Cell-type-resolved somatic variant discovery from bulk long-read sequencing
Tool / method
Assignment of native long reads to cell types through methylation signatures, enabling cell-type-specific somatic variant calling from bulk tissue.
Summary
Somatic mutations arise throughout life and their consequences depend on the cell population in which they occur: genome-wide studies measure bulk tissue, whereas single-cell approaches resolve cell identity but detect complex alleles poorly. SniffCell uses the DNA methylation carried natively on long reads to assign somatic variant-supporting molecules to methylation-resolvable cell types, from signatures built across eight tissues. On peripheral blood mononuclear cells and brain benchmarks, the tool recovers sorted cell identities and validates its assignments using purified immune, neuronal and oligodendrocyte fractions. In blood, it recovers lineage-restricted antigen receptor rearrangements and localises a somatic tandem-repeat expansion to T cells; in the frontal cortex, it identifies recurrent neuron-specific expansions in genes including FGF14, LRRC7 and SH3RF3. Across three brain cohorts comprising 172 donors, neuron-associated recurrent expansions were enriched for GAA-rich motifs.
Synthesis written by Geno'X. For the full original abstract, please refer to the source publication.
Analysis
The idea is elegant: use the methylation natively carried on the read as a marker of cell identity, and thereby recover cell-type resolution without sorting cells or going single-cell. For brain somatic mosaicism, a diagnostic blind spot where the variants sought are absent from blood, this is a potential way to exploit tissues that have already been sequenced. This is a medRxiv preprint that has not been peer reviewed, and the demonstration rests on research cohorts: nothing indicates diagnostic use at this stage.
Analysis by Dr Thibaut Benquey
Why this score?
Clinical impact: 1/3 · Evidence strength: 2/3 · Novelty: 2/2 · Sample size: 0/1 · Publication status: 0/1 → Total: 5/10
Keywords
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