Large-scale determination and characterization of cell type-specific regulatory elements in the human genome

Mapping Intimacies ◽

10.1101/176602 ◽

2017 ◽

Author(s):

Can Wang ◽

Shihua Zhang

Keyword(s):

Histone Modifications ◽

Large Scale ◽

Chromatin Modification ◽

Cell Types ◽

Regulatory Elements ◽

Cell Type ◽

Cell Identity ◽

Functional Roles ◽

Cancer Occurrence ◽

Cell Type Specific

AbstractHistone modifications have been widely elucidated to play vital roles in gene regulation and cell identity. The Roadmap Epigenomics Consortium generated a reference catalogue of several key histone modifications across >100s of human cell types and tissues. Decoding these epigenomes into functional regulatory elements is a challenging task in computational biology. To this end, we adopted a differential chromatin modification analysis framework to comprehensively determine and characterize cell type-specific regulatory elements (CSREs) and their histone modification codes in the human epigenomes of five histone modifications across 127 tissues or cell types. The CSREs show significant relevance with cell type-specific biological functions and diseases and cell identity. Clustering of CSREs with their specificity signals reveals diverse histone codes, demonstrating the diversity of functional roles of CSREs within the same cell or tissue. Last but not least, dynamics of CSREs from close cell types or tissues can give a detailed view of developmental processes such as normal tissue development and cancer occurrence.

A probabilistic framework to dissect functional cell-type-specific regulatory elements and risk loci underlying the genetics of complex traits

10.1101/059345 ◽

2016 ◽

Cited By ~ 4

Author(s):

Yue Li ◽

Jose Davila-Velderrain ◽

Manolis Kellis

Keyword(s):

Complex Traits ◽

Large Scale ◽

Learning Algorithm ◽

Cell Types ◽

Regulatory Elements ◽

Probabilistic Framework ◽

Cell Type ◽

Tissue Specific ◽

Functional Variants ◽

Cell Type Specific

AbstractDissecting the physiological circuitry underlying diverse human complex traits associated with heritable common mutations is an ongoing effort. The primary challenge involves identifying the relevant cell types and the causal variants among the vast majority of the associated mutations in the noncoding regions. To address this challenge, we developed an efficient probabilistic framework. First, we propose a sparse group-guided learning algorithm to infer cell-type-specific enrichments. Second, we propose a fine-mapping Bayesian model that incorporates as Bayesian priors the sparse enrichments to infer risk variants. Using the proposed framework to analyze 32 complex human traits revealed meaningful tissue-specific epigenomic enrichments indicative of the relevant disease pathologies. The prioritized variants exhibit prominent tissue-specific epigenomic signatures and significant enrichments for eQTL and conserved elements. Together, we demonstrate the general benefits of the proposed integrative framework in elucidating meaningful tissue-specific epigenomic elements from large-scale correlated annotations and the implicated functional variants for future experimental interrogation.

Histone modifications form a cell-type-specific chromosomal bar code that persists through the cell cycle

Scientific Reports ◽

10.1038/s41598-021-82539-z ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

John A. Halsall ◽

Simon Andrews ◽

Felix Krueger ◽

Charlotte E. Rutledge ◽

Gabriella Ficz ◽

...

Keyword(s):

Gene Expression ◽

Cell Cycle ◽

Histone Modifications ◽

Expression Patterns ◽

Cell Types ◽

Cell Type ◽

Bar Code ◽

Genes Encoding ◽

Cell Type Specific ◽

Rolling Windows

AbstractChromatin configuration influences gene expression in eukaryotes at multiple levels, from individual nucleosomes to chromatin domains several Mb long. Post-translational modifications (PTM) of core histones seem to be involved in chromatin structural transitions, but how remains unclear. To explore this, we used ChIP-seq and two cell types, HeLa and lymphoblastoid (LCL), to define how changes in chromatin packaging through the cell cycle influence the distributions of three transcription-associated histone modifications, H3K9ac, H3K4me3 and H3K27me3. We show that chromosome regions (bands) of 10–50 Mb, detectable by immunofluorescence microscopy of metaphase (M) chromosomes, are also present in G1 and G2. They comprise 1–5 Mb sub-bands that differ between HeLa and LCL but remain consistent through the cell cycle. The same sub-bands are defined by H3K9ac and H3K4me3, while H3K27me3 spreads more widely. We found little change between cell cycle phases, whether compared by 5 Kb rolling windows or when analysis was restricted to functional elements such as transcription start sites and topologically associating domains. Only a small number of genes showed cell-cycle related changes: at genes encoding proteins involved in mitosis, H3K9 became highly acetylated in G2M, possibly because of ongoing transcription. In conclusion, modified histone isoforms H3K9ac, H3K4me3 and H3K27me3 exhibit a characteristic genomic distribution at resolutions of 1 Mb and below that differs between HeLa and lymphoblastoid cells but remains remarkably consistent through the cell cycle. We suggest that this cell-type-specific chromosomal bar-code is part of a homeostatic mechanism by which cells retain their characteristic gene expression patterns, and hence their identity, through multiple mitoses.

A scalable platform for the development of cell-type-specific viral drivers

eLife ◽

10.7554/elife.48089 ◽

2019 ◽

Vol 8 ◽

Cited By ~ 12

Author(s):

Sinisa Hrvatin ◽

Christopher P Tzeng ◽

M Aurel Nagy ◽

Hume Stroud ◽

Charalampia Koutsioumpa ◽

...

Keyword(s):

Gene Expression ◽

Heterologous Gene Expression ◽

High Specificity ◽

Cell Types ◽

Regulatory Elements ◽

Cell Type ◽

Cell Type Specificity ◽

Cell Type Specific ◽

The Many ◽

Dna Regulatory Elements

Enhancers are the primary DNA regulatory elements that confer cell type specificity of gene expression. Recent studies characterizing individual enhancers have revealed their potential to direct heterologous gene expression in a highly cell-type-specific manner. However, it has not yet been possible to systematically identify and test the function of enhancers for each of the many cell types in an organism. We have developed PESCA, a scalable and generalizable method that leverages ATAC- and single-cell RNA-sequencing protocols, to characterize cell-type-specific enhancers that should enable genetic access and perturbation of gene function across mammalian cell types. Focusing on the highly heterogeneous mammalian cerebral cortex, we apply PESCA to find enhancers and generate viral reagents capable of accessing and manipulating a subset of somatostatin-expressing cortical interneurons with high specificity. This study demonstrates the utility of this platform for developing new cell-type-specific viral reagents, with significant implications for both basic and translational research.

Analysis of putative cis-regulatory elements regulating blood pressure variation

Human Molecular Genetics ◽

10.1093/hmg/ddaa098 ◽

2020 ◽

Vol 29 (11) ◽

pp. 1922-1932

Author(s):

Priyanka Nandakumar ◽

Dongwon Lee ◽

Thomas J Hoffmann ◽

Georg B Ehret ◽

Dan Arking ◽

...

Keyword(s):

Blood Pressure ◽

Association Studies ◽

Specific Effect ◽

Cell Types ◽

Regulatory Elements ◽

Open Chromatin ◽

Genome Wide Association Studies ◽

Cell Type ◽

Functional Scores ◽

Cell Type Specific

Abstract Hundreds of loci have been associated with blood pressure (BP) traits from many genome-wide association studies. We identified an enrichment of these loci in aorta and tibial artery expression quantitative trait loci in our previous work in ~100 000 Genetic Epidemiology Research on Aging study participants. In the present study, we sought to fine-map known loci and identify novel genes by determining putative regulatory regions for these and other tissues relevant to BP. We constructed maps of putative cis-regulatory elements (CREs) using publicly available open chromatin data for the heart, aorta and tibial arteries, and multiple kidney cell types. Variants within these regions may be evaluated quantitatively for their tissue- or cell-type-specific regulatory impact using deltaSVM functional scores, as described in our previous work. We aggregate variants within these putative CREs within 50 Kb of the start or end of ‘expressed’ genes in these tissues or cell types using public expression data and use deltaSVM scores as weights in the group-wise sequence kernel association test to identify candidates. We test for association with both BP traits and expression within these tissues or cell types of interest and identify the candidates MTHFR, C10orf32, CSK, NOV, ULK4, SDCCAG8, SCAMP5, RPP25, HDGFRP3, VPS37B and PPCDC. Additionally, we examined two known QT interval genes, SCN5A and NOS1AP, in the Atherosclerosis Risk in Communities Study, as a positive control, and observed the expected heart-specific effect. Thus, our method identifies variants and genes for further functional testing using tissue- or cell-type-specific putative regulatory information.

An in vivo, neuron-specific approach for pairing translational and epigenetic signatures of early-life exercise

10.1101/2021.12.23.473936 ◽

2021 ◽

Author(s):

Anthony Mark Raus ◽

Tyson D Fuller ◽

Nellie E Nelson ◽

David A Valientes ◽

Anita Bayat ◽

...

Keyword(s):

Gene Expression ◽

Histone Modifications ◽

Early Life ◽

Affinity Purification ◽

Cell Types ◽

Cell Type ◽

Cell Type Specificity ◽

Cell Type Specific ◽

Induced Changes ◽

Epigenetic Signatures

Aerobic exercise promotes physiological and molecular adaptations in neurons to influence brain function and behavior. The most well studied neurobiological consequences of exercise are those which underlie exercise-induced improvements in hippocampal memory, including the expression and regulation of the neurotrophic factor Bdnf. Whether aerobic exercise taking place during early-life periods of postnatal brain maturation has similar impacts on gene expression and its regulation remains to be investigated. Using unbiased next-generation sequencing we characterize gene expression programs and their regulation by specific, memory-associated histone modifications during juvenile-adolescent voluntary exercise (ELE). Traditional transcriptomic and epigenomic sequencing approaches have either used heterogeneous cell populations from whole tissue homogenates or flow cytometry for single cell isolation to distinguish cell types / subtypes. These methods fall short in providing cell-type specificity without compromising sequencing depth or procedure-induced changes to cellular phenotype. In this study, we use simultaneous isolation of translating mRNA and nuclear chromatin from a neuron-enriched cell population to more accurately pair ELE-induced changes in gene expression with epigenetic modifications. We employ a line of transgenic mice expressing the NuTRAP (Nuclear Tagging and Translating Ribosome Affinity Purification) cassette under the Emx1 promoter allowing for brain cell-type specificity. We then developed a technique that combines nuclear isolation using Isolation of Nuclei TAgged in Specific Cell Types (INTACT) with Translating Ribosomal Affinity Purification (TRAP) methods to determine cell type-specific epigenetic modifications influencing gene expression programs from a population of Emx1 expressing hippocampal neurons. Data from RNA-seq and CUT&RUN-seq were coupled to evaluate histone modifications influencing the expression of translating mRNA in neurons after early-life exercise (ELE). We also performed separate INTACT and TRAP isolations for validation of our protocol and demonstrate similar molecular functions and biological processes implicated by gene ontology (GO) analysis. Finally, as prior studies use tissue from opposite brain hemispheres to pair transcriptomic and epigenomic data from the same rodent, we take a bioinformatics approach to compare hemispheric differences in gene expression programs and histone modifications altered by by ELE. Our data reveal transcriptional and epigenetic signatures of ELE exposure and identify novel candidate gene-histone modification interactions for further investigation. Importantly, our novel approach of combined INTACT/TRAP methods from the same cell suspension allows for simultaneous transcriptomic and epigenomic sequencing in a cell-type specific manner.

Analysis of putative cis-regulatory elements regulating blood pressure variation

10.1101/820522 ◽

2019 ◽

Author(s):

Priyanka Nandakumar ◽

Dongwon Lee ◽

Thomas J. Hoffmann ◽

Georg B. Ehret ◽

Dan Arking ◽

...

Keyword(s):

Gene Expression ◽

Blood Pressure ◽

Cell Types ◽

Regulatory Elements ◽

Open Chromatin ◽

Genome Wide Association Studies ◽

Cell Type ◽

Functional Scores ◽

Cell Type Specific ◽

Different Tissues

AbstractHundreds of loci have been associated with blood pressure traits from many genome-wide association studies. We identified an enrichment of these loci in aorta and tibial artery expression quantitative trait loci in our previous work in ∼100,000 Genetic Epidemiology Research on Aging (GERA) study participants. In the present study, we subsequently focused on determining putative regulatory regions for these and other tissues of relevance to blood pressure, to both fine-map these loci by pinpointing genes and variants of functional interest within them, and to identify any novel genes.We constructed maps of putative cis-regulatory elements using publicly available open chromatin data for the heart, aorta and tibial arteries, and multiple kidney cell types. Sequence variants within these regions may be evaluated quantitatively for their tissue- or cell-type-specific regulatory impact using deltaSVM functional scores, as described in our previous work. In order to identify genes of interest, we aggregate these variants in these putative cis-regulatory elements within 50Kb of the start or end of genes considered as “expressed” in these tissues or cell types using publicly available gene expression data, and use the deltaSVM scores as weights in the well-known group-wise sequence kernel association test (SKAT). We test for association with both blood pressure traits as well as expression within these tissues or cell types of interest, and identify several genes, including MTHFR, C10orf32, CSK, NOV, ULK4, SDCCAG8, SCAMP5, RPP25, HDGFRP3, VPS37B, and PPCDC. Although our study centers on blood pressure traits, we additionally examined two known genes, SCN5A and NOS1AP involved in the cardiac trait QT interval, in the Atherosclerosis Risk in Communities Study (ARIC), as a positive control, and observed an expected heart-specific effect. Thus, our method may be used to identify variants and genes for further functional testing using tissue- or cell-type-specific putative regulatory information.Author SummarySequence change in genes (“variants”) are linked to the presence and severity of different traits or diseases. However, as genes may be expressed in different tissues and at different times and degrees, using this information is expected to more accurately identify genes of interest. Variants within the genes are essential, but also in the sequences (“regulatory elements”) that control the genes’ expression in different tissues or cell types. In this study, we aim to use this information about expression and variants potentially involved in gene expression regulation to better pinpoint genes and variants in regulatory elements of interest for blood pressure regulation. We do so by taking advantage of such data that are publicly available, and use methods to combine information about variants in aggregate within a gene’s putative regulatory elements in tissues thought to be relevant for blood pressure, and identify several genes, meant to enable experimental follow-up.

Single-nucleus RNA-seq reveals dysregulation of striatal cell identity due to Huntington’s disease mutations

10.1101/2020.07.08.192880 ◽

2020 ◽

Author(s):

Sonia Malaiya ◽

Marcia Cortes-Gutierrez ◽

Brian R. Herb ◽

Sydney R. Coffey ◽

Samuel R.W. Legg ◽

...

Keyword(s):

Huntington's Disease ◽

Huntington’S Disease ◽

Neurodegenerative Disorder ◽

Cell Types ◽

Transcriptional Networks ◽

Rna Seq ◽

Cell Type ◽

Cell Identity ◽

Transcriptional Changes ◽

Cell Type Specific

ABSTRACTHuntington’s disease (HD) is a dominantly inherited neurodegenerative disorder caused by a trinucleotide expansion in exon 1 of the huntingtin (Htt) gene. Cell death in HD occurs primarily in striatal medium spiny neurons (MSNs), but the involvement of specific MSN subtypes and of other striatal cell types remains poorly understood. To gain insight into cell type-specific disease processes, we studied the nuclear transcriptomes of 4,524 cells from the striatum of a genetically precise knock-in mouse model of the HD mutation, HttQ175/+, and from wildtype controls. We used 14-15-month-old mice, a time point roughly equivalent to an early stage of symptomatic human disease. Cell type distributions indicated selective loss of D2 MSNs and increased microglia in aged HttQ175/+ mice. Thousands of differentially expressed genes were distributed across most striatal cell types, including transcriptional changes in glial populations that are not apparent from RNA-seq of bulk tissue. Reconstruction of cell typespecific transcriptional networks revealed a striking pattern of bidirectional dysregulation for many cell type-specific genes. Typically, these genes were repressed in their primary cell type, yet de-repressed in other striatal cell types. Integration with existing epigenomic and transcriptomic data suggest that partial loss-of-function of the Polycomb Repressive Complex 2 (PRC2) may underlie many of these transcriptional changes, leading to deficits in the maintenance of cell identity across virtually all cell types in the adult striatum.

SeqEnhDL: sequence-based classification of cell type-specific enhancers using deep learning models

10.21203/rs.3.rs-94396/v1 ◽

2020 ◽

Author(s):

Yupeng Wang ◽

Rosario Jaime-Lara ◽

Abhrarup Roy ◽

Ying Sun ◽

Xinyue Liu ◽

...

Keyword(s):

Neural Network ◽

Deep Learning ◽

Cell Types ◽

Regulatory Elements ◽

Learning Models ◽

Cell Type ◽

Coding Sequences ◽

Sequence Features ◽

A Genome ◽

Cell Type Specific

Abstract ObjectiveComputational identification of cell type-specific regulatory elements on a genome-wide scale is very challenging.ResultsWe propose SeqEnhDL, a deep learning framework for classifying cell type-specific enhancers based on sequence features. DNA sequences of “strong enhancer” chromatin states in nine cell types from the ENCODE project were retrieved to build and test enhancer classifiers. For any DNA sequence, sequential k-mer (k=5, 7, 9 and 11) fold changes relative to randomly selected non-coding sequences were used as features for deep learning models. Three deep learning models were implemented, including multi-layer perceptron (MLP), Convolutional Neural Network (CNN) and Recurrent Neural Network (RNN). All models in SeqEnhDL outperform state-of-the-art enhancer classifiers including gkm-SVM and DanQ, with regard to distinguishing cell type-specific enhancers from randomly selected non-coding sequences. Moreover, SeqEnhDL is able to directly discriminate enhancers from different cell types, which has not been achieved by other enhancer classifiers. Our analysis suggests that both enhancers and their tissue-specificity can be accurately identified according to their sequence features. SeqEnhDL is publicly available at https://github.com/wyp1125/SeqEnhDL.

A cis-regulatory atlas in maize at single-cell resolution

10.1101/2020.09.27.315499 ◽

2020 ◽

Author(s):

Alexandre P. Marand ◽

Zongliang Chen ◽

Andrea Gallavotti ◽

Robert J. Schmitz

Keyword(s):

Single Cell ◽

Cell Types ◽

Regulatory Elements ◽

Cellular Heterogeneity ◽

Cell Type ◽

Crop Species ◽

Cell Functions ◽

Cell Type Specific ◽

Type Specification ◽

Accessible Chromatin

ABSTRACTCis-regulatory elements (CREs) encode the genomic blueprints for coordinating spatiotemporal gene expression programs underlying highly specialized cell functions. To identify CREs underlying cell-type specification and developmental transitions, we implemented single-cell sequencing of Assay for Transposase Accessible Chromatin in an atlas of Zea mays organs. We describe 92 distinct states of chromatin accessibility across more than 165,913 putative CREs, 56,575 cells, and 52 known cell-types in maize using a novel implementation of regularized quasibinomial logistic regression. Cell states were largely determined by combinatorial accessibility of transcription factors (TFs) and their binding sites. A neural network revealed that cell identity could be accurately predicted (>0.94) solely based on TF binding site accessibility. Co-accessible chromatin recapitulated higher-order chromatin interactions, with distinct sets of TFs coordinating cell type-specific regulatory dynamics. Pseudotime reconstruction and alignment with Arabidopsis thaliana trajectories identified conserved TFs, associated motifs, and cis-regulatory regions specifying sequential developmental progressions. Cell-type specific accessible chromatin regions were enriched with phenotype-associated genetic variants and signatures of selection, revealing the major cell-types and putative CREs targeted by modern maize breeding. Collectively, our analysis affords a comprehensive framework for understanding cellular heterogeneity, evolution, and cis-regulatory grammar of cell-type specification in a major crop species.

Single-nuclei chromatin profiling of ventral midbrain reveals cell identity transcription factors and cell-type-specific gene regulatory variation

Epigenetics & Chromatin ◽

10.1186/s13072-021-00418-3 ◽

2021 ◽

Vol 14 (1) ◽

Author(s):

Yujuan Gui ◽

Kamil Grzyb ◽

Mélanie H. Thomas ◽

Jochen Ohnmacht ◽

Pierre Garcia ◽

...

Keyword(s):

Gene Expression ◽

Transcription Factors ◽

Cell Types ◽

Mouse Strains ◽

Cell Type ◽

Data Set ◽

Cell Identity ◽

Regulatory Variation ◽

Ventral Midbrain ◽

Cell Type Specific

Abstract Background Cell types in ventral midbrain are involved in diseases with variable genetic susceptibility, such as Parkinson’s disease and schizophrenia. Many genetic variants affect regulatory regions and alter gene expression in a cell-type-specific manner depending on the chromatin structure and accessibility. Results We report 20,658 single-nuclei chromatin accessibility profiles of ventral midbrain from two genetically and phenotypically distinct mouse strains. We distinguish ten cell types based on chromatin profiles and analysis of accessible regions controlling cell identity genes highlights cell-type-specific key transcription factors. Regulatory variation segregating the mouse strains manifests more on transcriptome than chromatin level. However, cell-type-level data reveals changes not captured at tissue level. To discover the scope and cell-type specificity of cis-acting variation in midbrain gene expression, we identify putative regulatory variants and show them to be enriched at differentially expressed loci. Finally, we find TCF7L2 to mediate trans-acting variation selectively in midbrain neurons. Conclusions Our data set provides an extensive resource to study gene regulation in mesencephalon and provides insights into control of cell identity in the midbrain and identifies cell-type-specific regulatory variation possibly underlying phenotypic and behavioural differences between mouse strains.