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Lucero, J.

Publications and source records attributed to Lucero, J..

12 recordsLinked to original sources

Single-Cell Atlas of Transcription and Chromatin States Reveals Regulatory Programs in the Human Brain

Directly measuring chromatin states alongside transcription is essential for understanding how cell-type-specific regulatory programs are established and maintained in the adult human brain. We present a large-scale single-cell multimodal atlas generated by jointly profiling transcriptome with active (H3K27ac) and repressive (H3K27me3) histone modifications across 18 brain regions. We profile >750,000 nuclei spanning 160 cell types and integrate these data with chromatin accessibility, DNA methylation, 3D genome architecture, and spatial transcriptome. This framework annotates >500,000 regulatory elements and resolves cell-type-specific chromatin states. We link enhancers to target genes, infer gene regulatory networks, and classify chromatin interactions, revealing neuron-enriched long-range Polycomb repression of developmental genes. Integrating these maps with GWAS data and sequence-based model prioritizes noncoding variants, effector genes, and vulnerable cell types for neuropsychiatric disorders. Finally, cross-species comparisons show conserved activation but more divergent repression. Together, this study provides a functional reference for interpreting noncoding variants, epigenetic memory, and brain organization. HIGHLIGHTSO_LIJoint single-cell profiling of transcriptomes with active or repressive histone modification in >750,000 nuclei across adult human brain. C_LIO_LIChromatin state annotation of >500,000 candidate cis-regulatory elements distinguishes active enhancers from accessible and Polycomb-repressed regions. C_LIO_LICell-type-resolved regulatory networks and sequence-based deep learning model prioritize functional neuropsychiatric risk variants. C_LIO_LISpatial epigenomic imputation reveals laminar layer-specific Polycomb repression programs. C_LIO_LIIntegration with 3D genome architecture reveals neuron-specific super long-range chromatin loops silencing early developmental genes. C_LIO_LIEvolutionary analysis uncovers conserved active regulatory grammar but divergent repressive landscape. C_LI

genomics↗

Single cell and spatial characterization of the human pancreas reveals drivers of beta cell dysfunction in cystic fibrosis

Cystic fibrosis (CF) causes severely damaged pancreas morphology and results in high rates of cystic fibrosis-related diabetes (CFRD), but the cellular pathways and regulatory programs driving CFRD pathogenesis in the pancreas are not understood. In this study, we performed single cell multiomic and spatial profiling of 2.04M cells in the pancreas from 23 non-disease and CF donors and defined regulatory programs and tissue niches of specific cell types and sub-types in CF. A high-mucin sub-type of ductal cells had relatively preserved abundance, altered localization and up-regulated stress, secretion and pro-fibrotic activity in CF, and conventional ductal cells showed evidence for transition to the high-mucin state. Increased inflammatory and fibrotic pathway activity in CF was linked to closer proximity and crosstalk between immune and stellate cells in specific niches. Beta cells had extensive genomic changes in CF, including increased stress and insulin secretion-related processes, and these changes were broadly distinct from those in type 1 and type 2 diabetes. Islets in CF preferentially localized near large adipose tissue and collagen structures, and both areas were strongly linked to beta cell loss in CF due to signaling from adipocytes, macrophages, stellate, and high-mucin ductal cells. Overall, our results reveal cellular drivers of pancreatic dysfunction in CF and offer new in-roads to preserving beta cells in CFRD.

genomics↗

Single-cell DNA Methylome and 3D Multi-omic Atlas of the Adult Mouse Brain

Cytosine DNA methylation is essential in brain development and has been implicated in various neurological disorders. A comprehensive understanding of DNA methylation diversity across the entire brain in the context of the brains 3D spatial organization is essential for building a complete molecular atlas of brain cell types and understanding their gene regulatory landscapes. To this end, we employed optimized single-nucleus methylome (snmC-seq3) and multi-omic (snm3C-seq1) sequencing technologies to generate 301,626 methylomes and 176,003 chromatin conformation/methylome joint profiles from 117 dissected regions throughout the adult mouse brain. Using iterative clustering and integrating with companion whole-brain transcriptome and chromatin accessibility datasets, we constructed a methylation-based cell type taxonomy that contains 4,673 cell groups and 261 cross-modality-annotated subclasses. We identified millions of differentially methylated regions (DMRs) across the genome, representing potential gene regulation elements. Notably, we observed spatial cytosine methylation patterns on both genes and regulatory elements in cell types within and across brain regions. Brain-wide multiplexed error-robust fluorescence in situ hybridization (MERFISH2) data validated the association of this spatial epigenetic diversity with transcription and allowed the mapping of the DNA methylation and topology information into anatomical structures more precisely than our dissections. Furthermore, multi-scale chromatin conformation diversities occur in important neuronal genes, highly associated with DNA methylation and transcription changes. Brain-wide cell type comparison allowed us to build a regulatory model for each gene, linking transcription factors, DMRs, chromatin contacts, and downstream genes to establish regulatory networks. Finally, intragenic DNA methylation and chromatin conformation patterns predicted alternative gene isoform expression observed in a companion whole-brain SMART-seq3 dataset. Our study establishes the first brain-wide, single-cell resolution DNA methylome and 3D multi-omic atlas, providing an unparalleled resource for comprehending the mouse brains cellular-spatial and regulatory genome diversity.

genomics↗

Epigenomic complexity of the human brain revealed by single-cell DNA methylomes and 3D genome structures

Delineating the gene regulatory programs underlying complex cell types is fundamental for understanding brain functions in health and disease. Here, we comprehensively examine human brain cell epigenomes by probing DNA methylation and chromatin conformation at single-cell resolution in over 500,000 cells from 46 brain regions. We identified 188 cell types and characterized their molecular signatures. Integrative analyses revealed concordant changes in DNA methylation, chromatin accessibility, chromatin organization, and gene expression across cell types, cortical areas, and basal ganglia structures. With these resources, we developed scMCodes that reliably predict brain cell types using their methylation status at select genomic sites. This multimodal epigenomic brain cell atlas provides new insights into the complexity of cell type-specific gene regulation in the adult human brain.

neuroscience↗

A comparative atlas of single-cell chromatin accessibility in the human brain

The human brain contains an extraordinarily diverse set of neuronal and glial cell types. Recent advances in single cell transcriptomics have begun to delineate the cellular heterogeneity in different brain regions, but the transcriptional regulatory programs responsible for the identity and function of each brain cell type remain to be defined. Here, we carried out single nucleus ATAC-seq analysis to probe the open chromatin landscape from over 1.1 million cells in 42 brain regions of three neurotypical adult donors. Integrative analysis of the resulting data identified 107 distinct cell types and revealed the cell-type-specific usage of 544,735 candidate cis-regulatory DNA elements (cCREs) in the human genome. Nearly 1/3 of them displayed sequence conservation as well as chromatin accessibility in the mouse brain. On the other hand, nearly 40% cCREs were human specific, with chromatin accessibility associated with species-restricted gene expression. Interestingly, these human specific cCREs were enriched for distinct families of retrotransposable elements, which displayed cell-type-specific chromatin accessibility. We uncovered strong associations between specific brain cell types and neuropsychiatric disorders. We futher developed deep learning models to predict regulatory function of non-coding disease risk variants.

neuroscience↗

Inhibition of Lipopolysaccharide E. coli-induced acute lung injury by extracted Antidesma bunius (L.) Spreng fruits as compared to Fluticasone Propionate, a corticosteroid

The hallmark of Acute Lung Injury/Acute Respiratory Distress Syndrome (ALI/ARDS) is inflammation-induced alveolar-vascular barrier destruction and neutrophilic infiltration that leads to the formation of cytokines and oxygen radicals. The objective of the study is to investigate the protective and toxicological effects of Antidesma bunius (L.) Spreng [Bignay] in murine model of Lipopolysaccharide E. coli (LPS)-induced ALI and compared with Fluticasone Propionate (FP), a synthetic corticosteroid. We showed that extracted Bignay fruits have high amount of phenols, steroids and flavonoids but insignificant amount of heavy metals and aflatoxins. BALB/c mice of either sex were divided into 4 groups in the ALI mouse model; Group 1: vehicle control; Group 2: LPS alone; Group 3: Bignay + LPS; and Group 4: FP + LPS. Bignay and FP were administered via intraperitoneal injection while LPS was given intra-tracheally. Biomarkers of ALI such as total lung inflammatory cell count, total lung protein content, lung edema and interleukin-6 (IL-6) secretion were measured 24 hrs after vehicle control or LPS treatment. Compared to vehicle controls, LPS caused significant increased in all measured biomarkers of ALI in samples collected from bronchoalveolar lavage fluid and were significantly attenuated by Bignay fruit extract or FP. Pulmonary vascular leakage caused by LPS was also evaluated after injection with Evans blue dye, an indication of lung injury. Extracted Bignay fruits or FP when given to mice 2 hrs after LPS administration substantially decreased the pulmonary vascular leak. Our findings are the first evidence demonstrating the preventive and non-toxic effects of extracted Bignay fruits in a murine model of LPS-induced ALI. The results could be attributed to the presence of active secondary metabolites such as flavonoids, phenols and steroids. It is also evident that extracted Bignay fruits are as effective as FP, well-established steroid, in blocking the biomarkers of ALI caused by LPS.

pharmacology and toxicology↗

An Atlas of Gene Regulatory Elements in Adult Mouse Cerebrum

The mammalian cerebrum performs high level sensory, motor control and cognitive functions through highly specialized cortical networks and subcortical nuclei. Recent surveys of mouse and human brains with single cell transcriptomics1-3 and high-throughput imaging technologies4,5 have uncovered hundreds of neuronal cell types and a variety of non-neuronal cell types distributed in different brain regions, but the cell-type-specific transcriptional regulatory programs responsible for the unique identity and function of each brain cell type have yet to be elucidated. Here, we probe the accessible chromatin in >800,000 individual nuclei from 45 regions spanning the adult mouse isocortex, olfactory bulb, hippocampus and cerebral nuclei, and use the resulting data to define 491,818 candidate cis regulatory DNA elements in 160 distinct sub-types. We link a significant fraction of them to putative target genes expressed in diverse cerebral cell types and uncover transcriptional regulators involved in a broad spectrum of molecular and cellular pathways in different neuronal and glial cell populations. Our results provide a foundation for comprehensive analysis of gene regulatory programs of the mammalian brain and assist in the interpretation of non-coding risk variants associated with various neurological disease and traits in humans. To facilitate the dissemination of information, we have set up a web portal (http://catlas.org/mousebrain).

neuroscience↗

DNA Methylation Atlas of the Mouse Brain at Single-Cell Resolution

Mammalian brain cells are remarkably diverse in gene expression, anatomy, and function, yet the regulatory DNA landscape underlying this extensive heterogeneity is poorly understood. We carried out a comprehensive assessment of the epigenomes of mouse brain cell types by applying single nucleus DNA methylation sequencing to profile 110,294 nuclei 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, an artificial neural network model was constructed that precisely predicts single neuron cell-type identity and brain area spatial location. Integration of high-resolution DNA methylomes with single-nucleus chromatin accessibility data allowed prediction of high-confidence enhancer-gene interactions for all identified cell types, which were subsequently validated by cell-type-specific chromatin conformation capture experiments. 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 brain.

genomics↗

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↗