Brain-wide correspondence of neuronal epigenomics and distant projections.

Single-cell analyses parse the brain's billions of neurons into thousands of 'cell-type' clusters residing in different brain structures1. Many cell types mediate their functions through targeted long-distance projections allowing interactions between specific cell types. Here we used epi-retro-seq2 to link single-cell epigenomes and cell types to long-distance projections for 33,034 neurons dissected from 32 different regions projecting to 24 different targets (225 source-to-target combinations) across the whole mouse brain. We highlight uses of these data for interrogating principles relating projection types to transcriptomics and epigenomics, and for addressing hypotheses about cell types and connections related to genetics. We provide an overall synthesis with 926 statistical comparisons of discriminability of neurons projecting to each target for every source. We integrate this dataset into the larger BRAIN Initiative Cell Census Network atlas, composed of millions of neurons, to link projection cell types to consensus clusters. Integration with spatial transcriptomics further assigns projection-enriched clusters to smaller source regions than the original dissections. We exemplify this by presenting in-depth analyses of projection neurons from the hypothalamus, thalamus, hindbrain, amygdala and midbrain to provide insights into properties of those cell types, including differentially expressed genes, their associated cis-regulatory elements and transcription-factor-binding motifs, and neurotransmitter use.

DNA methylation atlas of the mouse brain at single-cell resolution.

Mammalian brain cells show remarkable diversity in gene expression, anatomy and function, yet the regulatory DNA landscape underlying this extensive heterogeneity is poorly understood. Here we carry out a comprehensive assessment of the epigenomes of mouse brain cell types by applying single-nucleus DNA methylation sequencing1,2 to profile 103,982 nuclei (including 95,815 neurons and 8,167 non-neuronal cells) from 45 regions of the mouse cortex, hippocampus, striatum, pallidum and olfactory areas. We identified 161 cell clusters with distinct spatial locations and projection targets. We constructed taxonomies of these epigenetic types, annotated with signature genes, regulatory elements and transcription factors. These features indicate the potential regulatory landscape supporting the assignment of putative cell types and reveal repetitive usage of regulators in excitatory and inhibitory cells for determining subtypes. The DNA methylation landscape of excitatory neurons in the cortex and hippocampus varied continuously along spatial gradients. Using this deep dataset, we constructed an artificial neural network model that precisely predicts single neuron cell-type identity and brain area spatial location. Integration of high-resolution DNA methylomes with single-nucleus chromatin accessibility data3 enabled prediction of high-confidence enhancer-gene interactions for all identified cell types, which were subsequently validated by cell-type-specific chromatin conformation capture experiments4. By combining multi-omic datasets (DNA methylation, chromatin contacts, and open chromatin) from single nuclei and annotating the regulatory genome of hundreds of cell types in the mouse brain, our DNA methylation atlas establishes the epigenetic basis for neuronal diversity and spatial organization throughout the mouse cerebrum.

Epigenomic diversity of cortical projection neurons in the mouse brain.

Neuronal cell types are classically defined by their molecular properties, anatomy and functions. Although recent advances in single-cell genomics have led to high-resolution molecular characterization of cell type diversity in the brain1, neuronal cell types are often studied out of the context of their anatomical properties. To improve our understanding of the relationship between molecular and anatomical features that define cortical neurons, here we combined retrograde labelling with single-nucleus DNA methylation sequencing to link neural epigenomic properties to projections. We examined 11,827 single neocortical neurons from 63 cortico-cortical and cortico-subcortical long-distance projections. Our results showed unique epigenetic signatures of projection neurons that correspond to their laminar and regional location and projection patterns. On the basis of their epigenomes, intra-telencephalic cells that project to different cortical targets could be further distinguished, and some layer 5 neurons that project to extra-telencephalic targets (L5 ET) formed separate clusters that aligned with their axonal projections. Such separation varied between cortical areas, which suggests that there are area-specific differences in L5 ET subtypes, which were further validated by anatomical studies. Notably, a population of cortico-cortical projection neurons clustered with L5 ET rather than intra-telencephalic neurons, which suggests that a population of L5 ET cortical neurons projects to both targets. We verified the existence of these neurons by dual retrograde labelling and anterograde tracing of cortico-cortical projection neurons, which revealed axon terminals in extra-telencephalic targets including the thalamus, superior colliculus and pons. These findings highlight the power of single-cell epigenomic approaches to connect the molecular properties of neurons with their anatomical and projection properties.

Simultaneous profiling of 3D genome structure and DNA methylation in single human cells.

Dynamic three-dimensional chromatin conformation is a critical mechanism for gene regulation during development and disease. Despite this, profiling of three-dimensional genome structure from complex tissues with cell-type specific resolution remains challenging. Recent efforts have demonstrated that cell-type specific epigenomic features can be resolved in complex tissues using single-cell assays. However, it remains unclear whether single-cell chromatin conformation capture (3C) or Hi-C profiles can effectively identify cell types and reconstruct cell-type specific chromatin conformation maps. To address these challenges, we have developed single-nucleus methyl-3C sequencing to capture chromatin organization and DNA methylation information and robustly separate heterogeneous cell types. Applying this method to >4,200 single human brain prefrontal cortex cells, we reconstruct cell-type specific chromatin conformation maps from 14 cortical cell types. These datasets reveal the genome-wide association between cell-type specific chromatin conformation and differential DNA methylation, suggesting pervasive interactions between epigenetic processes regulating gene expression.

The complex architecture and epigenomic impact of plant T-DNA insertions.

The bacterium Agrobacterium tumefaciens has been the workhorse in plant genome engineering. Customized replacement of native tumor-inducing (Ti) plasmid elements enabled insertion of a sequence of interest called Transfer-DNA (T-DNA) into any plant genome. Although these transfer mechanisms are well understood, detailed understanding of structure and epigenomic status of insertion events was limited by current technologies. Here we applied two single-molecule technologies and analyzed Arabidopsis thaliana lines from three widely used T-DNA insertion collections (SALK, SAIL and WISC). Optical maps for four randomly selected T-DNA lines revealed between one and seven insertions/rearrangements, and the length of individual insertions from 27 to 236 kilobases. De novo nanopore sequencing-based assemblies for two segregating lines partially resolved T-DNA structures and revealed multiple translocations and exchange of chromosome arm ends. For the current TAIR10 reference genome, nanopore contigs corrected 83% of non-centromeric misassemblies. The unprecedented contiguous nucleotide-level resolution enabled an in-depth study of the epigenome at T-DNA insertion sites. SALK_059379 line T-DNA insertions were enriched for 24nt small interfering RNAs (siRNA) and dense cytosine DNA methylation, resulting in transgene silencing via the RNA-directed DNA methylation pathway. In contrast, SAIL_232 line T-DNA insertions are predominantly targeted by 21/22nt siRNAs, with DNA methylation and silencing limited to a reporter, but not the resistance gene. Additionally, we profiled the H3K4me3, H3K27me3 and H2A.Z chromatin environments around T-DNA insertions using ChIP-seq in SALK_059379, SAIL_232 and five additional T-DNA lines. We discovered various effect s ranging from complete loss of chromatin marks to the de novo incorporation of H2A.Z and trimethylation of H3K4 and H3K27 around the T-DNA integration sites. This study provides new insights into the structural impact of inserting foreign fragments into plant genomes and demonstrates the utility of state-of-the-art long-range sequencing technologies to rapidly identify unanticipated genomic changes.

Recurrent colon cancer in a patient with Muir-Torre syndrome: a case report.

Muir-Torre syndrome (MTS) is a rare subtype of hereditary nonpolyposis colorectal cancer syndrome caused by a defect in DNA mismatch repair leading to microsatellite instability. It is characterized by the presence of at least one sebaceous gland tumor and one internal malignancy, most commonly colorectal and endometrial tumors. These patients have a high propensity for tumorigenesis, and while strict screening protocols are in place, there are only two cases that describe the management approach to recurrent colon cancer. Here, we present a case of recurrent colorectal cancer in a patient with MTS, and describe how it was managed at our facility by a multidisciplinary team.

Pregnancy outcomes in the medical management of glaucoma: An international multicenter descriptive survey.

PURPOSE: To determine if glaucoma medications are associated with pregnancy and/or postnatal complications. METHODS: Multicenter descriptive survey. Subjects were female patients 18-45 years who were previously pregnant with a diagnosis of glaucoma or ocular hypertension prior to pregnancy. Chart review queried diagnosis, glaucoma severity, and race. Survey questions were asked for each pregnancy and queried pregnancy age, medications used, and pregnancy outcomes/complications. RESULTS: 114 pregnancies of 56 patients (mean 2.0 pregnancies per patient) were included. Three pregnancies with therapeutic abortion were excluded from further analysis. Mean age during pregnancy was 29.1 ± 5.7 years. Of the 111 pregnancies, 20 (18.0%) used no medications and 91 (82.0%) used at least one medication. Medications were topical carbonic anhydrase inhibitors (n = 45), beta-blockers (n = 55), alpha-agonists (n = 56), and prostaglandin analogues (n = 28). Outcomes were: preterm contractions/labour (6.3%), miscarriage (4.5%), stillbirth (4.5%), induction of labour (11.9%), emergency/unplanned caesarean delivery (13.9%), neonatal intensive care unit (NICU) stay (15.8%), congenital anomalies (8.1%), and low birth weight (10.9%). Fisher exact test assessed outcome associations with individual agents, use of any agent, and different number of agents. Alpha-agonist use was associated with NICU stay: 25.5% rate (p = 0.012) in alpha-agonist use. Most of the alpha-agonist use NICU stays occurred in pregnancies with third trimester use. All other associations were not statistically significant. CONCLUSIONS: The data from this survey suggest an overall favourable safety profile for topical glaucoma medications in pregnancy, but further investigation is needed. Caution should be employed regarding third trimester alpha-agonist use owing to association with NICU stay.

Robust enhancer-gene regulation identified by single-cell transcriptomes and epigenomes.

Single-cell sequencing could help to solve the fundamental challenge of linking millions of cell-type-specific enhancers with their target genes. However, this task is confounded by patterns of gene co-expression in much the same way that genetic correlation due to linkage disequilibrium confounds fine-mapping in genome-wide association studies (GWAS). We developed a non-parametric permutation-based procedure to establish stringent statistical criteria to control the risk of false-positive associations in enhancer-gene association studies (EGAS). We applied our procedure to large-scale transcriptome and epigenome data from multiple tissues and species, including the mouse and human brain, to predict enhancer-gene associations genome wide. We tested the functional validity of our predictions by comparing them with chromatin conformation data and causal enhancer perturbation experiments. Our study shows how controlling for gene co-expression enables robust enhancer-gene linkage using single-cell sequencing data.

Single nucleus multi-omics identifies human cortical cell regulatory genome diversity.

Single-cell technologies measure unique cellular signatures but are typically limited to a single modality. Computational approaches allow the fusion of diverse single-cell data types, but their efficacy is difficult to validate in the absence of authentic multi-omic measurements. To comprehensively assess the molecular phenotypes of single cells, we devised single-nucleus methylcytosine, chromatin accessibility, and transcriptome sequencing (snmCAT-seq) and applied it to postmortem human frontal cortex tissue. We developed a cross-validation approach using multi-modal information to validate fine-grained cell types and assessed the effectiveness of computational data fusion methods. Correlation analysis in individual cells revealed distinct relations between methylation and gene expression. Our integrative approach enabled joint analyses of the methylome, transcriptome, chromatin accessibility, and conformation for 63 human cortical cell types. We reconstructed regulatory lineages for cortical cell populations and found specific enrichment of genetic risk for neuropsychiatric traits, enabling the prediction of cell types that are associated with diseases.

Iterative single-cell multi-omic integration using online learning.

Integrating large single-cell gene expression, chromatin accessibility and DNA methylation datasets requires general and scalable computational approaches. Here we describe online integrative non-negative matrix factorization (iNMF), an algorithm for integrating large, diverse and continually arriving single-cell datasets. Our approach scales to arbitrarily large numbers of cells using fixed memory, iteratively incorporates new datasets as they are generated and allows many users to simultaneously analyze a single copy of a large dataset by streaming it over the internet. Iterative data addition can also be used to map new data to a reference dataset. Comparisons with previous methods indicate that the improvements in efficiency do not sacrifice dataset alignment and cluster preservation performance. We demonstrate the effectiveness of online iNMF by integrating more than 1 million cells on a standard laptop, integrating large single-cell RNA sequencing and spatial transcriptomic datasets, and iteratively constructing a single-cell multi-omic atlas of the mouse motor cortex.

Robust single-cell DNA methylome profiling with snmC-seq2.

Single-cell DNA methylome profiling has enabled the study of epigenomic heterogeneity in complex tissues and during cellular reprogramming. However, broader applications of the method have been impeded by the modest quality of sequencing libraries. Here we report snmC-seq2, which provides improved read mapping, reduced artifactual reads, enhanced throughput, as well as increased library complexity and coverage uniformity compared to snmC-seq. snmC-seq2 is an efficient strategy suited for large-scale single-cell epigenomic studies.