Chapter title |
Detecting long-range chromatin interactions using the chromosome conformation capture sequencing (4C-seq) method.
|
---|---|
Chapter number | 13 |
Book title |
Gene Regulatory Networks
|
Published in |
Methods in molecular biology, January 2012
|
DOI | 10.1007/978-1-61779-292-2_13 |
Pubmed ID | |
Book ISBNs |
978-1-61779-291-5, 978-1-61779-292-2
|
Authors |
Nele Gheldof, Marion Leleu, Daan Noordermeer, Jacques Rougemont, Alexandre Reymond, Gheldof, Nele, Leleu, Marion, Noordermeer, Daan, Rougemont, Jacques, Reymond, Alexandre |
Abstract |
Eukaryotic transcription is tightly regulated by transcriptional regulatory elements, even though these elements may be located far away from their target genes. It is now widely recognized that these regulatory elements can be brought in close proximity through the formation of chromatin loops, and that these loops are crucial for transcriptional regulation of their target genes. The chromosome conformation capture (3C) technique presents a snapshot of long-range interactions, by fixing physically interacting elements with formaldehyde, digestion of the DNA, and ligation to obtain a library of unique ligation products. Recently, several large-scale modifications to the 3C technique have been presented. Here, we describe chromosome conformation capture sequencing (4C-seq), a high-throughput version of the 3C technique that combines the 3C-on-chip (4C) protocol with next-generation Illumina sequencing. The method is presented for use in mammalian cell lines, but can be adapted to use in mammalian tissues and any other eukaryotic genome. |
X Demographics
Geographical breakdown
Country | Count | As % |
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Unknown | 1 | 100% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 1 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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United States | 3 | 3% |
France | 1 | <1% |
United Kingdom | 1 | <1% |
Austria | 1 | <1% |
Denmark | 1 | <1% |
Canada | 1 | <1% |
Unknown | 99 | 93% |
Demographic breakdown
Readers by professional status | Count | As % |
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Student > Ph. D. Student | 31 | 29% |
Researcher | 29 | 27% |
Student > Master | 20 | 19% |
Student > Bachelor | 7 | 7% |
Student > Postgraduate | 3 | 3% |
Other | 8 | 7% |
Unknown | 9 | 8% |
Readers by discipline | Count | As % |
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Biochemistry, Genetics and Molecular Biology | 23 | 21% |
Immunology and Microbiology | 2 | 2% |
Computer Science | 2 | 2% |
Neuroscience | 2 | 2% |
Other | 7 | 7% |
Unknown | 11 | 10% |