title: Fine-mapping cellular QTLs with RASQUAL and ATAC-seq.
abstract: When cellular traits are measured using high-throughput DNA sequencing, quantitative trait loci (QTLs) manifest as fragment count differences between individuals and allelic differences within individuals. We present RASQUAL (Robust Allele-Specific Quantitation and Quality Control), a new statistical approach for association mapping that models genetic effects and accounts for biases in sequencing data using a single, probabilistic framework. RASQUAL substantially improves fine-mapping accuracy and sensitivity relative to existing methods in RNA-seq, DNase-seq and ChIP-seq data. We illustrate how RASQUAL can be used to maximize association detection by generating the first map of chromatin accessibility QTLs (caQTLs) in a European population using ATAC-seq. Despite a modest sample size, we identified 2,707 independent caQTLs (at a false discovery rate of 10%) and demonstrated how RASQUAL and ATAC-seq can provide powerful information for fine-mapping gene-regulatory variants and for linking distal regulatory elements with gene promoters. Our results highlight how combining between-individual and allele-specific genetic signals improves the functional interpretation of noncoding variation.
authors.affiliation: Wellcome Trust Sanger Institute, Wellcome Genome Campus, Cambridge, UK.
authors.forename: Natsuhiko
authors.initials: N
authors.lastname: Kumasaka
authors.affiliation: Wellcome Trust Sanger Institute, Wellcome Genome Campus, Cambridge, UK.
authors.forename: Andrew J
authors.initials: AJ
authors.lastname: Knights
authors.affiliation: Wellcome Trust Sanger Institute, Wellcome Genome Campus, Cambridge, UK.
authors.forename: Daniel J
authors.initials: DJ
authors.lastname: Gaffney
mesh_terms: D005828:Genetics, Population; D018392:Genomic Imprinting; D005838:Genotype; D059014:High-Throughput Nucleotide Sequencing; D006801:Humans; D020641:Polymorphism, Single Nucleotide; D040641:Quantitative Trait Loci; D044465:White People / Q000235:genetics