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Ratjen, F.

Publications and source records attributed to Ratjen, F..

6 recordsLinked to original sources

Beyond reference bias: Making pangenomes accessible with PangyPlot

Linear reference genomes have standardized genomics research but remain limited by reference bias, which skews read mapping and variant discovery. This bias can distort the interpretation of genetic variation, particularly for populations that are genetically distant from the reference. Pangenome graphs, such as those generated by the Human Pangenome Reference Consortium (HPRC), mitigate this limitation by integrating diverse haplotypes into a unified representation of human genetic variation. However, the complexity of graph-based data and the lack of intuitive visualization tools have hindered broader adoption. Here we introduce PangyPlot, a genome browser that simplifies exploration of pangenome graphs by retaining linear-style navigation, integrating gene annotations, abstracting complex variation into interpretable structures, and employing a dynamic, physics-based layout optimization engine. We demonstrate its utility by constructing a chromosome 7 graph from 101 individuals with cystic fibrosis (CF), capturing a broad spectrum of genetic variation. Using PangyPlot, we visualized CF-relevant loci and compared results with existing graph viewers, highlighting its ability to display both base-level and large structural variation. With an additional 64 PacBio HiFi assemblies, we fine-mapped a repeat-dense CF modifier locus on chromosome 5, where PangyPlot was used in conjunction with graph-based analysis to identify a repeat expansion in the 5' end of EXOC3 that may promote G-quadruplex formation and affect gene expression. Together, these examples demonstrate PangyPlot s capacity to make populationlevel variation interpretable. To support broader use of graph-based resources, we also released a live public instance of PangyPlot preloaded with HPRC data (https://pangyplot.research.sickkids.ca/).

genomics↗

GWAS SVatalog: a visualization tool to aid fine-mapping of GWAS loci with structural variations

BackgroundGenome-wide association studies (GWAS) have been successful in identifying single nucleotide polymorphisms (SNPs) associated with phenotypic traits. However, SNPs form an incomplete set of variation across the genome and since a large percentage of GWAS-significant SNPs lie in non-coding regions, their impact on a given trait is difficult to decipher. Recognizing whether these SNPs are tagging other polymorphisms, like structural variations (SV), is an important step towards understanding the putative causal variation at GWAS loci. ResultsHere, we develop GWAS SVatalog (https://svatalog.research.sickkids.ca/), a novel open-source web tool that computes and visualizes linkage disequilibrium (LD) between SVs and GWAS-associated SNPs throughout the human genome. The tool combines GWAS Catalogs SNP-trait association data across 14,479 phenotypes with LD statistics calculated between 35,732 SVs and 116,870 SNPs identified in 101 whole-genome long-read sequences. We use GWAS SVatalog to identify SVs that may explain GWAS loci for iron levels, refractive error, and Alzheimers disease, where previously SNPs were unable to provide a causal explanation. ConclusionsGWAS SVatalog advances the fine-mapping of GWAS loci with structural variations, enabling researchers to associate 35,732 common SVs with 14,479 phenotypes, accelerating the understanding of disease etiology.

bioinformatics↗

Single-cell RNA-Sequencing Co-Expression Analysis with CFTR in Lung Tissue

1BackgroundWhile cystic fibrosis is caused by loss-of-function variants in the Cystic Fibrosis Transmembrane Conductance Regulator (CFTR), other modifier genes have been shown to associate with disease severity. Co-expression of modifiers with CFTR in normal tissue indicates a cooperative relationship and suggests the potential for compensation in the presence of CFTR dysfunction. We examined the co-expression relationships with CFTR in the lung using single cell RNA sequencing to pinpoint cell types and their modifiers involved in the forced expiratory volume in 1 second (FEV1)-based cystic fibrosis lung phenotype and support target cell-type prioritization for therapy 1. MethodsSmartSeq2 single cell RNA sequencing data from non-cystic fibrosis lung tissue was used for evaluation of co-expression with CFTR and modifier genes. Zero-inflated negative binomial model was used to formally test the co-expression association. 10X Chromium based single cell RNA sequencing data from both cystic fibrosis and non-cystic fibrosis studies were assessed graphically to confirm conclusions from the SmartSeq2 primary analysis. ResultsDifferentiating basal, club and alveolar epithelial type 2 cells were found to have high proportions of cells expressing CFTR as well as the greatest number of significant co-expression relationships with the modifiers. In particular, among alveolar epithelial type 2 cells, we observed a strong co-expression trio relationship between CFTR, SLC6A14 and SLC26A9 (p < 0.05). ConclusionsCFTR-modifier gene co-expression suggests basal, club and alveolar epithelial type 2 cells show coordinated expression. Alveolar epithelial type 2 cells showed strong co-expression evidence with two of the most established cystic fibrosis modifier genes.

genetics↗

Early human fetal lung atlas reveals the temporal dynamics of epithelial cell plasticity.

While animal models have provided key insights into conserved mechanisms of how the lung forms during development, human-specific developmental mechanisms are not always captured. To fully appreciate how developmental defects and disease states alter the function of the lungs, studies in human lung models are important. Here, we sequenced >150,000 single single-cells from 19 healthy human fetal lung tissues from gestational weeks 10-19 and identified at least 58 unique cell types/states contributing to the developing lung. We captured novel dynamic developmental trajectories from various progenitor cells that give rise to club, ciliated, and pulmonary neuroendocrine cells. We also identified four CFTR-expressing progenitor cell types and pinpointed the temporal emergence of these cell types. These developmental dynamics reveal broader epithelial cell plasticity and novel lineage hierarchies that were not previously reported. Combined with spatial transcriptomics, we identified both cell autonomous and non-cell autonomous signalling pathways that may dictate the temporal and spatial emergence of cell lineages. Finally, we showed that human pluripotent stem cell-derived fetal lung models capture cell lineage trajectories specifically through CFTR-expressing progenitor cells, that were also observed in the native fetal tissue. Overall, this study provides a comprehensive single-cell atlas of the developing human lung, outlining the temporal and spatial complexities of cell lineage development. HighlightsO_LISingle-cell transcriptomics atlas from 19 human fetal lungs reveals cellular heterogeneity and previously unappreciated cellular plasticity in the epithelial compartment. C_LIO_LIIdentification of novel CFTR-expressing progenitor cells that gives rise to club, ciliated and PNEC. C_LIO_LINovel RNA velocity facilitated the identification of dynamic lineage trajectories in the epithelial compartment. C_LIO_LITemporally regulated cell signaling through promiscuous interactions between sender and receiving cells may dictate cell lineage fates. C_LIO_LIIntegration of human pluripotent stem cell (hPSC)-derived fetal lung cells and organoids with primary lung dataset show hPSC-differentiations captures key developmental trajectories of fetal epithelial cell states. C_LI

developmental biology↗

High Quality Phasing Using Linked-Read Whole Genome Sequencing of Patient Cohorts Informs Genetic Understanding of Complex Traits

Phasing of heterozygous alleles is critical for interpretation of cis-effects of disease-relevant variation. For population studies, phase is often inferred from external data but read-based phasing approaches that span long genomic distances would be more accurate because they enable both genotype and phase to be obtained from a single dataset. To demonstrate how read-based phasing can provide functional insights, we sequenced 477 individuals with Cystic Fibrosis (CF) using linked-read sequencing. We benchmark read-based phasing with different short- and long-read sequencing technologies, prioritize linked-read technology as the most informative and produce a benchmark phase call set from reference sample HG002 for the community. The 477 samples display an average phase block N50 of 4.39 Mb. We use these samples to construct a graph representation of CFTR haplotypes, which facilitates understanding of complex CF alleles. Fine-mapping and phasing of the chr7q35 trypsinogen locus associated with CF meconium ileus demonstrates a 20 kb deletion and a PRSS2 missense variant p.Thr8Ile (rs62473563) independently contribute to meconium ileus risk (p=0.0028, p=0.011, respectively) and are PRSS2 pancreas eQTLs (p=9.5e-7 and p=1.4e-4, respectively), explaining the mechanism by which these polymorphisms contribute to CF. Phase enables access to haplotypes that can be used for genome graph or reference panel construction, identification of cis-effects, and for understanding disease associated loci. The phase information from linked-reads provides a causal explanation for variation at a CF-relevant locus which also has implications for the genetic basis of non-CF pancreatitis to which this locus has been reported to contribute.

genetics↗

A new platform for high-throughput therapy testing on iPSC-derived, immature airway from Cystic Fibrosis Patients

Induced pluripotent, stem cell (iPSC)-derived models of airway tissue have successfully modeled the primary defect in regulated chloride conductance caused by the major Cystic Fibrosis causing mutation, F508del. However, it remains unclear if iPSC-derived airway cultures can be used in high-throughput therapy development for F508del and rarer mutations. There is an urgent need for airway tissue models that reflect the variability of patient-specific responses and are scalable for therapy development. In the current work, we describe a robust, high-throughput fluorescence assay of mutant CFTR function in iPSCs differentiated to immature airway epithelium. This assay measures reproducible functional responses to modulators targeting either the major CF mutant F508del or the nonsense mutant: W1282X-CFTR. We show that the ranking of patient-specific responses to interventions in this stem-cell based model recapitulates the ranking observed in primary nasal epithelial cultures obtained from the same individuals. In summary, these proof-of-concept studies show that this novel platform has the potential to support therapy development and precision medicine for Cystic Fibrosis patients. One Sentence SummaryWe describe a fluorescence-based platform that enables high-throughput Cystic Fibrosis therapy testing using iPSCs differentiated to immature lung.

genomics↗