Detecting Spatial Chromatin Organization by Chromosome Conformation Capture II : Genome-Wide Profiling by Hi-C
The chromosome conformation capture (3C) method has been invaluable in studying chromatin interactions in a population of cells at a resolution surpassing that of light microscopy, for example in the detection of functional contacts between enhancers and promoters. Recent developments in sequencing-based chromosomal contact mapping (Hi-C, 5C and 4C-Seq) have allowed researchers to interrogate pairwise chromatin interactions on a wider scale, shedding light on the three-dimensional organization of chromosomes. These methods present significant technical and bioinformatic challenges to consider at the start of the project. Here, we describe two alternative methods for Hi-C, depending on the size of the genome, and discuss the major computational approaches to convert the raw sequencing data into meaningful models of how genomes are organized.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2017 |
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| Erschienen: |
2017 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:1589 |
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| Enthalten in: |
Methods in molecular biology (Clifton, N.J.) - 1589(2017) vom: 22., Seite 47-74 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Vietri Rudan, Matteo [VerfasserIn] |
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| Links: |
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| Themen: |
3C (chromosome conformation capture) |
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| Anmerkungen: |
Date Completed 23.10.2017 Date Revised 29.01.2022 published: Print Citation Status MEDLINE |
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| doi: |
10.1007/7651_2015_261 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| 520 | |a The chromosome conformation capture (3C) method has been invaluable in studying chromatin interactions in a population of cells at a resolution surpassing that of light microscopy, for example in the detection of functional contacts between enhancers and promoters. Recent developments in sequencing-based chromosomal contact mapping (Hi-C, 5C and 4C-Seq) have allowed researchers to interrogate pairwise chromatin interactions on a wider scale, shedding light on the three-dimensional organization of chromosomes. These methods present significant technical and bioinformatic challenges to consider at the start of the project. Here, we describe two alternative methods for Hi-C, depending on the size of the genome, and discuss the major computational approaches to convert the raw sequencing data into meaningful models of how genomes are organized | ||
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