ayout 1 - EMBL Grenoble

EMBL Research at a Glance 2009
Ewan Birney
PhD 2000, Sanger Institute,
Hinxton, Cambridge.
Team leader at EMBL-EBI
since 2000.
PANDA nucleotides and methods for genome
analysis
Previous and current research
the way our DNA archival services operate and more focus on coordinating
with genomic resources.
In addition, the Birney research group focusses on DNA sequence interpretation.
There are two major themes to this research. The first is algorithm
development. There have been a number of algorithmic developments in the
Birney group, in particular on sequence alignment methods (Slater & Birney,
BMC Bioinformatics), multiple alignments (Paten et al., Genome Research)
and on de novo assembly using short reads (Zerbino & Birney,
Genome Research). The second is on data-driven discovery of important genomic
features in the genome. This includes large projects, such as the EN-
CODE project (The ENCODE Consortium, Nature), which involves a large
number of experimental groups focussing on the interpretation of genomic
information, particular from non-coding DNA sequence. Integration across
different data types provides new insights, for example, the surprising lack of
correlation of conservation with experimentally-assayed function. There are
also more specific, focussed projects, such as the exploration of cis-regulation
in vertebrates (Ettwiller et al., Genome Biology) in which specific new data
discovery technique are developed to elucidate genomic function.
Future projects and goals
Ewan Birney is joint head of the PANDA team, with Rolf Apweiler, and has a strategic oversight
of the major DNA projects: Ensembl, Ensembl Genomes and the European Nucleotide Archive
(ENA). These are large projects all dealing with DNA sequence information in a variety of forms,
in particular in the annotation and interpretation of genomes. DNA sequence remains at the heart
of molecular biology and hence bioinformatics and its use has grown significantly with the recent
advent of ultra-high throughput DNA sequencing machines. In 2008 we have seen a striking
growth in two areas – the use of these new machines for surveying natural variation in populations,
in particular the human population and the more routine determination of genotypes from large
disease cohorts, leading to associations between genetics and disease. The shift in technology and
the repositioning of genomic information as a key organisation principal has meant that there
have been significant changes to
Figure showing the expression of synthetic enhancers designed
using algorithms from the cis-regulatory research performed in
the group. The arrows show tissue specific expression in
medaka fish embryos from these ab initio designed enhancers.
Future research continues both of these themes – algorithm development
and data-driven discovery, both relating to genomic DNA sequence, but will
also add the use of intra-species variation (i.e. natural variation in a population)
with molecular markers as a component. Leveraging the natural polymorphisms in different populations allows us to understand how
molecular function varies between individuals, and how this variation is correlated to the genotype of each individual. In the context of the
human genome, very often this is done in the context of specific diseases, so one has genotype, functional information and disease status. In
other organisms (for example, rodents), one has more controlled phenotype measurement at the organism level, allowing more complex scenarios
to be explored.
Selected references
Ettwiller, L. et al. (2008). Analysis of mammalian gene batteries
reveals both stable ancestral cores and highly dynamic regulatory
sequences. Genome Biol., 9, R172
Paten, B. et al. (2008). Enredo and Pecan: genome-wide mammalian
consistency-based multiple alignment with paralogs. Genome
Res.,18, 181-1828
Zerbino, D.R. & Birney, E. (2008). Velvet: Algorithms for de novo
short read assembly using de Bruijn graphs. Genome Res., 18, 821-
829
The ENCODE Consortium (2007). Identification and analysis of
functional elements in 1% of the human genome by the ENCODE
pilot project. Nature, 7, 799-816
Slater, G.S. & Birney, E. (2005). Automated generation of heuristics
for biological sequence comparison. BMC Bioinformatics, 6, 31
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