Nature Communications · 2020 · 242 citations · 71 references
Life SciencesCell BiologyMolecular BiologyCell SignalingSingle-cell BioinformaticsTranscriptomicsLineage ReconstructionLineage TracingLung DevelopmentSingle-cell GenomicsSingle-cell Rna Sequencing AnalysisSingle-cell TranscriptomicsAirway Epithelial DifferentiationEpithelial Lineage SpecificationLung DiseasesRespiratory Lineage SpecificationSingle-cell Rna SequencingSingle-cell Rna Sequencing Cell Type AnnotationSmoking-related Lung DiseaseTobacco Smoking
Cigarette smoke first interacts with the lung through the cellularly diverse airway epithelium and goes on to drive development of most chronic lung diseases. Here, through single cell RNA-sequencing analysis of the tracheal epithelium from smokers and non-smokers, we generate a comprehensive atlas of epithelial cell types and states, connect these into lineages, and define cell-specific responses to smoking. Our analysis infers multi-state lineages that develop into surface mucus secretory and ciliated cells and then contrasts these to the unique specification of submucosal gland (SMG) cells. Accompanying knockout studies reveal that tuft-like cells are the likely progenitor of both pulmonary neuroendocrine cells and CFTR-rich ionocytes. Our smoking analysis finds that all cell types, including protected stem and SMG populations, are affected by smoking through both pan-epithelial smoking response networks and hundreds of cell-specific response genes, redefining the penetrance and cellular specificity of smoking effects on the human airway epithelium.
71
Cutadapt removes adapter sequences from high-throughput sequencing reads
Marcel Martin · EMBnet journal · 2011 · 35.8K citations · Full text
HTSeq—a Python framework to work with high-throughput sequencing data
Simon Anders, Paul Theodor Pyl, Wolfgang Huber · Bioinformatics · 2014 · 22.7K citations · Full text
Comprehensive Integration of Single-Cell Data
Tim Stuart, Andrew Butler, Paul Hoffman et al. · Cell · 2019 · 16.9K citations · Full text