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Proneural factors Ascl1 and Neurog2 contribute to neuronal subtype identities by establishing distinct chromatin landscapes

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TLDR
This study provides a mechanistic understanding of how transcription factors constrain terminal cell fates, and it delineates the importance of choosing the right proneural factor in neuronal reprogramming strategies.
Abstract
Developmental programs that generate the astonishing neuronal diversity of the nervous system are not completely understood and thus present a major challenge for clinical applications of guided cell differentiation strategies. Using direct neuronal programming of embryonic stem cells, we found that two main vertebrate proneural factors, Ascl1 and neurogenin 2 (Neurog2), induce different neuronal fates by binding to largely different sets of genomic sites. Their divergent binding patterns are not determined by the previous chromatin state, but are distinguished by enrichment of specific E-box sequences that reflect the binding preferences of the DNA-binding domains. The divergent Ascl1 and Neurog2 binding patterns result in distinct chromatin accessibility and enhancer activity profiles that differentially shape the binding of downstream transcription factors during neuronal differentiation. This study provides a mechanistic understanding of how transcription factors constrain terminal cell fates, and it delineates the importance of choosing the right proneural factor in neuronal reprogramming strategies. Aydin et al. show that the proneural factors Ascl1 and Neurog2 bind to largely non-overlapping sites in the genome, establishing distinct chromatin landscapes that shape the activity of downstream factors during neuronal fate specification.

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Journal ArticleDOI

Establishing neuronal diversity in the spinal cord: a time and a place

TL;DR: This Review outlines how distinct neuronal cell identities are established in response to spatial and temporal patterning systems, and outlines novel experimental approaches to study the emergence and function of neuronal diversity in the spinal cord.
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Efficient stimulation of retinal regeneration from Müller glia in adult mice using combinations of proneural bHLH transcription factors.

TL;DR: In this paper, the combination of Ascl1:Atoh1 is shown to be remarkably efficient at stimulating neurogenesis, even in the absence of retinal injury, with the majority expressing characteristics of the retinal ganglion cells.
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Vertebrate Sensory Ganglia: Common and Divergent Features of the Transcriptional Programs Generating Their Functional Specialization

TL;DR: The general anatomy, function and neuronal diversity of cranial sensory ganglia is summarized and an overview of the current knowledge of the transcriptional networks controlling neurogenesis and neuronal diversification in the developing sensory system is provided.
Journal ArticleDOI

Next-generation disease modeling with direct conversion: a new path to old neurons.

TL;DR: An overview of the state of the art of direct iN conversion is provided and the key epigenetic, transcriptomic, and metabolic changes that occur in converting fibroblasts are described.
References
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Journal ArticleDOI

Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2

TL;DR: This work presents DESeq2, a method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates, which enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression.
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edgeR: a Bioconductor package for differential expression analysis of digital gene expression data.

TL;DR: EdgeR as mentioned in this paper is a Bioconductor software package for examining differential expression of replicated count data, which uses an overdispersed Poisson model to account for both biological and technical variability and empirical Bayes methods are used to moderate the degree of overdispersion across transcripts, improving the reliability of inference.
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Ultrafast and memory-efficient alignment of short DNA sequences to the human genome

TL;DR: Bowtie extends previous Burrows-Wheeler techniques with a novel quality-aware backtracking algorithm that permits mismatches and can be used simultaneously to achieve even greater alignment speeds.
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TopHat2: accurate alignment of transcriptomes in the presence of insertions, deletions and gene fusions

TL;DR: TopHat2 is described, which incorporates many significant enhancements to TopHat, and combines the ability to identify novel splice sites with direct mapping to known transcripts, producing sensitive and accurate alignments, even for highly repetitive genomes or in the presence of pseudogenes.
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Integrating single-cell transcriptomic data across different conditions, technologies, and species.

TL;DR: An analytical strategy for integrating scRNA-seq data sets based on common sources of variation is introduced, enabling the identification of shared populations across data sets and downstream comparative analysis.
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