Annual Scientific Report 2015

Sequence Families
The Sequence Families team is responsible for the InterPro, Pfam, RNAcentral
and Rfam data resources, and coordinates the EBI Metagenomics project. We
are also responsible for the HMMER web server, which performs extremely fast
protein-homology searches.
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InterPro integrates protein-family data from 11 major
sources, and classifies hierarchically the different
protein family, domain and functional site definitions
to provide a unified view of diverse data. InterPro
curators build on this, adding functional descriptions
to the families and annotating entire datasets with
structured Gene Ontology terms. The InterProScan
tool allows users to identify InterPro entries on protein
sequences. Pfam generates new protein family entries
and has the largest sequence coverage of all the InterPro
member databases. Both InterPro and Pfam have
many important applications, including the automatic
annotation of proteins for UniProtKB/TrEMBL
and genome/metagenome annotation. HMMER, a
sequence-similarity search tool for identifying distant
relationships, enables users to infer function, annotate
protein sequences and trace evolutionary histories.
Rfam classifies non-coding RNA sequences into
families, using probabilistic models that take account
of both sequence and secondary-structure information,
termed covariance models. Rfam is used to annotate
non-coding RNAs in genome projects and is a major
contributor to RNAcentral, an integrating database of
non-coding RNA sequences that serves as a single entry
point for searching and accessing data from over 20
established RNA resources. RNAcentral gives
users a unified view of all non-coding RNA types from
all organisms.
Metagenomics is the study of the sum of genetic
material found in an environmental sample or host
species, using next-generation sequencing (NGS)
technology. The EBI Metagenomics service enables
researchers to submit sequence data and descriptive
metadata to public nucleotide archives. We help ensure
the data is functionally and taxonomically analysed, and
the results primed for visualisation and download.
Major achievements
InterPro, Pfam and HMMER
In 2015 we issued six releases of InterPro. We integrated
over 2000 new member database signatures, resulting
in over 1800 new InterPro entries. Version 54.0, released
in October, included an update to PANTHER 10.0,
which involved a substantial rebuild of the database and
enabled the addition of almost 60 000 new signatures
and the removal of over 20 000. Although this rebuild
2015 EMBL-EBI Annual Scientific Report
resulted in the loss of over 500 of the 3673 integrated
InterPro entries, the curation team ensured the resource
ultimately comprised over 4600 integrated PANTHER
signatures by the end of the year.
Despite the removal of redundant bacterial proteomes
from UniProtKB (see UniProt Development), InterPro
v55.0 coverage remained substantial (79.7% of
UniProtKB proteins). InterPro also continued to be
a major provider of GO terms, with the latest release
assigning almost 110 million terms to around 35 million
proteins in UniProt release 2016_01.
InterPro’s member databases use diverse analysis
algorithms, and our team collaborates with several
groups to improve analysis throughput. Release 50.0 saw
the incorporation of a new version of PIRSF, which uses
the HMMER3 analysis algorithm. HMMER3 runs about
1000 times faster than HMMER2.0, allowing InterPro
to calculate the growing volumes of UniProtKB match
data in a timely manner. InterPro release 51.0 debuted a
sequence database pre-filtering heuristic to reduce the
time it takes to calculate matches against the HAMAP
database. This sped up our protein-match-generation
process, and bolsters our capacity to handle future
sequence data growth.
We completed the migration of Pfam from the Wellcome
Trust Sanger Institute to EMBL-EBI in 2014, and in
2015 focused on issuing more frequent releases of
the databases. We changed the underlying database
to UniProt reference proteomes, rather than the
whole of UniProt. Using this subset, which provides
excellent representation of the whole of UniProt, brings
significant efficiencies. Training Pfam probabilistic
models on this representative set of sequences
demonstrated no reduction in sensitivity. Furthermore,
it reduces curation overheads, speeds up production and
reduces the amount of data to present via the website.
Pfam still calculates matches for all UniProt, and these
remain accessible for download.
To streamline and improve our curation processes,
we modified our quality-assurance measures to allow
a limited overlap between Pfam entries. This new
measure actually improves Pfam definitions, and helps
speed up entry curation. In 2015, these improvements
enabled the production of Pfam releases 28.0 and 29.0
We migrated the HMMER website from Janelia
Research Campus to EMBL-EBI, where it provides