scholarly journals Stable unmethylated DNA demarcates expressed genes and their cis-regulatory space in plant genomes

2020 ◽  
Vol 117 (38) ◽  
pp. 23991-24000 ◽  
Author(s):  
Peter A. Crisp ◽  
Alexandre P. Marand ◽  
Jaclyn M. Noshay ◽  
Peng Zhou ◽  
Zefu Lu ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Developmental Stages ◽  
Chromatin Modification ◽  
Leaf Tissue ◽  
Cell Types ◽  
Regulatory Elements ◽  
Chromatin Accessibility ◽  
Functional Genes ◽  
Specific Cell ◽  
Chromatin Interactions

The genomic sequences of crops continue to be produced at a frenetic pace. It remains challenging to develop complete annotations of functional genes and regulatory elements in these genomes. Chromatin accessibility assays enable discovery of functional elements; however, to uncover the full portfolio of cis-elements would require profiling of many combinations of cell types, tissues, developmental stages, and environments. Here, we explore the potential to use DNA methylation profiles to develop more complete annotations. Using leaf tissue in maize, we define ∼100,000 unmethylated regions (UMRs) that account for 5.8% of the genome; 33,375 UMRs are found greater than 2 kb from genes. UMRs are highly stable in multiple vegetative tissues, and they capture the vast majority of accessible chromatin regions from leaf tissue. However, many UMRs are not accessible in leaf, and these represent regions with potential to become accessible in specific cell types or developmental stages. These UMRs often occur near genes that are expressed in other tissues and are enriched for binding sites of transcription factors. The leaf-inaccessible UMRs exhibit unique chromatin modification patterns and are enriched for chromatin interactions with nearby genes. The total UMR space in four additional monocots ranges from 80 to 120 megabases, which is remarkably similar considering the range in genome size of 271 megabases to 4.8 gigabases. In summary, based on the profile from a single tissue, DNA methylation signatures provide powerful filters to distill large genomes down to the small fraction of putative functional genes and regulatory elements.

scholarly journals Stable unmethylated DNA demarcates expressed genes and their cis-regulatory space in plant genomes

2020 ◽  
Author(s):  
Peter A Crisp ◽  
Alexandre P Marand ◽  
Jaclyn M Noshay ◽  
Peng Zhou ◽  
Zefu Lu ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Developmental Stages ◽  
Chromatin Modification ◽  
Leaf Tissue ◽  
Cell Types ◽  
Regulatory Elements ◽  
Functional Genes ◽  
Specific Cell ◽  
Vegetative Development ◽  
A Genome

AbstractThe genomic sequences of crops continue to be produced at a frenetic pace. However, it remains challenging to develop complete annotations of functional genes and regulatory elements in these genomes. Here, we explore the potential to use DNA methylation profiles to develop more complete annotations. Using leaf tissue in maize, we define ∼100,000 unmethylated regions (UMRs) that account for 5.8% of the genome; 33,375 UMRs are found greater than 2 kilobase pairs from genes. UMRs are highly stable in multiple vegetative tissues and they capture the vast majority of accessible chromatin regions from leaf tissue. However, many UMRs are not accessible in leaf (leaf-iUMRs) and these represent a set of genomic regions with potential to become accessible in specific cell types or developmental stages. Leaf-iUMRs often occur near genes that are expressed in other tissues and are enriched for transcription factor (TF) binding sites of TFs that are also not expressed in leaf tissue. The leaf-iUMRs exhibit unique chromatin modification patterns and are enriched for chromatin interactions with nearby genes. The total UMRs space in four additional monocots ranges from 80-120 megabases, which is remarkably similar considering the range in genome size of 271 megabases to 4.8 gigabases. In summary, based on the profile from a single tissue, DNA methylation signatures pinpoint both accessible regions and regions poised to become accessible or expressed in other tissues. UMRs provide powerful filters to distill large genomes down to the small fraction of putative functional genes and regulatory elements.Significance StatementCrop genomes can be very large with many repetitive elements and pseudogenes. Distilling a genome down to the relatively small fraction of regions that are functionally valuable for trait variation can be like looking for needles in a haystack. The unmethylated regions in a genome are highly stable during vegetative development and can reveal the locations of potentially expressed genes or cis-regulatory elements. This approach provides a framework towards complete annotation of genes and discovery of cis-regulatory elements using methylation profiles from only a single tissue.

scholarly journals Deciphering programs of transcriptional regulation by combined deconvolution of multiple omics layers

2017 ◽  
Author(s):  
Daniel Hüebschmann ◽  
Nils Kurzawa ◽  
Sebastian Steinhauser ◽  
Philipp Rentzsch ◽  
Stephen Krämer ◽  
...  
Keyword(s):  
Gene Expression ◽  
Developmental Stages ◽  
Cell Types ◽  
Regulatory Elements ◽  
Chromatin Accessibility ◽  
Cell Type ◽  
Specific Expression ◽  
Input Size ◽  
Human Blood Cells ◽  
Cell Type Specific Expression

AbstractMetazoans are crucially dependent on multiple layers of gene regulatory mechanisms which allow them to control gene expression across developmental stages, tissues and cell types. Multiple recent research consortia have aimed to generate comprehensive datasets to profile the activity of these cell type- and condition-specific regulatory landscapes across many different cell lines and primary cells. However, extraction of genes or regulatory elements specific to certain entities from these datasets remains challenging. We here propose a novel method based on non-negative matrix factorization for disentangling and associating huge multi-assay datasets including chromatin accessibility and gene expression data. Taking advantage of implementations of NMF algorithms in the GPU CUDA environment full datasets composed of tens of thousands of genes as well as hundreds of samples can be processed without the need for prior feature selection to reduce the input size. Applying this framework to multiple layers of genomic data derived from human blood cells we unravel mechanisms of regulation of cell type-specific expression in T-cells and monocytes.

scholarly journals Selective demethylation of two CpG sites causes postnatal activation of the Dao gene and consequent removal of d-serine within the mouse cerebellum

2019 ◽  
Vol 11 (1) ◽  
Author(s):  
Mariella Cuomo ◽  
Simona Keller ◽  
Daniela Punzo ◽  
Tommaso Nuzzo ◽  
Ornella Affinito ◽  
...  
Keyword(s):  
Amino Acids ◽  
Dna Methylation ◽  
Single Molecule ◽  
Developmental Stages ◽  
Cell Types ◽  
Epigenetic Modifications ◽  
Specific Cell ◽  
Cpg Sites ◽  
Brain Levels ◽  
Mouse Cerebellum

Abstract Background Programmed epigenetic modifications occurring at early postnatal brain developmental stages may have a long-lasting impact on brain function and complex behavior throughout life. Notably, it is now emerging that several genes that undergo perinatal changes in DNA methylation are associated with neuropsychiatric disorders. In this context, we envisaged that epigenetic modifications during the perinatal period may potentially drive essential changes in the genes regulating brain levels of critical neuromodulators such as d-serine and d-aspartate. Dysfunction of this fine regulation may contribute to the genesis of schizophrenia or other mental disorders, in which altered levels of d-amino acids are found. We recently demonstrated that Ddo, the d-aspartate degradation gene, is actively demethylated to ultimately reduce d-aspartate levels. However, the role of epigenetics as a mechanism driving the regulation of appropriate d-ser levels during brain development has been poorly investigated to date. Methods We performed comprehensive ultradeep DNA methylation and hydroxymethylation profiling along with mRNA expression and HPLC-based d-amino acids level analyses of genes controlling the mammalian brain levels of d-serine and d-aspartate. DNA methylation changes occurring in specific cerebellar cell types were also investigated. We conducted high coverage targeted bisulfite sequencing by next-generation sequencing and single-molecule bioinformatic analysis. Results We report consistent spatiotemporal modifications occurring at the Dao gene during neonatal development in a specific brain region (the cerebellum) and within specific cell types (astrocytes) for the first time. Dynamic demethylation at two specific CpG sites located just downstream of the transcription start site was sufficient to strongly activate the Dao gene, ultimately promoting the complete physiological degradation of cerebellar d-serine a few days after mouse birth. High amount of 5′-hydroxymethylcytosine, exclusively detected at relevant CpG sites, strongly evoked the occurrence of an active demethylation process. Conclusion The present investigation demonstrates that robust and selective demethylation of two CpG sites is associated with postnatal activation of the Dao gene and consequent removal of d-serine within the mouse cerebellum. A single-molecule methylation approach applied at the Dao locus promises to identify different cell-type compositions and functions in different brain areas and developmental stages.

scholarly journals Incorporating Gene Expression in Genome-wide Prediction of Chromatin Accessibility via Deep Learning

2019 ◽  
Author(s):  
Qiao Liu ◽  
Wing Hung Wong ◽  
Rui Jiang
Keyword(s):  
Deep Learning ◽  
Human Genome ◽  
Cell Types ◽  
Regulatory Elements ◽  
Chromatin Accessibility ◽  
Superior Performance ◽  
Specific Cell ◽  
Cell Type ◽  
Transcriptome Profile ◽  
Cell Type Specific

AbstractRegulatory elements (REs) in human genome are major sites of non-coding transcription which lack adequate interpretation. Although computational approaches have been complementing high-throughput biological experiments towards the annotation of the human genome, it remains a big challenge to systematically and accurately characterize REs in the context of a specific cell type. To address this problem, we proposed DeepCAGE, an deep learning framework that incorporates transcriptome profile of human transcription factors (TFs) for accurately predicting the activities of cell type-specific REs. Our approach automatically learns the regulatory code of input DNA sequence incorporated with cell type-specific TFs expression. In a series of systematic comparison with existing methods, we show the superior performance of our model in not only the classification of accessible regions, but also the regression of DNase-seq signals. A typical scenario of usage for our method is to predict the activities of REs in novel cell types, especially where the chromatin accessibility data is not available. To sum up, our study provides a fascinating insight into disclosing complex regulatory mechanism by integrating transcriptome profile of human TFs.

scholarly journals Large organized chromatin lysine domains help distinguish primitive from differentiated cell populations

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Seyed Ali Madani Tonekaboni ◽  
Benjamin Haibe-Kains ◽  
Mathieu Lupien
Keyword(s):  
Transposable Elements ◽  
Histone Modifications ◽  
Cell Types ◽  
Regulatory Elements ◽  
Cell Populations ◽  
Genomic Features ◽  
Differentiated Cells ◽  
Chromatin Interactions ◽  
Topologically Associating Domains ◽  
Highly Expressed Genes

AbstractThe human genome is partitioned into a collection of genomic features, inclusive of genes, transposable elements, lamina interacting regions, early replicating control elements and cis-regulatory elements, such as promoters, enhancers, and anchors of chromatin interactions. Uneven distribution of these features within chromosomes gives rise to clusters, such as topologically associating domains (TADs), lamina-associated domains, clusters of cis-regulatory elements or large organized chromatin lysine (K) domains (LOCKs). Here we show that LOCKs from diverse histone modifications discriminate primitive from differentiated cell types. Active LOCKs (H3K4me1, H3K4me3 and H3K27ac) cover a higher fraction of the genome in primitive compared to differentiated cell types while repressive LOCKs (H3K9me3, H3K27me3 and H3K36me3) do not. Active LOCKs in differentiated cells lie proximal to highly expressed genes while active LOCKs in primitive cells tend to be bivalent. Genes proximal to bivalent LOCKs are minimally expressed in primitive cells. Furthermore, bivalent LOCKs populate TAD boundaries and are preferentially bound by regulators of chromatin interactions, including CTCF, RAD21 and ZNF143. Together, our results argue that LOCKs discriminate primitive from differentiated cell populations.

scholarly journals In vivotissue-specific chromatin profiling inDrosophila melanogasterusing GFP-tagged nuclei

2021 ◽  
Author(s):  
Juan Jauregui-Lozano ◽  
Kimaya Bakhle ◽  
Vikki M. Weake
Keyword(s):  
Cell Types ◽  
Chromatin Accessibility ◽  
Chromatin State ◽  
Specific Cell ◽  
Histone Marks ◽  
The Many ◽  
Chromatin Profiling ◽  
Photoreceptor Neurons ◽  
Multicellular Organisms

AbstractThe chromatin landscape defines cellular identity in multicellular organisms with unique patterns of DNA accessibility and histone marks decorating the genome of each cell type. Thus, profiling the chromatin state of different cell types in an intact organism under disease or physiological conditions can provide insight into how chromatin regulates cell homeostasisin vivo. To overcome the many challenges associated with characterizing chromatin state in specific cell types, we developed an improved approach to isolateDrosophilanuclei tagged with GFP expressed under Gal4/UAS control. Using this protocol, we profiled chromatin accessibility using Omni-ATAC, and examined the distribution of histone marks using ChIP-seq and CUT&Tag in adult photoreceptor neurons. We show that the chromatin landscape of photoreceptors reflects the transcriptional state of these cells, demonstrating the quality and reproducibility of our approach for profiling the transcriptome and epigenome of specific cell types inDrosophila.

scholarly journals Adeno-Associated Virus Technologies and Methods for Targeted Neuronal Manipulation

2019 ◽  
Author(s):  
Leila Haery ◽  
Benjamin E. Deverman ◽  
Katherine Matho ◽  
Ali Cetin ◽  
Kenton Woodard ◽  
...  
Keyword(s):  
Viral Vectors ◽  
Cell Types ◽  
Regulatory Elements ◽  
Specific Cell ◽  
Specific Expression ◽  
Adeno Associated Virus ◽  
Cell Type Specific Expression ◽  
Cell Type Specific ◽  
And Function ◽  
Novel Applications

AbstractCell-type-specific expression of molecular tools and sensors is critical to construct circuit diagrams and to investigate the activity and function of neurons within the nervous system. Strategies for targeted manipulation include combinations of classical genetic tools such as Cre/loxP and Flp/FRT, use of cis-regulatory elements, targeted knock-in transgenic mice, and gene delivery by AAV and other viral vectors. The combination of these complex technologies with the goal of precise neuronal targeting is a challenge in the lab. This report will discuss the theoretical and practical aspects of combining current technologies and establish best practices for achieving targeted manipulation of specific cell types. Novel applications and tools, as well as areas for development, will be envisioned and discussed.

scholarly journals CellWalker integrates single-cell and bulk data to resolve regulatory elements across cell types in complex tissues

2019 ◽  
Author(s):  
Pawel F. Przytycki ◽  
Katherine S. Pollard
Keyword(s):  
Single Cell ◽  
Cell Types ◽  
Regulatory Elements ◽  
Cell Labeling ◽  
Open Chromatin ◽  
Specific Cell ◽  
Rna Seq ◽  
Data Types ◽  
Bulk Data ◽  
Cell Type Specific

Single-cell and bulk genomics assays have complementary strengths and weaknesses, and alone neither strategy can fully capture regulatory elements across the diversity of cells in complex tissues. We present CellWalker, a method that integrates single-cell open chromatin (scATAC-seq) data with gene expression (RNA-seq) and other data types using a network model that simultaneously improves cell labeling in noisy scATAC-seq and annotates cell-type specific regulatory elements in bulk data. We demonstrate CellWalker’s robustness to sparse annotations and noise using simulations and combined RNA-seq and ATAC-seq in individual cells. We then apply CellWalker to the developing brain. We identify cells transitioning between transcriptional states, resolve enhancers to specific cell types, and observe that autism and other neurological traits can be mapped to specific cell types through their enhancers.

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

2020 ◽  
Author(s):  
Hanqing Liu ◽  
Jingtian Zhou ◽  
Wei Tian ◽  
Chongyuan Luo ◽  
Anna Bartlett ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Mouse Brain ◽  
Spatial Organization ◽  
Brain Area ◽  
Cell Types ◽  
Regulatory Elements ◽  
Mammalian Brain ◽  
Open Chromatin ◽  
Cell Type ◽  
Single Nucleus

SummaryMammalian 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.

scholarly journals Enhancer-dependence of gene expression increases with developmental age

2019 ◽  
Author(s):  
Wenqing Cai ◽  
Jialiang Huang ◽  
Qian Zhu ◽  
Bin E. Li ◽  
Davide Seruggia ◽  
...  
Keyword(s):  
Gene Expression ◽  
Developmental Stages ◽  
Chromatin Accessibility ◽  
List Type ◽  
Primary Cells ◽  
Embryonic Cells ◽  
Human Origin ◽  
Chromatin Interactions ◽  
Developmental Age ◽  
Specific Control

SummaryHow overall principles of gene regulation (the “logic”) may change during ontogeny is largely unexplored. We compared transcriptomic, epigenomic and topological profiles in embryonic (EryP) and adult (EryD) erythroblasts. Despite reduced chromatin accessibility compared to EryP, distal chromatin of EryD is enriched in H3K27ac, Gata1 and Myb occupancy. In contrast to EryP-specific genes, which exhibit promoter-centric regulation through Gata1, EryD-specific genes employ distal enhancers for long-range regulation through enhancer-promoter looping, confirmed by Gata1 HiChIP. Genome editing demonstrated distal enhancers are required for gene expression in EryD but not in EryP. Applying a metric for enhancer-dependence of transcription, we observed a progressive reliance on enhancer control with increasing age of ontogeny among diverse primary cells and tissues of mouse and human origin. Our findings highlight fundamental and conserved differences in regulatory logic at distinct developmental stages, characterized by simpler promoter-centric regulation in embryonic cells and combinatorial enhancer-driven control in adult cells.HighlightsRegulation of embryonic-specific erythroid genes is promoter-centric through Gata1Adult-specific control is combinatorial enhancer-driven and requires MybAdult specific genes have increased enhancer-promoter chromatin interactionsEnhancer-dependence increases progressively with increasing developmental age

Sign in / Sign up

Export Citation Format

Share Document