Cell-specific gene regulation in the developing human brain and genetic risk for neuropsychiatric disorders

Lead Research Organisation: Cardiff University
Department Name: School of Medicine

Abstract

Large-scale genetic studies have identified hundreds of regions of the human genome that commonly influence susceptibility to mental illnesses such as schizophrenia. The great majority of these risk variants are located in areas of the genome that do not encode proteins and are therefore thought to instead affect gene expression (i.e. the amount of that gene that the cell produces as RNA / protein). Recent studies indicate that many of these risk variants are active in the prenatal human brain, but the cells involved are unknown. We will use cutting-edge technology to determine the constituent cell types of 5 regions of the developing human brain and the genomic sites controlling gene expression within them. We will integrate these data with results from large genetic studies to delineate cell types of the prenatal brain that mediate genetic risk for psychiatric disorders. These studies will greatly advance our understanding of the cellular basis of major mental illnesses, which will promote improved treatments for these conditions.

Technical Summary

Large-scale genome-wide association studies (GWAS) have identified hundreds of risk loci that are commonly involved in neuropsychiatric disorders such as schizophrenia. Nearly all of these associations implicate non-coding regions of the genome and are therefore thought to reflect variants affecting gene regulation. Recent data indicate that an appreciable number of risk loci for neuropsychiatric disorders are active in the human prenatal brain, but the cells mediating these effects are unknown. We will perform single cell RNA sequencing and open chromatin profiling (ATAC-Seq) in order to define the constituent cell types of 5 regions of the human 2nd trimester foetal brain and the genomic sites controlling gene expression within them. We will integrate these data with results from large genomic studies of neuropsychiatric disorders in order to delineate cell types of the prenatal brain that mediate genetic risk for these conditions both at the polygenic level (through analyses of partitioned heritability) and at individual high-confidence risk loci. These studies will greatly improve our understanding of the aetiology and cellular basis of neuropsychiatric disorders as well as of gene regulation in the developing human brain.

Planned Impact

Although neuropsychiatric disorders are common and associated with considerable individual and societal burden, we know very little about the underlying neurobiology of these conditions. Elucidating the molecular and cellular mechanisms by which identified genetic risk variants operate will be an essential first step in advancing our biological understanding of these disorders, with the ultimate goal of developing improved treatments and possibly even prevention strategies.

In the short term, the primary beneficiaries of our research will be other researchers in academia and industry. Our identification of foetal brain cells in which genetic risk variants for neuropsychiatric disorders are active will benefit research seeking to understand the biological basis of these conditions. For example, it will foster more valid cellular and animal models for these disorders, with which improved therapies can be developed and tested. In addition, our mapping of regulatory genomic sites and gene networks within defined cell populations of the foetal brain will advance understanding of gene regulation in human brain development more generally, and this is likely to be relevant to many other disorders of the central nervous system.

We will maximise the impact of this research by publishing our findings in open access journals, extensive data sharing, conference presentations, and rapid dissemination of findings to academic and industrial communities seeking to advance therapeutics for neuropsychiatric and other central nervous system disorders.
 
Title Single nuclei RNA-Seq from 5 regions of the human fetal brain (raw data) 
Description Data generated through single nuclei RNA sequencing on 5 regions of the brain (frontal cortex, ganglionic eminence, hippocampus, thalamus and cerebellum) from 3 fetuses (two of 14 and one of 15 post-conception weeks, all female). These are FASTQ files containing raw sequencing data and available through controlled access to other researchers (as contain genotype information) via the he European Genome-phenome Archive (https://ega-archive.org/about/introduction) 
Type Of Material Database/Collection of data 
Year Produced 2022 
Provided To Others? Yes  
Impact We have provided these data to researchers upon request. 
URL https://ega-archive.org/datasets/EGAD00001009303
 
Title Single nuclei gene expression matrix from 5 regions of the human prenatal brain 
Description Data generated through single nuclei RNA sequencing on 5 regions of the brain (frontal cortex, ganglionic eminence, hippocampus, thalamus and cerebellum) from 3 fetuses (two of 14 and one of 15 post-conception weeks, all female). Tissue was acquired from the MRC-Wellcome Trust Human Developmental Biology Resource (HDBR) with ethical approval. snRNA-seq libraries were prepared from ~10,000 nuclei from each sample using Chromium Single Cell 3' (v3) reagents (10X Genomics). Quality control of libraries was performed using the Agilent 5200 Fragment Analyzer before sequencing on an Illumina NovaSeq 6000 to a depth of at least 865 million (median = 1.01 billion) read pairs per library. Raw sequencing data were converted into FASTQ files, aligned to the hg38 build of the human reference genome and quantified using cellranger count (10X Genomics). For a full description of data generation, please see Cameron et al, Biological Psychiatry 2022 https://doi.org/10.1016/j.biopsych.2022.06.033 
Type Of Material Database/Collection of data 
Year Produced 2022 
Provided To Others? Yes  
Impact To date (3rd March 2023), these data have been downloaded 177 times. 
URL https://figshare.com/articles/dataset/Single_nuclei_gene_expression_matrix_from_5_regions_of_the_hum...