Computational tools and Interoperability in Comparative ... - CBS

Chapter 1
Introduction
Introduction
Since the publication of the first complete bacterial genome sequence in 1995 close to a
thousand prokaryotes have been fully sequenced and made publicly available. These data
represent large efforts by many scientists and technicians, closing gaps in the chromosomal
sequences and providing detailed gene annotations. These genome projects constitute a
valuable collection of prokaryotic diversity and they serve as an indispensable resource for
comparative studies when novel features of newly discovered organisms are identified.
We are however witnessing a transition phase as genome sequencing becomes a trivial
step carried out by any researcher or company in the need of a better characterization of an
organism. Sequencing equipment and the capability of assembling an entire genome will
likely follow the same path as any other technological advance the world has seen. Telephones,
cars, aeroplanes, and computers all have started as costly and clumsy attempts,
and ended up as mainstream affordable and efficient products, taken for granted. Nothing
will prevent sequencing technology to follow the same path and it will likely end up as a
tiny desktop instrument on a doctor’s table next to the blood preasure measuring device.
But the decreasing novelty of presenting a new genome sequence could cause a decline in
the number of published genomes in the near future, causing less control and organization
of these data, with fewer demands on data integrity, sequencing and annotation quality.
Some major issues arrise as massive amounts of genomic data becomes a reality. There
are signs that our ability to process and analyze genomic data is being overtaken by the
technological developments of the sequencing equipment. For example, over the past
twenty-five years, GenBank has grown roughly 100,000 fold, whereas the computer processing
power, following Moore’s law has grown “only” a 1,000 times. The overwhelming
data generated by modern sequencing machines constitite tough challenges for most biologist
and although efforts are constantly being made to improve gene prediction and
genome assembly software, these steps are not yet functioning in a scalable and unsupervised
fashion. Further, post-annotation steps deriving knowledge from predicted genes
remain one of the biggest challenges. How do we transform contigs of nucleotide sequences
into knowledge to derive the phenotype of the organism?
As more prokaryotic genomes are being sequenced, there are now a number of species
for which multiple strains are sequenced. Roughly one fourth of all prokaryotic projects
exist within species where 5 or more strains are available. As this coverage of diversity
increases, we may begin to answer some key questions with better confidence. How do
we define core sets of genes? Can we estimate the size of the pan genome? Which
features are novel in selected strains and are these features regionally conserved within
the chromosomes? To answer these questions, there is a fundamental need to visuzalize
and overview the similarity and differences between larger number of genomes. Obtaining
such an overview allows some questions concerning gene acquisition and chromosomal
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