Scalable genotyping in fixed transcriptomes resolves clonal heterogeneity via single-cell sequencing

Single-cell transcriptomics has revolutionized our understanding of heterogeneous cell populations. However, technical limitations of widely-used platforms have limited our ability to link transcriptional states to somatic mutations within the same cells at scale. Here, we introduce Genotyping in Fixed Transcriptomes (GIFT), a novel assay for simultaneous detection of hundreds of targeted genetic variants and whole transcriptome profiles in single cells. The core innovation of GIFT is a rationally designed gapfilling reaction between adjacent single-stranded DNA (ssDNA) probes that barcodes native transcript sequence to enable highly-specific targeted mutation detection. GIFT achieves >99% genotyping accuracy and flexible capture of hundreds of mutations per cell, including in FFPE (Formalin-Fixed Paraffin-Embedded) tissue, enabling clonal lineage tracing in heterogeneous settings. We demonstrate the unique scalability of GIFT by profiling >700,000 cells from 35 donors with myeloproliferative neoplasms (MPN), revealing mutation-dependent hematopoietic responses to systemic inflammation associated with the characteristic JAK2V617 mutation, including an allelic dose gradient of interferon-associated transcriptional programs and transcriptional priming of hematopoietic stem cells that develop into divergent disease states. Together, the unique technical advantages of GIFT enable direct resolution of genotype-to-phenotype relationships via clonal lineage tracing with comprehensive cell state measurements at single-cell resolution.

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Publication Details

Journal
bioRxiv (Cold Spring Harbor Laboratory)
Published
2026-04-12
DOI
https://doi.org/10.64898/2026.04.11.717967
Primary Topic
Single-cell and spatial transcriptomics
Type
article
Field-Weighted Citation Impact
0.00

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Scalable genotyping in fixed transcriptomes resolves clonal heterogeneity via single-cell sequencing

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Scalable genotyping in fixed transcriptomes resolves clonal heterogeneity via single-cell sequencing

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article en

Abstract

Single-cell transcriptomics has revolutionized our understanding of heterogeneous cell populations. However, technical limitations of widely-used platforms have limited our ability to link transcriptional states to somatic mutations within the same cells at scale. Here, we introduce Genotyping in Fixed Transcriptomes (GIFT), a novel assay for simultaneous detection of hundreds of targeted genetic variants and whole transcriptome profiles in single cells. The core innovation of GIFT is a rationally designed gapfilling reaction between adjacent single-stranded DNA (ssDNA) probes that barcodes native transcript sequence to enable highly-specific targeted mutation detection. GIFT achieves >99% genotyping accuracy and flexible capture of hundreds of mutations per cell, including in FFPE (Formalin-Fixed Paraffin-Embedded) tissue, enabling clonal lineage tracing in heterogeneous settings. We demonstrate the unique scalability of GIFT by profiling >700,000 cells from 35 donors with myeloproliferative neoplasms (MPN), revealing mutation-dependent hematopoietic responses to systemic inflammation associated with the characteristic JAK2V617 mutation, including an allelic dose gradient of interferon-associated transcriptional programs and transcriptional priming of hematopoietic stem cells that develop into divergent disease states. Together, the unique technical advantages of GIFT enable direct resolution of genotype-to-phenotype relationships via clonal lineage tracing with comprehensive cell state measurements at single-cell resolution.

bioRxiv (Cold Spring Harbor Laboratory)
Kettering University (US), 10X Genomics (United States) (US), Hôpital Saint-Louis (FR), Stanford University (US)
Howard Hughes Medical Institute, Damon Runyon Cancer Research Foundation, Memorial Sloan-Kettering Cancer Center, Ligue Contre le Cancer, National Institutes of Health
Industry, innovation and infrastructure
Openalex Percentile: Top 29%
Single-cell and spatial transcriptomics
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