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

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 ¼ 85) and their sorted neuronal progeny (n ¼ 74), identifying numerous loci not detected in either bulk developing cortical wall or adult cortex. Using colocalization and genetic imputation via transcriptomewide 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.

Cellular genome wide association study identifies common genetic variation influencing lithium induced neural progenitor proliferation

“… d) Allele specific expression of two SNPs in GNL3 open reading frame in NPCs where donor lines are heterozygous for each SNP, assessed from baseline RNAseq data 30 . r 2 values relative to rs11709284.…”

“… a) To identify transcriptional heterogeneity in the library of NPCs we performed principal component analysis (PCA) of baseline gene expression 30 of the 500 highest variance genes in NPCs from 94 distinct NPC donor lines. Each donor line is a single point plotted in PC space.…”

Inference of cell-type specific imprinted regulatory elements and genes during human neuronal differentiation

“…Raw ATAC-seq and RNA-seq data were quality controlled and aligned to the human genome (GRCh38/hg38) using WASP to prevent mapping bias as previously described (Liang et al 2021;Aygün et al 2021). Genotype data were preprocessed and imputed as previously described (Liang et al 2021).…”

“…The final step was to calculate P=Prbinom(x>=k|n,p) using the binomial test to get the significance of the enrichment. We further filtered the enrichment results by differential expression from the same set of cells, and only kept the TFs with cell-type specific significantly enriched in imprinted REs and significantly differentially expressed in the cell type (Aygün et al 2021).…”

“…All libraries were sequenced on an Illumina HiSeq2500 or MiSeq machine using 50 bp paired-end sequencing. RNA-seq libraries were prepared as previously described (Aygün et al 2021) and were sequenced on a NovaSeq S2 flow cell using 150 bp paired-end sequencing.…”