Schizophrenia is a neuropsychiatric disorder characterized by positive symptoms (such as hallucinations and delusions), negative symptoms (such as avolition and withdrawal) and cognitive dysfunction1. Schizophrenia is highly heritable, and genetic studies are playing a pivotal role in identifying potential biomarkers and causal disease mechanisms with the hope of informing new treatments. Genome-wide association studies (GWAS) identified nearly 270 loci with a high statistical association with schizophrenia risk; however each locus confers only a small increase in risk therefore it is difficult to translate these findings into understanding disease biology that can lead to treatments. Induced pluripotent stem cell (iPSC) models are a tractable system to translate genetic findings and interrogate mechanisms of pathogenesis. Mounting research with patient-derived iPSCs has proposed several neurodevelopmental pathways altered in SCZ, such as neural progenitor cell (NPC) proliferation, imbalanced differentiation of excitatory and inhibitory cortical neurons. However, it is unclear what exactly these iPS models recapitulate, how potential perturbations of early brain development translates into illness in adults and how iPS models that represent fetal stages can be utilized to further drug development efforts to treat adult illness. I will present the largest transcriptome analysis of post-mortem caudate nucleus in schizophrenia where we discovered that decreased presynaptic DRD2 autoregulation is the causal dopamine risk factor for schizophrenia (Benjamin et al, Nature Neuroscience 2022 https://doi.org/10.1038/s41593-022-01182-7). We developed stem cell models from a subset of the postmortem cohort to better understand the molecular underpinnings of human psychiatric disorders (Sawada et al, Stem Cell Research 2020). We established a method for the differentiation of iPS cells into ventral forebrain organoids and performed single cell RNAseq and cellular phenotyping. To our knowledge, this is the first study to evaluate iPSC models of SZ from the same individuals with postmortem tissue. Our study establishes that striatal neurons in the patients with SCZ carry abnormalities that originated during early brain development. Differentiation of inhibitory neurons is accelerated whereas excitatory neuronal development is delayed, implicating an excitation and inhibition (E-I) imbalance during early brain development in SCZ. We found a significant overlap of genes upregulated in the inhibitory neurons in SCZ organoids with upregulated genes in postmortem caudate tissues from patients with SCZ compared with control individuals, including the donors of our iPS cell cohort. Altogether, we demonstrate that ventral forebrain organoids derived from postmortem tissue of individuals with schizophrenia recapitulate perturbed striatal gene expression dynamics of the donors’ brains (Sawada et al, biorxiv 2022 https://doi.org/10.1101/2022.05.26.493589).

The cerebral cortex is the most evolved structure of the brain and the site for higher cognitive functions. It consists of 6 layers, each composed of specific types of neurons. Interconnectivity between cortical areas is critical for sensory integration and sensorimotor transformation. Inter-areal cortical projection neurons are located in all cortical layers and form a heterogeneous population, which send their axon across cortical areas, both within and across hemispheres. How this diversity emerges during development remains largely unknown. Here, we address this question by linking the connectome and transcriptome of developing cortical projection neurons and show distinct maturation paces in neurons with distinct projections, which correlates with the sequential development of sensory and motor functions during postnatal period.

Exploration of genome organization and function in the HIV infected brain is critical to aid in the understanding and development of treatments for HIV-associated neurocognitive disorder (HAND). Here, we applied a multiomic approach, including single nuclei transcriptomics, cell-type specific Hi-C 3D genome mapping, and viral integration site sequencing (IS-seq) to frontal lobe tissue from HIV-infected individuals with encephalitis (HIVE) and without encephalitis (HIV+). We observed reorganization of open/repressive (A/B) compartment structures in HIVE microglia encompassing 6.4% of the genome with enrichment for regions containing interferon (IFN) pathway genes. 3D genome remodeling was associated with transcriptomic reprogramming, including down-regulation of cell adhesion and synapse-related functions and robust activation of IFN signaling and cell migratory pathways, and was recapitulated by IFN-g stimulation of cultured microglial cells. Microglia from HIV+ brains showed, to a lesser extent, similar transcriptional alterations. IS-seq recovered 1,221 integration sites in the brain that were enriched for chromosomal domains newly mobilized into a permissive chromatin environment in HIVE microglia. Viral transcription, which was detected in 0.003% of all nuclei in HIVE brain, occurred in a subset of highly activated microglia that drove differential expression in HIVE. Thus, we observed a dynamic interrelationship of interferon-associated 3D genome and transcriptome remodeling with HIV integration and transcription in the brain.

Night shift work is associated with adverse health effects and leads to misalignment between timing cues from the environment and the endogenous circadian clock. In this presentation, I will discuss the effect of circadian misalignment induced by night shift work on peripheral 24-h rhythms on the transcriptome and metabolome in humans, presenting findings from both controlled laboratory studies and field studies. Furthermore, I will highlight the importance of taking into account interindividual differences in the response to circadian misalignment.

The complex morphology of neurons, with synapses located hundreds of microns from the cell body, necessitates the localization of important cell biological machines, including ribosomes, within dendrites and axons. Local translation of mRNAs is important for the function and plasticity of synapses. Using advanced sequencing and imaging techniques we have updated our understanding of the local transcriptome and identified the local translatome- identifying over 800 transcripts for which local translation is the dominant source of protein. In addition, we have explored the unique mechanisms neurons use to meet protein demands at synapses, identifying surprising features of neuronal and synaptic protein synthesis.

Animals traversing different environments encounter both stable background stimuli and novel cues, which are generally thought to be detected by primary sensory neurons and then distinguished by downstream brain circuits. Sensory adaptation is a neural mechanism that filters background by minimizing responses to stable sensory stimuli, and a fundamental feature of sensory systems. Adaptation over relatively fast timescales (milliseconds to minutes) have been reported in many sensory systems. However, adaptation to persistent environmental stimuli over longer timescales (hours to days) have been largely unexplored, even though those timescales are ethologically important since animals typically stay in one environment for hours. I showed that each of the ~1,000 olfactory sensory neuron (OSN) subtypes in the mouse harbors a distinct transcriptome whose content is precisely determined by interactions between its odorant receptor and the environment. This transcriptional variation is systematically organized to support sensory adaptation: expression levels of many genes relevant to transforming odors into spikes continuously vary across OSN subtypes, dynamically adjust to new environments over hours, and accurately predict acute OSN-specific odor responses. The sensory periphery therefore separates salient signals from predictable background via a transcriptional mechanism whose moment-to-moment state reflects the past and constrains the future; these findings suggest a general model in which structured transcriptional variation within a cell type reflects individual experience.

Three intimately related dimensions of the mammalian genome—linear DNA sequence, gene transcription, and 3D genome architecture—are crucial for the development of nervous systems. Changes in the linear genome (e.g., de novo mutations), transcriptome, and 3D genome structure lead to debilitating neurodevelopmental disorders, such as autism and schizophrenia. However, current technologies and data are severely limited: (1) 3D genome structures of single brain cells have not been solved; (2) little is known about the dynamics of single-cell transcriptome and 3D genome after birth; (3) true de novo mutations are extremely difficult to distinguish from false positives (DNA damage and/or amplification errors). Here, I filled in this longstanding technological and knowledge gap. I recently developed a high-resolution method—diploid chromatin conformation capture (Dip-C)—which resolved the first 3D structure of the human genome, tackling a longstanding problem dating back to the 1880s. Using Dip-C, I obtained the first 3D genome structure of a single brain cell, and created the first transcriptome and 3D genome atlas of the mouse brain during postnatal development. I found that in adults, 3D genome “structure types” delineate all major cell types, with high correlation between chromatin A/B compartments and gene expression. During development, both transcriptome and 3D genome are extensively transformed in the first month of life. In neurons, 3D genome is rewired across scales, correlated with gene expression modules, and independent of sensory experience. Finally, I examined allele-specific structure of imprinted genes, revealing local and chromosome-wide differences. More recently, I expanded my 3D genome atlas to the human and mouse cerebellum—the most consistently affected brain region in autism. I uncovered unique 3D genome rewiring throughout life, providing a structural basis for the cerebellum’s unique mode of development and aging. In addition, to accurately measure de novo mutations in a single cell, I developed a new method—multiplex end-tagging amplification of complementary strands (META-CS), which eliminates nearly all false positives by virtue of DNA complementarity. Using META-CS, I determined the true mutation spectrum of single human brain cells, free from chemical artifacts. Together, my findings uncovered an unknown dimension of neurodevelopment, and open up opportunities for new treatments for autism and other developmental disorders.

Ten of thousands of open reading frames (ORFs) are hidden within transcripts. They have eluded annotations because they are either small or within unsuspected locations. These are named alternative ORFs (altORFs) or small ORFs and have recently been highlighted by innovative proteogenomic approaches, such as our OpenProt resource, revealing their existence and implications in biological functions. Due to the absence of altORFs from annotations, pathogenic mutations within these are being ignored. I will discuss our latest progress on the re-analysis of large-scale proteomics datasets to improve our knowledge of proteomic diversity, and the functional characterization of a second protein coded by the FUS gene. Finally, I will explain the need to map the coding potential of the transcriptome using artificial intelligence rather than with conventional annotations that do not capture the full translational activity of ribosomes.

Over the past years, genetic studies have uncovered hundreds of genetic variants to be associated with complex brain disorders. While this really represents a big step forward in understanding the genetic etiology of brain disorders, the functional interpretation of these variants remains challenging. We aim to help with the functional characterization of variants through transcriptomic data analysis. For instance, we rely on brain transcriptome atlases, such as Allen Brain Atlases, to infer functional relations between genes. One example of this is the identification of signaling mechanisms of steroid receptors. Further, by integrating brain transcriptome atlases with neuropathology and neuroimaging data, we identify key genes and pathways associated with brain disorders (e.g. Parkinson's disease). With technological advances, we can now profile gene expression in single-cells at large scale. These developments have presented significant computational developments. Our lab focuses on developing scalable methods to identify cells in single-cell data through interactive visualization, scalable clustering, classification, and interpretable trajectory modelling. We also work on methods to integrate single-cell data across studies and technologies.

The precise spatial localization of molecular signals within tissues richly informs the mechanisms of tissue formation and function. Here, we’ll introduce Slide-seq, a technology which enables transcriptome-wide measurements with near-single cell spatial resolution. We’ll describe recent experimental and computational advances to enable Slide-seq in biological contexts in biological contexts where high detection sensitivity is important. More broadly, we’ll discuss the promise and challenges of spatial transcriptomics for tissue genomics. Lastly, we’ll touch upon novel molecular recording technologies, which allows recording of the absolute time dynamics of gene expression in live systems into DNA sequences.

The complex morphology of neurons, with synapses located 100’s of microns from the cell body, necessitates the localization of important cell biological machines and processes within dendrites and axons. Using expansion microscopy together with metabolic labeling we have discovered that both postsynaptic spines and presynaptic terminals exhibit rapid translation, which exhibits differential sensitivity to different neurotransmitters and neuromodulators. In addition, we have explored the unique mechanisms neurons use to meet protein demands at synapses, identifying the transcriptome and translatome in the neuropil.