The advent of next generation sequencing ushered in a ten-year period of exuberant technology development, enabling the quantification of gene expression and epigenetic features within individual cells, and within intact tissue sections.  In this seminar, I will outline our technological contributions, beginning with the development of Drop-seq, a method for high-throughput single cell analysis, followed by the development of Slide-seq, a technique for measuring genome-wide expression at 10 micron spatial resolution.  Using a combination of these techniques, we recently constructed a comprehensive cell type atlas of the adult mouse brain, positioning cell types within individual brain structures.  I will discuss the major findings from this dataset, including emerging principles of neurotransmission, and the localization of disease gene signatures to specific cell types.  Finally, I will introduce a new spatial technology, Slide-tags, that unifies single cell and spatial genomics into a single, highly scalable assay.

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.

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.

Classification of neurons, long viewed as a fairly boring enterprise, has emerged as a major bottleneck in analysis of neural circuits. High throughput single cell RNA-seq has provided a new way to improve the situation. We initially applied this method to mouse retina, showing that its five neuronal classes (photoreceptors, three groups of interneurons, and retinal ganglion cells) can be divided into 130 discrete types. We then applied the method to other species including human, macaque, zebrafish and chick. With the atlases in hand, we are now using them to address questions about how retinal cell types diversify, how they differ in their responses to injury and disease, and the extent to which cell classes and types are conserved among vertebrates.

Repeat-rich sequence blocks are considered major determinants for 3D folding and structural genome organization in the cell nucleus in all higher eukaryotes. Here, we discuss how megabase-scale chromatin domain and chromosomal compartment organization in adult mouse cerebral cortex is linked, in highly cell type-specific fashion, to multiple retrotransposon superfamilies which comprise the vast majority of mobile DNA elements in the murine genome. We show that neuronal megadomain architectures include an evolutionarily adaptive heterochromatic organization which, upon perturbation, unleashes proviruses from the Long Terminal Repeat (LTR) Endogenous Retrovirus family that exhibit strong tropism in mature neurons. Furthermore, we mapped, in the human brain, cell type-specific genomic integration patterns of the human pathogen and exogenous retrovirus, HIV, together with changes in genome organization and function of the HIV infected brain. Our work highlights the critical importance of chromosomal conformations and the ‘spatial genome’ for neuron- and glia-specific regulatory mechanisms and defenses aimed at exogenous and endogenous retrotransposons in the brain

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 ability to read the DNA sequences of different organisms has transformed biology in much the same way that the telescope transformed astronomy. And yet, much of the sequence found in these genomes is as enigmatic as the Rosetta Stone was to early Egyptologists. With the aim of making steps to crack the genomic Rosetta Stone, I will describe unexpected ways of using the physics of information transfer first developed at Bell Labs for thinking about telephone communications to try to decipher the meaning of the regulatory features of genomes. Specifically, I will show how we have been able to explore genes for which we know nothing about how they are regulated by using a combination of mutagenesis, deep sequencing and the physics of information, with the result that we now have falsifiable hypotheses about how those genes work. With those results in hand, I will show how simple tools from statistical physics can be used to predict the level of expression of different genes, followed by a description of precision measurements used to test those predictions. Bringing the two threads of the talk together, I will think about next steps in reading and writing genomes at will.