Improving chromatin-interaction prediction using single-cell open-chromatin profile and making insight about the cis-regulatory landscape of the human brain

AbstractSingle-cell open-chromatin profiles have the potential to reveal the pattern of chromatin-interaction in a cell-type. However, currently available cis-regulatory network prediction methods using single-cell open-chromatin profiles focus more on local chromatin-interactions despite the fact that long-range interaction among genomic sites plays a significant role in gene regulation. Here, we propose a method that predicts both local and long-range interactions among genomic sites using single-cell open chromatin profiles. Using our method’s better sensitivity, we could predict almost 0.7 million interactions among genomic sites across 7 cell-types in the human brain. The chromatin-interactions estimated in the human brain revealed surprising but useful insight about target genes of human-accelerated-elements and disease-associated mutations.

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Improving Chromatin-Interaction Prediction Using Single-Cell Open-Chromatin Profiles and Making Insight Into the Cis-Regulatory Landscape of the Human Brain

Frontiers in Genetics ◽

10.3389/fgene.2021.738194 ◽

2021 ◽

Vol 12 ◽

Author(s):

Neetesh Pandey ◽

Omkar Chandra ◽

Shreya Mishra ◽

Vibhor Kumar

Keyword(s):

Human Brain ◽

Single Cell ◽

Long Range ◽

Target Genes ◽

Interaction Analysis ◽

Chromatin Interaction ◽

Open Chromatin ◽

Cell Type ◽

Range Interaction ◽

Long Range Interactions

Single-cell open-chromatin profiles have the potential to reveal the pattern of chromatin-interaction in a cell type. However, currently available cis-regulatory network prediction methods using single-cell open-chromatin profiles focus more on local chromatin interactions despite the fact that long-range interactions among genomic sites play a significant role in gene regulation. Here, we propose a method that predicts both short and long-range interactions among genomic sites using single-cell open chromatin profiles. Our method, termed as single-cell epigenome based chromatin-interaction analysis (scEChIA) exploits signal imputation and refined L1 regularization. For a few single-cell open-chromatin profiles, scEChIA outperformed other tools even in terms of accuracy of prediction. Using scEChIA, we predicted almost 0.7 million interactions among genomic sites across seven cell types in the human brain. Further analysis revealed cell type for connection between genes and expression quantitative trait locus (eQTL) in the human brain and making insight about target genes of human-accelerated-elements and disease-associated mutations. Our analysis enabled by scEChIA also hints about the possible action of a few transcription factors (TFs), especially through long-range interaction in brain endothelial cells.

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Revealing the transcription factor regulatory context of human specific cortical development using single-cell multi-omics

10.1101/2021.03.19.436193 ◽

2021 ◽

Author(s):

Yan Wu ◽

Blue Lake ◽

Brandon Sos ◽

Song Chen ◽

Thu E. Duong ◽

...

Keyword(s):

Transcription Factor ◽

Human Brain ◽

Single Cell ◽

Target Genes ◽

Cell Types ◽

Chromatin Interaction ◽

Specific Sequence ◽

Enhancer Activity ◽

Genomic Regions ◽

Human Specific

AbstractHuman behaviors are at least partially driven by genomic regions that influence human-specific neurodevelopment. This includes genomic regions undergoing human specific sequence acceleration (Human Accelerated Regions or HARs) and regions showing human-specific enhancer activity (Human Gained Enhancers or HGEs) not present in other primates. However, prior studies on HAR/HGE activities involved mixtures of brain cell types and focused only on putative downstream target genes. Here, we directly measured cell type specific HAR/HGE activity in the developing fetal human brain using two independent single-cell chromatin accessibility datasets with matching single-cell gene expression data. Transcription factor (TF) motif analyses identified upstream TFs binding to HARs/HGEs and identified LHX2, a key regulator of forebrain development, as an active HGE regulator in neuronal progenitors. We integrated our TF motif analyses with published chromatin interaction maps to build detailed regulatory networks where TFs are linked to downstream genes via HARs/HGEs. Through these networks, we identified a potential regulatory role for NFIC in human neuronal progenitor networks via modulating the Notch signaling and cell adhesion pathways. Therefore, by using a single cell multi-omics approach, we were able to capture both the upstream and downstream regulatory context of HARs/HGEs, which may provide a more comprehensive picture of the roles HARs/HGEs play amongst diverse fetal cell types of the developing human brain.

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HiChIP and Hi-C Protocol Optimized for Primary Murine T Cells

Methods and Protocols ◽

10.3390/mps4030049 ◽

2021 ◽

Vol 4 (3) ◽

pp. 49

Author(s):

Tomas Zelenka ◽

Charalampos Spilianakis

Keyword(s):

T Cells ◽

Long Range ◽

Three Dimensional ◽

Cell Types ◽

Range Interaction ◽

Chromatin Interactions ◽

Optimized Protocol ◽

Long Range Interaction ◽

Chromatin Compactness ◽

Detailed Protocol

The functional implications of the three-dimensional genome organization are becoming increasingly recognized. The Hi-C and HiChIP research approaches belong among the most popular choices for probing long-range chromatin interactions. A few methodical protocols have been published so far, yet their reproducibility and efficiency may vary. Most importantly, the high frequency of the dangling ends may dramatically affect the number of usable reads mapped to valid interaction pairs. Additionally, more obstacles arise from the chromatin compactness of certain investigated cell types, such as primary T cells, which due to their small and compact nuclei, impede limitations for their use in various genomic approaches. Here we systematically optimized all the major steps of the HiChIP protocol in T cells. As a result, we reduced the number of dangling ends to nearly zero and increased the proportion of long-range interaction pairs. Moreover, using three different mouse genotypes and multiple biological replicates, we demonstrated the high reproducibility of the optimized protocol. Although our primary goal was to optimize HiChIP, we also successfully applied the optimized steps to Hi-C, given their significant protocol overlap. Overall, we describe the rationale behind every optimization step, followed by a detailed protocol for both HiChIP and Hi-C experiments.

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MUNIn (Multiple cell-type UNifying long-range chromatin Interaction detector): a statistical framework for identifying long-range chromatin interactions from multiple cell types

10.1101/2020.11.12.380782 ◽

2020 ◽

Author(s):

Weifang Liu ◽

Armen Abnousi ◽

Qian Zhang ◽

Yun Li ◽

Ming Hu ◽

...

Keyword(s):

Long Range ◽

Spatial Organization ◽

Critical Role ◽

Cell Types ◽

Chromatin Interaction ◽

Cell Type ◽

Statistical Framework ◽

Chromatin Interactions ◽

The Status ◽

Multiple Cell

AbstractChromatin spatial organization (interactome) plays a critical role in genome function. Deep understanding of chromatin interactome can shed insights into transcriptional regulation mechanisms and human disease pathology. One essential task in the analysis of chromatin interactomic data is to identify long-range chromatin interactions. Existing approaches, such as HiCCUPS, FitHiC/FitHiC2 and FastHiC, are all designed for analyzing individual cell types. None of them accounts for unbalanced sequencing depths and heterogeneity among multiple cell types in a unified statistical framework. To fill in the gap, we have developed a novel statistical framework MUNIn (Multiple cell-type UNifying long-range chromatin Interaction detector) for identifying long-range chromatin interactions from multiple cell types. MUNIn adopts a hierarchical hidden Markov random field (H-HMRF) model, in which the status (peak or background) of each interacting chromatin loci pair depends not only on the status of loci pairs in its neighborhood region, but also on the status of the same loci pair in other cell types. To benchmark the performance of MUNIn, we performed comprehensive simulation studies and real data analysis, and showed that MUNIn can achieve much lower false positive rates for detecting cell-type-specific interactions (33.1 - 36.2%), and much enhanced statistical power for detecting shared peaks (up to 74.3%), compared to uni-cell-type analysis. Our data demonstrated that MUNIn is a useful tool for the integrative analysis of interactomic data from multiple cell types.

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Transcriptome and regulatory maps of decidua-derived stromal cells inform gene discovery in preterm birth

Science Advances ◽

10.1126/sciadv.abc8696 ◽

2020 ◽

Vol 6 (49) ◽

pp. eabc8696

Author(s):

Noboru J. Sakabe ◽

Ivy Aneas ◽

Nicholas Knoblauch ◽

Debora R. Sobreira ◽

Nicole Clark ◽

...

Keyword(s):

Preterm Birth ◽

Stromal Cells ◽

Target Genes ◽

Association Studies ◽

Cell Types ◽

Chromatin Interaction ◽

Open Chromatin ◽

Genome Wide Association Studies ◽

Functional Annotations ◽

Gestational Duration

While a genetic component of preterm birth (PTB) has long been recognized and recently mapped by genome-wide association studies (GWASs), the molecular determinants underlying PTB remain elusive. This stems in part from an incomplete availability of functional genomic annotations in human cell types relevant to pregnancy and PTB. We generated transcriptome (RNA-seq), epigenome (ChIP-seq of H3K27ac, H3K4me1, and H3K4me3 histone modifications), open chromatin (ATAC-seq), and chromatin interaction (promoter capture Hi-C) annotations of cultured primary decidua-derived mesenchymal stromal/stem cells and in vitro differentiated decidual stromal cells and developed a computational framework to integrate these functional annotations with results from a GWAS of gestational duration in 56,384 women. Using these resources, we uncovered additional loci associated with gestational duration and target genes of associated loci. Our strategy illustrates how functional annotations in pregnancy-relevant cell types aid in the experimental follow-up of GWAS for PTB and, likely, other pregnancy-related conditions.

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Efficient pre-processing of Single-cell ATAC-seq data

10.1101/2021.12.08.471788 ◽

2021 ◽

Author(s):

Fan Gao ◽

Lior Pachter

Keyword(s):

Human Brain ◽

Single Cell ◽

Healthy Adult ◽

Chromatin Interaction ◽

Open Chromatin ◽

Cell Type ◽

Cell Groups ◽

Cell Type Specific ◽

Interaction Traces ◽

Regulatory Landscape

The primary tool currently used to pre-process 10X Chromium single-cell ATAC-seq data is Cell Ranger, which can take very long to run on standard datasets. To facilitate rapid pre-processing that enables reproducible workflows, we present a suite of tools called scATAK for pre-processing single-cell ATAC-seq data that is 18 times faster than Cell Ranger on human samples, and that uses 33% less RAM when 8 CPU threads are used. Our tool can also calculate chromatin interaction potential matrices, and generate open chromatin signals and interaction traces for cell groups. We demonstrate the utility of scATAK in an exploration of the chromatin regulatory landscape of a healthy adult human brain and show that it can reveal cell-type-specific features. scATAK is available at https://pachterlab.github.io/scATAK/.

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Single-cell atlas of early human brain development highlights heterogeneity of human neuroepithelial cells and early radial glia

Nature Neuroscience ◽

10.1038/s41593-020-00794-1 ◽

2021 ◽

Author(s):

Ugomma C. Eze ◽

Aparna Bhaduri ◽

Maximilian Haeussler ◽

Tomasz J. Nowakowski ◽

Arnold R. Kriegstein

Keyword(s):

Human Brain ◽

Brain Development ◽

Single Cell ◽

Radial Glia ◽

Cortical Development ◽

Cell Types ◽

Human Cortex ◽

Early Stages ◽

Human Brain Development ◽

Neuroepithelial Cells

AbstractThe human cortex comprises diverse cell types that emerge from an initially uniform neuroepithelium that gives rise to radial glia, the neural stem cells of the cortex. To characterize the earliest stages of human brain development, we performed single-cell RNA-sequencing across regions of the developing human brain, including the telencephalon, diencephalon, midbrain, hindbrain and cerebellum. We identify nine progenitor populations physically proximal to the telencephalon, suggesting more heterogeneity than previously described, including a highly prevalent mesenchymal-like population that disappears once neurogenesis begins. Comparison of human and mouse progenitor populations at corresponding stages identifies two progenitor clusters that are enriched in the early stages of human cortical development. We also find that organoid systems display low fidelity to neuroepithelial and early radial glia cell types, but improve as neurogenesis progresses. Overall, we provide a comprehensive molecular and spatial atlas of early stages of human brain and cortical development.

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Human PRE-PIK3C2B exhibits long-range intra- and inter-chromosomal interactions with genomic regions enriched in repressive marks

10.1101/2020.11.11.378745 ◽

2020 ◽

Author(s):

Jayant Maini ◽

Ankit Kumar Pathak ◽

Kausik Bhattacharyya ◽

Narendra Kumar ◽

Ankita Narang ◽

...

Keyword(s):

Long Range ◽

Meta Analysis ◽

Range Interaction ◽

Dual Nature ◽

Polycomb Response Element ◽

Chromatin Interactions ◽

Long Range Interaction ◽

Intergenic Regions ◽

Genomic Regions ◽

Transcriptional Start Sites

AbstractHuman PRE-PIK3C2B is a dual nature polycomb response element that interacts with both polycomb as well as trithorax members. In the current study, using 4C-Seq (Capturing Circular Chromosomal Conformation-Sequencing), we identified long-range chromatin interactions associated with PRE-PIK3C2B and validated them with 3C-PCR. We identified both intra-as well as inter-chromosomal interactions, a large proportion of which were found to be closely distributed around transcriptional start sites (TSS). A significant number of interactions were also found to be associated with heterochromatic regions. Meta-analysis of ENCODE ChIP-Seq data identified an overall enrichment of YY1, CTCF as well as histone modification such as H3K4me3 and H3K27me marks in different cell lines. Almost 90% interactions were derived from either intronic or intergenic regions. among which large proportions of intronic interactors were either unique sequences or LINE/SINE derived. In case of intergenic interactions, majority of the interaction were associated with LINE/SINE repeats. We further found that genes proximal to the interactor sequences were co-expressed, they showed reduced expression. To the best of our knowledge this is one of the early demonstrations of long-range interaction of PRE sequences in human genome.

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Localization of migraine susceptibility genes in human brain by single-cell RNA sequencing

Cephalalgia ◽

10.1177/0333102418762476 ◽

2018 ◽

Vol 38 (13) ◽

pp. 1976-1983 ◽

Cited By ~ 5

Author(s):

William Renthal

Keyword(s):

Human Brain ◽

Single Cell ◽

Rna Sequencing ◽

Expression Profiles ◽

Cell Types ◽

Susceptibility Genes ◽

Brain Cell ◽

Cell Type ◽

Single Cell Rna Sequencing ◽

Brain Cell Types

Background Migraine is a debilitating disorder characterized by severe headaches and associated neurological symptoms. A key challenge to understanding migraine has been the cellular complexity of the human brain and the multiple cell types implicated in its pathophysiology. The present study leverages recent advances in single-cell transcriptomics to localize the specific human brain cell types in which putative migraine susceptibility genes are expressed. Methods The cell-type specific expression of both familial and common migraine-associated genes was determined bioinformatically using data from 2,039 individual human brain cells across two published single-cell RNA sequencing datasets. Enrichment of migraine-associated genes was determined for each brain cell type. Results Analysis of single-brain cell RNA sequencing data from five major subtypes of cells in the human cortex (neurons, oligodendrocytes, astrocytes, microglia, and endothelial cells) indicates that over 40% of known migraine-associated genes are enriched in the expression profiles of a specific brain cell type. Further analysis of neuronal migraine-associated genes demonstrated that approximately 70% were significantly enriched in inhibitory neurons and 30% in excitatory neurons. Conclusions This study takes the next step in understanding the human brain cell types in which putative migraine susceptibility genes are expressed. Both familial and common migraine may arise from dysfunction of discrete cell types within the neurovascular unit, and localization of the affected cell type(s) in an individual patient may provide insight into to their susceptibility to migraine.

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STAB: a spatio-temporal cell atlas of the human brain

Nucleic Acids Research ◽

10.1093/nar/gkaa762 ◽

2020 ◽

Vol 49 (D1) ◽

pp. D1029-D1037

Author(s):

Liting Song ◽

Shaojun Pan ◽

Zichao Zhang ◽

Longhao Jia ◽

Wei-Hua Chen ◽

...

Keyword(s):

Human Brain ◽

Single Cell ◽

Temporal Dynamics ◽

Cell Types ◽

Brain Regions ◽

Molecular Characteristics ◽

Great Effort ◽

Brain Functions ◽

Spatio Temporal ◽

The Brain

Abstract The human brain is the most complex organ consisting of billions of neuronal and non-neuronal cells that are organized into distinct anatomical and functional regions. Elucidating the cellular and transcriptome architecture underlying the brain is crucial for understanding brain functions and brain disorders. Thanks to the single-cell RNA sequencing technologies, it is becoming possible to dissect the cellular compositions of the brain. Although great effort has been made to explore the transcriptome architecture of the human brain, a comprehensive database with dynamic cellular compositions and molecular characteristics of the human brain during the lifespan is still not available. Here, we present STAB (a Spatio-Temporal cell Atlas of the human Brain), a database consists of single-cell transcriptomes across multiple brain regions and developmental periods. Right now, STAB contains single-cell gene expression profiling of 42 cell subtypes across 20 brain regions and 11 developmental periods. With STAB, the landscape of cell types and their regional heterogeneity and temporal dynamics across the human brain can be clearly seen, which can help to understand both the development of the normal human brain and the etiology of neuropsychiatric disorders. STAB is available at http://stab.comp-sysbio.org.

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