Cell type-specific regulation of the Drosophila FMRF-NH2 neuropeptide gene by Apterous, a LIM homeodomain transcription factor

Development ◽  
1998 ◽  
Vol 125 (23) ◽  
pp. 4757-4765 ◽  
Author(s):  
R.J. Benveniste ◽  
S. Thor ◽  
J.B. Thomas ◽  
P.H. Taghert
Keyword(s):  
Transcription Factor ◽  
Morphological Differentiation ◽  
Cell Types ◽  
Neuroendocrine Cells ◽  
Cell Type ◽  
Homeodomain Transcription Factor ◽  
Neuron Survival ◽  
Cell Type Specific ◽  
Specific Regulation ◽  
Lim Homeodomain

We describe the direct and cell-specific regulation of the Drosophila FMRFa neuropeptide gene by Apterous, a LIM homeodomain transcription factor. dFMRFa and Apterous are expressed in partially overlapping subsets of neurons, including two of the seventeen dFMRFa cell types, the Tv neuroendocrine cells and the SP2 interneurons. Apterous contributes to the initiation of dFMRFa expression in Tv neurons, but not in those dFMRFa neurons that do not express Apterous. Apterous is not required for Tv neuron survival or morphological differentiation. Apterous contributes to the maintenance of dFMRFa expression by postembryonic Tv neurons, although the strength of its regulation is diminished. Apterous regulation of dFMRFa expression includes direct mechanisms, although ectopic Apterous does not induce ectopic dFMRFa. These findings show that, for a subset of neurons that share a common neurotransmitter phenotype, the Apterous LIM homeoprotein helps define neurotransmitter expression with very limited effects on other aspects of differentiation.

scholarly journals Shisa6 mediates cell-type specific regulation of depression in the nucleus accumbens

2021 ◽  
Author(s):  
Hee-Dae Kim ◽  
Jing Wei ◽  
Tanessa Call ◽  
Nicole Teru Quintus ◽  
Alexander J. Summers ◽  
...  
Keyword(s):  
Nucleus Accumbens ◽  
Molecular Mechanisms ◽  
Cell Types ◽  
Current Treatment ◽  
Specific Cell ◽  
Excitatory Synapses ◽  
Cell Type ◽  
Cell Type Specific ◽  
Specific Regulation ◽  
Circuit Function

AbstractDepression is the leading cause of disability and produces enormous health and economic burdens. Current treatment approaches for depression are largely ineffective and leave more than 50% of patients symptomatic, mainly because of non-selective and broad action of antidepressants. Thus, there is an urgent need to design and develop novel therapeutics to treat depression. Given the heterogeneity and complexity of the brain, identification of molecular mechanisms within specific cell-types responsible for producing depression-like behaviors will advance development of therapies. In the reward circuitry, the nucleus accumbens (NAc) is a key brain region of depression pathophysiology, possibly based on differential activity of D1- or D2- medium spiny neurons (MSNs). Here we report a circuit- and cell-type specific molecular target for depression, Shisa6, recently defined as an AMPAR component, which is increased only in D1-MSNs in the NAc of susceptible mice. Using the Ribotag approach, we dissected the transcriptional profile of D1- and D2-MSNs by RNA sequencing following a mouse model of depression, chronic social defeat stress (CSDS). Bioinformatic analyses identified cell-type specific genes that may contribute to the pathogenesis of depression, including Shisa6. We found selective optogenetic activation of the ventral tegmental area (VTA) to NAc circuit increases Shisa6 expression in D1-MSNs. Shisa6 is specifically located in excitatory synapses of D1-MSNs and increases excitability of neurons, which promotes anxiety- and depression-like behaviors in mice. Cell-type and circuit-specific action of Shisa6, which directly modulates excitatory synapses that convey aversive information, identifies the protein as a potential rapid-antidepressant target for aberrant circuit function in depression.

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 Leopard: fast decoding cell type-specific transcription factor binding landscape at single-nucleotide resolution

2019 ◽  
Author(s):  
Hongyang Li ◽  
Yuanfang Guan
Keyword(s):  
Transcription Factor ◽  
Network Architecture ◽  
Characteristic Curve ◽  
Cell Types ◽  
Cell Type ◽  
Single Nucleotide ◽  
Specific Transcription Factor ◽  
Cell Type Specific ◽  
Nucleotide Resolution ◽  
Single Nucleotide Resolution

AbstractDecoding the cell type-specific transcription factor (TF) binding landscape at single-nucleotide resolution is crucial for understanding the regulatory mechanisms underlying many fundamental biological processes and human diseases. However, limits on time and resources restrict the high-resolution experimental measurements of TF binding profiles of all possible TF-cell type combinations. Previous computational approaches either can not distinguish the cell-context-dependent TF binding profiles across diverse cell types, or only provide a relatively low-resolution prediction. Here we present a novel deep learning approach, Leopard, for predicting TF-binding sites at single-nucleotide resolution, achieving the median area under receiver operating characteristic curve (AUROC) of 0.994. Our method substantially outperformed state-of-the-art methods Anchor and FactorNet, improving the performance by 19% and 27% respectively despite evaluated at a lower resolution. Meanwhile, by leveraging a many-to-many neural network architecture, Leopard features hundred-fold to thousand-fold speedup compared to current many-to-one machine learning methods.

scholarly journals Learning from mistakes: Accurate prediction of cell type-specific transcription factor binding

2017 ◽  
Author(s):  
Jens Keilwagen ◽  
Stefan Posch ◽  
Jan Grau
Keyword(s):  
Transcription Factor ◽  
Cell Types ◽  
Transcription Factor Binding ◽  
Ensemble Prediction ◽  
Training Procedure ◽  
Cell Type ◽  
Binding Motifs ◽  
Factor Binding ◽  
Cell Type Specific

Computational prediction of cell type-specific, in-vivo transcription factor binding sites is still one of the central challenges in regulatory genomics, and a variety of approaches has been proposed for this purpose.Here, we present our approach that earned a shared first rank in the “ENCODE-DREAM in vivo Transcription Factor Binding Site Prediction Challenge” in 2017. This approach employs features derived from chromatin accessibility, binding motifs, gene expression, genomic sequence and annotation to train classifiers using a supervised, discriminative learning principle. Two further key aspects of this approach are learning classifier parameters in an iterative training procedure that successively adds additional negative examples to the training set, and creating an ensemble prediction by averaging over classifiers obtained for different training cell types.In post-challenge analyses, we benchmark the influence of different feature sets and find that chromatin accessiblity and binding motifs are sufficient to yield state-of-the-art performance for in-vivo binding site predictions. We also show that the iterative training procedure and the ensemble prediction are pivotal for the final prediction performance.To make predictions of this approach readily accessible, we predict 682 peak lists for a total of 31 transcription factors in 22 primary cell types and tissues, which are available for download at https://www.synapse.org/#!Synapse:syn11526239, and we demonstrate that these may help to yield biological conclusions. Finally, we provide a user-friendly version of our approach as open source software at http://jstacs.de/index.php/[email protected]

scholarly journals RNA polymerase II pausing as a context-dependent reader of the genome

2016 ◽  
Vol 94 (1) ◽  
pp. 82-92 ◽  
Author(s):  
Adam Scheidegger ◽  
Sergei Nechaev
Keyword(s):  
Rna Polymerase ◽  
Rna Polymerase Ii ◽  
Cell Types ◽  
Gene Promoters ◽  
Cell Type ◽  
Pol Ii ◽  
Cell Type Specific ◽  
Pol Ii Pausing ◽  
Context Dependent ◽  
Specific Regulation

The RNA polymerase II (Pol II) transcribes all mRNA genes in eukaryotes and is among the most highly regulated enzymes in the cell. The classic model of mRNA gene regulation involves recruitment of the RNA polymerase to gene promoters in response to environmental signals. Higher eukaryotes have an additional ability to generate multiple cell types. This extra level of regulation enables each cell to interpret the same genome by committing to one of the many possible transcription programs and executing it in a precise and robust manner. Whereas multiple mechanisms are implicated in cell type-specific transcriptional regulation, how one genome can give rise to distinct transcriptional programs and what mechanisms activate and maintain the appropriate program in each cell remains unclear. This review focuses on the process of promoter-proximal Pol II pausing during early transcription elongation as a key step in context-dependent interpretation of the metazoan genome. We highlight aspects of promoter-proximal Pol II pausing, including its interplay with epigenetic mechanisms, that may enable cell type-specific regulation, and emphasize some of the pertinent questions that remain unanswered and open for investigation.

scholarly journals Spatiotemporal mapping of RNA editing in the developing mouse brain using in situ sequencing reveals regional and cell-type-specific regulation

BMC Biology ◽  
2020 ◽  
Vol 18 (1) ◽  
Author(s):  
Elin Lundin ◽  
Chenglin Wu ◽  
Albin Widmark ◽  
Mikaela Behm ◽  
Jens Hjerling-Leffler ◽  
...  
Keyword(s):  
Single Cell ◽  
Rna Editing ◽  
Mouse Brain ◽  
Developmental Stages ◽  
Cell Types ◽  
Specific Cell ◽  
Cell Type ◽  
Cell Type Specific ◽  
Specific Regulation

Abstract Background Adenosine-to-inosine (A-to-I) RNA editing is a process that contributes to the diversification of proteins that has been shown to be essential for neurotransmission and other neuronal functions. However, the spatiotemporal and diversification properties of RNA editing in the brain are largely unknown. Here, we applied in situ sequencing to distinguish between edited and unedited transcripts in distinct regions of the mouse brain at four developmental stages, and investigate the diversity of the RNA landscape. Results We analyzed RNA editing at codon-altering sites using in situ sequencing at single-cell resolution, in combination with the detection of individual ADAR enzymes and specific cell type marker transcripts. This approach revealed cell-type-specific regulation of RNA editing of a set of transcripts, and developmental and regional variation in editing levels for many of the targeted sites. We found increasing editing diversity throughout development, which arises through regional- and cell type-specific regulation of ADAR enzymes and target transcripts. Conclusions Our single-cell in situ sequencing method has proved useful to study the complex landscape of RNA editing and our results indicate that this complexity arises due to distinct mechanisms of regulating individual RNA editing sites, acting both regionally and in specific cell types.

Cell Type-Specific Regulation of Expression of Transcription Factor AP-2 in Neuroectodermal Cells

1994 ◽  
Vol 165 (2) ◽  
pp. 602-614 ◽  
Author(s):  
Jeannette Philipp ◽  
Pamela J. Mitchell ◽  
Ursula Malipiero ◽  
Adriano Fontana
Keyword(s):  
Transcription Factor ◽  
Cell Type ◽  
Regulation Of Expression ◽  
Cell Type Specific ◽  
Specific Regulation

scholarly journals Quantifying the Tissue-Specific Regulatory Information within Enhancer DNA Sequences

2021 ◽  
Author(s):  
Philipp Benner ◽  
Martin Vingron
Keyword(s):  
Dna Sequences ◽  
Cell Types ◽  
Cell Type ◽  
Regulate Gene Expression ◽  
Tissue Specific ◽  
Sequence Patterns ◽  
Cell Type Specific ◽  
Specific Regulation ◽  
Different Cell Types ◽  
Regulatory Landscape

AbstractRecent efforts to measure epigenetic marks across a wide variety of different cell types and tissues provide insights into the cell type-specific regulatory landscape. We use this data to study if there exists a correlate of epigenetic signals in the DNA sequence of enhancers and explore with computational methods to what degree such sequence patterns can be used to predict cell type-specific regulatory activity. By constructing classifiers that predict in which tissues enhancers are active, we are able to identify sequence features that might be recognized by the cell in order to regulate gene expression. While classification performances vary greatly between tissues, we show examples where our classifiers correctly predict tissue specific regulation from sequence alone. We also show that many of the informative patterns indeed harbor transcription factor footprints.

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