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Bio-IT World and Cambridge Healthtech Institute’s Inaugural

RNA-Seq and Transcriptome Analysis
Unraveling Layers of Expression

5-6 December 2013 | Sheraton Lisbon Hotel & Spa | Lisbon, Portugal

Transcriptome sequencing (RNA-Seq) is a robust approach steadily replacing microarrays as the choice method to accurately profile and quantify overall gene expression levels, while simultaneously allowing unbiased discovery of alternative splicing variants, rare and novel transcripts, miRNA precursors, differential isoforms and de novo analysis of samples. The ability to obtain a complete picture of disease transcriptomes provides clearer understanding of how the underlying genome is converted into the functional proteins, allowing for clinical utility in patient classification, diagnosis, and individualized treatment. However, a myriad of advanced bioinformatics tools and techniques for quality control, pre-processing, alignment, quantitative analysis and differential expression pose significant hurdles for many biologists and clinicians. Bio-IT World and Cambridge Healthtech Institute’s RNA-Seq and Transcriptome Analysis is designed to navigate the many bioinformatics challenges encountered by transcriptome sequencing, while highlighting its recent clinical applications.

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Recommended Pre-Conference Symposia*

Clinical Epigenetics
Quantitative Digital Detection Technologies 

*Separate Registration Required


11:30 Conference Registration


11:45 From Genome Annotation to Genome Medicine

Timothy Hubbard. Ph.D.Timothy Hubbard, Ph.D., Senior Group Leader, Wellcome Trust Sanger Institute, United Kingdom

I will describe the status of the human genome sequence and its annotation, in particular the generation of the GENCODE geneset as part of the ENCODE project and the impact of RNA-seq. I’ll also discuss the latest human genome assembly from the Genome Reference Consortium (GRC). As the UK plans to sequence 100,000 human genomes in the National Health Service (NHS), I’ll discuss requirements for integrating genomics into healthcare systems and summarize progress towards genomic medicine in UK.


12:35 Enjoy Lunch on Your Own



14:00 Chairperson’s Opening Remarks

Melanie Lehman, Ph.D., Research Fellow, Australian Prostate Cancer Research Centre, Queensland University of Technology, Australia

14:05 De Novo Full-Length Transcriptome Analysis by a Hybrid Sequencing Approach

Wei ChenWei Chen, Ph.D., Senior Scientist & Group Leader, Max Delbruck Center for Molecular Medicine, Germany

I will present a hybrid sequencing approach based transcriptome analysis pipeline that reports high quality transcripts in their full length independent of reference genome sequences. Using full-length cDNA libraries in conjunction with Single Molecule Read-Time (SMRT) DNA sequencing technology, we can directly capture the full-length transcripts, but with low sequencing accuracy. To report high quality transcriptome, we then developed a novel computational tool, IPEC (Illumina Pacbio Error Correction), which utilizes the high quality Illumina sequencing data to correct the random errors generated in the SMRT sequencing. Our method can be widely applied in different organisms, especially those without genome reference sequences.

14:35 Detecting Differential Splicing Employing SplicingCompass on RNA Sequencing Data

Agnes Hotz-WagenblattAgnes Hotz-Wagenblatt, Ph.D., Co-Leader and Senior Scientist, HUSAR Bioinformatics Lab, Core Facility Genomics & Proteomics, German Cancer Research Center

Aberrant splicing events often have pathological consequences and are associated with various diseases and cancer types. The emergence of next generation RNA sequencing (RNA-seq) provides an exciting new technology to analyse alternative splicing on a large scale. We present a new method and software to predict genes that are differentially spliced between two different conditions using RNA-seq data. Our method employs geometric angles between the high dimensional vectors of exon read counts. With this, differential splicing can be detected even if the splicing events comprise of higher complexity and involve previously unknown splicing patterns.

15:05 A Hybrid Approach to Comprehensive Transcriptome Reconstruction Using Genome-Guided and De Novo RNA-Seq Assembly Leveraging Trinity and PASA2

Brian HaasBrian Haas, Manager, Genome Annotation, Outreach, Bioinformatics and Analysis, The Broad Institute, United States

The utility of RNA-sequencing and the broad range of organisms to which it is applied requires analysis tools that can be effectively leveraged across diverse realms of biology. Existing reference genomes or draft genome assemblies may yield a limited view of the transcript content of a sample due genome misassembly, sequencing gaps, or genuine sequence variation between sequenced samples and available reference genomes. Here we present a hybrid approach that combines genome-guided and de novo RNA-Seq assembly to annotate gene structures and capture those transcripts missing or otherwise insufficiently represented by genome assemblies. We demonstrate our approach to be highly effective across diverse eukaryotes and to the restructured genomes of human breast cancer cell lines.

15:35 Sponsored Presentation (Sponsorship Opportunity Available)

16:05 Refreshment Break in the Exhibit Hall with Poster Viewing

16:50 Sponsored Presentation (Sponsorship Opportunity Available)



17:20 Alternative Protein-Coding Transcripts in Prostate Cancer

Melanie LehmanMelanie Lehman, Ph.D., Research Fellow, Australian Prostate Cancer Research Centre, Queensland University of Technology, Australia

We have applied de novo transcriptome assembly methods to RNA-seq data to profile RNA expression in prostate cancer cells. We have identified alternative protein-coding RNAs that are missing canonical functional domains as well as long coding RNAs (lncRNAs) that are overlapping—and often mistaken for—protein-coding RNAs. We will present the implications of these alternative transcripts to pathway and functional analysis in the context of our research in late stage prostate cancer.

17:50 Deciphering the Neuroblastoma Transcriptome by RNA-Seq, qPCR and Exon-Level Resolution Array Analyzes

Alexander SchrammAlexander Schramm, Ph.D., Lab Head, Oncology Research, Children’s Hospital, University Hospital Essen, Germany

During my presentation, I will report on integration of technologies required to understand which coding and non-coding RNAs are transcribed in a cancer cell. Results from array-based technologies, qPCR and next-generation RNA-seq will be compared using the embryonal tumor, neuroblastoma, as a model system. An automated workflow for the analyses of RNA-seq data will be presented. Finally, I will discuss some ideas for integrating NGS data into clinical decision making.

18:35 Close of Day


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Clinical Exome Sequencing 



High-Scale Computing 

Genome Informatics 

Pre-Conference Symposia:

Clinical Epigenetics 

Digital Detection 

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