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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. Chronic lung diseases are characterized by molecular and cellular composition changes. Here the authors use single-cell RNA sequencing to map cell type-specific changes in human tracheal epithelium related to smoking, and to provide evidence for a tuft-like progenitor for pulmonary neuroendocrine cells and ionocytes.

Background Albuterol is the first-line asthma medication used in diverse populations. Although DNA methylation (DNAm) is an epigenetic mechanism involved in asthma and bronchodilator drug response (BDR), no study has assessed whether albuterol could induce changes in the airway epithelial methylome. We aimed to characterize albuterol-induced DNAm changes in airway epithelial cells, and assess potential functional consequences and the influence of genetic variation and asthma-related clinical variables. Results We followed a discovery and validation study design to characterize albuterol-induced DNAm changes in paired airway epithelial cultures stimulated in vitro with albuterol. In the discovery phase, an epigenome-wide association study using paired nasal epithelial cultures from Puerto Rican children ( n  = 97) identified 22 CpGs genome-wide associated with repeated-use albuterol treatment ( p  < 9 × 10 –8 ). Albuterol predominantly induced a hypomethylation effect on CpGs captured by the EPIC array across the genome (probability of hypomethylation: 76%, p value = 3.3 × 10 –5 ). DNAm changes on the CpGs cg23032799 ( CREB3L1 ), cg00483640 ( MYLK4-LINC01600 ), and cg05673431 ( KSR1 ) were validated in nasal epithelia from 10 independent donors (false discovery rate [FDR] < 0.05). The effect on the CpG cg23032799 ( CREB3L1 ) was cross-tissue validated in bronchial epithelial cells at nominal level ( p  = 0.030). DNAm changes in these three CpGs were shown to be influenced by three independent genetic variants (FDR < 0.05). In silico analyses showed these polymorphisms regulated gene expression of nearby genes in lungs and/or fibroblasts including KSR1 and LINC01600 (6.30 × 10 –14  ≤  p  ≤ 6.60 × 10 –5 ). Additionally, hypomethylation at the CpGs cg10290200 ( FLNC ) and cg05673431 (KSR1 ) was associated with increased gene expression of the genes where they are located (FDR < 0.05). Furthermore, while the epigenetic effect of albuterol was independent of the asthma status, severity, and use of medication, BDR was nominally associated with the effect on the CpG cg23032799 ( CREB3L1) ( p  = 0.004). Gene-set enrichment analyses revealed that epigenomic modifications of albuterol could participate in asthma-relevant processes (e.g., IL-2, TNF-α, and NF-κB signaling pathways). Finally, nine differentially methylated regions were associated with albuterol treatment, including CREB3L1 , MYLK4 , and KSR1 (adjusted p value < 0.05). Conclusions This study revealed evidence of epigenetic modifications induced by albuterol in the mucociliary airway epithelium. The epigenomic response induced by albuterol might have potential clinical implications by affecting biological pathways relevant to asthma.

Coronavirus disease 2019 (COVID-19) is caused by SARS-CoV-2, an emerging virus that utilizes host proteins ACE2 and TMPRSS2 as entry factors. Understanding the factors affecting the pattern and levels of expression of these genes is important for deeper understanding of SARS-CoV-2 tropism and pathogenesis. Here we explore the role of genetics and co-expression networks in regulating these genes in the airway, through the analysis of nasal airway transcriptome data from 695 children. We identify expression quantitative trait loci for both ACE2 and TMPRSS2 , that vary in frequency across world populations. We find TMPRSS2 is part of a mucus secretory network, highly upregulated by type 2 (T2) inflammation through the action of interleukin-13, and that the interferon response to respiratory viruses highly upregulates ACE2 expression. IL-13 and virus infection mediated effects on ACE2 expression were also observed at the protein level in the airway epithelium. Finally, we define airway responses to common coronavirus infections in children, finding that these infections generate host responses similar to other viral species, including upregulation of IL6 and ACE2 . Our results reveal possible mechanisms influencing SARS-CoV-2 infectivity and COVID-19 clinical outcomes. ACE2 and TMPRSS2 have received recent attention as entry factors for SARS-CoV-2. Here the authors analyze nasal airway transcriptome data from 695 children determining ACE2 and TMPRSS2 expression is induced by viral and type2 inflammation, respectively, and both exhibit eQTLs that vary across world populations.

The human genome contains numerous structurally-variable polymorphic loci, including several hundred disease-associated genes, almost inaccessible for accurate variant calling. Here we present Locityper, a tool capable of genotyping such challenging genes using short and long-read whole genome sequencing. For each target, Locityper recruits and aligns reads to locus haplotypes, for instance extracted from a pangenome, and finds the likeliest haplotype pair by optimizing read alignment, insert size and read depth profiles. Locityper accurately genotypes up to 194 of 256 challenging medically relevant loci (95% haplotypes at QV33), an 8.8-fold gain compared to 22 genes achieved with standard variant calling pipelines. Furthermore, Locityper provides access to hyperpolymorphic HLA genes and other gene families, including KIR, MUC and FCGR. With its low running time of 1h10m per sample at 8 threads, Locityper is scalable to biobank-sized cohorts, enabling association studies for previously intractable disease-relevant genes.

The secreted mucins MUC5AC and MUC5B play critical defensive roles in airway pathogen entrapment and mucociliary clearance by encoding large glycoproteins with variable number tandem repeats (VNTRs). These polymorphic and degenerate protein coding VNTRs make the loci difficult to investigate with short reads. We characterize the structural diversity of and by long-read sequencing and assembly of 206 human and 20 nonhuman primate (NHP) haplotypes. We find that human is largely invariant (5761-5762aa); however, seven haplotypes have expanded VNTRs (6291-7019aa). In contrast, 30 allelic variants of encode 16 distinct proteins (5249-6325aa) with cysteine-rich domain and VNTR copy number variation. We grouped alleles into three phylogenetic clades: H1 (46%, ~5654aa), H2 (33%, ~5742aa), and H3 (7%, ~6325aa). The two most common human variants are smaller than NHP gene models, suggesting a reduction in protein length during recent human evolution. Linkage disequilibrium (LD) and Tajima's D analyses reveal that East Asians carry exceptionally large LD blocks with an excess of rare variation (p<0.05). To validate this result, we used Locityper for genotyping haplogroups in 2,600 unrelated samples from the 1000 Genomes Project. We observed signatures of positive selection in H1 and H2 among East Asians and a depletion of the likely ancestral haplogroup (H3). In Africans and Europeans, H3 alleles show an excess of common variation and deviate from Hardy-Weinberg equilibrium, consistent with heterozygote advantage and balancing selection. This study provides a generalizable strategy to characterize complex protein coding VNTRs for improved disease associations.

Coronavirus disease 2019 (COVID-19) outcomes vary from asymptomatic infection to death. This disparity may reflect different airway levels of the SARS-CoV-2 receptor, ACE2, and the spike protein activator, TMPRSS2. Here we explore the role of genetics and co-expression networks in regulating these genes in the airway, through the analysis of nasal airway transcriptome data from 695 children. We identify expression quantitative trait loci (eQTL) for both and , that vary in frequency across world populations. Importantly, we find is part of a mucus secretory network, highly upregulated by T2 inflammation through the action of interleukin-13, and that interferon response to respiratory viruses highly upregulates expression. Finally, we define airway responses to coronavirus infections in children, finding that these infections upregulate while also stimulating a more pronounced cytotoxic immune response relative to other respiratory viruses. Our results reveal mechanisms likely influencing SARS-CoV-2 infectivity and COVID-19 clinical outcomes.

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 nonsmokers, we generated a comprehensive atlas of epithelial cell types and states, connected these into lineages, and defined cell-specific responses to smoking. Our analysis inferred multi-state lineages that develop into surface mucus secretory and ciliated cells and contrasted these to the unique lineage and specialization of submucosal gland (SMG) cells. Our analysis also suggests a lineage relationship between tuft, pulmonary neuroendocrine, and the newly discovered CFTR-rich ionocyte cells. Our smoking analysis found 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 type-specific response genes, redefining the penetrance and cellular specificity of smoking effects on the human airway epithelium.