@comment{{This file has been generated by bib2bib 1.97}}
@comment{{Command line: bib2bib ../bibli.bib -c 'subject:"hic" or keywords:"hic"' -ob tmp.bib}}
@article{Ben-Elazar2013Spatial,
author = {Ben-Elazar, S. and Yakhini, Z. and Yanai, I.},
title = {Spatial localization of co-regulated genes exceeds genomic gene clustering
in the Saccharomyces cerevisiae genome.},
journal = {Nucleic Acids Res},
year = {2013},
volume = {41},
pages = {2191--2201},
number = {4},
month = {Feb},
abstract = {While it has been long recognized that genes are not randomly positioned
along the genome, the degree to which its 3D structure influences
the arrangement of genes has remained elusive. In particular, several
lines of evidence suggest that actively transcribed genes are spatially
co-localized, forming transcription factories; however, a generalized
systematic test has hitherto not been described. Here we reveal transcription
factories using a rigorous definition of genomic structure based
on Saccharomyces cerevisiae chromosome conformation capture data,
coupled with an experimental design controlling for the primary gene
order. We develop a data-driven method for the interpolation and
the embedding of such datasets and introduce statistics that enable
the comparison of the spatial and genomic densities of genes. Combining
these, we report evidence that co-regulated genes are clustered in
space, beyond their observed clustering in the context of gene order
along the genome and show this phenomenon is significant for 64 out
of 117 transcription factors. Furthermore, we show that those transcription
factors with high spatially co-localized targets are expressed higher
than those whose targets are not spatially clustered. Collectively,
our results support the notion that, at a given time, the physical
density of genes is intimately related to regulatory activity.},
doi = {10.1093/nar/gks1360},
pdf = {../local/Ben-Elazar2013Spatial.pdf},
file = {Ben-Elazar2013Spatial.pdf:Ben-Elazar2013Spatial.pdf:PDF},
institution = {Department of Biology, Technion - Israel Institute of Technology,
Haifa, Israel, Department of Computer Science, Technion - Israel
Institute of Technology, Haifa, Israel and Agilent Laboratories,
Tel Aviv, Israel.},
keywords = {ngs, hic},
language = {eng},
medline-pst = {ppublish},
owner = {jp},
pii = {gks1360},
pmid = {23303780},
timestamp = {2013.03.29},
url = {http://dx.doi.org/10.1093/nar/gks1360}
}
@article{Berkum2010HiC,
author = {van Berkum, N. L. and Lieberman-Aiden, E. and Williams, L. and Imakaev,
M. and Gnirke, A. and Mirny, L. A. and Dekker, J. and Lander, E.
S.},
title = {{Hi-C}: a method to study the three-dimensional architecture of genomes.},
journal = {J. Vis. Exp.},
year = {2010},
volume = {39},
pages = {e1869},
abstract = {The three-dimensional folding of chromosomes compartmentalizes the
genome and and can bring distant functional elements, such as promoters
and enhancers, into close spatial proximity (2-6). Deciphering the
relationship between chromosome organization and genome activity
will aid in understanding genomic processes, like transcription and
replication. However, little is known about how chromosomes fold.
Microscopy is unable to distinguish large numbers of loci simultaneously
or at high resolution. To date, the detection of chromosomal interactions
using chromosome conformation capture (3C) and its subsequent adaptations
required the choice of a set of target loci, making genome-wide studies
impossible (7-10). We developed Hi-C, an extension of 3C that is
capable of identifying long range interactions in an unbiased, genome-wide
fashion. In Hi-C, cells are fixed with formaldehyde, causing interacting
loci to be bound to one another by means of covalent DNA-protein
cross-links. When the DNA is subsequently fragmented with a restriction
enzyme, these loci remain linked. A biotinylated residue is incorporated
as the 5' overhangs are filled in. Next, blunt-end ligation is performed
under dilute conditions that favor ligation events between cross-linked
DNA fragments. This results in a genome-wide library of ligation
products, corresponding to pairs of fragments that were originally
in close proximity to each other in the nucleus. Each ligation product
is marked with biotin at the site of the junction. The library is
sheared, and the junctions are pulled-down with streptavidin beads.
The purified junctions can subsequently be analyzed using a high-throughput
sequencer, resulting in a catalog of interacting fragments. Direct
analysis of the resulting contact matrix reveals numerous features
of genomic organization, such as the presence of chromosome territories
and the preferential association of small gene-rich chromosomes.
Correlation analysis can be applied to the contact matrix, demonstrating
that the human genome is segregated into two compartments: a less
densely packed compartment containing open, accessible, and active
chromatin and a more dense compartment containing closed, inaccessible,
and inactive chromatin regions. Finally, ensemble analysis of the
contact matrix, coupled with theoretical derivations and computational
simulations, revealed that at the megabase scale Hi-C reveals features
consistent with a fractal globule conformation.},
doi = {10.3791/1869},
institution = {Program in Gene Function and Expression, Department of Biochemistry
and Molecular Pharmacology, University of Massachusetts Medical School.},
keywords = {ngs, hic},
language = {eng},
medline-pst = {epublish},
owner = {philippe},
pii = {1869},
pmid = {20461051},
timestamp = {2010.07.27},
url = {http://dx.doi.org/10.3791/1869}
}
@article{Dixon2012Topological,
author = {Dixon, J. R. and Selvaraj, S. and Yue, F. and Kim, A. and Li, Y.
and Shen, Y. and Hu, M. and Liu, J. S. and Ren, B.},
title = {Topological domains in mammalian genomes identified by analysis of
chromatin interactions.},
journal = {Nature},
year = {2012},
volume = {485},
pages = {376-80},
number = {5},
doi = {10.1038/nature11082},
pdf = {../local/Dixon2012Topological.pdf},
file = {Dixon2012Topological.pdf:Dixon2012Topological.pdf:PDF},
keywords = {ngs, hic},
owner = {nelle},
timestamp = {2013.03.30},
url = {http://dx.doi.org/10.1038/nature11082}
}
@article{Homouz20133D,
author = {Homouz, D. and Kudlicki, A. S.},
title = {The {3D} Organization of the Yeast Genome Correlates with Co-Expression
and Reflects Functional Relations between Genes},
journal = {PLoS ONE},
year = {2013},
volume = {8},
pages = {e54699},
number = {1},
month = {01},
abstract = {The spatial organization of eukaryotic genomes is thought to play
an important role in regulating gene expression. The recent advances
in experimental methods including chromatin capture techniques, as
well as the large amounts of accumulated gene expression data allow
studying the relationship between spatial organization of the genome
and co-expression of protein-coding genes. To analyse this genome-wide
relationship at a single gene resolution, we combined the interchromosomal
DNA contacts in the yeast genome measured by Duan et al. with a comprehensive
collection of 1,496 gene expression datasets. We find significant
enhancement of co-expression among genes with contact links. The
co-expression is most prominent when two gene loci fall within 1,000
base pairs from the observed contact. We also demonstrate an enrichment
of inter-chromosomal links between functionally related genes, which
suggests that the non random nature of the genome organization serves
to facilitate coordinated transcription in groups of genes.
},
doi = {10.1371/journal.pone.0054699},
pdf = {../local/Homouz20133D.pdf},
file = {Homouz20133D.pdf:Homouz20133D.pdf:PDF},
keywords = {hic, ngs},
owner = {nelle},
publisher = {Public Library of Science},
timestamp = {2013.03.30},
url = {http://dx.doi.org/10.1371/journal.pone.0054699}
}
@article{Lieberman-Aiden2009Comprehensive,
author = {Erez Lieberman-Aiden and Nynke L van Berkum and Louise Williams and
Maxim Imakaev and Tobias Ragoczy and Agnes Telling and Ido Amit and
Bryan R Lajoie and Peter J Sabo and Michael O Dorschner and Richard
Sandstrom and Bradley Bernstein and M. A. Bender and Mark Groudine
and Andreas Gnirke and John Stamatoyannopoulos and Leonid A Mirny
and Eric S Lander and Job Dekker},
title = {Comprehensive mapping of long-range interactions reveals folding
principles of the human genome.},
journal = {Science},
year = {2009},
volume = {326},
pages = {289--293},
number = {5950},
month = {Oct},
abstract = {We describe Hi-C, a method that probes the three-dimensional architecture
of whole genomes by coupling proximity-based ligation with massively
parallel sequencing. We constructed spatial proximity maps of the
human genome with Hi-C at a resolution of 1 megabase. These maps
confirm the presence of chromosome territories and the spatial proximity
of small, gene-rich chromosomes. We identified an additional level
of genome organization that is characterized by the spatial segregation
of open and closed chromatin to form two genome-wide compartments.
At the megabase scale, the chromatin conformation is consistent with
a fractal globule, a knot-free, polymer conformation that enables
maximally dense packing while preserving the ability to easily fold
and unfold any genomic locus. The fractal globule is distinct from
the more commonly used globular equilibrium model. Our results demonstrate
the power of Hi-C to map the dynamic conformations of whole genomes.},
doi = {10.1126/science.1181369},
pdf = {../local/Lieberman-Aiden2009Comprehensive.pdf},
file = {Lieberman-Aiden2009Comprehensive.pdf:Lieberman-Aiden2009Comprehensive.pdf:PDF},
institution = {Broad Institute of Harvard and Massachusetts Institute of Technology
(MIT), MA 02139, USA.},
keywords = {hic, ngs},
owner = {phupe},
pii = {326/5950/289},
pmid = {19815776},
timestamp = {2010.08.26},
url = {http://dx.doi.org/10.1126/science.1181369}
}
@article{Yaffe2011Probabilistic,
author = {Yaffe, E. and Tanay, A.},
title = {Probabilistic modeling of {Hi-C} contact maps eliminates systematic
biases to characterize global chromosomal architecture},
journal = {Nat. Genet.},
year = {2011},
volume = {43},
pages = {1059--1065},
number = {11},
abstract = {Hi-C experiments measure the probability of physical proximity between
pairs of chromosomal loci on a genomic scale. We report on several
systematic biases that substantially affect the Hi-C experimental
procedure, including the distance between restriction sites, the
GC content of trimmed ligation junctions and sequence uniqueness.
To address these biases, we introduce an integrated probabilistic
background model and develop algorithms to estimate its parameters
and renormalize Hi-C data. Analysis of corrected human lymphoblast
contact maps provides genome-wide evidence for interchromosomal aggregation
of active chromatin marks, including DNase-hypersensitive sites and
transcriptionally active foci. We observe extensive long-range (up
to 400 kb) cis interactions at active promoters and derive asymmetric
contact profiles next to transcription start sites and CTCF binding
sites. Clusters of interacting chromosomal domains suggest physical
separation of centromere-proximal and centromere-distal regions.
These results provide a computational basis for the inference of
chromosomal architectures from Hi-C experiments.},
doi = {10.1038/ng.947},
pdf = {../local/Yaffe2011Probabilistic.pdf},
file = {Yaffe2011Probabilistic.pdf:Yaffe2011Probabilistic.pdf:PDF},
issn = {1061-4036},
keywords = {hic, ngs},
owner = {nelle},
url = {http://dx.doi.org/10.1038/ng.947},
urldate = {2012-01-11}
}
@article{Zhang2012Spatial,
author = {Zhang, Y. and McCord, R. A. and Ho, Y.-J. and Lajoie, B. R. and Hildebrand,
D. G. and Simon, A. C. and Becker, M. S. and Alt, F. W. and Dekker,
J.},
title = {Spatial Organization of the Mouse Genome and Its Role in Recurrent
Chromosomal Translocations},
journal = {Cell},
year = {2012},
volume = {148},
pages = {908 - 921},
number = {5},
abstract = {Summary The extent to which the three-dimensional organization of
the genome contributes to chromosomal translocations is an important
question in cancer genomics. We generated a high-resolution Hi-C
spatial organization map of the G1-arrested mouse pro-B cell genome
and used high-throughput genome-wide translocation sequencing to
map translocations from target DNA double-strand breaks (DSBs) within
it. RAG endonuclease-cleaved antigen-receptor loci are dominant translocation
partners for target DSBs regardless of genomic position, reflecting
high-frequency DSBs at these loci and their colocalization in a fraction
of cells. To directly assess spatial proximity contributions, we
normalized genomic DSBs via ionizing radiation. Under these conditions,
translocations were highly enriched in cis along single chromosomes
containing target DSBs and within other chromosomes and subchromosomal
domains in a manner directly related to pre-existing spatial proximity.
By combining two high-throughput genomic methods in a genetically
tractable system, we provide a new lens for viewing cancer genomes.},
doi = {10.1016/j.cell.2012.02.002},
pdf = {../local/Zhang2012Spatial.pdf},
file = {Zhang2012Spatial.pdf:Zhang2012Spatial.pdf:PDF},
issn = {0092-8674},
keywords = {hic, ngs},
owner = {nelle},
url = {http://www.sciencedirect.com/science/article/pii/S0092867412001584}
}
@comment{{jabref-meta: selector_author:}}
@comment{{jabref-meta: selector_journal:Adv. Drug Deliv. Rev.;Am. J. Hu
m. Genet.;Am. J. Pathol.;Ann. Appl. Stat.;Ann. Math. Statist.;Ann. N.
Y. Acad. Sci.;Ann. Probab.;Ann. Stat.;Artif. Intell. Med.;Bernoulli;Bi
ochim. Biophys. Acta;Bioinformatics;Biometrika;BMC Bioinformatics;Br.
J. Pharmacol.;Breast Cancer Res.;Cell;Cell. Signal.;Chem. Res. Toxicol
.;Clin. Cancer Res.;Combinator. Probab. Comput.;Comm. Pure Appl. Math.
;Comput. Chem.;Comput. Comm. Rev.;Comput. Stat. Data An.;Curr. Genom.;
Curr. Opin. Chem. Biol.;Curr. Opin. Drug Discov. Devel.;Data Min. Know
l. Discov.;Electron. J. Statist.;Eur. J. Hum. Genet.;FEBS Lett.;Found.
Comput. Math.;Genome Biol.;IEEE T. Neural Networ.;IEEE T. Pattern. An
al.;IEEE T. Signal. Proces.;IEEE Trans. Inform. Theory;IEEE Trans. Kno
wl. Data Eng.;IEEE/ACM Trans. Comput. Biol. Bioinf.;Int. J. Comput. Vi
sion;Int. J. Data Min. Bioinform.;Int. J. Qantum Chem.;J Biol Syst;J.
ACM;J. Am. Soc. Inf. Sci. Technol.;J. Am. Stat. Assoc.;J. Bioinform. C
omput. Biol.;J. Biol. Chem.;J. Biomed. Inform.;J. Cell. Biochem.;J. Ch
em. Inf. Comput. Sci.;J. Chem. Inf. Model.;J. Clin. Oncol.;J. Comput.
Biol.;J. Comput. Graph. Stat.;J. Eur. Math. Soc.;J. Intell. Inform. Sy
st.;J. Mach. Learn. Res.;J. Med. Chem.;J. Mol. BIol.;J. R. Stat. Soc.
Ser. B;Journal of Statistical Planning and Inference;Mach. Learn.;Math
. Program.;Meth. Enzymol.;Mol. Biol. Cell;Mol. Biol. Evol.;Mol. Cell.
Biol.;Mol. Syst. Biol.;N. Engl. J. Med.;Nat. Biotechnol.;Nat. Genet.;N
at. Med.;Nat. Methods;Nat. Rev. Cancer;Nat. Rev. Drug Discov.;Nat. Rev
. Genet.;Nature;Neural Comput.;Neural Network.;Neurocomputing;Nucleic
Acids Res.;Pattern Anal. Appl.;Pattern Recognit.;Phys. Rev. E;Phys. Re
v. Lett.;PLoS Biology;PLoS Comput. Biol.;Probab. Theory Relat. Fields;
Proc. IEEE;Proc. Natl. Acad. Sci. USA;Protein Eng.;Protein Eng. Des. S
el.;Protein Sci.;Protein. Struct. Funct. Genet.;Random Struct. Algorit
hm.;Rev. Mod. Phys.;Science;Stat. Probab. Lett.;Statistica Sinica;Theo
r. Comput. Sci.;Trans. Am. Math. Soc.;Trends Genet.;}}
@comment{{jabref-meta: selector_keywords:biogm;biosvm;breastcancer;cgh;
chemogenomics;chemoinformatics;csbcbook;csbcbook-ch1;csbcbook-ch2;csbc
book-ch3;csbcbook-ch4;csbcbook-ch5;csbcbook-ch6;csbcbook-ch7;csbcbook-
ch8;csbcbook-ch9;csbcbook-mustread;dimred;featureselection;glycans;her
g;hic;highcontentscreening;image;immunoinformatics;kernel-theory;kerne
lbook;lasso;microarray;ngs;nlp;plasmodium;proteomics;PUlearning;rnaseq
;segmentation;sirna;}}
@comment{{jabref-meta: selector_booktitle:Adv. Neural. Inform. Process
Syst.;}}
This file was generated by bibtex2html 1.97.