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34ae3d80-bf9d-4d97-ac8e-9cf7f223c138 - samples

ABSTRACT: Raw reads from single-cell RNA-sequencing of peripheral blood of five TET2 mutation carriers as well as three non-carrier family members. Single-cells were captured into 10x barcoded gel beads and RNA-sequencing library preparation was done using Chromium Single Cell 3' v2 chemistry (10x Genomics, Pleasanton, CA, USA). Sequencing was performed as recommended with 98bp length of read 2 using HiSeq4000 sequencer.

PROVIDER: EGAD00001004778 | EGA |

REPOSITORIES: EGA

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Project description:Purpose: The goal of this study was to use enzyme activity as a proxy for profiling tumor progression and treatment response in an autochthonous mouse model of Alk-mutant non-small-cell lung cancer (NSCLC). The Eml4-Alk model was originally described in Maddalo et al., Nature 2014. Single-cell transcriptomic profiling of the Eml4-Alk NSCLC model was performed for unbiased discovery of the phenotypic landscape of Eml4-Alk and wild type mice. Methods: Single cell suspensions were prepared from excised lungs of Eml4-Alk and sex- and age-matched healthy, wild type C57/Bl6J mice. Suspensions were pooled from n=3 mice per condition, and then were enriched for cell viability and depleted for CD45+ cells. Single cells were processed using the 10X Genomics Single Cell 3’ platform using the Chromium Single Cell 3’ Library & Gel Bead Kit V2 kit (10X Genomics), per manufacturer’s protocol. Approximately 10,000 cells were loaded onto each channel and partitioned into Gel Beads in Emulsion (GEMs) in the 10x Chromium instrument. Following lysis of the captured cells, the released RNA was barcoded through reverse transcription in individual GEMs, and complementary DNA was generated and amplified. Libraries were constructed using a Single Cell 3’ Library and Gel Bead kit. The libraries were sequenced using an Illumina NovaSeq6000 sequencer on an Illumina NovaSeq SP flow cell. Results: Gene expression matrices were generated for each sample by the Cell Ranger (v.3.0.2) Pipeline coupled with mouse reference version GRCm38. The output filtered gene expression matrices were analyzed by Python software (v.3.9.0) with the scanpy package (v.1.7.2). For final analysis, genes expressed in at least three cells in the data and cells with > 200 genes detected were selected for further analyses, and low quality cells were removed based on number of total counts and percentage of mitochondrial genes expressed. Conclusions: This study provides the first (to the best of our knowledge) single-cell RNA-seq dataset of the Eml4-Alk autochthonous model of NSCLC.

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34ae3d80-bf9d-4d97-ac8e-9cf7f223c138 - samples

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