Simultaneous single-cell profiling of lineages and cell types in the vertebrate brain
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A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
No Canadian affiliation. An affiliation-only frame — the usual design — would never have seen this work. It is one of the works that make the case for inverting the frame.
Machine scores (provisional)
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
- Teacher spread
- 0.215 · how far apart the two teachers sit on this one work
- Validation status
score_only:v0-immature-baseline· verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it
Abstract
The lineage relationships among the hundreds of cell types generated during development are difficult to reconstruct. A recent method, GESTALT, used CRISPR-Cas9 barcode editing for large-scale lineage tracing, but was restricted to early development and did not identify cell types. Here we present scGESTALT, which combines the lineage recording capabilities of GESTALT with cell-type identification by single-cell RNA sequencing. The method relies on an inducible system that enables barcodes to be edited at multiple time points, capturing lineage information from later stages of development. Sequencing of ∼60,000 transcriptomes from the juvenile zebrafish brain identified >100 cell types and marker genes. Using these data, we generate lineage trees with hundreds of branches that help uncover restrictions at the level of cell types, brain regions, and gene expression cascades during differentiation. scGESTALT can be applied to other multicellular organisms to simultaneously characterize molecular identities and lineage histories of thousands of cells during development and disease.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
The record
- Venue
- Nature Biotechnology
- Topic
- Single-cell and spatial transcriptomics
- Field
- Biochemistry, Genetics and Molecular Biology
- Canadian institutions
- —
- Funders
- National Human Genome Research InstituteNational Institute of General Medical SciencesNational Institute of Mental HealthCanadian Institutes of Health ResearchNational Institutes of HealthEdward Mallinckrodt, Jr. FoundationWellcome TrustNational Heart, Lung, and Blood InstituteLife Sciences Research FoundationEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentHoward Hughes Medical Institute
- Keywords
- BiologyCell typeLineage (genetic)Multicellular organismZebrafishVertebrateComputational biologyGeneCellular differentiationEvolutionary biologyCellGenetics
- Has abstract in OpenAlex
- yes