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Open AccessJournal ArticleDOI

Single-cell RNA sequencing identifies celltype-specific cis-eQTLs and co-expression QTLs.

TLDR
Single-cell RNA sequencing of ~25,000 peripheral blood mononuclear cells from 45 donors identifies new celltype-specific cis-eQTLs and genetic variants that significantly alter co-expression relationships (‘co-expression QTLs’).
Abstract
Genome-wide association studies have identified thousands of genetic variants that are associated with disease 1 . Most of these variants have small effect sizes, but their downstream expression effects, so-called expression quantitative trait loci (eQTLs), are often large 2 and celltype-specific3-5. To identify these celltype-specific eQTLs using an unbiased approach, we used single-cell RNA sequencing to generate expression profiles of ~25,000 peripheral blood mononuclear cells from 45 donors. We identified previously reported cis-eQTLs, but also identified new celltype-specific cis-eQTLs. Finally, we generated personalized co-expression networks and identified genetic variants that significantly alter co-expression relationships (which we termed 'co-expression QTLs'). Single-cell eQTL analysis thus allows for the identification of genetic variants that impact regulatory networks.

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Journal ArticleDOI

Integrative single-cell analysis

TL;DR: Diverse approaches for integrative single-cell analysis are discussed, including experimental methods for profiling multiple omics types from the same cells, analytical approaches for extracting additional layers of information directly from scRNA-seq data and computational integration of omics data collected across different cell samples.
Posted ContentDOI

Unraveling the polygenic architecture of complex traits using blood eQTL metaanalysis

Urmo Võsa, +100 more
- 19 Oct 2018 - 
TL;DR: It is observed that cis-eQTLs can be detected for 88% of the studied genes, but that they have a different genetic architecture compared to disease-associated variants, limiting the ability to use cis- eZTLs to pinpoint causal genes within susceptibility loci.
Journal ArticleDOI

Cell type–specific genetic regulation of gene expression across human tissues

TL;DR: A growing number of in silico cell type deconvolution methods and associated reference panels with cell type–specific marker genes enable the robust estimation of the enrichment of specific cell types from bulk tissue gene expression data.
Journal ArticleDOI

Large eQTL meta-analysis reveals differing patterns between cerebral cortical and cerebellar brain regions.

Solveig K. Sieberts, +100 more
- 12 Oct 2020 - 
TL;DR: A colocalization analysis is applied to identify genes underlying the GWAS association peaks for schizophrenia and identify a potentially novel gene colocalized with lncRNA RP11-677M14.
Journal ArticleDOI

Transcriptional and Cellular Diversity of the Human Heart

TL;DR: Using large-scale single nuclei RNA sequencing, the transcriptional and cellular diversity in the normal human heart was defined and the identification of discrete cell subtypes and differentially expressed genes within the heart will ultimately facilitate the development of new therapeutics for cardiovascular diseases.
References
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Journal Article

Visualizing Data using t-SNE

TL;DR: A new technique called t-SNE that visualizes high-dimensional data by giving each datapoint a location in a two or three-dimensional map, a variation of Stochastic Neighbor Embedding that is much easier to optimize, and produces significantly better visualizations by reducing the tendency to crowd points together in the center of the map.
Journal ArticleDOI

Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls

Paul Burton, +195 more
- 07 Jun 2007 - 
TL;DR: This study has demonstrated that careful use of a shared control group represents a safe and effective approach to GWA analyses of multiple disease phenotypes; generated a genome-wide genotype database for future studies of common diseases in the British population; and shown that, provided individuals with non-European ancestry are excluded, the extent of population stratification in theBritish population is generally modest.
Journal ArticleDOI

The dynamics and regulators of cell fate decisions are revealed by pseudotemporal ordering of single cells

TL;DR: Monocle is described, an unsupervised algorithm that increases the temporal resolution of transcriptome dynamics using single-cell RNA-Seq data collected at multiple time points that revealed switch-like changes in expression of key regulatory factors, sequential waves of gene regulation, and expression of regulators that were not known to act in differentiation.
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