Biology subjects

Gaffney, D. J.

Publications and source records attributed to Gaffney, D. J..

4 recordsLinked to original sources

bioRxiv2018

Cardelino: Integrating whole exomes and single-cell transcriptomes to reveal phenotypic impact of somatic variants

Decoding the clonal substructures of somatic tissues sheds light on cell growth, development and differentiation in health, ageing and disease. DNA-sequencing, either using bulk or using single-cell assays, has enabled the reconstruction of clonal trees from frequency and co-occurrence patterns of somatic variants. However, approaches to systematically characterize phenotypic and functional variations between individual clones are not established. Here we present cardelino (https://github.com/PMBio/cardelino), a computational method for inferring the clone of origin of individual cells that have been assayed using single-cell RNA-seq (scRNA-seq). After validating our model using simulations, we apply cardelino to matched scRNA-seq and exome sequencing data from 32 human dermal fibroblast lines, identifying hundreds of differentially expressed genes between cells from different somatic clones. These genes are frequently enriched for cell cycle and proliferation pathways, indicating a key role for cell division genes in non-neutral somatic evolution.\n\nKey findingsO_LIA novel approach for integrating DNA-seq and single-cell RNA-seq data to reconstruct clonal substructure for single-cell transcriptomes.\nC_LIO_LIEvidence for non-neutral evolution of clonal populations in human fibroblasts.\nC_LIO_LIProliferation and cell cycle pathways are commonly distorted in mutated clonal populations.\nC_LI

genomics↗

bioRxiv2018

Genetic effects on promoter usage are highly context-specific and contribute to complex traits

Genetic variants regulating RNA splicing and transcript usage have been implicated in both common and rare diseases. Although transcript usage quantitative trait loci (tuQTLs) have now been mapped in multiple cell types and conditions, the molecular mechanisms through which these variants exert their effect have remained elusive. Specifically, changes in transcript usage could arise from promoter choice, alternative splicing or 3' end choice, but current tuQTL studies have not been able to distinguish between them. Here, we performed comprehensive analysis of RNA-seq data from human macrophages exposed to a range of inflammatory stimuli (IFN{gamma}, Salmonella, IFN{gamma} + Salmonella) and a metabolic stimulus (acetylated LDL), obtained from up to 84 individuals. In addition to conventional gene-level and transcript-level analyses, we also developed an analytical approach to directly quantify promoter, internal exon and 3' end usage. We found that although naive transcript-level analysis often links single genetic variants to multiple coupled changes on the transcriptome, this appears to be an artefact of incomplete transcript annotations. Most of this coupling disappears when promoters, splicing and 3' end usage are quantified directly. Furthermore, promoter, splicing and 3' end QTLs are each enriched in distinct genomic features, suggesting that they are predominantly controlled by independent regulatory mechanisms. We also find that promoter usage QTLs are 50% more likely to be context-specific than canonical splicing QTLs and constitute 25% of the transcript-level colocalisations with complex traits. Thus, promoter usage might be a previously underappreciated molecular mechanism mediating complex trait associations in a context-specific manner.

genomics↗

bioRxiv2017

Genetic effects on chromatin accessibility foreshadow gene expression changes in macrophage immune response

Noncoding regulatory variants play an important role in the genetics of complex traits. Although quantitative trait locus (QTL) mapping is a powerful approach to identify these variants, many genetic effects may remain unobserved when cells are sampled in only one of a large number of possible environments. Using a novel induced pluripotent stem cell-derived system, we mapped QTLs regulating chromatin accessibility and gene expression in macrophages in four conditions mimicking the interplay between interferon-gamma response and Salmonella infection. We found that approximately 50% of condition-specific effects on gene expression altered chromatin accessibility prior to stimulation. Furthermore, 6% of the chromatin accessibility QTLs regulated multiple neighbouring regions and these interactions were modulated by stimulation, occasionally producing condition-specific changes in gene expression. Profiling additional states also doubled the number of expression QTLs that could be confidently colocalised with disease associations. Thus, a substantial fraction of disease-associated variants may affect primed regulatory elements in naive cells.

genomics↗

bioRxiv2017

Molecular and functional variation in iPSC-derived sensory neurons

Induced pluripotent stem cells (iPSCs), and cells derived from them, have become key tools to model biological processes and disease mechanisms, particularly in cell types such as neurons that are difficult to access from living donors. Here, we present the first map of regulatory variants in an iPSC-derived cell type. To investigate genetic contributions to human sensory function, we performed 123 differentiations of iPSCs from 103 unique donors to a sensory neuronal fate, and measured gene expression, chromatin accessibility, and neuronal excitability. Compared with primary dorsal root ganglion, where sensory nerves collect near the spinal cord, gene expression was more variable across iPSC-derived neuronal cultures, particularly in genes related to differentiation and nervous system development. Single cell RNA-sequencing revealed that although the majority of cells are neuronal and express the expected marker genes, a substantial fraction have a fibroblast-like expression profile. By applying an allele-specific method we identify 3,778 quantitative trait loci influencing gene expression, 6,318 for chromatin accessibility, and 2,097 for RNA splicing at FDR 10%. A number of these overlap with common disease associations, and suggest candidate causal variants and target genes. These include known causal variants at SNCA for Parkinsons disease and TNFRSF1A for multiple sclerosis, as well as new candidates for migraine, Parkinsons disease, and schizophrenia.

genomics↗