Parallel evolution of a splicing program controlling neuronal excitability in flies and mammals

SummaryNeurons draw on alternative splicing for their increased transcriptomic complexity throughout animal phylogeny. To delve into the mechanisms controlling the assembly and evolution of this regulatory layer, we characterized the neuronal microexon program in Drosophila and compared it with that of mammals. We found that in Drosophila, this splicing program is restricted to neurons by the post-transcriptional processing of the enhancer of microexons (eMIC) domain in Srrm234 by Elav and Fne. eMIC deficiency or misexpression leads to widespread neurological alterations largely emerging from impaired neuronal activity, as revealed by a combination of neuronal imaging experiments and cell-type-specific rescues. These defects are associated with the genome-wide skipping of short neural exons, which are strongly enriched in ion channels. Remarkably, we found no overlap of eMIC-regulated exons between flies and mice, illustrating how ancient post-transcriptional programs can evolve independently in different phyla to impact distinct cellular modules while maintaining cell-type specificity.

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Evaluating the contribution of cell-type specific alternative splicing to variation in lipid levels

10.1101/659326 ◽

2019 ◽

Author(s):

K.A.B. Gawronski ◽

W. Bone ◽

Y. Park ◽

E. Pashos ◽

X. Wang ◽

...

Keyword(s):

Alternative Splicing ◽

Quantitative Trait ◽

Cell Types ◽

Genome Wide Association ◽

Genome Wide Association Studies ◽

Lipid Levels ◽

Cell Type ◽

Genome Wide ◽

Genetic Mechanisms ◽

Cell Type Specific

AbstractBackgroundGenome-wide association studies have identified 150+ loci associated with lipid levels. However, the genetic mechanisms underlying most of these loci are not well-understood. Recent work indicates that changes in the abundance of alternatively spliced transcripts contributes to complex trait variation. Consequently, identifying genetic loci that associate with alternative splicing in disease-relevant cell types and determining the degree to which these loci are informative for lipid biology is of broad interest.Methods and ResultsWe analyze gene splicing in 83 sample-matched induced pluripotent stem cell (iPSC) and hepatocyte-like cell (HLC) lines (n=166), as well as in an independent collection of primary liver tissues (n=96). We observe that transcript splicing is highly cell-type specific, and the genes that are differentially spliced between iPSCs and HLCs are enriched for metabolism pathway annotations. We identify 1,381 HLC splicing quantitative trait loci (sQTLs) and 1,462 iPSC sQTLs and find that sQTLs are often shared across cell types. To evaluate the contribution of sQTLs to variation in lipid levels, we conduct colocalization analysis using lipid genome-wide association data. We identify 19 lipid-associated loci that colocalize either with an HLC expression quantitative trait locus (eQTL) or sQTL. Only one locus colocalizes with both an sQTL and eQTL, indicating that sQTLs contribute information about GWAS loci that cannot be obtained by analysis of steady-state gene expression alone.ConclusionsThese results provide an important foundation for future efforts that use iPSC and iPSC-derived cells to evaluate genetic mechanisms influencing both cardiovascular disease risk and complex traits in general.

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A viral toolkit for recording transcription factor–DNA interactions in live mouse tissues

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.1918241117 ◽

2020 ◽

Vol 117 (18) ◽

pp. 10003-10014 ◽

Cited By ~ 3

Author(s):

Alexander J. Cammack ◽

Arnav Moudgil ◽

Jiayang Chen ◽

Michael J. Vasek ◽

Mark Shabsovich ◽

...

Keyword(s):

Regulation Of Gene Expression ◽

Cell Type ◽

Cell Type Specificity ◽

Live Animal ◽

Specific Antibodies ◽

Genome Wide ◽

Mouse Tissues ◽

Conditional Expression ◽

Cell Type Specific ◽

Live Mouse

Transcription factors (TFs) enact precise regulation of gene expression through site-specific, genome-wide binding. Common methods for TF-occupancy profiling, such as chromatin immunoprecipitation, are limited by requirement of TF-specific antibodies and provide only end-point snapshots of TF binding. Alternatively, TF-tagging techniques, in which a TF is fused to a DNA-modifying enzyme that marks TF-binding events across the genome as they occur, do not require TF-specific antibodies and offer the potential for unique applications, such as recording of TF occupancy over time and cell type specificity through conditional expression of the TF–enzyme fusion. Here, we create a viral toolkit for one such method, calling cards, and demonstrate that these reagents can be delivered to the live mouse brain and used to report TF occupancy. Further, we establish a Cre-dependent calling cards system and, in proof-of-principle experiments, show utility in defining cell type-specific TF profiles and recording and integrating TF-binding events across time. This versatile approach will enable unique studies of TF-mediated gene regulation in live animal models.

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Cell-type specificity of neuronal excitability and morphology in the central amygdala

10.1101/832295 ◽

2019 ◽

Author(s):

Anisha P. Adke ◽

Aleisha Khan ◽

Hye-Sook Ahn ◽

Jordan J. Becker ◽

Torri D. Wilson ◽

...

Keyword(s):

Neuronal Excitability ◽

Brain Slices ◽

Neuronal Morphology ◽

Membrane Properties ◽

Specific Function ◽

Cell Type ◽

Central Amygdala ◽

Cell Type Specificity ◽

Cell Type Specific ◽

Distinguishing Features

ABSTRACTCentral amygdala (CeA) neurons expressing protein kinase C delta (PKCδ+) or Somatostatin (Som+) differentially modulate diverse behaviors. The underlying features supporting cell-type-specific function in the CeA, however, remain unknown. Using whole-cell patch-clamp electrophysiology in acute mouse brain slices and biocytin-based neuronal reconstructions, we demonstrate that neuronal morphology and relative excitability are two distinguishing features between Som+ and PKCδ+ CeLC neurons. Som+ neurons, for example, are more excitable, compact and with more complex dendritic arborizations than PKCδ+ neurons. Cell size, intrinsic membrane properties, and anatomical localization were further shown to correlate with cell-type-specific differences in excitability. Lastly, in the context of neuropathic pain, we show a shift in the excitability equilibrium between PKCδ+ and Som+ neurons, suggesting that imbalances in the relative output of these cells underlie maladaptive changes in behaviors. Together, our results identify fundamentally important distinguishing features of PKCδ+ and Som+ cells that support cell-type-specific function in the CeA.

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Cell-type specific dysregulation of RNA alternative splicing in short tandem repeat mouse knockin models of myotonic dystrophy

10.26226/morressier.5ebd45acffea6f735881b195 ◽

2020 ◽

Author(s):

Curtis Nutter

Keyword(s):

Alternative Splicing ◽

Myotonic Dystrophy ◽

Tandem Repeat ◽

Short Tandem Repeat ◽

Cell Type ◽

Cell Type Specific ◽

Short Tandem

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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.

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Partitioning heritability by functional category using GWAS summary statistics

10.1101/014241 ◽

2015 ◽

Cited By ~ 9

Author(s):

Hilary Kiyo Finucane ◽

Brendan Bulik-Sullivan ◽

Alexander Gusev ◽

Gosia Trynka ◽

Yakir Reshef ◽

...

Keyword(s):

Association Studies ◽

Smoking Behavior ◽

Complex Diseases ◽

New Method ◽

Age At Menarche ◽

Genome Wide Association Studies ◽

Summary Statistics ◽

Cell Type ◽

Genome Wide ◽

Cell Type Specific

Recent work has demonstrated that some functional categories of the genome contribute disproportionately to the heritability of complex diseases. Here, we analyze a broad set of functional elements, including cell-type-specific elements, to estimate their polygenic contributions to heritability in genome-wide association studies (GWAS) of 17 complex diseases and traits spanning a total of 1.3 million phenotype measurements. To enable this analysis, we introduce a new method for partitioning heritability from GWAS summary statistics while controlling for linked markers. This new method is computationally tractable at very large sample sizes, and leverages genome-wide information. Our results include a large enrichment of heritability in conserved regions across many traits; a very large immunological disease-specific enrichment of heritability in FANTOM5 enhancers; and many cell-type-specific enrichments including significant enrichment of central nervous system cell types in body mass index, age at menarche, educational attainment, and smoking behavior. These results demonstrate that GWAS can aid in understanding the biological basis of disease and provide direction for functional follow-up.

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Calling differential DNA methylation at cell-type resolution: addressing misconceptions and best practices

10.1101/2021.02.14.431168 ◽

2021 ◽

Author(s):

Elior Rahmani ◽

Brandon Jew ◽

Regev Schweiger ◽

Brooke Rhead ◽

Lindsey A. Criswell ◽

...

Keyword(s):

Dna Methylation ◽

Best Practices ◽

Regression Model ◽

Association Studies ◽

Composition Analysis ◽

Cell Type ◽

Cell Type Specificity ◽

Interaction Terms ◽

Mathematical Explanations ◽

Cell Type Specific

AbstractWe benchmarked two approaches for the detection of cell-type-specific differential DNA methylation: Tensor Composition Analysis (TCA) and a regression model with interaction terms (CellDMC). Our experiments alongside rigorous mathematical explanations show that TCA is superior over CellDMC, thus resolving recent criticisms suggested by Jing et al. Following misconceptions by Jing and colleagues with modelling cell-type-specificity and the application of TCA, we further discuss best practices for performing association studies at cell-type resolution. The scripts for reproducing all of our results and figures are publicly available at github.com/cozygene/CellTypeSpecificMethylationAnalysis.

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Cell-Type Specificity of Neuronal Excitability and Morphology in the Central Amygdala

eNeuro ◽

10.1523/eneuro.0402-20.2020 ◽

2020 ◽

pp. ENEURO.0402-20.2020

Author(s):

Anisha P. Adke ◽

Aleisha Khan ◽

Hye-Sook Ahn ◽

Jordan J. Becker ◽

Torri D. Wilson ◽

...

Keyword(s):

Neuronal Excitability ◽

Cell Type ◽

Central Amygdala ◽

Cell Type Specificity

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Capturing cell type-specific chromatin structural patterns by applying topic modeling to single-cell Hi-C data

10.1101/534800 ◽

2019 ◽

Cited By ~ 2

Author(s):

Hyeon-Jin Kim ◽

Galip Gürkan Yardımcı ◽

Giancarlo Bonora ◽

Vijay Ramani ◽

Jie Liu ◽

...

Keyword(s):

Single Cell ◽

Topic Modeling ◽

Biological Information ◽

Chromatin Interaction ◽

Cell Type ◽

3D Genome ◽

Genome Wide ◽

Significant Barrier ◽

Chromatin Structural ◽

Cell Type Specific

AbstractSingle-cell Hi-C (scHi-C) interrogates genome-wide chromatin interaction in individual cells, allowing us to gain insights into 3D genome organization. However, the extremely sparse nature of scHi-C data poses a significant barrier to analysis, limiting our ability to tease out hidden biological information. In this work, we approach this problem by applying topic modeling to scHi-C data. Topic modeling is well-suited for discovering latent topics in a collection of discrete data. For our analysis, we generate twelve different single-cell combinatorial indexed Hi-C (sciHi-C) libraries from five human cell lines (GM12878, H1Esc, HFF, IMR90, and HAP1), consisting over 25,000 cells. We demonstrate that topic modeling is able to successfully capture cell type differences from sciHi-C data in the form of “chromatin topics.” We further show enrichment of particular compartment structures associated with locus pairs in these topics.

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