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    From linear genome sequence to three-dimensional organization of the cell nucleus

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    Authors
    Politz, Joan C. Ritland
    van Driel, Roel
    Sauer, Markus
    Pombo, Ana
    UMass Chan Affiliations
    University of Massachusetts Medical School
    Document Type
    Journal Article
    Publication Date
    2003-03-07
    Keywords
    Animals
    Cell Nucleus
    Chromatin
    Computational Biology
    *Genome
    *Genome, Human
    Genomics
    Humans
    Mice
    Microscopy, Fluorescence
    Nanotechnology
    Computational Biology
    Genomics
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    Source
    Genome Biol. 2003;4(3):310. Epub 2003 Feb 28.
    Permanent Link to this Item
    http://hdl.handle.net/20.500.14038/42246
    PubMed ID
    12620101
    Related Resources
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      Computational Approaches for the Analysis of Chromosome Conformation Capture Data and Their Application to Study Long-Range Gene Regulation: A Dissertation

      Lajoie, Bryan R. (2016-02-10)
      Over the last decade, development and application of a set of molecular genomic approaches based on the chromosome conformation capture method (3C), combined with increasingly powerful imaging approaches have enabled high resolution and genome-wide analysis of the spatial organization of chromosomes. The aim of this thesis is two-fold; 1), to provide guidelines for analyzing and interpreting data obtained from genome-wide 3C methods such as Hi-C and 3C-seq and 2), to leverage the 3C technology to solve genome function, structure, assembly, development and dosage problems across a broad range of organisms and disease models. First, through the introduction of cWorld, a toolkit for manipulating genome structure data, I accelerate the pace at which *C experiments can be performed, analyzed and biological insights inferred. Next I discuss a set of practical guidelines one should consider while planning an experiment to study the structure of the genome, a simple workflow for data processing unique to *C data and a set of considerations one should be aware of while attempting to gain insights from the data. Next, I apply these guidelines and leverage the cWorld toolkit in the context of two dosage compensation systems. The first is a worm condensin mutant which shows a reduction in dosage compensation in the hermaphrodite X chromosomes. The second is an allele-specific study consisting of genome wide Hi-C, RNA-Seq and ATAC-Seq which can measure the state of the active (Xa) and inactive (Xi) X chromosome. Finally I turn to studying specific gene – enhancer looping interactions across a panel of ENCODE cell-lines. These studies, when taken together, further our understanding of how genome structure relates to genome function.
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      Structural Variation Discovery and Genotyping from Whole Genome Sequencing: Methodology and Applications: A Dissertation

      Zhuang, Jiali (2015-09-15)
      A comprehensive understanding about how genetic variants and mutations contribute to phenotypic variations and alterations entails experimental technologies and analytical methodologies that are able to detect genetic variants/mutations from various biological samples in a timely and accurate manner. High-throughput sequencing technology represents the latest achievement in a series of efforts to facilitate genetic variants discovery and genotyping and promises to transform the way we tackle healthcare and biomedical problems. The tremendous amount of data generated by this new technology, however, needs to be processed and analyzed in an accurate and efficient way in order to fully harness its potential. Structural variation (SV) encompasses a wide range of genetic variations with different sizes and generated by diverse mechanisms. Due to the technical difficulties of reliably detecting SVs, their characterization lags behind that of SNPs and indels. In this dissertation I presented two novel computational methods: one for detecting transposable element (TE) transpositions and the other for detecting SVs in general using a local assembly approach. Both methods are able to pinpoint breakpoint junctions at single-nucleotide resolution and estimate variant allele frequencies in the sample. I also applied those methods to study the impact of TE transpositions on the genomic stability, the inheritance patterns of TE insertions in the population and the molecular mechanisms and potential functional consequences of somatic SVs in cancer genomes.
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      Genome-Wide Identification of Early-Firing Human Replication Origins by Optical Replication Mapping [preprint]

      Klein, Kyle; Wang, Weitao; Borrman, Tyler M.; Chan, Saki; Zhang, Denghong; Weng, Zhiping; Hastie, Alex; Chen, Chunlong; Gilbert, David M.; Rhind, Nicholas R. (2017-11-06)
      The timing of DNA replication is largely regulated by the location and timing of replication origin firing. Therefore, much effort has been invested in identifying and analyzing human replication origins. However, the heterogeneous nature of eukaryotic replication kinetics and the low efficiency of individual origins in metazoans has made mapping the location and timing of replication initiation in human cells difficult. We have mapped early-firing origins in HeLa cells using Optical Replication Mapping, a high-throughput single-molecule approach based on Bionano Genomics genomic mapping technology. The single-molecule nature and 290-fold coverage of our dataset allowed us to identify origins that fire with as little as 1% efficiency. We find sites of human replication initiation in early S phase are not confined to well-defined efficient replication origins, but are instead distributed across broad initiation zones consisting of many inefficient origins. These early-firing initiation zones co-localize with initiation zones inferred from Okazaki-fragment-mapping analysis and are enriched in ORC1 binding sites. Although most early-firing origins fire in early-replication regions of the genome, a significant number fire in late-replicating regions, suggesting that the major difference between origins in early and late replicating regions is their probability of firing in early S-phase, as opposed to qualitative differences in their firing-time distributions. This observation is consistent with stochastic models of origin timing regulation, which explain the regulation of replication timing in yeast.
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