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. Author manuscript; available in PMC: 2020 May 1.
Published in final edited form as: Hear Res. 2019 Jan 12;376:69–85. doi: 10.1016/j.heares.2019.01.007

Table 3:

Methods for Investigating Chromatin Structure

Approach Utility Caveats Examples from Inner Ear or Related Tissues
ATAC-seq Provides genome-level data revealing the probabilities of finding any given region in an open or closed state across a cell population. 1. Can be costly
2. May require additional bioinformatics and next generation sequencing expertise.		 Galvez et al., 2017
DNase-seq Provides genome-level data revealing the probabilities of finding any given region in an open or closed state across a cell population. 1. Can be technically challenging as it requires determination of optimal DNase concentration and duration of treatment which is variable across sample types.
2. May require pooling of samples to achieve the required numbers of cells.
3. Can be costly
4. May require additional bioinformatics and next generation sequencing expertise.		 N/A
Chromatin capture techniques (3C, 4C, 5C, Hi-C) Provides structural information about chromatin from cells or tissues of interest. Is particularly useful for discovery of distal promoters and enhancers.
Can provide indirect information about the level to which DNA is condensed or open.		 1. Can be costly
2. May require additional expertise, including bioinformatic assistance to map ligated sequences to two or more disparate locations in the genome.
3. ATAC-seq and DNase-seq provide more direct measures of chromatin accessibility.		 N/A
ChIA-PET, Hi-ChIP Highly useful for investigating the role of specific DNA interacting proteins and their effects on chromatin structure. 1. Can be costly
2. May require additional expertise, including bioinformatic assistance to map ligated sequences to two or more disparate locations in the genome.
3. May require pooling of cells as the ChIP step reduces the amount of input material obtained per cell.		 N/A

NOTE for Table 3: All of the techniques listed above are ideally performed with sorted or homogeneous populations of cells or isolated single cells. Cellular heterogeneity can introduce a large degree of noise into the data resulting in incorrect estimations of the frequencies of chromatin interactions or the degree to which DNA in certain regions is accessible in a given cell type.