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Open AccessJournal ArticleDOI

Brain-trait-associated variants impact cell-type-specific gene regulation during neurogenesis.

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TLDR
In this paper, the authors map e/sQTLs and allele-specific expression in cultured cells representing two major developmental stages, primary human neural progenitors and their sorted neuronal progeny, identifying numerous loci not detected in either bulk developing cortical wall or adult cortex.
Abstract
Interpretation of the function of non-coding risk loci for neuropsychiatric disorders and brain-relevant traits via gene expression and alternative splicing quantitative trait locus (e/sQTL) analyses is generally performed in bulk post-mortem adult tissue. However, genetic risk loci are enriched in regulatory elements active during neocortical differentiation, and regulatory effects of risk variants may be masked by heterogeneity in bulk tissue. Here, we map e/sQTLs, and allele-specific expression in cultured cells representing two major developmental stages, primary human neural progenitors (n = 85) and their sorted neuronal progeny (n = 74), identifying numerous loci not detected in either bulk developing cortical wall or adult cortex. Using colocalization and genetic imputation via transcriptome-wide association, we uncover cell-type-specific regulatory mechanisms underlying risk for brain-relevant traits that are active during neocortical differentiation. Specifically, we identified a progenitor-specific eQTL for CENPW co-localized with common variant associations for cortical surface area and educational attainment.

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Posted ContentDOI

Cell-type specific cis-eQTLs in eight brain cell-types identifies novel risk genes for human brain disorders

TL;DR: In this paper, the authors performed an eQTL analysis using single nuclei RNA-seq from 196 individuals in eight central nervous system (CNS) cell types and identified 6108 eGenes, a substantial fraction of which show cell-type specific effects, with strongest effects in microglia.
Journal ArticleDOI

Bridging the splicing gap in human genetics with long-read RNA sequencing: finding the protein isoform drivers of disease.

TL;DR: An overview of s QTL mapping approaches, the use of long-read sequencing to characterize sQTL effects on isoforms, the linkage of RNA isoforms to protein-level functions, and comment on future directions in the field are provided.
Journal ArticleDOI

Accounting for cis-regulatory constraint prioritizes genes likely to affect species-specific traits

TL;DR: In this paper , a simple strategy that leverages population-scale allele-specific RNA-seq data to identify genes that show constrained cis-regulation within species yet show divergence between species was proposed.
Journal ArticleDOI

Natural variation in gene expression and viral susceptibility revealed by neural progenitor cell villages.

TL;DR: In this paper , a "cell village" experimental platform was used to analyze genetic, molecular, and phenotypic heterogeneity across neural progenitor cells from 44 human donors cultured in a shared in vitro environment using algorithms (Dropulation and Census-seq) to assign cells and phenotypes to individual donors.
Journal ArticleDOI

Cellular Genome-wide Association Study Identifies Common Genetic Variation Influencing Lithium-Induced Neural Progenitor Proliferation

TL;DR: In this paper , the authors performed a genome-wide association study to identify common genetic variants that influence lithium-induced neural progenitor cell proliferation and found that common genetic variation was necessary for the full proliferation-stimulating effects of lithium.
References
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Journal ArticleDOI

Controlling the false discovery rate: a practical and powerful approach to multiple testing

TL;DR: In this paper, a different approach to problems of multiple significance testing is presented, which calls for controlling the expected proportion of falsely rejected hypotheses -the false discovery rate, which is equivalent to the FWER when all hypotheses are true but is smaller otherwise.
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Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2

TL;DR: This work presents DESeq2, a method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates, which enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression.
Journal ArticleDOI

Regression Shrinkage and Selection via the Lasso

TL;DR: A new method for estimation in linear models called the lasso, which minimizes the residual sum of squares subject to the sum of the absolute value of the coefficients being less than a constant, is proposed.
Journal ArticleDOI

STAR: ultrafast universal RNA-seq aligner

TL;DR: The Spliced Transcripts Alignment to a Reference (STAR) software based on a previously undescribed RNA-seq alignment algorithm that uses sequential maximum mappable seed search in uncompressed suffix arrays followed by seed clustering and stitching procedure outperforms other aligners by a factor of >50 in mapping speed.
Journal ArticleDOI

limma powers differential expression analyses for RNA-sequencing and microarray studies

TL;DR: The philosophy and design of the limma package is reviewed, summarizing both new and historical features, with an emphasis on recent enhancements and features that have not been previously described.
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