Keynote: Edwin Cuppen

Edwin Cuppen, senior staff scientist at the Hubrecht Institute for Developmental Biology and Stem Cell Research, and Professor of Genome Biology at the University of Utrecht.

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Meeting Program

The program of the Short Read SIG will have 17 contributed talks on topics including read SNP discovery, indel and copy number variation discovery, RNA sequencing, Cancer genomics, and metagenomics, and a talk on TopHat -- selected from the papers published in the Bioinformatics journal in the past year. We will also have a keynote talk by Edwin Cuppen. The full schedule of the SIG is available here. You can also now browse the abstract book.

While the promise of next generation sequencing (NGS) technologies has become a reality, and in the past year several computational methods for assembly and alignment with short reads have been developed, realizing the full promise of these technologies requires the development of methods that can analyze the resulting assemblies and mappings of the reads to infer biological meaning: genome variation, novel transcript discovery, microRNA expression analysis, and metagenomic analysis.

In particular, we are interested in presentations describing methodology to infer various polymorphisms (SNPs, large insertions/deletions, copy number variations) with short read data. As the HapMap project has increased our understanding of SNPs, structural variation (including insertions, deletions, translocation, inversions, and CNVs) have come to the forefront as one of the main sources of variation within a species. NGS technologies offer the potential of high resolution detection of most types of genomic variants that are just beginning to be explored.

Another exciting application of NGS technologies is RNA sequencing. RNA sequencing is currently used for several applications, including RNA expression, de-novo transcriptome sequencing for non-model organisms, and novel transcript discovery, however computational methods for analysis of this data is in its infancy. For RNA and micro-RNA expression profiling, NGS has significant advantages compared to microarray methods in that it is better able to identify quantities of very common and very rare transcripts. Transcriptome profiling is also increasingly used for sequencing the RNA of non-model organisms for phylogenetic and population studies, and methods for transcriptome assembly and co-assembly need to be improved.

NGS Sequencing is also commonly used for discovery of transcription factor binding sites (and nucleosome positioning) using CHiP-SEQ, for methylation profiling, and for analysis of metagenomic samples. We will certainly welcome presentations on these topics, as well as any other important methods related to NGS technologies.

Last Modified: Jun 10 2009 0:04:19 EDT

Michael Brudno, University of Toronto

Jens Stoye, Universitat Bielefeld

Francisco de la Vega, Applied Biosystems