A probabilistic framework for cellular lineage reconstruction using integrated single-cell 5-hydroxymethylcytosine and genomic DNA sequencing
Autor: | Nicolas C. Rivron, Chatarin Wangsanuwat, Siddharth S. Dey, Alex Chialastri, Javier F. Aldeguer |
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Rok vydání: | 2021 |
Předmět: |
Cultural Studies
History Lineage (genetic) Literature and Literary Theory Cell division Science integrated single-cell genomic DNA and 5-hydroxymethylcytosine sequencing Computational biology QD415-436 Biology preimplantation mouse embryogenesis Immortal DNA strand hypothesis Biochemistry Article chemistry.chemical_compound individual-cell-division resolution lineage reconstruction Copy-number variation 5-hydroxymethylcytosine Sequence (medicine) 5-Hydroxymethylcytosine Tree (graph theory) immortal strand hypothesis genomic DNA chemistry TP248.13-248.65 Biotechnology |
Zdroj: | Cell reports methods Cell Reports: Methods, Vol 1, Iss 4, Pp 100060-(2021) |
ISSN: | 2667-2375 |
Popis: | SUMMARY Lineage reconstruction is central to understanding tissue development and maintenance. To overcome the limitations of current techniques that typically reconstruct clonal trees using genetically encoded reporters, we report scPECLR, a probabilistic algorithm to endogenously infer lineage trees at a single-cell-division resolution by using 5-hydroxymethylcytosine (5hmC). When applied to 8-cell pre-implantation mouse embryos, scPECLR predicts the full lineage tree with greater than 95% accuracy. In addition, we developed scH&G-seq to sequence both 5hmC and genomic DNA from the same cell. Given that genomic DNA sequencing yields information on both copy number variations and single-nucleotide polymorphisms, when combined with scPECLR it enables more accurate lineage reconstruction of larger trees. Finally, we show that scPECLR can also be used to map chromosome strand segregation patterns during cell division, thereby providing a strategy to test the “immortal strand” hypothesis. Thus, scPECLR provides a generalized method to endogenously reconstruct lineage trees at an individual-cell-division resolution. In brief Wangsanuwat et al. develop a probabilistic algorithm to reconstruct cellular lineages at an individual-cell-division resolution by using strand-specific 5hmC measurements in single cells, and combine it with the development of a single-cell multi-omics technology to quantify 5hmC and genomic DNA from the same cell to reconstruct larger lineage trees. Graphical Abstract |
Databáze: | OpenAIRE |
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