Massively multiplex single-cell Hi-C
By V. Ramani, Xinxian Deng, R. Qiu, Kevin L. Gunderson, Frank Steemers, C. Disteche, William Stafford Noble, Z. Duan, Jay Shendure. Nature Methods, 2016
530 citations recorded by the source corpus.
We present single-cell combinatorial indexed Hi-C (sciHi-C), a method that applies combinatorial cellular indexing to chromosome conformation capture. In this proof of concept, we generate and sequence six sciHi-C libraries comprising a total of 10,696 single cells. We use sciHi-C data to separate cells by karyotypic and cell-cycle state differences and identify cell-to-cell heterogeneity in mammalian chromosomal conformation. Our results demonstrate that combinatorial indexing is a generalizable strategy for single-cell genomics.
Subfields: Cancer Research, Molecular Biology
View Paper: https://www.semanticscholar.org/paper/b73ce24d28a1c5eb7ca36054a5d226fb2a0ca09c
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In Molecular Biology
Citations in the corpus
- Gene regulatory network inference in the era of single-cell multi-omics (2023, methodology): “Chromosome conformation capture techniques such as Hi-C 127–129 allow to measure the probability of contact between genomic regions and to identify topologically associating domains .”
- Integrative single-cell analysis of transcriptional and epigenetic states in the human adult brain (2017, unknown): “…of single cells in complex tissues at a massive scale: as long as the data from individual cells are informative enough for clustering and “virtual sorting” into different groups 54, 55 , they can be combined into aggregate profiles that are as rich as bulk sequencing of different cell populations.”
- Higher-order inter-chromosomal hubs shape 3D genome organization in the nucleus (2018, unknown): “In addition, SPRITE can be extended to generate global single-cell maps by split-pool tagging of all molecules within individual cells (Ramani et al., 2017).”
- The Human Cell Atlas (2017, unknown): “…(Buenrostro et al., 2015; Cusanovich et al., 2015)), or likewise characterize DNA methylation patterns (single-cell DNAme-Seq (Farlik et al., 2015; Guo et al., 2013; Mooijman et al., 2016; Smallwood et al., 2014)) or 3D organization (single-cell Hi-C (Nagano et al., 2013; Ramani et al., 2017)).”
- Cell-cycle dynamics of chromosomal organisation at single-cell resolution (2016, unknown): “This was initially demonstrated by correlating Hoechst/Geminin FACS indices to the inferred phasing rank of 342 single-cell Hi-C profiles (Fig.”
- A Single-Cell Atlas of In Vivo Mammalian Chromatin Accessibility. (2018, unknown): “, 2017), genome conformation (Ramani et al., 2017), DNA sequence (Vitak et al.”
- Reversed graph embedding resolves complex single-cell trajectories (2017, unknown): “Testing whether Gfi1−/− or Irf8−/− had fully adopted the monocyte and granulocyte expression programs, revealed that Gfi1−/− cells on the branch to F M express higher levels of genes from normally associated with granulocytes than wild-type monocytes (Supplementary Figure 19, Methods ).”