scholarly journals Ciliary photoreceptors in sea urchin larvae indicate pan-deuterostome cell type conservation

BMC Biology ◽  
2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Jonathan E. Valencia ◽  
Roberto Feuda ◽  
Dan O. Mellott ◽  
Robert D. Burke ◽  
Isabelle S. Peter
Keyword(s):  
Transcription Factor ◽  
Transcription Factors ◽  
Sea Urchin ◽  
Evolutionary Relationship ◽  
Cell Types ◽  
Developmental Expression ◽  
Pigment Cells ◽  
Cell Type ◽  
Neuronal Marker ◽  
Neurogenic Ectoderm

Abstract Background The evolutionary history of cell types provides insights into how morphological and functional complexity arose during animal evolution. Photoreceptor cell types are particularly broadly distributed throughout Bilateria; however, their evolutionary relationship is so far unresolved. Previous studies indicate that ciliary photoreceptors are homologous at least within chordates, and here, we present evidence that a related form of this cell type is also present in echinoderm larvae. Results Larvae of the purple sea urchin Strongylocentrotus purpuratus have photoreceptors that are positioned bilaterally in the oral/anterior apical neurogenic ectoderm. Here, we show that these photoreceptors express the transcription factor Rx, which is commonly expressed in ciliary photoreceptors, together with an atypical opsin of the GO family, opsin3.2, which localizes in particular to the cilia on the cell surface of photoreceptors. We show that these ciliary photoreceptors express the neuronal marker synaptotagmin and are located in proximity to pigment cells. Furthermore, we systematically identified additional transcription factors expressed in these larval photoreceptors and found that a majority are orthologous to transcription factors expressed in vertebrate ciliary photoreceptors, including Otx, Six3, Tbx2/3, and Rx. Based on the developmental expression of rx, these photoreceptors derive from the anterior apical neurogenic ectoderm. However, genes typically involved in eye development in bilateria, including pax6, six1/2, eya, and dac, are not expressed in sea urchin larval photoreceptors but are instead co-expressed in the hydropore canal. Conclusions Based on transcription factor expression, location, and developmental origin, we conclude that the sea urchin larval photoreceptors constitute a cell type that is likely homologous to the ciliary photoreceptors present in chordates.

scholarly journals Ciliary photoreceptors in sea urchin larvae indicate pan-deuterostome cell type conservation

2019 ◽  
Author(s):  
Jonathan E. Valencia ◽  
Roberto Feuda ◽  
Dan O. Mellott ◽  
Robert D. Burke ◽  
Isabelle S. Peter
Keyword(s):  
Transcription Factor ◽  
Transcription Factors ◽  
Sea Urchin ◽  
Cell Types ◽  
Pigment Cells ◽  
Current Evidence ◽  
Regulatory State ◽  
Developmental Context ◽  
Immotile Cilia ◽  
Retinal Determination

ABSTRACTOne of the signatures of evolutionarily related cell types is the expression of similar combinations of transcription factors in distantly related animals. Here we present evidence that sea urchin larvae possess bilateral clusters of ciliary photoreceptors that are positioned in the oral/anterior apical neurogenic domain and associated with pigment cells. The expression of synaptotagmin indicates that the photoreceptors are neurons. Immunostaining shows that the sea urchin photoreceptors express an RGR/GO-opsin, opsin3.2, which co-localizes with tubulin on immotile cilia on the cell surface. Furthermore, orthologs of several transcription factors expressed in vertebrate photoreceptors are expressed in sea urchin ciliary photoreceptors, including Otx, Six3, Tbx2/3, and Rx, a transcription factor typically associated with ciliary photoreceptors. Analysis of gene expression during sea urchin development indicates that the photoreceptors derive from the anterior apical neurogenic domain. Thus, based on location, developmental origin, and transcription factor expression, sea urchin ciliary photoreceptors are likely homologous to vertebrate rods and cones. However, we found that genes typically involved in eye development in many animals, including pax6, six1/2, eya, and dac, are not expressed in sea urchin ciliary photoreceptors. Instead, all four genes are co-expressed in the hydropore canal, indicating that these genes operate as a module in an unrelated developmental context. Thus, based on current evidence, we conclude that at least within deuterostomes, ciliary photoreceptors share a common evolutionary origin and express a shared regulatory state that includes Rx, Otx, and Six3, but not transcription factors that are commonly associated with the retinal determination circuit.

scholarly journals Genomic Architecture of Cells in Tissues (GeACT): Study of Human Mid-gestation Fetus

2020 ◽  
Author(s):  
Feng Tian ◽  
Fan Zhou ◽  
Xiang Li ◽  
Wenping Ma ◽  
Honggui Wu ◽  
...  
Keyword(s):  
Transcription Factors ◽  
Single Cell ◽  
Human Cell ◽  
Expression Profiles ◽  
Single Cells ◽  
Cell Types ◽  
List Type ◽  
Cell Type ◽  
Genomic Architecture ◽  
Gene Modules

SummaryBy circumventing cellular heterogeneity, single cell omics have now been widely utilized for cell typing in human tissues, culminating with the undertaking of human cell atlas aimed at characterizing all human cell types. However, more important are the probing of gene regulatory networks, underlying chromatin architecture and critical transcription factors for each cell type. Here we report the Genomic Architecture of Cells in Tissues (GeACT), a comprehensive genomic data base that collectively address the above needs with the goal of understanding the functional genome in action. GeACT was made possible by our novel single-cell RNA-seq (MALBAC-DT) and ATAC-seq (METATAC) methods of high detectability and precision. We exemplified GeACT by first studying representative organs in human mid-gestation fetus. In particular, correlated gene modules (CGMs) are observed and found to be cell-type-dependent. We linked gene expression profiles to the underlying chromatin states, and found the key transcription factors for representative CGMs.HighlightsGenomic Architecture of Cells in Tissues (GeACT) data for human mid-gestation fetusDetermining correlated gene modules (CGMs) in different cell types by MALBAC-DTMeasuring chromatin open regions in single cells with high detectability by METATACIntegrating transcriptomics and chromatin accessibility to reveal key TFs for a CGM

scholarly journals HOT or not: examining the basis of high-occupancy target regions

2017 ◽  
Author(s):  
Katarzyna Wreczycka ◽  
Vedran Franke ◽  
Bora Uyar ◽  
Ricardo Wurmus ◽  
Altuna Akalin
Keyword(s):  
Transcription Factor ◽  
Transcription Factors ◽  
Binding Sites ◽  
Cell Types ◽  
Data Sets ◽  
Gene Promoters ◽  
Quadruplex Dna ◽  
Golden Standard ◽  
Multiple Cell ◽  
Multiple Species

AbstractHigh-occupancy target (HOT) regions are the segments of the genome with unusually high number of transcription factor binding sites. These regions are observed in multiple species and thought to have biological importance due to high transcription factor occupancy. Furthermore, they coincide with house-keeping gene promoters and the associated genes are stably expressed across multiple cell types. Despite these features, HOT regions are solemnly defined using ChIP-seq experiments and shown to lack canonical motifs for transcription factors that are thought to be bound there. Although, ChIP-seq experiments are the golden standard for finding genome-wide binding sites of a protein, they are not noise free. Here, we show that HOT regions are likely to be ChIP-seq artifacts and they are similar to previously proposed “hyper-ChIPable” regions. Using ChIP-seq data sets for knocked-out transcription factors, we demonstrate presence of false positive signals on HOT regions. We observe sequence characteristics and genomic features that are discriminatory of HOT regions, such as GC/CpG-rich k-mers and enrichment of RNA-DNA hybrids (R-loops) and DNA tertiary structures (G-quadruplex DNA). The artificial ChIP-seq enrichment on HOT regions could be associated to these discriminatory features. Furthermore, we propose strategies to deal with such artifacts for the future ChIP-seq studies.

scholarly journals Virtual ChIP-seq: predicting transcription factor binding by learning from the transcriptome

2018 ◽  
Author(s):  
Mehran Karimzadeh ◽  
Michael M. Hoffman
Keyword(s):  
Transcription Factor ◽  
Transcription Factors ◽  
Binding Sites ◽  
Cell Types ◽  
Transcription Factor Binding ◽  
Regulatory Function ◽  
Factor Binding ◽  
Link Type ◽  
Genomic Regions ◽  
Factor Sequence

AbstractMotivationIdentifying transcription factor binding sites is the first step in pinpointing non-coding mutations that disrupt the regulatory function of transcription factors and promote disease. ChIP-seq is the most common method for identifying binding sites, but performing it on patient samples is hampered by the amount of available biological material and the cost of the experiment. Existing methods for computational prediction of regulatory elements primarily predict binding in genomic regions with sequence similarity to known transcription factor sequence preferences. This has limited efficacy since most binding sites do not resemble known transcription factor sequence motifs, and many transcription factors are not even sequence-specific.ResultsWe developed Virtual ChIP-seq, which predicts binding of individual transcription factors in new cell types using an artificial neural network that integrates ChIP-seq results from other cell types and chromatin accessibility data in the new cell type. Virtual ChIP-seq also uses learned associations between gene expression and transcription factor binding at specific genomic regions. This approach outperforms methods that predict TF binding solely based on sequence preference, pre-dicting binding for 36 transcription factors (Matthews correlation coefficient > 0.3).AvailabilityThe datasets we used for training and validation are available at https://virchip.hoffmanlab.org. We have deposited in Zenodo the current version of our software (http://doi.org/10.5281/zenodo.1066928), datasets (http://doi.org/10.5281/zenodo.823297), predictions for 36 transcription factors on Roadmap Epigenomics cell types (http://doi.org/10.5281/zenodo.1455759), and predictions in Cistrome as well as ENCODE-DREAM in vivo TF Binding Site Prediction Challenge (http://doi.org/10.5281/zenodo.1209308).

scholarly journals An Algorithm for Cellular Reprogramming

2017 ◽  
Author(s):  
Scott Ronquist ◽  
Geoff Patterson ◽  
Markus Brown ◽  
Stephen Lindsly ◽  
Haiming Chen ◽  
...  
Keyword(s):  
Cell Cycle ◽  
Transcription Factor ◽  
Transcription Factors ◽  
Cell Biology ◽  
Human Fibroblasts ◽  
Cell Types ◽  
Approximate Model ◽  
Cellular Reprogramming ◽  
Biological Processes ◽  
Moderate Complexity

AbstractThe day we understand the time evolution of subcellular elements at a level of detail comparable to physical systems governed by Newton’s laws of motion seems far away. Even so, quantitative approaches to cellular dynamics add to our understanding of cell biology, providing data-guided frameworks that allow us to develop better predictions about, and methods for, control over specific biological processes and system-wide cell behavior. In this paper, we describe an approach to optimizing the use of transcription factors (TFs) in the context of cellular reprogramming. We construct an approximate model for the natural evolution of a cell cycle synchronized population of human fibroblasts, based on data obtained by sampling the expression of 22,083 genes at several time points along the cell cycle. In order to arrive at a model of moderate complexity, we cluster gene expression based on the division of the genome into topologically associating domains (TADs) and then model the dynamics of the TAD expression levels. Based on this dynamical model and known bioinformatics, such as transcription factor binding sites (TFBS) and functions, we develop a methodology for identifying the top transcription factor candidates for a specific cellular reprogramming task. The approach used is based on a device commonly used in optimal control. Our data-guided methodology identifies a number of transcription factors previously validated for reprogramming and/or natural differentiation. Our findings highlight the immense potential of dynamical models, mathematics, and data-guided methodologies for improving strategies for control over biological processes.Significance StatementReprogramming the human genome toward any desirable state is within reach; application of select transcription factors drives cell types toward different lineages in many settings. We introduce the concept of data-guided control in building a universal algorithm for directly reprogramming any human cell type into any other type. Our algorithm is based on time series genome transcription and architecture data and known regulatory activities of transcription factors, with natural dimension reduction using genome architectural features. Our algorithm predicts known reprogramming factors, top candidates for new settings, and ideal timing for application of transcription factors. This framework can be used to develop strategies for tissue regeneration, cancer cell reprogramming, and control of dynamical systems beyond cell biology.

Developmental expression of the maternal protein XDCoH, the dimerization cofactor of the homeoprotein LFB1 (HNF1)

Development ◽  
1995 ◽  
Vol 121 (4) ◽  
pp. 1217-1226
Author(s):  
E. Pogge yon Strandmann ◽  
G.U. Ryffel
Keyword(s):  
Transcription Factors ◽  
Anterior Part ◽  
Regulatory Element ◽  
Cdna Probe ◽  
Cell Types ◽  
Developmental Expression ◽  
Variant Form ◽  
Cis Acting ◽  
Liver And Kidney

The tissue-specific transcription factors LFB1 (HNF1) and LFB3 (vHNF1) mainly expressed in liver, kidney and intestine are homeoproteins that interact with the regulatory element HP1. The HP1 sequence constitutes one of the most important cis-acting elements in liver-specifically expressed genes, while its function in other cell types containing LFB1 and LFB3 is not fully understood. In mammals, LFB1 activity is modulated by DCoH, a cofactor that stimulates the LFB1 transactivation significantly. Using the rat cDNA probe, we cloned the corresponding Xenopus sequence XDCoH, encoding a 104 amino acid protein, that is 85% identical to the rat protein. XDCoH enhances the LFB1-dependent transactivation potential in transfection experiments and interacts in vitro directly with LFB1 and its variant form LFB3. The protein is detectable in liver and kidney extracts of adult frogs and in small amounts also in lung and stomach, organs expressing LFB1 and/or LFB3 protein as well. To investigate the possible involvement of XDCoH in Xenopus development, we analyzed its temporal and spatial expression pattern during early embryogenesis. XDCoH is a maternal factor, although LFB1 is absent in the egg. In early cleavage stages, the protein is detectable in the cytoplasm of each blastomere and enters the nuclei of the cells as early as the zygotic transcription in the Xenopus embryo starts. The amount of XDCoH increases dramatically following neurulation, when the formation of liver, pronephros and other organs takes place. Whole-mount immunostaining demonstrates that, in the developing larvae, XDCoH is localized in the nuclei of the hepatocytes, the gut cells and the pronephric cells, tissues of mesodermal and endodermal origin known to contain LFB1 and LFB3. Surprisingly it is also present in the pigmented epithelium surrounding the eye of the embryo, which is derived from the anterior part of the ectodermal neural plates and lacks LFB1. The tissue distribution of XDCoH during embryogenesis suggests that XDCoH is involved in determination and differentiation of various unrelated cell types. It seems likely that XDCoH interaction is not only essential for the function of LFB1 and LFB3 but also for certain other transcription factors.

scholarly journals Chemical compound-based direct reprogramming for future clinical applications

2018 ◽  
Vol 38 (3) ◽  
Author(s):  
Yukimasa Takeda ◽  
Yoshinori Harada ◽  
Toshikazu Yoshikawa ◽  
Ping Dai
Keyword(s):  
Stem Cells ◽  
Transcription Factors ◽  
Chemical Compound ◽  
Chemical Compounds ◽  
Cell Types ◽  
Direct Reprogramming ◽  
Cell Type ◽  
Promising Alternative ◽  
Cell Functions ◽  
Transplantation Therapy

Recent studies have revealed that a combination of chemical compounds enables direct reprogramming from one somatic cell type into another without the use of transgenes by regulating cellular signaling pathways and epigenetic modifications. The generation of induced pluripotent stem (iPS) cells generally requires virus vector-mediated expression of multiple transcription factors, which might disrupt genomic integrity and proper cell functions. The direct reprogramming is a promising alternative to rapidly prepare different cell types by bypassing the pluripotent state. Because the strategy also depends on forced expression of exogenous lineage-specific transcription factors, the direct reprogramming in a chemical compound-based manner is an ideal approach to further reduce the risk for tumorigenesis. So far, a number of reported research efforts have revealed that combinations of chemical compounds and cell-type specific medium transdifferentiate somatic cells into desired cell types including neuronal cells, glial cells, neural stem cells, brown adipocytes, cardiomyocytes, somatic progenitor cells, and pluripotent stem cells. These desired cells rapidly converted from patient-derived autologous fibroblasts can be applied for their own transplantation therapy to avoid immune rejection. However, complete chemical compound-induced conversions remain challenging particularly in adult human-derived fibroblasts compared with mouse embryonic fibroblasts (MEFs). This review summarizes up-to-date progress in each specific cell type and discusses prospects for future clinical application toward cell transplantation therapy.

scholarly journals A single cell brain atlas in human Alzheimer’s disease

2019 ◽  
Author(s):  
Alexandra Grubman ◽  
Gabriel Chew ◽  
John F. Ouyang ◽  
Guizhi Sun ◽  
Xin Yi Choo ◽  
...  
Keyword(s):  
Gene Expression ◽  
Transcription Factor ◽  
Single Cell ◽  
Cell Fate ◽  
Expression Patterns ◽  
Cell Types ◽  
Gene Expression Patterns ◽  
Cell Type ◽  
Web Resource ◽  
Cell Type Specific

AbstractAlzheimer’s disease (AD) is a heterogeneous disease that is largely dependent on the complex cellular microenvironment in the brain. This complexity impedes our understanding of how individual cell types contribute to disease progression and outcome. To characterize the molecular and functional cell diversity in the human AD brain we utilized single nuclei RNA- seq in AD and control patient brains in order to map the landscape of cellular heterogeneity in AD. We detail gene expression changes at the level of cells and cell subclusters, highlighting specific cellular contributions to global gene expression patterns between control and Alzheimer’s patient brains. We observed distinct cellular regulation of APOE which was repressed in oligodendrocyte progenitor cells (OPCs) and astrocyte AD subclusters, and highly enriched in a microglial AD subcluster. In addition, oligodendrocyte and microglia AD subclusters show discordant expression of APOE. Integration of transcription factor regulatory modules with downstream GWAS gene targets revealed subcluster-specific control of AD cell fate transitions. For example, this analysis uncovered that astrocyte diversity in AD was under the control of transcription factor EB (TFEB), a master regulator of lysosomal function and which initiated a regulatory cascade containing multiple AD GWAS genes. These results establish functional links between specific cellular sub-populations in AD, and provide new insights into the coordinated control of AD GWAS genes and their cell-type specific contribution to disease susceptibility. Finally, we created an interactive reference web resource which will facilitate brain and AD researchers to explore the molecular architecture of subtype and AD-specific cell identity, molecular and functional diversity at the single cell level.HighlightsWe generated the first human single cell transcriptome in AD patient brainsOur study unveiled 9 clusters of cell-type specific and common gene expression patterns between control and AD brains, including clusters of genes that present properties of different cell types (i.e. astrocytes and oligodendrocytes)Our analyses also uncovered functionally specialized sub-cellular clusters: 5 microglial clusters, 8 astrocyte clusters, 6 neuronal clusters, 6 oligodendrocyte clusters, 4 OPC and 2 endothelial clusters, each enriched for specific ontological gene categoriesOur analyses found manifold AD GWAS genes specifically associated with one cell-type, and sets of AD GWAS genes co-ordinately and differentially regulated between different brain cell-types in AD sub-cellular clustersWe mapped the regulatory landscape driving transcriptional changes in AD brain, and identified transcription factor networks which we predict to control cell fate transitions between control and AD sub-cellular clustersFinally, we provide an interactive web-resource that allows the user to further visualise and interrogate our dataset.Data resource web interface:http://adsn.ddnetbio.com

scholarly journals Phenotypic convergence in the brain: distinct transcription factors regulate common terminal neuronal characters

2018 ◽  
Author(s):  
Nikos Konstantinides ◽  
Katarina Kapuralin ◽  
Chaimaa Fadil ◽  
Luendreo Barboza ◽  
Rahul Satija ◽  
...  
Keyword(s):  
Transcription Factors ◽  
Single Cell ◽  
Large Scale ◽  
Single Cells ◽  
Deep Understanding ◽  
Cell Types ◽  
Marker Genes ◽  
Cell Type ◽  
Functional Specification ◽  
Phenotypic Convergence

SummaryTranscription factors regulate the molecular, morphological, and physiological characters of neurons and generate their impressive cell type diversity. To gain insight into general principles that govern how transcription factors regulate cell type diversity, we used large-scale single-cell mRNA sequencing to characterize the extensive cellular diversity in the Drosophila optic lobes. We sequenced 55,000 single optic lobe neurons and glia and assigned them to 52 clusters of transcriptionally distinct single cells. We validated the clustering and annotated many of the clusters using RNA sequencing of characterized FACS-sorted single cell types, as well as marker genes specific to given clusters. To identify transcription factors responsible for inducing specific terminal differentiation features, we used machine-learning to generate a ‘random forest’ model. The predictive power of the model was confirmed by showing that two transcription factors expressed specifically in cholinergic (apterous) and glutamatergic (traffic-jam) neurons are necessary for the expression of ChAT and VGlut in many, but not all, cholinergic or glutamatergic neurons, respectively. We used a transcriptome-wide approach to show that the same terminal characters, including but not restricted to neurotransmitter identity, can be regulated by different transcription factors in different cell types, arguing for extensive phenotypic convergence. Our data provide a deep understanding of the developmental and functional specification of a complex brain structure.

Sign in / Sign up

Export Citation Format

Share Document