Matthew James Hill

The complexity of cell fate decisions that underpin early eye development can be effectively modelled by leveraging the unique properties of human induced pluripotent stem cells (hiPSCs). In this study, we have utilised transcriptomic data generated from hiPSCs as they begin to self-organise and differentiate into two-dimensional eye-like organoids in vitro, and employ advanced single-cell analytical tools to dissect the cellular communication networks that direct this dynamic process. We have identified key signalling mediators and transcriptional effectors that guide the transition from pluripotency through to ocular differentiation, and our analyses reveal the conservation of developmentally defined signalling pathways. Members of the Activin, FGF, BMP, WNT, and retinoic acid families of ligands and receptors displayed communication probabilities consistent with their ocular-specific developmental roles in vivo, and this was accompanied by conserved tissue-specific activity of transcriptional regulators. These findings not only highlight the utility of hiPSCs for studying the cellular interactions and molecular pathways that drive early developmental decisions, but also advance our understanding of eye development in an accessible stem cell-based system.

The generation of a self-formed, ectodermal, autonomous multi-zone (SEAM) from human induced pluripotent stem cells (hiPSCs) offers a unique perspective to study the dynamics of ocular cell differentiation over time. Here, by utilising single-cell transcriptomics, we have (i) identified, (ii) molecularly characterised and (iii) ascertained the developmental trajectories of ectodermally-derived ocular cell populations which emerge within SEAMs as they form. Our analysis reveals interdependency between tissues of the early eye and delineates the sequential formation and maturation of distinct cell types over a 12-week period. We demonstrate a progression from pluripotency through to tissue specification and differentiation which encompasses both surface ectodermal and neuroectodermal ocular lineages and the generation of iPSC-derived components of the developing cornea, conjunctiva, lens, and retina. Our findings not only advance the understanding of ocular development in a stem cell-based system of human origin, but also establish a robust methodological paradigm for exploring cellular and molecular dynamics during SEAM formation at single-cell resolution and highlight the potential of hiPSC-derived systems as powerful platforms for modelling human eye development and disease.

Background: Although a number of imprinted genes are known to be highly expressed in the brain, and in certain brain regions in particular, whether they are truly over-represented in the brain has never been formally tested. Using thirteen single-cell RNA sequencing datasets we systematically investigated imprinted gene over-representation at the organ, brain region, and cell-specific levels. Results: We established that imprinted genes are indeed over-represented in the adult brain, and in neurons particularly compared to other brain cell-types. We then examined brain-wide datasets to test enrichment within distinct brain regions and neuron subpopulations and demonstrated over-representation of imprinted genes in the hypothalamus, ventral midbrain, pons and medulla. Finally, using datasets focusing on these regions of enrichment, we identified hypothalamic neuroendocrine populations and the monoaminergic hindbrain neurons as specific hotspots of imprinted gene expression. Conclusions: These analyses provide the first robust assessment of the neural systems on which imprinted genes converge. Moreover, the unbiased approach, with each analysis informed by the findings of the previous level, permits highly informed inferences about the functions on which imprinted gene expression converges. Our findings indicate the neuronal regulation of motivated behaviours such as feeding and sleep, alongside the regulation of pituitary function as functional hotspots for imprinting, thus adding statistical rigour to prior assumptions and providing testable predictions for novel neural and behavioural phenotypes associated with specific genes and imprinted gene networks. In turn, this work sheds further light on the potential evolutionary drivers of genomic imprinting in the brain.

Genes play a strong role in Alzheimer’s disease (AD), with late-onset AD showing heritability of 58–79% and early-onset AD showing over 90%. Genetic association provides a robust platform to build our understanding of the etiology of this complex disease. Over 50 loci are now implicated for AD, suggesting that AD is a disease of multiple components, as supported by pathway analyses (immunity, endocytosis, cholesterol transport, ubiquitination, amyloid-β and tau processing). Over 50% of late-onset AD heritability has been captured, allowing researchers to calculate the accumulation of AD genetic risk through polygenic risk scores. A polygenic risk score predicts disease with up to 90% accuracy and is an exciting tool in our research armory that could allow selection of those with high polygenic risk scores for clinical trials and precision medicine. It could also allow cellular modelling of the combined risk. Here we propose the multiplex model as a new perspective from which to understand AD. The multiplex model reflects the combination of some, or all, of these model components (genetic and environmental), in a tissue-specific manner, to trigger or sustain a disease cascade, which ultimately results in the cell and synaptic loss observed in AD.

A genome-wide significant association has been reported between non-coding variants at the dopamine D2 receptor (DRD2) gene locus and schizophrenia. However, effects of identified schizophrenia risk alleles on DRD2 function are yet to be demonstrated. Using highly sensitive measures of allele-specific expression, we have assessed cis-regulatory effects associated with genotype at lead SNP rs2514218 on DRD2expression in the adult human striatum. No significant differences were observed in the extent of allelic expression imbalance between samples that were genomic heterozygotes for rs2514218 (where cis-regulatory effects of the risk allele are compared with those of the non-risk allele within individual subjects) and samples that were homozygous for rs2514218 (where cis-regulatory effects of this SNP on each expressed DRD2 allele will be equal). We therefore conclude that rs2514218 genotype is not associated with large effects on overall DRD2 RNA expression, at least in postmortem adult striatum. Alternative explanations for the genetic association between this variant and schizophrenia include effects on DRD2 that are transcript specific, restricted to minor DRD2-expressing cell populations or elicited only under certain physiological circumstances, or mediation through effects on another gene (or genes) at the locus.

Late onset Alzheimer’s disease is the most common form of dementia for which about 30 susceptibility loci have been reported. The aim of the current study is to identify novel genes associated with Alzheimer’s disease using the largest up-to-date reference single nucleotide polymorphism (SNP) panel, the most accurate imputation software and a novel gene-based analysis approach which tests for patterns of association within genes, in the powerful genome-wide association dataset of the International Genomics of Alzheimer’s Project Consortium, comprising over 7 million genotypes from 17,008 Alzheimer’s cases and 37,154 controls. In addition to earlier reported genes, we detected three novel gene-wide significant loci PPARGC1A (p = 2.2 × 10⁻⁶), RORA (p = 7.4 × 10⁻⁷) and ZNF423 (p = 2.1 × 10⁻⁶). PPARGC1A and RORA are involved in circadian rhythm; circadian disturbances are one of the earliest symptoms of Alzheimer’s disease. PPARGC1A is additionally linked to energy metabolism and the generation of amyloid beta plaques. RORA is involved in a variety of functions apart from circadian rhythm, such as cholesterol metabolism and inflammation. The ZNF423 gene resides in an Alzheimer’s disease-specific protein network and is likely involved with centrosomes and DNA damage repair.

Loss of function mutations in SETD1A are the first experiment-wide significant findings to emerge from exome sequencing studies of schizophrenia. Although SETD1A is known to encode a histone methyltransferase, the consequences of reduced SETD1A activity on gene expression in neural cells have, to date, been unknown. To explore transcriptional changes through which genetic perturbation of SETD1A could confer risk for schizophrenia, we have performed genome-wide gene expression profiling of a commonly used human neuroblastoma cell line in which SETD1A expression has been experimentally reduced using RNA interference (RNAi). We identified 1,031 gene expression changes that were significant in two separate RNAi conditions compared with control, including effects on genes of known neurodevelopmental importance such as DCX and DLX5. Genes that were differentially expressed following SETD1A knockdown were enriched for annotation to metabolic pathways, peptidase regulator activity and integrin-mediated regulation of cell adhesion. Moreover, differentially expressed genes were enriched for common variant association with schizophrenia, suggesting a degree of molecular convergence between this rare schizophrenia risk factor and susceptibility variants for the disorder operating more generally.

Genome-wide association studies have linked common variation in ZNF804A with an increased risk of schizophrenia. However, little is known about the biology of ZNF804A and its role in schizophrenia. Here, we investigate the function of ZNF804A using a variety of complementary molecular techniques. We show that ZNF804A is a nuclear protein that interacts with neuronal RNA splicing factors and RNA-binding proteins including RBFOX1, which is also associated with schizophrenia, CELF3/4, components of the ubiquitin-proteasome system and the ZNF804A paralog, GPATCH8. GPATCH8 also interacts with splicing factors and is localized to nuclear speckles indicative of a role in pre-messenger RNA (mRNA) processing. Sequence analysis showed that GPATCH8 contains ultraconserved, alternatively spliced poison exons that are also regulated by RBFOX proteins. ZNF804A knockdown in SH-SY5Y cells resulted in robust changes in gene expression and pre-mRNA splicing converging on pathways associated with nervous system development, synaptic contact, and cell adhesion. We observed enrichment (P = 1.66 × 10^–9) for differentially spliced genes in ZNF804A-depleted cells among genes that contain RBFOX-dependent alternatively spliced exons. Differentially spliced genes in ZNF804A-depleted cells were also enriched for genes harboring de novo loss of function mutations in autism spectrum disorder (P = 6.25 × 10^–7, enrichment 2.16) and common variant alleles associated with schizophrenia (P = .014), bipolar disorder and schizophrenia (P = .003), and autism spectrum disorder (P = .005). These data suggest that ZNF804A and its paralogs may interact with neuronal-splicing factors and RNA-binding proteins to regulate the expression of a subset of synaptic and neurodevelopmental genes.

Widespread structural, chemical and molecular differences have been reported between the male and female human brain. Although several neurodevelopmental disorders are more commonly diagnosed in males, little is known regarding sex differences in early human brain development. Here, we used RNA sequencing data from a large collection of human brain samples from the second trimester of gestation (N = 120) to assess sex biases in gene expression within the human fetal brain. In addition to 43 genes (102 Ensembl transcripts) transcribed from the Y-chromosome in males, we detected sex differences in the expression of 2558 autosomal genes (2723 Ensembl transcripts) and 155 genes on the X-chromosome (207 Ensembl transcripts) at a false discovery rate (FDR) < 0.1. Genes exhibiting sex-biased expression in human fetal brain are enriched for high-confidence risk genes for autism and other developmental disorders. Male-biased genes are enriched for expression in neural progenitor cells, whereas female-biased genes are enriched for expression in Cajal-Retzius cells and glia. All gene- and transcript-level data are provided as an online resource (available at http://fgen.psycm.cf.ac.uk/FBSeq1 ) through which researchers can search, download and visualize data pertaining to sex biases in gene expression during early human brain development.