| Chapter title |
MINCE-Seq: Mapping In Vivo Nascent Chromatin with EdU and Sequencing
|
|---|---|
| Chapter number | 8 |
| Book title |
Histone Variants
|
| Published in |
Methods in molecular biology, August 2018
|
| DOI | 10.1007/978-1-4939-8663-7_8 |
| Pubmed ID | |
| Book ISBNs |
978-1-4939-8662-0, 978-1-4939-8663-7
|
| Authors |
Srinivas Ramachandran, Steven Henikoff |
| Abstract |
The epigenome has been mapped in different cell types to understand the relationship between the chromatin landscape and the control of gene expression. Most mapping studies profile a large population of cells in various stages of the cell cycle, which results in an average snapshot of the chromatin landscape. However, chromatin is highly dynamic, undergoing rapid changes during active processes such as replication, transcription, repair, and remodeling. Hence, we need methods to map chromatin as a function of time. To address this problem in the context of replication, we developed the method MINCE-seq (Mapping In vivo Nascent Chromatin with EdU and sequencing). MINCE-seq is a genome-wide method that uses the passage of replication fork as a starting point to map the chromatin landscape as a function of time. MINCE-seq can measure chromatin dynamics in a time scale of minutes and at the resolution of individual nucleosome positions and transcription factor-binding sites genome-wide. |
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 17% |
| Unknown | 5 | 83% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 6 | 100% |
Mendeley readers
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 10 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Doctoral Student | 2 | 20% |
| Researcher | 2 | 20% |
| Student > Ph. D. Student | 1 | 10% |
| Student > Bachelor | 1 | 10% |
| Unknown | 4 | 40% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 3 | 30% |
| Chemical Engineering | 1 | 10% |
| Computer Science | 1 | 10% |
| Immunology and Microbiology | 1 | 10% |
| Unknown | 4 | 40% |