODE.
In this initiative, we want to greatly expand the activities for the DCC -- I’ll describe
in a moment -- over what is currently funded.
And the DAC activities will be more tightly focused on creating and validating the encyclopedia
and a little less focused on integrated analyses.
For funding, we again want the cooperative agreement, U54, research-resource mechanism;
again, funding two centers, one data coordination center, one data analysis center, at $7.5
million total cost per year.
And this is -- unlike the others, which were four years, this is for five years.
So, we’re proposing one year beyond the data production to help final all the -- finalize
all the data and have closeout activities.
And related to that, we’re seeking additional $2.6 million in FY ’16 for the existing
data coordination center to close out current ENCODE activities.
And this is approximately 75 percent of their current level of funding.
So, we’re expecting that these two groups will work very closely together, but based
on the needs and the expertise will -- each group will have the lead in particular activities.
And I’m now just going to run through these.
I’m going to go these in a -- in a bit of detail because it’s not always obvious what
these -- groups are doing.
The DCC will lead activities such as -- they will develop, house, and maintain databases
to track, store, and provide access to data, metadata, and computational tools.
They will develop, maintain, and update the data processing pipelines; will maintain and
enhance a portal to ensure easy access to the data and resources.
They will provide the -- to the community access to data and state-of-the-art browser
visualization formats.
They will track and report on data submissions.
One of their new activities, highlighted here in yellow, is to import data from outside
investigators and projects, developing the needed infrastructure and methodology.
And we expect that this will actually be a significant amount of work, having to work
individually with different groups.
They’ll have to develop standards -- you know, what is the minimum data quality, et
cetera -- to maintain the high-quality resource.
And then, another new activity is to serve as the data coordinating center.
And this would be to facilitate communication and coordination, organize and support annual
meetings and working groups, and to support outreach activities to promote broad use of
data analyses and tools.
And except for the outreach activities, ENCODE has not had this support previously, unlike
a lot of -- several other large projects that NHGRI supports.
And we feel that this would be very helpful to have.
Okay.
In terms of the DAC-led activities, the DAC will specify and update data processing pipelines.
It will provide leadership and computational expertise to analyze data for several different
activities.
One is to update and refine the encyclopedia.
A new activity would be to develop the scientific strategy to bound the cell space to be deeply
interrogated, that I referred to under initiative one.
Another new activity would be to expand the lexicon of functional elements beyond basic
categories of promoter and enhancer and insulator.
And we’ve -- I think the group feels very constrained by having just such little -- few
categories, when you’re thinking about function -- you know, that it’s more complex than
that; and then, also, to update existing and develop new data quality metrics and standards
for all data types.
And then, finally, a new -- another new activity is, we would like the DAC to reserve a small
funds to be able to bring in additional expertise to conduct short-term specialized analyses
needed to maximize the quality and the utility of the resource.
Okay.
Those are the four initiatives.
Just want to point out a couple places where we see opportunity for co-funding.
We plan to work with our colleagues in other institutes to seek support for projects that
are focused on specific diseases or biology of interest to these other institutes.
We can imagine either whole or partial funding of projects, especially for in -- under the
functional characterization initiative.
We could see supplemental funding for mapping samples that are -- mapping of samples that
are of particular interest to an institute, particularly in the mapping centers.
And opportunity for supplemental finding to support submission of existing or planned
data that is being generated under other projects, that would go directly to the EDCAC.
Okay.
This is a summary of the budget request.
We are looking for flat funding over four years for each of these four initiatives,
with the exception I just went over for the EDCAC of a -- of a fifth year of funding to
close out activities, as well as an extension -- one-year extension of the current DCC.
This is for a total of $36.4 million a year.
And this level of support is actually equivalent to the level that ENCODE received in FY ’12,
the first year that this -- that the current phase of ENCODE was funded.
Due to budget constraints, however, much of that funding was actually just for one year.
And so, we’ve had to take significant reductions in the out years.
And so, for the latest -- FY ’14 is the -- we have the latest budget information -- this
request represents approximately 21 percent increase over what ENCODE currently already
has.
Okay.
Are there any immediate questions before we go back to discuss each of the individual
initiatives?
Guess so.
Okay.
And I’m going to heavily rely on my colleagues here to help answer these questions.
So, Howard.
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