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Behrens, M. M.

Publications and source records attributed to Behrens, M. M..

25 records · Page 2Linked to original sources

Epigenomic Diversity of Cortical Projection Neurons in the Mouse Brain

Neuronal cell types are classically defined by their molecular properties, anatomy, and functions. While recent advances in single-cell genomics have led to high-resolution molecular characterization of cell type diversity in the brain, neuronal cell types are often studied out of the context of their anatomical properties. To better understand the relationship between molecular and anatomical features defining cortical neurons, we combined retrograde labeling with single-nucleus DNA methylation sequencing to link epigenomic properties of cell types to neuronal projections. We examined 11,827 single neocortical neurons from 63 cortico-cortical (CC) and cortico-subcortical long-distance projections. Our results revealed unique epigenetic signatures of projection neurons that correspond to their laminar and regional location and projection patterns. Based on their epigenomes, intra-telencephalic (IT) cells projecting to different cortical targets could be further distinguished, and some layer 5 neurons projecting to extra-telencephalic targets (L5-ET) formed separate subclusters that aligned with their axonal projections. Such separation varied between cortical areas, suggesting area-specific differences in L5-ET subtypes, which were further validated by anatomical studies. Interestingly, a population of CC projection neurons clustered with L5-ET rather than IT neurons, suggesting a population of L5-ET cortical neurons projecting to both targets (L5-ET+CC). We verified the existence of these neurons by labeling the axon terminals of CC projection neurons and observed clear labeling in ET targets including 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.

neuroscience↗

An integrated transcriptomic and epigenomic atlas of mouse primary motor cortex cell types

Single cell transcriptomics has transformed the characterization of brain cell identity by providing quantitative molecular signatures for large, unbiased samples of brain cell populations. With the proliferation of taxonomies based on individual datasets, a major challenge is to integrate and validate results toward defining biologically meaningful cell types. We used a battery of single-cell transcriptome and epigenome measurements generated by the BRAIN Initiative Cell Census Network (BICCN) to comprehensively assess the molecular signatures of cell types in the mouse primary motor cortex (MOp). We further developed computational and statistical methods to integrate these multimodal data and quantitatively validate the reproducibility of the cell types. The reference atlas, based on more than 600,000 high quality single-cell or -nucleus samples assayed by six molecular modalities, is a comprehensive molecular account of the diverse neuronal and non-neuronal cell types in MOp. Collectively, our study indicates that the mouse primary motor cortex contains over 55 neuronal cell types that are highly replicable across analysis methods, sequencing technologies, and modalities. We find many concordant multimodal markers for each cell type, as well as thousands of genes and gene regulatory elements with discrepant transcriptomic and epigenomic signatures. These data highlight the complex molecular regulation of brain cell types and will directly enable design of reagents to target specific MOp cell types for functional analysis.

neuroscience↗

Polycomb-mediated repression compensates for loss of postnatal DNA methylation in excitatory neurons

Two epigenetic pathways of repression, DNA methylation and Polycomb repressive complex 2 (PRC2) mediated gene silencing, regulate neuron development and function, but their respective contributions are unknown. We found that conditional loss of the de novo DNA methyltransferase Dnmt3a in mouse excitatory neurons altered expression of synapse-related genes, stunted synapse maturation, and impaired working memory and social interest. Loss of Dnmt3a abolished postnatal accumulation of CG and non-CG DNA methylation, leaving neurons with an unmethylated, fetal-like epigenomic pattern at -140,000 genomic regions. The PRC2-associated histone modification H3K27me3 increased at many of these sites, partially compensating for the loss of DNA methylation. Our data support a dynamic interaction between two fundamental modes of epigenetic repression during postnatal maturation of excitatory neurons, which together confer robustness on neuronal regulation.

neuroscience↗

Single nucleus multi-omics links human cortical cell regulatory genome diversity to disease risk variants

Single-cell technologies enable measure of unique cellular signatures, but are typically limited to a single modality. Computational approaches allow integration of diverse single-cell datasets, but their efficacy is difficult to validate in the absence of authentic multi-omic measurements. To comprehensively assess the molecular phenotypes of single cells in tissues, we devised single-nucleus methylCytosine, Chromatin accessibility and Transcriptome sequencing (snmC2T-seq) and applied it to post-mortem human frontal cortex tissue. We developed a computational framework to validate fine-grained cell types using multi-modal information and assessed the effectiveness of computational integration 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 prediction of cell types with causal roles in disease.

genomics↗

Loss of Dnmt3a dependent methylation in inhibitory neurons impairs neural function through a mechanism that impacts Rett syndrome

Methylated cytosine is an effector of epigenetic gene regulation. In the mammalian brain, the DNA methyltransferase, Dnmt3a, is the sole \"writer\" of atypical non-CpG methylation (mCH), and methyl CpG binding protein 2 (MeCP2) is the only known \"reader\" for mCH. We set out to determine if MeCP2 is the sole reader for Dnmt3a dependent methylation by comparing mice lacking either Dnmt3a or MeCP2 in GABAergic inhibitory neurons. Loss of either the writer or the reader causes overlapping and distinct features from the behavioral to the molecular level. Loss of Dnmt3a results in global loss of mCH and a small subset of mCG sites resulting in more widespread transcriptional alterations and severe neurological dysfunction than seen upon MeCP2 loss. These data indicate that MeCP2 is responsible for reading part of the Dnmt3a dependent methylation in the brain. Importantly, the impact of MeCP2 on genes differentially expressed in both cKO models shows a strong dependence on mCH, but not Dnmt3a dependent mCG, consistent with mCH playing a central role in the pathogenesis of Rett Syndrome.

neuroscience↗

Fast and Accurate Clustering of Single Cell Epigenomes Reveals Cis-Regulatory Elements in Rare Cell Types

Identification of the cis-regulatory elements controlling cell-type specific gene expression patterns is essential for understanding the origin of cellular diversity. Conventional assays to map regulatory elements via open chromatin analysis of primary tissues is hindered by heterogeneity of the samples. Single cell analysis of transposase-accessible chromatin (scATAC-seq) can overcome this limitation. However, the high-level noise of each single cell profile and the large volumes of data could pose unique computational challenges. Here, we introduce SnapATAC, a software package for analyzing scATAC-seq datasets. SnapATAC can efficiently dissect cellular heterogeneity in an unbiased manner and map the trajectories of cellular states. Using the Nystrom method, a sampling technique that generates the low rank embedding for large-scale dataset, SnapATAC can process data from up to a million cells. Furthermore, SnapATAC incorporates existing tools into a comprehensive package for analyzing single cell ATAC-seq dataset. As demonstration of its utility, SnapATAC was applied to 55,592 single-nucleus ATAC-seq profiles from the mouse secondary motor cortex. The analysis revealed [~]370,000 candidate regulatory elements in 31 distinct cell populations in this brain region and inferred candidate transcriptional regulators in each of the cell types.

bioinformatics↗

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.

genomics↗