Expression profiling by high throughput sequencing Other
Summary
Cellular barcoding using heritable synthetic barcodes coupled to high throughput sequencing is a powerful technique for the accurate tracing of clonal lineages in a wide variety of biological contexts. Recent studies have integrated cellular barcoding with a single-cell transcriptomics readout, extending the capabilities of these lineage tracing methods to the single-cell level. However there remains a lack of scalable and standardised open-source tools to pre-process and visualise both bulk and single-cell level cellular barcoding datasets. Here, we describe bartools, an open-source R-based toolkit that streamlines the pre-processing, analysis and visualisation of synthetic cellular barcoding datasets. In addition, we developed BARtab, a portable and scalable Nextflow pipeline that automates upstream barcode extraction, quality control, filtering and enumeration from high throughput sequencing data. In addition to population-level cellular barcoding datasets, BARtab and bartools contain methods for the extraction, annotation, and visualisation of transcribed barcodes from single-cell RNA-seq and spatial transcriptomics experiments, thus extending the analytical toolbox to also support novel expressed cellular barcoding methodologies. We showcase the integrated BARtab and bartools workflow through the analysis of bulk, single-cell, and spatial transcriptomics cellular barcoding datasets.
Overall design
We generated three independent cellular barcoding datasets using the SPLINTR lineage tracing system comprising population-level DNA barcoding or expressed cellular barcoding approaches using single-cell RNA and spatial transcriptomics platforms. For the population-level DNA barcoding dataset, Mouse MLL-AF9 fusion oncogene containing AML cells were barcoded with SPLINTR and cultured in vitro with increasing doses of IBET-151, Cytarabine or DMSO. At each dose escalation, cells were sampled for bulk barcode sequencing. The dose escalation dataset comprises bulk barcode-seq data per timepoint. For the single-cell dataset, SPLINTR barcoded MLL-AF9 AML cells were cultured in vitro and sequenced using the 10X Genomics 3’ single-cell RNA-seq platform. For the spatial dataset, SPLINTR barcoded MLL-AF9 AML cells were transplanted into a recipient C57BL6 mouse and BGI Stereo-seq spatial transcriptomics was performed on spleen cross sections isolated at the time of fulminant disease.
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