This is a protocol preprint, a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
Method Article
Jesse R Dixon
Salk Institute for Biological Studies
Corresponding Author
ORCiD: https://orcid.org/0000-0002-6273-2181
Joseph R Ecker
Salk Institute for Biological Studies
Corresponding Author
ORCiD: https://orcid.org/0000-0001-5799-5895
License:
This work is licensed under a CC BY 4.0 License. Read Full License
The ability to profile epigenomic features in single cells is facilitating the study of the variation in transcription regulation at the single cell level. Single cell methods have also facilitated the generation of cell-type resolved transcriptomic and epigenetic profiles of lineages derived from complex heterogeneous samples. However, integrating different epigenetic features remain challenging, as many current methods profile a single data type at at time. Furthermore, some epigenetic features, such as 3D genome organization, are intrinsically variable between single cells of the same lineage, so it remains unclear how well these methods may resolve cell-types from complex mixtures. Here we describe a method for profiling 3D genome organization and DNA methylation in single cells. This protocol accompanies Lee et al. (Nature Methods 2019) after peer review to aid potential users in applying the method to their own samples.
Keywords
Single Cell, 3D genome, DNA methylation, chromatin, epigenetics, genomics
Figure 1
Figure 2
The authors declare no conflicting financial interests.
Loading...
Version History
CURRENT STATUS: Posted
Version 1
Posted 09 Sep, 2019
No community comments so far
Metrics
Comments: 0
HTML Views: ...
Subject Areas
Molecular Biology
Biotechnology
Computational biology and bioinformatics
Genetics
Cell biology
Associated Publications
Method Article
Jesse R Dixon
Salk Institute for Biological Studies
Corresponding Author
ORCiD: https://orcid.org/0000-0002-6273-2181
Joseph R Ecker
Salk Institute for Biological Studies
Corresponding Author
ORCiD: https://orcid.org/0000-0001-5799-5895
Version History
CURRENT STATUS: Posted
Version 1
Posted 09 Sep, 2019
No community comments so far
Metrics
Comments: 0
HTML Views: ...
License:
This work is licensed under a CC BY 4.0 License. Read Full License
The ability to profile epigenomic features in single cells is facilitating the study of the variation in transcription regulation at the single cell level. Single cell methods have also facilitated the generation of cell-type resolved transcriptomic and epigenetic profiles of lineages derived from complex heterogeneous samples. However, integrating different epigenetic features remain challenging, as many current methods profile a single data type at at time. Furthermore, some epigenetic features, such as 3D genome organization, are intrinsically variable between single cells of the same lineage, so it remains unclear how well these methods may resolve cell-types from complex mixtures. Here we describe a method for profiling 3D genome organization and DNA methylation in single cells. This protocol accompanies Lee et al. (Nature Methods 2019) after peer review to aid potential users in applying the method to their own samples.
Figure 1
Figure 2
Loading...