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Panjwani, N.

Publications and source records attributed to Panjwani, N..

3 recordsLinked to original sources

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 flexible summary-based colocalization method with application to the mucin Cystic Fibrosis lung disease modifier locus

Mucus obstruction is a central feature in the Cystic Fibrosis (CF) airways. A genome-wide association study (GWAS) of lung disease by the CF Gene Modifier Consortium (CFGMC) identified a significant locus containing two mucin genes, MUC20 and MUC4. Expression quantitative trait locus (eQTL) analysis using human nasal epithelial (HNE) from 94 CF Canadians in the CFGMC demonstrated MUC4 eQTLs that mirrored the lung association pattern in the region, suggesting that MUC4 expression may mediate CF lung disease. Complications arose, however, with colocalization testing using existing methods: the locus is complex and the associated SNPs span a 0.2Mb region with high linkage disequilibrium and evidence of eQTLs for multiple genes and tissues (heterogeneity). We previously developed the Simple Sum (SS), a powerful colocalization test in regions with heterogeneity, but SS assumed eQTLs to be present to achieve type I error control. Here we propose a two-stage SS (SS2) colocalization test that avoids a prior eQTL assumptions, accounts for multiple hypothesis testing and the composite null hypothesis and enables meta-analysis. We compare SS2 to published approaches through simulation and demonstrate type I error control for all settings with the greatest power in the presence of high LD and heterogeneity. Applying SS2 to the MUC20/MUC4 CF lung disease locus with eQTLs from CF HNE revealed significant colocalization with MUC4 (p = 1.71x10-5) rather than MUC20. The SS2 is a powerful method to inform the responsible gene(s) at a locus and guide future functional studies. SS2 has been implemented in the application LocusFocus (locusfocus.research.sickkids.ca).

genetics↗

LocusFocus: A web-based colocalization tool for the annotation and functional follow-up of GWAS

Genome-wide association studies (GWAS) have primarily identified trait-associated loci in the non-coding genome. Colocalization analyses of SNP-level associations from GWAS with expression quantitative trait loci (eQTL) evidence enable the generation of hypotheses about responsible mechanism, genes and tissues of origin to guide functional characterization. Here, we present a web-based colocalization browsing and testing tool named LocusFocus (https://locusfocus.research.sickkids.ca). LocusFocus formally tests colocalization using our established Simple Sum method to identify the most relevant genes and tissues for a particular GWAS locus in the presence of high linkage disequilibrium and/or allelic heterogeneity. Full documentation and source code for LocusFocus are publicly available.

genomics↗