Diverse reprogramming codes for neuronal identity
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA445859 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| Other | ||||
| SRR6904010.fastq.gz | Fastqsanger.gz | |||
| SRR6904020.fastq.gz | Fastqsanger.gz | |||
| SRR6904030.fastq.gz | Fastqsanger.gz | |||
| SRR6904040.fastq.gz | Fastqsanger.gz |
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Project description:The transcriptional programs that establish neuronal identity evolved to produce a rich diversity of neuronal cell types that arise sequentially during development. Remarkably, transient expression of certain transcription factors (TFs) can also endow non-neural cells with neuronal properties. To decipher the relationship between reprogramming factors and transcriptional networks that produce neuronal identity and diversity, we screened ~600 TF pairs and identified 76 that produce induced neurons (iNs) from fibroblasts. By intersecting the transcriptomes of iNs with those of endogenous neurons, we define a “core” cell-autonomous neuronal signature. The iNs also exhibit diversity; each TF pair produces iNs with unique transcriptional patterns that can predict their pharmacological responses. By linking distinct TF input “codes” to defined transcriptional outputs, this study uncovers cell autonomous features of neuronal identity and expands the reprogramming toolbox to enable more facile engineering of induced neurons with desired patterns of gene expression and related functional properties.
2018-05-10 | GSE112381 | GEO
Project description:The transcriptional programs that establish neuronal identity evolved to produce the rich diversity of neuronal cell types that arise sequentially during development. Remarkably, transient expression of certain transcription factors can also endow non-neural cells with neuronal properties. The relationship between reprogramming factors and the transcriptional networks that produce neuronal identity and diversity remains largely unknown. Here, from a screen of 598 pairs of transcription factors, we identify 76 pairs of transcription factors that induce mouse fibroblasts to differentiate into cells with neuronal features. By comparing the transcriptomes of these induced neuronal cells (iN cells) with those of endogenous neurons, we define a 'core' cell-autonomous neuronal signature. The iN cells also exhibit diversity; each transcription factor pair produces iN cells with unique transcriptional patterns that can predict their pharmacological responses. By linking distinct transcription factor input 'codes' to defined transcriptional outputs, this study delineates cell-autonomous features of neuronal identity and diversity and expands the reprogramming toolbox to facilitate engineering of induced neurons with desired patterns of gene expression and related functional properties.
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Project description:Direct neuronal reprogramming by temporal identity factors
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Project description:Temporal identity factors are sufficient to reprogram developmental competence of neural progenitors and shift cell fate output, but whether they can also reprogram the identity of terminally differentiated cells is unknown. To address this question, we designed a conditional gene expression system that allows rapid screening of potential reprogramming factors in mouse retinal glial cells combined with genetic lineage tracing. Using this assay, we found that co-expression of the early temporal identity transcription factors Ikzf1 and Ikzf4 is sufficient to directly convert Müller glial cells into cells that translocate to the outer nuclear layer (ONL), where photoreceptor cells normally reside. We name these “induced ONL (iONL)” cells. Using genetic lineage tracing, histological, immunohistochemical, and single-cell transcriptome and multiome analyses, we show that expression of Ikzf1/4 in Müller glia in vivo, without retinal injury, mostly generate iONL cells that share molecular characteristics with bipolar cells, although a fraction of them stain for Rxrg, a cone photoreceptor marker. Furthermore, we show that co-expression of Ikzf1 and Ikzf4 can reprogram mouse embryonic fibroblasts to induced neurons (iN) in culture by rapidly remodeling chromatin and activating a neuronal gene expression program. This work uncovers general neuronal reprogramming properties for temporal identity factors in terminally differentiated cells.
2023-05-04 | GSE169519 | GEO
Project description:Combinations of transcription factors govern the identity of cell types, which is reflected by genomic enhancer codes. We utilized deep learning to characterize these enhancer codes and devised three novel metrics to compare cell types in the telencephalon between mammals and birds. To this end, we generated single-cell multiome and spatially-resolved transcriptomics data of the chicken telencephalon. Enhancer codes of orthologous non-neuronal and GABAergic cell types show a high degree of similarity across vertebrates, while excitatory neurons of the mammalian neocortex and avian pallium exhibit varying degrees of similarity. Enhancer codes of avian mesopallial neurons are most similar to those of mammalian deep layer neurons. With this study, we present generally applicable deep learning approaches to characterize and compare cell types solely based on genomic sequences.
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Project description:Combinations of transcription factors govern the identity of cell types, which is reflected by genomic enhancer codes. We utilized deep learning to characterize these enhancer codes and devised three novel metrics to compare cell types in the telencephalon between mammals and birds. To this end, we generated single-cell multiome and spatially-resolved transcriptomics data of the chicken telencephalon. Enhancer codes of orthologous non-neuronal and GABAergic cell types show a high degree of similarity across vertebrates, while excitatory neurons of the mammalian neocortex and avian pallium exhibit varying degrees of similarity. Enhancer codes of avian mesopallial neurons are most similar to those of mammalian deep layer neurons. With this study, we present generally applicable deep learning approaches to characterize and compare cell types solely based on genomic sequences.
2024-09-16 | GSE262322 | GEO
Project description:Combinations of transcription factors govern the identity of cell types, which is reflected by genomic enhancer codes. We utilized deep learning to characterize these enhancer codes and devised three novel metrics to compare cell types in the telencephalon between mammals and birds. To this end, we generated single-cell multiome and spatially-resolved transcriptomics data of the chicken telencephalon. Enhancer codes of orthologous non-neuronal and GABAergic cell types show a high degree of similarity across vertebrates, while excitatory neurons of the mammalian neocortex and avian pallium exhibit varying degrees of similarity. Enhancer codes of avian mesopallial neurons are most similar to those of mammalian deep layer neurons. With this study, we present generally applicable deep learning approaches to characterize and compare cell types solely based on genomic sequences.
2024-06-14 | GSE262321 | GEO
Project description:Although the importance of Notch signaling in brain development is well-known, its specific contribution to cellular reprogramming remains less defined. Here, we use microRNA-induced neurons (miNs) that are directly reprogrammed from human fibroblasts to determine how Notch signaling contributes to neuronal identity. We found that inhibiting Notch signaling led to an increase in neurite extension, while activating Notch signaling had the opposite effect. Surprisingly, Notch inhibition during the first week of reprogramming was both necessary and sufficient to enhance neurite outgrowth at a later timepoint. This timeframe is when the reprogramming miRNAs, miR-9/9* and miR-124, primarily induce a post-mitotic state and erase fibroblast identity. Accordingly, transcriptomic analysis showed that the effect of Notch inhibition was likely due to improvements in fibroblast fate erasure and silencing of anti-neuronal genes. To this effect, we identify MYLIP, whose downregulation in response to Notch inhibition significantly promoted neurite outgrowth. Moreover, Notch inhibition resulted in cells with neuronal transcriptome signature defined by long gene expression at a faster rate than the control, demonstrating the effect of accelerated fate erasure on neuronal fate acquisition. Our results demonstrate the critical role of Notch signaling in mediating morphological changes in miRNA-based neuronal reprogramming of human adult fibroblasts.
2024-01-12 | GSE252626 | GEO
Project description:Although the importance of Notch signaling in brain development is well-known, its specific contribution to cellular reprogramming remains less defined. Here, we use microRNA-induced neurons (miNs) that are directly reprogrammed from human fibroblasts to determine how Notch signaling contributes to neuronal identity. We found that inhibiting Notch signaling led to an increase in neurite extension, while activating Notch signaling had the opposite effect. Surprisingly, Notch inhibition during the first week of reprogramming was both necessary and sufficient to enhance neurite outgrowth at a later timepoint. This timeframe is when the reprogramming miRNAs, miR-9/9* and miR-124, primarily induce a post-mitotic state and erase fibroblast identity. Accordingly, transcriptomic analysis showed that the effect of Notch inhibition was likely due to improvements in fibroblast fate erasure and silencing of anti-neuronal genes. To this effect, we identify MYLIP, whose downregulation in response to Notch inhibition significantly promoted neurite outgrowth. Moreover, Notch inhibition resulted in cells with neuronal transcriptome signature defined by long gene expression at a faster rate than the control, demonstrating the effect of accelerated fate erasure on neuronal fate acquisition. Our results demonstrate the critical role of Notch signaling in mediating morphological changes in miRNA-based neuronal reprogramming of human adult fibroblasts.
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