2017 PQG Conference: Quantitative Analysis of Higher Order Chromatin Interactions
Е-мейл Оргкомітету: https://www.hsph.harvard.edu/2017-pqg-conference/submit-an-abstract/
Організатори: Biostatistics Department, Harvard T.H. Chan School of Public Health
The Program in Quantitative Genomics will host its 11th annual conference, “Quantitative Analysis of Higher order chromatin interactions” on November 2-3, 2016 at the Joseph B. Martin Conference Center at Harvard Medical School in Boston, MA.
The conference will be centered on the following three topics:
SESSION I: Emerging Technologies
SESSION II: Applications to Basic Biology and Disease Mechanisms
SESSION III: Computational Challenges
The impetus for this year’s theme comes from the increasing amount of data that provides information on the nuclear organization of the human genome and its applications. A series of “chromatin confirmation capture” techniques have been developed in the past decade for identifying a three-dimensional interaction, starting with an assay that interrogates physical interaction between two specified loci to now, the most recent form, called “Hi-C,” that can measure interactions between all pairs of genomic loci at once. Profiling such three-dimensional interactions is critical for a full understanding of gene regulation. Distal regulatory elements—including enhancers, silencers, insulators, and locus control regions—play a critical role in transcriptional control; a distant enhancer, for instance, must be brought close to a promoter to initiate transcription. Until recently, we did not have data with sufficient resolution to infer such interactions accurately. However, with more refined technology and the decreasing sequencing cost, it is now possible to generate high-resolution datasets (with close to a billion sequencing reads, on the same order as human whole-genome sequencing), and the scientific community is on the verge of generating an immense amount of Hi-C and related types of data. The conference will deal with the key aspects in analyzing and interpreting these large and complex datasets.
Higher-order chromatin data are particularly important for aiding interpretation of non-coding variants. With the large amount of whole-genome sequencing data (theme of last year’s conference), there is a great deal of interest in determining which non-coding mutations are functional. Knowing which non-coding variants are in which regulatory elements and what their target genes may be, is crucial. A flurry of recent papers has provided ample evidence for this idea. For instance, in IDH-mutant gliomas, the mutation causes hypermethylation at CTCF-binding sites, which causes loss of CTCF, leading to aberrant enhancer interactions with an oncogene (PDGFRA) that is normally insulated from such interactions [Flavahan et al, Insulator dysfunction and oncogene activation in IDH mutant gliomas, Nature, 2016]; similarly, it was shown that in T-cell acute lymphoblastic leukemias, perturbing the loop structure (binding of the insulator CTCF) activated proto-oncogenes [Hnisz et al., Activation of proto-oncogenes by disruption of chromosome neighborhoods, Science, 2016]. Therefore, integrative analysis of chromatin data will be essential for whole-genome analysis as well as for other mechanistic studies of gene regulation. NIH has recognized the importance of this area by funding 4D Nucleome, a large Common Fund project.
Our conference will bring together those at the forefront of technology for measuring 3D interactions (including both sequencing-based and imaging-based assays), molecular biologists and geneticists, and quantitative methodologists. The conference schedule includes time for scientific presentations and a poster session and reception for submitted abstracts.
Веб-сторінка конференції: https://www.hsph.harvard.edu/2017-pqg-conference/
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