3000+ Attendees, 450 Speakers, 12 Conference Tracks, 100+ Posters
 
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2014 Archived Content

 

Cambridge Healthtech Institute’s Fifth Annual

Genome and Transcriptome Analysis

Next-Generation Sequencing of Disease Genomes, Epigenomes & Transcriptomes

February 10-12, 2014 | Moscone North Convention Center | San Francisco, CA

 

Over a decade following the completion of the Human Genome Project, next-generation sequencing has progressed from the future to the forefront of modern-day research. The advent of NGS– along with a shift toward precision medicine – has revolutionized the prevention, diagnosis, prognosis, treatment and understanding of the basic biology of complex disease, by offering unprecedented interrogation of the human genome at high resolution, and relatively low costs. With NGS becoming commonplace, and canvassing a wide range of applications within genome, epigenome, and transcriptome interrogation, holistic views of human diseases are emerging from the integration of varied NGS data - providing insights into the underlying genome, a regulatory epigenome, and a dynamic transcriptome. The Genome and Transcriptome Analysis meeting is designed to explore how NGS is continuing to shape our understanding human disease, by uncovering biological meaning from analyzing NGS data.

Day 1 | Day 2 | Day 3 | Download Brochure 

Tuesday, February 11

7:00 am Registration and Morning Coffee


8:00 Plenary Keynote Session (Click Here For More Details)  


9:15 Refreshment Break in the Exhibit Hall with Poster Viewing



SINGLE-CELL GENOME & TRANSCRIPTOME SEQUENCING 

10:25 Chairperson’s Remarks

Jan Vijg, Ph.D., Professor & Chair, Department of Genetics, Albert Einstein College of Medicine

10:30 Sequencing Both the Transcriptome and Genome of Single Cells in Health and Disease

Chris P. Ponting, Ph.D., Head, Computational and Disease Genomics, Functional Genomics Unit, University of Oxford; Associate Member, Wellcome Trust Sanger Institute

In this presentation I will discuss experimental approaches being developed to sequence the poly-adenylated transcriptome together with the genome of individual cells. These approaches now enable consideration of the effects of DNA variants on transcript levels in single cells.

11:00 Dynamic Heterogeneity of Primary Immune Cells Revealed By Large-Scale Single-Cell RNA-Seq

Hongkun Park, Ph.D., Professor, Chemistry and Physics, Department of Chemistry and Chemical Biology, Harvard University; Associate Member, The Broad Institute

Recent molecular studies have revealed that individual cells can exhibit substantial differences in gene expression, protein levels, and phenotypic output, with important functional consequences. I will describe our efforts to dissect this heterogeneity and its biological implications using large-scale single-cell transcriptomics. In particular, I will discuss our recent studies of immune dendritic cells and T cells using single-cell RNA-Seq and describe how these studies can be used to uncover functional diversity between cells and to decipher cell states and circuits.

11:30 Single-Cell Genomics in Aging

Jan Vijg, Ph.D., Professor & Chair, Department of Genetics, Albert Einstein College of Medicine

To dissect age-related intra-tissue heterogeneity we developed single-cell, genome-wide sequencing procedures to measure both single nucleotide and structural variation. To directly link single-cell, genomic mutation loads to possible consequences at the level of the transcriptome, we performed concurrent global mRNA and whole genome amplification, followed by RNA-Seq and whole exome sequencing. This method, “single-cell transcriptogenomics”, allows us to directly track the consequences of randomly induced genetic mutations on gene expression profiles in the same single cell.

12:00 pm Genetic Programming in Human and Mouse Early Embryos Revealed by Single-Cell RNA Sequencing

Guoping Fan, Ph.D., Professor, Human Genetics, University of California, Los Angeles

We report here a comprehensive analysis of transcriptome dynamics from oocyte to morula in both human and mouse embryos, using single-cell RNA sequencing. By weighted gene co-expression network analysis, we find that each developmental stage can be delineated concisely by a small number of functional modules of co-expressed genes. This result indicates a sequential order of transcriptional changes in pathways of cell cycle, gene regulation, translation and metabolism, acting in a step-wise fashion from cleavage to morula.

12:30 Session Break

12:40 Luncheon Presentation I: Creating Predictive Disease Models Using Knowledge Networks

Nikolai Daraselia, Ph.D., Director, Research, Elsevier

Drug induced cholestasis is a common liver toxicity resulting in reduced bile acid secretion – a potential adverse event in drug development.   A cholestasis disease model was developed predicting FGF 19/15 involvement in bile acid biosynthesis and regulation by FXR and PXR.  When FXR and PXR are up-regulated, bile acid biosynthesis is down-regulated resulting in drug-induced cholestasis.  Since this publication, FXR, PXR and FGF19/15 roles in drug-induced cholestasis have been clearly established. Discussion on the role of predictive molecular disease models in early discovery will be presented.

1:10 Luncheon Presentation II (Sponsorship Opportunity Available)  

1:40 Refreshment Break in the Exhibit Hall with Poster Viewing


FUNCTIONAL IMPACT OF NON-CODING RNA 

2:15 Chairperson’s Remarks

Leonard Lipovich, Ph.D., Associate Professor, Center for Molecular Medicine and Genetics, Wayne State University School of Medicine

2:20 microRNA Dysregulation in Cancer

Carlo M. Croce, M.D., Professor and Chair, Department of Molecular Virology, Immunology and Medical Genetics, Human Cancer Genetic Program, The Ohio State University

2:50 Long Non-Coding RNA Genes Shift Human Breast Cancer Cells along the Apoptosis- Proliferation Axis

Leonard Lipovich, Ph.D., Associate Professor, Center for Molecular Medicine and Genetics, Wayne State University School of Medicine

The ENCODE Consortium highlighted the extraordinary abundance of long non-coding RNA (lncRNA) genes in the human genome. We interrogated the estrogen-responsive lncRNA transcriptome of human estrogen receptor alpha positive breast cancer, pinpointing a set of estrogen-induced lncRNAs. Knockdown and overexpression of these lncRNAs, followed by five phenotypic assays indicated they have profound and reproducible phenotypic impacts on human breast cancer cell morphology and growth. These functional lncRNAs should be rationally targeted in cancer therapeutics.

3:20 The Impact of Rare Non-Coding Variants of Gene Expression and Disease

Stephen B. Montgomery, Ph.D., Assistant Professor, Pathology, Genetics & Computer Science, Stanford University School of Medicine

Recent and rapid human population expansion has led to an excess of rare genetic variants that are expected to contribute to an individual’s genetic burden of disease risk. Large-scale sequencing studies have highlighted an abundance of rare, deleterious variants within protein-coding sequences. However, in addition to rare protein-coding variants, rare non-coding variants are likely enriched for functional consequences. I will highlight investigations of individual, family and population transcriptomes to identify the extent and impact of rare non-coding variants.

3:50 Selected Poster Presentation: From Public Repositories to Molecular Biomarkers Using Cloud Computing: Prostate Cancer-Specific lncRNAs

Subha Srinivasan, Ph.D., Core Faculty Scientist, Bioinformatics, Institute of Bioinformatics and Applied biotechnology

4:20 Valentine’s Day Celebration in the Exhibit Hall with Poster Viewing

5:20 Breakout Discussions in the Exhibit Hall 

These interactive discussion groups are open to all attendees, speakers, sponsors, & exhibitors. Participants choose a specific breakout discussion group to join. Each group has a moderator to ensure focused discussions around key issues within the topic. This format allows participants to meet potential collaborators, share examples from their work, vet ideas with peers, and be part of a group problem-solving endeavor. The discussions provide an informal exchange of ideas and are not meant to be a corporate or specific product discussion.

Overcoming Limitations in Single-Cell Sequencing 

Jan Vijg, Ph.D., Professor & Chair, Department of Genetics, Albert Einstein College of Medicine     

  • Why single-cell genomics?
  • What are the critical limitations of single cell sequencing of genomes and transcriptomes and what measures are being taken to overcome these issues?
  • Can single-cell genomics be applied in a cost-effective, high-throughput mode?
  • What are the key computational and/or statistical issues in single-cell genomics?
  • What are the main clinical and industrial applications of single-cell genomics?

Transcriptomics to Therapeutics: Bridging the lncRNA Divide 

Leonard Lipovich, Ph.D., Associate Professor, Center for Molecular Medicine and Genetics, Wayne State University School of Medicine 

  • Have exomes and RNA-Seq hindered, rather than helped, lncRNA disease genomics?
  • How can we proceed from disease lncRNA discovery, in GWAS and functional studies, to translational therapeutics?
  • Which of the currently known lncRNA mechanisms present the best opportunities for therapeutic targeting?
  • What are the limitations of animal models for studying lncRNA function, in view of lncRNA evolutionary non-conservation?
  • In the absence of a "national institute of RNA" or lncRNA study sections at the NIH, can pharmaceutical companies drive clinical-translational work in this field through academic-industry partnerships?

Clinical-Grade Genomic Interpretation and the Role of Clinical Data Sharing 

Gabe Rudy, Vice President, Product Development, Golden Helix 

  • What are the critical limitations in interpreting genomic data?
  • How do you incorporate the latest genomic annotations and research while providing a certifiable dry-bench clinical test?
  • Are the proposed federally sponsored clinical variant repository ClinVar sufficient as data sharing platform?
  • For the patient with an undiagnosed genetic disorder: is the risk of privacy violation of data sharing outweighed by the potential benefits?
  • What are both the ideal and the pragmatic solution to re-analyzing samples as public annotations variant’s classifications change and when is notifying physicians and patients warranted?
  • How should the level of certainty of a given genomic interpretation be communicated to the physician and patient?
 

6:30 Close of Day

 

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