FY2010 - Oak Ridge National Laboratory

Director’s R&D Fund—
Systems Biology and the Environment
Systems Biology, the Joint Genome Institute (JGI) partnership, Bioremediation, Microbial Sequencing,
and Genome Annotation that will be critically dependent on appropriate computational capabilities for
data management, annotation, and support of experimental direction. The prototype developed in this
project will demonstrate a new approach that could be expanded for these programs and the larger
research community.
Results and Accomplishments
A number of whole genome transcriptome data sets for C. thermocellum were collected under normal and
ethanol stress conditions using older standard gene expression array technology, newer high-density tiling
array technology, and high-throughput sequencing. Analysis methods were developed or integrated and
improved to determine differential expression and quantify genes and other features such as operons.
Tools were also developed for visualization of both tiling array data and gene expression as determined
by sequencing (RNAseq) data in conjunction with genome annotation. Analysis using these tools shows
that transcription in the bacterial cell is much more complicated than previously known. We were able to
detect the presence of several previously unknown features such as 5ꞌ regulatory RNAs, small regulatory
RNAs, and alternative transcription start sites including ones in the middle of annotated genes.
Inference of genetic regulatory circuits depends on many things including accurate genome annotation,
correct quantification of the genes in the cell, precise structure of operons including transcription start
sites, quantification of the transcription factors in the cell, and accurate models for the association of
transcription factors to binding sites. Conventional data models (e.g., Genbank files) are inadequate for
assembling data of different types into a computational model of the genetic regulatory network because
they do not adequately describe concepts associated with regulatory networks and the underlying
assumptions of the data used to generate these models. Over the course of this project, we investigated
multiple data representation alternatives including SMBL, XML, Chado, and RDF/XML. The goal was to
find a model that was appropriate for representing a genetic regulatory network. We were able to
determine that BioPAX (built on RDF/XML) is a community adopted data standard that is capable of
representing Genetic Regulatory networks. We developed two alternative methods for linking traditional
genome annotations to the BioPAX standard. First, we implemented a proof-of-concept annotation
representation based on the Semantic Web (RDF/XML). This approach allows one to merge the BioPAX
annotation directly with annotation data using the SPARQL query language. Second, we explored the
approach of directly importing all of the concepts stored in raw ontologies and the raw data from
expression experiments into a Chado relational database schema. The relational database approach is
currently better suited to production use, whereas the Semantic Web-based representation is better suited
for sharing of scientific data and transparency. Future advancements in Semantic Web technologies may
also make it suitable for production.
Program Development
Since this project began it has become clear that transcriptomics will be the “next big wave” in systems
biology research based on rapid advancements in sequencing technology and RNAseq. With the new
Illumina technology using 100× sample multiplexing, RNAseq data will be more cheaply generated than
alternative technologies so it was fortuitous that we focused on this area. We have discussed incorporating
RNAseq transcriptomics as part of the JGI sequencing and annotation pipeline with the JGI management.
As a preliminary test they have agreed to sequence 12 samples from some of the Caldicellulosiruptor
genomes being studied by ORNL’s BioEnergy Science Center using their Illumina sequencing machines.
We will process this data using the RNAseq analysis pipeline created as part of this project. Successful
results in this project could include additional Caldicellulosiruptor transcriptome RNAseq samples
sequenced by both JGI and ORNL and eventually could include an expanded ORNL annotation pipeline
which would include transcriptome analysis as a new product for all researchers. Newmodifications to the
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