Annual Scientific Report 2015

Genome Analysis
The Genome Analysis team is responsible for the development of scalable
solutions for the functional annotation of genomes, with a focus on genetics
and epigenomics. Within Ensembl, we maintain the Variation and Regulation
databases that collect all available data on vertebrate genetic markers and gene
expression regulation.
Whereas the cost of sequencing a genome has dropped,
the downstream analysis is still costly and error
prone. Outside of the coding sequences, which are
comparatively well understood, our knowledge of what
the vast majority of the genome does is still hazy, and
our ability to predict the functional consequence of
most variants approximate. For example, most genetic
markers that are revealed by genome wide association
studies (GWAS) lie outside of coding regions. It is
therefore very difficult to understand the corresponding
disease mechanisms, let alone devise effective
therapeutic strategies to counter them.
The first obstacle that needs to be addressed is easy
access to the data. For a number of practical, commercial
or ethical reasons, many genetic datasets are isolated
in separate databases. It is now clear that to detect
minute genetic associations researchers must pool their
resources so as to create a greater common dataset. It
is similarly clear that to understand the full dynamics
of the epigenome, the world research community needs
to coordinate a very large number of assays. With
this in mind, we are active members in a number of
international collaborations to collect and share data.
Having gained access to the relevant datasets, we
develop technical solutions to efficiently process them,
and cross-examine large numbers of experiments. We
therefore develop specialised infrastructure to process
multidimensional genome-wide datasets. This includes
user-friendly webtools as well as more advanced
command-line tools and micro-services. In particular,
the Variant Effect Predictor (VEP) stands out as the
most popular way of querying Ensembl for a set of
DNA variants.
Downstream of our data and our tools, we deliver
integrative analyses that summarise all the data that
we processed. Our users can rely on these results, with
the knowledge that we integrated as many experiments
as possible to produce the most precise annotation
possible. For example, the Ensembl Regulatory Build is
the first published annotation that integrates ChIP-Seq
and open chromatin experiments from multiple
consortia into a single synthetic summary.
Major achievements
A lot of our efforts were focused on obtaining more
datasets and encouraging healthy data sharing between
research partners. We are active members of the
Global Alliance for Genomics and Health (GA4GH),
an organisation that strives to break the technical and
legal barriers to genomic data sharing across the world.
This year, the Global Alliance finished its first standard
exchange protocols. We also play an important role
in the International Human Epigenome Consortium
(IHEC) and the Functional Annotation of Animal
Genomes (FAANG) consortium, that set the standards
and collect references to epigenomic datasets produced
by all major consortia. Finally, we are collaborating with
the GWAS Catalog project to help collect and curate
available GWAS results.
We also continued to improve access to our data. We
continued to improve the VEP, for example by speeding
it up. We also helped develop and release user-friendly
tools for epigenomics as produced by the BLUEPRINT
consortium, GenomeStats and EpiExplorer. We
also improved the querying of the datasets that we
store locally, for example by acceleration linkage
disequilibrium calculations and displaying them as
Manhattan plots. Cis-regulatory interactions are making
their way into Ensembl, and we are currently able to
display user datasets (see Figure 1).
Finally, we kept abreast of technical development in
the field. Our Ensembl Regulatory Build algorithm was
published in Genome Biology. We collaborated with
Peter Fraser and Mikhail Spivakov of the Babraham
Institute on the downstream analysis of an exciting
technology, called Promoter Capture Hi-C, that produces
high-resolution maps of the 3 dimensional conformation
of the chromatin. We are also working with the CTTV
Epigenome Project, where we compare and contrast cell
line epigenomic data.
Future plans
In the next few years, we aim to greatly expand the
number of species, tissues and cell types covered by
the Ensembl Regulatory Build. Having spent much of
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2015 EMBL-EBI Annual Scientific Report